Evidence map›Paper›PMID 41293615›Full record

ArticleFrontiers in cardiovascular medicine2025

Quantitative cardiac CT perfusion: physiologically-inspired model and identifying microvascular disease from discordant CTA CAD-RADS.

Hao Wu, Yingnan Song, Ammar Hoori, Juhwan Lee, Sadeer Al-Kindi, Wei-Ming Huang, Chun-Ho Yun, Chung-Lieh Hung, Sanjay Rajagopalan, David L Wilson

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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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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

10 authors.

Hao WuDepartment of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States.
Yingnan SongDepartment of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States.
Ammar HooriDepartment of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States.
Juhwan LeeDepartment of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States.
Sadeer Al-KindiHarrington Heart and Vascular Institute, University Hospitals Cleveland Medical Center, Cleveland, OH, United States.
Wei-Ming HuangDepartment of Radiology, MacKay Memorial Hospital, Taipei, Taiwan.
Chun-Ho YunDepartment of Radiology, MacKay Memorial Hospital, Taipei, Taiwan.
Chung-Lieh HungDivision of Cardiology, Department of Internal Medicine, MacKay Memorial Hospital, Taipei, Taiwan.
Sanjay RajagopalanHarrington Heart and Vascular Institute, University Hospitals Cleveland Medical Center, Cleveland, OH, United States.
David L WilsonDepartment of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Use our advanced, physiologically inspired cardiac CT perfusion (CCTP) software to distinguish ischemia due to obstructive disease vs. microvascular disease (MVD). Background: Previously validated advanced CCTP methods were used. We interpreted results to identify flow-limiting stenosis [i.e., obstructive-lesion & low myocardial blood flow (MBF)] vs. microvascular disease (i.e., no-obstructive-lesion & low-MBF). Methods: We retrospectively evaluated 104 patients with suspected CAD, including 18 with diabetes, who underwent CCTA + CCTP. Whole heart and territorial MBF was assessed using our automated pipeline for CCTP analysis that included beam hardening correction; temporal scan registration; automated segmentation; fast, accurate, robust MBF estimation; and visualization. Stenosis severity was scored using the CCTA coronary-artery-disease-reporting-and-data-system (CAD-RADS), with obstructive stenosis deemed as CAD-RADS ≥ 3. Results: We established a threshold MBF (MBF = 200-mL/min-100 g) for normal perfusion. In patients with CAD-RADS ≥ 3 (obstructive disease), 28/37(76%) patients showed ischemia in the corresponding territory. On a per-vessel basis ( Conclusion: CCTA in conjunction with a new automated quantitative CCTP approach can determine the distinction of ischemia due to obstructive lesions vs. MVD.

Indexed as

cardiac CT perfusioncoronary CT angiographydeep learningflow-limiting stenosisimage processingmicrovascular disease

Identifiers

PMID41293615
PMCPMC12640952

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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.