Evidence map›Paper›PMID 39426860›Full record

ArticleJournal of cardiovascular computed tomography

Impact of an institutional process change adopting end-systolic coronary CTA acquisition and automated dose selection on patient throughput and image quality.

Nisha Hosadurg, Kara Harrison, Joseph Dan Khoa Nguyen, Patricia Rodriguez Lozano, Christopher M Kramer, Patrick T Norton, Amit R Patel, Todd C Villines

Abstract read
In one paragraph

Article in Journal of cardiovascular computed tomography. 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

What it found

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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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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

8 authors.

Nisha HosadurgDivision of Cardiovascular Medicine, Department of Medicine, University of Virginia School of Medicine, Charlottesville, VA, USA.
Kara HarrisonDepartment of Medicine, University of Virginia School of Medicine, Charlottesville, VA, USA.
Joseph Dan Khoa NguyenUniversity of Virginia School of Medicine, Charlottesville, VA, USA.
Patricia Rodriguez LozanoDivision of Cardiovascular Medicine, Department of Medicine, University of Virginia School of Medicine, Charlottesville, VA, USA; Division of Noninvasive Cardiovascular Imaging, Department of Radiology and Medical Imaging, University of Virginia School of Medicine, Charlottesville, VA, USA.
Christopher M KramerDivision of Cardiovascular Medicine, Department of Medicine, University of Virginia School of Medicine, Charlottesville, VA, USA; Division of Noninvasive Cardiovascular Imaging, Department of Radiology and Medical Imaging, University of Virginia School of Medicine, Charlottesville, VA, USA.
Patrick T NortonDivision of Noninvasive Cardiovascular Imaging, Department of Radiology and Medical Imaging, University of Virginia School of Medicine, Charlottesville, VA, USA.
Amit R PatelDivision of Cardiovascular Medicine, Department of Medicine, University of Virginia School of Medicine, Charlottesville, VA, USA; Division of Noninvasive Cardiovascular Imaging, Department of Radiology and Medical Imaging, University of Virginia School of Medicine, Charlottesville, VA, USA.
Todd C VillinesDivision of Cardiovascular Medicine, Department of Medicine, University of Virginia School of Medicine, Charlottesville, VA, USA; Division of Noninvasive Cardiovascular Imaging, Department of Radiology and Medical Imaging, University of Virginia School of Medicine, Charlottesville, VA, USA. Electronic address: tv4bc@virginia.edu.

Funding

Project 4: APOB-specific CD4 and CD8 T cells exacerbate atherosclerosisP01HL136275 · NHLBI · LA JOLLA INSTITUTE FOR IMMUNOLOGY · PI Catherine C Hedrick · 2017 to 2026
$25.5M
The integrated Translational Health Research Institute of Virginia (iTHRIV): Using Data to Improve HealthUL1TR003015 · NCATS · UNIVERSITY OF VIRGINIA · PI BROWN, DONALD E, JOHNSTON, KAREN C. · 2019 to 2023
$20.3M
Comprehensive Magnetic Resonance in PADR01HL075792 · NHLBI · UNIVERSITY OF VIRGINIA CHARLOTTESVILLE · PI KRAMER, CHRISTOPHER M. · 2003 to 2021
$10.5M
Training in Cardiovascular Imaging ResearchT32EB003841 · NIBIB · UNIVERSITY OF VIRGINIA CHARLOTTESVILLE · PI Jonathan R Lindner · 2004 to 2026
$4.4M
Institutional Career Development CoreKL2TR003016 · NCATS · UNIVERSITY OF VIRGINIA · PI PAPIN, JASON, WORRALL, BRADFORD B · 2019 to 2023
$3.9M
Innovative Therapy to Treat Women with Angina with Nonobstructive CAD (ANOCA) and Coronary Microvascular DiseaseK01HL174889 · NHLBI · UNIVERSITY OF VIRGINIA · PI Patricia Fiorella Rodriguez Lozano · 2024 to 2026
$486k
NCATS NIH HHS KL2 TR003016NCATS NIH HHS UL1 TR003015NHLBI NIH HHS K01 HL174889NHLBI NIH HHS P01 HL136275NHLBI NIH HHS R01 HL075792NIBIB NIH HHS T32 EB003841
6 · The paper itself

Abstract

introductionGuidelines recommend prospective ECG-triggered mid-diastolic coronary computed tomographic angiography (CCTA) acquisition after achieving optimal heart rate (HR) control in order to optimize scan image quality. With dual-source CCTA, prospective end-systolic acquisition has been shown to be less prone to motion artifacts at higher heart rates and may improve scan and CT laboratory efficiency by allowing CCTA without routine pre-scan beta-blocker (BB) administration.

methodsWe implemented an institutional process change in CCTA performance effective January 2023, comprising a transition from prospective ECG-triggered mid-diastolic acquisitions individually supervised by a physician at the scanner to an algorithmic approach predominately utilizing prospective end-systolic acquisition (200-400 ​ms after R peak), employing an automated dose selection algorithm, without BB administration. All scans were performed on a third-generation 192-slice dual-source scanner. We reviewed 300 consecutive CCTAs done pre- and post-process change in Jan 2022 (phase 0), Jan 2023 (phase 1), and in May 2023 (phase 2) after implementation of a process improvement involving more selective utilization of automated tube potential/current algorithms (CARE kV) to optimize image quality. Coronary segmental image quality was assessed by two experienced CCTA readers by consensus using an 18-segment SCCT model on a 5-point Likert scale (1 ​= ​non-interpretable; 2 ​= ​poor; 3 ​= ​acceptable; 4 ​= ​good; 5 ​= ​excellent). Measures of radiation dose, medication administration, and time required for patient scanning were compared. Logistic regression was used to determine factors associated with patient-level reduction in image quality (IQ) and with repeat scans.

resultsPost-process change, there was a significant reduction in the median overall patient appointment [phase 0: 95 (75-125) min vs. phase 1: 68 (52-88) min and phase 2: 72 (59-90) min; P ​< ​0.001] and scan times [phase 0: 13 (10-16) min vs. phase 1: 8 (6-13) min and phase 2: 9 (7-13) min; P ​< ​0.001]. Median IQ score in both post-process change phases was 4 (4-5) compared to a median score of 5 (4-5) pre-process change (P for comparison <0.001). The majority of segments post-process change had "good" IQ (Phase 1 segmental IQ scores: 5 ​= ​36.7 ​%, 4 ​= ​46.8 ​%, 3 ​= ​13 ​%, 2 ​= ​2.6 ​%, 1 ​= ​0.9 ​%; Phase 2 segmental IQ scores: 5 ​= ​26 ​%, 4 ​= ​49.7 ​%, 3 ​= ​16.3 ​%, 2 ​= ​6.1 ​%, 1 ​= ​1.9 ​%), whereas pre-process change, the majority of segments had "excellent" IQ (Phase 0 segmental IQ scores: 5 ​= ​56 ​%, 4 ​= ​34.3 ​%, 3 ​= ​7.5 ​%, 2 ​= ​1.8 ​%, 1 ​= ​0.4 ​%) There was no significant increase in non-interpretable scans at the patient level. The 22 ​% re-scan rate in phase 1 (vs. 6 ​% in phase 0, P ​= ​.002) improved to 15 ​% in phase 2. While patient related factors of body mass index [adjusted OR obese 2.64, 95 ​% CI 1.12-6.51, P ​= ​0.03; aOR morbidly obese 6.94, 95 ​% CI 2.21-23.52, P ​= ​0.001] and average HR [aOR (per 10 bpm increase) 1.51, 95 ​% CI 1.21-1.9, P ​< ​0.001] were associated with the scoring of any segment as ​≤ ​3 ​at the patient level in a fully adjusted model, the improved phase 2 of the process change was not [aOR 1.61, 95 ​% CI 0.78-3.32].

conclusionImplementation of an institutional process change utilizing prospective ECG-triggered dual-source end-systolic acquisition avoided the use of beta-blockers, significantly reduced patient appointment and scan times with acceptable diagnostic performance.

Indexed as

Cardiac-Gated Imaging TechniquesComputed Tomography AngiographyCoronary AngiographyCoronary Artery DiseaseCoronary VesselsMultidetector Computed TomographyRadiation DosageRadiation ExposureAgedAlgorithmsAutomationElectrocardiographyFemaleHeart RateHumansMaleCardiac computed tomographyCoronary CT angiographyImage qualityProcess changeRadiation

Identifiers

PMID39426860
PMCPMC11829828

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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.