Andrew J Swift1, Smitha Rajaram2, Judith Hurdman3, Catherine Hill4, Christine Davies4, Tom W Sproson2, Allison C Morton5, Dave Capener2, Charlie Elliot5, Robin Condliffe5, Jim M Wild6, David G Kiely5. 1. Unit of Academic Radiology, University of Sheffield, Sheffield, England; National Institute of Health Research, Cardiovascular Biomedical Research Unit, Sheffield, England. Electronic address: a.j.swift@shef.ac.uk. 2. Unit of Academic Radiology, University of Sheffield, Sheffield, England. 3. Sheffield Pulmonary Vascular Disease Unit, Royal Hallamshire Hospital, Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield, England. 4. Radiology Department, Sheffield Teaching Hospitals Trust, Sheffield, England. 5. National Institute of Health Research, Cardiovascular Biomedical Research Unit, Sheffield, England; Sheffield Pulmonary Vascular Disease Unit, Royal Hallamshire Hospital, Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield, England. 6. Unit of Academic Radiology, University of Sheffield, Sheffield, England; Sheffield Pulmonary Vascular Disease Unit, Royal Hallamshire Hospital, Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield, England.
Abstract
OBJECTIVES: The aim of this study was to develop a composite numerical model based on parameters from cardiac magnetic resonance (CMR) imaging for noninvasive estimation of the key hemodynamic measurements made at right heart catheterization (RHC). BACKGROUND: Diagnosis and assessment of disease severity in patients with pulmonary hypertension is reliant on hemodynamic measurements at RHC. A robust noninvasive approach that can estimate key RHC measurements is desirable. METHODS: A derivation cohort of 64 successive, unselected, treatment naive patients with suspected pulmonary hypertension from the ASPIRE (Assessing the Spectrum of Pulmonary Hypertension Identified at a Referral Centre) Registry, underwent RHC and CMR within 12 h. Predicted mean pulmonary arterial pressure (mPAP) was derived using multivariate regression analysis of CMR measurements. The model was tested in an independent prospective validation cohort of 64 patients with suspected pulmonary hypertension. Surrogate measures of pulmonary capillary wedge pressure (PCWP) and cardiac output (CO) were estimated by left atrial volumetry and pulmonary arterial phase contrast imaging, respectively. Noninvasive pulmonary vascular resistance (PVR) was calculated from the CMR-derived measurements, defined as: (CMR-predicted mPAP - CMR-predicted PCWP)/CMR phase contrast CO. RESULTS: The following composite statistical model of mPAP was derived: CMR-predicted mPAP = -4.6 + (interventricular septal angle × 0.23) + (ventricular mass index × 16.3). In the validation cohort a strong correlation between mPAP and MR estimated mPAP was demonstrated (R(2) = 0.67). For detection of the presence of pulmonary hypertension the area under the receiver-operating characteristic (ROC) curve was 0.96 (0.92 to 1.00; p < 0.0001). CMR-estimated PVR reliably identified invasive PVR ≥3 Wood units (WU) with a high degree of accuracy, the area under the ROC curve was 0.94 (0.88 to 0.99; p < 0.0001). CONCLUSIONS: CMR imaging can accurately estimate mean pulmonary artery pressure in patients with suspected pulmonary hypertension and calculate PVR by estimating all major pulmonary hemodynamic metrics measured at RHC.
OBJECTIVES: The aim of this study was to develop a composite numerical model based on parameters from cardiac magnetic resonance (CMR) imaging for noninvasive estimation of the key hemodynamic measurements made at right heart catheterization (RHC). BACKGROUND: Diagnosis and assessment of disease severity in patients with pulmonary hypertension is reliant on hemodynamic measurements at RHC. A robust noninvasive approach that can estimate key RHC measurements is desirable. METHODS: A derivation cohort of 64 successive, unselected, treatment naive patients with suspected pulmonary hypertension from the ASPIRE (Assessing the Spectrum of Pulmonary Hypertension Identified at a Referral Centre) Registry, underwent RHC and CMR within 12 h. Predicted mean pulmonary arterial pressure (mPAP) was derived using multivariate regression analysis of CMR measurements. The model was tested in an independent prospective validation cohort of 64 patients with suspected pulmonary hypertension. Surrogate measures of pulmonary capillary wedge pressure (PCWP) and cardiac output (CO) were estimated by left atrial volumetry and pulmonary arterial phase contrast imaging, respectively. Noninvasive pulmonary vascular resistance (PVR) was calculated from the CMR-derived measurements, defined as: (CMR-predicted mPAP - CMR-predicted PCWP)/CMR phase contrast CO. RESULTS: The following composite statistical model of mPAP was derived: CMR-predicted mPAP = -4.6 + (interventricular septal angle × 0.23) + (ventricular mass index × 16.3). In the validation cohort a strong correlation between mPAP and MR estimated mPAP was demonstrated (R(2) = 0.67). For detection of the presence of pulmonary hypertension the area under the receiver-operating characteristic (ROC) curve was 0.96 (0.92 to 1.00; p < 0.0001). CMR-estimated PVR reliably identified invasive PVR ≥3 Wood units (WU) with a high degree of accuracy, the area under the ROC curve was 0.94 (0.88 to 0.99; p < 0.0001). CONCLUSIONS: CMR imaging can accurately estimate mean pulmonary artery pressure in patients with suspected pulmonary hypertension and calculate PVR by estimating all major pulmonary hemodynamic metrics measured at RHC.
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