Evidence map›Paper›PMID 40851670›Full record

ArticleProceedings. IEEE International Symposium on Biomedical Imaging2024

QUANTIFYING WHITE MATTER HYPERINTENSITY AND BRAIN VOLUMES IN HETEROGENEOUS CLINICAL AND LOW-FIELD PORTABLE MRI.

Pablo Laso, Stefano Cerri, Annabel Sorby-Adams, Jennifer Guo, Farrah Mateen, Philipp Goebl, Jiaming Wu, Peirong Liu, Hongwei Li, Sean I Young and 14 more

Abstract read
In one paragraph

Article in Proceedings. IEEE International Symposium on Biomedical Imaging, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.

0numbers the graph read from it
0cells of the map it votes in
37citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

37 citing papers in PubMed.

  1. Trial
  2. Vulnerability of locus coeruleus connections to aging and Alzheimer's disease.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026
    Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Review
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

24 authors.

Pablo LasoMassachusetts General Hospital, Harvard Medical School, USA.
Stefano CerriMassachusetts General Hospital, Harvard Medical School, USA.
Annabel Sorby-AdamsMassachusetts General Hospital, Harvard Medical School, USA.
Jennifer GuoMassachusetts General Hospital, Harvard Medical School, USA.
Farrah MateenMassachusetts General Hospital, Harvard Medical School, USA.
Philipp GoeblCentre for Medical Image Computing, University College London, UK.
Jiaming WuCentre for Medical Image Computing, University College London, UK.
Peirong LiuMassachusetts General Hospital, Harvard Medical School, USA.
Hongwei LiMassachusetts General Hospital, Harvard Medical School, USA.
Sean I YoungMassachusetts General Hospital, Harvard Medical School, USA.
Benjamin BillotComputer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, USA.
Oula PuontiMassachusetts General Hospital, Harvard Medical School, USA.
Gordon SzeYale School of Medicine, USA.
Sam PayabavashYale School of Medicine, USA.
Adam DeHavenonYale School of Medicine, USA.
Kevin N ShethYale School of Medicine, USA.
Matthew S RosenMassachusetts General Hospital, Harvard Medical School, USA.
John KirschMassachusetts General Hospital, Harvard Medical School, USA.
Nicola StrisciuglioElectrical Engineering, Mathematics and Computer Science, University of Twente, The Netherlands.
Jelmer M WolterinkElectrical Engineering, Mathematics and Computer Science, University of Twente, The Netherlands.
Arman EshaghiCentre for Medical Image Computing, University College London, UK.
Frederik BarkhofCentre for Medical Image Computing, University College London, UK.
W Taylor KimberlyMassachusetts General Hospital, Harvard Medical School, USA.
Juan Eugenio IglesiasMassachusetts General Hospital, Harvard Medical School, USA.

Funding

Functionally guided adult whole brain cell atlas in human and NHPUM1MH130981 · NIMH · ALLEN INSTITUTE · PI Ed Lein, Hongkui Zeng · 2022 to 2026
$91.9M
Acquisition-independent machine learning for morphometric analysis of underrepresented aging populations with clinical and low-field brain MRIRF1AG080371 · NIA · MASSACHUSETTS GENERAL HOSPITAL · PI Juan Eugenio Iglesias Gonzalez · 2023 to 2026
$4.0M
Portable, Low Field Brain Magnetic Resonance Imaging (MRI) for Acute StrokeR01EB031114 · NIBIB · YALE UNIVERSITY · PI William Taylor Kimberly, Matthew Scot Rosen · 2022 to 2026
$3.5M
Diagnosing the undiagnosable: studies of Alzheimer disease mimics and confounders via "neuropathometry" of dissection photos with 3D scanningR01AG070988 · NIA · MASSACHUSETTS GENERAL HOSPITAL · PI IGLESIAS GONZALEZ, JUAN EUGENIO · 2021 to 2025
$2.7M
Open-source software for multi-scale mapping of the human brainRF1MH123195 · NIMH · MASSACHUSETTS GENERAL HOSPITAL · PI FISCHL, BRUCE, IGLESIAS GONZALEZ, JUAN EUGENIO · 2020 to 2020
$2.0M
Computational Imaging Biomarkers of Multiple SclerosisR01NS112161 · NINDS · MASSACHUSETTS GENERAL HOSPITAL · PI VAN LEEMPUT, KOEN · 2019 to 2023
$1.5M
NIA NIH HHS R01 AG070988NIA NIH HHS RF1 AG080371NIBIB NIH HHS R01 EB031114NIMH NIH HHS RF1 MH123195NIMH NIH HHS UM1 MH130981NINDS NIH HHS R01 NS112161
6 · The paper itself

Abstract

Brain atrophy and white matter hyperintensity (WMH) are critical neuroimaging features for ascertaining brain injury in cerebrovascular disease and multiple sclerosis. Automated segmentation and quantification is desirable but existing methods require high-resolution MRI with good signal-to-noise ratio (SNR). This precludes application to clinical and low-field portable MRI (pMRI) scans, thus hampering large-scale tracking of atrophy and WMH progression, especially in underserved areas where pMRI has huge potential. Here we present a method that segments white matter hyperintensity and 36 brain regions from scans of any resolution and contrast (including pMRI) without retraining. We show results on eight public datasets and on a private dataset with paired high- and low-field scans (3T and 64mT), where we attain strong correlation between the WMH (

Identifiers

PMID40851670
PMCPMC12369672

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.