• Bo Ram Kim, Jung Hoon Kim, Su Joa Ahn, Ijin Joo, Seo-Youn Choi, Sang Joon Park, and Joon Koo Han.
• Department of Radiology, Seoul National University Hospital, 101 Daehangno, Jongno-gu, Seoul, 110-744, Republic of Korea.
• Eur Radiol. 2019 Jan 1; 29 (1): 362-372.

ObjectivesTo assess utility of CT findings and texture analysis for predicting the resectability and prognosis in patients after neoadjuvant therapy for pancreatic ductal adenocarcinoma (PDAC).Materials And MethodsAmong 308 patients, 45 with PDAC underwent neoadjuvant therapy (concurrent-chemoradiation-therapy, CCRT, n = 27 and chemotherapy, ChoT, n = 18) before surgery were included. All underwent baseline and preoperative CT. Two reviewers assessed CT findings and resectability. We analyzed relationship between CT resectability and residual tumor. CT texture values obtained by subtracting preoperative from baseline CT were analyzed using multivariate Cox/logistic regression analysis to identify significant parameters predicting resectability and prognosis.ResultsThere were 30 patients without residual tumor (CCRT, n = 20; ChoT, n = 10) and 15 with residual tumor (CCRT, n = 7; ChoT, n = 8). Considering borderline as resectable was more accurate for R0 resectability than considering borderline as unresectable (68.9% vs 55.6% and 51.1%, p < 0.001). Particularly, neoadjuvant CCRT provided better accuracy than that in (p < 0.001). In CT texture analysis, higher subtracted entropy (cut-off: 0.03, HR 0.159, p = 0.005) and lower subtracted GLCM entropy (cut-off: -0.35, HR 10.235, p = 0.036) are important parameters for prediction of longer overall survival.ConclusionCT findings with texture analysis can be useful for predicting a patient's outcome, including resectability and prognosis, after neoadjuvant therapy for PDAC.Key Points• Considering borderline resectable tumor as resectable have better accuracy for resectability. • Considering borderline as resectable, CCRT-patients have better resectability accuracy than chemotherapy-patients. • Higher subtracted entropy and lower subtracted GLCM entropy are predictors of favorable outcome.

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