Suppr超能文献

肠系膜上动脉受累的胰腺导管腺癌的 CT 放射组学特征:一项初步研究。

CT Radiomic Features of Superior Mesenteric Artery Involvement in Pancreatic Ductal Adenocarcinoma: A Pilot Study.

机构信息

From the Departments of Radiology (F.R., K.J.L., M.M., P.L., Y.D., F.R.S., E.S., D.M.) and Radiation Oncology (K.J.L.), Duke University Medical Center, 2301 Erwin Rd, Box 3808, Durham, NC 27710; Multi-Dimensional Image Processing Laboratory, Duke Radiology, Duke University School of Medicine, Durham, NC (F.R., M.M., P.L., Y.D., F.R.S., D.M.); progettoDiventerò, Bracco Foundation, Milan, Italy (F.R.); Carl E. Ravin Advanced Imaging Laboratories (J.H., E.S.), Department of Biostatistics and Bioinformatics (R.L., S.L.), and Duke Electrical and Computer Engineering (K.J.L.), Duke University, Durham, NC; Department of Biostatistics, Yale University, New Haven, Conn (C.L.); Department of Diagnostic and Interventional Radiology and Nuclear Medicine, University Hospital Hamburg-Eppendorf, Hamburg, Germany (M.M.); Department of Radiology, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan Province, People's Republic of China (P.L.); Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, People's Republic of China (Y.D.); Duke Cancer Center, Duke Health, Durham, NC (N.B.M., S.Z.); and Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (D.E.M.).

出版信息

Radiology. 2021 Dec;301(3):610-622. doi: 10.1148/radiol.2021210699. Epub 2021 Sep 7.

Abstract

Background Current imaging methods for prediction of complete margin resection (R0) in patients with pancreatic ductal adenocarcinoma (PDAC) are not reliable. Purpose To investigate whether tumor-related and perivascular CT radiomic features improve preoperative assessment of arterial involvement in patients with surgically proven PDAC. Materials and Methods This retrospective study included consecutive patients with PDAC who underwent surgery after preoperative CT between 2012 and 2019. A three-dimensional segmentation of PDAC and perivascular tissue surrounding the superior mesenteric artery (SMA) was performed on preoperative CT images with radiomic features extracted to characterize morphology, intensity, texture, and task-based spatial information. The reference standard was the pathologic SMA margin status of the surgical sample: SMA involved (tumor cells ≤1 mm from margin) versus SMA not involved (tumor cells >1 mm from margin). The preoperative assessment of SMA involvement by a fellowship-trained radiologist in multidisciplinary consensus was the comparison. High reproducibility (intraclass correlation coefficient, 0.7) and the Kolmogorov-Smirnov test were used to select features included in the logistic regression model. Results A total of 194 patients (median age, 66 years; interquartile range, 60-71 years; age range, 36-85 years; 99 men) were evaluated. Aside from surgery, 148 patients underwent neoadjuvant therapy. A total of 141 patients' samples did not involve SMA, whereas 53 involved SMA. A total of 1695 CT radiomic features were extracted. The model with five features (maximum hugging angle, maximum diameter, logarithm robust mean absolute deviation, minimum distance, square gray level co-occurrence matrix correlation) showed a better performance compared with the radiologist assessment (model vs radiologist area under the curve, 0.71 [95% CI: 0.62, 0.79] vs 0.54 [95% CI: 0.50, 0.59]; < .001). The model showed a sensitivity of 62% (33 of 53 patients) (95% CI: 51, 77) and a specificity of 77% (108 of 141 patients) (95% CI: 60, 84). Conclusion A model based on tumor-related and perivascular CT radiomic features improved the detection of superior mesenteric artery involvement in patients with pancreatic ductal adenocarcinoma. © RSNA, 2021 See also the editorial by Do and Kambadakone in this issue.

摘要

背景 当前用于预测胰腺导管腺癌(PDAC)患者完全切缘切除(R0)的影像学方法并不可靠。目的 旨在探讨肿瘤相关和血管周围 CT 放射组学特征是否能提高术前对手术证实的 PDAC 患者肠系膜上动脉(SMA)受累的评估能力。材料与方法 本回顾性研究纳入了 2012 年至 2019 年间接受术前 CT 检查且随后接受手术治疗的 PDAC 连续患者。对术前 CT 图像进行 PDAC 和 SMA 周围血管周围组织的三维分割,并提取放射组学特征以描述形态、强度、纹理和基于任务的空间信息。参考标准为手术样本 SMA 切缘状态:SMA 受累(肿瘤细胞距切缘≤1mm)与 SMA 未受累(肿瘤细胞距切缘>1mm)。 SMA 受累的术前评估由多学科共识中的一名 fellowship 培训的放射科医生进行。高重复性(组内相关系数,0.7)和 Kolmogorov-Smirnov 检验用于选择纳入逻辑回归模型的特征。结果 共评估了 194 例患者(中位年龄 66 岁;四分位间距 60-71 岁;年龄范围 36-85 岁;99 例男性)。除手术外,148 例患者还接受了新辅助治疗。共有 141 例患者的样本未累及 SMA,53 例累及 SMA。共提取了 1695 个 CT 放射组学特征。与放射科医生评估相比,具有 5 个特征的模型(最大抱角、最大直径、对数稳健均值绝对偏差、最小距离、平方灰度共生矩阵相关)显示出更好的性能(模型与放射科医生曲线下面积,0.71[95%CI:0.62,0.79]与 0.54[95%CI:0.50,0.59];<.001)。该模型的敏感性为 62%(53 例患者中的 33 例)(95%CI:51,77),特异性为 77%(141 例患者中的 108 例)(95%CI:60,84)。结论 基于肿瘤相关和血管周围 CT 放射组学特征的模型提高了对胰腺导管腺癌患者 SMA 受累的检测能力。

相似文献

引用本文的文献

本文引用的文献

3
The Biological Meaning of Radiomic Features.放射组特征的生物学意义。
Radiology. 2021 Mar;298(3):505-516. doi: 10.1148/radiol.2021202553. Epub 2021 Jan 5.
5
Digital pathology and computational image analysis in nephropathology.数字病理学和肾脏病学中的计算图像分析。
Nat Rev Nephrol. 2020 Nov;16(11):669-685. doi: 10.1038/s41581-020-0321-6. Epub 2020 Aug 26.

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验