Quantifying inter-fraction cardiac substructure displacement during radiotherapy via magnetic resonance imaging guidance

Eric D Morris; Ahmed I Ghanem; Simeng Zhu; Ming Dong; Milan V Pantelic; Carri K Glide-Hurst

doi:10.1016/j.phro.2021.03.005

Quantifying inter-fraction cardiac substructure displacement during radiotherapy via magnetic resonance imaging guidance

Phys Imaging Radiat Oncol. 2021 Apr 16:18:34-40. doi: 10.1016/j.phro.2021.03.005. eCollection 2021 Apr.

Authors

Eric D Morris¹, Ahmed I Ghanem^{2

3}, Simeng Zhu², Ming Dong⁴, Milan V Pantelic⁵, Carri K Glide-Hurst⁶

Affiliations

¹ Department of Radiation Oncology, University of California-Los Angeles, Los Angeles, CA 90095, United States.
² Department of Radiation Oncology, Henry Ford Cancer Institute, Detroit, MI 48202, United States.
³ Alexandria Clinical Oncology Department, Alexandria University, Alexandria, Egypt.
⁴ Department of Computer Science, Wayne State University, Detroit, MI 48202, United States.
⁵ Department of Radiology, Henry Ford Cancer Institute, Detroit, MI 48202, United States.
⁶ Department of Human Oncology, University of Wisconsin, Madison, Madison, WI 53792, United States.

Abstract

Purpose: Emerging evidence suggests cardiac substructures are highly radiosensitive during radiation therapy for cancer treatment. However, variability in substructure position after tumor localization has not been well characterized. This study quantifies inter-fraction displacement and planning organ at risk volumes (PRVs) of substructures by leveraging the excellent soft tissue contrast of magnetic resonance imaging (MRI).

Methods: Eighteen retrospectively evaluated patients underwent radiotherapy for intrathoracic tumors with a 0.35 T MRI-guided linear accelerator. Imaging was acquired at a 17-25 s breath-hold (resolution 1.5 × 1.5 × 3 mm³). Three to four daily MRIs per patient (n = 71) were rigidly registered to the planning MRI-simulation based on tumor matching. Deep learning or atlas-based segmentation propagated 13 substructures (e.g., chambers, coronary arteries, great vessels) to daily MRIs and were verified by two radiation oncologists. Daily centroid displacements from MRI-simulation were quantified and PRVs were calculated.

Results: Across substructures, inter-fraction displacements for 14% in the left-right, 18% in the anterior-posterior, and 21% of fractions in the superior-inferior were > 5 mm. Due to lack of breath-hold compliance, ~4% of all structures shifted > 10 mm in any axis. For the chambers, median displacements were 1.8, 1.9, and 2.2 mm in the left-right, anterior-posterior, and superior-inferior axis, respectively. Great vessels demonstrated larger displacements (> 3 mm) in the superior-inferior axis (43% of shifts) and were only 25% (left-right) and 29% (anterior-posterior) elsewhere. PRVs from 3 to 5 mm were determined as anisotropic substructure-specific margins.

Conclusions: This exploratory work derived substructure-specific safety margins to ensure highly effective cardiac sparing. Findings require validation in a larger cohort for robust margin derivation and for applications in prospective clinical trials.

Keywords: Cardiac substructures; Inter-fraction; MRI; MRgRT; Margins; Segmentation.

Grants and funding

R01 CA204189/CA/NCI NIH HHS/United States