High-resolution MRI Images Research Articles

Correlations between the trigeminal nerve microstructural changes and the trigeminal-pontine angle features.

Morphological and microstructural changes of the trigeminal nerve due to neurovascular compression (NVC) have been reported in primary trigeminal neuralgia (PTN) patients. This investigation was to examine the relationship between the trigeminal-pontine angle and nerve microstructural changes. Twenty-five patients underwent microvascular decompression (MVD) for trigeminal neuralgia, and 25 age- and sex-matched controls were studied. The two groups underwent high-resolution three-dimensional MRI and diffusion tensor imaging (DTI). Bilateral trigeminal-pontine angle, cross-sectional area of cerebellopontine angle (CPA) cistern, and the length of trigeminal nerve were evaluated. The mean values of fractional anisotropy and apparent diffusion coefficient at the site of NVC were also measured. Correlation analyses were performed for the trigeminal-pontine angle and the diffusion metrics (FA and ADC) in PTN patients. The mean trigeminal-pontine angle and FA value on the affected side was significantly smaller than the unaffected side and the control group (p < 0.001), while the mean ADC value was significantly increased (p < 0.01). When taking the conflicting vessel types into consideration, the angle affected by the superior cerebellar artery (SCA) was statistically sharper than when affected by other vessels (p < 0.01). However, there were no significant changes in the area of the CPA cistern or the length of the trigeminal nerve between the groups. Correlation analyses showed that the trigeminal-pontine angle was positively correlated with FA and negatively correlated with ADC. A sharp trigeminal-pontine angle may increase the chance of NVC and exacerbate nerve degeneration, which may be one of the supplementary factors that contribute to the pathogenesis of trigeminal neuralgia.

Does Meningioma Volume Correlate With Clinical Disease Manifestation Irrespective of Histopathologic Tumor Grade?

The aim of the study was to investigate the association between meningioma volume and the occurrence of clinic-radiologic signs of tumor aggressiveness. For volumetric approximation, the authors evaluated the method of semiautomatic image segmentation at hand of high-resolution MRI-image sequences. ITK-SNAP was utilized for semiautomatic image segmentation of 58 gadolinium-contrast enhanced T1-weighted thin-slice MRI datasets for volumetric analysis. Furthermore, multimodal imaging datasets (including T2, FLAIR, T1) were evaluated for radiological biomarkers of aggressiveness and growth potential. Thereby generated data was checked for association with retrospectively collected data points. Location (P = 0.001), clinical disease manifestation (P = 0.033), peritumoral edema (P = 0.038), tumor intrinsic cystic degeneration (P = 0.007), three-dimensional complexity (P = 0.022), and the presence of meningioma mass effect (P = 0.001) were statistically associated with higher tumor volumes. There was no association between higher tumor volumes and histopathological tumor grade. The size of a meningioma does not seem to reliably predict tumor grade. Growth potential seems to be influenced by tumor location. Higher tumor volumes were significantly associated with the occurrence of clinical symptoms.

Learning from cases: Analysis of two cases of craniopharyngioma from the 19 th to the 21 st centuries.

This manuscript describes the study of two cases of craniopharyngioma, which have been examined repeatedly over three separate centuries. This includes analysis by Josef Engel in 1839, who sought to uncover the physiological role of the pituitary gland; Jacob Erdheim in 1904, who initially described the disease we now call craniopharyngioma, and recent high resolution MRI and micro-CT imaging and attempted DNA analyses of the tumours. The cases highlight how, rightly or wrongly, our interpretation of data is shaped by the technologies, methodologies and prevailing theories of a given time.

Learning from cases: Analysis of two cases of craniopharyngioma from the 19 th to the 21 st centuries.

This manuscript describes the study of two cases of craniopharyngioma, which have been examined repeatedly over three separate centuries. This includes analysis by Josef Engel in 1839, who sought to uncover the physiological role of the pituitary gland; Jacob Erdheim in 1904, who initially described the disease we now call craniopharyngioma, and recent high resolution MRI and micro-CT imaging and attempted DNA analyses of the tumours. The cases highlight how, rightly or wrongly, our interpretation of data is shaped by the technologies, methodologies and prevailing theories of a given time.

Accuracy of high resolution MRI in measurement of vascular stenosis ratio in atherosclerotic middle cerebral artery

Objective To evaluate the accuracy of measurements of atherosclerotic middle cerebral artery (MCA) stenosis with 3.0 T high-resolution magnetic resonance imaging (HR-MRI). Methods Forty patients with symptomatic atherosclerotic stenosis of middle cerebral artery (MCA) confirmed by digital subtraction angiography (DSA) in the Affiliated Hospital of Binzhou Medical College from September 2017 to May 2018 were enrolled in the study. Patients were scanned by HR-MRI sequence (including T1WI, T2WI, PDWI). The MCA M1 stenosis rate on HR-MR images was assessed by warfarin-aspirin symptomatic intracranial artery disease (WASID) method and area measurement algorithm, respectively, and based on the stenosis rate the degree of stenosis (semi-quantitative measurement) was determined. The accuracy of the two measurement methods was evaluated with DSA results as the gold standard. Results The HR-MRI images showed the structure of the vessel wall clearly in 30 patients meeting the measurement requirements. The inner edge of the vessel was clearly distinguishable and smooth, showing eccentric stenosis. The stenosis rate of MCA measured by DSA, WASID method and area measurement algorithm were (82±17)%, (70±12)%, (81±16)%, respectively (P>0.05). The result of area measurement algorithm was better correlated with DSA (r=0.893); and the coincidence of the stenosis degree rate of two measurement method was 90%(27/30). Conclusion The area measurement algorithm based on the HS-MRI has high accuracy in measuring the degree of MCA stenosis,which is of high clinical application value. Key words: Magnetic resonance imaging; Middle cerebral artery stenosis; Atherosclerosis

Diagnostic Accuracy of High-Resolution Black-Blood MRI in the Evaluation of Intracranial Large-Vessel Arterial Occlusions

3D high-resolution black-blood MRI or MR vessel wall imaging allows evaluation of the intracranial arterial wall and extraluminal pathology. We investigated the diagnostic accuracy and reliability of black-blood MRI for the intraluminal detection of large-vessel arterial occlusions. We retrospectively identified patients with intracranial arterial occlusions, confirmed by CTA or DSA, who also underwent 3D black-blood MRI with nonenhanced and contrast-enhanced T1 sampling perfection with application-optimized contrasts by using different flip angle evolution (T1 SPACE) sequences. Black-blood MRI findings were evaluated by 2 independent and blinded neuroradiologists. Large-vessel intracranial arterial segments were graded on a 3-point scale (grades 0-2) for intraluminal baseline T1 hyperintensity and contrast enhancement. Vessel segments were considered positive for arterial occlusion if focal weak (grade 1) or strong (grade 2) T1-hyperintense signal and/or enhancement replaced the normal intraluminal black-blood signal. Thirty-one patients with 38 intracranial arterial occlusions were studied. The median time interval between black-blood MRI and CTA/DSA reference standard studies was 2 days (range, 0-20 days). Interobserver agreement was good for T1 hyperintensity (κ = 0.63) and excellent for contrast enhancement (κ = 0.89). High sensitivity (100%) and specificity (99.8%) for intracranial arterial occlusion diagnosis was observed with either intraluminal T1 hyperintensity or contrast-enhancement imaging criteria on black-blood MRI. Strong grade 2 intraluminal enhancement was maintained in >80% of occlusions irrespective of location or chronicity. Relatively increased strong grade 2 intraluminal T1 hyperintensity was noted in chronic/incidental versus acute/subacute occlusions (45.5% versus 12.5%, P = .04). Black-blood MRI with or without contrast has high diagnostic accuracy and reliability in evaluating intracranial large-vessel arterial occlusions with near-equivalency to DSA and CTA.

The Clinical and Vascular Characteristics of RNF213 c.14576G>A Variant-Related Intracranial Major Artery Disease in China.

Background and Purpose Recently, several studies indicated the c.14576G>A variant on the ring finger protein 213 (RNF213), a founder variant of moyamoya diseases (MMD), was associated with non-MMD intracranial major artery stenosis/occlusion (non-MMD ICASO). We proposed that RNF213 variant-related ICASO including MMD might be a special entity with its own characteristics based on a genetic background. The aim of the study was to learn the clinical and vascular features of RNF213 variant-related ICASO. Moreover, we tried to explore the clinical significance of a testing variant in ICASO patients in China. Methods Clinical material and routine image data were collected in 160 Chinese patients with ICASO, including 41 verified MMD and 119 non-MMD. DNA samples were extracted, and the c.14576G>A variant on RNF213 was genotyped. Then, the clinical and vascular features were compared between the patients with and without a relevant variant. Furthermore, the patients with RNF213 mutation were performed with high resolution magnetic resonance imaging (HR-MRI) examination to conclude features of the artery wall. Results There were 16 (10%) patients (including 9 MMD and 7 non-MMD ICASO) presenting a heterozygous c.14576G>A variant while none of homozygote was found. Compared to the patients without the c.14576G>A variant, the variant group had more female, less symptomatic patients, and more possibility of having collateral vessels in vascular imaging. In the symptomatic subgroup, there is no significant difference in clinical presentation (p > 0.05) between two groups. However, RNF213 variant-related ICASO had lower scores in NIHSS (1.0 ± 3.0 vs. 3.9 ± 5.0, p < 0.05) but not in mRS. In the symptomatic subgroup, in addition, most of the HR-MRI images of variant ICASO (77.8%, 7 of 9) were characterized by a shrunken outer diameter, concentric thickening vessel wall, and collateral vessel structures on the stenotic portion, which was prone to be diagnosed as HR-MMD (a MMD diagnosis diagnosed by HR-MRI). The rest of the two variants showed a relatively eccentric luminal narrow, normal outer diameter without collateral vessel findings, identified as HR-ICAD (intracranial atherosclerotic disease diagnosed by HR-MRI). Conclusions Our study demonstrated that the c.14576G>A variant on RNF213 may be a biomarker to good outcome of ICASO in Chinese. The variant-related ICASO was characterized by both features of MMD and ICAD diagnosed by HR-MRI.

Super-Resolution of Brain MRI Images Using Overcomplete Dictionaries and Nonlocal Similarity

Recently, the Magnetic Resonance Imaging (MRI) images have limited and unsatisfactory resolutions due to various constraints such as physical, technological and economic considerations. Super-resolution techniques can obtain high-resolution MRI images. The traditional methods obtained the resolution enhancement of brain MRI by interpolations, affecting the accuracy of the following diagnose process. The requirement for brain image quality is fast increasing. In this paper, we propose an image super-resolution (SR) method based on overcomplete dictionaries and inherent similarity of an image to recover the high-resolution (HR) image from a single low-resolution (LR) image. We explore the nonlocal similarity of the image to tentatively search for similar blocks in the whole image and present a joint reconstruction method based on compressive sensing (CS) and similarity constraints. The sparsity and self-similarity of the image blocks are taken as the constraints. The proposed method is summarized in the following steps. First, a dictionary classification method based on the measurement domain is presented. The image blocks are classified into smooth, texture and edge parts by analyzing their features in the measurement domain. Then, the corresponding dictionaries are trained using the classified image blocks. Equally important, in the reconstruction part, we use the CS reconstruction method to recover the HR brain MRI image, considering both nonlocal similarity and the sparsity of an image as the constraints. This method performs better both visually and quantitatively than some existing methods.

Hippocampal subfields alterations in adolescents with post-traumatic stress disorder.

Reexperiencing symptoms in adolescent Post-Traumatic Stress Disorder (PTSD) are characterized by the apparition of vivid intrusive images of the traumatic event. The emergence of these intrusions is thought to be related to a deficiency in context processing and could then be related to hippocampal alterations. The hippocampus is a complex structure which can be divided into several subfields, namely, the Cornu Ammonis (CA1, CA2, and CA3), the subiculum, and the dentate gyrus (DG). As each subfield presents different histological characteristics and functions, it appears more relevant to consider hippocampal subfields, instead of only assessing the whole hippocampus, to understand the neurobiology of PTSD. Hence, this study presents the first investigation of structural alterations within hippocampal subfields and their links to reexperiencing symptoms in adolescent PTSD. Hippocampal subfields were manually delineated on high-resolution MRI images in 15 adolescents (13-18 years old) with PTSD and 24 age-matched healthy controls. The volume of the region CA2-3/DG region was significantly smaller in the PTSD group compared to controls in both hemispheres. No other significant difference was found for other subfields. Moreover, the volume of the left CA2-3/DG was negatively correlated with the intrusion score (as measured by the Impact of Events Scale-Revised) in the PTSD group. To conclude, an alteration in the hippocampal subregion CA2-3/DG, known to resolve interferences between new and similar stored memories, could participate in the apparition of intrusive trauma memories in adolescents with PTSD.

Support Vector Machine Classification of Obsessive-Compulsive Disorder Based on Whole-Brain Volumetry and Diffusion Tensor Imaging.

Magnetic resonance imaging (MRI) methods have been used to detect cerebral anatomical distinction between obsessive-compulsive disorder (OCD) patients and healthy controls (HC). Machine learning approach allows for the possibility of discriminating patients on the individual level. However, few studies have used this automatic technique based on multiple modalities to identify potential biomarkers of OCD. High-resolution structural MRI and diffusion tensor imaging (DTI) data were acquired from 48 OCD patients and 45 well-matched HC. Gray matter volume (GMV), white matter volume (WMV), fractional anisotropy (FA), and mean diffusivity (MD) were extracted as four features were examined using support vector machine (SVM). Ten brain regions of each feature contributed most to the classification were also estimated. Using different algorithms, the classifier achieved accuracies of 72.08, 61.29, 80.65, and 77.42% for GMV, WMV, FA, and MD, respectively. The most discriminative gray matter regions that contributed to the classification were mainly distributed in the orbitofronto-striatal “affective” circuit, the dorsolateral, prefronto-striatal “executive” circuit and the cerebellum. For WMV feature and the two feature sets of DTI, the shared regions contributed the most to the discrimination mainly included the uncinate fasciculus, the cingulum in the hippocampus, corticospinal tract, as well as cerebellar peduncle. Based on whole-brain volumetry and DTI images, SVM algorithm revealed high accuracies for distinguishing OCD patients from healthy subjects at the individual level. Computer-aided method is capable of providing accurate diagnostic information and might provide a new perspective for clinical diagnosis of OCD.

Simultaneous single- and multi-contrast super-resolution for brain MRI images based on a convolutional neural network

In magnetic resonance imaging (MRI), the acquired images are usually not of high enough resolution due to constraints such as long sampling times and patient comfort. High-resolution MRI images can be obtained by super-resolution techniques, which can be grouped into two categories: single-contrast super-resolution and multi-contrast super-resolution, where the former has no reference information, and the latter applies a high-resolution image of another modality as a reference. In this paper, we propose a deep convolutional neural network model, which performs single- and multi-contrast super-resolution reconstructions simultaneously. Experimental results on synthetic and real brain MRI images show that our convolutional neural network model outperforms state-of-the-art MRI super-resolution methods in terms of visual quality and objective quality criteria such as peak signal-to-noise ratio and structural similarity.

18F-FDG PET and high-resolution MRI co-registration for pre-surgical evaluation of patients with conventional MRI-negative refractory extra-temporal lobe epilepsy.

Epilepsy that originates outside of the temporal lobe can present some of the most challenging problems for surgical therapy, especially for patients with conventional magnetic resonance imaging (MRI)-negative refractory extra-temporal lobe epilepsy (ETLE). This study aimed to evaluate the clinical value of pre-surgical 18F-fluoro-deoxy-glucose positron emission tomography (18F-FDG PET) and high-resolution MRI (HR-MRI) co-registration in patients with conventional MRI-negative refractory ETLE, and compare their surgical outcomes. Sixty-seven patients with conventional MRI-negative refractory ETLE were prospectively included for pre-surgical 18F-FDG PET and HR-MRI examinations. Under the guidance of 18F-FDG PET and HR-MRI co-registration, HR-MRI images were re-read. Based on the image result changes from first reading to re-reading, patients were divided into three groups: Change-1 (lesions of subtle abnormality could be identified in re-read), Change-2 (non-specific abnormalities reported in the first reading were considered as lesions on HR-MRI re-read) and No-change. Post-surgical follow-ups were conducted for up to 59months. Visual analysis of 18F-FDG PET showed focal or regional abnormality in 46 patients (68.6%), while the abnormal rate increased to 94.0% (P < 0.05) by co-registration. Of the 67 patients, 46.3% of them were identified as Change-1, and 11.9% as Change-2 after co-registration and HR-MRI re-read. Patients with Change-1 and -2 were more likely to be recommended to receive surgical resection (P< 0.001). In the 17 post-surgical patients, 88% had good outcomes, whereas 11.7% had poor outcomes during our study period. Pre-surgical evaluation by co-registration of 18F-FDG PET and HR-MRI could improve the identification of the epileptogenic onset zone (EOZ), and may further guide the surgical decision-making and improve the outcome of the refractory ETLE with normal conventional MRI; therefore, it should be recommended as a standard procedure for pre-surgical evaluation of these patients.

FIIND: Ferret Interactive Integrated Neurodevelopment Atlas

The first days after birth in ferrets provide a privileged view of the development of a complex mammalian brain. Unlike mice, ferrets develop a rich pattern of deep neocortical folds and cortico- cortical connections. Unlike humans and other primates, whose brains are well differentiated and folded at birth, ferrets are born with a very immature and completely smooth neocortex: folds, neocortical regionalisation and cortico-cortical connectivity develop in ferrets during the first postnatal days. After a period of fast neocortical expansion, during which brain volume increases by up to a factor of 4 in 2 weeks, the ferret brain reaches its adult volume at about 6 weeks of age. Ferrets could thus become a major animal model to investigate the neurobiological correlates of the phenomena observed in human neuroimaging. Many of these phenomena, such as the relationship between brain folding, cortico-cortical connectivity and neocortical regionalisation cannot be investigated in mice, but could be investigated in ferrets. Our aim is to provide the research community with a detailed description of the development of a complex brain, necessary to better understand the nature of human neuroimaging data, create models of brain development, or analyse the relationship between multiple spatial scales. We have already started a project to constitute an open, collaborative atlas of ferret brain development, integrating multi-modal and multi-scale data. We have acquired data for 28 ferrets (4 animals per time point from P0 to adults), using high-resolution MRI and diffusion tensor imaging (DTI). We have developed an open-source pipeline to segment and produce – online – 3D reconstructions of brain MRI data. We propose to process the brains of 16 of our specimens (from P0 to P16) using high-throughput 3D histology, staining for cytoarchitectonic landmarks, neuronal progenitors and neurogenesis. This would allow us to relate the MRI data that we have already acquired with multi-dimensional cell-scale information. Brains will be sectioned at 25 μm, stained, scanned at 0.25 μm of resolution, and processed for real-time multi-scale visualisation. We will extend our current web-platform to integrate an interactive multi-scale visualisation of the data. Using our combined expertise in computational neuroanatomy, multi-modal neuroimaging, neuroinformatics, and the development of inter-species atlases, we propose to build an open-source web platform to allow the collaborative, online, creation of atlases of the development of the ferret brain. The web platform will allow researchers to access and visualise interactively the MRI and histology data. It will also allow researchers to create collaborative, human curated, 3D segmentations of brain structures, as well as vectorial atlases. Our work will provide a first integrated atlas of ferret brain development, and the basis for an open platform for the creation of collaborative multi-modal, multi-scale, multi-species atlases.

Radiofrequency-thermoablation: General principle, historical overview and modern applications for epilepsy

Stereotactically guided radiofrequency thermoablation (RFTA) for epilepsy has been frequently applied over the last 40 years. Radiofrequency electrodes with temperature control function generate a coagulation lesion with clearly defined borders. In combination with high-resolution MRI imaging, this technique allows minimally-invasive ablation of periventricular nodular heterotopias, small focal type II dysplasias, and hypothalamic hamartomas. This review summarises the literature addressing this topic mainly regarding technical aspects. In essence, RFTA is a safe treatment option for patients suffering from epileptogenic pathologies visible on MRI-images.

Synthesis of Realistic Simultaneous Positron Emission Tomography and Magnetic Resonance Imaging Data.

The investigation of the performance of different positron emission tomography (PET) reconstruction and motion compensation methods requires accurate and realistic representation of the anatomy and motion trajectories as observed in real subjects during acquisitions. The generation of well-controlled clinical datasets is difficult due to the many different clinical protocols, scanner specifications, patient sizes, and physiological variations. Alternatively, computational phantoms can be used to generate large data sets for different disease states, providing a ground truth. Several studies use registration of dynamic images to derive voxel deformations to create moving computational phantoms. These phantoms together with simulation software generate raw data. This paper proposes a method for the synthesis of dynamic PET data using a fast analytic method. This is achieved by incorporating realistic models of respiratory motion into a numerical phantom to generate datasets with continuous and variable motion with magnetic resonance imaging (MRI)-derived motion modeling and high resolution MRI images. In this paper, data sets for two different clinical traces are presented, 18F-FDG and 68Ga-PSMA. This approach incorporates realistic models of respiratory motion to generate temporally and spatially correlated MRI and PET data sets, as those expected to be obtained from simultaneous PET-MRI acquisitions.

The Influence of DAT1, COMT, and BDNF Genetic Polymorphisms on Total and Subregional Hippocampal Volumes in Early Onset Heavy Cannabis Users.

Introduction: Hippocampal neuroanatomy is affected by genetic variations in dopaminergic candidate genes and environmental insults, such as early onset of chronic cannabis exposure. Here, we examine how hippocampal total and subregional volumes are affected by cannabis use and functional polymorphisms of dopamine-relevant genes, including the catechol-O-methyltransferase (COMT), dopamine transporter (DAT1), and the brain-derived neurotrophic factor (BDNF) genes.Material and Methods: We manually traced total hippocampal volumes and automatically segmented hippocampal subregions using high-resolution MRI images, and performed COMT, DAT1, and BDNF genotyping in 59 male Caucasian young adults aged 18–30 years. These included 30 chronic cannabis users with early-onset (regular use at <16 years) and 29 age-, education-, and intelligence-matched controls.Results: Cannabis use and dopaminergic gene polymorphism had both distinct and interactive effects on the hippocampus. We found emerging alterations of hippocampal total and specific subregional volumes in cannabis users relative to controls (i.e., CA1, CA2/3, and CA4), and associations between cannabis use levels and total and specific subregional volumes. Furthermore, total hippocampal volume and the fissure subregion were affected by cannabis×DAT1 polymorphism (i.e., 9/9R and in 10/10R alleles), reflecting high and low levels of dopamine availability.Conclusion: These findings suggest that cannabis exposure alters the normal relationship between DAT1 polymorphism and the anatomy of total and subregional hippocampal volumes, and that specific hippocampal subregions may be particularly affected.

Spatial variation in high-frequency oscillation rates and amplitudes in intracranial EEG.

To assess the variation in baseline and seizure onset zone interictal high-frequency oscillation (HFO) rates and amplitudes across different anatomic brain regions in a large cohort of patients. Seventy patients who had wide-bandwidth (5 kHz) intracranial EEG (iEEG) recordings during surgical evaluation for drug-resistant epilepsy between 2005 and 2014 who had high-resolution MRI and CT imaging were identified. Discrete HFOs were identified in 2-hour segments of high-quality interictal iEEG data with an automated detector. Electrode locations were determined by coregistering the patient's preoperative MRI with an X-ray CT scan acquired immediately after electrode implantation and correcting electrode locations for postimplant brain shift. The anatomic locations of electrodes were determined using the Desikan-Killiany brain atlas via FreeSurfer. HFO rates and mean amplitudes were measured in seizure onset zone (SOZ) and non-SOZ electrodes, as determined by the clinical iEEG seizure recordings. To promote reproducible research, imaging and iEEG data are made freely available (msel.mayo.edu). Baseline (non-SOZ) HFO rates and amplitudes vary significantly in different brain structures, and between homologous structures in left and right hemispheres. While HFO rates and amplitudes were significantly higher in SOZ than non-SOZ electrodes when analyzed regardless of contact location, SOZ and non-SOZ HFO rates and amplitudes were not separable in some lobes and structures (e.g., frontal and temporal neocortex). The anatomic variation in SOZ and non-SOZ HFO rates and amplitudes suggests the need to assess interictal HFO activity relative to anatomically accurate normative standards when using HFOs for presurgical planning.

The Habenula's Role in Adaptive Behaviors: Contributions From Neuroimaging.

The Habenula's Role in Adaptive Behaviors: Contributions From Neuroimaging.

A digital 3D atlas of the marmoset brain based on multi-modal MRI

The common marmoset (Callithrix jacchus) is a New-World monkey of growing interest in neuroscience. Magnetic resonance imaging (MRI) is an essential tool to unveil the anatomical and functional organization of the marmoset brain. To facilitate identification of regions of interest, it is desirable to register MR images to an atlas of the brain. However, currently available atlases of the marmoset brain are mainly based on 2D histological data, which are difficult to apply to 3D imaging techniques. Here, we constructed a 3D digital atlas based on high-resolution ex-vivo MRI images, including magnetization transfer ratio (a T1-like contrast), T2w images, and multi-shell diffusion MRI. Based on the multi-modal MRI images, we manually delineated 54 cortical areas and 16 subcortical regions on one hemisphere of the brain (the core version). The 54 cortical areas were merged into 13 larger cortical regions according to their locations to yield a coarse version of the atlas, and also parcellated into 106 sub-regions using a connectivity-based parcellation method to produce a refined atlas. Finally, we compared the new atlas set with existing histology atlases and demonstrated its applications in connectome studies, and in resting state and stimulus-based fMRI. The atlas set has been integrated into the widely-distributed neuroimaging data analysis software AFNI and SUMA, providing a readily usable multi-modal template space with multi-level anatomical labels (including labels from the Paxinos atlas) that can facilitate various neuroimaging studies of marmosets.

Differential involvement of nigral subregions in idiopathic parkinson's disease.

In this study, the prevalence of abnormality in putative nigrosome 1 and nigrosome 4 (N1 and N4, respectively) was investigated in early versus late-stage idiopathic Parkinson's disease (IPD) patients. A total of 128 IPD patients (early stage[n = 89]; late stage[n = 39]) and 15 healthy subjects were scanned for high-resolution (0.5 × 0.5 × 1.0mm3 ) multiecho gradient-recalled echo MRI and dopamine transporter PET imaging. The MRI data were processed for susceptibility map-weighted imaging (SMWI) to improve a contrast-to-noise ratio, and the images were resliced at 0.5 mm to define N1 and N4. When each side of N1 and N4 was assessed separately for the loss of hyperintensity by two independent reviewers, the consensus review results showed that in early-stage IPD (178 substantia nigras [SNs]), the loss of hyperintensity was observed more often in only the N1 region (65.2%) when compared to in both N1 and N4 regions (34.8%). In late-stage IPD (78 SNs), on the other hand, the loss in only the N1 region (25.6%) was less prevalent than in both N1 and N4 (74.4%) (P < 0.0001). Additionally, intact SNs (both in N1 and N4) were observed 17 SNs (9.6%) of the early-stage IPD patients, whereas it was not found in any SNs of the late-stage IPD patients (P = 0.005). Moreover, involvement of both N1 and N4 on both sides was found in 19.1% of the early-stage IPD patients, whereas its incidence was higher (61.5%) in the late-stage IPD patients (P < 0.0001), suggesting that the loss of hyperintensity in IPD progresses from N1 to N4 as the disease advances. Hum Brain Mapp 39:542-553, 2018. © 2017 Wiley Periodicals, Inc.