Comparison between Ki67 labeling index determined using image analysis software with virtual slide system and that determined visually in breast cancer

Ki-67 assessment-agreeability between immunohistochemistry and flow cytometry in canine lymphoma

Recent literature suggests a combination of flow cytometric determination of Ki-67 and immunophenotype as a reliable tool to classify canine lymphomas. Immunohistochemistry (IHC) on histological samples is the gold standard technique assessing Ki-67 index. Agreement between IHC and FCM derived Ki-67 indices has never been investigated. The aim of this study was to investigate the agreement between IHC and FCM in the assessment of Ki-67 expression/index, in order to evaluate whether FCM may serve as a non-invasive alternative method for the estimation of proliferative activity in canine lymphoma. Dogs with previously untreated canine lymphoma undergoing diagnostic lymphadenectomy were prospectively enrolled. Ki-67 expression/index was assessed by FCM and IHC and expressed as percentage of positive cells. 39 dogs classified by histopathology matched the inclusion criteria. With both methods, Ki-67 expression/index was higher in intermediate/high-grade lymphomas. Spearman's coefficient of correlation was ρ = 0.57; (95% CI0.33-0.75) suggesting a moderate correlation. A Bland-Altman plot revealed a negative constant bias of -3.55 (95% CI: -10.52 to 3.42) with limits of agreement from -45.71 to 38.61. The study confirmed agreement albeit with wide confidence intervals between the values of Ki-67 expression/index assessed with FCM and IHC. Discrepancies were observed in a subset of cases. Possible explanation could be that Ki-67 index in IHC is determined in the most proliferative areas of the slide, which could introduce kind of sampling bias, whereas FCM evaluates many more cells in cell suspension. Further studies are warranted to investigate this phenomenon.

Concomitant use of 18F-FDG PET-CT SUVmax is useful in the assessment of Ki67 labeling index in core-needle biopsy specimens of breast cancer

Background

Ki67 is a recognized proliferative and predictive marker in invasive breast cancer. However, results of Ki67 evaluation are affected by the method employed for sample fixation or biopsy, as well as by intratumor heterogeneity. Here, we aimed to compare the Ki67 labeling index (Ki67LI) between core-needle biopsy specimens (CNBSs) and surgically resected specimens (SRSs) of invasive breast cancer, and verify whether the discordance in Ki67LI can be reduced by analyzing the maximum standardized uptake value (SUVmax) obtained from pretreatment whole-body positron emission tomography/computed tomography (PET/CT) in combination with Ki67LI.

Methods

Tumor tissues were obtained from 118 patients with invasive breast cancer. Ki67LI was evaluated in CNBSs and SRSs by immunohistochemistry. First, we directly compared Ki67LI between CNBS and SRS, "allowing a tolerance margin of 5%." We divided the Ki67LI values into three groups (Low: 0≤ Ki67LI ≤10, Intermediate: 10< Ki67LI <30, and High: 30≤ Ki67LI) and the SUVmax into three groups (SUVmax ≤4, 4< SUVmax <8, and 8≤ SUVmax). We then verified the concordance rate between CNBS and SRS in each group in combination with the SUVmax obtained by PET/CT.

Results

The median Ki67LI was 17.8% (0.5-75.9%) and 17.0% (1.0-75.7%) in CNBS and SRS, respectively. The overall Ki67LI concordance rate between CNBS and SRS was 37.3% (44/118). The concordance was improved in the Low and High Ki67LI groups by applying SUVmax thresholds of 4 [82.6% (19/23), P=0.033 and 8 (92.3% (12/13), P=0.009], respectively.

Conclusions

Our results indicated that CNBS Ki67LI alone was not able to reflect SRS Ki67LI with sufficient accuracy. By dividing CNBS Ki67LI into three classes in combination with SUVmax, tumor proliferation could be predicted with higher accuracy in patients with invasive breast carcinoma.

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

BACKGROUND

The 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.

METHODS

Ki-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).

RESULTS

The 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.

CONCLUSIONS

The 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.

Cross-Platform Comparison of Computer-assisted Image Analysis Quantification of In Situ mRNA Hybridization in Investigative Pathology

Although availability of automated platforms has proliferated, there is no standard practice for computer-assisted generation of scores for mRNA in situ hybridization (ISH) visualized by brightfield microscopic imaging on tissue sections. To address this systematically, an ISH for peptidylprolyl isomerase B (PPIB) (cyclophilin B) mRNA was optimized and applied to a tissue microarray of archival non-small cell lung carcinoma cases, and then automated image analysis for PPIB was refined across 4 commercially available software platforms. Operator experience and scoring results from ImageScope, HALO, CellMap, and Developer XD were systematically compared with each other and to manual pathologist scoring. Markup images were compared and contrasted for accuracy, the ability of the platform to identify cells, and the ease of visual assessment to determine appropriate interpretation. Comparing weighted scoring approaches using H-scores (Developer XD, ImageScope, and manual scoring) a correlation was observed (R value=0.7955), and association between the remaining 2 approaches (HALO and CellMap) was of similar value. ImageScope showed the highest R value in comparison with manual scoring (0.7377). Mean-difference plots showed that HALO produced the highest relative normalized values, suggesting higher relative sensitivity. ImageScope overestimated PPIB ISH signal at the high end of the range scores; however, this tendency was not observed in other platforms. HALO emerged with the highest number of favorable observations, no apparent systematic bias in score generation compared with the other methods, and potentially higher sensitivity to detect ISH. HALO may serve as a tool to empower teams of investigative pathology laboratory scientists to assist pathologists readily with quantitative scoring of ISH.

Differential clinicopathologic features of EGPA-associated neuropathy with and without ANCA

OBJECTIVE

To investigate the clinicopathologic features of eosinophilic granulomatosis with polyangiitis (EGPA)-associated neuropathy with a focus on the presence or absence of anti-neutrophil cytoplasmic antibodies (ANCAs).

METHODS

We examined the clinical features and pathologic findings of sural nerve biopsy specimens from 82 patients with EGPA-associated neuropathy. Of these patients, 32.9% were myeloperoxidase (MPO)-ANCA positive, and 67.1% were MPO-ANCA negative. PR3-ANCA was negative in all of 78 examined patients.

RESULTS

Upper limb symptoms were more frequently reported as initial neuropathic manifestations in the MPO-ANCA-positive group than in the MPO-ANCA-negative group (44.4% vs 14.6%, p < 0.01). The serum levels of C-reactive protein were significantly higher in the MPO-ANCA-positive group than in the MPO-ANCA-negative group (p < 0.05). Sural nerve biopsy specimens showed findings suggestive of vasculitis (i.e., destruction of vascular structures) in epineurial vessels; these results were seen more frequently in the MPO-ANCA-positive group than in the MPO-ANCA-negative group (p < 0.0001). Conversely, the numbers of eosinophils in the lumen of the epineurial vessels (p < 0.01) and epineurial vessels occluded by intraluminal eosinophils (p < 0.05) were higher in the MPO-ANCA-negative group than in the MPO-ANCA-positive group. Furthermore, the incidence of eosinophil infiltration in the endoneurium was higher in the MPO-ANCA-negative group than in the MPO-ANCA-positive group (p < 0.01).

CONCLUSIONS

This study suggests that the pathogenesis of EGPA comprises at least 2 distinct mechanisms: ANCA-associated vasculitis resulting in ischemic effects and inflammation, which is prominent in MPO-ANCA-positive patients, and eosinophil-associated vascular occlusion leading to ischemia and eosinophil-associated tissue damage, which is conspicuous in MPO-ANCA-negative patients.

Practical approaches to automated digital image analysis of Ki-67 labeling index in 997 breast carcinomas and causes of discordance with visual assessment

The Ki-67 labeling index (LI) is an important prognostic factor in breast carcinoma. The Ki-67 LI is traditionally calculated via unaided microscopic estimation; however, inter-observer and intra-observer variability and low reproducibility are problems with this visual assessment (VA) method. For more accurate assessment and better reproducibility with Ki-67 LI, digital image analysis was introduced recently. We used both VA and automated digital image analysis (ADIA) (Ventana Virtuoso image management software) to estimate Ki-67 LI for 997 cases of breast carcinoma, and compared VA and ADIA results. VA and ADIA were highly correlated (intraclass correlation coefficient 0.982, and Spearman’s correlation coefficient 0.966, p<0.05). We retrospectively analyzed cases with a greater than 5% difference between VA and ADIA results. The cause of these differences was: (1) tumor heterogeneity (98 cases, 56.0%), (2) VA interpretation error (32 cases, 18.3%), (3) misidentification of tumor cells (26 cases, 14.9%), (4) poor immunostaining or slide quality (16 cases, 9.1%), and (5) Estimation of non-tumor cells (3 cases, 1.7%). There were more discrepancies between VA and ADIA results in the group with a VA value of 10–20% compared to groups with <10% and ≥20%. Although ADIA is more accurate than VA, there are some limitations. Therefore, ADIA findings require confirmation by a pathologist.

Ancillary Prognostic and Predictive Testing in Breast Cancer: Focus on Discordant, Unusual, and Borderline Results

Ancillary testing in breast cancer has become standard of care to determine what therapies may be most effective for individual patients with breast cancer. Single-marker tests are required on all newly diagnosed and newly metastatic breast cancers. Markers of proliferation are also used, and include both single-marker tests like Ki67 as well as panel-based gene expression tests, which have made more recent contributions to prognostic and predictive testing in breast cancers. This review focuses on pathologist interpretation of these ancillary test results, with a focus on expected versus unexpected results and troubleshooting borderline, unusual, or discordant results.

Value of K i -67 Labeling Index in Predicting Recurrence of WHO Grade I Cranial Base Meningiomas

Objectives  Assess impact of K _i -67 labeling index (LI; K _i -67 LI) on risk of recurrence or progression of WHO grade I meningiomas. Study Design  Retrospective study of adult patients who underwent resection of cranial base meningioma between 2004 and 2016. Results  272 patients fulfilled criteria for inclusion in the study. Average age was 61.8 years; 196 (72%) were females. Simpson's grade 1 resection was noted in 77 patients (32%), grade 2 in 39 (16%), grade 3 in 36 (15%), and grade 4 in 88 (37%). The K _i -67 LI was low (1-4%) in 214 (78.7%), intermediate (5-9%) in 44 (16.2%), and high (>10%) in 14 (5.2%). Median follow-up was 39 months (IQR: 16-71 months); 221 (87.1%) tumors remained stable or did not recur, 19 (7.4%) recurred, and 14 (5.5%) progressed. Compared with tumors with low K _i -67 LI, those with intermediate K _i -67 LI had 2.47 times (2.47 [1.09-5.59], p  = 0.03), and those with high K _i -67 LI had 3.38 times (3.38 [1.16-9.89], p  = 0.03) higher risk of recurrence or progression. Tumors with K _i -67 LI > 4% had a shorter time to recurrence or progression ( p  = 0.01). Recurrence or progression-free survival rates at 3, 5, and 10 years for tumors with low K _i -67 LI were 95%, 89%, and 75%, respectively; tumors with intermediate K _i -67 LI, 87%, 69%, and 52%, respectively; tumors with high K _i -67 LI, 78%, 49%, and 49%, respectively. Conclusions  Following surgical resection of a WHO grade I cranial base meningioma, K _i -67 LI > 4% may predict an increased risk of recurrence or progression of residual tumor.

Relationship between the Ki67 index and its area based approximation in breast cancer

BACKGROUND

The Ki67 Index has been extensively studied as a prognostic biomarker in breast cancer. However, its clinical adoption is largely hampered by the lack of a standardized method to assess Ki67 that limits inter-laboratory reproducibility. It is important to standardize the computation of the Ki67 Index before it can be effectively used in clincial practice.

METHOD

In this study, we develop a systematic approach towards standardization of the Ki67 Index. We first create the ground truth consisting of tumor positive and tumor negative nuclei by registering adjacent breast tissue sections stained with Ki67 and H&E. The registration is followed by segmentation of positive and negative nuclei within tumor regions from Ki67 images. The true Ki67 Index is then approximated with a linear model of the area of positive to the total area of tumor nuclei.

RESULTS

When tested on 75 images of Ki67 stained breast cancer biopsies, the proposed method resulted in an average root mean square error of 3.34. In comparison, an expert pathologist resulted in an average root mean square error of 9.98 and an existing automated approach produced an average root mean square error of 5.64.

CONCLUSIONS

We show that it is possible to approximate the true Ki67 Index accurately without detecting individual nuclei and also statically demonstrate the weaknesses of commonly adopted approaches that use both tumor and non-tumor regions together while compensating for the latter with higher order approximations.

Comparison of Ki-67 labeling index measurements using digital image analysis and scoring by pathologists

BACKGROUND

Routine analysis of Ki-67 is not widely recommended for clinical decision-making because of poor reproducibility. Furthermore, counting numerous cells can be laborious for pathologists. Digital image analysis for immunohistochemical analysis was recently developed; however, the clinical efficacy of the Ki-67 index obtained using image analysis is unknown.

METHODS

We retrospectively identified female patients with breast cancer with immunohistochemical Ki-67 and survival data using the pathology database at the Tokai University, Japan. Ki-67 expression was scored by three pathologists. Slides were scanned and converted to virtual slides; Ki-67-positive cells were counted using image analysis. Ki-67 indices obtained by the pathologist's scoring and image analysis were evaluated by 2 × 2 analysis. Relationships between Ki-67 index and survival outcomes were evaluated using the Kaplan-Meier method and compared using the log-rank test.

RESULTS

Based on the 2 × 2 analysis, Ki-67 index obtained using image analysis was moderately correlated with the pathologist's scoring for all patients (κ 0.41; sensitivity, 0.573; specificity, 0.878). Poorer relapse-free survival was associated with high Ki-67 index than with low Ki-67 index for estrogen receptor-positive, human epidermal growth factor receptor 2-negative, and stage I or II patients scored by pathologists (p < 0.001) and obtained using image analysis (p = 0.031).

CONCLUSIONS

The Ki-67 indices obtained using image analysis were moderately correlated with those scored by pathologists. Digital image analysis can be effective for measuring Ki-67 values, because they are associated with relapse-free survival in estrogen receptor-positive, human epidermal growth factor receptor 2-negative, and patients at stage I or II.

Construction of a pathological risk model of occult lymph node metastases for prognostication by semi-automated image analysis of tumor budding in early-stage oral squamous cell carcinoma

It is challenging to identify at diagnosis those patients with early oral squamous cell carcinoma (OSCC), who have a poor prognosis and those that have a high risk of harboring occult lymph node metastases. The aim of this study was to develop a standardized and objective digital scoring method to evaluate the predictive value of tumor budding. We developed a semi-automated image-analysis algorithm, Digital Tumor Bud Count (DTBC), to evaluate tumor budding. The algorithm was tested in 222 consecutive patients with early-stage OSCC and major endpoints were overall (OS) and progression free survival (PFS). We subsequently constructed and cross-validated a binary logistic regression model and evaluated its clinical utility by decision curve analysis. A high DTBC was an independent predictor of both poor OS and PFS in a multivariate Cox regression model. The logistic regression model was able to identify patients with occult lymph node metastases with an area under the curve (AUC) of 0.83 (95% CI: 0.78–0.89, P <0.001) and a 10-fold cross-validated AUC of 0.79. Compared to other known histopathological risk factors, the DTBC had a higher diagnostic accuracy. The proposed, novel risk model could be used as a guide to identify patients who would benefit from an up-front neck dissection.

Construction and analysis of tissue microarrays in the era of digital pathology: a pilot study targeting CDX1 and CDX2 in a colon cancer cohort of 612 patients

CDX1 and CDX2 are possibly predictive biomarkers in colorectal cancer. We combined digitally‐guided (next generation) TMA construction (ngTMA) and the utility of digital image analysis (DIA) to assess accuracy, tumour heterogeneity and the selective impact of different combined intensity‐percentage levels on prognosis.CDX1 and CDX2 immunohistochemistry was performed on ngTMAs covering normal tissue, tumour centre and invasive front. The percentages of all epithelial cells per staining intensity per core were analysed digitally. Beyond classical prognosis analysis following REMARK guidelines, we investigated pre‐analytical conditions, three different types of heterogeneity (mosaic‐like, targeted and haphazard) and influences on cohort segregation and patient selection. The ngTMA‐DIA approach produced robust biomarker data with infrequent core loss and excellent on‐target punching. The detailed assessment of tumour heterogeneity could – except for a certain diffuse mosaic‐like heterogeneity – exclude differences between the invasive front and tumour centre, as well as detect haphazard clonal heterogeneous elements. Moreover, lower CDX1 and CDX2 counts correlated with mucinous histology, higher TNM stage, higher tumour grade and worse survival (p < 0.01, all). Different protein expression intensity levels shared comparable prognostic power and a great overlap in patient selection. The combination of ngTMA with DIA enhances accuracy and controls for biomarker analysis. Beyond the confirmation of CDX1 and CDX2 as prognostically relevant markers in CRC, this study highlights the greater robustness of CDX2 in comparison to CDX1. For the assessment of CDX2 protein loss, cut‐points as percentage data of complete protein loss can be deduced as a recommendation.

Immune infiltrates in the breast cancer microenvironment: detection, characterization and clinical implication

Although unlike melanoma, breast cancer is not generally viewed as a highly immunogenic cancer, recent studies have described a rich tumor immune microenvironment in a subset of breast cancers. These immune infiltrates, comprised cells from the innate and adaptive immune response, can be detected and characterized in biopsy specimens and have prognostic value. Tumor-infiltrating lymphocytes (TILs) represent the majority of mononuclear immune infiltrates in the breast tumor microenvironment and can be easily identified in formalin-fixed paraffin-embedded tissues after standard hematoxylin and eosin staining. High levels of TILs are most common in HER2+ and basal-like subtypes where they are associated with good prognosis and with response to certain therapies such as the anti-HER2 antibody trastuzumab. International collaborative efforts are underway to standardize the assessment of TILs so as to facilitate their implementation as a breast cancer biomarker. Using immunohistochemistry to further characterize TILs, recent reports describe the presence of important lymphocyte populations including CD8+ cytotoxic, FOXP3+ regulatory, and CD4+ helper and follicular T cells which have overlapping associations with prognosis and response to therapies. Moreover, recently identified immune checkpoint markers (PD-1, PD-L1) are present in some breast cancers, implying some cases might be especially amenable to immune checkpoint inhibitor treatment strategies which are being evaluated in a number of active clinical trials.