Evidence map›Paper›PMID 40450607›Full record

ArticleInternational journal of computer assisted radiology and surgery2025

Spatiotemporally constrained 3D reconstruction from biplanar digital subtraction angiography.

Sarah Frisken, Vivek Gopalakrishnan, David Dimitris Chlorogiannis, Nazim Haouchine, Alexandre Cafaro, Alexandra J Golby, William M Wells Iii, Rose Du

Abstract read
In one paragraph

Article in International journal of computer assisted radiology and surgery, 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.

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2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Sarah FriskenBrigham and Women's Hospital, Boston, USA. sfrisken@bwh.harvard.edu.ORCID http://orcid.org/0000-0001-5731-5095
Vivek GopalakrishnanBrigham and Women's Hospital, Boston, USA.
David Dimitris ChlorogiannisBrigham and Women's Hospital, Boston, USA.
Nazim HaouchineBrigham and Women's Hospital, Boston, USA.
Alexandre CafaroTheraPanacea, Paris, France.
Alexandra J GolbyBrigham and Women's Hospital, Boston, USA.
William M Wells IiiBrigham and Women's Hospital, Boston, USA.
Rose DuBrigham and Women's Hospital, Boston, USA.

Funding

Neuroimaging Training ProgramT32EB001680 · NIBIB · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI BRUCE R ROSEN · 2003 to 2026
$3.8M
Ultrasound based neurosurgical navigation with uncertainty visualizationR01EB032387 · NIBIB · BRIGHAM AND WOMEN'S HOSPITAL · PI FRISKEN, SARAH, GOLBY, ALEXANDRA J · 2022 to 2025
$2.0M
Generating High Quality, High Resolution, Patient-Specific 4D Models of Cerebral VasculatureR01EB034223 · NIBIB · BRIGHAM AND WOMEN'S HOSPITAL · PI SARAH FRISKEN · 2023 to 2026
$1.6M
New Tools for Enhancing Cerebral Angiography: From Planning to NavigationK25EB035166 · NIBIB · BRIGHAM AND WOMEN'S HOSPITAL · PI Nazim Haouchine · 2024 to 2026
$375k
Vessel Identification and Tracing in DSA Image Series for Cerebrovascular Surgical PlanningR03EB033910 · NIBIB · BRIGHAM AND WOMEN'S HOSPITAL · PI HAOUCHINE, NAZIM · 2023 to 2023
$179k
Foundation for the National Institutes of Health K25EB035166Foundation for the National Institutes of Health R01EB032387Foundation for the National Institutes of Health R01EB034223Foundation for the National Institutes of Health R03EB033910NIBIB NIH HHS K25 EB035166NIBIB NIH HHS R01 EB032387NIBIB NIH HHS R01 EB034223NIBIB NIH HHS R03 EB033910NIBIB NIH HHS T32 EB001680
6 · The paper itself

Abstract

purposeOur goal is to reconstruct 3D cerebral vessels from two 2D digital subtraction angiography (DSA) images acquired using a biplane scanner. This could provide intraoperative 3D imaging with 2-5 × spatial and 20 × temporal resolution of 3D magnetic resonance angiography, computed tomography angiography (CTA), or rotational DSA. Because many interventional radiology suites have biplane scanners, our method could be easily integrated into clinical workflows.

methodsWe present a constrained 3D reconstruction method that utilizes vessel centerlines, radii, and the flow of contrast agent through vessels from DSA. The reconstructed volume samples 'vesselness' at each voxel, i.e., its probability of containing a vessel. We present evaluation metrics which we used to optimize reconstruction parameters and evaluate our method on synthetic data. We provide preliminary results on clinical data. To handle clinical data, we developed a software tool for extracting vessel centerlines, radii, and contrast arrival times from clinical DSA. We provide an automated method for registering DSA to CTA which allows us to compare reconstructed vessels with vessels extracted from CTA.

resultOur method reduced reconstruction artifacts in vesselness volumes for both synthetic and clinical data. In synthetic DSA, where 3D ground-truth vessel centerlines are available, our constrained reconstruction method improved accuracy, selectivity, and Dice scores with two views compared to existing sparse reconstruction methods with up to 16 views.

conclusionIncorporating additional constraints into 3D reconstruction can successfully reduce artifacts introduced when a complex 3D structure like the brain vasculature is reconstructed from a small number of 2D views.

Indexed as

Angiography, Digital SubtractionCerebral AngiographyImaging, Three-DimensionalComputed Tomography AngiographyContrast MediaHumansContrast Media3D image reconstructionCerebrovascular diseaseDigital subtraction angiographyNeurovascular imaging

Identifiers

PMID40450607
PMCPMC12350070

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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.