title: Quantitative imaging to evaluate malignant potential of IPMNs.
abstract: OBJECTIVE
  To investigate using quantitative imaging to assess the malignant potential of intraductal papillary mucinous neoplasms (IPMNs) in the pancreas.
  
  
  BACKGROUND
  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).
  
  
  METHODS
  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.
  
  
  RESULTS
  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.
  
  
  CONCLUSIONS
  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.
authors: University of Texas Medical School, Houston, TX, USA.|Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, USA.
authors: Alexander N
authors: AN
authors: Hanania
authors: Department of Biostatistics, University of Texas MD Anderson Cancer Center, Houston, TX, USA.
authors: Leonidas E
authors: LE
authors: Bantis
authors: Department of Biostatistics, University of Texas MD Anderson Cancer Center, Houston, TX, USA.
authors: Ziding
authors: Z
authors: Feng
authors: Department of Pathology, University of Texas MD Anderson Cancer Center, Houston, TX, USA.
authors: Huamin
authors: H
authors: Wang
authors: Department of Diagnostic Radiology, University of Texas MD Anderson Cancer Center, Houston, TX, USA.
authors: Eric P
authors: EP
authors: Tamm
authors: Department of Surgical Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, USA.
authors: Matthew H
authors: MH
authors: Katz
authors: Department of Pathology, University of Texas MD Anderson Cancer Center, Houston, TX, USA.
authors: Anirban
authors: A
authors: Maitra
authors: Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, USA.
authors: Eugene J
authors: EJ
authors: Koay
mesh_terms: D002288:Adenocarcinoma, Mucinous / Q000000981:diagnostic imaging / Q000473:pathology*; D000368:Aged; D000369:Aged, 80 and over; D021441:Carcinoma, Pancreatic Ductal / Q000000981:diagnostic imaging / Q000473:pathology*; D002291:Carcinoma, Papillary / Q000000981:diagnostic imaging / Q000473:pathology*; D005260:Female; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D010190:Pancreatic Neoplasms / Q000000981:diagnostic imaging / Q000473:pathology*; D012189:Retrospective Studies; D014057:Tomography, X-Ray Computed
keywords: IPMN; fukuoka; pancreatic cyst; quantitative imaging; radiomics