A Novel MRI Biomarker of Spinal Cord White Matter Injury: T2*-Weighted White Matter to Gray Matter Signal Intensity Ratio

BACKGROUND AND PURPOSE:DTI, magnetization transfer, T2*-weighted imaging, and cross-sectional area can quantify aspects of spinal cord microstructure. However, clinical adoption remains elusive due to complex acquisitions, cumbersome analysis, limited reliability, and wide ranges of normal values. We propose a simple multiparametric protocol with automated analysis and report normative data, analysis of confounding variables, and reliability.MATERIALS AND METHODS:Forty healthy subjects underwent T2WI, DTI, magnetization transfer, and T2*WI at 3T in <35 minutes using standard hardware and pulse sequences. Cross-sectional area, fractional anisotropy, magnetization transfer ratio, and T2*WI WM/GM signal intensity ratio were calculated. Relationships between MR imaging metrics and age, sex, height, weight, cervical cord length, and rostrocaudal level were analyzed. Test-retest coefficient of variation measured reliability in 24 DTI, 17 magnetization transfer, and 16 T2*WI datasets. DTI with and without cardiac triggering was compared in 10 subjects.RESULTS:T2*WI WM/GM showed lower intersubject coefficient of variation (3.5%) compared with magnetization transfer ratio (5.8%), fractional anisotropy (6.0%), and cross-sectional area (12.2%). Linear correction of cross-sectional area with cervical cord length, fractional anisotropy with age, and magnetization transfer ratio with age and height led to decreased coefficients of variation (4.8%, 5.4%, and 10.2%, respectively). Acceptable reliability was achieved for all metrics/levels (test-retest coefficient of variation < 5%), with T2*WI WM/GM comparing favorably with fractional anisotropy and magnetization transfer ratio. DTI with and without cardiac triggering showed no significant differences for fractional anisotropy and test-retest coefficient of variation.CONCLUSIONS:Reliable multiparametric assessment of spinal cord microstructure is possible by using clinically suitable methods. These results establish normalization procedures and pave the way for clinical studies, with the potential for improving diagnostics, objectively monitoring disease progression, and predicting outcomes in spinal pathologies.

The era of quantitative MR imaging has arrived, allowing in vivo measurement of specific physical properties reflecting spinal cord (SC) microstructure and tissue damage.^1,2 Such measures have potential clinical applications, including improved diagnostic tools, objective monitoring for disease progression, and prediction of clinical outcomes.³ However, technical challenges such as artifacts, image distortion, and achieving acceptable SNR have led to limited reliability. Specialized pulse sequences and custom hardware have advanced the field but incur costs of increased complexity and acquisition time while creating barriers to portability and clinical adoption. Furthermore, quantitative MR imaging metrics often show wide ranges of normal values and confounding relationships with subject characteristics such as age,^4–8 for which most previous studies have not accounted.³Among the most promising SC quantitative MR imaging techniques are DTI and magnetization transfer (MT).^1–3 These provide measures of axonal integrity and myelin quantity that correlate with functional impairment in conditions such as degenerative cervical myelopathy (DCM)^5–7,9 and MS,^3,9 albeit with limited physiologic specificity (eg, fractional anisotropy [FA] reflects both demyelination and axonal injury).^10,11 SC cross-sectional area (CSA) computed from high-resolution anatomic images can measure atrophy (eg, in MS)¹² or the degree of SC compression in DCM.¹³ T2*-weighted imaging at 3T or higher field strengths offers high resolution and sharp contrast between SC WM and GM, allowing segmentation between these structures similar to that in phase-sensitive inversion recovery.^14,15 T2*WI also demonstrates hyperintensity in injured WM,^16–18 reflecting demyelination, gliosis, and increased calcium and nonheme iron concentrations.¹⁹ T2*WI signal intensity is not an absolute quantity, so we normalize its value in WM by the average GM signal intensity in each axial section, creating a novel measure of WM injury: T2*WI WM/GM ratio.²⁰We propose a multiparametric approach to cervical SC quantitative MR imaging with clinically feasible methods, including acceptable acquisition times, standard hardware/pulse sequences, and automated image analysis. Our protocol yields 4 measures of SC tissue injury (CSA, FA, MT ratio [MTR], and T2*WI WM/GM), for which this study establishes normative values in numerous ROIs. We characterize the variation of these metrics with age, sex, height, weight, cervical cord length, and rostrocaudal level and propose normalization methods. Finally, we assess test-retest reliability of FA, MTR, and T2*WI WM/GM and compare our DTI results against those with cardiac triggering.     

A validation study of multicenter diffusion tensor imaging: reliability of fractional anisotropy and diffusivity values

BACKGROUND AND PURPOSE:DTI is increasingly being used as a measure to study tissue damage in several neurologic diseases. Our aim was to investigate the comparability of DTI measures between different MR imaging magnets and platforms.MATERIALS AND METHODS:Two healthy volunteers underwent DTI on five 3T MR imaging scanners (3 Trios and 2 Signas) by using a matched 33 noncollinear diffusion-direction pulse sequence. Within each subject, a total of 16 white matter (corpus callosum, periventricular, and deep white matter) and gray matter (cortical and deep gray) ROIs were drawn on a single image set and then were coregistered to the other images. Mean FA, ADC, and longitudinal and transverse diffusivities were calculated within each ROI. Concordance correlations were derived by comparing ROI DTI values among each of the 5 magnets.RESULTS:Mean concordance for FA was 0.96; for both longitudinal and transverse diffusivities, it was 0.93; and for ADC, it was 0.88. Mean scan-rescan concordance was 0.96–0.97 for all DTI measures. Concordance correlations within platforms were, in general, better than those between platforms for all DTI measures (mean concordance of 0.96).CONCLUSIONS:We found that a 3T magnet and high-angular-resolution pulse sequence yielded comparable DTI measurements across different MR imaging magnets and platforms. Our results indicate that FA is the most comparable measure across magnets, followed by individual diffusivities. The comparability of DTI measures between different magnets supports the feasibility of multicentered clinical trials by using DTI as an outcome measure.

DTI provides a quantitative measurement of the magnitude and direction of water diffusion within tissues.^1,2 Changes in water diffusion reflect alterations in tissue microstructure³ and thus make DTI a noninvasive technique to study diseases caused by tissue destruction, such as MS.^2,4 The extent of tissue injury is commonly evaluated by using DTI-derived measures such as FA, λ_‖, λ_⊥, and ADC.^2,5 Studies in patients with MS revealed changes in DTI measures not only within MS lesions but also in normal-appearing white matter and gray matter, which are generally not discernible by using conventional T1- and T2-weighted imaging techniques.^6,–9The sensitivity of DTI metrics to ongoing changes in the brain makes it an attractive outcome measure for MS therapeutic studies.¹⁰ However, little is known about the validity of DTI measures between scanners. Recently, 2 independent studies^11,12 have attempted to address the reproducibility of DTI measures. They assessed FA^11,12 and λ_⊥¹¹ in the corpus callosum across different centers, all by using 3T scanners. They both found DTI measures to generally be homogeneous across centers when measured with scanners from the same manufacturer.However, 2 major issues that remain to be resolved are the following: the comparability of DTI measures across different brain regions and the comparability of DTI measures across different scanners. We thus sought to address these issues by comparing DTI measures obtained from 5 centers from 2 subjects. We addressed the following issues: 1) scanners from different manufacturers, 2) multiple platforms from the same manufacturer, 3) DTI measures from different brain regions with a wide range of anisotropy, and 4) software upgrades.     

A distinct MR imaging phenotype in amyotrophic lateral sclerosis: correlation between T1 magnetization transfer contrast hyperintensity along the corticospinal tract and diffusion tensor imaging analysis

BACKGROUND AND PURPOSE:In the search for a diagnostic marker in ALS, we focused our attention on the hyperintense signal intensity in T1 MTC MR images along the CST, detected in some patients and not found in other patients with ALS and in control subjects. The aim of this study was to investigate the relationship between the hyperintense signal intensity in T1 MTC images and white matter damage. To this purpose, we studied potential heterogeneities in DTI values within our patients by using TBSS without a priori anatomic information.MATERIALS AND METHODS:In 43 patients with ALS and 43 healthy control subjects, the presence or absence of T1 MTC hyperintense signal intensity was evaluated. With a DTI analysis with a TBSS approach, differences in FA distribution between the 2 groups (patients with T1 MTC hyperintense signal intensity and patients without it) compared with each other and with control subjects were investigated.RESULTS:We found regional differences in white matter FA between patients with T1 MTC hyperintense signal intensity (37.2%) and patients without it. Patients with T1 MTC abnormal signal intensity showed lower FA strictly limited to the motor network and the posterior aspect of the body of the CC without extramotor FA reductions, whereas patients without this sign showed FA reductions in several confluent regions within and outside the CST and in the whole CC.CONCLUSIONS:T1 MTC hyperintense signal intensity in the CST and posterior CC, when present, is specific for ALS and represents, among patients with ALS, a possible distinct phenotype of presentation of the disease with prominent UMN involvement.

ALS is a chronic neurodegenerative disease that selectively involves the motor system. Clinically, patients present with UMN and LMN signs and symptoms. Degeneration of the UMNs in the precentral gyrus of the cerebral cortex is the main pathologic change, accompanied by degeneration of the CST from the cerebral cortex to the spinal cord.^1,2The incidence of sporadic ALS ranges between 1.5 and 2.7 per 100,000 population/year (average 1.89 per 100,000/year) in Europe and North America.^3–7In patients with ALS, MR imaging of the brain may show signal-intensity abnormalities, namely a hyperintense signal intensity in PD-T2^8–10 and FLAIR^11–14 MR images in the CST from the white matter of the precentral gyrus through the corona radiata and posterior limb of the internal capsule down to the brain stem, consistent with CST degeneration.In addition, a hypointense rim in the posterior aspect of the precentral gyrus attributed to iron accumulation has been found.^{12,13,15–17}Only a few authors have specifically studied T1^13,16,18 and T1 MTC sequences, finding either a hyperintense signal intensity¹⁸ or a reduction of MTR along the CST,^19,20 suggesting the presence of a more severe tissue damage. MTC imaging focuses on fundamental relaxation properties of water protons and is applied to augment image contrast and tissue specificity. This technique is based on the application of off-resonance radio frequency pulses before the pulse sequence to preferentially saturate immobile protons of macromolecules, which then transfer magnetization to mobile protons in free water and can be used to detect changes in the structural status of the brain tissue.²¹MT imaging of the gray matter of patients with ALS recently showed a reduction of MTR in the precentral gyrus and also in the prefrontal and temporal cortices.²²In our experience, T1 MTC hyperintense signal intensity of the CST is a characteristic but inconstant finding in patients with ALS. On the hypothesis that this feature could correspond to a specific disease phenotype, we used MT imaging of the white matter of patients with ALS, focusing our attention on the T1 MTC signal intensity along the CST. To further characterize the relationship between the hyperintense signal intensity in T1 MTC and the white matter damage, we followed a DTI approach. Among in vivo neuroimaging techniques, DTI is in fact the criterion standard method to assess the structural integrity of white matter. Diffusion anisotropy describes how variable the diffusion is in different directions and is most commonly quantified via a measure known as FA.^23,24 A decrease in FA has been shown to be related to axonal fiber degeneration and myelin breakdown.²⁵In this article, we used TBSS,²⁶ a voxel-based approach that uses extracted and skeletonized white matter tracts in the FA images of all subjects. TBSS is used in an effort to overcome the problems associated with the use of standard registration algorithms in other voxel-based approaches.Several DTI studies have reported reduced FA in the CSTs of patients with ALS, though the extent and distribution of these changes have been variable.^26–39 Reduced FA along the CST from the corona radiata through the internal capsule and into the brain stem has been reported by using both region-of-interest^27,32,36 and voxel-based approaches.^{28,33,35,38,40}In addition, some authors^28,35 described a decrease in FA, not only in the CST but also in regions outside the main motor cortices and the CST. In previous studies that used TBSS, FA reductions were found in regions outside the motor network, such as the CC and the white matter underneath the premotor, primary sensory, frontal, and prefrontal cortices.^37,38 In another DTI study by using TBSS, the authors reported FA reductions in the body and genu of the CC and corona radiata in patients with ALS compared with controls, and mean diffusivity, axial diffusivity, and radial diffusivity increased in regions outside strictly motor areas.³⁹The aim of our investigation was to explore the relationship between the hyperintense signal intensity in T1 MTC and white matter damage in a series of patients with ALS by using a TBSS approach and to establish whether there were regional differences in white matter FA between patients with T1 MTC hyperintense signal intensity and patients without it.     

Differentiation between glioblastomas, solitary brain metastases, and primary cerebral lymphomas using diffusion tensor and dynamic susceptibility contrast-enhanced MR imaging

BACKGROUND AND PURPOSE:Glioblastomas, brain metastases, and PCLs may have similar enhancement patterns on MR imaging, making the differential diagnosis difficult or even impossible. The purpose of this study was to determine whether a combination of DTI and DSC can assist in the differentiation of glioblastomas, solitary brain metastases, and PCLs.MATERIALS AND METHODS:Twenty-six glioblastomas, 25 brain metastases, and 16 PCLs were retrospectively identified. DTI metrics, including FA, ADC, CL, CP, CS, and rCBV were measured from the enhancing, immediate peritumoral and distant peritumoral regions. A 2-level decision tree was designed, and a multivariate logistic regression analysis was used at each level to determine the best model for classification.RESULTS:From the enhancing region, significantly elevated FA, CL, and CP and decreased CS values were observed in glioblastomas compared with brain metastases and PCLs (P < .001), whereas ADC, rCBV, and rCBV_max values of glioblastomas were significantly higher than those of PCLs (P < .01). The best model to distinguish glioblastomas from nonglioblastomas consisted of ADC, CS (or FA) from the enhancing region, and rCBV from the immediate peritumoral region, resulting in AUC = 0.938. The best predictor to differentiate PCLs from brain metastases comprised ADC from the enhancing region and CP from the immediate peritumoral region with AUC = 0.909.CONCLUSIONS:The combination of DTI metrics and rCBV measurement can help in the differentiation of glioblastomas from brain metastases and PCLs.

Glioblastomas, brain metastases, and PCLs are common brain malignancies in adults, which may have similar enhancement patterns on MR imaging. Conventional MR imaging is very limited in making the distinction. Contrast enhancement on T1-weighted images reflects areas of blood-brain barrier breakdown regardless of the pathology. FLAIR imaging can depict a large portion of the tumor but also is nonspecific.^1,2 Accurate preoperative diagnosis is often crucial because the management and prognosis of these tumors are substantially different.^3–5 For example, patients with glioblastomas are almost always treated by surgical resection,⁴ while patients with suspected brain metastases without a clinical history of systemic cancer should undergo a complicated systemic staging to determine the site of primary carcinoma and evaluate other distant metastases before any surgical intervention or medical therapy.⁵ PCLs are managed primarily with chemotherapy or radiation therapy after stereotactic biopsy.³DTI has been widely reported in brain tumor classification.^1,6–9 The ADC value, measured from diffusion-weighted imaging or DTI, has been reported to be inversely correlated with cellularity in tumors.^7,8 Prior studies have shown that ADC can help differentiate PCLs from high-grade gliomas^1,6–8,10 and brain metastases⁸; however, other studies have reported a substantial overlap between these tumor types.^11,12 DTI also provides diffusion anisotropy information about the tissue, such as FA, CL, CP, and CS. Of these parameters, FA has been most commonly used in the study of brain neoplasms.^13,14 In contrast to ADC, the relationship between FA and cellularity has not been substantiated. Toh et al¹⁰ reported significantly decreased FA in highly cellular cerebral PCLs compared with glioblastomas, whereas Kinoshita et al¹⁴ demonstrated high FA values in PCLs. Our previous study demonstrated that DTI metrics, including ADC, FA, and CP, from the enhancing region of the tumor can differentiate glioblastomas from brain metastases with 92% sensitivity and 100% specificity.⁹DSC provides maps of CBV, which correlate with tumor vascularity and allow indirect assessment of tumor angiogenesis.^2,15 Vascular proliferation and tumor angiogenesis are among the most important factors in the biologic behavior of malignant brain tumors.¹⁶ An increase in the microvascularity and neovascularity of these tumors leads to increased rCBV. It has been reported that PCLs have lower mean rCBV,^17–19 or lower rCBV_max values^6,20–22 compared with glioblastomas or brain metastases.¹⁷ In the peritumoral region, glioblastomas demonstrate elevated rCBV due to tumor infiltration in the normal brain parenchyma in comparison with brain metastases.²³In this study, we hypothesized that a combination of DTI (FA, ADC, CL, CP, and CS) and DSC (rCBV) parameters can assist in better differentiation of glioblastomas, solitary brain metastases, and PCLs. A 2-level decision tree and a multivariate logistic regression analysis were used to determine the best model for tumor classification.     

Diffusion MRI Microstructural Abnormalities at Term-Equivalent Age Are Associated with Neurodevelopmental Outcomes at 3 Years of Age in Very Preterm Infants

BACKGROUND AND PURPOSE:Microstructural white matter abnormalities on DTI using Tract-Based Spatial Statistics at term-equivalent age are associated with cognitive and motor outcomes at 2 years of age or younger. However, neurodevelopmental tests administered at such early time points are insufficiently predictive of mild-moderate motor and cognitive impairment at school age. Our objective was to evaluate the microstructural antecedents of cognitive and motor outcomes at 3 years'' corrected age in a cohort of very preterm infants.MATERIALS AND METHODS:We prospectively recruited 101 very preterm infants (<32 weeks'' gestational age) and performed DTI at term-equivalent age. The Differential Ability Scales, 2nd ed, Verbal and Nonverbal subtests, and the Bayley Scales of Infant and Toddler Development, 3rd ed, Motor subtest, were administered at 3 years of age. We correlated DTI metrics from Tract-Based Spatial Statistics with the Bayley Scales of Infant and Toddler Development, 3rd ed, and the Differential Ability Scales, 2nd ed, scores with correction for multiple comparisons.RESULTS:Of the 101 subjects, 84 had high-quality DTI data, and of these, 69 returned for developmental testing (82%). Their mean (SD) gestational age was 28.4 (2.5) weeks, and birth weight was 1121.4 (394.1) g. DTI metrics were significantly associated with Nonverbal Ability in the corpus callosum, posterior thalamic radiations, fornix, and inferior longitudinal fasciculus and with Motor scores in the corpus callosum, internal and external capsules, posterior thalamic radiations, superior and inferior longitudinal fasciculi, cerebral peduncles, and corticospinal tracts.CONCLUSIONS:We identified widespread microstructural white matter abnormalities in very preterm infants at term that were significantly associated with cognitive and motor development at 3 years'' corrected age.

Premature birth is associated with a significantly increased risk of brain abnormalities and long-term neurodevelopmental impairment. Injuries or maturational delays affecting the WM are observed in 50%–80% of very preterm infants.^1-3 These abnormalities are associated with serious neurodevelopmental impairment.^1,3,4 However, such abnormalities are challenging to detect using conventional MR imaging techniques alone. Fortunately, DTI, a specialized form of MR imaging that can sensitively query the brain''s microstructure, offers a novel approach for identifying these WM injuries. In preterm brains, the evolution of fractional anisotropy (FA) and mean diffusivity (MD), 2 metrics derived from DTI, varies from that of normative populations, and underlying brain injury may lead to neurodevelopmental impairment later in life.^4-6Functional MR imaging with the FMRIB Tract-Based Spatial Statistics (TBSS; http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/TBSS) tool uses observer-independent voxelwise statistical analysis to process the complex information contained within diffusion-weighted images.^4-16 TBSS can be used to identify specific WM tracts and structures in the infant brain that correlate with later developmental outcomes.^8,10,13-15 Previous studies have used TBSS to objectively assess WM microstructure following clinical events such as infection, sports injury, or preterm brain injury (eg, intraventricular hemorrhage) and to relate the associated WM alterations to outcomes.^9,11,16-19 In addition, studies have used TBSS to identify brain regions and tracts in which FA significantly correlates with cognitive and motor outcomes at 2 years of age or younger.^10,13,15 These studies have consistently concluded that higher FA is associated with better motor, cognitive, and language functioning.Past studies emphasizing the value of TBSS correlated DTI parameters with neurodevelopmental outcomes derived from the Bayley Scales of Infant and Toddler Development, 3rd ed (Bayley-III) collected at 2 years of age or younger. Such standardized assessments are administered between 18 and 24 months of age, representing the earliest time point at which cognitive, language, and motor development can be reliably ascertained. However, assessment at these earliest ages is not necessarily predictive of school age outcomes.^20-22 For example, the Bayley-III Motor subscale at 2 years of age significantly underestimates rates of motor impairment at 4 years of age in preterm infants.²² Spencer-Smith et al²³ showed that cognitive delay, as assessed by the Bayley-III administered at 2 years of age, was not strongly associated with cognitive impairment at 4 years of age as assessed by the Differential Ability Scales, 2nd ed (DAS-II).²⁴ We propose that correlating FA from term-equivalent age MR imaging with 3-year outcomes may provide a more robust understanding of the early changes in WM microstructure that are also significantly associated with cognitive development.Our objective was to test the hypothesis that WM microstructure, assessed using TBSS at term-corrected age (CA), is associated with neurodevelopmental performance at 3 years'' CA in a regional cohort of very preterm infants.     

Diffusion Measures Indicate Fight Exposure–Related Damage to Cerebral White Matter in Boxers and Mixed Martial Arts Fighters

BACKGROUND AND PURPOSE:Traumatic brain injury is common in fighting athletes such as boxers, given the frequency of blows to the head. Because DTI is sensitive to microstructural changes in white matter, this technique is often used to investigate white matter integrity in patients with traumatic brain injury. We hypothesized that previous fight exposure would predict DTI abnormalities in fighting athletes after controlling for individual variation.MATERIALS AND METHODS:A total of 74 boxers and 81 mixed martial arts fighters were included in the analysis and scanned by use of DTI. Individual information and data on fight exposures, including number of fights and knockouts, were collected. A multiple hierarchical linear regression model was used in region-of-interest analysis to test the hypothesis that fight-related exposure could predict DTI values separately in boxers and mixed martial arts fighters. Age, weight, and years of education were controlled to ensure that these factors would not account for the hypothesized effects.RESULTS:We found that the number of knockouts among boxers predicted increased longitudinal diffusivity and transversal diffusivity in white matter and subcortical gray matter regions, including corpus callosum, isthmus cingulate, pericalcarine, precuneus, and amygdala, leading to increased mean diffusivity and decreased fractional anisotropy in the corresponding regions. The mixed martial arts fighters had increased transversal diffusivity in the posterior cingulate. The number of fights did not predict any DTI measures in either group.CONCLUSIONS:These findings suggest that the history of fight exposure in a fighter population can be used to predict microstructural brain damage.

Traumatic brain injury (TBI) has been reported in athletes involved in combat sports who are frequently exposed to repetitive blows to the head, such as boxers.^1–8 This cumulative head trauma is thought to cause chronic traumatic encephalopathy as a result of chronic axonal injury.⁹ The clinical syndrome related to chronic traumatic encephalopathy in boxing is characterized by impulsive behavior, cognitive dysfunction, and in some cases, violence or suicide.¹⁰Conventional MR imaging, such as T1-weighted and T2-weighted anatomic scans, cannot assess mild white matter disruption. Because DTI is sensitive to microstructural changes in white matter, this technique is often used to investigate white matter integrity in patients with TBI.^11–17 Previous studies have found that fractional anisotropy (FA) values in the corpus callosum,^14,16,17 internal capsule,^11,14,16,17 cingulum,¹⁴ and centrum semiovale^11,14,16,17 are decreased in patients with TBI versus healthy control subjects. A longitudinal TBI study found that FA was decreased in the white matter of study participants because of decreased longitudinal diffusivity (LD) and increased transversal diffusivity (TD).¹³ Another study demonstrated that the peaks of whole-brain ADC histograms were significantly correlated with scores on the Glasgow Coma Scale in patients with TBI, indicating that a change in DTI values can predict functional deficit.¹⁸A limited number of studies have investigated diffusion changes in the white matter of fighting athletes.^7,8,19 These studies found that among fighting athletes, whole-brain diffusion is increased,⁸ FA is reduced in the genu and splenium of the corpus callosum and the posterior internal capsule,⁷ and FA is reduced and ADC increased in the lower brain, the splenium of the corpus callosum, and the lateral and dorsolateral cortical regions.¹⁹ Although these studies used age- and sex-matched control groups, variations among fighters in number of fights and number of knockouts have not been fully investigated. Zhang et al⁸ found that the number of hospitalizations for boxing injuries was positively correlated with the peak of the Gaussian-fitted brain tissue compartment in a whole-brain diffusion histogram in 24 professional boxers. However, this finding did not offer information regarding which regions were affected in hospitalized boxers.In the present study, we sought to assess previous fight history and regional MR diffusion parameters to evaluate the relationship between microstructural brain damage and fight-related exposure. We hypothesized that previous fight exposure would predict DTI changes suggestive of microstructural damage in fighter populations.     

Is Contrast Medium Really Needed for Follow-up MRI of Untreated Intracranial Meningiomas?

BACKGROUND AND PURPOSE:Recent concerns relating to tissue deposition of gadolinium are favoring the use of noncontrast MR imaging whenever possible. The purpose of this study was to assess the necessity of gadolinium contrast for follow-up MR imaging of untreated intracranial meningiomas.MATERIALS AND METHODS:One-hundred twenty-two patients (35 men, 87 women) with meningiomas who underwent brain MR imaging between May 2007 and May 2019 in our institution were included in this retrospective cohort study. We analyzed 132 meningiomas: 73 non-skull base (55%) versus 59 skull base (45%), 93 symptomatic (70%) versus 39 asymptomatic (30%). Fifty-nine meningiomas underwent an operation: 54 World Health Organization grade I (92%) and 5 World Health Organization grade II (8%). All meningiomas were segmented on T1 3D-gadolinium and 2D-T2WI. Agreement between T1 3D-gadolinium and 2D-T2WI segmentations was assessed by the intraclass correlation coefficient.RESULTS:The mean time between MR images was 1485 days (range, 760–3810 days). There was excellent agreement between T1 3D-gadolinium and T2WI segmentations (P < .001): mean tumor volume (T1 3D-gadolinium: 9012.15 [SD, 19,223.03] mm³; T2WI: 8528.45 [SD, 18,368.18 ] mm³; intraclass correlation coefficient = 0.996), surface area (intraclass correlation coefficient = 0.989), surface/volume ratio (intraclass correlation coefficient = 0.924), maximum 3D diameter (intraclass correlation coefficient = 0.986), maximum 2D diameter in the axial (intraclass correlation coefficient = 0.990), coronal (intraclass correlation coefficient = 0.982), and sagittal planes (intraclass correlation coefficient = 0.985), major axis length (intraclass correlation coefficient = 0.989), minor axis length (intraclass correlation coefficient = 0.992), and least axis length (intraclass correlation coefficient = 0.988). Tumor growth also showed good agreement (P < .001), estimated as a mean of 461.87 [SD, 2704.1] mm³/year on T1 3D-gadolinium and 556.64 [SD, 2624.02 ] mm³/year on T2WI.CONCLUSIONS:Our results show excellent agreement between the size and growth of meningiomas derived from T1 3D-gadolinium and 2D-T2WI, suggesting that the use of noncontrast MR imaging may be appropriate for the follow-up of untreated meningiomas, which would be cost-effective and avert risks associated with contrast media.

Recent concerns regarding gadolinium (Gd) compounds are fueling a trend to use contrast media in MR imaging less frequently. Notwithstanding the well-established safety profile of Gd compounds, a small number of immediate adverse effects, which may be life-threatening, has been reported^1,2 at a rate of approximately 0.3%.² Furthermore, repeat administration of Gd-based contrast may lead to deposition of Gd in the dentate nucleus and the globus pallidus,^3-7 which seems to be the case with linear rather than macrocyclic Gd compounds,⁴ despite a normal renal function⁷ and an intact blood-brain barrier.⁶ Health care costs should also be considered because they are a heavy burden to modern Western societies,^8-10 and medical imaging accounts for a large proportion of these costs.¹⁰ Gd-based contrast media significantly contribute to the cost of an MR image, due to the price of the contrast medium itself and also because of the prolonged image-acquisition time. Using contrast media more sparingly could, therefore, reduce these costs considerably.The above-mentioned concerns are particularly pertinent to young patients with incidental or asymptomatic meningiomas in which frequent and long-term follow-up MR imaging is usually performed, the current standard-of-care being MR with Gd-based contrast media.¹¹ Intracranial meningiomas are, by and large, benign World Health Organization (WHO) grade I tumors derived from meningothelial cells,^12,13 representing approximately one-third of all primary central nervous system tumors¹⁴ and 15% of symptomatic intracranial masses.¹⁵ They are extra-axial lesions that usually exhibit slow growth (approximately 14%/year for WHO grade I lesions).¹⁶ However, the growth rate can be substantially higher, particularly in WHO grade II and III meningiomas, necessitating frequent MR imaging follow-up. For instance, the European Association of Neuro-Oncology advocates diligent radiologic follow-up of meningiomas. For small asymptomatic meningiomas, the recommendation of this institution is to assess the tumor dynamics with contrast MR imaging at 6 months after the initial diagnosis and then annually as long as the patient remains asymptomatic.¹¹Quantitative MR imaging parameters such as tumor volume¹⁷ are important in predicting tumor growth and behavior. Nakasu and Nakasu,¹⁸ in 2020, identified large tumor size and annual volume change of ≥2.1 cm³ as the strongest predictors of symptomatic tumor progression. Several other parameters may be important in predicting the potential for rapid tumor growth, such as male sex,¹⁸ younger age,¹⁸ absence of calcification,^18-23 peritumoral edema,^21,22,24 and hyperintensity on T2WI.^{18,19,22,25,26}Considering these points, the purpose of this retrospective cohort study was to assess the hypothesis that size and growth of untreated intracranial meningiomas derived from T1 3D-Gd and 2D-T2WI sequences show good agreement, which would, should this be the case, question the added value of Gd-based contrast media for routine follow-up MRIs of intracranial meningiomas.     

Evaluation of Common Structural Brain Changes in Aging and Alzheimer Disease with the Use of an MRI-Based Brain Atrophy and Lesion Index: A Comparison Between T1WI and T2WI at 1.5T and 3T

BACKGROUND AND PURPOSE:The Brain Atrophy and Lesion Index combines several common, aging-related structural brain changes and has been validated for high-field MR imaging. In this study, we evaluated measurement properties of the Brain Atrophy and Lesion Index by use of T1WI and T2WI at 1.5T and 3T MR imaging to comprehensively assess the usefulness of the lower field-strength testing.MATERIALS AND METHODS:Data were obtained from the Alzheimer''s Disease Neuroimaging Initiative. Images of subjects (n = 127) who had T1WI and T2WI at both 3T and 1.5T on the same day were evaluated, applying the Brain Atrophy and Lesion Index rating. Criterion and construct validity and interrater agreement were tested for each field strength and image type.RESULTS:Regarding reliability, the intraclass correlation coefficients for the Brain Atrophy and Lesion Index score were consistently high (>0.81) across image type and field strength. Regarding construct validity, the Brain Atrophy and Lesion Index score differed among diagnostic groups, being lowest in people without cognitive impairment and highest in those with Alzheimer disease (F > 5.14; P < .007). Brain Atrophy and Lesion Index scores correlated with age (r > 0.37, P < .001) and cognitive performance (r > 0.38, P < .001) and were associated with positive amyloid-β test (F > 3.96, P < .050). The T1WI and T2WI Brain Atrophy and Lesion Index scores were correlated (r > 0.93, P < .001), with the T2WI scores slightly greater than the T1WI scores (F > 4.25, P < .041). Regarding criterion validation of the 1.5T images, the 1.5T scores were highly correlated with the 3T Brain Atrophy and Lesion Index scores (r > 0.93, P < .001).CONCLUSIONS:The higher field and T2WI more sensitively detect subtle changes in the deep white matter and perivascular spaces in particular. Even so, 1.5T Brain Atrophy and Lesion Index scores are similar to those obtained by use of 3T images. The Brain Atrophy and Lesion Index may have use in quantifying the impact of dementia on brain structures.

Aging involves multiple structural changes in the brain that can have an additive effect on cognition.^1–3 Such common brain changes include global atrophy, white matter injury, small-vessel ischemia, and microhemorrhages.^4–8 These changes are more frequent and more severe in neurodegenerative and neurovascular conditions such as Alzheimer disease (AD), than in healthy aging.^9–11 To collectively evaluate multiple common brain changes and their additive effects on brain function, a semi-quantitative rating scale, the Brain Atrophy and Lesion Index (BALI), has been validated.^12,13 The BALI assesses global atrophy and lesions in the supratentorial and the infratentorial compartments, including lesions in the gray matter (eg, cortical infarcts) and dilated perivascular spaces in the subcortical white matter as well as lesions in the periventricular regions, deep white matter, basal ganglia, and the surrounding regions.^12,13 Through the use of different datasets, for example, the Alzheimer''s Disease Neuroimaging Initiative (ADNI),¹⁴ the BALI has been used to distinguish AD from healthy aging¹⁵ and to evaluate the dynamics of brain structural changes with aging.¹⁶ To date, BALI has been applied only to MR imaging acquired at 3T and 4T to exploit the higher SNR.¹⁷ Although high-field systems represent the mainstream in future research and clinical settings, large amounts of data have been collected at 1.5T. To generalize the BALI to 1.5T MR imaging has potential value in understanding brain aging.Our goal was to test the measurement properties of the BALI at both 1.5T and 3T MR imaging, for both T1WI and T2WI. In consequence, we compared BALI scores derived from T1WI and T2WI at both 3T and 1.5T and tested the relationship of the score with age, cognitive test scores, AD and mild cognitive impairment (MCI) diagnosis, and AD biomarkers. Our specific objectives were to validate BALI in 1.5T MR imaging by investigating 1) its criterion validity, for example, how well brain images acquired at 1.5T can be used to capture various structural changes in aging, and 2) whether T1WI and T2WI can both be used in the evaluation of global brain changes at 1.5T.     

Ultra-High-Field MRI Visualization of Cortical Multiple Sclerosis Lesions with T2 and T2*: A Postmortem MRI and Histopathology Study

BACKGROUND AND PURPOSE:At 7T MR imaging, T2*-weighted gradient echo has been shown to provide high-resolution anatomic images of gray matter lesions. However, few studies have verified T2*WI lesions histopathologically or compared them with more standard techniques at ultra-high-field strength. This study aimed to determine the sensitivity of T2WI and T2*WI sequences for detecting cortical GM lesions in MS.MATERIALS AND METHODS:At 7T, 2D multiecho spin-echo T2WI and 3D gradient-echo T2*WI were acquired from 27 formalin-fixed coronal hemispheric brain sections of 15 patients and 4 healthy controls. Proteolipid-stained tissue sections (8 μm) were matched to the corresponding MR images, and lesions were manually scored on both MR imaging sequences (blinded to histopathology) and tissue sections (blinded to MR imaging). The sensitivity of MR imaging sequences for GM lesion types and white matter lesions was calculated. An unblinded retrospective scoring was also performed.RESULTS:If all cortical GM lesions were taken into account, the T2WI sequence detected slightly more lesions than the T2*WI sequence: 28% and 16%, respectively (P = .054). This difference disappeared when only intracortical lesions were considered. When histopathologic information (type, location) was revealed to the reader, the sensitivity went up to 84% (T2WI) and 85% (T2*WI) (not significant). Furthermore, the false-positive rate was 8.6% for the T2WI and 10.5% for the T2*WI sequence.CONCLUSIONS:There is no strong advantage of the T2*WI sequence compared with a conventional T2WI sequence in the detection of cortical lesions at 7T. Retrospectively, a high percentage of lesions could be detected with both sequences. However, many lesions are still missed prospectively. This could possibly be minimized with better a priori observer training.

Multiple sclerosis is traditionally regarded as a chronic inflammatory demyelinating disease of the white matter with a variable clinical course; primary-progressive or relapsing-remitting with possible conversion to secondary-progressive. Pathologic, immunologic, and imaging studies have confirmed that tissue damage in the gray matter is also a key component of the disease process.^1–4 GM pathology occurs frequently, already early in the disease course, and explains cognitive and clinical disability better than white matter lesions.^5,6 Nevertheless, visualizing these GM abnormalities has been challenging due to their small size, absence of inflammation, and partial volume effect from adjacent CSF and WM. The introduction of ultra-high-field MR imaging scanners and specific MR imaging pulse sequences has improved the detection of GM lesions due to a higher signal-to-noise ratio and better spatial resolution.^7–9 7T T2*-weighted gradient-echo MR imaging has been shown to provide high-resolution anatomic images of GM lesions, and it has even been suggested that this sequence be used as the new criterion standard for GM lesion detection.¹⁰ It was reported to be 44% more sensitive than 1.5T MR imaging in detecting lesions with cortical involvement¹¹ and up to 69% more sensitive than 3T double inversion recovery (DIR) imaging in detecting subpial lesions.¹⁰Few groups have had the opportunity to study GM lesions that were visualized with 7T T2*WI in terms of histopathology. Therefore, little information is available on the exact sensitivity of T2*WI and/or whether certain lesion types are more visible than others with this sequence. One postmortem study that did look at T2*WI sensitivity showed a 48% prospective sensitivity but made no distinction among lesion types.¹² Another 7T study found that 46% of cortical lesions could be prospectively detected by using T2*WI and a similar 43% could be detected by using a WM-attenuated turbo field echo.¹³ However, the 2 sequences studied were suboptimally matched in terms of image resolution, which may explain the relative absence of differences between them. The current study aimed to determine the sensitivity of a standard T2WI and a T2*WI sequence, by using the same image resolution, for detecting MS GM lesion types in postmortem MS tissue.     

Quantitative fiber tracking in the corpus callosum and internal capsule reveals microstructural abnormalities in preterm infants at term-equivalent age

BACKGROUND AND PURPOSE:Signal-intensity abnormalities in the PLIC and thinning of the CC are often seen in preterm infants and associated with poor outcome. DTI is able to detect subtle abnormalities. We used FT to select bundles of interest (CC and PLIC) to acquire additional information on the WMI.MATERIALS AND METHODS:One hundred twenty preterm infants born at <31 weeks'' gestation with 3T DTI at TEA entered this prospective study. Quantitative information (ie, volume, length, anisotropy, and MD) was obtained from fiber bundles passing through the PLIC and CC. A general linear model was used to assess the effects of factor (sex) and variables (GA, BW, HC, PMA, and WMI) on FT-segmented parameters.RESULTS:Seventy-two CC and 85 PLIC fiber bundles were assessed. For the CC, increasing WMI and decreasing FA (P = .038), bundle volume (P < .001), and length (P = .001) were observed, whereas MD increased (P = .001). For PLIC, MD increased with increasing WMI (P = .002). Higher anisotropy and larger bundle length were observed in the left PLIC compared with the right (P = .003, P = .018).CONCLUSIONS:We have shown that in the CC bundle, anisotropy was decreased and diffusivity was increased in infants with high WMI scores. A relation of PLIC with WMI was also shown but was less pronounced. Brain maturation is affected more if birth was more premature.

Premature birth of <30 weeks'' gestation is associated with a high risk of neurodevelopmental impairments, including cognitive and motor disabilities.^1–3 The underlying neuropathology for cognitive disabilities is largely unknown, though it has been suggested that disturbances in the WM maturation play a role.^4,5 In teenagers, the effects of preterm birth are associated with thinning of the CC, widening of the ventricles, reduced volumes of the WM, and microstructural changes in the PLIC and the CC.^6–9MR imaging is commonly performed in preterm infants around TEA to detect brain injury. Different scoring systems have been developed to quantify MR imaging findings.^2,10 Although these scoring systems were related to outcome, they did not provide information about the pathology on a microstructural level. WM maturation may best be followed with DTI because this technique uses both information on the diffusion properties of water molecules that are restricted in tissue and information on the direction of diffusion (anisotropy). DTI has been shown to be sensitive to microstructural WM changes, like myelination.^11,12 Most information concerning DTI changes in relation to brain maturation is available from studies assessing selected ROIs in the WM.¹¹ It has been shown that the anisotropy in preterm infants is decreased at TEA in certain brain regions (among these, the CC and the frontal WM) compared with term-born controls.¹³Instead of measuring local effects in selected ROIs, FT can be applied to measure changes in bundles of WM. FT is a 3D visualization technique that reconstructs the underlying linear structure defined by the diffusion tensor.¹⁴ Quantification of WM tracts in infants has been performed previously^15–23 and is based on calculating an average of a certain DTI parameter over the complete bundle. Axial and radial diffusivity over specific tracts have been shown to be differentially affected by bundle maturation with age,^20,21 and DTI parameters quantifying the corticospinal tract are affected in preterm infants with WMI.²² Only 1 study recently investigated the genu and splenium of the CC in premature infants at TEA by using FT.²³ The CC is of interest because reduced callosal volumes have been shown to correlate with motor function and cognitive impairment.^24,25The aim of our study was to investigate whether diffusion tensor parameters, abstracted by using FT to select complete CC and PLIC bundles, display WM abnormalities in the premature infant at TEA. The WMI score² (as measured with conventional MR imaging) was used as a reference index.We hypothesized that WMI would be better detected with DTI and that it would give more information on the microstructure. We investigated, furthermore, how the DTI parameters were affected by GA at birth, BW, HC, sex, and the PMA, defined here as the age at the time of scanning.     

Phase White Matter Signal Abnormalities in Patients with Clinically Isolated Syndrome and Other Neurologic Disorders

BACKGROUND AND PURPOSE:Identifying MRI biomarkers that can differentiate multiple sclerosis patients from other neurological disorders is a subject of intense research. Our aim was to investigate phase WM signal abnormalities for their presence, prevalence, location, and diagnostic value among patients with clinically isolated syndrome and other neurologic disorders and age-, sex-, and group-matched healthy controls.MATERIALS AND METHODS:Forty-eight patients with clinically isolated syndrome and 30 patients with other neurologic diseases and a healthy control group (n = 47) were included in the study. Subjects were scanned at 3T by using SWI-filtered phase and T2WI, with WM signal abnormalities ≥3 mm being classified.RESULTS:Patients with clinically isolated syndrome had significantly more phase and T2 WM signal abnormalities than healthy controls (P < .001). Phase WM signal abnormalities were more prevalent among patients with clinically isolated syndrome compared with patients with other neurologic disorders (4:1 ratio), whereas T2 WM signal abnormalities were more ubiquitous with a 2:1 ratio. The presence of phase WM signal abnormalities was sensitive for clinically isolated syndrome (70.8%) and achieved a moderate-to-high specificity for differentiating patients with clinically isolated syndrome and healthy controls, patients with other neurologic disorders, and patients with other neurologic disorders of other autoimmune origin (specificity, 70%–76.7%). Combining the presence of ≥2 phase lesions with the McDonald 2005 and 2010 criteria for dissemination in space improved the specificity (90%), but not the accuracy, in differentiating patients with clinically isolated syndrome from those with other neurologic disorders. In subanalyses among patients with clinically isolated syndrome who converted to clinically definite multiple sclerosis versus those who did not within a 3-year follow-up period, converters had significantly more phase (P = .008) but not T2 or T1 WM signal abnormalities.CONCLUSIONS:Phase WM signal abnormalities are prevalent among patients with clinically isolated syndrome. The presence of (multiple) phase WM signal abnormalities tended to be more predictive of conversion to clinically definite multiple sclerosis and was specific in differentiating patients with clinically isolated syndrome and other neurologic disorders, compared with T2 WM signal abnormalities; however, the accuracy remains similar to that of the current McDonald criteria.

The occurrence of WM signal abnormalities (SAs) is a hallmark feature of multiple sclerosis, yet the clinical relevance of the pathologic substrate of WM-SAs is disappointing.^1–4 WM-SAs observed on T2WI and T1WI represent focal pathology and are thought to be caused by inflammation, edema, demyelination, or gliosis.² They are usually secondary to active inflammation, imaged by using postcontrast T1WI gadolinium-enhanced scanning.⁵ Even though T2 WM-SAs are present at the first demyelinating episode, the poor specificity of conventional MR imaging^1,6 and comparable MR imaging features at disease onset compared with ischemic, autoimmune diseases or aging limits their predictive value.Previously, differential diagnosis between MS and other conditions was considered by using brain and spinal cord MR imaging and incorporating number, location, and morphology of T2 WM-SAs in the diagnostic criteria of MS⁷ or by using different nonconventional MR imaging techniques.^6,8–10 It is important to further investigate the value of nonconventional MR imaging techniques in the MS differential diagnosis, for example by using SWI-filtered phase to identify early focal brain pathology indicative of MS, especially in patients with clinically isolated syndrome (CIS).Recent studies have confirmed histologically that WM-SAs visible on MR imaging phase and R^2* correspond to focal iron deposits, whereas T2 and T1 WM-SAs are influenced by water content.¹¹ A substantial subset of MS WM-SAs has phase shifts^11,12 and morphologic differences.^11–15 However, factors other than nonheme iron may influence the observed WM-SA signal, such as changes in myelin, deoxyhemoglobin, and inflammation.^11,16–19 Therefore, because there are a multitude of effects, it is not fully known to what extent they each individually influence SWI-filtered phase changes.Phase changes may signal early WM-SA development^17,20 in that these phase WM-SAs may appear initially but then disappear as the pathology advances.¹⁷ Considering that the distinct pathologies influencing phase shift (eg, cellular/myelin destruction, iron levels, microstructural changes) in WM-SAs are most likely intricately related and are observed in MS and related disorders,^{12,14,15,21–23} the inquiry into pathology visible on SWI-filtered phase remains important regardless of the causative factors.SWI-filtered phase work has mostly focused on patients with MS,^{11,13–15,24} high-field-strength imaging,^11,13,24 or histologically validating phase WM-SAs.^11,25 Regardless of what pathology phase WM-SAs represent, it is imperative to identify whether their presence has diagnostic value. In the present study, we assessed WM-SAs visible on T2WI and SWI-filtered phase among patients with CIS and patients with other neurologic disorders (OND) to investigate their prevalence, location, and ability to differentiate disease groups.     

Progression of Microstructural Damage in Spinocerebellar Ataxia Type 2: A Longitudinal DTI Study

BACKGROUND AND PURPOSE:The ability of DTI to track the progression of microstructural damage in patients with inherited ataxias has not been explored so far. We performed a longitudinal DTI study in patients with spinocerebellar ataxia type 2.MATERIALS AND METHODS:Ten patients with spinocerebellar ataxia type 2 and 16 healthy age-matched controls were examined twice with DTI (mean time between scans, 3.6 years [patients] and 3.3 years [controls]) on the same 1.5T MR scanner. Using tract-based spatial statistics, we analyzed changes in DTI-derived indices: mean diffusivity, axial diffusivity, radial diffusivity, fractional anisotropy, and mode of anisotropy.RESULTS:At baseline, the patients with spinocerebellar ataxia type 2, as compared with controls, showed numerous WM tracts with significantly increased mean diffusivity, axial diffusivity, and radial diffusivity and decreased fractional anisotropy and mode of anisotropy in the brain stem, cerebellar peduncles, cerebellum, cerebral hemisphere WM, corpus callosum, and thalami. Longitudinal analysis revealed changes in axial diffusivity and mode of anisotropy in patients with spinocerebellar ataxia type 2 that were significantly different than those in the controls. In patients with spinocerebellar ataxia type 2, axial diffusivity was increased in WM tracts of the right cerebral hemisphere and the corpus callosum, and the mode of anisotropy was extensively decreased in hemispheric cerebral WM, corpus callosum, internal capsules, cerebral peduncles, pons and left cerebellar peduncles, and WM of the left paramedian vermis. There was no correlation between the progression of changes in DTI-derived indices and clinical deterioration.CONCLUSIONS:DTI can reveal the progression of microstructural damage of WM fibers in the brains of patients with spinocerebellar ataxia type 2, and mode of anisotropy seems particularly sensitive to such changes. These results support the potential of DTI-derived indices as biomarkers of disease progression.

Spinocerebellar ataxia type 2 (SCA2) is the second most frequent autosomal dominant inherited ataxia worldwide, after SCA3.¹ It is caused by expansion in excess of 32 CAG repeats in the gene encoding the Ataxin-2 protein, which mainly targets several pontine neurons and Purkinje cells in the cerebellum,² and it is associated with a pathologic pattern of pontocerebellar atrophy.^1,3 MR T1-weighted imaging enables in vivo detection of brain stem and cerebellar atrophy in patients with SCA2 in cross-sectional^4–6 and longitudinal⁷ studies.Recently, DWI and DTI have enabled quantitative assessment of the microstructural changes in brain tissue that result from neurodegenerative diseases.^5,8–21 In particular, in longitudinal studies, DTI may be a sensitive instrument for tracking the progression of neurodegeneration (namely, neuronal damage and loss, Wallerian degeneration, demyelination, and gliosis) and, we hope, for detecting the efficacy (or lack of thereof) of new therapeutic strategies. So far, relatively few studies have addressed this point,^22–30 and none have addressed it in relation to autosomal dominant ataxias.We performed a longitudinal DTI study in 10 patients with SCA2 and 16 age-matched healthy controls to explore the ability of DTI to detect and map the progression of microstructural damage reflecting advance of neurodegeneration. In particular, we analyzed several DTI-derived indices, including mean diffusivity (MD), axial diffusivity (AD), radial diffusivity (RD), fractional anisotropy (FA), and mode of anisotropy (MO), by using tract-based spatial statistics (TBSS), which enable a robust and unbiased voxelwise whole-brain analysis of the main white matter tracts.^19,21,31,32     

Characterization of Extensive Microstructural Variations Associated with Punctate White Matter Lesions in Preterm Neonates

BACKGROUND AND PURPOSE:Punctate white matter lesions are common in preterm neonates. Neurodevelopmental outcomes of the neonates are related to the degree of extension. This study aimed to characterize the extent of microstructural variations for different punctate white matter lesion grades.MATERIALS AND METHODS:Preterm neonates with punctate white matter lesions were divided into 3 grades (from mild to severe: grades I–III). DTI-derived fractional anisotropy, axial diffusivity, and radial diffusivity between patients with punctate white matter lesions and controls were compared with Tract-Based Spatial Statistics and tract-quantification methods.RESULTS:Thirty-three preterm neonates with punctate white matter lesions and 33 matched controls were enrolled. There were 15, 9, and 9 patients, respectively, in grades I, II, and III. Punctate white matter lesions were mainly located in white matter adjacent to the lateral ventricles, especially regions lateral to the trigone, posterior horns, and centrum semiovale and/or corona radiata. Extensive microstructural changes were observed in neonates with grade III punctate white matter lesions, while no significant changes in DTI metrics were found for grades I and II. A pattern of increased axial diffusivity, increased radial diffusivity, and reduced/unchanged fractional anisotropy was found in regions adjacent to punctate white matter lesion sites seen on T1WI and T2WI. Unchanged axial diffusivity, increased radial diffusivity, and reduced/unchanged fractional anisotropy were observed in regions distant from punctate white matter lesion sites.CONCLUSIONS:White matter microstructural variations were different across punctate white matter lesion grades. Extensive change patterns varied according to the distance to the lesion sites in neonates with severe punctate white matter lesions. These findings may help in determining the outcomes of punctate white matter lesions and selecting treatment strategies.

Punctate white matter lesions (PWMLs) are common in neonates and have been found in >20% of preterm neonates (<37 weeks of gestation).^1–5 These lesions may cause severe neurologic disorders, such as cerebral palsy.^2,4 PWMLs can be identified on conventional MR imaging as hyperintensity on T1WI and hypointensity on T2WI.^1–3,6 PWMLs without cystic lesions can be divided into 3 grades.⁶ The grading scale ascends in severity on the basis of the number, size, and distribution of cerebral white matter lesions. Extensive microstructural alterations in white matter beyond the PWMLs visible on conventional MR imaging have been observed.³ The neurodevelopmental outcome of neonates is related to the degree of extension associated with PWMLs.^7,8 However, little is known about the extent of microstructural variations for different PWML grades. More detail is needed regarding the size ranges, shapes, and locations of neonatal/infantile PWMLs, PWML diffusion characteristics, and the distinction between hemorrhagic and nonhemorrhagic PWMLs.⁹DTI could provide quantitative metrics that reveal microstructural alterations associated with lesions.^10,11 DTI metrics, especially directional diffusivities, are sensitive to underlying histopathologic processes.¹² Several methods for analyzing DTI data have been proposed. Tract-Based Spatial Statistics (TBSS; http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/TBSS) is an automated approach for assessing alterations on major white matter tracts.¹³ The tract quantification method was proposed to characterize the location of alterations in white matter.¹⁴ These automated quantified methods have been used to detect variations due to brain development or injury^3,13–15 and may enable characterization of alterations associated with PWMLs.The goal of this study was to explore white matter microstructural variations associated with PWMLs of different grades in preterm neonates and to characterize the change in microstructural patterns along white matter tracts.     

Changes in the Thalamus in Atypical Parkinsonism Detected Using Shape Analysis and Diffusion Tensor Imaging

BACKGROUND AND PURPOSE:The thalamus is interconnected with the nigrostriatal system and cerebral cortex and has a major role in cognitive function and sensorimotor integration. The purpose of this study was to determine how regional involvement of the thalamus differs among Parkinson disease, progressive supranuclear palsy, and corticobasal syndrome.MATERIALS AND METHODS:Nine patients with Parkinson disease, 5 with progressive supranuclear palsy, and 6 with corticobasal syndrome underwent 3T MR imaging along with 12 matched, asymptomatic volunteers by using a protocol that included volumetric T1 and diffusion tensor imaging. Acquired data were automatically processed to delineate the margins of the motor and nonmotor thalamic nuclear groups, and measurements of ADC were calculated from the DTI data within these regions. Thalamic volume, shape, and ADC were compared across groups.RESULTS:Thalamic volume was smaller in the progressive supranuclear palsy and corticobasal syndrome groups compared with the Parkinson disease and control groups. Shape analysis revealed that this was mainly due to the diminished size of the lateral thalamus. Overall, ADC measurements were higher in the progressive supranuclear palsy group compared with both the Parkinson disease and control groups, and anatomic subgroup analysis demonstrated that these changes were greater within the motor regions of the thalamus in progressive supranuclear palsy and corticobasal degeneration.CONCLUSIONS:Reduced size and increased ADC disproportionately involve the lateral thalamus in progressive supranuclear palsy and corticobasal syndrome, consistent with selective neurodegeneration and atrophy in this region. Because these findings were not observed in Parkinson disease, they may be more specific markers of tau-related neurodegeneration.

The neurodegenerative movement disorders Parkinson disease (PD), progressive supranuclear palsy (PSP), and corticobasal degeneration (CBD) are distinguished postmortem by differing histologic abnormalities and regional patterns of neuropathologic changes. PSP and corticobasal syndrome (CBS) exhibit neuronal and glial cytoplasmic inclusions from accumulation of highly phosphorylated microtubule-associated tau protein, which is not evident in PD.^1–3 Paralleling these differences, typical clinical phenotypes help to distinguish these disorders. However, classic presentations are consistent only in advanced disease, and misdiagnosis is frequent in patients with early symptoms.^4,5 The diagnosis of CBD is particularly problematic⁶; for this reason, the term “corticobasal syndrome” is applied in lieu of CBD to convey the fact that disorders including Alzheimer disease, certain variants of frontotemporal lobar degeneration, and prion disease can present similarly.Various observations on MR imaging have been reported to differentiate PD, PSP, and CBD. Alterations in the shape or volume of several subcortical brain regions correlate with gross inspection of the brain in pathologically confirmed cases.⁷ However, such changes are subject to observer bias and are reliably found only in late disease. Unbiased approaches by using voxel-based morphometry and automated segmentation have also been applied with some success.^8–13 DTI studies have revealed increased diffusivity within the superior cerebellar peduncles in PSP,^14–16 along with more widespread changes within supratentorial white matter.^17,18 A number of groups have also described alterations in deep gray matter diffusion. For example, measurements of ADC are elevated within the putamen in up to 90% of patients with atypical parkinsonism but not significantly different from controls in patients with PD.^16,19The shared anatomic involvement of the basal ganglia and other brain regions in these disorders likely contributes to their frequent clinical overlap. Few studies have focused specifically on the thalamus, which, through the nigrostriatal system and thalamocortical circuits, plays a major role in cognition and sensorimotor integration. Alterations in thalamic volume have not been shown in prior studies of CBS, but significantly lower thalamic volume has been observed in PSP compared with both patients with PD²⁰ and controls.^10,20 Diminished volume by itself does not provide insight into how separate nuclear groups within the thalamus are selectively affected, however. One study suggested that thalamic shape differs between subjects with PD and healthy elders, though these changes were challenging to interpret because there was multifocal involvement over the entire surface of the thalamus without a corresponding difference in volume.²¹ Using DTI, Erbetta et al²² measured higher ADC within the anterior and lateral thalami in PSP and CBS compared with controls, but their analysis was based on relatively imprecise atlas-based estimates of nuclear boundaries.²²We hypothesized that regional thalamic morphology and tissue microstructure, measured with volumetric T1-weighted MR imaging and DTI, respectively, would be different in patients with PSP and CBS compared with patients with PD and controls. Using fully automated analysis of 3T T1 and DTI data, we evaluated thalamic shape and diffusion within motor and nonmotor thalamic nuclear groups and compared these measurements in patients with CBS, PSP, and PD and in healthy control subjects.     

Pre- and Postcontrast 3D Double Inversion Recovery Sequence in Multiple Sclerosis: A Simple and Effective MR Imaging Protocol

BACKGROUND AND PURPOSE:The double inversion recovery sequence is known to be very sensitive and specific for MS-related lesions. Our aim was to compare the sensitivity of pre- and postcontrast images of 3D double inversion recovery and conventional 3D T1-weighted images for the detection of contrast-enhancing MS-related lesions in the brain to analyze whether double inversion recovery could be as effective as T1WI.MATERIALS AND METHODS:A postcontrast 3D double inversion recovery sequence was acquired in addition to the standard MR imaging protocol at 3T, including pre- and postcontrast 3D T1WI sequences as well as precontrast double inversion recovery of 45 consecutive patients with MS or clinically isolated syndrome between June and December 2013. Two neuroradiologists independently assessed precontrast, postcontrast, and subtraction images of double inversion recovery as well as T1WI to count the number of contrast-enhancing lesions. Afterward, a consensus reading was performed. Lin concordance was calculated between both radiologists, and differences in lesion detectability were assessed with the Student t test. Additionally, the contrast-to-noise ratio was calculated.RESULTS:Significantly more contrast-enhancing lesions could be detected with double inversion recovery compared with T1WI (16%, 214 versus 185, P = .007). The concordance between both radiologists was almost perfect (ρ_c = 0.94 for T1WI and ρ_c = 0.98 for double inversion recovery, respectively). The contrast-to-noise ratio was significantly higher in double inversion recovery subtraction images compared with T1-weighted subtraction images (double inversion recovery, 14.3 ± 5.5; T1WI, 6.3 ± 7.1; P < .001).CONCLUSIONS:Pre- and postcontrast double inversion recovery enables better detection of contrast-enhancing lesions in MS in the brain compared with T1WI and may be considered an alternative to the standard MR imaging protocol.

Since the introduction of the double inversion recovery (DIR) sequence in 1994 by Redpath and Smith,^1,2 many studies have investigated the usefulness of DIR for the detection of inflammatory lesions in the brain in multiple sclerosis. In this sequence, the signals from both the CSF and normal white matter are suppressed simultaneously; thus, differentiation between gray matter and white matter is facilitated. Additionally, inflammatory lesions remain unsuppressed and appear hyperintense. The studies concluded that DIR is very sensitive and specific for MS lesions in the brain,^3–5 especially for intracortical lesions.^6–8 One group could also show that DIR provides the highest sensitivity in the detection of MS lesions in the infratentorial region compared with FLAIR and T2WI.⁴ A similar benefit was found for an adapted DIR sequence in the spinal cord.⁹ Due to the high sensitivity and specificity as well as the increasing availability of the DIR sequence, it is more often included in routine MR imaging protocols.The standard MR imaging protocol for the examination of patients with MS commonly includes the intravenous administration of gadolinium-based contrast agents (GBCAs). The presence of contrast-enhancing lesions is important for the diagnosis and therapeutic strategies of MS and is listed in the revised McDonald criteria from 2010¹⁰ and the magnetic resonance imaging in multiple sclerosis consensus guidelines¹¹ for the criteria of dissemination in time. Because the best sensitivity for enhancing lesions is achieved about 5–10 minutes after injection of a GBCA,¹² further sequences, usually T2WI, are performed for bridging the waiting time. However, these sequences should be carefully selected because the signal of contrast-enhancing lesions might be changed in modified T2WI sequences such as FLAIR^13,14 or DIR.^15,16One group found that contrast-enhancing parts of tumors appear hypointense in postcontrast DIR.¹⁵ Furthermore, it has been shown recently that there is an altered signal intensity of active enhancing inflammatory MS lesions in postcontrast DIR of the brain.¹⁶ This observation led to the recommendation to acquire DIR sequences before GBCA administration.Here, we test the hypothesis that the signal loss on DIR images after GBCA administration can be used to detect active enhancing lesions. In particular, the aim was to compare the sensitivity of pre- and postcontrast images of 3D double inversion recovery and conventional 3D T1WI for the detection of contrast-enhancing MS-related lesions in the brain to analyze whether DIR could be as effective as T1WI.     

Test-Retest and Interreader Reproducibility of Semiautomated Atlas-Based Analysis of Diffusion Tensor Imaging Data in Acute Cervical Spine Trauma in Adult Patients

BACKGROUND AND PURPOSE:DTI is a tool for microstructural spinal cord injury evaluation. This study evaluated the reproducibility of a semiautomated segmentation algorithm of spinal cord DTI.MATERIALS AND METHODS:Forty-two consecutive patients undergoing acute trauma cervical spine MR imaging underwent 2 axial DTI scans in addition to their clinical scan. The datasets were put through a semiautomated probabilistic segmentation algorithm that selected white matter, gray matter, and 24 individual white matter tracts. Regional and white matter tract volume, fractional anisotropy, and mean diffusivity values were calculated. Two readers performed the nonautomated steps to evaluate interreader reproducibility. The coefficient of variation and intraclass correlation coefficient were used to assess test-retest and interreader reproducibility.RESULTS:Of 42 patients, 30 had useable data. Test-retest reproducibility of fractional anisotropy was high for white matter as a whole (coefficient of variation, 3.8%; intraclass correlation coefficient, 0.93). Test-retest coefficient-of-variation ranged from 8.0%–18.2% and intraclass correlation coefficients from 0.47–0.80 across individual white matter tracts. Mean diffusivity metrics also had high test-retest reproducibility (white matter: coefficient-of-variation, 5.6%; intraclass correlation coefficient, 0.86) with coefficients of variation from 11.6%–18.3% and intraclass correlation coefficients from 0.57–0.74 across individual tracts, with better agreement for larger tracts. The coefficients of variation of fractional anisotropy and mean diffusivity both had significant negative relationships with white matter volume (26%–27% decrease for each doubling of white matter volume, P < .01).CONCLUSIONS:DTI spinal cord segmentation is reproducible in the setting of acute spine trauma, specifically for larger white matter tracts and total white or gray matter.

DTI is a technique that provides microstructural evaluation not afforded by conventional MR imaging techniques.¹ In various disease states, DTI has been extensively investigated in brain applications and can detect abnormalities in otherwise normal-appearing brain regions^2,3 and is able to predict outcomes.⁴ Early DTI use shows promise in detecting spinal cord abnormalities associated with spinal cord injury,^5,6 demyelinating diseases,⁷ spondylotic myelopathy,⁸ HIV myelopathy,⁹ and various inflammatory and vascular myelopathies.¹⁰ In acute spinal cord trauma, DTI has shown value in assessing microstructural injury, differentiating between hemorrhagic and nonhemorrhagic contusions, and strong correlation with clinical injury scores.⁵Similar to brain DTI, tract-based white matter analysis of the spinal cord may offer additional insight into white matter characteristics in both healthy and diseased states.^11–13 Current methods of evaluating spine DTI data, however, are either purely qualitative assessments or labor-intensive hand-drawn ROIs that may be prone to reader-related variability/imprecision and poor reproducibility. In brain DTI, completely automated methods are available to reliably parcel the brain,¹⁴ with application to clinical care.¹⁵ Recently, a set of tools has been released as part of the “Spinal Cord Toolbox” that can allow for spinal cord registration, segmentation, and parcellation.¹⁶ The Spinal Cord Toolbox (https://www.nitrc.org/projects/sct/) has been applied to flaccid myelitis on T2-weighted imaging,¹⁷ functional imaging of the spine,¹⁸ and T2*, DTI, and inhomogeneous magnetization transfer sequences in healthy patients at a range of ages.¹⁹ To date, evaluation of the reproducibility of spinal cord segmentation and analysis algorithms such as the Spinal Cord Toolbox when using DTI sequences has been lacking. In addition, the reproducibility of DTI in the setting of acute spinal cord trauma has yet to be evaluated. Determination of these characteristics is particularly important in the setting of trauma evaluation, where the presence of factors such as pain or cognitive dysfunction from associated injuries, medication effect, susceptibility artifact from metallic fusion hardware, or the presence of external lines may impact image acquisition and interpretation.In this study, we evaluated the test-retest reproducibility of a semiautomated atlas-based technique for extracting tract-specific and level-specific diffusion metrics in patients with acute cervical spine trauma. Furthermore, we also assessed the influence of reader-induced variability on the parcellation process.     

Diffusional Kurtosis Imaging of the Corticospinal Tract in Multiple Sclerosis: Association with Neurologic Disability

BACKGROUND AND PURPOSE:Multiple sclerosis is an autoimmune disorder resulting in progressive neurologic disability. Our aim was to evaluate the associations between diffusional kurtosis imaging–derived metrics for the corticospinal tract and disability in multiple sclerosis.MATERIALS AND METHODS:Forty patients with MS underwent brain MR imaging including diffusional kurtosis imaging. After we masked out T2 hyperintense lesions, the fractional anisotropy, mean diffusivity, radial diffusivity, axial diffusivity, mean kurtosis, radial kurtosis, and axial kurtosis were estimated for the corticospinal tract. Disability was quantified by using the Expanded Disability Status Scale at the time of MR imaging and 12 months post-MR imaging. The Pearson correlation coefficient and linear regression analyses were conducted to evaluate the associations between diffusion metrics and disability.RESULTS:Significant correlations were found between the Expanded Disability Status Scale scores during the baseline visit and age (r = 0.47), T2 lesion volume (r = 0.38), corticospinal tract mean diffusivity (r = 0.41), radial diffusivity (r = 0.41), axial diffusivity (r = 0.34), fractional anisotropy (r = −0.36), and radial kurtosis (r = −0.42). Significant correlations were also found between the Expanded Disability Status Scale scores at 12-month follow-up and age (r = 0.38), mean diffusivity (r = 0.45), radial diffusivity (r = 0.41), axial diffusivity (r = 0.45), mean kurtosis (r = −0.42), radial kurtosis (r = −0.56), and axial kurtosis (r = −0.36). Linear regression analyses demonstrated significant associations among radial kurtosis, age, and Expanded Disability Status Scale score during the baseline visit, while radial kurtosis was the only variable associated with Expanded Disability Status Scale score for the 12-month follow-up.CONCLUSIONS:Radial kurtosis of the corticospinal tract may have an association with neurologic disability in MS.

Multiple sclerosis is an autoimmune disorder of the central nervous system characterized by recurrent episodes of inflammation, demyelination, edema, and axonal loss, which can result in a progressive accumulation of neurologic disability.¹ MR imaging is routinely performed to assess the burden of disease in patients with MS to guide therapeutic decisions.² Conventional MR imaging is widely used to evaluate macrostructural changes such as T2 hyperintense lesions, T1 black holes, gadolinium-enhancing lesions, and brain volume loss.^3,4 Although conventional MR imaging analysis has been used for years to assess the disease burden, it cannot fully explain the degree of neurologic dysfunction. The lack of correlation between neurologic disability and conventional MR imaging measures is commonly described as the “clinicoradiologic paradox.”⁴DTI has been previously used to assess the integrity of brain tissue and to probe specific white matter tracts.^5–12 Prior studies have evaluated microstructural changes of the corticospinal tract (CST) in MS and the association between diffusivity of the CST and measures of neurologic disability.^5,7,13–17 However, a fundamental limitation of DTI is that the data analysis approximates the water diffusion dynamics within brain tissue as being a Gaussian process, though considerable non-Gaussian diffusion effects are observed throughout the brain. Hence, DTI does not fully characterize water diffusion in the brain. Diffusional kurtosis imaging (DKI)¹⁸ is a clinically feasible diffusion MR imaging method, which extends the DTI model to include non-Gaussian diffusion effects.^18–20 As a result, DKI has the potential to provide more sensitive biomarkers for probing microscopic structural changes occurring in the normal-appearing white matter (NAWM), which could lead to better predictive biomarkers for disease progression. Although DKI has been applied to MS in a few preliminary studies,^18–22 the potential of DKI to aid in the assessment of neurologic disability in MS is still not well-established.The aim of this study was to examine the associations between DKI-derived diffusion metrics of the corticospinal tract and physical disability in patients affected by MS, as measured by the Extended Disability Status Scale (EDSS).²³ Our hypothesis was that DKI-derived metrics have stronger associations with neurologic dysfunction than DTI metrics.     

White Matter Microstructural Abnormalities in Type 2 Diabetes Mellitus: A Diffusional Kurtosis Imaging Analysis

BACKGROUND AND PURPOSE:Increasing DTI studies have demonstrated that white matter microstructural abnormalities play an important role in type 2 diabetes mellitus–related cognitive impairment. In this study, the diffusional kurtosis imaging method was used to investigate WM microstructural alterations in patients with type 2 diabetes mellitus and to detect associations between diffusional kurtosis imaging metrics and clinical/cognitive measurements.MATERIALS AND METHODS:Diffusional kurtosis imaging and cognitive assessments were performed on 58 patients with type 2 diabetes mellitus and 58 controls. Voxel-based intergroup comparisons of diffusional kurtosis imaging metrics were conducted, and ROI-based intergroup comparisons were further performed. Correlations between the diffusional kurtosis imaging metrics and cognitive/clinical measurements were assessed after controlling for age, sex, and education in both patients and controls.RESULTS:Altered diffusion metrics were observed in the corpus callosum, the bilateral frontal WM, the right superior temporal WM, the left external capsule, and the pons in patients with type 2 diabetes mellitus compared with controls. The splenium of the corpus callosum and the pons had abnormal kurtosis metrics in patients with type 2 diabetes mellitus. Additionally, altered diffusion metrics in the right prefrontal WM were significantly correlated with disease duration and attention task performance in patients with type 2 diabetes mellitus.CONCLUSIONS:With both conventional diffusion and additional kurtosis metrics, diffusional kurtosis imaging can provide additional information on WM microstructural abnormalities in patients with type 2 diabetes mellitus. Our results indicate that WM microstructural abnormalities occur before cognitive decline and may be used as neuroimaging markers for predicting the early cognitive impairment in patients with type 2 diabetes mellitus.

Type 2 diabetes mellitus (T2DM) is a common metabolic disorder with an increasing worldwide prevalence,¹ and is widely accepted as a risk factor associated with mild cognitive impairment and dementia.^2,3 A number of neuroimaging studies have demonstrated that GM structural abnormalities^4–6 might account for cognitive deficits in patients with T2DM. By contrast, studies on white matter structures, which play a vital role in transferring information between GM regions, are relatively rare. A few studies using the DTI method identified microstructural changes of WM in patients with T2DM,^7–13 and alterations of local and global network properties were also observed in patients with T2DM with the tractography method.¹⁴ In addition, the association between the WM microstructural abnormalities and cognitive performance was also revealed in patients with T2DM.^7,10,12–14However, information provided by DTI was limited, partly because diffusion metrics obtained from DTI are calculated on the basis of the assumption of Gaussian diffusion of water molecules.¹⁵ However, non-Gaussian diffusion is known to be substantial¹⁶ and is believed to result from the diffusion barriers, such as cell membranes and organelles, as well as water compartments (eg, extracellular and intracellular) with altering diffusion properties. In this study, we sought to further characterize WM changes in patients with T2DM without cognitive impairment by using diffusional kurtosis imaging (DKI), which is a clinically feasible extension of DTI that enables the examination of additional non-Gaussian diffusion effects, providing both DTI-compatible diffusion metrics and additional kurtosis metrics.¹⁷ Additionally, due to the inclusion of non-Gaussian effects, DKI-derived estimates of diffusion metrics are generally more accurate than those obtained with conventional DTI,¹⁸ and the added kurtosis metrics can yield additional information about tissue microstructure beyond that provided by diffusion metrics.The aims of this study were the following: 1) to assess the ability of DKI and DTI to identify microstructural abnormalities in patients with T2DM; 2) to investigate whether DKI-specific diffusion and kurtosis metrics could provide additional information about the WM microstructural changes; and 3) to investigate whether these microstructural abnormalities are related to clinical/cognitive variables in patients with T2DM without cognitive impairment.