Xu HaoPing, Arsene Henry Alexandre, Robillard Magalie, Amessis Malika, Kirova Youlia M
1 Departments of Radiation Oncology, Institut Curie , Paris , France.
2 Departments of Radiation Oncology, Ruijin Hospital, Shanghai Jiao Tong University, School of Medicine , Shanghai , China.
Br J Radiol. 2018 Oct;91(1090):20180095. doi: 10.1259/bjr.20180095. Epub 2018 Jul 13.
: To describe the practical procedure of implementation and optimization of delineation using "Mirada" software, as well as evaluation of the automatic segmentation for the daily practice of lymph nodes (LN) and organs at risk (OARs) in early stage breast cancer patients.
: 40 patients' CT scans in treatment position were selected and recontoured according to the European Society of Therapeutic Radiation Oncology guidelines. The atlas of data set was then created for automatic delineation. 30 patients with breast/chest wall and lymph nodes regions irradiated were recruited for evaluation. With the same treatment position, the CT scan images were acquired and then contoured by the MIRADA system automatically as well as by the radiation oncologist manually (as the reference). The conformity index (CI) was used to evaluate the concordance between both of them.
: The mean time for manual contour was 24.1 ± 5.1 and 26.4 ± 2.8 min for the LN and the OARs respectively. All the volumes of interest were contoured using the software (including corrections) in 30 min, which reduced the time of delineation of target volumes and OAR by about 40%. Of the 30 cases evaluated, the mean CI of 5 principal OARs showed ≥0.8. While the automatic contour of LN was less satisfactory with mean CI of 0.43 ± 0.1 (0.23-0.52).
: For the breast cancer patients, the studied software permitted to save time for delineation with acceptable OAR contours. The improvement of LN regions contour is needed. More cases and further evaluation are needed for the system to realize its routine use.
: It's the first description and evaluation of the automatic delineation and segmentation system for the breast cancer.
描述使用“Mirada”软件进行轮廓勾画的实施及优化的实际流程,以及评估早期乳腺癌患者日常淋巴结(LN)和危及器官(OARs)自动分割的情况。
选取40例处于治疗体位的患者的CT扫描图像,并根据欧洲放射肿瘤学会指南重新进行轮廓勾画。然后创建数据集图谱用于自动轮廓勾画。招募30例接受乳房/胸壁和淋巴结区域照射的患者进行评估。在相同治疗体位下,获取CT扫描图像,然后由MIRADA系统自动进行轮廓勾画,并由放射肿瘤学家手动进行轮廓勾画(作为参考)。使用一致性指数(CI)评估两者之间的一致性。
手动勾画LN和OARs轮廓的平均时间分别为24.1±5.1分钟和26.4±2.8分钟。使用该软件(包括校正)在30分钟内完成了所有感兴趣体积的轮廓勾画,这使靶区体积和OARs的勾画时间减少了约40%。在评估的30例病例中,5个主要OARs的平均CI显示≥0.8。而LN的自动轮廓勾画效果较差,平均CI为0.43±0.1(0.23 - 0.52)。
对于乳腺癌患者,所研究的软件能够在保证OARs轮廓可接受的情况下节省轮廓勾画时间。LN区域的轮廓勾画有待改进。该系统要实现常规应用还需要更多病例和进一步评估。
这是对乳腺癌自动轮廓勾画和分割系统的首次描述与评估。