BACKGROUND: The Ki-67 proliferative index (PI) is part of the diagnosis of nodal B-cell lymphoma (nBCL), but its determination in cytological samples is not standardized. We aimed to establish an approach for the accurate determination of the Ki-67 PI in cytological slides to differentiate between indolent and aggressive nBCLs.
METHODS: Patients diagnosed with nBCL by fine-needle aspiration biopsy and subsequent excision biopsy were included. Cell suspensions were prepared from biopsy samples for CD3/Ki-67 double immunocytochemical staining and flow-cytometric verification of lymphoma B-cell counts. The Ki-67 PI was assessed by manual counting and eyeballing in cytology and eyeballing in histology. The cut-off values for the differentiation between aggressive and indolent lymphomas were determined for each method.
RESULTS: A strong correlation between manual and flow-cytometric counting of lymphoma B cells was confirmed (interclass correlation coefficient (IC coef.) = 0.78). The correlation of the Ki-67 PI determined in cytological and histological slides was also strong (IC coef. > 0.80). Histologically, 55 cases were classified as indolent and 31 as aggressive nBCLs. KI-67 PI cut-off values of 28.5%, 27.5%, and 35.5% were established for manual counting and eyeballing in cytology and eyeballing in histology, respectively, with high sensitivity and specificity.
CONCLUSIONS: The Ki-67 PI, assessed by manual counting and eyeballing in cytological samples, accurately differentiates between indolent and aggressive nBCLs.

Sysmex DI-60 enumerates and classifies leukocytes. Limited research has evaluated the performance of Sysmex DI-60 in abnormal samples, and most focused on leukopenic samples. We evaluate the efficacy of DI-60 in determining white blood cell (WBC) differentials in normal and abnormal samples in different WBC count. Peripheral blood smears (n = 166) were categorised into normal control and disease groups, and further divided into moderate and severe leucocytosis, mild leucocytosis, normal, mild leukopenia, and moderate and severe leukopenia groups based on WBC count. DI-60 preclassification and verification and manual counting results were assessed using Bland-Altman and Passing-Bablok regression analyses. The Kappa test compared the concordance in the abnormal cell detection between DI-60 and manual counting. DI-60 exhibited notable overall sensitivity and specificity for all cells, except basophils. The correlation between the DI-60 preclassification and manual counting was high for segmented neutrophils, band neutrophils, lymphocytes, and blasts, and improved for all cell classes after verification. The mean difference between DI-60 and manual counting for all cell classes was significantly high in moderate and severe leucocytosis (WBC > 30.0 × 109/L) and moderate and severe leukopenia (WBC < 1.5 × 109/L) groups. For blast cells, immature granulocytes, and atypical lymphocytes, the DI-60 verification results were similar to the manual counting results. Plasma cells showed poor agreement. In conclusion, DI-60 demonstrates consistent and reliable analysis of WBC differentials within the range of 1.5-30.0 × 109. Manual counting was indispensable in examining moderate and severe leucocytosis samples, moderate and severe leukopenia samples, and in enumerating of monocytes and plasma cells.

BACKGROUND: Although uncommon, medullary thyroid carcinoma (MTC) accounts for a significant proportion of thyroid cancer deaths. Recent studies have validated the two-tier International Medullary Thyroid Carcinoma Grading System (IMTCGS) to predict clinical outcomes. A 5% Ki67 proliferative index (Ki67PI) cut-off separates low-grade from high-grade MTC. In this study, we compared digital image analysis (DIA) to manual counting (MC) for determining the Ki67PI in a MTC cohort, and explored the challenges encountered.
METHODS: Available slides from 85 MTCs were reviewed by two pathologists. The Ki67PI was documented by immunohistochemistry for each case, scanned with the Aperio® slide scanner at 40× magnification, and quantified using the QuPath® DIA platform. The same hotspots were screenshot, printed in color, and blindly counted. For each case, over 500 MTC cells were counted. Each MTC was graded using IMTCGS criteria.
RESULTS: In our MTC cohort (n = 85), 84.7 and 15.3% were low- and high-grade with the IMTCGS. In the entire cohort, QuPath® DIA performed well (R2 = 0.9891) but appeared to undercall compared to MC. QuPath® performed better in high-grade cases (R2 = 0.99) compared to low-grade cases (R2 = 0.7071). Overall, Ki67PI determined with either MC or DIA did not affect IMTCGS grade. Encountered DIA challenges include optimizing cell detection, overlapping nuclei, and tissue artifacts. Encountered MC challenges include background staining, morphologic overlap with normal elements, and counting time.
CONCLUSIONS: Our study highlights the utility of DIA in quantifying Ki67PI for MTC and can serve as an adjunct for grading in conjunction with the other criteria of mitotic activity and necrosis.

The role of Ki-67 index in determining the prognosis and management of gastroenteropancreatic neuroendocrine tumors (GEP-NETs) has become more important yet presents a challenging assessment dilemma. Although the precise method of Ki-67 index evaluation has not been standardized, several methods have been proposed, and each has its pros and cons. Our study proposes an imaging semiautomated informatics framework [semiautomated counting (SAC)] using the popular biomedical imaging tool \"ImageJ\" to quantify Ki-67 index of the GEP-NETs using camera-captured images of tumor hotspots. It aims to assist pathologists in achieving an accurate and rapid interpretation of Ki-67 index and better reproducibility of the results with minimal human interaction and calibration. Twenty cases of resected GEP-NETs with Ki-67 staining that had been done for diagnostic purposes have been randomly selected from the pathology archive. All of these cases were reviewed in a multidisciplinary cancer center between 2012 and 2019. For each case, the Ki-67 immunostained slide was evaluated and five camera-captured images at 40 × magnification were taken. Prints of images were used by three pathologists to manually count the tumor cells. The digital versions of the images were used for the semiautomated cell counting using ImageJ. Statistical analysis of the Ki-67 index correlation between the proposed method and the MC revealed strong agreement on all the cases evaluates ( n = 20 ), with an intraclass correlation coefficient of 0.993, \"95% CI: 0.984 to 0.997.\" The results obtained from the SAC are promising and demonstrate the capability of this methodology for the development of reproducible and accurate semiautomated quantitative pathological assessments. ImageJ features are investigated carefully and accurately fine-tuned to obtain the optimal sequence of steps that will accurately calculate Ki-67 index. SAC is able to accurately grade all the cases evaluated perfectly mating histopathologists\' manual grading, providing reliable and efficient solution for Ki-67 index assessment.

Sperm concentration is an essential parameter in the diagnostic evaluation of men from infertile couples. It is usually determined by manual counting using a hemocytometer, and is therefore both laborious and subjective. We have earlier shown that a newly developed image cytometry (IC) method may be used to determine sperm concentration. Here we present a validation of the IC method by analysis of 4010 semen samples. There was high agreement between IC and manual counting at sperm concentrations above 3mill/ml and in samples with concentrations above 12mill/ml the two methods can be used interchangeable. However, we found substantial differences in samples below 3mill/ml. We also assessed the accuracy of the two methods by repeated measurements of 248 samples, which revealed that IC measurements seemed more accurate. Moreover, based on ten samples counted by several operators the IC method had a lower coefficient of variation than the manual method (5% vs 10%), indicating a better precision of the IC method. In conclusion, measurement of sperm concentration by IC can be used at concentrations above 3mill/ml and seems more accurate and precise than manual counting, making it an attractive option in the daily clinical practice.