Traditional Serrated Adenomas on CT Colonography: International Multicenter Experience With This Rare Colorectal Neoplasm.

OBJECTIVE. Serrated polyps include hyperplastic polyps, sessile serrated polyps, and traditional serrated adenomas (TSAs). Hyperplastic polyps and sessile serrated polyps account for approximately 99% of all serrated lesions; TSAs are rare. However, both sessile serrated polyps and TSAs are now recognized as precursor lesions to carcinogenesis, representing approximately one-fourth of all sporadic colorectal cancers. We report what is, to our knowledge, the first series describing the characteristics of CTAs on CT colonography (CTC). MATERIALS AND METHODS. An international, multicenter, retrospective review of CT colonography-detected TSAs diagnosed between 2008 and 2018 was conducted. Data collected included patient demographics and data from CTC, optical colonoscopy, and pathologic analysis. RESULTS. A total of 67 proven TSAs in 58 patients (mean age, 67 years) were identified. The majority (66%) were located in the distal colon (descending colon, sigmoid colon, and rectum), and their mean size was 19 mm (range, 3-80 mm). Small (< 10 mm) TSAs typically had a simple sessile or pedunculated morphologic appearance, whereas large (≥ 10 mm) TSAs tended to be more lobulated and irregular, pedunculated, or carpetlike. The majority (88%) showed at least some contrast medium surface coating. CONCLUSION. We report what we believe to be the first multicenter experience describing the characteristics of TSAs on CTC. Unlike sessile serrated lesions, TSAs are more often left-sided and tend to be more lobulated and irregular. However, like sessile serrated polyps, most TSAs show contrast medium surface coating. Detection of these rare lesions on CTC is important, given their malignant potential.

Delta-Radiomics Predicts Response to First-Line Oxaliplatin-Based Chemotherapy in Colorectal Cancer Patients with Liver Metastases.

The purpose of this paper is to develop and validate a delta-radiomics score to predict the response of individual colorectal cancer liver metastases (lmCRC) to first-line FOLFOX chemotherapy. Three hundred one lmCRC were manually segmented on both CT performed at baseline and after the first cycle of first-line FOLFOX, and 107 radiomics features were computed by subtracting textural features of CT at baseline from those at timepoint 1 (TP1). LmCRC were classified as nonresponders (R-) if they showed progression of disease (PD), according to RECIST1.1, before 8 months, and as responders (R+), otherwise. After feature selection, we developed a decision tree statistical model trained using all lmCRC coming from one hospital. The final output was a delta-radiomics signature subsequently validated on an external dataset. Sensitivity, specificity, positive (PPV), and negative (NPV) predictive values in correctly classifying individual lesions were assessed on both datasets. Per-lesion sensitivity, specificity, PPV, and NPV were 99%, 94%, 95%, 99%, 85%, 92%, 90%, and 87%, respectively, in the training and validation datasets. The delta-radiomics signature was able to reliably predict R- lmCRC, which were wrongly classified by lesion RECIST as R+ at TP1, (93%, averaging training and validation set, versus 67% of RECIST). The delta-radiomics signature developed in this study can reliably predict the response of individual lmCRC to oxaliplatin-based chemotherapy. Lesions forecasted as poor or nonresponders by the signature could be further investigated, potentially paving the way to lesion-specific therapies.