Quantitative imaging to evaluate malignant potential of IPMNs

• Published in: Oncotarget 2016-12, Vol.7 (52), p.85776-85784
• Main Authors: Hanania, Alexander N, Bantis, Leonidas E, Feng, Ziding, Wang, Huamin, Tamm, Eric P, Katz, Matthew H, Maitra, Anirban, Koay, Eugene J
• Format: Article
• Language: English
• Subjects: Adenocarcinoma, Mucinous - diagnostic imaging; Adenocarcinoma, Mucinous - pathology; Aged; Aged, 80 and over; Carcinoma, Pancreatic Ductal - diagnostic imaging; Carcinoma, Pancreatic Ductal - pathology; Carcinoma, Papillary - diagnostic imaging; Carcinoma, Papillary - pathology; Female; Humans; Logistic Models; Male; Middle Aged; Pancreatic Neoplasms - diagnostic imaging; Pancreatic Neoplasms - pathology; Research Paper; Retrospective Studies; Tomography, X-Ray Computed
• ISSN: 1949-2553; 1949-2553
• DOI: 10.18632/oncotarget.11769

To investigate using quantitative imaging to assess the malignant potential of intraductal papillary mucinous neoplasms (IPMNs) in the pancreas. Pancreatic cysts are identified in over 2% of the population and a subset of these, including intraductal papillary mucinous neoplasms (IPMNs), represent pre-malignant lesions. Unfortunately, clinicians cannot accurately predict which of these lesions are likely to progress to pancreatic ductal adenocarcinoma (PDAC). We investigated 360 imaging features within the domains of intensity, texture and shape using pancreatic protocol CT images in 53 patients diagnosed with IPMN (34 "high-grade" [HG] and 19 "low-grade" [LG]) who subsequently underwent surgical resection. We evaluated the performance of these features as well as the Fukuoka criteria for pancreatic cyst resection. In our cohort, the Fukuoka criteria had a false positive rate of 36%. We identified 14 imaging biomarkers within Gray-Level Co-Occurrence Matrix (GLCM) that predicted histopathological grade within cyst contours. The most predictive marker differentiated LG and HG lesions with an area under the curve (AUC) of .82 at a sensitivity of 85% and specificity of 68%. Using a cross-validated design, the best logistic regression yielded an AUC of 0.96 (σ = .05) at a sensitivity of 97% and specificity of 88%. Based on the principal component analysis, HG IPMNs demonstrated a pattern of separation from LG IPMNs. HG IPMNs appear to have distinct imaging properties. Further validation of these findings may address a major clinical need in this population by identifying those most likely to benefit from surgical resection.