{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,30]],"date-time":"2026-07-30T14:03:42Z","timestamp":1785420222384,"version":"3.56.0"},"reference-count":41,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2026,5,21]],"date-time":"2026-05-21T00:00:00Z","timestamp":1779321600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Tulane University School of Medicine"},{"id":[{"id":"https:\/\/ror.org\/04vmvtb21","id-type":"ROR","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Cancers"],"abstract":"<jats:p>Background. Preoperative risk stratification of pancreatic neuroendocrine tumors (PNETs) is constrained by the unavailability of histologic grade before resection. We hypothesized that a panel of biologically informed CT-radiomic signatures, combined with patient-level \u0394-radiomics referenced to the contralateral pancreas, would support preoperative discrimination of progression and grade in a two-center pilot cohort. Methods. Forty-four patients with histologically confirmed PNET who underwent contrast-enhanced preoperative CT and surgical resection at two academic centers were analyzed. Lesion and contralateral non-tumor-bearing pancreatic parenchyma regions of interest were revised in 3D Slicer by a board-certified pancreatic surgeon and verified intraoperatively against surgical pathology. PyRadiomics v3.0 features were extracted with IBSI-concordant settings. Parametric ComBat batch correction was applied across the two centers (biological-covariate balance verified beforehand), and \u0394-radiomic features (lesion combat\u2013pancreas combat) were computed for the 106 intensity\/texture primitives. We constructed a panel of biology-informed hybrid signatures partitioned into a preoperative lesion-only family (Family A; seven signatures) and a preoperative \u0394-radiomic family (Family B; three signatures). Candidate features were filtered through correlation clustering, baseline-adjusted likelihood-ratio testing with Benjamini\u2013Hochberg FDR control, and 100-bootstrap stability selection. Three predictor blocks were compared per target with three classifiers each (Logistic Regression, Random Forest, Gradient Boosting): M0 (five-variable clinical baseline), MA (M0 + Family A), and MB (M0 + Family B). Discrimination was reported as AUC with bootstrap 95% CI; calibration was assessed using the Brier score and TRIPOD-recommended calibration intercept and slope; and cross-center generalization was evaluated with leave-one-center-out (LOCO) cross-validation. Univariable Cox regression with bootstrap and permutation inference was used for progression-free survival (PFS). Results. The cohort had 16 progression events and eight deaths (median follow-up was 38 months, IQR 14\u201359). Prespecified clinical\u2013radiomic and \u0394-radiomic signatures were associated with progression-free survival, including B2 = \u0394Busyness \u00d7 Ki-67 (HR 0.38, 95% CI 0.19\u20130.76, p = 0.006). For progression prediction, the \u0394-radiomic model achieved the strongest discrimination, with a nested cross-validation AUC of 0.85 and leave-one-center-out AUC of 0.87. For higher-grade disease, radiomic models also demonstrated high discrimination, with AUCs up to 0.93. Conclusions. Radiomics-derived shape and texture features, especially when combined with clinical markers, may noninvasively identify aggressive PNET phenotypes and support preoperative risk stratification. Prospective validation in larger multicenter cohorts is warranted.<\/jats:p>","DOI":"10.3390\/cancers18101663","type":"journal-article","created":{"date-parts":[[2026,5,21]],"date-time":"2026-05-21T09:29:58Z","timestamp":1779355798000},"page":"1663","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Novel Radiomics-Integrated Panel for Preoperative Stratification of Pancreatic Neuroendocrine Tumors (PNETs)"],"prefix":"10.3390","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2163-0637","authenticated-orcid":false,"given":"Abdallah","family":"Attia","sequence":"first","affiliation":[{"name":"Department of Surgery, Tulane University School of Medicine, New Orleans, LA 70112, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jihun","family":"Hamm","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Tulane University School of Science and Engineering, New Orleans, LA 70118, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mahmoud A.","family":"AbdAlnaeem","sequence":"additional","affiliation":[{"name":"Department of Surgery, Tulane University School of Medicine, New Orleans, LA 70112, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhengming","family":"Ding","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Tulane University School of Science and Engineering, New Orleans, LA 70118, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2425-3323","authenticated-orcid":false,"given":"Michael","family":"O\u2019Rorke","sequence":"additional","affiliation":[{"name":"Department of Surgery, University of Iowa Carver College of Medicine, Iowa City, IA 52242, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4002-1418","authenticated-orcid":false,"given":"Joseph","family":"Dillon","sequence":"additional","affiliation":[{"name":"Department of Surgery, University of Iowa Carver College of Medicine, Iowa City, IA 52242, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mary","family":"Maluccio","sequence":"additional","affiliation":[{"name":"Department of Surgery, Louisiana State University Health Sciences Center, New Orleans, LA 70112, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0965-3836","authenticated-orcid":false,"given":"Nicholas","family":"Skill","sequence":"additional","affiliation":[{"name":"Department of Surgery, Louisiana State University Health Sciences Center, New Orleans, LA 70112, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kristen","family":"Limbach","sequence":"additional","affiliation":[{"name":"Department of Surgery, Tulane University School of Medicine, New Orleans, LA 70112, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,5,21]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"934","DOI":"10.1002\/cncr.11105","article-title":"A 5-decade analysis of 13,715 carcinoid tumors","volume":"97","author":"Modlin","year":"2003","journal-title":"Cancer"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"589","DOI":"10.1002\/cncr.29099","article-title":"Exploring the rising incidence of neuroendocrine tumors: A population-based analysis of epidemiology, metastatic presentation, and 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