Application and exploration of digital pathology technology in standardized residency training

To evaluate the effectiveness of digital pathology technology in the standardized residency training (SRT) in clinical pathology, compare the performance differences between digital slide-based and traditional microscope-based assessments, examine the association between assessment modality and residents’ slide-reading scores, explore residents’ perceptions and acceptance of digital pathology, and explore the potential presence of the “novice tool dependence” effect among junior residents. A retrospective analysis was performed on assessment data from 64 resident physicians at the clinical pathology training base of Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, between 2021 and 2024. Assessment scores from traditional glass slides (2021–2022) were compared with those from digital slides (2023–2024). Additionally, a questionnaire survey was conducted among 59 resident physicians from six SRT bases in Zhejiang Province to evaluate their usage, functional experience, and acceptance of digital slides. Open-ended responses were independently reviewed by two investigators. Similar responses were categorized into descriptive themes, and the frequency of each theme was documented. Since the open-ended responses were used to supplement and support the quantitative findings, no formal qualitative approach was applied. No significant difference was observed in assessment scores between the digital slide group ( n = 33, 73.80 ± 11.34) and the traditional glass slide group ( n = 31, 74.65 ± 13.45). Hierarchical multiple linear regression showed no statistically significant independent association between assessment modality and assessment scores after adjustment for residency year and educational background (β=-0.015, P = 0.878). In contrast, residency year (β = 0.607, P < 0.001) and educational background (β = 0.218, P = 0.030) were independently associated with assessment scores. Questionnaire responses indicated that the overall use rate of digital slides among resident physicians was 66.10%, with teaching and assessment as the most common applications (86.44%). Exploratory factor analysis showed that junior resident physicians scored significantly higher in the “diagnostic operation efficiency” dimension of digital slides (F = 4.614, P = 0.014). We tentatively describe this pattern as “novice tool dependence”. The Kruskal–Wallis H test showed relatively lower acceptance of digital slides for routine reading among senior residents compared to juniors (H = 6.636, P = 0.036). Open-ended responses suggested that residents generally perceived benefits of digital pathology in overcoming time and space limitations, enhancing learning motivation, and standardizing teaching resources across multiple hospital campuses. Nonetheless, participants reported concerns regarding system stability, image resolution, and network dependence. Based on this single-center before-and-after comparison, digital slide-based assessment was not associated with a statistically significant difference in archived overall slide-reading scores. These findings provide preliminary support for the feasibility of digital slide-based assessment in SRT, but should be interpreted cautiously because of temporal confounding, limited sample size, and regional restrictions. The observed “novice tool dependence” among junior residents could serve as a preliminary reference for designing targeted SRT training curricula. Within the scope of the present sample, digital slides may serve as an auxiliary educational option for residency teaching and assessment; given limitations, including a limited sample size and regional restrictions, multi-center, cross-regional research is still needed to verify their applicability for wide-scale promotion.

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Publication Details

Journal
BMC Medical Education
Published
2026-06-13
DOI
https://doi.org/10.1186/s12909-026-09666-x
Primary Topic
AI in cancer detection
Type
article
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article

Application and exploration of digital pathology technology in standardized residency training

Wangwang Liu, Shi Wei, Z N Jiang, Qiuxia Gu et al.
BMC Medical Education
AI in cancer detection
article

Application and exploration of digital pathology technology in standardized residency training

Wangwang Liu, Shi Wei, Z N Jiang, Qiuxia Gu, Dan Qiao, Yi Gan
article en

Abstract

To evaluate the effectiveness of digital pathology technology in the standardized residency training (SRT) in clinical pathology, compare the performance differences between digital slide-based and traditional microscope-based assessments, examine the association between assessment modality and residents’ slide-reading scores, explore residents’ perceptions and acceptance of digital pathology, and explore the potential presence of the “novice tool dependence” effect among junior residents. A retrospective analysis was performed on assessment data from 64 resident physicians at the clinical pathology training base of Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, between 2021 and 2024. Assessment scores from traditional glass slides (2021–2022) were compared with those from digital slides (2023–2024). Additionally, a questionnaire survey was conducted among 59 resident physicians from six SRT bases in Zhejiang Province to evaluate their usage, functional experience, and acceptance of digital slides. Open-ended responses were independently reviewed by two investigators. Similar responses were categorized into descriptive themes, and the frequency of each theme was documented. Since the open-ended responses were used to supplement and support the quantitative findings, no formal qualitative approach was applied. No significant difference was observed in assessment scores between the digital slide group ( n = 33, 73.80 ± 11.34) and the traditional glass slide group ( n = 31, 74.65 ± 13.45). Hierarchical multiple linear regression showed no statistically significant independent association between assessment modality and assessment scores after adjustment for residency year and educational background (β=-0.015, P = 0.878). In contrast, residency year (β = 0.607, P < 0.001) and educational background (β = 0.218, P = 0.030) were independently associated with assessment scores. Questionnaire responses indicated that the overall use rate of digital slides among resident physicians was 66.10%, with teaching and assessment as the most common applications (86.44%). Exploratory factor analysis showed that junior resident physicians scored significantly higher in the “diagnostic operation efficiency” dimension of digital slides (F = 4.614, P = 0.014). We tentatively describe this pattern as “novice tool dependence”. The Kruskal–Wallis H test showed relatively lower acceptance of digital slides for routine reading among senior residents compared to juniors (H = 6.636, P = 0.036). Open-ended responses suggested that residents generally perceived benefits of digital pathology in overcoming time and space limitations, enhancing learning motivation, and standardizing teaching resources across multiple hospital campuses. Nonetheless, participants reported concerns regarding system stability, image resolution, and network dependence. Based on this single-center before-and-after comparison, digital slide-based assessment was not associated with a statistically significant difference in archived overall slide-reading scores. These findings provide preliminary support for the feasibility of digital slide-based assessment in SRT, but should be interpreted cautiously because of temporal confounding, limited sample size, and regional restrictions. The observed “novice tool dependence” among junior residents could serve as a preliminary reference for designing targeted SRT training curricula. Within the scope of the present sample, digital slides may serve as an auxiliary educational option for residency teaching and assessment; given limitations, including a limited sample size and regional restrictions, multi-center, cross-regional research is still needed to verify their applicability for wide-scale promotion.

BMC Medical Education
Sir Run Run Shaw Hospital (CN), Zhejiang University (CN)
Quality Education
Openalex Percentile: Top 4%
AI in cancer detection
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