Fully automated detection of heart irradiation in cine MV images acquired during breast cancer radiotherapy. (November 2020)

• Record Type: Journal Article
• Authors: Poulsen, Per Rugaard; Thomsen, Mette Skovhus; Hansen, Rune; Worm, Esben; Spejlborg, Harald; Offersen, Birgitte
• Is Part Of: Radiotherapy and oncology. Volume 152(2020)
• Page Start: 189
• Page End: 195
• Publication Date: 2020-11
• Subjects: Breast cancer radiotherapy -- Heart toxicity -- Interfraction motion -- Cine MV imaging -- Image processing -- Organs at risk; Oncology -- Periodicals; Radiotherapy -- Periodicals; Tumors -- Periodicals; Medical Oncology -- Periodicals; Neoplasms -- radiotherapy -- Periodicals; Radiotherapy -- Periodicals; Radiothérapie -- Périodiques; Cancérologie -- Périodiques; Tumeurs -- Périodiques; Electronic journals; 616.9940642
• DOI: 10.1016/j.radonc.2019.11.006
• Languages: English
• ISSNs: 0167-8140

Abstract

Highlights: Automated heart edge detection in cine MV images was proposed and developed. Highly efficient detection of heart irradiation in breast cancer radiotherapy. Allows unmonitored surveillance of heart irradiation during breast treatments. Abstract: Purpose: To develop robust automated detection of heart irradiation in continuous portal images (cine MV images) of tangential breast cancer treatments. Methods: Cine MV images of 302 tangential field deliveries were recorded for ten left-sided breast cancer patients receiving deep-inspiration breath-hold radiotherapy. An algorithm for fully automated heart edge detection in cine MV images was developed and tested for all images. The algorithm first enhances the heart edge contrast greatly by exploiting that pixels on the heart edge change their intensity cyclically, and highly correlated, at 1–3 Hz due to heartbeat. The algorithm then detects the heart edge in the enhanced image and calculates the exposed heart area within the field aperture. Results: The algorithm correctly identified the heart edge in all cine MV series with heart exposure (169 of 302 field deliveries). With conservative selection criteria the algorithm on average identified 70 heart edge pixels in the heart-including field deliveries (range: 10–230) without false positives. With less strict criteria 106 heart edge pixels were identified on average (range: 13–262) with 0.6% being false positives. The heart edge bordering the lung was segmented highly reliably even a few millimeters outside the field edge. For six patients with frequent heart irradiation, the exposed heart area showed large interfraction variations and smaller intrafraction variations. Conclusions: Automated heart edge detection in cine MV images was proposed, developed and shown to be highly efficient for heart exposure detection in tangential breast fields. It may allow unsupervised surveillance of heart exposure at all tangential breast cancer treatments in a clinic.