Cherenkov Imaged Bio-morphological Features Verify Patient Positioning with Deformable Tissue Translocation in Breast Radiotherapy

Abstract

PurposeAccurate patient positioning is crucial for precise radiotherapy dose delivery, as errors in positioning can profoundly influence treatment outcomes. This study introduces a novel application for loco-regional tissue deformation tracking via Cherenkov image analysis, during fractionated breast cancer radiotherapy. The primary objective of this research was to develop and test an algorithmic method for Cherenkov-based position accuracy quantification, particularly for loco-regional deformations which do not have an ideal method for quantification during radiotherapy. Methods and materialsBio-morphological features in the Cherenkov images such as vessels were segmented. A rigid/non-rigid combined registration technique was employed to pinpoint both inter- and intra-fractional positioning variations. The methodology was tested on an anthropomorphic chest phantom experiment via shifting treatment couch with known distances and inducing respiratory motion, to simulate inter-fraction setup uncertainties and intra-fraction motions respectively. It was then applied to a dataset of fractionated whole breast radiotherapy human imaging (n=10 patients). ResultsThe methodology provides quantified positioning variations, comprising two components: a global shift determined through rigid registration, and a two-dimensional variation map illustrating loco-regional tissue deformation quantified via non-rigid registration. Controlled phantom testing yielded an average accuracy of 0.83 mm for couch translations up to 20 mm in various directions. Analysis of clinical Cherenkov imaging data from ten breast cancer patients compared to their first imaged fraction revealed an inter-fraction setup variation of 3.7 ± 2.4 mm in the global shift and loco-regional deformation up to 3.3 ± 1.9 mm (95th percentile of all regional deformation). ConclusionsThis study introduces the use of Cherenkov visualized bio-morphological features to quantify the global and local variations in patient positioning based on rigid and non-rigid registrations. This new approach demonstrates the feasibility to provide quantitative guidance for inter-/intra-fraction positioning, particularly for the loco-regional deformations that have been unappreciated in current practice with conventional imaging techniques.