Comparison of Ki67 Proliferation Index in Gastrointestinal Non-Hodgkin Large B-Cell Lymphomas: The Conventional Method of Evaluation or AI Evaluation?

Author:

Cristian Miruna1234ORCID,Așchie Mariana235,Deacu Mariana13,Boșoteanu Mădălina13,Bălțătescu Gabriela Izabela23ORCID,Stoica Andreea Georgiana126,Nicolau Anca Antonela23ORCID,Poinăreanu Ionuț17,Orășanu Cristian Ionuț1234ORCID

Affiliation:

1. Faculty of Medicine, “Ovidius” University of Constanta, 900470 Constanta, Romania

2. Center for Research and Development of the Morphological and Genetic Studies of Malignant Pathology-CEDMOG, “Ovidius” University of Constanta, 900591 Constanta, Romania

3. Department of Clinical Pathology, “Sf. Apostol Andrei” Emergency County Hospital, 900591 Constanta, Romania

4. Institute of Doctoral Studies, School of Medicine, ”Ovidius” University, 900573 Constanta, Romania

5. Academy of Medical Sciences, 030171 Bucharest, Romania

6. Department of Hematology, ”Sf. Apostol Andrei” Emergency County Hospital, 900591 Constanta, Romania

7. Department of Pathology, Săcele Municipal Hospital, 505600 Brașov, Romania

Abstract

The most common NHL subtype in SEEU is DLBCL (39%), and it manifests with a variety of cellular morphologies and a high proliferation index. Also, the GI tract is the most common site of extranodal NHLs, and most NHLs involving the GI tract are of B-cell lineage, of which diffuse large B-cell lymphoma is the most common subtype, irrespective of location. The last few years have seen digital pathology as a vital technology that has a positive impact on diagnostics, but studies on the use of DP for lymphoma identification, however, are still restricted to only determining whether a tumor is present or absent. Using the example of cases of malignant NHL, we aim to investigate the diagnostic utility of DP using QuPath software in evaluating the proliferation index and the prognostic significance and to show that improved visualization and analysis contribute to the convergence of these complementary diagnostic modalities for lymphomas. The average proliferation index (Ki67) was 58.33% with values between 10% and 85%. After the stratification of the cases, an increased proliferation index was observed in the majority of cases (53.33%), and this aspect was associated with the advanced age of the patients (p = 0.045). Visual assessment provides lower Ki67 values than automated digital image analysis. However, the agreement coefficient between the conventional method and the AI method indicates an excellent level of reliability (ICC1–0.970, ICC2–0.990). The multivariate analysis revealed that in the cases where the proliferation index Ki67 is high (˃70%), the IPI score represents an important risk factor predicting mortality (HR = 10.597, p = 0.033).

Publisher

MDPI AG

Subject

Clinical Biochemistry

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