Quantifying vascular invasion in pancreatic cancer-a contrast CT based method for surgical resectability evaluation

Yi Lao; John David; Zhaoyang FanShelly BianAlmon ShiuEric L ChangKe ShengWensha YangRichard Tuli

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Quantifying vascular invasion in pancreatic cancer-a contrast CT based method for surgical resectability evaluation

机译：Quantifying vascular invasion in pancreatic cancer-a contrast CT based method for surgical resectability evaluation

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Pancreatic cancer (PC) is one of the most lethal cancers, with frequent local therapy resistance and dismal 5-year survival rate. To date, surgical resection remains to be the only treatment option offering potential cure. Unfortunately, at diagnosis, the majority of patients demonstrate varying levels of vascular infiltration, which can contraindicate surgical resection. Patients unsuitable for immediate resection are further divided into locally advanced (LA) and borderline resectable (BR), with different treatment goals and therapeutic designs. Accurate definition of resectability is thus critical for PC patients, yet the existing methods to determine resectability rely on descriptive abutment to surrounding vessels rather than quantitative geometric characterization. Here, we aim to introduce a novel intra-subject object-space support-vector-machine (OsSVM) method to quantitatively characterize the degree of vascular involvement—the main factor determining the PC resectability. Intra-subject OsSVMs were applied on 107 contrast CT scans (56 LA, BR and 26 resectable (RE) PC cases) for optimized tumor-vessel separations. Nine metrics derived from OsSVM margins were calculated as indicators of the overall vascular infiltration. The combined sets of matrics selected by the elastic net yielded high classification capability between LA and BR (AUC = 0.95), as well as BR and RE (AUC = 0.98). The proposed OsSVM method may provide an improved quantitative imaging guideline to refine the PC resectability grading system.

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《Physics in medicine and biology.》 |2020年第10期|105012-105012|共9页
作者
Yi Lao; John David; Zhaoyang FanShelly BianAlmon ShiuEric L ChangKe ShengWensha YangRichard Tuli;
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Department of Radiation Oncology, University of California-Los Angeles, Los Angeles, United States;

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原文格式 PDF
正文语种英语
中图分类 R35;
关键词
computer-aided diagnosis; quantitative resectability; SVM; contrast-CT; pancreatic cancer;

Quantifying vascular invasion in pancreatic cancer-a contrast CT based method for surgical resectability evaluation

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