Voxel-based analysis of age and gender effects on striatal [123I] FP-CIT binding in healthy Japanese adults

Annals of Nuclear Medicine - Although previous studies have investigated age and gender effects on striatal subregional dopamine transporter (DaT) binding, these studies were mostly based on a...     

Application of a Machine Learning Algorithm for Structural Brain Images in Chronic Schizophrenia to Earlier Clinical Stages of Psychosis and Autism Spectrum Disorder: A Multiprotocol Imaging Dataset Study

Background and HypothesisMachine learning approaches using structural magnetic resonance imaging (MRI) can be informative for disease classification; however, their applicability to earlier clinical stages of psychosis and other disease spectra is unknown. We evaluated whether a model differentiating patients with chronic schizophrenia (ChSZ) from healthy controls (HCs) could be applied to earlier clinical stages such as first-episode psychosis (FEP), ultra-high risk for psychosis (UHR), and autism spectrum disorders (ASDs).Study DesignTotal 359 T1-weighted MRI scans, including 154 individuals with schizophrenia spectrum (UHR, n = 37; FEP, n = 24; and ChSZ, n = 93), 64 with ASD, and 141 HCs, were obtained using three acquisition protocols. Of these, data regarding ChSZ (n = 75) and HC (n = 101) from two protocols were used to build a classifier (training dataset). The remainder was used to evaluate the classifier (test, independent confirmatory, and independent group datasets). Scanner and protocol effects were diminished using ComBat.Study ResultsThe accuracy of the classifier for the test and independent confirmatory datasets were 75% and 76%, respectively. The bilateral pallidum and inferior frontal gyrus pars triangularis strongly contributed to classifying ChSZ. Schizophrenia spectrum individuals were more likely to be classified as ChSZ compared to ASD (classification rate to ChSZ: UHR, 41%; FEP, 54%; ChSZ, 70%; ASD, 19%; HC, 21%).ConclusionWe built a classifier from multiple protocol structural brain images applicable to independent samples from different clinical stages and spectra. The predictive information of the classifier could be useful for applying neuroimaging techniques to clinical differential diagnosis and predicting disease onset earlier.     

Whole brain analyses of age-related microstructural changes quantified using different diffusional magnetic resonance imaging methods

Purpose

The new diffusional magnetic resonance imaging (dMRI) techniques, diffusional kurtosis imaging (DKI) and neurite orientation dispersion and density imaging (NODDI) have been developed to clarify the microstructural changes. To our knowledge, however, there is little information on the similarities and differences of these metrics evaluated by the image-by-image paired t test.

Materials and methods

Twenty-three healthy subjects underwent dMRI. We estimated the relationships of these metrics evaluated by the image-by-image paired t-test and compared aging effects on each metric.

Results

We found that fractional anisotropy (FA), mean kurtosis (MK) derived from DKI and neurite density index (NDI) values derived from NODDI correlated with each other positively, and mean diffusivity (MD) and orientation dispersion index (ODI) values from NODDI correlated negatively with the FA value. There were no significant relationships of age with FA or MD values, while MK, ODI and NDI values showed significant correlations with age.

Conclusion

These results may indicate not only the similar tendency among the metrics, but also the higher sensitivity of NODDI and DKI to the changes in microstructural tissue organization with advancing age. These techniques could shed light on both normal and degenerated brain changes.

     

Intraventricular temperature measured by diffusion‐weighted imaging compared with brain parenchymal temperature measured by MRS in vivo

We examined and compared the temperatures of the intraventricular cerebrospinal fluid (T_v) and the brain parenchyma (T_p) using MRI, with reference to the tympanic membrane temperature (T_t) in healthy subjects. We estimated T_v and T_p values from data gathered simultaneously by MR diffusion‐weighted imaging (DWI) and MRS, respectively, in 35 healthy volunteers (17 males, 18 females; age 25–78 years). We also obtained T_t values just before each MR examination to evaluate the relationships among the three temperatures. There were significant positive correlations between T_v and T_p (R = 0.611, p < 0.001). The correlation was also significant after correction for T_t (R = 0.642, p < 0.001). There was no significant correlation between T_v and T_t or between T_p and T_t in the men or the women. Negative correlations were found between T_v and age and between T_p and age in the males but not females. DWI thermometry seems to reflect the intracranial environment as accurately as MRS thermometry. An age‐dependent decline in temperature was evident in our male subjects by both DWI and MRS thermometry, probably due to the decrease in cerebral metabolism with age. Copyright © 2016 John Wiley & Sons, Ltd.     

Comparison of traveling‐subject and ComBat harmonization methods for assessing structural brain characteristics

Multisite magnetic resonance imaging (MRI) is increasingly used in clinical research and development. Measurement biases—caused by site differences in scanner/image‐acquisition protocols—negatively influence the reliability and reproducibility of image‐analysis methods. Harmonization can reduce bias and improve the reproducibility of multisite datasets. Herein, a traveling‐subject (TS) dataset including 56 T1‐weighted MRI scans of 20 healthy participants in three different MRI procedures—20, 19, and 17 subjects in Procedures 1, 2, and 3, respectively—was considered to compare the reproducibility of TS‐GLM, ComBat, and TS‐ComBat harmonization methods. The minimum participant count required for harmonization was determined, and the Cohen''s d between different MRI procedures was evaluated as a measurement‐bias indicator. The measurement‐bias reduction realized with different methods was evaluated by comparing test–retest scans for 20 healthy participants. Moreover, the minimum subject count for harmonization was determined by comparing test–retest datasets. The results revealed that TS‐GLM and TS‐ComBat reduced measurement bias by up to 85 and 81.3%, respectively. Meanwhile, ComBat showed a reduction of only 59.0%. At least 6 TSs were required to harmonize data obtained from different MRI scanners, complying with the imaging protocol predetermined for multisite investigations and operated with similar scan parameters. The results indicate that TS‐based harmonization outperforms ComBat for measurement‐bias reduction and is optimal for MRI data in well‐prepared multisite investigations. One drawback is the small sample size used, potentially limiting the applicability of ComBat. Investigation on the number of subjects needed for a large‐scale study is an interesting future problem.     

Serial MRI alterations of pediatric patients with beta-propeller protein associated neurodegeneration (BPAN)

Background and PurposeBeta-propeller protein-associated neurodegeneration (BPAN) is one subtype of neurodegeneration with brain iron accumulation. It is difficult to diagnose BPAN due to the non-specificity of their clinical findings and neuroimaging in early childhood. We experienced four pediatric patients with serial brain MRI and evaluated the alteration of the findings through their course.MethodsWe retrospectively reviewed the clinical findings and 21 MRI findings of the four patients with genetically confirmed pediatric BPAN. We also performed a quantitative MR assessment using the quantitative susceptibility mapping (QSM) values of the globus pallidus (GP), substantia nigra (SN), and deep cerebellar nuclei (DCN) compared to 10 age-matched disease controls.ResultsOnly one patient was suspected of BPAN based on imaging findings before the genetic diagnosis was made. The other three patients could not be suspected until their Whole-exome sequencings (WES) done. In all four cases, no abnormal signals were noted in the GP and SN at the initial brain MRI, but hypointensities were observed after the ages of 4–7 years on T2-weighted images and after the ages of 2–7 years on susceptibility-weighted images. In three patients, T2 hyperintensity in the bilateral DCN was persistently observed throughout the observational period. Three patients showed transient T2 hyperintensity and swelling in the GP, SN and/or DCN during the episodes of pyrexia and seizures. The other findings included cerebral and cerebellar atrophy, thinning of the corpus callosum, and delayed myelination. The QSM values of the GP and SN were significantly higher in the patients compared to the controls (P = 0.005, respectively), but that of the DCN did not differ significantly (P = 0.16).ConclusionBrain MRI is a useful method to establish the early diagnosis of BPAN.     

Recent Advances and Future Directions in Brain MR Imaging Studies in Schizophrenia: Toward Elucidating Brain Pathology and Developing Clinical Tools

Schizophrenia is a common severe psychiatric disorder that affects approximately 1% of general population through the life course. Historically, in Kraepelin’s time, schizophrenia was a disease unit conceptualized as dementia praecox; however, since then, the disease concept has changed. Recent MRI studies had shown that the neuropathology of the brain in this disorder was characterized by mild progression before and after the onset of the disease, and that the brain alterations were relatively smaller than assumed. Although genetic factors contribute to the brain alterations in schizophrenia, which are thought to be trait differences, other changes include factors that are common in psychiatric diseases. Furthermore, it has been shown that the brain differences specific to schizophrenia were relatively small compared to other changes, such as those caused by brain development, aging, and gender. In addition, compared to the disease and participant factors, machine and imaging protocol differences could affect MRI signals, which should be addressed in multi-site studies. Recent advances in MRI modalities, such as multi-shell diffusion-weighted imaging, magnetic resonance spectroscopy, and multimodal brain imaging analysis, may be candidates to sharpen the characterization of schizophrenia-specific factors and provide new insights. The Brain/MINDS Beyond Human Brain MRI (BMB-HBM) project has been launched considering the differences and noises irrespective of the disease pathologies and includes the future perspectives of MRI studies for various psychiatric and neurological disorders. The sites use restricted MRI machines and harmonized multi-modal protocols, standardized image preprocessing, and traveling subject harmonization. Data sharing to the public will be planned in FY 2024. In the future, we believe that combining a high-quality human MRI dataset with genetic data, randomized controlled trials, and MRI for non-human primates and animal models will enable us to understand schizophrenia, elucidate its neural bases and therapeutic targets, and provide tools for clinical application at bedside.     

Altered coupling of regional cerebral blood flow and brain temperature in schizophrenia compared with bipolar disorder and healthy subjects

Previous studies have suggested that schizophrenia patients have dysfunctional thermoregulation. The aim of this study was to examine whether brain temperature (BT) in schizophrenia patients differs from that in patients with bipolar disorder and healthy subjects by using magnetic resonance imaging. We also evaluated the possible relationship between BT and cerebral blood flow (CBF). We analyzed the temperature of lateral ventricles as the mean BT using diffusion-weighted imaging (DWI) thermometry, and evaluated the relationships between the BT and the CBF using pseudo-continuous arterial spin labeling (pCASL) among 3 diagnostic groups, 22 male patients with schizophrenia, 19 male patients with bipolar disorder, and 23 healthy male subjects. There were significant positive correlations between BT in the lateral ventricles and CBF in both the patients with bipolar disorder and healthy subjects. By contrast, there were significant negative correlations in patients with schizophrenia. We could not detect the significant difference in the surrogates of BT among three diagnostic groups. We showed that patients with schizophrenia, but not those with bipolar disorder, have dysfunctional thermoregulation in the brain. Brain temperature is highly dependent on cerebral metabolism and CBF, and thus uncoupling of cerebral metabolism and CBF may occur in schizophrenics.