Atlas-based Approach Research Articles

Selection Strategies for Atlas-Based Mosaicing of Left Atrial 3-D Transesophageal Echocardiography Data

Three-dimensional transesophageal echocardiography (TEE) provides real-time soft tissue information, but its use is hampered by its limited field of view. The mosaicing of multiple TEE views makes it possible to visualize a large structure, like the left atrium, in a single volume. To this end, an automatic registration method is required. Similarly to atlas-based segmentation approaches, atlas-based mosaicing (ABM) uses a full volume atlas set to moderate the onerous registration of the individual TEE views. The performance of ABM depends both on the quality of the involved registrations and on the selection of the optimal transformation from the candidate transformations that result from the various atlases. The study described here explored the performance of different selection strategies on multiview TEE data of the left atrium. We found that by incorporating two stages of transformation selection, using the image similarity and the conformity between the candidate transformations as selection criteria, the average registration error dropped below 3 mm with respect to manual registration of these data. Finally, we used this method for the automatic construction of a wide-view TEE volume of the left atrium.

The importance of hippocampal dynamic connectivity in explaining memory function in multiple sclerosis.

IntroductionBrain dynamics (i.e., variable strength of communication between areas), even at the scale of seconds, are thought to underlie complex human behavior, such as learning and memory. In multiple sclerosis (MS), memory problems occur often and have so far only been related to “stationary” brain measures (e.g., atrophy, lesions, activation and stationary (s) functional connectivity (FC) over an entire functional scanning session). However, dynamics in FC (dFC) between the hippocampus and the (neo)cortex may be another important neurobiological substrate of memory impairment in MS that has not yet been explored. Therefore, we investigated hippocampal dFC during a functional (f) magnetic resonance imaging (MRI) episodic memory task and its relationship with verbal and visuospatial memory performance outside the MR scanner.MethodsThirty‐eight MS patients and 29 healthy controls underwent neuropsychological tests to assess memory function. Imaging (1.5T) was obtained during performance of a memory task. We assessed hippocampal volume, functional activation, and sFC (i.e., FC of the hippocampus with the rest of the brain averaged over the entire scan, using an atlas‐based approach). Dynamic FC of the hippocampus was calculated using a sliding window approach.ResultsNo group differences were found in hippocampal activation, sFC, and dFC. However, stepwise forward regression analyses in patients revealed that lower dFC of the left hippocampus (standardized β = −0.30; p = .021) could explain an additional 7% of variance (53% in total) in verbal memory, in addition to female sex and larger left hippocampal volume. For visuospatial memory, lower dFC of the right hippocampus (standardized β = −0.38; p = .013) could explain an additional 13% of variance (24% in total) in addition to higher sFC of the right hippocampus.ConclusionLow hippocampal dFC is an important indicator for maintained memory performance in MS, in addition to other hippocampal imaging measures. Hence, brain dynamics may offer new insights into the neurobiological mechanisms underlying memory (dys)function.

Non-motor outcomes of subthalamic stimulation in Parkinson's disease depend on location of active contacts

BackgroundSubthalamic nucleus (STN) deep brain stimulation (DBS) improves quality of life (QoL), motor, and non-motor symptoms (NMS) in Parkinson's disease (PD). Few studies have investigated the influence of the location of neurostimulation on NMS. ObjectiveTo investigate the impact of active contact location on NMS in STN-DBS in PD. MethodsIn this prospective, open-label, multicenter study including 50 PD patients undergoing bilateral STN-DBS, we collected NMSScale (NMSS), NMSQuestionnaire (NMSQ), Hospital Anxiety and Depression Scale (anxiety/depression, HADS-A/-D), PDQuestionnaire-8 (PDQ-8), Scales for Outcomes in PD-motor examination, motor complications, activities of daily living (ADL), and levodopa equivalent daily dose (LEDD) preoperatively and at 6 months follow-up. Changes were analyzed with Wilcoxon signed-rank/t-test and Bonferroni-correction for multiple comparisons. Although the STN was targeted visually, we employed an atlas-based approach to explore the relationship between active contact locations and DBS outcomes. Based on fused MRI/CT-images, we identified Cartesian coordinates of active contacts with patient-specific Mai-atlas standardization. We computed linear mixed-effects models with x-/y-/z-coordinates as independent, hemispheres as within-subject, and test change scores as dependent variables. ResultsNMSS, NMSQ, PDQ-8, motor examination, complications, and LEDD significantly improved at follow-up. Linear mixed-effect models showed that NMS and QoL improvement significantly depended on more medial (HADS-D, NMSS), anterior (HADS-D, NMSQ, PDQ-8), and ventral (HADS-A/-D, NMSS, PDQ-8) neurostimulation. ADL improved more in posterior, LEDD in lateral neurostimulation locations. No relationship was observed for motor examination and complications scores. ConclusionsOur study provides evidence that more anterior, medial, and ventral STN-DBS is significantly related to more beneficial non-motor outcomes.

Progressive microstructural changes of the occipital cortex in Huntington\u2019s disease

In this study we longitudinally investigated the rate of microstructural alterations in the occipital cortex in different stages of Huntington’s disease (HD) by applying an automated atlas-based approach to diffusion MRI data. Twenty-two premanifest (preHD), 10 early manifest HD (early HD) and 24 healthy control subjects completed baseline and two year follow-up scans. The preHD group was stratified based on the predicted years to disease onset into a far (preHD-A) and near (preHD-B) to disease onset group. Clinical and behavioral measures were collected per assessment time point. An automated atlas-based DTI analysis approach was used to obtain the mean, axial and radial diffusivities of the occipital cortex. We found that the longitudinal rate of diffusivity change in the superior occipital gyrus (SOG), middle occipital gyrus (MOG), and inferior occipital gyrus (IOG) was significantly higher in early HD compared to both preHD and controls (all p’s ≤ 0.005), which can be interpreted as an increased rate of microstructural degeneration. Furthermore, the change rate in the diffusivity of the MOG could significantly discriminate between preHD-B compared to preHD-A and the other groups (all p’s ≤ 0.04). Finally, we found an inverse correlation between the Stroop Word Reading task and diffusivities in the SOG and MOG (all p’s ≤ 0.01). These findings suggest that measures obtained from the occipital cortex can serve as sensitive longitudinal biomarkers for disease progression in preHD-B and early HD. These could in turn be used to assess potential effects of proposed disease modifying therapies.

Association of white matter diffusion characteristics and cognitive deficits in temporal lobe epilepsy

ObjectiveThe purpose of this study was to evaluate the relation between cognitive performance and white matter (WM) integrity in patients with temporal lobe epilepsy (TLE) with mesial temporal sclerosis (MTS). MethodsWe included 26 patients with TLE (10 right, 16 left onset) as well as 24 healthy controls matched for age, gender, and years of education. In addition to quantitative hippocampal volume and transverse relaxation (T2) evaluation, whole-brain WM was analyzed using fractional anisotropy (FA) maps, derived from the diffusion tensor model. Average FA values were obtained from 38 regions of interest (ROI) of the main WM fascicles using an atlas-based approach. All subjects underwent extensive coFignitive assessments, Wechsler Adult Intelligence Scale (WAIS-IV) and Wechsler Memory Scale (WMS-IV). Fractional anisotropy was correlated with neuropsychological scores, and group effects were evaluated. Finally, patients were clustered based on their cognitive performance to evaluate if clinical and structural variables relate to specific cognitive profiles. ResultsPatients had differential alterations in the integrity of the WM dependent on seizure laterality and presence of hippocampal sclerosis. Patients with TLE showed, on average, lower scores in most of the cognitive assessments. Correlations between cognition and WM followed specific trajectories per group with TLE, particularly in Left-TLE, in which we found a marked association between cognitive abilities and WM abnormalities. Cluster analysis of cognitive performance revealed three cognitive profiles, which were associated with the degree and spread of WM abnormalities. SignificanceWhite matter diffusion characteristics differ between patients, particularly in relation to seizure laterality and hippocampal damage. Moreover, WM abnormalities are associated with cognitive performance. The extent of WM alterations leads to disrupted cerebral intercommunication and therefore negatively affects cognition.

Regional cortical perfusion on arterial spin labeling MRI in dementia with Lewy bodies: Associations with clinical severity, glucose metabolism and tau PET.

Visually preserved metabolism in posterior cingulate cortex relative to hypometabolism in precuneus and cuneus, the cingulate island sign, is a feature of dementia with Lewy bodies (DLB) on FDG-PET. Lower cingulate island sign ratio (posterior cingulate cortex/cuneus+precuneus; FDG-CISr) values have been associated with a higher Braak neurofibrillary tangle stage in autopsied DLB. Using voxel-wise analysis, we assessed the patterns of regional cortical perfusion and metabolism, and using an atlas-based approach, we measured perfusion cingulate island sign ratio on arterial spin labeling MRI (ASL-CISr), and its associations with FDG-CISr, uptake on tau-PET and clinical severity in DLB. Our study sample (n = 114) included clinically probable DLB patients (n = 19), age-matched patients with probable Alzheimer's disease dementia (AD; n = 19) and matched controls (n = 76) who underwent MRI with 3-dimensional pseudo-continuous arterial spin labeling, 18F-FDG-PET and 18F-AV-1451 tau PET. Patterns of cortical perfusion and metabolism were derived from quantitative maps using Statistical Parametric Mapping. DLB patients showed hypoperfusion on ASL-MRI in precuneus, cuneus and posterior parieto-occipital cortices, compared to controls, and relatively spared posterior cingulate gyrus, similar to pattern of hypometabolism on FDG-PET. DLB patients had higher ASL-CISr and FDG-CISr than AD patients (p <0.001). ASL-CISr correlated with FDG-CISr in DLB patients (r = 0.67; p =0.002). Accuracy of distinguishing DLB from AD patients was 0.80 for ASL-CISr and 0.91 for FDG-CISr. Lower ASL-CISr was moderately associated with a higher composite medial temporal AV-1451 uptake (r = −0.50; p =0.03) in DLB. Lower perfusion in precuneus and cuneus was associated with worse global clinical scores. In summary, the pattern of cortical hypoperfusion on ASL-MRI is similar to hypometabolism on FDG-PET, and respective cingulate island sign ratios correlate with each other in DLB. Non-invasive and radiotracer-free ASL-MRI may be further developed as a tool for the screening and diagnostic evaluation of DLB patients in a variety of clinical settings where FDG-PET is not accessible.

Widespread diffusion changes differentiate Parkinson's disease and progressive supranuclear palsy.

BackgroundParkinson's disease (PD) and progressive supranuclear palsy – Richardson's syndrome (PSP-RS) are often represented by similar clinical symptoms, which may challenge diagnostic accuracy. The objective of this study was to investigate and compare regional cerebral diffusion properties in PD and PSP-RS subjects and evaluate the use of these metrics for an automatic classification framework.Material and methodsDiffusion-tensor MRI datasets from 52 PD and 21 PSP-RS subjects were employed for this study. Using an atlas-based approach, regional median values of mean diffusivity (MD), fractional anisotropy (FA), radial diffusivity (RD), and axial diffusivity (AD) were measured and employed for feature selection using RELIEFF and subsequent classification using a support vector machine.ResultsAccording to RELIEFF, the top 17 diffusion values consisting of deep gray matter structures, the brainstem, and frontal cortex were found to be especially informative for an automatic classification. A MANCOVA analysis performed on these diffusion values as dependent variables revealed that PSP-RS and PD subjects differ significantly (p < .001). Generally, PSP-RS subjects exhibit reduced FA, and increased MD, RD, and AD values in nearly all brain structures analyzed compared to PD subjects. The leave-one-out cross-validation of the support vector machine classifier revealed that the classifier can differentiate PD and PSP-RS subjects with an accuracy of 87.7%. More precisely, six PD subjects were wrongly classified as PSP-RS and three PSP-RS subjects were wrongly classified as PD.ConclusionThe results of this study demonstrate that PSP-RS subjects exhibit widespread and more severe diffusion alterations compared to PD patients, which appears valuable for an automatic computer-aided diagnosis approach.

Prostate shapes on pre-treatment MRI between prostate cancer patients who do and do not undergo biochemical recurrence are different: Preliminary Findings

Early identification of PCa patients at risk for biochemical recurrence (BCR) post-therapy will potentially complement definitive therapy with either neo- or adjuvant therapy to improve prognosis. BCR post definitive therapy is often associated with disease progression that might cause a bulge in the prostate gland. In this work we explored if an atlas-based comparison approach reveals shape differences in the prostate capsule as observed on pre-treatment T2-weighted MRI between prostate cancer patients who do (BCR+) and do not (BCR−) have BCR following definitive therapy. A single center IRB approved study included 874 patients. Complete image datasets, clinically localized PCa, availability of Gleason score, data available for post-treatment PSA and follow-up for at least 3 years in patients without BCR were the inclusion criteria to select 77 patients out of the 874 patients. Further controlling for Gleason score, stage, age and to maintain equal number of cases for the BCR+ and BCR− categories, the total number of cases was reduced to 50. Manually segmented prostate capsules were aligned to a BCR− template for statistical comparison between the BCR+ and BCR− groups. Statistically significant shape difference between the two groups was observed towards the lateral and the posterior sides of prostate.

Atlas-Based Segmentation of Temporal Bone Anatomy.

To develop a time-efficient automated segmentation approach that could identify critical structures in the temporal bone for visual enhancement and use in surgical simulation software. An atlas-based segmentation approach was developed to segment the cochlea, ossicles, semicircular canals (SCCs), and facial nerve in normal temporal bone CT images. This approach was tested in images of 26 cadaver bones (13 left, 13 right). The results of the automated segmentation were compared to manual segmentation visually and using DICE metric, average Hausdorff distance, and volume similarity. The DICE metrics were greater than 0.8 for the cochlea, malleus, incus, and the SCCs combined. It was slightly lower for the facial nerve. The average Hausdorff distance was less than one voxel for all structures, and the volume similarity was 0.86 or greater for all structures except the stapes. The atlas-based approach with rigid body registration of the otic capsule was successful in segmenting critical structures of temporal bone anatomy for use in surgical simulation software.

136 Long-term Supratentorial Radiographic Effects of Surgery and Local Radiation in Children with Infratenorial Ependymoma

Abstract INTRODUCTION Current standard of care for children with an infratentorial ependymoma includes maximal safe resection with local radiation of 54–59gy. High-dose local radiation has been associated with decline in multiple cognitive domains. The anatomic correlates of this cognitive decline remain undefined and there have been no radiographic studies on the long-term effects of this treatment paradigm. METHODS A comprehensive database of pediatric brain tumor patients treated at Stanford Children's from 2004–2016 was queried. 7 patients with posterior fossa ependymoma were identified who were treated with surgery and local radiation alone, who had no evidence of recurrent disease, and had imaging suitable for analysis. Diffusion-weighted MRI (DWI) datasets were used to calculate apparent diffusion coefficient (ADC) maps for each subject, while arterial spin labeling (ASL) datasets were used to calculated maps of cerebral blood flow (CBF). Using an atlas-based approach, the following brain structures were automatically segmented: cerebral white matter, cerebral cortex, thalamus, caudate, putamen, pallidum, hippocampus, amygdala, and accumbens. Furthermore, DWI and ASL datasets of 52 age-matched healthy children were available and analyzed in the same fashion to enable group comparisons. Binomial logistic regression models were developed for CBF and ADC measurements with disease status as a binary response variable and a significance threshold of P &lt; 0.05. RESULTS &gt;Several statistically significant differences were detected between the two groups. CBF was lower in the caudate (OR = .424 95%CI.142-.838 p = .05) and pallidum (OR = .479 95%CI = .204-.808 p = .029) and higher in the accumbens (OR = 1.917 95%CI = 1.182-4.472 p = .046) in the ependymoma cohort compared to controls. ADC was increased in the thalamus (OR = 1.168 95%CI = 1.040-1.407 p = .027) and trended towards decreased in the amygdala (OR = .93 95%CI = .846-.996 P = 0.068). CONCLUSION Surgery and local radiation for posterior fossa ependymoma are associated with supratentorial ADC and CBF alterations which may represent an anatomical and physiologic correlate to the previously published decline in neurocognitive outcomes in this population.

A diffusion spectrum imaging-based tractographic study into the anatomical subdivision and cortical connectivity of the ventral external capsule: uncinate and inferior fronto-occipital fascicles.

The inferior fronto-occipital fasciculus (IFOF) and uncinate fasciculus (UF) are major fronto-capsular white matter pathways. IFOF connects frontal areas of the brain to parieto-occipital areas. UF connects ventral frontal areas to anterior temporal areas. Both fascicles are thought to subserve higher language and emotion roles. Controversy pertaining to their connectivity and subdivision persists in the literature, however. High-definition fiber tractography (HDFT) is a non-tensor tractographic method using diffusion spectrum imaging data. Its major advantage over tensor-based tractography is its ability to trace crossing fiber pathways. We used HDFT to investigate subdivisions and cortical connectivity of IFOF and UF in 30 single subjects and in an atlas comprising averaged data from 842 individuals. A per-subject aligned, atlas-based approach was employed to seed fiber tracts and to study cortical terminations. For IFOF, we observed a tripartite arrangement corresponding to ventrolateral, ventromedial, and dorsomedial frontal origins. IFOF volume was not significantly lateralized to either hemisphere. UF fibers arose from ventromedial and ventrolateral frontal areas on the left and from ventromedial frontal areas on the right. UF volume was significantly lateralized to the left hemisphere. The data from the averaged atlas was largely in concordance with subject-specific findings. IFOF connected to parietal, occipital, but not temporal, areas. UF connected predominantly to temporal poles. Both IFOF and UF possess subdivided arrangements according to their frontal origin. Our connectivity results indicate the multifunctional involvement of IFOF and UF in language tasks. We discuss our findings in context of the tractographic literature.

Planification à partir d’imagerie par résonance magnétique en radiothérapie

MRI-based radiotherapy planning is a topical subject due to the introduction of a new generation of treatment machines combining a linear accelerator and a MRI. One of the issues for introducing MRI in this task is the lack of information to provide tissue density information required for dose calculation. To cope with this issue, two strategies may be distinguished from the literature. Either a synthetic CT scan is generated from the MRI to plan the dose, or a dose is generated from the MRI based on physical underpinnings. Within the first group, three approaches appear: bulk density mapping assign a homogeneous density to different volumes of interest manually defined on a patient MRI; machine learning-based approaches model local relationship between CT and MRI image intensities from multiple data, then applying the model to a new MRI; atlas-based approaches use a co-registered training data set (CT-MRI) which are registered to a new MRI to create a pseudo CT from spatial correspondences in a final fusion step. Within the second group, physics-based approaches aim at computing the dose directly from the hydrogen contained within the tissues, quantified by MRI. Excepting the physics approach, all these methods generate a synthetic CT called “pseudo CT”, on which radiotherapy planning will be finally realized. This literature review shows that atlas- and machine learning-based approaches appear more accurate dosimetrically. Bulk density approaches are not appropriate for bone localization. The fastest methods are machine learning and the slowest are atlas-based approaches. The less automatized are bulk density assignation methods. The physical approaches appear very promising methods. Finally, the validation of these methods is crucial for a clinical practice, in particular in the perspective of adaptive radiotherapy delivered by a linear accelerator combined with an MRI scanner.

Fully automated treatment planning for head and neck radiotherapy using a voxel-based dose prediction and dose mimicking method

Recent works in automated radiotherapy treatment planning have used machine learning based on historical treatment plans to infer the spatial dose distribution for a novel patient directly from the planning image. We present a probabilistic, atlas-based approach which predicts the dose for novel patients using a set of automatically selected most similar patients (atlases). The output is a spatial dose objective, which specifies the desired dose-per-voxel, and therefore replaces the need to specify and tune dose-volume objectives. Voxel-based dose mimicking optimization then converts the predicted dose distribution to a complete treatment plan with dose calculation using a collapsed cone convolution dose engine. In this study, we investigated automated planning for right-sided oropharaynx head and neck patients treated with IMRT and VMAT. We compare four versions of our dose prediction pipeline using a database of 54 training and 12 independent testing patients by evaluating 14 clinical dose evaluation criteria. Our preliminary results are promising and demonstrate that automated methods can generate comparable dose distributions to clinical. Overall, automated plans achieved an average of 0.6% higher dose for target coverage evaluation criteria, and 2.4% lower dose at the organs at risk criteria levels evaluated compared with clinical. There was no statistically significant difference detected in high-dose conformity between automated and clinical plans as measured by the conformation number. Automated plans achieved nine more unique criteria than clinical across the 12 patients tested and automated plans scored a significantly higher dose at the evaluation limit for two high-risk target coverage criteria and a significantly lower dose in one critical organ maximum dose. The novel dose prediction method with dose mimicking can generate complete treatment plans in 12–13 min without user interaction. It is a promising approach for fully automated treatment planning and can be readily applied to different treatment sites and modalities.

Fast Numerical Simulation of Focused Ultrasound Treatments During Respiratory Motion With Discontinuous Motion Boundaries.

Focused ultrasound (FUS) is rapidly gaining clinical acceptance for several target tissues in the human body. Yet, treating liver targets is not clinically applied due to a high complexity of the procedure (noninvasiveness, target motion, complex anatomy, blood cooling effects, shielding by ribs, and limited image-based monitoring). To reduce the complexity, numerical FUS simulations can be utilized for both treatment planning and execution. These use-cases demand highly accurate and computationally efficient simulations. We propose a numerical method for the simulation of abdominal FUS treatments during respiratory motion of the organs and target. Especially, a novel approach is proposed to simulate the heating during motion by solving Pennes' bioheat equation in a computational reference space, i.e.,the equation is mathematically transformed to the reference. The approach allows for motion discontinuities, e.g., the sliding of the liver along the abdominal wall. Implementing the solver completely on the graphics processing unit and combining it with an atlas-based ultrasound simulation approach yields a simulation performance faster than real time (less than 50-s computing time for 100s of treatment time) on a modern off-the-shelf laptop. The simulation method is incorporated into a treatment planning demonstration application that allows to simulate real patient cases including respiratory motion. The high performance of the presented simulation method opens the door to clinical applications. The methods bear the potential to enable the application of FUS for moving organs.

Methods for the computation of templates from quantitative magnetic susceptibility maps (QSM): Toward improved atlas- and voxel-based analyses (VBA).

To develop and assess a method for the creation of templates for voxel-based analysis (VBA) and atlas-based approaches using quantitative magnetic susceptibility mapping (QSM). We studied four strategies for the creation of magnetic susceptibility brain templates, derived as successive extensions of the conventional template generation (CONV) based on only T1 -weighted (T1 w) images. One method that used only T1 w images involved a minor improvement of CONV (U-CONV). One method used only magnetic susceptibility maps as input for template generation (DIRECT), and the other two used a linear combination of susceptibility and T1 w images (HYBRID) and an algorithm that directly used both image modalities (MULTI), respectively. The strategies were evaluated in a group of N = 10 healthy human subjects and semiquantitatively assessed by three experienced raters. Template quality was compared statistically via worth estimates (WEs) obtained with a log-linear Bradley-Terry model. The overall quality of the templates was better for strategies including both susceptibility and T1 w contrast (MULTI: WE = 0.62; HYBRID: WE = 0.21), but the best method depended on the anatomical region of interest. While methods using only one modality resulted in lower WEs, lowest overall WEs were obtained when only T1 w images were used (DIRECT: WE = 0.12; U-CONV: WE = 0.05). Template generation strategies that employ only magnetic susceptibility contrast or both magnetic susceptibility and T1 w contrast produce templates with the highest quality. The optimal approach depends on the anatomical structures of interest. The established approach of using only T1 w images (CONV) results in reduced image quality compared to all other approaches studied. 2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2017;46:1474-1484.

Reference standard space hippocampus labels according to the European Alzheimer's Disease Consortium–Alzheimer's Disease Neuroimaging Initiative harmonized protocol: Utility in automated volumetry

IntroductionA harmonized protocol (HarP) for manual hippocampal segmentation on magnetic resonance imaging (MRI) has recently been developed by an international European Alzheimer's Disease Consortium–Alzheimer's Disease Neuroimaging Initiative project. We aimed at providing consensual certified HarP hippocampal labels in Montreal Neurological Institute (MNI) standard space to serve as reference in automated image analyses. MethodsManual HarP tracings on the high-resolution MNI152 standard space template of four expert certified HarP tracers were combined to obtain consensual bilateral hippocampus labels. Utility and validity of these reference labels is demonstrated in a simple atlas-based morphometry approach for automated calculation of HarP-compliant hippocampal volumes within SPM software. ResultsIndividual tracings showed very high agreement among the four expert tracers (pairwise Jaccard indices 0.82–0.87). Automatically calculated hippocampal volumes were highly correlated (rL/R = 0.89/0.91) with gold standard volumes in the HarP benchmark data set (N = 135 MRIs), with a mean volume difference of 9% (standard deviation 7%). ConclusionThe consensual HarP hippocampus labels in the MNI152 template can serve as a reference standard for automated image analyses involving MNI standard space normalization.

Mapping the critical gestational age at birth that alters brain development in preterm-born infants using multi-modal MRI

Preterm birth adversely affects postnatal brain development. In order to investigate the critical gestational age at birth (GAB) that alters the developmental trajectory of gray and white matter structures in the brain, we investigated diffusion tensor and quantitative T2 mapping data in 43 term-born and 43 preterm-born infants. A novel multivariate linear model—the change point model, was applied to detect change points in fractional anisotropy, mean diffusivity, and T2 relaxation time. Change points captured the “critical” GAB value associated with a change in the linear relation between GAB and MRI measures. The analysis was performed in 126 regions across the whole brain using an atlas-based image quantification approach to investigate the spatial pattern of the critical GAB. Our results demonstrate that the critical GABs are region- and modality-specific, generally following a central-to-peripheral and bottom-to-top order of structural development. This study may offer unique insights into the postnatal neurological development associated with differential degrees of preterm birth.

Atlas-Based Mosaicing of Left Atrial 3-D Transesophageal Echocardiography Images

Transesophageal echocardiography (TEE) is a promising imaging modality used to guide cardiac interventions, such as catheter ablation for the treatment of cardiac arrhythmias. These procedures rely on good visualization of the left atrium and pulmonary veins. To visualize these structures in a single volume, the acquisition, registration and fusion of multiple TEE views of the left atrium are required. We introduce atlas-based mosaicing as a method for the registration of images that are acquired according to a standardized protocol. Inspired by atlas-based segmentation approaches, compounded data of other patients serve as atlases for the registration of new data. The performance of atlas-based mosaicing is studied on 3-D TEE data of the left atrium and compared with that of regular pairwise registration. This study indicates that improved registration robustness and smaller registration errors are achieved with atlas-based mosaicing compared with regular pairwise registration. This is an important step toward the use of TEE for interventional guidance of ablation procedures.

Multi-Atlas Segmentation of Mouse Brain MRM Based on Optimized Advanced Normalization Tools

In recent years, with the deepening of brain science research, mouse magnetic resonance microscopy (MRM) for neuroimaging research has gradually become a main research interest. Brain segmentation is an essential techniques for investigating the brain morphometry, while the traditional approach to segment a given brain involves the manual delineation of the ROIs by an expert. This practice can be slow and unscalable. Although automatic atlas-based segmentation approaches have been developed and validated for the human brain MRI, there is limited work for the mouse brain MRM. This paper combined optimized image registration and multi-atlas model for mouse brain segmentation. The results showed that multiple atlases with optimized geodesic-SyN can best improve the segmentation accuracy in the mouse brain, and registration algorithm plays important role in performance improvement.

Heritability of white matter microstructure in late middle age: A twin study of tract-based fractional anisotropy and absolute diffusivity indices.

There is evidence that differences among individuals in white matter microstructure, as measured with diffusion tensor imaging (DTI), are under genetic control. However, little is known about the relative contribution of genetic and environmental effects on different diffusivity indices among late middle-aged adults. Here, we examined the magnitude of genetic influences for fractional anisotropy (FA), and mean (MD), axial (AD), and radial (RD) diffusivities in male twins aged 56-66 years old. Using an atlas-based registration approach to delineate individual white matter tracts, we investigated mean DTI-based indices within the corpus callosum, 12 bilateral tracts and all these regions of interest combined. All four diffusivity indices had high heritability at the global level (72%-80%). The magnitude of genetic effects in individual tracts varied from 0% to 82% for FA, 0% to 81% for MD, 8% to 77% for AD, and 0% to 80% for RD with most of the tracts showing significant heritability estimates. Despite the narrow age range of this community-based sample, age was correlated with all four diffusivity indices at the global level. In sum, all diffusion indices proved to have substantial heritability for most of the tracts and the heritability estimates were similar in magnitude for different diffusivity measures. Future studies could aim to discover the particular set of genes that underlie the significant heritability of white matter microstructure. Hum Brain Mapp 38:2026-2036, 2017. © 2017 Wiley Periodicals, Inc.