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Accuracy of Left Ventricular Cavity Volume and Ejection Fraction for Conventional Estimation Methods and 3D Surface Fitting

W O'Dell1 , B Terracino2*, (1) University of Florida, Gainesville, fl, (2) University of Florida, Gainesville, FL


(Sunday, 7/29/2018) 4:00 PM - 4:55 PM

Room: Karl Dean Ballroom C

Purpose: While left ventricular cavity volume (LVV) and ejection fraction (LVEF) are used routinely for clinical decision-making, the errors in their clinical estimates have yet to be rigorously quantified and are perhaps underappreciated. The goal of this study was to quantify the accuracy and precision of several common imaging-based LVV and LVEF estimation methods and a 3D conformal surface modelling approach. We then applied surface modeling to quantify subclinical changes in LVEF in patients undergoing breast radiation therapy to the chest wall.

Methods: An isolated canine heart preparation was prepared with a balloon inserted into the LV cavity and connected to a computer-controlled pump assembly to simulate physiologic LV filling. Twelve short-axis and twelve long-axis high-resolution MR images were acquired at 14 phases of the cardiac cycle from end-systole to end-diastole. The MR images were processed to generate 64 endocardial contour points per image. Multiple slice variants were used to calculate the LVEF error for each of 12 common models plus the 3D conformal surface fitting approach. The LVEF was then calculated for 4 breast cancer patients before and 6-12 months after IMRT to quantify possible changes in LVEF.

Results: Using 6 or more short-axis views and Simpson’s method can achieve LVEF error of less than 3% and LVV error of around 10%, however, in the clinic additional errors of >8% are expected. The 3D conformal surface fitting method achieved <3% error for both LVEF and LVV. Using this approach on breast cancer patients, LVEF was observed to decrease by 5.1% ± 3.5% within 12 months after IMRT.

Conclusion: The use of MRI imaging and a mathematical 3D surface model achieves superior LVEF accuracy compared to conventional clinical methods. By reducing the measurement uncertainty, we are able to identify patients with subclinical cardiac radiation toxicity prior to major cardiac event.


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