Evidence map›Paper›PMID 39832899›Full record

ArticleJournal of neurointerventional surgery2025

Real-world evaluation of the accuracy of the Viz.AI automated intracranial hemorrhage volume calculation tool.

Ian Odland, Kayla J Liu, Dylan Wu, Kurt A Yaeger, Luis C Ascanio, Colton Smith, Braxton Riley Schuldt, Tirone Young, Christina P Rossitto, Margaret Downes and 7 more

Abstract read
In one paragraph

Article in Journal of neurointerventional surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–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

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. 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

17 authors.

Ian OdlandDepartment of Neurosurgery, Icahn School of Medicine at Mount Sinai, New York, New York, USA ian.odland@icahn.mssm.edu.ORCID http://orcid.org/0000-0002-2418-4479
Kayla J LiuDepartment of Neurosurgery, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
Dylan WuDepartment of Neurosurgery, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
Kurt A YaegerDepartment of Neurosurgery, Icahn School of Medicine at Mount Sinai, New York, New York, USA.ORCID http://orcid.org/0000-0001-7520-4743
Luis C AscanioDepartment of Neurosurgery, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
Colton SmithDepartment of Neurosurgery, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
Braxton Riley SchuldtDepartment of Neurosurgery, Icahn School of Medicine at Mount Sinai, New York, New York, USA.ORCID http://orcid.org/0000-0002-1737-707X
Tirone YoungDepartment of Neurosurgery, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
Christina P RossittoDepartment of Neurosurgery, Icahn School of Medicine at Mount Sinai, New York, New York, USA.ORCID http://orcid.org/0000-0001-8819-2198
Margaret DownesDepartment of Neurosurgery, Icahn School of Medicine at Mount Sinai, New York, New York, USA.ORCID http://orcid.org/0000-0003-2596-5151
Vikram VasanDepartment of Neurosurgery, Icahn School of Medicine at Mount Sinai, New York, New York, USA.ORCID http://orcid.org/0000-0003-2754-4107
Muhammad AliDepartment of Neurosurgery, Icahn School of Medicine at Mount Sinai, New York, New York, USA.ORCID http://orcid.org/0000-0002-6556-9156
Trevor HardiganDepartment of Neurosurgery, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
Tomoyoshi ShigematsuDepartment of Neurosurgery, Icahn School of Medicine at Mount Sinai, New York, New York, USA.ORCID http://orcid.org/0000-0003-3463-0222
Johanna T FifiDepartment of Neurosurgery, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
J MoccoDepartment of Neurosurgery, Icahn School of Medicine at Mount Sinai, New York, New York, USA.ORCID http://orcid.org/0000-0001-5489-2524
Christopher Paul KellnerDepartment of Neurosurgery, Icahn School of Medicine at Mount Sinai, New York, New York, USA.ORCID http://orcid.org/0000-0003-4604-8205

Funding

Training Future Leaders in Aging ResearchT35AG067578 · NIA · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI ALDRIDGE, MELISSA DIANE, SORIANO, RAINIER P · 2020 to 2024
$616k
NIA NIH HHS T35 AG067578
6 · The paper itself

Abstract

backgroundAppropriate management of spontaneous intracerebral hemorrhage (ICH) and intraventricular hemorrhage (IVH) requires rapid, accurate volume estimation. Viz.AI has developed an artificial intelligence (AI)-powered ICH calculation tool that may improve existing methods.

methodsAdult patients presenting to a large healthcare system between December 2015 and December 2021 with spontaneous ICH greater than 10mL and within 72 hours since ictus were analyzed for hematoma volume. mABC/2 (modified ABC/2) was measured by a board-certified neurosurgeon. Semi-autonomous segmentation (SAS) was performed by a trained medical student on 3D Slicer, adjudicated by a board-certified neurosurgeon and used as a surrogate ground-truth volume.

results139 CTs met inclusion criteria. Mean ICH volume via ground-truth SAS was 47.69±27.19 mL. Mean ICH volume difference between SAS and AI and SAS and mABC/2 was 4.77±4.06 mL and 8.36±9.48 mL, respectively (p<0.01). Bland-Altman plots yielded AI and SAS limits of agreement between -4.45 and 13.18 mL, and mABC/2 and SAS limits of agreement between -21.35 and 27.02 mL. The average absolute difference between IVH volume yielded by SAS and AI was 3.26±3.55 mL. Bland-Altman plots yielded IVH volume limits of agreement between -7.48 mLand 10.47 mL. AI was 94.6% sensitive and 94.0% specific for detecting IVH in the presence of ICH. The average time-to-volume for SAS and AI was 424±208 and 151±49.7 s (P<0.01), respectively.

conclusionViz.AI is more accurate than mABC/2, and more rapid than SAS. The combination of speed and accuracy makes Viz.AI viable for clinical decision-making and clinical trial use.

Indexed as

Artificial IntelligenceIntracranial HemorrhagesAdultAgedAged, 80 and overFemaleHumansImaging, Three-DimensionalMaleMiddle AgedRetrospective StudiesTomography, X-Ray ComputedCTHemorrhageStroke

Identifiers

PMID39832899
PMCPMC12276904

What OpenQuestion holds

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Registered trials

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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.