Evidence map›Paper›PMID 42344990›Full record

ArticleImaging neuroscience (Cambridge, Mass.)2025

Comparison of brain normalization software and lesion compensation techniques in chronic perinatal stroke imaging.

Gillian N Miller, Clara J Steeby, Jorge Ortega-Márquez, Alberto Castro Palacin, Carrie Chui, Kenda Alhadid, Alyssa W Sullivan, Aaron D Boes, Patricia L Musolino, Alexander L Cohen

Abstract read
In one paragraph

Article in Imaging neuroscience (Cambridge, Mass.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Gillian N MillerDepartment of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, United States.ORCID https://orcid.org/0009-0001-6306-8163
Clara J SteebyDepartment of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, United States.
Jorge Ortega-MárquezDepartment of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, United States.ORCID https://orcid.org/0009-0000-7534-384X
Alberto Castro PalacinDepartment of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, United States.
Carrie ChuiDepartment of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States.
Kenda AlhadidDepartment of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States.
Alyssa W SullivanDepartment of Psychological and Brain Sciences, University of Iowa, Iowa City, IA, United States.
Aaron D BoesDepartments of Pediatrics, Neurology, Psychiatry, Carver College of Medicine, University of Iowa, Iowa City, IA, United States.
Patricia L MusolinoDepartment of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States.
Alexander L CohenDepartment of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, United States.ORCID https://orcid.org/0000-0001-6557-5866

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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", that is, 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.

Indexed as

focal lesionsMRIneuroimagingperinatal strokeregistrationspatial normalization

Identifiers

PMID42344990
PMCPMC13288496

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.