Article
Mathematics
Chenwei Cai, Lvda Wang, Shihui Ying
Summary: Image registration, an important technique in brain imaging analysis, aims to align two images through a spatial transformation. This research proposes a symmetric diffeomorphic image registration model based on multi-label segmentation masks. By introducing a new similarity metric and adaptive parameters, the proposed model improves accuracy, robustness, and smoothness of the registration compared to mainstream methods.
Article
Neurosciences
Xiaoluan Xia, Xinglin Zeng, Fei Gao, Zhen Yuan
Summary: This study proposes a normative mapping framework for a cross-species connectome atlas (CCA) and applies it to the human and macaque striatum. By classifying striatal voxels based on their shared within-striatum resting-state functional connectivity, six corresponding striatal parcels are delineated in both species. The study also demonstrates the best-matched whole-brain connectivity between interspecies corresponding regions and describes interspecies differences in whole-brain multimodal connectivities and brain functions.
Article
Engineering, Biomedical
Samah Khawaled, Moti Freiman
Summary: This study introduces the NPBDREG method for DNN-based image registration, which accurately estimates the uncertainty of registration and improves the registration accuracy and smoothness. It also demonstrates superior generalization capability when handling corrupted data.
COMPUTERIZED MEDICAL IMAGING AND GRAPHICS
(2022)
Article
Neurosciences
Liangjun Chen, Zhengwang Wu, Dan Hu, Ya Wang, Fenqiang Zhao, Tao Zhong, Weili Lin, Li Wang, Gang Li
Summary: This paper constructs a four-dimensional brain atlas based on infant brain MR images, which has a high spatiotemporal resolution and preserves more structural details. It greatly improves the accuracy of neurodevelopmental analysis during infancy.
Review
Medicine, Research & Experimental
Enrico Capobianco, Marco Dominietto
Summary: This review discusses the potential applications of using multimodal imaging, radiomic data processing, and brain atlases in GBM studies, as well as the development of inference tools that can be generalized to other cancers. The focus is on building radiomic models from multimodal imaging data and translating suitably processed information into more accurate patient stratifications and evaluations of treatment efficacy using machine learning and other computational tools.
JOURNAL OF TRANSLATIONAL MEDICINE
(2023)
Article
Neurosciences
Molly B. D. Prigge, Nicholas Lange, Erin D. Bigler, Jace B. King, Douglas C. Dean, Nagesh Adluru, Andrew L. Alexander, Janet E. Lainhart, Brandon A. Zielinski
Summary: This longitudinal study found different changes in brain volume at different ages in individuals with autism, including increased gray matter volume, enlarged ventricles, and smaller corpus callosum volume. These findings expand our understanding of volumetric brain-based abnormalities in males with autism.
Article
Computer Science, Artificial Intelligence
Somayeh Ebrahimkhani, Anuja Dharmaratne, Mohamed Hisham Jaward, Yuanyuan Wang, Flavia M. Cicuttini
Summary: The study proposed a joint deep and hand-crafted learning-based framework for automated segmentation of knee articular cartilage tissue, achieving high segmentation accuracy and volume correlation on multiple datasets.
Article
Veterinary Sciences
Kari D. Foss, Krista A. Keller, Spencer P. Kehoe, Bradley P. Sutton
Summary: This study aimed to improve diagnostic capabilities for bearded dragons with neurologic dysfunction by establishing an MRI protocol and brain atlas. MRI scans of the brain were successfully performed on seven healthy bearded dragons, resulting in the creation of a brain atlas and identification of nine regions of interest. The entire process took only 35 minutes, and all lizards recovered without complications.
FRONTIERS IN VETERINARY SCIENCE
(2022)
Review
Veterinary Sciences
Ashik Banstola, John N. J. Reynolds
Summary: A brain atlas is essential for understanding the anatomical relationship between neuroanatomical structures. Despite the similarities between the sheep and human brain, little is known about the sheep brain stereotaxy, and a detailed sheep atlas is scarce. The lack of a 3D stereotaxic sheep atlas hinders the application of advanced imaging techniques in sheep and the mapping of sheep brain structures to its human counterparts. Developing a detailed sheep brain atlas would facilitate the use of sheep as a non-primate model for neurological research.
FRONTIERS IN VETERINARY SCIENCE
(2022)
Article
Chemistry, Multidisciplinary
Andrea Urru, Ayako Nakaki, Oualid Benkarim, Francesca Crovetto, Laura Segales, Valentin Comte, Nadine Hahner, Elisenda Eixarch, Eduard Gratacos, Fatima Crispi, Gemma Piella, Miguel A. Gonzalez Ballester
Summary: In this study, a new pipeline for fetal and neonatal segmentation has been developed, along with the creation of two new fetal atlases. The results show that the use of the new templates and segmentation strategy leads to accurate results, outperforming a reference pipeline in early and late-onset fetal brain segmentation.
Article
Neurosciences
Jingru Fu, Antonios Tzortzakakis, Jose Barroso, Eric Westman, Daniel Ferreira, Rodrigo Moreno
Summary: Predicting brain aging is important for early detection and prognosis of neurodegenerative diseases. This paper proposes a methodology to fill missing data in longitudinal cohorts with anatomically plausible images. The proposed methodology uses deep learning-based diffeomorphic registration to simulate the aging process and rearrange the generated images to specific age ranges. The experimental results show that this methodology can produce anatomically plausible aging predictions and enhance longitudinal datasets.
HUMAN BRAIN MAPPING
(2023)
Article
Neurosciences
Ahmed M. Radwan, Stefan Sunaert, Kurt Schilling, Maxime Descoteaux, Bennett A. Landman, Mathieu Vandenbulcke, Tom Theys, Patrick Dupont, Louise Emsell
Summary: The virtual dissection of white matter using diffusion MRI tractography has poor reproducibility, but this study provides a comprehensive description of white matter anatomy using a reproducible automated subject-specific parcellation-based approach with probabilistic CSD tractography. The study demonstrates high inter-session similarity and provides a WM atlas that can be useful for mapping white matter fasciculi in healthy adults.
Article
Anatomy & Morphology
Yingying Yang, Quan Zhang, Jialiang Ren, Qingfeng Zhu, Lixin Wang, Zuojun Geng
Summary: This study constructed an MRI template set for spontaneously hypertensive rats (SHRs) and demonstrated its potential as a beneficial tool for precise analysis of the SHR brain using structural and functional MRI.
BRAIN STRUCTURE & FUNCTION
(2022)
Article
Multidisciplinary Sciences
Yasser Aleman-Gomez, Alessandra Griffa, Jean-Christophe Houde, Elena Najdenovska, Stefano Magon, Meritxell Bach Cuadra, Maxime Descoteaux, Patric Hagmann
Summary: In this work, a whole-brain multi-scale structural connectome atlas is presented, which can provide valuable network information for imaging studies. This tool is derived from healthy subject data, using extensively validated processing and segmentation tools, and it offers user-friendly code to extract connection-specific quantitative information from individual brain imaging data. This method contributes to analyzing the network-level consequences of regional changes.
Article
Biochemical Research Methods
Anand A. Joshi, Soyoung Choi, Yijun Liu, Minqi Chong, Gaurav Sonkar, Jorge Gonzalez-Martinez, Dileep Nair, Jessica L. Wisnowski, Justin P. Haldar, David W. Shattuck, Hanna Damasio, Richard M. Leahy
Summary: This study presents a new high-quality single-subject brain atlas with fine anatomical details, high SNR, and excellent tissue contrast. The atlas includes both manual labeling based on known features and sub-parcellation guided by functional information. It provides consistent parcellation and labeling, and can be used as a reference template for structural coregistration and labeling of individual brains. The atlas contains 66 cortical regions, 29 noncortical regions, and additional subregions based on connectivity analysis. It also includes a probabilistic map for reliability assessment.
JOURNAL OF NEUROSCIENCE METHODS
(2022)
Article
Psychology, Clinical
Milap A. Nowrangi, Christopher Marano, Kenichi Oishi, Susumu Mori, Haris Sair, John Outen, Jeannie Leoutsakos, Constantine Lyketsos, Paul B. Rosenberg
Summary: The study found that agitation, apathy, and delusions are associated with volumes of specific brain regions, particularly the anterior cingulate cortex (ACC). These findings help reveal the important role of ACC in these symptoms.
INTERNATIONAL PSYCHOGERIATRICS
(2021)
Article
Anatomy & Morphology
Kenichi Oishi, Susumu Mori, Juan C. Troncoso, Frederick A. Lenz
BRAIN STRUCTURE & FUNCTION
(2020)
Article
Behavioral Sciences
Adrian Suarez, Sadhvi Saxena, Kenichi Oishi, Kumiko Oishi, Alexandra Walker, Chris Rorden, Argye E. Hillis
Article
Neurosciences
Hua-Jun Liang, Erin E. O'Connor, Thomas Ernst, Kenichi Oishi, Eric Cunningham, Linda Chang
Summary: The study found that HIV+ women had poorer sensorimotor function and lower GP_FA compared to HIV+ men. Regardless of sex, the HIV+ group performed worse in Fluency, Speed, and Attention, with lower FA and higher MD in multiple brain regions. Gender had an impact on the manifestation of cognitive impairment.
JOURNAL OF NEUROIMMUNE PHARMACOLOGY
(2021)
Article
Engineering, Biomedical
Rajan Kashyap, Sagarika Bhattacharjee, Ramaswamy Arumugam, Kenichi Oishi, John E. Desmond, S. H. Annabel Chen
JOURNAL OF NEURAL ENGINEERING
(2020)
Article
Immunology
Hannah A. Wang, Hua-Jun Liang, Thomas M. Ernst, Kenichi Oishi, Linda Chang
JOURNAL OF NEUROINFLAMMATION
(2020)
Article
Anatomy & Morphology
Yukako Kawasaki, Kenichi Oishi, Antonette Hernandez, Thomas Ernst, Dan Wu, Yoshihisa Otsuka, Can Ceritoglu, Linda Chang
Summary: Newborn infants with the BDNF-Val66Met variant exhibit smaller hippocampal and amygdala volumes, as well as slower age-dependent declines in total brain and white matter volumes, indicating a potential influence of this genetic variant on prenatal and postnatal developmental processes.
BRAIN STRUCTURE & FUNCTION
(2021)
Article
Radiology, Nuclear Medicine & Medical Imaging
Lin Chen, Anja Soldan, Kenichi Oishi, Andreia Faria, Yuxin Zhu, Marilyn Albert, Peter C. M. van Zijl, Xu Li
Summary: The study found that elevated brain iron content, together with beta-amyloid, is associated with lower cognitive functioning in cognitively normal older adults, particularly in the hippocampus. In the PET subgroup, iron content in the hippocampus was negatively correlated with episodic memory and visuospatial score, independent of beta-amyloid burden.Clusters showing negative and positive correlations between brain iron and beta-amyloid were observed, particularly in the frontal cortex, where iron content negatively correlated with both beta-amyloid and global cognitive scores.
Article
Psychiatry
Thomas L. Athey, Can Ceritoglu, Daniel J. Tward, Kwame S. Kutten, J. Raymond DePaulo, Kara Glazer, Fernando S. Goes, John R. Kelsoe, Francis Mondimore, Caroline M. Nievergelt, Kelly Rootes-Murdy, Peter P. Zandi, J. Tilak Ratnanather, Pamela B. Mahon
Summary: Research has shown that predictors of lithium response in bipolar disorder patients are difficult to pinpoint. However, this study has demonstrated potential for using detailed neuroimaging to fill this gap. Findings suggest that there are significant anatomical differences, particularly in the left hippocampus, between lithium responders and non-responders, which may help in future investigations of neuroimaging predictors for lithium response in bipolar disorder.
FRONTIERS IN PSYCHIATRY
(2021)
Article
Clinical Neurology
Sagarika Bhattacharjee, Rajan Kashyap, Alicia M. Goodwill, Beth Ann O'Brien, Brenda Rapp, Kenichi Oishi, John E. Desmond, S. H. Annabel Chen
Summary: The study revealed sex differences in simulated tDCS current density, though patterns varied across age groups and stimulation locations.
Article
Multidisciplinary Sciences
Kumiko Oishi, Anja Soldan, Corinne Pettigrew, Johnny Hsu, Susumu Mori, Marilyn Albert, Kenichi Oishi
Summary: The study demonstrates an association between measured and predicted changes in cognitive performance in older adults who are cognitively normal. By analyzing changes in pairwise functional connectivity between 80 gray matter regions, the study identifies 11 pairs of functional connections associated with the default mode network as features related to changes in cognitive performance. Linear and elastic net regression models allow the use of these 11 features to predict changes in cognitive performance over two years.
Article
Neurosciences
Mingyang Li, Xinyi Xu, Zuozhen Cao, Ruike Chen, Ruoke Zhao, Zhiyong Zhao, Xixi Dang, Kenichi Oishi, Dan Wu
Summary: The neonatal period is a critical window for brain development and has implications for long-term cognition and disorders. This study used multi-modal MRI data to generate automated multi-resolution and neonate-specific parcellations of the cerebral cortex, which showed high reproducibility and stability. Additionally, a manually delineated parcellation with high interpretability was provided. These findings may facilitate future studies of the human connectome in early development.
Article
Developmental Biology
Kengo Onda, Raul Chavez-Valdez, Ernest M. Graham, Allen D. Everett, Frances J. Northington, Kenichi Oishi
Summary: Neonatal hypoxic-ischemic encephalopathy (HIE) is a common condition in newborns that can result in severe neurological outcomes. Diffusion tensor imaging (DTI) is a powerful neuroimaging tool that can accurately predict the prognosis of HIE by measuring microscopic features of brain tissue. Previous studies have shown that DTI measurements, such as fractional anisotropy (FA) and mean diffusivity (MD), can effectively predict the occurrence of neurological sequelae in HIE patients. Recent research also suggests that machine learning techniques applied to whole-brain image quantification may provide accurate prognostication for HIE. However, further research and validation are needed for the clinical application of DTI in prognostication.
DEVELOPMENTAL NEUROSCIENCE
(2023)
Article
Computer Science, Information Systems
Kei Nishimaki, Kumpei Ikuta, Shingo Fujiyama, Kenichi Oishi, Hitoshi Iyatomi
Summary: This study proposes a novel posture correction skull stripping (PCSS) method to improve the accuracy and consistency of skull stripping by adjusting the subject's head angle and position and utilizing machine learning techniques. Experimental results show that the PCSS method outperforms current state-of-the-art techniques in skull stripping performance.
