Measuring distance from lowest boundary of rectal tumor to anal verge on CT images using pyramid attention pooling transformer

Accurately measuring the Distance from the lowest boundary of rectal tumor To the Anal Verge (DTAV) is critical for developing optimal surgical plans for treating patients with rectal cancer. DTAV was traditionally estimated by colonoscopy or manual measurement on computed tomography (CT) images. However, colonoscopy brings substantial pains to the patient. As for manual measurement on CT images, it is time-consuming and its accuracy depends on the surgeon's expertise. In this work, we present a novel method for automatically measuring DTAV from sagittal CT images. The success of our method is mainly credited to a pyramid attention pooling (PAP) transformer architecture, which naturally entangles global lesion localization and local boundary delineation. Our method automatically generates the rectum's centerline based on a segmented rectum and tumor image to simulate the manual measurement of DTAV. We conduct a comprehensive evaluation of the method with a newly collected rectum tumor CT image dataset. On a test dataset of 48 patients' CT images with rectal tumors, the mean absolute difference between our method and the gold standard is 1.74 cm, which is a significant improvement of 1.29 cm over that measured by a resident surgeon (P < 0.001). In addition, The results measured by the resident surgeon referring to our segmentation results improved by 1.46 cm compared to the results measured independently by the residents. As experimentally demonstrated, our method exhibits great application potential in clinical scenarios.