Journal of Pathology and Translational Medicine

Articles in E-pub version are posted online ahead of regular printed publication.

Original Articles

Attitudes toward artificial intelligence in pathology: a survey-based study of pathologists in northern India: Manupriya Sharma, Kavita Kumari, Navpreet Navpreet, Sushma Bharti, Rajneesh Kumari; Received February 16, 2025 Accepted July 10, 2025 Published online October 2, 2025; DOI: https://doi.org/10.4132/jptm.2025.07.10 [Epub ahead of print]

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Abstract PDF Supplementary Material: Background
Artificial intelligence (AI) is transforming pathology by enhancing diagnostic accuracy, efficiency, and workflow standardization. Despite its growing presence, AI adoption remains limited, particularly in resource-constrained settings like India. This study assessed the knowledge, awareness, and perceptions of AI among pathologists in Northern India. Methods: A cross-sectional survey was conducted among 138 practicing pathologists in Northern India between April and June 2024. A structured online questionnaire was used to collect data on demographics, AI awareness, self-reported knowledge, sources of AI education, technological proficiency, and interest in AI-related training programs. Data analysis included descriptive statistics and chi-square tests, with p < .05 considered statistically significant. Results: AI awareness was high (88.4%), with significant sex differences (93.5% in females vs. 78.3% in males, p = .008). However, formal AI training was limited (6.5%), and only 16.7% had used AI as a diagnostic tool. Academic pathologists were more likely to engage with AI literature than their non-academic counterparts (p = .003). Interest in AI workshops was strong (92.8%). Access to whole slide imaging (WSI) correlated with higher AI knowledge (p = .008), as did self-reported technological proficiency (p = .001). Conclusions: Despite high AI awareness among pathologists, significant gaps remain in training, infrastructure, and practical application. Expanding access to digital pathology tools like WSI and improving digital literacy could facilitate AI adoption. Structured educational programs and greater investment in digital infrastructure are crucial for integrating AI into pathology practice.

Frozen section histopathology and preanalytical factors affecting nucleic acid integrity in biobanked fresh-frozen human cancer tissues: Soungeun Kim, Jaewon Kang, Boyeon Kim, Yoonjin Kwak, Hye Seung Lee; Received June 5, 2025 Accepted July 22, 2025 Published online September 12, 2025; DOI: https://doi.org/10.4132/jptm.2025.07.22 [Epub ahead of print]

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Abstract PDF Supplementary Material: Background
In this study, we evaluated the effects of storage duration and ischemic time on nucleic acid quality of fresh-frozen tissue (FFT) from colon adenocarcinoma (COAD), hepatocellular carcinoma (HCC), and renal cell carcinoma (RCC) collected at the Cancer Tissue Bank of Seoul National University Hospital. Methods: A total of 102 FFT samples were analyzed to compare DNA integrity number (DIN) and RNA integrity number (RIN) according to storage duration and ischemic time. Additionally, the effects of histopathologic features—such as tumor cell proportion, inflammatory cell infiltration, and stromal fibrosis—on nucleic acid quality were evaluated. Results: DIN and RIN remained stable overall even though the storage duration increased, with no statistically significant differences observed. In particular, there was almost no decrease in RNA quality in HCC and RCC samples, but in COAD samples, RIN tended to decrease slightly as the storage duration increased. No significant difference was confirmed between ischemic time and nucleic acid quality, but in COAD tissue, RNA quality variability tended to increase as the ischemic time increased. Furthermore, RIN increased as the tumor cell proportion increased, whereas inflammatory cell infiltration and extracellular mucin pool were identified as independent negative predictors of RIN. Conclusions: This study confirmed that nucleic acid integrity can be maintained even during long-term storage of FFT and demonstrated that histologic features are closely related to RNA quality. This study would contribute to the establishment of quality assessment and management standards for biobank FFT samples.

Characterization of undifferentiated carcinoma of the salivary gland: clinicopathological and immunohistochemical analyses in comparison with lymphoepithelial carcinoma: Sangjoon Choi, Gyuheon Choi, Hee Jin Lee, Joon Seon Song, Yoon Se Lee, Seung-Ho Choi, Kyung-Ja Cho; Received May 3, 2025 Accepted July 7, 2025 Published online September 8, 2025; DOI: https://doi.org/10.4132/jptm.2025.07.07 [Epub ahead of print]

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Abstract PDF: Background
This study aimed to reclassify a subset of poorly differentiated salivary gland carcinoma that do not conform to any entities of the current World Health Organization (WHO) classification into the category of undifferentiated carcinoma (UDC) because they lack specific histologic differentiation or immunophenotype. Methods: Cases of salivary gland carcinomas from Asan Medical Center (2002–2020) that did not fit any existing WHO classification criteria and were diagnosed as poorly differentiated carcinoma, high-grade carcinoma, or UDC, were retrospectively reviewed. Immunohistochemical (IHC) staining for p40, neuroendocrine markers, androgen receptor (AR), and gross cystic disease fluid protein 15 (GCDFP-15) and Epstein-Barr virus (EBV) in situ hybridization (ISH) were performed. Clinical data were collected from the electronic medical records. Results: Six salivary gland carcinomas did not align with any specific entities and lacked distinct differentiation. Two of six cases displayed lymphoepithelial carcinoma (LEC)-like morphology but were negative or showed negligible immunoreactivity for p40 and EBV ISH, distinguishing them from LEC of the salivary gland. Two cases showed strong AR positivity, suggesting a potential overlap with salivary duct carcinoma (SDC) but lacked classic SDC morphologies and GCDFP-15 expression. No cases expressed neuroendocrine markers. Conclusions: This study proposes reclassifying these poorly differentiated or high-grade salivary gland carcinomas as UDC based on their indeterminate differentiation and IHC profiles. This may lead to a clearer diagnostic category and enhance our understanding of these high-grade tumors.

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