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利用定量组织病理学评估胰腺导管内乳头状黏液性肿瘤和胰腺癌。

Evaluating IPMN and pancreatic carcinoma utilizing quantitative histopathology.

作者信息

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

机构信息

University of Tennessee Health Sciences Center, Memphis, Tennessee.

The University of Arizona, Tucson, Arizona.

出版信息

Cancer Med. 2016 Oct;5(10):2841-2847. doi: 10.1002/cam4.923. Epub 2016 Sep 26.

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.

摘要

导管内乳头状黏液性肿瘤(IPMN)是生物学行为不确定的胰腺病变。本研究通过使用细胞核图像的定量组织病理学特征,寻求客观、准确的预测工具,以将病变分类为慢性胰腺炎(CP)、IPMN或胰腺癌(PC)。本研究回顾性纳入了44例接受胰腺切除术的患者(12例CP;16例IPMN;16例PC)。正则化多项回归以自动化、盲法的方式将每个标本定量分类为CP、IPMN或PC。分类确定性通过从最大分类概率(三组中)减去最小分类概率来确定。确定性函数范围从1.0(完美分类)到0.0(随机)。从每个病变中摄取了180±22个细胞核的图像。利用六个独特的细胞核特征,总体分类准确率为89.6%。没有CP病例被误分类,1/16的IPMN病例被误分类,4/16的PC病例被误分类。正确分类病变的确定性函数为0.75±0.16,错误分类病变的确定性函数为0.47±0.10(P = 0.0005)。在五个误分类病变中有四个存在不确定性。定量组织病理学提供了一种强大的新方法,可通过定量不确定性来区分CP、IPMN和PC。当诊断存在不确定性时,这可能会有所帮助。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/aa56/5083737/c503a19659c0/CAM4-5-2841-g001.jpg

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