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.

中文翻译：

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在乳腺癌放疗期间获得的电影 MV 图像中全自动检测心脏辐射

目的 在切向乳腺癌治疗的连续门户图像（电影 MV 图像）中开发强大的心脏照射自动检测。方法 记录了 10 名接受深吸气屏气放疗的左侧乳腺癌患者的 302 次切向场分娩的 Cine MV 图像。开发了一种用于电影 MV 图像中全自动心脏边缘检测的算法，并针对所有图像进行了测试。该算法首先通过利用心脏边缘上的像素由于心跳而以 1-3 Hz 周期性地改变其强度并且高度相关，从而极大地增强了心脏边缘的对比度。该算法然后检测增强图像中的心脏边缘并计算视场孔径内暴露的心脏区域。结果 该算法正确识别了所有带有心脏曝光的电影 MV 系列中的心脏边缘（302 次现场交付中的 169 次）。使用保守的选择标准，算法平均在包括心脏的场交付（范围：10-230）中识别了 70 个心脏边缘像素，没有误报。使用不太严格的标准，平均识别出 106 个心脏边缘像素（范围：13-262），其中 0.6% 为误报。即使在视野边缘外几毫米处，与肺接壤的心脏边缘也被高度可靠地分割。对于频繁心脏照射的 6 名患者，暴露的心脏区域显示出较大的次间变异和较小的次间变异。结论 提出了电影 MV 图像中的自动心脏边缘检测，开发并证明对切向乳房区域的心脏暴露检测非常有效。它可能允许在诊所的所有切向乳腺癌治疗中对心脏暴露进行无人监督的监测。