Evidence map›Paper›PMID 40161447›Full record

ArticleInternational journal of imaging systems and technology2025

Quantitative Susceptibility Mapping MRI with Computer Vision Metrics to Reduce Scan Time for Brain Hemorrhage Assessment.

Huiyu Huang, Shreyas Balaji, Bulent Aslan, Yan Wen, Magdy Selim, Ajith J Thomas, Aristotelis Filippidis, Pascal Spincemaille, Yi Wang, Salil Soman

Abstract read
In one paragraph

Article in International journal of imaging systems and technology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

10 authors.

Huiyu HuangDepartment of Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA.
Shreyas BalajiDepartment of Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA.
Bulent AslanDepartment of Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA.
Yan WenGE Healthcare, Lincoln Medical Center, New York, NY, United States.
Magdy SelimDepartment of Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA.
Ajith J ThomasDepartment of Neurosurgery, Cooper University Health Care, Cooper Medical School of Rowan University, Camden, NJ USA.
Aristotelis FilippidisDepartment of Neurosurgery, Barrow Neurological Institute, Phoenix, Arizona, USA.
Pascal SpincemailleDepartment of Radiology, Weill Cornell Medicine, New York, NY, United States.
Yi WangDepartment of Radiology, Weill Cornell Medicine, New York, NY, United States.
Salil SomanDepartment of Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA.

Funding

StATins Use in intRacerebral hemorrhage patieNts (SATURN)U01NS102289 · NINDS · BETH ISRAEL DEACONESS MEDICAL CENTER · PI Magdy H Selim · 2019 to 2026
$15.7M
Quantitative Mapping of Substantia Nigra Iron in Parkinson's DiseaseR01NS095562 · NINDS · WEILL MEDICAL COLL OF CORNELL UNIV · PI SHTILBANS, ALEXANDER, WANG, YI · 2016 to 2022
$3.1M
StAtins Use in intRacereberal hemorrhage patieNts MRI (SATURN MRI) Ancillary StudyUF1NS120871 · NINDS · BETH ISRAEL DEACONESS MEDICAL CENTER · PI SELIM, MAGDY H, SHOAMANESH, ASHKAN · 2021 to 2021
$2.7M
Improved MRI Detection of Cerebral Microbleeds with Novel Susceptibility MappingR21NS109728 · NINDS · BETH ISRAEL DEACONESS MEDICAL CENTER · PI SOMAN, SALIL · 2020 to 2021
$491k
Quantitative Susceptibility Mapping (QSM) as a Non-Invasive Imaging Biomarker for Predicting Neurodegeneration in Alzheimer's DiseaseR21AG067466 · NIA · WEILL MEDICAL COLL OF CORNELL UNIV · PI KOVANLIKAYA, ILHAMI, WANG, YI · 2020 to 2020
$466k
NIA NIH HHS R21 AG067466NINDS NIH HHS R01 NS095562NINDS NIH HHS R21 NS109728NINDS NIH HHS U01 NS102289NINDS NIH HHS UF1 NS120871
6 · The paper itself

Abstract

Purpose: Optimizing clinical imaging parameters balances scan time and image quality. Quantitative Susceptibility Mapping (QSM) MRI, particularly for detecting intracranial hemorrhage (ICH), involves multiple echo times (TEs), leading to longer scan durations that can impact patient comfort and imaging efficiency. This study evaluates the necessity of specific TEs for QSM MRI in ICH patients and identifies shorter scan protocols using Computer Vision Metrics (CVMs) to maintain diagnostic accuracy. Approach: 54 patients with suspected ICH were retrospectively recruited. Multi-echo Gradient Recalled Echo (mGRE) sequences with 11 TEs were used for QSM MRI (reference). Subsets of TEs compatible with producing QSM MRI images were generated, producing 71 subgroups per patient. QSM images from each subgroup were compared to reference images using 14 CVMs. Linear regression and Wilcoxon Signed-Rank tests identified optimal subgroups minimizing scan time while preserving image quality as part of the computer vision Optimized Rapid Imaging (CORI) method described. Results: CVM based analysis demonstrated subgroup 1 (TE1-3) to be optimal using several CVMs, supporting a reduction in scan time from 4.5 to 1.23 minutes (73% reduction). Other CVMs suggested longer maximum TE subgroups as optimal, achieving scan time reductions of 9% to 37%. Visual assessments by a neuroradiologist and trained research assistant confirmed no significant difference in ICH area measurements between reference and CORI identified optimal subgroup derived QSM, while CORI identified worst subgroups derived QSM differed significantly (p < 0.05). Conclusions: The findings support using shorter QSM MRI protocols for ICH evaluation and suggest CVMs may aid optimization efforts for other clinical imaging protocols.

Indexed as

Computer Vision MetricsImage Quality AssessmentIntracranial HemorrhageMRI Protocol OptimizationQuantitative Susceptibility Mapping

Identifiers

PMID40161447
PMCPMC11951294

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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.