Evaluating IPMN and pancreatic carcinoma utilizing quantitative histopathology
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Glazer_et_al-2016-Cancer_Medic ...
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Author
Glazer, Evan S.Zhang, Hao Helen
Hill, Kimberly A.
Patel, Charmi
Kha, Stephanie T.
Yozwiak, Michael L.
Bartels, Hubert
Nafissi, Nellie N.
Watkins, Joseph C.
Alberts, David S.
Krouse, Robert S.
Affiliation
Univ ArizonaIssue Date
2016-10Keywords
Intraductal papillary mucinous neoplasmskaryometry
pancreatic carcinoma
quantitative histopathology
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WILEY-BLACKWELLCitation
Evaluating IPMN and pancreatic carcinoma utilizing quantitative histopathology 2016, 5 (10):2841 Cancer MedicineJournal
Cancer MedicineRights
Copyright © 2016 The Authors. Cancer Medicine published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution License.Collection Information
This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.Abstract
Intraductal papillary mucinous neoplasms (IPMN) are pancreatic lesions with uncertain biologic behavior. This study sought objective, accurate prediction tools, through the use of quantitative histopathological signatures of nuclear images, for classifying lesions as chronic pancreatitis (CP), IPMN, or pancreatic carcinoma (PC). Forty-four pancreatic resection patients were retrospectively identified for this study (12 CP; 16 IPMN; 16 PC). Regularized multinomial regression quantitatively classified each specimen as CP, IPMN, or PC in an automated, blinded fashion. Classification certainty was determined by subtracting the smallest classification probability from the largest probability (of the three groups). The certainty function varied from 1.0 (perfectly classified) to 0.0 (random). From each lesion, 180 +/- 22 nuclei were imaged. Overall classification accuracy was 89.6% with six unique nuclear features. No CP cases were misclassified, 1/16 IPMN cases were misclassified, and 4/16 PC cases were misclassified. Certainty function was 0.75 +/- 0.16 for correctly classified lesions and 0.47 +/- 0.10 for incorrectly classified lesions (P = 0.0005). Uncertainty was identified in four of the five misclassified lesions. Quantitative histopathology provides a robust, novel method to distinguish among CP, IPMN, and PC with a quantitative measure of uncertainty. This may be useful when there is uncertainty in diagnosis.Note
Open Access Journal.ISSN
20457634PubMed ID
27666740DOI
10.1002/cam4.923Version
Final published versionSponsors
National Cancer Institute (Arizona Cancer Center) [CA023074]; National Institutes of Health, Bethesda, MD [T35HL007479]; National Science Foundation, Arlington, VA [NSF DMS-1309507, NSF DMS-1418172]; Graduate Medical Education Office at the University of Arizona; Jim Click Family Foundation, Tucson, AZ; J. Russell Skelton Family, Phoenix, AZAdditional Links
http://doi.wiley.com/10.1002/cam4.923ae974a485f413a2113503eed53cd6c53
10.1002/cam4.923
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Except where otherwise noted, this item's license is described as Copyright © 2016 The Authors. Cancer Medicine published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution License.
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