Cervico-vaginal (CV) localization of extra-mammary Paget’s disease (EMPD) of the vulva is extremely rare. In order to investigate the incidence risk and the pathognomonic clinical and pathological features of this condition, a retrospective analysis was conducted including 94 women treated for vulvar EMPD at the European Institute of Oncology, Milan, Italy, from October 1997 to May 2020. Overall nine patients developed CV involvement from EMPD, with a cumulative incidence of 2.5% (95% CI: 0.5–8.0%) at 5 years, 6.5% (95% CI: 1.9–15.1%) at 10 years and 14.0% (95% CI: 4.8–27.8%) at 15 years, respectively. All cases except one were firstly detected by abnormal glandular cytology. None reported vaginal bleeding or other suspicious symptoms. The colposcopic findings were heterogeneous and could sometimes be misdiagnosed. Cervical and/or vaginal biopsies were always performed for histopathological diagnosis by identification of Paget cells in the epithelium or stroma. Most patients developed invasive EMPD (5/9) of the cervix and/or vagina and underwent hysterectomy with partial or total colpectomy. CV involvement from EMPD should not be underestimated in women with a long-standing history of vulvar Paget’s disease. Liquid-based cytology with immunocytochemistry represents a valuable tool for early diagnosis and should be routinely performed during the required lifelong follow-up.

Introduction: Depth of invasion (DOI) in vulvar squamous cell carcinoma (vSCC) predicts risk of nodal metastasis, with measurement >1 mm dictating the need for lymph node diagnostic procedures. In 2021, the International Federation of Gynecology and Obstetrics (FIGO) changed its advice on how pathologists measure DOI. Some organizations revised guidelines to this “New” method; others continued to endorse the FIGO 2009 “Old” method. This study compares interobserver variation of vSCC DOI using Old and New FIGO measurement strategies. Methods: A single representative image was chosen from 50 consecutive vSCC excisions with reported DOI of 0.1–3 mm. Ten pathologists provided 2 electronic measurements for each, using Old and New methods. Statistical evaluation included analyses of variance, Student t-test, and the kappa statistic. Results: The Old method yielded a larger mean DOI than the New [1.3 vs 0.9 mm; p < .001]. The Old method had a lower proportion of measurement disagreements spanning 1 mm (53%, κ = 0.65% vs 68%, κ = 0.6). Agreement by all pathologists of DOI being either ≤1 mm or >1 mm occurred in 29/50 cases (58%) using the Old and 26 (52%) using the New method. When at least 2 pathologists measured DOI >1 mm, interobserver variation was lower using the Old method in 30 (83%) of 36 cases [mean difference = −0.1 mm, t(280) = −2.78, p = .008]. Conclusions: The FIGO 2021 DOI measurement method has higher interobserver variation than FIGO 2009, with this difference arising from tumors with DOI >1 mm. This finding, combined with inadequate international consensus and scant clinical outcome data, should trigger reconsideration of 2021 FIGO staging guidelines.

Designing an optimal digital pathology workspace is essential to ensure diagnostic accuracy and safeguard the long-term well-being of pathologists. While digital pathology improves reproducibility, facilitates multidisciplinary collaboration, and supports data-driven precision medicine, its clinical effectiveness depends not only on computational performance but also on the physical and ergonomic environment in which pathologists operate. Inadequate workstation design may impair visual perception, increase cognitive and musculoskeletal strain, and potentially affect diagnostic consistency. Moreover, the progressive integration of artificial intelligence (AI) into routine diagnostics introduces additional requirements related to display performance, visualization interfaces, and human–machine interaction. Despite the rapid global adoption of digital pathology systems, standardized recommendations addressing ergonomic, environmental, and technological aspects of the digital workspace remain limited. In this work, we propose a clinically oriented framework for the design of digital pathology workspaces suitable for AI-assisted diagnostics. Key elements include the selection and calibration of medical-grade displays, ergonomic furniture and input devices, optimized ambient lighting conditions, and institutional quality assurance procedures. Emerging developments, such as intelligent ergonomic monitoring, advanced visualization interfaces, and adaptive AI-assisted workflows, may further support safe, sustainable, and high-performance digital diagnostic environments.

The impact of multiple infections on the risk of cervical lesions is a subject of ongoing debate. This study aims to explore whether the richness of HPV genotype infections and the biodiversity of squamous and glandular cervical dysplasias could influence the progression of precancerous lesions. We conducted a cross-sectional analysis involving 469 women who attended the Colposcopy Unit at the European Institute of Oncology in Milan, Italy, from December 2006 to December 2014. HPV type richness was measured as the number of different genotypes per patient. We calculated the associations between richness and age, as well as histologic grade, along with Simpson’s biodiversity index for cervical dysplasias. We observed significant inverse relationships between the richness of high-risk (HR) genotypes and both age (p = 0.007) and histologic grade (p < 0.001). Furthermore, as the histologic grade increased, the mean biodiversity index of cervical dysplasias decreased, with exceptions noted in cases of normal histology and adenocarcinoma in situ. Different histologic grades formed five clusters with distinct mean ages and mean biodiversity indices. These findings suggest that HPV genotype richness and the biodiversity of cervical dysplasias may play a crucial role in predicting the risk of high-grade cervical lesions, enabling personalized management of precancers.