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Expert Panel on Cardiac Imaging, Renapurkar RD, Rajiah PS, Bartel TB, El-Sherief AH, Francois CJ, Hanneman K, Hsu JY, Jackson CD, Lenge de Rosen V, Safi LM, Sierra-Galan LM, Young PM, Bolen MA. ACR Appropriateness Criteria® Imaging for Pulmonary Embolism, Known Clot. J Am Coll Radiol 2025; 22:S261-S273. [PMID: 40409881 DOI: 10.1016/j.jacr.2025.02.028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2025] [Accepted: 02/24/2025] [Indexed: 05/25/2025]
Abstract
Acute pulmonary embolism (PE) is a common medical problem associated with high cardiovascular morbidity and mortality. Often, survivors of acute PE present with recurring symptoms and can have long-term functional sequela. Imaging plays a crucial role in initial evaluation of patients with suspected recurrent or residual PE with V/Q scan and CT angiography often used as the initial test of choice. In patients with known chronic thromboembolic disease, imaging is often used to map the disease burden, for surveillance and treatment planning; CT angiography is often used as the preliminary test for this purpose. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision process support the systematic analysis of the medical literature from peer reviewed journals. Established methodology principles such as Grading of Recommendations Assessment, Development, and Evaluation or GRADE are adapted to evaluate the evidence. The RAND/UCLA Appropriateness Method User Manual provides the methodology to determine the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where peer reviewed literature is lacking or equivocal, experts may be the primary evidentiary source available to formulate a recommendation.
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Affiliation(s)
| | | | | | - Twyla B Bartel
- Global Advanced Imaging, Little Rock, Arkansas; Commission on Nuclear Medicine and Molecular Imaging
| | | | | | - Kate Hanneman
- University Medical Imaging Toronto, Department of Medical Imaging, University of Toronto, Toronto, Ontario, Canada
| | - Joe Y Hsu
- Kaiser Permanente, Los Angeles, California
| | - Christopher D Jackson
- The University of Tennessee Health Science Center, Memphis, Tennessee; Society of General Internal Medicine
| | | | - Lucy M Safi
- Mount Sinai Hospital, New York, New York; American Society of Echocardiography
| | - Lilia M Sierra-Galan
- American British Cowdray Medical Center, Mexico City, Mexico; Society for Cardiovascular Magnetic Resonance
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Gawlitza J, Endres S, Fries P, Graf M, Wilkens H, Stroeder J, Buecker A, Massmann A, Ziegelmayer S. Machine learning assisted feature identification and prediction of hemodynamic endpoints using computed tomography in patients with CTEPH. Int J Cardiovasc Imaging 2024; 40:569-577. [PMID: 38143250 PMCID: PMC10950991 DOI: 10.1007/s10554-023-03026-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/18/2023] [Accepted: 11/24/2023] [Indexed: 12/26/2023]
Abstract
Chronic thromboembolic pulmonary hypertension (CTEPH) is a rare but potentially curable cause of pulmonary hypertension (PH). Currently PH is diagnosed by right heart catheterisation. Computed tomography (CT) is used for ruling out other causes and operative planning. This study aims to evaluate importance of different quantitative/qualitative imaging features and develop a supervised machine learning (ML) model to predict hemodynamic risk groups. 127 Patients with diagnosed CTEPH who received preoperative right heart catheterization and thoracic CTA examinations (39 ECG-gated; 88 non-ECG gated) were included. 19 qualitative/quantitative imaging features and 3 hemodynamic parameters [mean pulmonary artery pressure, right atrial pressure (RAP), pulmonary artery oxygen saturation (PA SaO2)] were gathered. Diameter-based CT features were measured in axial and adjusted multiplane reconstructions (MPR). Univariate analysis was performed for qualitative and quantitative features. A random forest algorithm was trained on imaging features to predict hemodynamic risk groups. Feature importance was calculated for all models. Qualitative and quantitative parameters showed no significant differences between ECG and non-ECG gated CTs. Depending on reconstruction plane, five quantitative features were significantly different, but mean absolute difference between parameters (MPR vs. axial) was 0.3 mm with no difference in correlation with hemodynamic parameters. Univariate analysis showed moderate to strong correlation for multiple imaging features with hemodynamic parameters. The model achieved an AUC score of 0.82 for the mPAP based risk stratification and 0.74 for the PA SaO2 risk stratification. Contrast agent retention in hepatic vein, mosaic attenuation pattern and the ratio right atrium/left ventricle were the most important features among other parameters. Quantitative and qualitative imaging features of reconstructions correlate with hemodynamic parameters in preoperative CTEPH patients-regardless of MPR adaption. Machine learning based analysis of preoperative imaging features can be used for non-invasive risk stratification. Qualitative features seem to be more important than previously anticipated.
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Affiliation(s)
- Joshua Gawlitza
- Clinic/Institute of Diagnostic and Interventional Radiology, Klinikum rechts der Isar, Technical University of Munich, Ismaninger Straße 22, 81675, Munich, Germany.
| | - Sophie Endres
- Clinic for Diagnostic and Interventional Radiology, Saarland University Medical Center, Kirrberger Strasse 100 (Building 41), 66424, Homburg, Germany
| | - Peter Fries
- Clinic for Diagnostic and Interventional Radiology, Saarland University Medical Center, Kirrberger Strasse 100 (Building 41), 66424, Homburg, Germany
| | - Markus Graf
- Clinic/Institute of Diagnostic and Interventional Radiology, Klinikum rechts der Isar, Technical University of Munich, Ismaninger Straße 22, 81675, Munich, Germany
| | - Heinrike Wilkens
- Cardiology, Angiology, Pulmonary and Intensive Care, Saarland University Medical Center, Kirrberger Strasse 100, 66424, Homburg, Germany
| | - Jonas Stroeder
- Department of Radiology and Nuclear Medicine, University Hospital Schleswig-Holstein, Campus Lübeck, Lübeck, Germany
| | - Arno Buecker
- Clinic for Diagnostic and Interventional Radiology, Saarland University Medical Center, Kirrberger Strasse 100 (Building 41), 66424, Homburg, Germany
| | - Alexander Massmann
- Department of Radiology and Nuclear Medicine, Robert-Bosch-Krankenhaus, Auerbachstr. 110, 70376, Stuttgart, Germany
| | - Sebastian Ziegelmayer
- Clinic/Institute of Diagnostic and Interventional Radiology, Klinikum rechts der Isar, Technical University of Munich, Ismaninger Straße 22, 81675, Munich, Germany
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Yamaguchi T, Ehara S, Yoshida H, Himoto D, Izuta S, Hayashi O, Hayashi H, Ogawa M, Shibata A, Yamazaki T, Izumiya Y, Fukuda D. Quantification of pulmonary perfusion using LSIM-CT correlates with pulmonary hemodynamics in patients with CTEPD. Front Cardiovasc Med 2023; 10:1237296. [PMID: 38028450 PMCID: PMC10654960 DOI: 10.3389/fcvm.2023.1237296] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Accepted: 10/04/2023] [Indexed: 12/01/2023] Open
Abstract
Background Lung subtraction iodine mapping (LSIM)-CT is a clinically useful technique that can visualize pulmonary mal-perfusion in patients with chronic thromboembolic pulmonary disease (CTEPD). However, little is known about the associations of LSIM images with hemodynamic parameters of patients with CTEPD. This study investigates a parameter of LSIM images associated with mean pulmonary arterial pressure (mPAP) and validates the association between pulmonary vascular resistance, right atrial pressure, cardiac index, and exercise capacity in patients with CTEPD. Methods This single-center, prospective, observational study involved 30 patients diagnosed with CTEPD using lung perfusion scintigraphy. To examine the correlation of decreased pulmonary perfusion area (DPA) with mPAP, areas with 0-10, 0-15, 0-20, and 0-30 HU in lung subtraction images were adopted in statistical analysis. The DPA to total lung volume ratio (DPA ratio, %) was calculated as the ratio of each DPA volume to the total lung volume. To assess the correlation between DPA ratios of 0-10, 0-15, 0-20, and 0-30 HU and mPAP, Spearman's rank correlation coefficient was used. Results The DPA ratio of 0-10 HU had the most preferable correlation with mPAP than DPA ratios of 0-15, 0-20, and 0-30 HU (ρ = 0.440, P = 0.015). The DPA ratio of 0-10 HU significantly correlates with pulmonary vascular resistance (ρ = 0.445, P = 0.015). The receiver operating characteristic curve analysis indicated that the best cutoff value of the DPA ratio of 0-10 HU for the prediction of an mPAP of ≥30 mmHg was 8.5% (AUC, 0.773; 95% CI, 0.572-0.974; sensitivity, 83.3%; specificity, 75.0%). Multivariate linear regression analysis, which was adjusted for the main pulmonary arterial to ascending aortic diameter ratio and right ventricular to left ventricular diameter ratio, indicated that the DPA ratio of 0-10 HU was independently and significantly associated with mPAP (B = 89.7; 95% CI, 46.3-133.1, P < 0.001). Conclusion The DPA ratio calculated using LSIM-CT is possibly useful for estimating the hemodynamic status in patients with CTEPD.
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Affiliation(s)
- Tomohiro Yamaguchi
- Department of Cardiovascular Medicine, Osaka Metropolitan University Graduate School of Medicine, Osaka, Japan
| | - Shoichi Ehara
- Department of Intensive Care Medicine, Osaka Metropolitan University Graduate School of Medicine, Osaka, Japan
| | - Hisako Yoshida
- Department of Medical Statistics, Osaka Metropolitan University Graduate School of Medicine, Osaka, Japan
| | - Daisuke Himoto
- Department of Radiology, Osaka Metropolitan University Hospital, Osaka, Japan
| | - Shinichiro Izuta
- Department of Radiology, Osaka Metropolitan University Hospital, Osaka, Japan
| | - Ou Hayashi
- Department of Cardiovascular Medicine, Osaka Metropolitan University Graduate School of Medicine, Osaka, Japan
| | - Hiroya Hayashi
- Department of Cardiovascular Medicine, Osaka Metropolitan University Graduate School of Medicine, Osaka, Japan
| | - Mana Ogawa
- Department of Cardiovascular Medicine, Osaka Metropolitan University Graduate School of Medicine, Osaka, Japan
| | - Atsushi Shibata
- Department of Cardiovascular Medicine, Osaka Metropolitan University Graduate School of Medicine, Osaka, Japan
| | - Takanori Yamazaki
- Department of Cardiovascular Medicine, Osaka Metropolitan University Graduate School of Medicine, Osaka, Japan
| | - Yasuhiro Izumiya
- Department of Cardiovascular Medicine, Osaka Metropolitan University Graduate School of Medicine, Osaka, Japan
| | - Daiju Fukuda
- Department of Cardiovascular Medicine, Osaka Metropolitan University Graduate School of Medicine, Osaka, Japan
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Lanham S, Maiter A, Swift AJ, Dwivedi K, Alabed S, Evans O, Sharkey MJ, Matthews S, Johns CS. The reproducibility of manual RV/LV ratio measurement on CT pulmonary angiography. BJR Open 2022; 4:20220041. [PMID: 38495814 PMCID: PMC10941330 DOI: 10.1259/bjro.20220041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2022] [Accepted: 09/18/2022] [Indexed: 11/29/2022] Open
Abstract
Objectives Right ventricular (RV) dysfunction carries elevated risk in acute pulmonary embolism (PE). An increased ratio between the size of the right and left ventricles (RV/LV ratio) is a biomarker of RV dysfunction. This study evaluated the reproducibility of RV/LV ratio measurement on CT pulmonary angiography (CTPA). Methods 20 inpatient CTPA scans performed to assess for acute PE were retrospectively identified from a tertiary UK centre. Each scan was evaluated by 14 radiologists who provided a qualitative overall opinion on the presence of RV dysfunction and measured the RV/LV ratio. Using a threshold of 1.0, the RV/LV ratio measurements were classified as positive (≥1.0) or negative (<1.0) for RV dysfunction. Interobserver agreement was quantified using the Fleiss κ and intraclass correlation coefficient (ICC). Results Qualitative opinion of RV dysfunction showed weak agreement (κ = 0.42, 95% CI 0.37-0.46). The mean RV/LV ratio measurement for all cases was 1.28 ± 0.68 with significant variation between reporters (p < 0.001). Although agreement for RV/LV measurement was good (ICC = 0.83, 95% CI 0.73-0.91), categorisation of RV dysfunction according to RV/LV ratio measurements showed weak agreement (κ = 0.46, 95% CI 0.41-0.50). Conclusion Both qualitative opinion and quantitative manual RV/LV ratio measurement show poor agreement for identifying RV dysfunction on CTPA. Advances in knowledge Caution should be exerted if using manual RV/LV ratio measurements to inform clinical risk stratification and management decisions.
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Affiliation(s)
- Sarah Lanham
- Department of Clinical Radiology, Sheffield Teaching Hospitals
NHS Foundation Trust, Sheffield, United Kingdom
| | - Ahmed Maiter
- Department of Clinical Radiology, Sheffield Teaching Hospitals
NHS Foundation Trust, Sheffield, United Kingdom
- Department of Infection, Immunity and Cardiovascular Disease,
University of Sheffield, Sheffield, United Kingdom
| | - Andrew J Swift
- Department of Clinical Radiology, Sheffield Teaching Hospitals
NHS Foundation Trust, Sheffield, United Kingdom
- Department of Infection, Immunity and Cardiovascular Disease,
University of Sheffield, Sheffield, United Kingdom
- INSIGNEO Institute for In Silico Medicine, University of
Sheffield, Sheffield, United Kingdom
| | - Krit Dwivedi
- Department of Clinical Radiology, Sheffield Teaching Hospitals
NHS Foundation Trust, Sheffield, United Kingdom
- Department of Infection, Immunity and Cardiovascular Disease,
University of Sheffield, Sheffield, United Kingdom
- INSIGNEO Institute for In Silico Medicine, University of
Sheffield, Sheffield, United Kingdom
| | - Samer Alabed
- Department of Clinical Radiology, Sheffield Teaching Hospitals
NHS Foundation Trust, Sheffield, United Kingdom
- Department of Infection, Immunity and Cardiovascular Disease,
University of Sheffield, Sheffield, United Kingdom
- INSIGNEO Institute for In Silico Medicine, University of
Sheffield, Sheffield, United Kingdom
| | - Oscar Evans
- Department of Clinical Radiology, Sheffield Teaching Hospitals
NHS Foundation Trust, Sheffield, United Kingdom
| | - Michael J Sharkey
- Department of Infection, Immunity and Cardiovascular Disease,
University of Sheffield, Sheffield, United Kingdom
- INSIGNEO Institute for In Silico Medicine, University of
Sheffield, Sheffield, United Kingdom
| | - Suzanne Matthews
- Department of Clinical Radiology, Sheffield Teaching Hospitals
NHS Foundation Trust, Sheffield, United Kingdom
| | - Christopher S Johns
- Department of Clinical Radiology, Sheffield Teaching Hospitals
NHS Foundation Trust, Sheffield, United Kingdom
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