1
|
Ramadass K, Yu X, Cai LY, Tang Y, Bao S, Kerley C, D'Archangel M, Barquero LA, Newton AT, Gauthier I, McGugin RW, Dawant BM, Cutting LE, Huo Y, Landman BA. Deep whole brain segmentation of 7T structural MRI. Proc SPIE Int Soc Opt Eng 2023; 12464:124642O. [PMID: 37123016 PMCID: PMC10139750 DOI: 10.1117/12.2654108] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/02/2023]
Abstract
7T magnetic resonance imaging (MRI) has the potential to drive our understanding of human brain function through new contrast and enhanced resolution. Whole brain segmentation is a key neuroimaging technique that allows for region-by-region analysis of the brain. Segmentation is also an important preliminary step that provides spatial and volumetric information for running other neuroimaging pipelines. Spatially localized atlas network tiles (SLANT) is a popular 3D convolutional neural network (CNN) tool that breaks the whole brain segmentation task into localized sub-tasks. Each sub-task involves a specific spatial location handled by an independent 3D convolutional network to provide high resolution whole brain segmentation results. SLANT has been widely used to generate whole brain segmentations from structural scans acquired on 3T MRI. However, the use of SLANT for whole brain segmentation from structural 7T MRI scans has not been successful due to the inhomogeneous image contrast usually seen across the brain in 7T MRI. For instance, we demonstrate the mean percent difference of SLANT label volumes between a 3T scan-rescan is approximately 1.73%, whereas its 3T-7T scan-rescan counterpart has higher differences around 15.13%. Our approach to address this problem is to register the whole brain segmentation performed on 3T MRI to 7T MRI and use this information to finetune SLANT for structural 7T MRI. With the finetuned SLANT pipeline, we observe a lower mean relative difference in the label volumes of ~8.43% acquired from structural 7T MRI data. Dice similarity coefficient between SLANT segmentation on the 3T MRI scan and the after finetuning SLANT segmentation on the 7T MRI increased from 0.79 to 0.83 with p<0.01. These results suggest finetuning of SLANT is a viable solution for improving whole brain segmentation on high resolution 7T structural imaging.
Collapse
Affiliation(s)
- Karthik Ramadass
- Department of Computer Science, Vanderbilt University, Nashville, TN, USA
| | - Xin Yu
- Department of Computer Science, Vanderbilt University, Nashville, TN, USA
| | - Leon Y Cai
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
| | - Yucheng Tang
- Department of Computer Science, Vanderbilt University, Nashville, TN, USA
| | - Shunxing Bao
- Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA
| | - Cailey Kerley
- Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA
| | - Micah D'Archangel
- Vanderbilt Brain Institute, Vanderbilt University, Nashville, TN, USA
| | - Laura A Barquero
- Vanderbilt Brain Institute, Vanderbilt University, Nashville, TN, USA
| | - Allen T Newton
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
- Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, TN, USA
| | - Isabel Gauthier
- Department of Psychology, Vanderbilt University, Nashville, TN, USA
| | | | - Benoit M Dawant
- Department of Computer Science, Vanderbilt University, Nashville, TN, USA
- Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA
| | - Laurie E Cutting
- Vanderbilt Brain Institute, Vanderbilt University, Nashville, TN, USA
| | - Yuankai Huo
- Department of Computer Science, Vanderbilt University, Nashville, TN, USA
- Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA
| | - Bennett A Landman
- Department of Computer Science, Vanderbilt University, Nashville, TN, USA
- Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
- Vanderbilt Brain Institute, Vanderbilt University, Nashville, TN, USA
- Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, TN, USA
| |
Collapse
|
2
|
Rheault F, Bayrak RG, Wang X, Schilling KG, Greer JM, Hansen CB, Kerley C, Ramadass K, Remedios LW, Blaber JA, Williams O, Beason-Held LL, Resnick SM, Rogers BP, Landman BA. TractEM: Evaluation of protocols for deterministic tractography white matter atlas. Magn Reson Imaging 2022; 85:44-56. [PMID: 34666161 PMCID: PMC8629950 DOI: 10.1016/j.mri.2021.10.017] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2021] [Revised: 08/25/2021] [Accepted: 10/12/2021] [Indexed: 01/03/2023]
Abstract
Reproducible identification of white matter pathways across subjects is essential for the study of structural connectivity of the human brain. One of the key challenges is anatomical differences between subjects and human rater subjectivity in labeling. Labeling white matter regions of interest presents many challenges due to the need to integrate both local and global information. Clearly communicating the manual processes to capture this information is cumbersome, yet essential to lay a solid foundation for comprehensive atlases. Segmentation protocols must be designed so the interpretation of the requested tasks as well as locating structural landmarks is anatomically accurate, intuitive and reproducible. In this work, we quantified the reproducibility of a first iteration of an open/public multi-bundle segmentation protocol. This allowed us to establish a baseline for its reproducibility as well as to identify the limitations for future iterations. The protocol was tested/evaluated on both typical 3 T research acquisition Baltimore Longitudinal Study of Aging (BLSA) and high-acquisition quality Human Connectome Project (HCP) datasets. The results show that a rudimentary protocol can produce acceptable intra-rater and inter-rater reproducibility. However, this work highlights the difficulty in generalizing reproducible results and the importance of reaching consensus on anatomical description of white matter pathways. The protocol has been made available in open source to improve generalizability and reliability in collaboration. The goal is to improve upon the first iteration and initiate a discussion on the anatomical validity (or lack thereof) of some bundle definitions and the importance of reproducibility of tractography segmentation.
Collapse
Affiliation(s)
- Francois Rheault
- Electrical Engineering, Vanderbilt University, Nashville, TN, USA.
| | - Roza G Bayrak
- Computer Science, Vanderbilt University, Nashville, TN, USA
| | - Xuan Wang
- Computer Science, Vanderbilt University, Nashville, TN, USA
| | - Kurt G Schilling
- Vanderbilt University Institute of Imaging Science, Nashville, TN, USA
| | - Jasmine M Greer
- Vanderbilt University Institute of Imaging Science, Nashville, TN, USA
| | - Colin B Hansen
- Computer Science, Vanderbilt University, Nashville, TN, USA
| | - Cailey Kerley
- Electrical Engineering, Vanderbilt University, Nashville, TN, USA
| | | | | | | | - Owen Williams
- Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Lori L Beason-Held
- Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Susan M Resnick
- Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Baxter P Rogers
- Vanderbilt University Institute of Imaging Science, Nashville, TN, USA; Department of Radiology and Radiological Sciences, Vanderbilt University, Nashville, TN, USA
| | - Bennett A Landman
- Electrical Engineering, Vanderbilt University, Nashville, TN, USA; Vanderbilt University Institute of Imaging Science, Nashville, TN, USA; Computer Science, Vanderbilt University, Nashville, TN, USA; Department of Radiology and Radiological Sciences, Vanderbilt University, Nashville, TN, USA
| |
Collapse
|
3
|
Hansen CB, Yang Q, Lyu I, Rheault F, Kerley C, Chandio BQ, Fadnavis S, Williams O, Shafer AT, Resnick SM, Zald DH, Cutting LE, Taylor WD, Boyd B, Garyfallidis E, Anderson AW, Descoteaux M, Landman BA, Schilling KG. Pandora: 4-D White Matter Bundle Population-Based Atlases Derived from Diffusion MRI Fiber Tractography. Neuroinformatics 2021; 19:447-460. [PMID: 33196967 PMCID: PMC8124084 DOI: 10.1007/s12021-020-09497-1] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/02/2020] [Indexed: 12/21/2022]
Abstract
Brain atlases have proven to be valuable neuroscience tools for localizing regions of interest and performing statistical inferences on populations. Although many human brain atlases exist, most do not contain information about white matter structures, often neglecting them completely or labelling all white matter as a single homogenous substrate. While few white matter atlases do exist based on diffusion MRI fiber tractography, they are often limited to descriptions of white matter as spatially separate "regions" rather than as white matter "bundles" or fascicles, which are well-known to overlap throughout the brain. Additional limitations include small sample sizes, few white matter pathways, and the use of outdated diffusion models and techniques. Here, we present a new population-based collection of white matter atlases represented in both volumetric and surface coordinates in a standard space. These atlases are based on 2443 subjects, and include 216 white matter bundles derived from 6 different automated state-of-the-art tractography techniques. This atlas is freely available and will be a useful resource for parcellation and segmentation.
Collapse
Affiliation(s)
- Colin B Hansen
- Department of Computer Science, Vanderbilt University, Nashville, TN, USA
| | - Qi Yang
- Department of Computer Science, Vanderbilt University, Nashville, TN, USA
| | - Ilwoo Lyu
- Department of Computer Science, Vanderbilt University, Nashville, TN, USA
- Department of Electrical Engineering, Vanderbilt University, Nashville, TN, USA
| | - Francois Rheault
- Sherbrooke Connectivity Imaging Laboratory (SCIL), Université de Sherbrooke, Sherbrooke, Canada
| | - Cailey Kerley
- Department of Electrical Engineering, Vanderbilt University, Nashville, TN, USA
| | - Bramsh Qamar Chandio
- Department of Intelligent Systems Engineering, Indiana University, Bloomington, IN, USA
| | - Shreyas Fadnavis
- Department of Intelligent Systems Engineering, Indiana University, Bloomington, IN, USA
| | - Owen Williams
- Laboratory of Behavioral Neuroscience, National Institute on Aging, Baltimore, MD, USA
| | - Andrea T Shafer
- Laboratory of Behavioral Neuroscience, National Institute on Aging, Baltimore, MD, USA
| | - Susan M Resnick
- Laboratory of Behavioral Neuroscience, National Institute on Aging, Baltimore, MD, USA
| | - David H Zald
- Center for Advanced Human Brain Imaging Research, Rutgers University, Piscataway, NJ, USA
| | - Laurie E Cutting
- Vanderbilt Kennedy Center, Vanderbilt University, Nashville, TN, USA
| | - Warren D Taylor
- Vanderbilt Kennedy Center, Vanderbilt University, Nashville, TN, USA
| | - Brian Boyd
- Vanderbilt Kennedy Center, Vanderbilt University, Nashville, TN, USA
| | - Eleftherios Garyfallidis
- Department of Intelligent Systems Engineering, Indiana University, Bloomington, IN, USA
- Program of Neuroscience, Indiana University, Bloomington, IN, USA
| | - Adam W Anderson
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
| | - Maxime Descoteaux
- Sherbrooke Connectivity Imaging Laboratory (SCIL), Université de Sherbrooke, Sherbrooke, Canada
| | - Bennett A Landman
- Department of Computer Science, Vanderbilt University, Nashville, TN, USA
- Department of Electrical Engineering, Vanderbilt University, Nashville, TN, USA
| | - Kurt G Schilling
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA.
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA.
| |
Collapse
|
4
|
Hutchinson K, Kerley C, Cormican L, Rochev Y, Faul J. The Association Between 25 Hydroxyvitamin D and Airway Obstruction in Asthma. Ir Med J 2016; 109:371. [PMID: 27685818] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
Since Vitamin D has anti-inflammatory effects we wondered whether the association between low serum 25OHD and airway obstruction in moderate persistent asthma might be explained by inflammatory pathways that worsen asthma. All subjects examined were Irish Caucasians with moderate persistent asthma and none took systemic steroid therapy. In addition to computerized spirometry, we measured BMI, serum 25-hydroxyvitamin D (25OHD), total IgE, Eosinophil Cationic Protein (ECP), and high sensitive C- reactive protein (hs-CRP). One hundred (47 male) subjects completed the testing. Within single level of asthma severity, 25OHD levels were related to post-bronchodilator FEV1/FVC (r = 0.26, p< 0.01), but multiple linear regression analysis demonstrated that the association was not explained by obesity or inflammatory markers. We find a relationship exists between airway obstruction and 25OHD levels in asthmatic adults, and the effect is not explained by the presence of potential confounders such as obesity, allergy and systemic inflammation.
Collapse
Affiliation(s)
| | - C Kerley
- BCF Diagnostics, Asthma Research Centre, Dublin 15
| | - L Cormican
- Department of Respiratory Medicine, Connolly Hospital, Blanchardstown, Dublin 15
| | - Y Rochev
- National University of Ireland, Galway
| | - J Faul
- Department of Respiratory Medicine, Connolly Hospital, Blanchardstown, Dublin 15
| |
Collapse
|
5
|
|