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Ki67 has potential clinical importance in breast cancer but has yet to see broad acceptance due to inter-laboratory variability. Here we tested an open source and calibrated automated digital image analysis (DIA) platform to: (i) investigate the comparability of Ki67 measurement across corresponding core biopsy and resection specimen cases, and (ii) assess section to section differences in Ki67 scoring. Two sets of 60 previously stained slides containing 30 core-cut biopsy and 30 corresponding resection specimens from 30 estrogen receptor-positive breast cancer patients were sent to 17 participating labs for automated assessment of average Ki67 expression. The blocks were centrally cut and immunohistochemically (IHC) stained for Ki67 (MIB-1 antibody). The QuPath platform was used to evaluate tumoral Ki67 expression. Calibration of the DIA method was performed as in published studies. A guideline for building an automated Ki67 scoring algorithm was sent to participating labs. Very high correlation and no systematic error (p = 0.08) was found between consecutive Ki67 IHC sections. Ki67 scores were higher for core biopsy slides compared to paired whole sections from resections (p ≤ 0.001; median difference: 5.31%). The systematic discrepancy between core biopsy and corresponding whole sections was likely due to pre-analytical factors (tissue handling, fixation). Therefore, Ki67 IHC should be tested on core biopsy samples to best reflect the biological status of the tumor.

Objective Salivary glands of primary SS (pSS) patients characteristically harbour periductal infiltrates, in which lymphoepithelial lesions (LELs) can develop. LELs are composed of hyperplastic ductal epithelium with infiltrating lymphocytes and may assist in the challenging diagnostic process of pSS. As manual identification of LELs remains difficult, we aimed to identify LELs by using an objective digital image analysis (DIA) algorithm that detects intraepithelial lymphocytes. Methods A virtual triple-staining technique developed for this study was used to count intraepithelial lymphocytes in consecutive slides stained for CD3 (T-lymphocytes), high-molecular-weight cytokeratin (hmwCK) (striated ducts) and CD20 (B-lymphocytes) in labial and parotid gland biopsies in a diagnostic cohort of 109 sicca patients. Patients were classified as having pSS or non-SS according to the ACR-EULAR classification criteria. Results T-lymphocytes were detected in almost all analysed ducts of pSS and non-SS sicca patients, whereas intraepithelial B-lymphocytes were present in 59–68% of labial and parotid gland biopsies of pSS patients, against only 2–3% of patients classified as non-SS. Intraepithelial B-lymphocytes were found in almost all striated ducts with hyperplasia (LELs). Remarkably, ∼25% of analysed striated ducts without hyperplasia of pSS patients also contained B-lymphocytes (precursor-LELs). Furthermore, presence of intraepithelial B-lymphocytes was associated with clinical parameters of pSS (i.e. serology). Conclusion The presence of intraepithelial B-lymphocytes in salivary gland biopsies of sicca patients is a clear indicator of pSS and can be used as an objective alternative to LEL scoring. Therefore, identification of B-lymphocyte–containing ducts should be added to the diagnostic histopathological work-up of patients suspected of pSS. [ABSTRACT FROM AUTHOR]

Aim Methods Results Conclusion Manual detection and scoring of Ki67 hotspots is difficult and prone to variability, limiting its clinical utility. Automated hotspot detection and scoring by digital image analysis (DIA) could improve the assessment of the Ki67 hotspot proliferation index (PI). This study compared the clinical performance of Ki67 hotspot detection and scoring DIA algorithms based on virtual dual staining (VDS) and deep learning (DL) with manual Ki67 hotspot PI assessment.Tissue sections of 135 consecutive invasive breast carcinomas were immunohistochemically stained for Ki67. Two DIA algorithms, based on VDS and DL, automatically determined the Ki67 hotspot PI. For manual assessment; two independent observers detected hotspots and calculated scores using a validated scoring protocol.Automated hotspot detection and assessment by VDS and DL could be performed in 73% and 100% of the cases, respectively. Automated hotspot detection by VDS and DL led to higher Ki67 hotspot PIs (mean 39.6% and 38.3%, respectively) compared to manual consensus Ki67 PIs (mean 28.8%). Comparing manual consensus Ki67 PIs with VDS Ki67 PIs revealed substantial correlation (r = 0.90), while manual consensus versus DL Ki67 PIs demonstrated high correlation (r = 0.95).Automated Ki67 hotspot detection and analysis correlated strongly with manual Ki67 assessment and provided higher PIs compared to manual assessment. The DL‐based algorithm outperformed the VDS‐based algorithm in clinical applicability, because it did not depend on virtual alignment of slides and correlated stronger with manual scores. Use of a DL‐based algorithm may allow clearer Ki67 PI cutoff values, thereby improving the clinical usability of Ki67. [ABSTRACT FROM AUTHOR]

Aims: We aimed to compare digital image analysis (DIA) of human epidermal growth factor receptor 2 (HER2) immunohistochemistry (IHC) in breast cancer by two platforms: (i) to validate DIA against standard diagnostics; and (ii) to evaluate the added value of DIA in clinical practice. Methods and results: HER2 IHC and in‐situ hybridisation (ISH) were performed on 152 consecutive invasive breast carcinomas. IHC scores were determined with DIA using two independent platforms. Manual scoring was performed by two independent observers. HER2 status was considered positive in 3+ and ISH‐positive 2+ cases. HER2 status using DIA was compared to HER2 status with standard diagnostics (manual scoring with ISH in 2+ cases). Interplatform agreement of IHC scores was 'moderate' (linear weighted κ = 0.58), agreement between manual scoring and platform A was 'moderate' (κ = 0.60) and between manual scoring and platform B 'almost perfect' (κ = 0.85). Compared to manual scoring, DIA resulted in a reduction of 2+ cases from 17.1 to 1.3% with platform A and from 17.1 to 15.8% with platform B. However, compared to standard diagnostics, there were three false‐negative cases with DIA using platform A [81.3% sensitivity, 100% specificity, 100% positive predictive value (PPV), 97.8% negative predictive value (NPV)]. Sensitivity, specificity, PPV and NPV were 100% with DIA using platform B. Conclusions: DIA of HER2 IHC is a valid tool in determining HER2 status in breast carcinoma. Algorithms in different platforms can behave differently, and optimal calibration is essential. In clinical practice, DIA offers an objective alternative to manual scoring, but a reduction in 2+ cases could result in loss of sensitivity. [ABSTRACT FROM AUTHOR]

The article presents a study which aims to determine the diagnostic relevance of methylation patterns of the 13 gene promoters in cervical tumor growth as well cervical cancer. Five of these 13 gene promoters were found to be more frequently methylated in frozen cervical cancer while both CCNA1 and C13ORF18 were meththylated in 68 of 67 cervical scrapings from cervical cancer patients. It notes that patients with a methylation-positive scraping may use the markers for referral to gynecologists.