Journal article
Comparison of Brain Normalization Software and Lesion Compensation Techniques in Chronic Perinatal Stroke Imaging
Imaging neuroscience (Cambridge, Mass.), Vol.3, IMAGa1048
2025
DOI: 10.1162/IMAG.a.1048
Abstract
Neuroimaging research depends on registration, the alignment of patients’ brains to a template or standard space, to enable accurate comparisons across individuals. Decades of work have advanced our ability to accurately register typical brains, but registering atypical brains, such as those with injury or highly distorted anatomy, remains a challenge. In particular, registration of perinatal stroke imaging is often complicated by delayed injury identification, which results in imaging obtained during the chronic stage where secondary structural impacts are evident. While analyses in native space can be valuable for subject-specific investigations, group-level studies require registration to a common template space, which enables between-subject comparisons of lesion locations and their network correlates. Although many registration algorithms exist, as do various compensation techniques for focal lesions, it is unclear how effective they are when applied to the highly distorted anatomy often present in this chronic perinatal stroke imaging. Here, we quantitatively and qualitatively compared the performance of three registration algorithms (FNIRT, ANTs, EasyReg) in registering eleven variably distorted brains with perinatal stroke to a standard template using their default lesion-compensation techniques. We also assessed the impact of “brain grafting”, i.e., inserting a healthy tissue mask in place of the defined lesion area prior to registration. Our findings show that ANTs and EasyReg are significantly more accurate than FNIRT for chronic perinatal stroke imaging, although all three software packages have marked difficulty with large lesions. Notably, brain grafting significantly improved the lesion mask normalization performance of FNIRT. In light of these comparisons, the recently released EasyReg appears to be an appropriate starting point for registering cohorts with chronic perinatal strokes, but we still emphasize the necessity of consistent visual inspection of registered brains.
Details
- Title: Subtitle
- Comparison of Brain Normalization Software and Lesion Compensation Techniques in Chronic Perinatal Stroke Imaging
- Creators
- Gillian N. Miller - Boston Children's HospitalClara J. Steeby - Harvard UniversityJorge Ortega-Márquez - Harvard UniversityAlberto Castro Palacin - Harvard UniversityCarrie Chui - Massachusetts General HospitalKenda Alhadid - Massachusetts General HospitalAlyssa W. Sullivan - University of IowaAaron D. Boes - University of IowaPatricia L. Musolino - Massachusetts General HospitalAlexander L. Cohen - Brigham and Women's Hospital
- Resource Type
- Journal article
- Publication Details
- Imaging neuroscience (Cambridge, Mass.), Vol.3, IMAGa1048
- DOI
- 10.1162/IMAG.a.1048
- ISSN
- 2837-6056
- eISSN
- 2837-6056
- Publisher
- MIT Press
- Grant note
- National Institute of Neurological Disorders and Stroke: R01 NS114405-03, R01NS117575-05 Simons FoundationNIH: K23MH120510 Children's Miracle NetworkRoy J. Carver Trust
A.D.B. was supported by the National Institute of Neurological Disease and Stroke (R01 NS114405-03), The Children's Miracle Network, and the Roy J. Carver Trust. P.L.M. was funded by the National Institute of Neurological Disorders and Stroke (R01NS117575-05). A.L.C. was supported by the NIH (K23MH120510) and the Simons Foundation.
- Language
- English
- Electronic publication date
- 11/18/2025
- Date published
- 2025
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering; Neurology; Psychiatry; Stead Family Department of Pediatrics; Iowa Neuroscience Institute; Neurology (Pediatrics)
- Record Identifier
- 9985033849002771
Metrics
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