ChatGPT as a teaching tool: Preparing pathology residents for board examination with AI-generated digestive system pathology tests.

OBJECTIVES: To evaluate the effectiveness of ChatGPT 4 in generating multiple-choice questions (MCQs) with explanations for pathology board examinations, specifically for digestive system pathology. METHODS: The customized ChatGPT 4 model was developed for MCQ and explanation generation. Expert pathologists evaluated content accuracy and relevance. These MCQs were then administered to pathology residents, followed by an analysis focusing on question difficulty, accuracy, item discrimination, and internal consistency. RESULTS: The customized ChatGPT 4 generated 80 MCQs covering various gastrointestinal and hepatobiliary topics. While the MCQs demonstrated moderate to high agreement in evaluation parameters such as content accuracy, clinical relevance, and overall quality, there were issues in cognitive level and distractor quality. The explanations were generally acceptable. Involving 9 residents with a median experience of 1 year, the average score was 57.4 (71.8%). Pairwise comparisons revealed a significant difference in performance between each year group (P < .01). The test analysis showed moderate difficulty, effective item discrimination (index = 0.15), and good internal consistency (Cronbach's α = 0.74). CONCLUSIONS: ChatGPT 4 demonstrated significant potential as a supplementary educational tool in medical education, especially in generating MCQs with explanations similar to those seen in board examinations. While artificial intelligence-generated content was of high quality, it necessitated refinement and expert review.

Histopathologic evaluation of gastric intestinal metaplasia in non-neoplastic biopsy specimens: Accuracy and interobserver reliability among general pathologists and pathology residents.

OBJECTIVES: This study aimed to evaluate the accuracy and interobserver reliability of diagnosing and subtyping gastric intestinal metaplasia (IM) among general pathologists and pathology residents at a university hospital in Thailand, focusing on the challenges in the histopathologic evaluation of gastric IM for less experienced practitioners. METHODS: The study analyzed 44 non-neoplastic gastric biopsies, using a consensus diagnosis of gastrointestinal pathologists as the reference standard. Participants included 6 general pathologists and 9 pathology residents who assessed gastric IM and categorized its subtype (complete, incomplete, or mixed) on digital slides. After initial evaluations and receiving feedback, participants reviewed specific images of gastric IM, as agreed by experts. Following a one-month washout period, a reevaluation of the slides was conducted. RESULTS: Diagnostic accuracy, interobserver reliability, and time taken for diagnosis improved following training, with general pathologists showing higher accuracies than residents (median accuracy of gastric IM detection: 100 % vs. 97.7 %). Increased years of experience were associated with more IM detection accuracy (p-value<0.05). However, the overall median accuracy for diagnosing incomplete IM remained lower than for complete IM (86.4 % vs. 97.7 %). After training, diagnostic errors occurred in 6 out of 44 specimens (13.6 %), reported by over 40 % of participants. Errors involved omitting 5 slides with incomplete IM and 1 with complete IM, all showing a subtle presence of IM. CONCLUSIONS: The study highlights the diagnostic challenges in identifying incomplete gastric IM, showing notable discrepancies in accuracy and interobserver agreement. It underscores the need for better diagnostic protocols and training to enhance detection and management outcomes.

Validation of whole slide imaging for frozen section diagnosis of lymph node metastasis: A retrospective study from a tertiary care hospital in Thailand.

BACKGROUND: The use of whole slide imaging (WSI) for frozen section (FS) diagnosis is helpful, particularly in the context of pathologist shortages. However, there is minimal data on such usage in resource-limited settings. This study aims to validate the use of WSI for FS diagnosis of lymph node metastasis using a low-cost virtual microscope scanner with consumer-grade laptops at a tertiary care hospital in Thailand. METHODS: FS slides were retrieved for which the clinical query was to evaluate lymph node metastasis. They were digitized by a virtual microscope scanner (MoticEasyScan, Hong Kong) using up to 40× optical magnification. Three observers with different pathology experience levels diagnosed each slide, reviewing glass slides (GS) followed by digital slides (DS) after two weeks of a wash out period. WSI and GS diagnoses were compared. The time used for scanning and diagnosis of each slide was recorded. RESULTS: 295 FS slides were retrieved and digitized. The first-time successful scanning rate was 93.6 %. The mean scanning time was 2 min per slide. Both intraobserver agreement and interobserver agreement of WSI and GS diagnoses were high (Cohen's K; kappa value >0.84). The time used for DS diagnosis decreased as the observer's experience with WSI increased. CONCLUSIONS: Despite varying pathological experiences, observers using WSI provided accurate FS diagnoses of lymph node metastasis. The time required for DS diagnoses decreased with additional observer's experience with WSI. Therefore, a WSI system containing low-cost scanners and consumer-grade laptops could be used for FS services in hospital laboratories lacking pathologists.