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Nomogram_OPM_AGC: CT radiomic nomogram for preoperatively identify occult peritoneal metastasis (PM) in patients with advanced gastric cancer (AGC). The nomogram combines the signatures of primary tumor and nearby peritoneal region, as well as the Lauren type. We suggest the clinicians and physicians to use it to avoid suboptimal clinical practice, such as the improper use of surgical treatment for occult peritoneal metastasis patient which negatively affects patient prognosis. To use this model, one should outline the 2D primary tumor (ROI-1) in one slice with the maximum-tumor-area, and also outline the 2D peritoneum region (ROI-2, area>2cm2) nearest to the center of the primary tumor. All these processes are done in venous phase CT. Besides, Lauren type is also required for better prediction performance. The signatures of primary tumor (RS1) and the nearby peritoneum (RS2) will extracted from ROI-1 and ROI-2 respectively. The two signatures and Lauren type are input into the radiomic nomogram. Then the possible PM status will be given by the nomogram.
Occult peritoneal metastasis (PM) in advanced gastric cancer (AGC) patients is highly possible to be missed on CT images, and the patients have high risk to be lately detected during the subsequent laparotomy, or worse, receive improper surgery. We aimed to develop a radiomic nomogram to identify occult PMs.
A total of 554 AGC patients from four centers were divided into a training cohort and three validation cohorts. All patients were diagnosed as free from PM by CT, but confirmed the PM status by laparoscopy (PM positive n=122, PM negative n=432). 266 quantitative image features were extracted from both the primary tumor and nearby peritoneum region on CT. Then, radiomic signatures reflecting phenotypes of primary tumor (RS1) and peritoneum (RS2) were built as predictors of PM. An individualized nomogram incorporating RS1, RS2, and clinical factors was constructed and assessed.
The results revealed RS1, RS2, and the clinical factor of Lauren type were significant predictors for occult PM. The nomogram combining RS1, RS2 and Lauren type had powerful predictive ability with AUCs of 0.958 (95% confidence interval [CI]: 0.923-0.993) in the training cohort, 0.941 (95% CI: 0.904-0.977), 0.928 (95% CI: 0.886-0.971) and 0.920 (95% CI: 0.862-0.978) in the three validation cohorts. Moreover, the nomogram demonstrated better diagnostic accuracy than the model with only RS1, RS2, or clinical factors (net reclassification improvement p<0.05). Furthermore, the stratification analysis showed that our nomogram had potential generalization ability.
CT phenotypes of both primary tumor and nearby peritoneum are significantly associated with occult PM status. A nomogram based on these CT phenotypes as well as Lauren type has an excellent predictive ability of occult PM in AGC.