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

Abstract

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).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 mm 3 ). 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.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.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.

On the feasibility of cardiac substructure sparing in magnetic resonance imaging guided stereotactic lung radiotherapy

“…An important consideration for future research is the effect of cardiorespiratory motion on the dose distribution and how it may affect cardiac sparing. The motion of CS has been investigated recently by Morris et al 40 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. This leads to planning organ at risk volumes (PRVs) with 3-5 mm anisotropic substructure-specific margins.…”

“…Furthermore, the effect of respiratory motion on dose to the heart and CS has been explored by Miller et al 41 (The maximum vector displacements ranged from 5 to 10 mm across most substructures), however this was not in lung cancer patients alone. Motion effects can be mitigated by using PRVs (similar to Morris et al), using breath-hold (at risk of larger displacement when lack of compliance occurs 40 ) or by using active motion management. 42…”

“…The motion of CS has been investigated recently by Morris et al. 40 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. This leads to planning organ at risk volumes (PRVs) with 3–5 mm anisotropic substructure‐specific margins.…”

“…Motion effects can be mitigated by using PRVs (similar to Morris et al. ), using breath‐hold (at risk of larger displacement when lack of compliance occurs 40 ) or by using active motion management. 42 …”

Validation of an established deep learning auto-segmentation tool for cardiac substructures in 4D radiotherapy planning scans

“…Moreover, dose-volume characteristics for several of the specific cardiac substructures are important for predicting toxicity after conventional fractionation lung cancer RT [15] , [16] , [17] , [18] , [19] , [20] . The cardiac substructures are challenging to contour on RT planning computed tomography (CT), due to geometry complexity, limited intracardiac soft tissue definition and cardiorespiratory motion artefact [21] . The imminent requirement to incorporate substructures in treatment planning is an opportunity to embed a cardiac segmentation tool into RT workflows.…”