Potential Pitfalls in Diagnostic Digital Image Analysis: Experience with Ki-67 and PHH3 in Gastrointestinal Neuroendocrine Tumors

Hacking, Sean; Sajjan, Sujata; Lee, Lili; Ziemba, Yonah; Angert, Mallorie; Yang, Yihe; Cao, Ji; Chavarria, Hector; Kataria, Nidhi; Jain, Swachi; Nasim, Mansoor

doi:10.1016/j.prp.2019.152753

Cited by 11 publications

(14 citation statements)

References 26 publications

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“…This is in line with the results of others. 15,33,36 Accordingly, we believe the DIA and use of PHH3 are not supported for routine use or as an alternative in GEP-NEN grading. Some of the cases with low Ki67 had high PHH3.…”

Section: Discussionmentioning

confidence: 94%

“…This does not apply to all DIAs, which may partly explain the previously reported poor concordance between the DIA and manual analysis of Ki67 found by others. 33 …”

Section: Discussionmentioning

confidence: 99%

“…This illustrates the difficulty in separating grade 1 and grade 2 tumors. 33 , 37 A factor that might explain this finding is that the DIA method makes it easier to identify a hot spot than manual evaluation in a busy routine practice. With DIA, measurements can be repeated or several areas can be measured if the hot spot is difficult to identify.…”

Section: Discussionmentioning

confidence: 99%

“…Compared with other studies of GEP-NENs, the number of included patients with grades 2 and 3 was high, and the distribution of different grades was more even. 13,17,30,[33][34][35] A limitation of our study is that almost 40% of the tumor samples were from biopsies. However, this is in line with current routine practice at many centers since surgical specimens are not achievable for all patients, especially patients with advanced disease.…”

Section: Discussionmentioning

confidence: 99%

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Digital Image Analysis of the Proliferation Markers Ki67 and Phosphohistone H3 in Gastroenteropancreatic Neuroendocrine Neoplasms: Accuracy of Grading Compared With Routine Manual Hot Spot Evaluation of the Ki67 Index

Lea

Gudlaugsson²,

Skaland³

et al. 2021

Applied Immunohistochemistry &Amp; Molecular Morphology

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Gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs) are rare epithelial neoplasms. Grading is based on mitotic activity or the percentage of Ki67-positive cells in a hot spot. Routine methods have poor intraobserver and interobserver consistency, and objective measurements are lacking. This study aimed to evaluate digital image analysis (DIA) as an objective assessment of proliferation markers in GEP-NENs. A consecutive cohort of patients with automated DIA measurement of Ki67 (DIA Ki67) and phosphohistone H3 (DIA PHH3) on immunohistochemical slides was analyzed using Visiopharm image analysis software (Hoersholm, Denmark). The results were compared with the Ki67 index from routine pathology reports (pathology Ki67). The study included 159 patients (57% males). The median pathology Ki67 was 2.0% and DIA Ki67 was 4.1%. The interclass correlation coefficient of the DIA Ki67 compared with the pathology Ki67 showed an excellent agreement of 0.96 [95% confidence interval (CI): 0.94-0.96]. The observed kappa value was 0.86 (95% CI: 0.81-0.91) when comparing grades based on the same methods. PHH3 was measured in 145 (91.2%) cases. The observed kappa value was 0.74. (95% CI: 0.65-0.83) when comparing grade based on the DIA PHH3 and the pathology Ki67. The DIA Ki67 shows excellent agreement with the pathology Ki67. The DIA PHH3 measurements were more varied and cannot replace other methods for grading GEP-NENs.

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Section: Discussionmentioning

confidence: 94%

“…This does not apply to all DIAs, which may partly explain the previously reported poor concordance between the DIA and manual analysis of Ki67 found by others. 33 …”

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Digital Image Analysis of the Proliferation Markers Ki67 and Phosphohistone H3 in Gastroenteropancreatic Neuroendocrine Neoplasms: Accuracy of Grading Compared With Routine Manual Hot Spot Evaluation of the Ki67 Index

Lea

Gudlaugsson²,

Skaland³

et al. 2021

Applied Immunohistochemistry &Amp; Molecular Morphology

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“…Of note, more sophisticated AI-algorithms are being developed that only count neoplastic cells 47 – 49 and become more operator-independent. One potential solution that also has been employed is to utilize double-stained slides (e.g., Ki-67 and synaptophysin) with deep learning algorithms to improve the accuracy of Ki-67 index quantification 50 – 53 . More recently, some investigators have shown that they are able to predict Ki-67 positive cells directly from H&E images using AI-based methods 51 .…”

Section: Discussionmentioning

confidence: 99%

Ki-67 assessment of pancreatic neuroendocrine neoplasms: Systematic review and meta-analysis of manual vs. digital pathology scoring

et al. 2022

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Ki-67 assessment is a key step in the diagnosis of neuroendocrine neoplasms (NENs) from all anatomic locations. Several challenges exist related to quantifying the Ki-67 proliferation index due to lack of method standardization and inter-reader variability. The application of digital pathology coupled with machine learning has been shown to be highly accurate and reproducible for the evaluation of Ki-67 in NENs. We systematically reviewed all published studies on the subject of Ki-67 assessment in pancreatic NENs (PanNENs) employing digital image analysis (DIA). The most common advantages of DIA were improvement in the standardization and reliability of Ki-67 evaluation, as well as its speed and practicality, compared to the current gold standard approach of manual counts from captured images, which is cumbersome and time consuming. The main limitations were attributed to higher costs, lack of widespread availability (as of yet), operator qualification and training issues (if it is not done by pathologists), and most importantly, the drawback of image algorithms counting contaminating non-neoplastic cells and other signals like hemosiderin. However, solutions are rapidly developing for all of these challenging issues. A comparative meta-analysis for DIA versus manual counting shows very high concordance (global coefficient of concordance: 0.94, 95% CI: 0.83–0.98) between these two modalities. These findings support the widespread adoption of validated DIA methods for Ki-67 assessment in PanNENs, provided that measures are in place to ensure counting of only tumor cells either by software modifications or education of non-pathologist operators, as well as selection of standard regions of interest for analysis. NENs, being cellular and monotonous neoplasms, are naturally more amenable to Ki-67 assessment. However, lessons of this review may be applicable to other neoplasms where proliferation activity has become an integral part of theranostic evaluation including breast, brain, and hematolymphoid neoplasms.

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Ki‐67 proliferation index in neuroendocrine tumors: Can augmented reality microscopy with image analysis improve scoring?

Satturwar

Pantanowitz

Manko

et al. 2020

Cancer Cytopathology

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BackgroundThe Ki‐67 index is important for grading neuroendocrine tumors (NETs) in cytology. However, different counting methods exist. Recently, augmented reality microscopy (ARM) has enabled real‐time image analysis using glass slides. The objective of the current study was to compare different traditional Ki‐67 scoring methods in cell block material with newer methods such as ARM.MethodsKi‐67 immunostained slides from 50 NETs of varying grades were retrieved (39 from the pancreas and 11 metastases). Methods with which to quantify the Ki‐67 index in up to 3 hot spots included: 1) “eyeball” estimation (EE); 2) printed image manual counting (PIMC); 3) ARM with live image analysis; and 4) image analysis using whole‐slide images (WSI) (field of view [FOV] and the entire slide).ResultsThe Ki‐67 index obtained using the different methods varied. The pairwise kappa results varied from no agreement for image analysis using digital image analysis WSI (FOV) and histology to near‐perfect agreement for ARM and PIMC. Using surgical pathology as the gold standard, the EE method was found to have the highest concordance rate (84.2%), followed by WSI analysis of the entire slide (73.7%) and then both the ARM and PIMC methods (63.2% for both). The PIMC method was the most time‐consuming whereas image analysis using WSI (FOV) was the fastest method followed by ARM.ConclusionsThe Ki‐67 index for NETs in cell block material varied by the method used for scoring, which may affect grade. PIMC was the most time‐consuming method, and EE had the highest concordance rate. Although real‐time automated counting using image analysis demonstrated inaccuracies, ARM streamlined and hastened the task of Ki‐67 quantification in NETs.

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Potential Pitfalls in Diagnostic Digital Image Analysis: Experience with Ki-67 and PHH3 in Gastrointestinal Neuroendocrine Tumors

Cited by 11 publications

References 26 publications

Digital Image Analysis of the Proliferation Markers Ki67 and Phosphohistone H3 in Gastroenteropancreatic Neuroendocrine Neoplasms: Accuracy of Grading Compared With Routine Manual Hot Spot Evaluation of the Ki67 Index

Digital Image Analysis of the Proliferation Markers Ki67 and Phosphohistone H3 in Gastroenteropancreatic Neuroendocrine Neoplasms: Accuracy of Grading Compared With Routine Manual Hot Spot Evaluation of the Ki67 Index

Ki-67 assessment of pancreatic neuroendocrine neoplasms: Systematic review and meta-analysis of manual vs. digital pathology scoring

Ki‐67 proliferation index in neuroendocrine tumors: Can augmented reality microscopy with image analysis improve scoring?

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