Evidence map›Paper›PMID 41602341›Full record

ArticleFrontiers in cardiovascular medicine2025

CT-based visualization of aortic valve morphology: from 3D energy-integrating CT to 4D photon counting CT.

Alison M Pouch, Jessie N Dong, Harold I Litt, Brittany J Cannon, Melanie Freas, Victor Ferrari, Thomas G Gleason, Matthew A Jolley, Natalie Yushkevich, Jessica Nunez and 6 more

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Article in Frontiers in cardiovascular medicine, 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

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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

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

16 authors.

Alison M PouchDepartment of Radiology, University of Pennsylvania, Philadelphia, PA, United States.
Jessie N DongDepartment of Bioengineering, University of Pennsylvania, Philadelphia, PA, United States.
Harold I LittDepartment of Radiology, University of Pennsylvania, Philadelphia, PA, United States.
Brittany J CannonDivision of Cardiovascular Surgery, Department of Surgery, University of Pennsylvania, Philadelphia, PA, United States.
Melanie FreasDivision of Cardiovascular Surgery, Department of Surgery, University of Pennsylvania, Philadelphia, PA, United States.
Victor FerrariDivision of Cardiovascular Medicine, Department of Medicine, University of Pennsylvania, Philadelphia, PA, United States.
Thomas G GleasonAsheville Heart, Asheville, NC, United States.
Matthew A JolleyDivision of Cardiothoracic Anesthesiology, Department of Anesthesiology and Critical Care Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, United States.
Natalie YushkevichDepartment of Radiology, University of Pennsylvania, Philadelphia, PA, United States.
Jessica NunezDepartment of Radiology, University of Pennsylvania, Philadelphia, PA, United States.
Jilei HaoDepartment of Radiology, University of Pennsylvania, Philadelphia, PA, United States.
Zaiyang GuoDepartment of Bioengineering, University of Pennsylvania, Philadelphia, PA, United States.
Shir GoldfingerDepartment of Radiology, University of Pennsylvania, Philadelphia, PA, United States.
John KellyDivision of Cardiovascular Surgery, Department of Surgery, University of Pennsylvania, Philadelphia, PA, United States.
Joseph E BavariaDepartment of Cardiac Surgery, Thomas Jefferson University, Philadelphia, PA, United States.
Nimesh D DesaiDivision of Cardiovascular Surgery, Department of Surgery, University of Pennsylvania, Philadelphia, PA, United States.

Funding

4D Multimodal Image-Based Modeling for Bicuspid Aortic Valve Repair SurgeryR01HL163202 · NHLBI · UNIVERSITY OF PENNSYLVANIA · PI Alison Marie Pouch · 2022 to 2026
$3.5M
NHLBI NIH HHS R01 HL163202
6 · The paper itself

Abstract

Background: While 4D contrast-enhanced computed tomography (CT) is used to plan cardiovascular interventions such as transcatheter valve replacement, it is not yet routinely used to characterize minimally calcified aortic valves for planning of surgical valve repair. It is widely recognized that aortic valve morphology has implications for the durability of valve repair surgery. Purpose: The objective is to demonstrate the potential of CT image segmentation for elucidating aortic valve morphology prior to surgery and to illustrate a potential benefit of 4D CT and photon counting CT (PCCT) for patient-specific modeling of dysmorphic aortic valves. Materials and methods: This observational series includes nine patients who were suspected to have minimally calcified bicuspid aortic valve morphology on transthoracic echocardiography (TTE). Mean age was 53 +/- 13 years and seven patients were male. For the seven patients who underwent aortic root surgery, CT-based segmentation of the aortic valve was compared to echocardiographic interpretation and direct intraoperative visualization of valve morphology. Two patients who have not yet undergone aortic surgery were imaged longitudinally with 4D energy-integrating detector CT (EID-CT) and 4D PCCT, and the morphological interpretation of the aortic valve was compared to previous TTE reports. Results: In most surgical cases, CT-based segmentation and direct visualization of the valve revealed morphological features not previously confirmed on TTE, particularly related to the cusp fusion pattern. Moreover, 4D CT enabled morphological assessment at both systole and diastole, which captured maximal cusp separation and valve closure. PCCT images were reconstructed with slice thickness as low as 0.2 mm, and revealed detailed dysmorphic features such as a small accessory cusp with fistula and a double raphe in separate patients. Conclusion: 4D CT-based segmentation has the potential to dynamically capture aortic valve features that are relevant to risk stratification and surgical planning at high spatial resolution.

Indexed as

4D computed tomographyaortic valve (bicuspid)photon counting computed tomographysurgical planningvalve repair

Identifiers

PMID41602341
PMCPMC12833349

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