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Updated: Feb 14, 2026

Retzius-Sparing Robot-Assisted Radical Prostatectomy
Published on: May 19, 2022
Digital versus light microscopy assessment of surgical margin status after radical prostatectomy
Metka Volavšek1, Ana Blanca2, Rodolfo Montironi3
1Institute of Pathology, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia.
Abstract:
Positive surgical margin (PSM) extension reported as focal or non-focal/extensive is an important pathologic prognostic parameter after radical prostatectomy. Likewise, there is limited or no agreement on how to measure and what the best cut-off points to be used in practice are. We hypothesized that digital microscopy (DM) would potentially provide a more objective way to measure PSM and better define its clinical significance. To further our knowledge, we have evaluated PSM status in 107 laparoscopic radical prostatectomies using digital and conventional light microscopy (LM). DM evaluation detected three additional PSM cases, but no differences were seen (LM vs DM; p = 0.220). Mean linear measurement correlated to biochemical recurrence (BR) (LM, p = 0.002; DM, p = 0.001). ROC analysis identified a cut-off point to assess linear measurement by LM (3.5 mm) or DM (3.2 mm), but only digital measurement was significant for BR-free survival. Our study also evaluated a cut-off ≤ 3 mm that was associated to BR using LM (p = 0.023) or DM (p = 0.001). Finally, the number of paraffin blocks bearing PSM correlated with BR (p < 0.001) status with either LM or DM. In conclusion, DM produces similar data than LM but shows more accurate measurements. Reporting of PSM with score of ≤ 3 vs. > 3 mm linear extent using LM (3.2 mm if digital microscopy is applied) might represent an important prognostic feature after radical prostatectomy. Alternatively, reporting the number of blocks with PSM 1 vs. 2 or more might also provide important prognostic data in practice.
Insights
Digital microscopy (DM) offers more accurate measurements for positive surgical margins (PSM) after radical prostatectomy compared to light microscopy (LM). Both methods correlate with biochemical recurrence, but DM provides a more significant prognostic predictor for recurrence-free survival.
Area of Science:
- Uropathology
- Surgical Pathology
- Digital Pathology
Background:
- Positive surgical margin (PSM) is a critical prognostic factor after radical prostatectomy.
- Current methods for assessing PSM, including linear extent and focal/non-focal classification, lack standardized measurement and cut-off points.
- The clinical significance of PSM measurement requires further objective evaluation.
Purpose of the Study:
- To evaluate the utility of digital microscopy (DM) for objective measurement of PSM.
- To compare PSM assessment using DM versus conventional light microscopy (LM).
- To determine the prognostic significance of DM-based PSM measurements for biochemical recurrence (BR).
Main Methods:
- Analysis of PSM status in 107 laparoscopic radical prostatectomies using both DM and LM.
- Comparison of PSM detection rates and measurements between DM and LM.
- Correlation of linear PSM measurements and the number of positive blocks with BR using Receiver Operating Characteristic (ROC) analysis and survival analysis.
Main Results:
- DM identified three additional PSM cases, though overall differences between DM and LM were not statistically significant (p=0.220).
- Mean linear PSM measurements by both LM (p=0.002) and DM (p=0.001) correlated with BR.
- DM-derived cut-off (3.2 mm) was a significant predictor of BR-free survival, unlike LM (3.5 mm). A cut-off ≤3 mm was associated with BR for both LM (p=0.023) and DM (p=0.001). The number of blocks with PSM also correlated significantly with BR (p<0.001).
Conclusions:
- Digital microscopy provides more accurate PSM measurements than light microscopy.
- Reporting PSM linear extent (≤3 mm vs. >3 mm, with DM cut-off of 3.2 mm) or the number of positive blocks (1 vs. ≥2) can serve as important prognostic indicators after radical prostatectomy.
- DM enhances the prognostic value of PSM assessment in predicting biochemical recurrence.
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