Thomas A Treibel1, Marianna Fontana1, Viviana Maestrini2, Silvia Castelletti1, Stefania Rosmini1, Joanne Simpson3, Arthur Nasis3, Anish N Bhuva1, Heerajnarain Bulluck1, Amna Abdel-Gadir1, Steven K White1, Charlotte Manisty1, Bruce S Spottiswoode4, Timothy C Wong5, Stefan K Piechnik6, Peter Kellman7, Matthew D Robson6, Erik B Schelbert5, James C Moon8. 1. Barts Heart Centre, St Bartholomew's Hospital, London, United Kingdom; Institute of Cardiovascular Science, University College London, London, United Kingdom. 2. Barts Heart Centre, St Bartholomew's Hospital, London, United Kingdom; Department of Cardiovascular, Respiratory, Nephrology, Anesthesiology & Geriatric Sciences, Sapienza University, Rome, Italy. 3. Barts Heart Centre, St Bartholomew's Hospital, London, United Kingdom. 4. Siemens Healthcare, Chicago, Illinois. 5. UPMC Heart and Vascular Institute, University of Pittsburgh, Pittsburgh, Pennsylvania. 6. Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, John Radcliffe Hospital, Oxford, United Kingdom. 7. National Heart, Lung, and Blood Institute, National Institute for Health, Bethesda, Maryland. 8. Barts Heart Centre, St Bartholomew's Hospital, London, United Kingdom; Institute of Cardiovascular Science, University College London, London, United Kingdom. Electronic address: j.moon@ucl.ac.uk.
Abstract
OBJECTIVES: The authors sought to generate a synthetic extracellular volume fraction (ECV) from the relationship between hematocrit and longitudinal relaxation rate of blood. BACKGROUND: ECV quantification by cardiac magnetic resonance (CMR) measures diagnostically and prognostically relevant changes in the extracellular space. Current methodologies require blood hematocrit (Hct) measurement-a complication to easy clinical application. We hypothesized that the relationship between Hct and longitudinal relaxation rate of blood (R1 = 1/T1blood) could be calibrated and used to generate a synthetic ECV without Hct that was valid, user-friendly, and prognostic. METHODS: Proof-of-concept: 427 subjects with a wide range of health and disease were divided into derivation (n = 214) and validation (n = 213) cohorts. Histology cohort: 18 patients with severe aortic stenosis with histology obtained during valve replacement. Outcome cohort: For comparison with external outcome data, we applied synthetic ECV to 1,172 consecutive patients (median follow-up 1.7 years; 74 deaths). All underwent CMR scanning at 1.5-T with ECV calculation from pre- and post-contrast T1 (blood and myocardium) and venous Hct. RESULTS: Proof-of-concept: In the derivation cohort, native R1blood and Hct showed a linear relationship (R(2) = 0.51; p < 0.001), which was used to create synthetic Hct and ECV. Synthetic ECV correlated well with conventional ECV (R(2) = 0.97; p < 0.001) without bias. These results were maintained in the validation cohort. Histology cohort: Synthetic and conventional ECV both correlated well with collagen volume fraction measured from histology (R(2) = 0.61 and 0.69, both p < 0.001) with no statistical difference (p = 0.70). Outcome cohort: Synthetic ECV related to all-cause mortality (hazard ratio 1.90; 95% confidence interval 1.55 to 2.31; for every 5% increase in ECV). Finally, we engineered a synthetic ECV tool, generating automatic ECV maps during image acquisition. CONCLUSIONS: Synthetic ECV provides validated noninvasive quantification of the myocardial extracellular space without blood sampling and is associated with cardiovascular outcomes.
OBJECTIVES: The authors sought to generate a synthetic extracellular volume fraction (ECV) from the relationship between hematocrit and longitudinal relaxation rate of blood. BACKGROUND: ECV quantification by cardiac magnetic resonance (CMR) measures diagnostically and prognostically relevant changes in the extracellular space. Current methodologies require blood hematocrit (Hct) measurement-a complication to easy clinical application. We hypothesized that the relationship between Hct and longitudinal relaxation rate of blood (R1 = 1/T1blood) could be calibrated and used to generate a synthetic ECV without Hct that was valid, user-friendly, and prognostic. METHODS: Proof-of-concept: 427 subjects with a wide range of health and disease were divided into derivation (n = 214) and validation (n = 213) cohorts. Histology cohort: 18 patients with severe aortic stenosis with histology obtained during valve replacement. Outcome cohort: For comparison with external outcome data, we applied synthetic ECV to 1,172 consecutive patients (median follow-up 1.7 years; 74 deaths). All underwent CMR scanning at 1.5-T with ECV calculation from pre- and post-contrast T1 (blood and myocardium) and venous Hct. RESULTS: Proof-of-concept: In the derivation cohort, native R1blood and Hct showed a linear relationship (R(2) = 0.51; p < 0.001), which was used to create synthetic Hct and ECV. Synthetic ECV correlated well with conventional ECV (R(2) = 0.97; p < 0.001) without bias. These results were maintained in the validation cohort. Histology cohort: Synthetic and conventional ECV both correlated well with collagen volume fraction measured from histology (R(2) = 0.61 and 0.69, both p < 0.001) with no statistical difference (p = 0.70). Outcome cohort: Synthetic ECV related to all-cause mortality (hazard ratio 1.90; 95% confidence interval 1.55 to 2.31; for every 5% increase in ECV). Finally, we engineered a synthetic ECV tool, generating automatic ECV maps during image acquisition. CONCLUSIONS: Synthetic ECV provides validated noninvasive quantification of the myocardial extracellular space without blood sampling and is associated with cardiovascular outcomes.
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