Differentiating the histologic grades of gliomas preoperatively using amide proton transfer‐weighted (APTW) and intravoxel incoherent motion MRI

The purpose of this work was to investigate the diagnostic performance of amide proton transfer‐weighted (APTW) and intravoxel incoherent motion (IVIM) magnetic resonance imaging (MRI) in the preoperative grading of gliomas. Fifty‐one patients with suspected gliomas were recruited and underwent a preoperative MRI examination that included APTW and IVIM sequences. All cases were confirmed by postsurgical histopathology. APTW signal intensity, true diffusion coefficient (D), perfusion fraction (f) and pseudo‐diffusion coefficient (D*) were applied to assess the solid tumor component and contralateral normal‐appearing white matter. The relative APTW signal intensity (rAPTW) was also used. Independent‐sample and paired‐sample t‐tests were used to compare differences in MRI parameters between low‐grade glioma (LGG) and high‐grade glioma (HGG) groups. The diagnostic performance was assessed with the receiver operating characteristic curve. Twenty‐six patients were pathologically diagnosed with LGG and 25 were diagnosed with HGG. APTW, rAPTW and f values were significantly higher (all p < 0.001), whereas D values were significantly lower (p < 0.001) in the HGG group than in the LGG group. There was no significant difference between D* values for the two groups. rAPTW had an area under the curve (AUC) of 0.957, with a sensitivity of 100% and a specificity of 84.6%, followed by APTW, f, D and D*. The combined use of APTW and IVIM showed the best diagnostic performance, with an AUC of 0.986. In conclusion, APTW and IVIM, as two promising supplementary sequences for routine MRI, could be valuable in differentiating LGGs from HGGs.     

Assessment of diffusion parameters by intravoxel incoherent motion MRI in head and neck squamous cell carcinoma

The objectives of this study were to assess the diffusion parameters derived from intravoxel incoherent motion (IVIM) MRI in head and neck squamous cell carcinoma (HNSCC) and to investigate the agreement between different methods of tumor delineation and two numerical methods to extract the perfusion fraction f. Thirty‐seven untreated patients with histopathologically confirmed primary HNSCC were included retrospectively in the study. The entire volume of the primary tumor was outlined on diffusion‐weighted images using co‐registered morphological images as a guide to the tumor location. Apparent diffusion coefficient (ADC) and IVIM diffusion parameters were estimated considering the largest tumor section as well as the entire tumor volume. A bi‐exponential fit was implemented to extract f, D (pure diffusion coefficient) and D* (pseudo‐diffusion coefficient). A second simplified method, based on an asymptotic extrapolation, was used to determine f. The agreement between ADC and IVIM diffusion parameters derived from the delineation of single and multiple slices, and between the two f estimations, was assessed by Bland–Altman plots. The inter‐slice variability of ADC and IVIM diffusion parameters was evaluated. The Kruskal–Wallis test was used to investigate whether the tumor location had a statistically significant influence on the values of the parameters. Comparing the tumor delineation methods, a better accordance was found for ADC and D, with a mean percentage difference of less than 2%. Larger discrepancies were found for f and D*, with mean differences of 4.5% and 5.5%, respectively. When comparing the two f estimation methods, small mean differences were found (<3.5%), suggesting that the two methods may be considered as equivalent for the assessment of f in our patient population. The observed ADC and IVIM diffusion parameters were dependent on the anatomic site of the lesion, carcinoma of the nasopharynx showing more homogeneous and dissimilar estimations than other HNSCCs. Copyright © 2013 John Wiley & Sons, Ltd.     

Stroke assessment with intravoxel incoherent motion diffusion‐weighted MRI

Intravoxel incoherent motion (IVIM) diffusion‐weighted MRI can simultaneously measure diffusion and perfusion characteristics in a non‐invasive way. This study aimed to determine the potential utility of IVIM in characterizing brain diffusion and perfusion properties for clinical stroke. The multi‐b‐value diffusion‐weighted images of 101 patients diagnosed with acute/subacute ischemic stroke were retrospectively evaluated. The diffusion coefficient D, representing the water apparent diffusivity, was obtained by fitting the diffusion data with increasing high b‐values to a simple mono‐exponential model. The IVIM‐derived perfusion parameters, pseudodiffusion coefficient D*, vascular volume fraction f and blood flow‐related parameter fD*, were calculated with the bi‐exponential model. Additionally, the apparent diffusion coefficient (ADC) was fitted according to the mono‐exponential model using all b‐values. The diffusion parameters for the ischemic lesion and normal contralateral region were measured in each patient. Statistical analysis was performed using the paired Student t‐test and Pearson correlation test. Diffusion data in both the ischemic lesion and normal contralateral region followed the IVIM bi‐exponential behavior, and the IVIM model showed better goodness of fit than the mono‐exponential model with lower Akaike information criterion values. The paired Student t‐test revealed significant differences for all diffusion parameters (all P < 0.001) except D* (P = 0.218) between ischemic and normal areas. For all patients in both ischemic and normal regions, ADC was significantly positively correlated with D (both r = 1, both P < 0.001) and f (r = 0.541, P < 0.001; r = 0.262, P = 0.008); significant correlation was also found between ADC and fD* in the ischemic region (r = 0.254, P = 0.010). For all pixels within the region of interest from a representative subject in both ischemic and normal regions, ADC was significantly positively correlated with D (both r = 1, both P < 0.001), f (r = 0.823, P < 0.001; r = 0.652, P < 0.001) and fD* (r = 0.294, P < 0.001; r = 0.340, P < 0.001). These findings may have clinical implications for the use of IVIM imaging in the assessment and management of acute/subacute stroke patients. Copyright © 2016 John Wiley & Sons, Ltd.     

Multi‐centre reproducibility of diffusion MRI parameters for clinical sequences in the brain

The purpose of this work was to assess the reproducibility of diffusion imaging, and in particular the apparent diffusion coefficient (ADC), intra‐voxel incoherent motion (IVIM) parameters and diffusion tensor imaging (DTI) parameters, across multiple centres using clinically available protocols with limited harmonization between sequences. An ice–water phantom and nine healthy volunteers were scanned across fives centres on eight scanners (four Siemens 1.5T, four Philips 3T). The mean ADC, IVIM parameters (diffusion coefficient D and perfusion fraction f) and DTI parameters (mean diffusivity MD and fractional anisotropy FA), were measured in grey matter, white matter and specific brain sub‐regions. A mixed effect model was used to measure the intra‐ and inter‐scanner coefficient of variation (CV) for each of the five parameters. ADC, D, MD and FA had a good intra‐ and inter‐scanner reproducibility in both grey and white matter, with a CV ranging between 1% and 7.4%; mean 2.6%. Other brain regions also showed high levels of reproducibility except for small structures such as the choroid plexus. The IVIM parameter f had a higher intra‐scanner CV of 8.4% and inter‐scanner CV of 24.8%. No major difference in the inter‐scanner CV for ADC, D, MD and FA was observed when analysing the 1.5T and 3T scanners separately. ADC, D, MD and FA all showed good intra‐scanner reproducibility, with the inter‐scanner reproducibility being comparable or faring slightly worse, suggesting that using data from multiple scanners does not have an adverse effect compared with using data from the same scanner. The IVIM parameter f had a poorer inter‐scanner CV when scanners of different field strengths were combined, and the parameter was also affected by the scan acquisition resolution. This study shows that the majority of diffusion MRI derived parameters are robust across 1.5T and 3T scanners and suitable for use in multi‐centre clinical studies and trials. © 2015 The Authors NMR in Biomedicine Published by John Wiley & Sons Ltd.     

Relationship between diffusion parameters derived from intravoxel incoherent motion MRI and perfusion measured by dynamic contrast‐enhanced MRI of soft tissue tumors

Our aim was to evaluate the link between diffusion parameters measured by intravoxel incoherent motion (IVIM) diffusion‐weighted imaging (DWI) and the perfusion metrics obtained with dynamic contrast‐enhanced (DCE) MRI in soft tissue tumors (STTs). Twenty‐eight patients affected by histopathologically confirmed STT were included in a prospective study. All patients underwent both DCE MRI and IVIM DWI. The perfusion fraction f, diffusion coefficient D and perfusion‐related diffusion coefficient D* were estimated using a bi‐exponential function to fit the DWI data. DCE MRI was acquired with a temporal resolution of 3–5 s. Maps of the initial area under the gadolinium concentration curve (IAUGC), time to peak (TTP) and maximum slope of increase (MSI) were derived using commercial software. The relationships between the DCE MRI and IVIM DWI measurements were assessed by Spearman's test. To exclude false positive results under multiple testing, the false discovery rate (FDR) procedure was applied. The Mann–Whitney test was used to evaluate the differences between all variables in patients with non‐myxoid and myxoid STT. No significant relationship was found between IVIM parameters and any DCE MRI parameters. Higher f and D*f values were found in non‐myxoid tumors compared with myxoid tumors (p = 0.004 and p = 0.003, respectively). MSI was significantly higher in non‐myxoid tumors than in myxoid tumors (p = 0.029). From the visual assessments of single clinical cases, both f and D*f maps were in satisfactory agreement with DCE maps in the extreme cases of an avascular mass and a highly vascularized mass, whereas, for tumors with slight vascularity or with a highly heterogeneous perfusion pattern, this association was not straightforward. Although IVIM DWI was demonstrated to be feasible in STT, our data did not support evident relationships between perfusion‐related IVIM parameters and perfusion measured by DCE MRI. Copyright © 2015 John Wiley & Sons, Ltd.     

Correlative assessment of tumor microcirculation using contrast‐enhanced perfusion MRI and intravoxel incoherent motion diffusion‐weighted MRI: is there a link between them?

The purpose of this study was to correlate intravoxel incoherent motion (IVIM) imaging with classical perfusion‐weighted MRI metrics in human gliomas. Parametric images for slow diffusion coefficient (D), fast diffusion coefficient (D*), and fractional perfusion‐related volume (f) in patients with high‐grade gliomas were generated. Maps of F_p (plasma flow), v_p (vascular plasma volume), PS (permeability surface–area product), v_e (extravascular, extracellular volume), E (extraction ratio), k_e (influx ratio into the interstitium), and t_c (vascular transit time) from dynamic contrast‐enhanced (DCE) and dynamic susceptibility contrast‐enhanced (DSC) MRI were also generated. A region‐of‐interest analysis on the contralateral healthy white matter and on the tumor areas was performed and the extracted parameter values were tested for any significant differences among tumor grades or any correlations. Only f could be significantly correlated to DSC‐derived v_p and t_c in healthy brain tissue. Concerning the tumor regions, F_p was significantly positively correlated with D* and inversely correlated with f in DSC measurements. The D*, f, and f × D* values in the WHO grade III gliomas were non‐significantly different from those in the grade IV gliomas. There was a trend to significant negative correlations between f and PS as well as between f × D* and k_e in DCE experiments. Presumably due to different theoretical background, tracer properties and modeling of the tumor vasculature in the IVIM theory, there is no clearly evident link between D*, f and DSC‐ and DCE‐derived metrics. Copyright © 2014 John Wiley & Sons, Ltd.     

Time‐dependent diffusion MRI as a probe of microstructural changes in a mouse model of Duchenne muscular dystrophy

Dystrophic muscles show a high variability of fibre sizes and altered sarcolemmal integrity, which are typically assessed by histology. Time‐dependent diffusion MRI is sensitive to tissue microstructure and its investigation through age‐related changes in dystrophic and healthy muscles may help the understanding of the onset and progression of Duchenne muscular dystrophy (DMD). We investigated the capability of time‐dependent diffusion MRI to quantify age and disease‐related changes in hind‐limb muscle microstructure between dystrophic (mdx) and wild‐type (WT) mice of three age groups (7.5, 22 and 44 weeks). Diffusion time‐dependent apparent diffusion coefficients (ADCs) of the gastrocnemius and tibialis anterior muscles were determined versus age and diffusion‐gradient orientation at six diffusion times (Δ; range: 25–350 ms). Mean muscle ADCs were compared between groups and ages, and correlated with T₂, using Student's t test, one‐way analysis of variance and Pearson correlation, respectively. Muscle fibre sizes and sarcolemmal integrity were evaluated by histology and compared with diffusion measurements. Hind‐limb muscle ADC showed characteristic restricted diffusion behaviour in both mdx and WT animals with decreasing ADC values at longer Δ. Significant differences in ADC were observed at long Δ values (≥ 250 ms; p < 0.05, comparison between groups; p < 0.01, comparison between ages) with ADC increased by 5–15% in dystrophic muscles, indicative of reduced diffusion restriction. No significant correlation was found between T₂ and ADC. Additionally, muscle fibre size distributions showed higher variability and lower mean fibre size in mdx than WT animals (p < 0.001). The extensive Evans Blue Dye uptake shown in dystrophic muscles revealed substantial sarcolemmal damage, suggesting diffusion measurements as more consistent with altered permeability rather than changes in muscle fibre sizes. This study shows the potential of diffusion MRI to non‐invasively discriminate between dystrophic and healthy muscles with enhanced sensitivity when using long Δ.     

Interstitial fluid pressure correlates with intravoxel incoherent motion imaging metrics in a mouse mammary carcinoma model

The effective delivery of a therapeutic drug to the core of a tumor is often impeded by physiological barriers, such as the interstitial fluid pressure (IFP). There are a number of therapies that can decrease IFP and induce tumor vascular normalization. However, a lack of a noninvasive means to measure IFP hinders the utilization of such a window of opportunity for the maximization of the treatment response. Thus, the purpose of this study was to investigate the feasibility of using intravoxel incoherent motion (IVIM) diffusion parameters as noninvasive imaging biomarkers for IFP. Mice bearing the 4T1 mammary carcinoma model were studied using diffusion‐weighted imaging (DWI), immediately followed by wick‐in‐needle IFP measurement. Voxelwise analysis was conducted with a conventional monoexponential diffusion model, as well as a biexponential model taking IVIM into account. There was no significant correlation of IFP with either the median apparent diffusion coefficient from the monoexponential model (r = 0.11, p = 0.78) or the median tissue diffusivity from the biexponential model (r = 0.30, p = 0.44). However, IFP was correlated with the median pseudo‐diffusivity (D_p) of apparent vascular voxels (r = 0.76, p = 0.02) and with the median product of the perfusion fraction and pseudo‐diffusivity (f_pD_p) of apparent vascular voxels (r = 0.77, p = 0.02). Although the effect of IVIM in tumors has been reported previously, to our knowledge, this study represents the first direct comparison of IVIM metrics with IFP, with the results supporting the feasibility of the use of IVIM DWI metrics as noninvasive biomarkers for tumor IFP. Copyright © 2011 John Wiley & Sons, Ltd.     

Diffusion‐weighted MRI with intravoxel incoherent motion modeling for assessment of muscle perfusion in the thigh during post‐exercise hyperemia in younger and older adults

Aging is associated with impaired endothelium‐dependent vasodilation that leads to muscle perfusion impairment and contributes to organ dysfunction. Impaired muscle perfusion may result in inadequate delivery of oxygen and nutrients during and after muscle contraction, leading to muscle damage. The ability to study the relationship between perfusion and muscle damage has been limited using traditional muscle perfusion measures, which are invasive and risky. To overcome this limitation, we optimized a diffusion‐weighted MRI sequence and validated an intravoxel incoherent motion (IVIM) analysis based on Monte Carlo simulation to study muscle perfusion impairment with aging during post‐exercise hyperemia. Simulation results demonstrated that the bias of IVIM‐derived perfusion fraction (f_p ) and diffusion of water molecules in extra‐vascular tissue (D ) ranged from ?3.3% to 14% and from ?16.5% to 0.002%, respectively, in the optimized experimental condition. The dispersion in f_p and D ranged from 3.2% to 9.5% and from 0.9% to 1.1%, respectively. The mid‐thigh of the left leg of four younger (21–30 year old) and four older (60–90 year old) healthy females was studied using the optimized protocol at baseline and at seven time increments occurring every 3.25 min following in‐magnet dynamic knee extension exercise performed using a MR‐compatible ergometer with a workload of 0.4 bar for 2.5 min. After exercise, both f_p and D significantly increased in the rectus femoris (active muscle during exercise) but not in adductor magnus (inactive muscle), reflecting the fact that the local increase in perfusion with both groups showed a maximum value in the second post‐exercise time‐point. A significantly greater increase in perfusion from the baseline (p < 0.05) was observed in the younger group (37 ± 12.05%) compared with the older group (17.57 ± 15.92%) at the first post‐exercise measurement. This work establishes a reliable non‐invasive method that can be used to study the effects of aging on dynamic changes in muscle perfusion as they relate to important measures of physical function.     

Triggered intravoxel incoherent motion MRI for the assessment of calf muscle perfusion during isometric intermittent exercise

The main aim of this paper was to propose triggered intravoxel incoherent motion (IVIM) imaging sequences for the evaluation of perfusion changes in calf muscles before, during and after isometric intermittent exercise. Twelve healthy volunteers were involved in the study. The subjects were asked to perform intermittent isometric plantar flexions inside the MRI bore. MRI of the calf muscles was performed on a 3.0 T scanner and diffusion‐weighted (DW) images were obtained using eight different b values (0 to 500 s/mm²). Acquisitions were performed at rest, during exercise and in the subsequent recovery phase. A motion‐triggered echo‐planar imaging DW sequence was implemented to avoid movement artifacts. Image quality was evaluated using the average edge strength (AES) as a quantitative metric to assess the motion artifact effect. IVIM parameters (diffusion D, perfusion fraction f and pseudo‐diffusion D*) were estimated using a segmented fitting approach and evaluated in gastrocnemius and soleus muscles. No differences were observed in quality of IVIM images between resting state and triggered exercise, whereas the non‐triggered images acquired during exercise had a significantly lower value of AES (reduction of more than 20%). The isometric intermittent plantar‐flexion exercise induced an increase of all IVIM parameters (D by 10%; f by 90%; D* by 124%; fD* by 260%), in agreement with the increased muscle perfusion occurring during exercise. Finally, IVIM parameters reverted to the resting values within 3 min during the recovery phase. In conclusion, the IVIM approach, if properly adapted using motion‐triggered sequences, seems to be a promising method to investigate muscle perfusion during isometric exercise.     

Reliable estimation of brain intravoxel incoherent motion parameters using denoised diffusion‐weighted MRI

In this study, we evaluate whether diffusion‐weighted magnetic resonance imaging (DW‐MRI) data after denoising can provide a reliable estimation of brain intravoxel incoherent motion (IVIM) perfusion parameters. Brain DW‐MRI was performed in five healthy volunteers on a 3 T clinical scanner with 12 different b‐values ranging from 0 to 1000 s/mm². DW‐MRI data denoised using the proposed method were fitted with a biexponential model to extract perfusion fraction (PF), diffusion coefficient (D) and pseudo‐diffusion coefficient (D*). To further evaluate the accuracy and precision of parameter estimation, IVIM parametric images obtained from one volunteer were used to resimulate the DW‐MRI data using the biexponential model with the same b‐values. Rician noise was added to generate DW‐MRI data with various signal‐to‐noise ratio (SNR) levels. The experimental results showed that the denoised DW‐MRI data yielded precise estimates for all IVIM parameters. We also found that IVIM parameters were significantly different between gray matter and white matter (P < 0.05), except for D* (P = 0.6). Our simulation results show that the proposed image denoising method displays good performance in estimating IVIM parameters (both bias and coefficient of variation were <12% for PF, D and D*) in the presence of different levels of simulated Rician noise (SNR_b=0 = 20‐40). Simulations and experiments show that brain DW‐MRI data after denoising can provide a reliable estimation of IVIM parameters.     

Demonstration of asymmetric muscle perfusion of the back after exercise in patients with adolescent idiopathic scoliosis using intravoxel incoherent motion (IVIM) MRI

The purpose of this work was to quantify muscular perfusion patterns of back muscles after exercise in patients with adolescent idiopathic scoliosis (AIS) using intravoxel incoherent motion (IVIM) MR perfusion imaging. The paraspinal muscles of eight patients with AIS (Cobb angle 35 ± 10°, range [25‐47°]) and nine healthy volunteers were scanned with a 1.5 T MRI, at rest and after performing a symmetric back muscle exercise on a Roman chair. An IVIM sequence with 16 b‐values from 0 to 900 s/mm² was acquired, and the IVIM bi‐exponential signal equation model was fitted in two steps. Perfusion asymmetries were evaluated using the blood flow related IVIM fD* parameter in regions of interest placed within the paraspinal muscles. Statistical significance was assessed using a Student t‐test. The observed perfusion pattern after performing a Roman chair muscle exercise differed consistently in patients with AIS compared with healthy normal volunteers, and consisted of an asymmetrical increase in IVIM fD* [10^?3 mm²/s] above the lumbar convexity from 6.5 ± 5.8 to 28.8 ± 26.8 (p < 0.005), with no increase in the concavity (decrease from 6.5 ± 10.0 to 3.2 ± 1.5 (p = 0.19)), compared with a bilateral symmetric increase in the healthy volunteers (right, increase from 3.3 ± 2.1 to 10.1 ± 4.6 (p < 0.05); left, 6.7 ± 10.7 to 13.3 ± 7.0 (p < 0.05)). In conclusion, patients with AIS exhibit significant asymmetric muscle perfusion over the convexity of the scoliotic curvature after Roman chair exercise.     

Diffusion parameter mapping with the combined intravoxel incoherent motion and kurtosis model using artificial neural networks at 3 T

Artificial neural networks (ANNs) were used for voxel‐wise parameter estimation with the combined intravoxel incoherent motion (IVIM) and kurtosis model facilitating robust diffusion parameter mapping in the human brain. The proposed ANN approach was compared with conventional least‐squares regression (LSR) and state‐of‐the‐art multi‐step fitting (LSR‐MS) in Monte‐Carlo simulations and in vivo in terms of estimation accuracy and precision, number of outliers and sensitivity in the distinction between grey (GM) and white (WM) matter. Both the proposed ANN approach and LSR‐MS yielded visually increased parameter map quality. Estimations of all parameters (perfusion fraction f, diffusion coefficient D, pseudo‐diffusion coefficient D*, kurtosis K) were in good agreement with the literature using ANN, whereas LSR‐MS resulted in D* overestimation and LSR yielded increased values for f and D*, as well as decreased values for K. Using ANN, outliers were reduced for the parameters f (ANN, 1%; LSR‐MS, 19%; LSR, 8%), D* (ANN, 21%; LSR‐MS, 25%; LSR, 23%) and K (ANN, 0%; LSR‐MS, 0%; LSR, 15%). Moreover, ANN enabled significant distinction between GM and WM based on all parameters, whereas LSR facilitated this distinction only based on D and LSR‐MS on f, D and K. Overall, the proposed ANN approach was found to be superior to conventional LSR, posing a powerful alternative to the state‐of‐the‐art method LSR‐MS with several advantages in the estimation of IVIM–kurtosis parameters, which might facilitate increased applicability of enhanced diffusion models at clinical scan times.     

Treatment response monitoring in patients with gastrointestinal stromal tumor using diffusion‐weighted imaging: preliminary results in comparison with positron emission tomography/computed tomography

We compared the parameters derived from diffusion‐weighted imaging (DWI) and positron emission tomography/computed tomography (PET/CT) for treatment response evaluation and response prediction in patients with gastrointestinal stromal tumor (GIST). Seven patients with histologically proven metastatic disease were enrolled. DWI and PET/CT data were collected from all patients at diagnosis and from six at follow‐up. All 37 lesions were identifiable in DWI with a sensitivity of 100%. To achieve higher accuracy, we used the apparent diffusion coefficient (ADC) of liver and background noise as thresholds for the measurement of the ADCs of lesions. Significant inverse correlations were found between ADC_{mean_thr} (ADC_mean with thresholds) and SUV_mean (mean standardized uptake value) (R² = 0.523, p < 0.001 at diagnosis, and R² = 0.916, p < 0.001 at follow‐up), between ADC_{mean_thr} and SUV_max (maximum SUV) (R² = 0.529, p < 0.001 at diagnosis, and R² = 0.761, p < 0.001 at follow‐up), between ΔADC_{mean_thr} (percentage change in ADC_{mean_thr}) and ΔSUV_mean (percentage change in SUV_mean) (R² = 0.384, p < 0.001), and between ΔADC_{mean_thr} and ΔSUV_max (percentage change in SUV_max) (R² = 0.500, p < 0.001). In lesion‐based analysis, pre‐treatment ADC_{mean_thr} outperformed SUV_mean and SUV_max in treatment response prediction, with an area under the receiver operating characteristic curve of 0.706. These results show that DWI can provide a quantitative assessment comparable with PET/CT in GIST lesion characterization, treatment response evaluation and response prediction. Copyright © 2012 John Wiley & Sons, Ltd.     

Pattern recognition analysis of directional intravoxel incoherent motion MRI in ischemic rodent brains

This study aimed to demonstrate a reliable automatic segmentation method for independently separating reduced diffusion and decreased perfusion areas in ischemic stroke brains using constrained nonnegative matrix factorization (cNMF) pattern recognition in directional intravoxel incoherent motion MRI (IVIM‐MRI). First, the feasibility of cNMF‐based segmentation of IVIM signals was investigated in both simulations and in vivo experiments. The cNMF analysis was independently performed for S₀‐normalized and scaled (by the difference between the maximum and minimum) IVIM signals, respectively. Segmentations of reduced diffusion (from S₀‐normalized IVIM signals) and decreased perfusion (from scaled IVIM signals) areas were performed using the corresponding cNMF pattern weight maps. Second, Monte Carlo simulations were performed for directional IVIM signals to investigate the relationship between the degree of vessel alignment and the direction of the diffusion gradient. Third, directional IVIM‐MRI experiments (x, y and z diffusion‐gradient directions, 20 b values at 7 T) were performed for normal (n = 4), sacrificed (n = 1, no flow) and ischemic stroke models (n = 4, locally reduced flow). The results showed that automatic segmentation of the hypoperfused lesion using cNMF analysis was more accurate than segmentation using the conventional double‐exponential fitting. Consistent with the simulation, the double‐exponential pattern of the IVIM signals was particularly strong in white matter and ventricle regions when the directional flows were aligned with the applied diffusion‐gradient directions. cNMF analysis of directional IVIM signals allowed robust automated segmentation of white matter, ventricle, vascular and hypoperfused regions in the ischemic brain. In conclusion, directional IVIM signals were simultaneously sensitive to diffusion and aligned flow and were particularly useful for automatically segmenting ischemic lesions via cNMF‐based pattern recognition.     

Dynamic intravoxel incoherent motion imaging of skeletal muscle at rest and after exercise

The purpose of this work was to demonstrate the feasibility of intravoxel incoherent motion imaging (IVIM) for non‐invasive quantification of perfusion and diffusion effects in skeletal muscle at rest and following exercise. After IRB approval, eight healthy volunteers underwent diffusion‐weighted MRI of the forearm at 3 T and eight different b values between 0 and 500 s/mm² with a temporal resolution of 57 s per dataset. Dynamic images were acquired before and after a standardized handgrip exercise. Diffusion (D) and pseudodiffusion (D*) coefficients as well as the perfusion fraction (F_P) were measured in regions of interest in the flexor digitorum superficialis and profundus (FDS/FDP), brachioradialis, and extensor carpi radialis longus and brevis muscles by using a multi‐step bi‐exponential analysis in MATLAB. Parametrical maps were calculated voxel‐wise. Differences in D, D*, and F_P between muscle groups and between time points were calculated using a repeated measures analysis of variance with post hoc Bonferroni tests. Mean values and standard deviations at rest were the following: D*, 28.5 ± 11.4 × 10^?3 mm²/s; F_P, 0.03 ± 0.01; D, 1.45 ± 0.09 × 10^?3 mm²/s. Changes of IVIM parameters were clearly visible on the parametrical maps. In the FDS/FDP, D* increased by 289 ± 236% (p < 0.029), F_P by 138 ± 58% (p < 0.01), and D by 17 ± 9% (p < 0.01). A significant increase of IVIM parameters could also be detected in the brachioradialis muscle, which however was significantly lower than in the FDS/FDP. After 20 min, all parameters were still significantly elevated in the FDS/FDP but not in the brachioradialis muscle compared with the resting state. The IVIM approach allows simultaneous quantification of muscle perfusion and diffusion effects at rest and following exercise. It may thus provide a useful alternative to other non‐invasive methods such as arterial spin labeling. Possible fields of interest for this technique include perfusion‐related muscle diseases, such as peripheral arterial occlusive disease. Copyright © 2014 John Wiley & Sons, Ltd.     

An intravoxel oriented flow model for diffusion‐weighted imaging of the kidney

By combining intravoxel incoherent motion (IVIM) and diffusion tensor imaging (DTI) we introduce a new diffusion model called intravoxel oriented flow (IVOF) that accounts for anisotropy of diffusion and the flow‐related signal. An IVOF model using a simplified apparent flow fraction tensor (IVOF_f) is applied to diffusion‐weighted imaging of human kidneys. The kidneys of 13 healthy volunteers were examined on a 3 T scanner. Diffusion‐weighted images were acquired with six b values between 0 and 800 s/mm² and 30 diffusion directions. Diffusivity and flow fraction were calculated for different diffusion models. The Akaike information criterion was used to compare the model fit of the proposed IVOF_f model to IVIM and DTI. In the majority of voxels the proposed IVOF_f model with a simplified apparent flow fraction tensor performs better than IVIM and DTI. Mean diffusivity is significantly higher in DTI compared with models that account for the flow‐related signal. The fractional anisotropy of diffusion is significantly reduced when flow fraction is considered to be anisotropic. Anisotropy of the apparent flow fraction tensor is significantly higher in the renal medulla than in the cortex region. The IVOF_f model describes diffusion‐weighted data in the human kidney more accurately than IVIM or DTI. The apparent flow fraction in the kidney proved to be anisotropic.     

Multi‐compartmental diffusion characterization of the human cervical spinal cord in vivo using the spherical mean technique

The purpose of this work was to evaluate the feasibility and reproducibility of the spherical mean technique (SMT), a multi‐compartmental diffusion model, in the spinal cord of healthy controls, and to assess its ability to improve spinal cord characterization in multiple sclerosis (MS) patients at 3 T. SMT was applied in the cervical spinal cord of eight controls and six relapsing‐remitting MS patients. SMT provides an elegant framework to model the apparent axonal volume fraction v_ax, intrinsic diffusivity D_ax, and extra‐axonal transverse diffusivity D_{ex_perp} (which is estimated as a function of v_ax and D_ax) without confounds related to complex fiber orientation distribution that reside in diffusion MRI modeling. SMT's reproducibility was assessed with two different scans within a month, and SMT‐derived indices in healthy and MS cohorts were compared. The influence of acquisition scheme on SMT was also evaluated. SMT's v_ax, D_ax, and D_{ex_perp} measurements all showed high reproducibility. A decrease in v_ax was observed at the site of lesions and normal appearing white matter (p < 0.05), and trends towards a decreased D_ax and increased D_{ex_perp} were seen. Importantly, a twofold reduction in acquisition yielded similarly high accuracy with SMT. SMT provides a fast, reproducible, and accurate method to improve characterization of the cervical spinal cord, and may have clinical potential for MS patients.     

VERDICT MRI for radiation treatment response assessment in neuroendocrine tumors

Noninvasive methods to study changes in tumor microstructure enable early assessment of treatment response and thus facilitate personalized treatment. The aim of this study was to evaluate the diffusion MRI model, Vascular, Extracellular and Restricted Diffusion for Cytometry in Tumors (VERDICT), for early response assessment to external radiation treatment and to compare the results with those of more studied sets of parameters derived from diffusion-weighted MRI data. Mice xenografted with human small intestine tumors were treated with external radiation treatment, and diffusion MRI experiments were performed on the day before and up to 2 weeks after treatment. The diffusion models VERDICT, ADC, IVIM, and DKI were fitted to MRI data, and the treatment response of each tumor was calculated based on pretreatment tumor growth and post-treatment tumor volume regression. Linear regression and correlation analysis were used to evaluate each model and their respective parameters for explaining the treatment response. VERDICT analysis showed significant changes from day −1 to day 3 for the intracellular and extracellular volume fraction, as well as the cell radius index (p < 0.05; Wilcoxon signed-rank test). The strongest correlation between the diffusion model parameters and the tumor treatment response was seen for the ADC, kurtosis-corrected diffusion coefficient, and intracellular volume fraction on day 3 (τ = 0.47, 0.52, and −0.49, respectively, p < 0.05; Kendall rank correlation coefficient). Of all the tested models, VERDICT held the strongest explanatory value for the tumor treatment response on day 3 (R² = 0.75, p < 0.01; linear regression). In conclusion, VERDICT has potential for early assessment of external radiation treatment and may provide further insights into the underlying biological effects of radiation on tumor tissue. In addition, the results suggest that the time window for assessment of treatment response using dMRI may be narrow.     

Prediction of pathologic response to neoadjuvant chemotherapy in patients with breast cancer using diffusion‐weighted imaging and MRS

The aim of this study was to determine whether tumor size, MRS parameters and apparent diffusion coefficient (ADC) measurements could be applied to predict pathologic complete response (pCR) after neoadjuvant chemotherapy (NAC). Ninety patients with breast cancer (median size, 4.5 cm; range, 1.6–9.5 cm) were evaluated with single‐voxel ¹H MRS and dynamic contrast‐enhanced MRI. Diffusion‐weighted imaging was performed in 41 of these patients using a 1.5‐T scanner before and after completion of NAC. Pre‐ and post‐treatment measurements and changes in tumor size, MRS parameters [absolute and normalized total choline‐containing compound (tCho) integral and tCho signal‐to‐noise ratio (SNR)] and ADCs in pCR versus non‐pCR were compared using the nonparametric Mann–Whitney test. Receiver operating characteristic (ROC) curve analysis was performed to assess the diagnostic performance of each parameter. After NAC, 30 patients (33%) showed pCR and 60 (67%) showed non‐pCR. At pretreatment, ADC was the only significant parameter in differentiating between pCR and non‐pCR [(0.83 ± 0.05) × 10^–3 versus (0.97 ± 0.14) × 10^–3 mm²/s] (p = 0.014). Post‐treatment measurements after completion of NAC and changes in tumor size (both p < 0.001), MRS parameters (p = 0.027 and p = 0.020 for absolute tCho integral, p = 0.036 and p = 0.023 for normalized tCho integral, and p = 0.032 and p = 0.061 for tCho SNR) and ADC (p = 0.003 and p < 0.001) were significantly different between the pCR and non‐pCR groups, except for changes in tCho SNR. In ROC analysis, the areas under the ROC curve (AUCs) of 0.63–0.73 were obtained for tumor size and MRS parameters. AUCs for pre‐ and post‐treatment ADC and changes in ADC were 0.75, 0.80 and 0.96, respectively. The optimal cut‐off of the percentage change in ADC for predicting pCR was 40.7%, yielding 100% sensitivity and 91% specificity. Patients with pCR showed significantly lower pretreatment ADCs than those with non‐pCR. The change in ADC after NAC was the most accurate predictor of pCR. Copyright © 2012 John Wiley & Sons, Ltd.