医学
边距(机器学习)
转移
胰腺肿瘤
手术切缘
胰腺
放射科
胰腺切除术
作者
Mary E. King,Jialing Zhang,John Q. Lin,Kyana Y. Garza,Rachel J. DeHoog,Clara L. Feider,Alena Bensussan,Marta Sans,Anna Krieger,Sunil Badal,Michael F Keating,Spencer Woody,Sadhna Dhingra,Wendong Yu,Christopher Pirko,Kirtan A. Brahmbhatt,George Van Buren,William E. Fisher,James W. Suliburk,Livia S. Eberlin
标识
DOI:10.1073/pnas.2104411118
摘要
Intraoperative delineation of tumor margins is critical for effective pancreatic cancer surgery. Yet, intraoperative frozen section analysis of tumor margins is a time-consuming and often challenging procedure that can yield confounding results due to histologic heterogeneity and tissue-processing artifacts. We have previously described the development of the MasSpec Pen technology as a handheld mass spectrometry-based device for nondestructive tissue analysis. Here, we evaluated the usefulness of the MasSpec Pen for intraoperative diagnosis of pancreatic ductal adenocarcinoma based on alterations in the metabolite and lipid profiles in in vivo and ex vivo tissues. We used the MasSpec Pen to analyze 157 banked human tissues, including pancreatic ductal adenocarcinoma, pancreatic, and bile duct tissues. Classification models generated from the molecular data yielded an overall agreement with pathology of 91.5%, sensitivity of 95.5%, and specificity of 89.7% for discriminating normal pancreas from cancer. We built a second classifier to distinguish bile duct from pancreatic cancer, achieving an overall accuracy of 95%, sensitivity of 92%, and specificity of 100%. We then translated the MasSpec Pen to the operative room and predicted on in vivo and ex vivo data acquired during 18 pancreatic surgeries, achieving 93.8% overall agreement with final postoperative pathology reports. Notably, when integrating banked tissue data with intraoperative data, an improved agreement of 100% was achieved. The result obtained demonstrate that the MasSpec Pen provides high predictive performance for tissue diagnosis and compatibility for intraoperative use, suggesting that the technology may be useful to guide surgical decision-making during pancreatic cancer surgeries.
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