Technological Innovation Group, Virgen del Rocío University Hospital, Avda Manuel Siurot, s/n, 41013, Sevilla, Spain.
Signal Theory and Communications Department, University of Seville, Camino de los Descubrimientos, s/n, 41092, Sevilla, Spain.
Int J Comput Assist Radiol Surg. 2017 Dec;12(12):2055-2067. doi: 10.1007/s11548-017-1530-8. Epub 2017 Feb 10.
In 2005, an application for surgical planning called AYRA[Formula: see text] was designed and validated by different surgeons and engineers at the Virgen del Rocío University Hospital, Seville (Spain). However, the segmentation methods included in AYRA and in other surgical planning applications are not able to segment accurately tumors that appear in soft tissue. The aims of this paper are to offer an exhaustive validation of an accurate semiautomatic segmentation tool to delimitate retroperitoneal tumors from CT images and to aid physicians in planning both radiotherapy doses and surgery.
A panel of 6 experts manually segmented 11 cases of tumors, and the segmentation results were compared exhaustively with: the results provided by a surgical planning tool (AYRA), the segmentations obtained using a radiotherapy treatment planning system (Pinnacle[Formula: see text]), the segmentation results obtained by a group of experts in the delimitation of retroperitoneal tumors and the segmentation results using the algorithm under validation.
11 cases of retroperitoneal tumors were tested. The proposed algorithm provided accurate results regarding the segmentation of the tumor. Moreover, the algorithm requires minimal computational time-an average of 90.5% less than that required when manually contouring the same tumor.
A method developed for the semiautomatic selection of retroperitoneal tumor has been validated in depth. AYRA, as well as other surgical and radiotherapy planning tools, could be greatly improved by including this algorithm.
2005 年，由塞维利亚 Virgen del Rocío 大学医院的不同外科医生和工程师设计并验证了一种名为 AYRA[公式：见正文]的手术规划应用程序。然而，AYRA 和其他手术规划应用程序中包含的分割方法无法准确地分割软组织中出现的肿瘤。本文的目的是提供一种准确的半自动分割工具，用于从 CT 图像中分割腹膜后肿瘤，以帮助医生规划放疗剂量和手术。
一组 6 名专家手动分割了 11 例肿瘤，并对分割结果进行了详尽的比较：与手术规划工具（AYRA）提供的结果、放射治疗计划系统（Pinnacle[公式：见正文]）的分割结果、腹膜后肿瘤专家小组的分割结果以及正在验证的算法的分割结果进行比较。
对 11 例腹膜后肿瘤进行了测试。该算法在肿瘤分割方面提供了准确的结果。此外，该算法所需的计算时间很少——平均比手动勾画同一肿瘤所需的时间少 90.5%。
已对用于腹膜后肿瘤半自动选择的方法进行了深入验证。AYRA 以及其他手术和放射治疗规划工具可以通过包含此算法来大大改进。
