Cardiac Substructure Segmentation and Dosimetry Using a Novel Hybrid Magnetic Resonance and Computed Tomography Cardiac Atlas

Abstract

Purpose: Radiation dose to the heart and cardiac substructures has been linked to cardiotoxicities. Because cardiac substructures are poorly visualized on treatment-planning computed tomography (CT) scans, we used the superior soft-tissue contrast of magnetic resonance (MR) imaging to optimize a hybrid MR/CT atlas for substructure dose assessment using CT.

Methods and materials: Thirty-one patients with left-sided breast cancer underwent a T2-weighted MR imaging scan and noncontrast simulation CT scans. A radiation oncologist delineated 13 substructures (chambers, great vessels, coronary arteries, etc) using MR/CT information via cardiac-confined rigid registration. Ground-truth contours for 20 patients were inputted into an intensity-based deformable registration atlas and applied to 11 validation patients. Automatic segmentations involved using majority vote and Simultaneous Truth and Performance Level Estimation (STAPLE) strategies with 1 to 15 atlas matches. Performance was evaluated via Dice similarity coefficient (DSC), mean distance to agreement, and centroid displacement. Three physicians evaluated segmentation performance via consensus scoring by using a 5-point scale. Dosimetric assessment included measurements of mean heart dose, left ventricular volume receiving 5 Gy, and left anterior descending artery mean and maximum doses.

Results: Atlas approaches performed similarly well, with 7 of 13 substructures (heart, chambers, ascending aorta, and pulmonary artery) having DSC >0.75 when averaged over 11 validation patients. Coronary artery segmentations were not successful with the atlas-based approach (mean DSC <0.3). The STAPLE method with 10 matches yielded the highest DSC and the lowest mean distance to agreement for all high-performing substructures (omitting coronary arteries). For the STAPLE method with 10 matches, >50% of all validation contours had centroid displacements <3.0 mm, with the largest shifts in the coronary arteries. Atlas-generated contours had no statistical difference from ground truth for left anterior descending artery maximum dose, mean heart dose, and left ventricular volume receiving 5 Gy (P > .05). Qualitative contour grading showed that 8 substructures required minor modifications.

Conclusions: The hybrid MR/CT atlas provided reliable segmentations of chambers, heart, and great vessels for patients undergoing noncontrast CT, suggesting potential widespread applicability for routine treatment planning.

Conflict of interest statement

Conflict of Interest Statement:

Copyright © 2018 Elsevier Inc. All rights reserved.

Figures

Figure 1:

Left: Axial planning CT, axial T2-weighted MRI, and contoured axial T2-weighted MRI, shown at 4 different axial locations. Right: List of cardiac substructures assessed in this study.

Figure 2:

Validation patient Dice Similarity Coefficient (DSC) results over all substructures (Left) and all high performing substructures (i.e. heart, cardiac chambers, and great vessels) (Right). Boxplots and line indicate the interquartile range (IQR) and median, respectively. Whiskers indicate the minimum and maximum, with data points >1.5 times the IQR and >3 times the IQR marked by circles and stars, respectively.

Figure 3:

Mean distance to agreement (MDA) (Left) and Dice similarity coefficient (DSC) (Right) between ground truth and ST10 contours for all delineated substructures (n = 11). Error bars represent the standard error of the mean.

Figure 4:

Three-dimensional rendering of substructures showing agreement between manually drawn ground truth (GT) contours and STAPLE 10 (ST) generated contours.

Figure 5:

Left: Axial cross section of a treatment planning CT for a representative validation patient showing contours generated from STAPLE 10 (ST10) and ground truth, as well as percentage dose delivered to the left breast (substructure colors not represented in the dose volume histogram (DVH): Dark Blue-RA, Denim Blue-RA_ST10, Pink-RV, Magenta-RV_ST10). Right: Corresponding DVH for the same validation patient.