Journal Article Ahead of print
PubMed: 42142520 DOI: 10.1016/j.ejrad.2026.112926
Structured MRI reporting in patients with deep pelvic endometriosis: performance and clinical impact of the deep pelvic endometriosis index (dPEI).
Eur J Radiol 202:112926
Authors: Valentina Miceli, Roberta Valerieva Ninkova, Marco Gennarini, Sandrine Riccardi, Federica Curti, Chiara Amoroso, Riccardo Manghi, Maria Grazia Porpora, Isabelle Thomassin-Naggara, Lucia Manganaro
Affiliations
- Department of Radiological, Oncological and Pathological Sciences, Sapienza University of Rome, Policlinico Umberto I, Viale del Policlinico 155, 00161 Rome, Italy.
- Department of Experimental Medicine, Sapienza - University of Rome, Rome, Italy - Viale Regina Elena, 324, 00161 Rome, Italy.
- Department of Experimental Medicine, Sapienza - University of Rome, Rome, Italy - Viale Regina Elena, 324, 00161 Rome, Italy.
- Department of Radiological, Oncological and Pathological Sciences, Sapienza University of Rome, Policlinico Umberto I, Viale del Policlinico 155, 00161 Rome, Italy.
- Department of Radiological, Oncological and Pathological Sciences, Sapienza University of Rome, Policlinico Umberto I, Viale del Policlinico 155, 00161 Rome, Italy.
- Department of Radiological, Oncological and Pathological Sciences, Sapienza University of Rome, Policlinico Umberto I, Viale del Policlinico 155, 00161 Rome, Italy.
- LUISS Guido Carli - Department economic and finance, Italy.
- Department of Maternal and Child Health and Urological Sciences, Umberto I Polyclinic Hospital, Sapienza University, Rome, Italy.
- Department of Radiology, Assistance Publique Hôpitaux de Paris-Hôpital Tenon, Paris, France; Service Imageries Radiologiques et Interventionnelles Spécialisées Sorbonne Université, Paris, France.
- Department of Radiological, Oncological and Pathological Sciences, Sapienza University of Rome, Policlinico Umberto I, Viale del Policlinico 155, 00161 Rome, Italy.
Abstract
PURPOSE
To evaluate the feasibility, interobserver reproducibility, reporting efficiency, and perceived clinical impact of the Deep Pelvic Endometriosis Index (dPEI) when implemented as part of structured MRI reporting in routine clinical practice.
MATERIALS AND METHODS
This retrospective single-center study included 100 consecutive women with surgically confirmed deep pelvic endometriosis who underwent preoperative 3-Tesla pelvic MRI. Three radiologists with different levels of experience (2, 4, and 20 years) independently reviewed all examinations using a structured MRI report based on the dPEI. Interobserver agreement for the global score was assessed using the intraclass correlation coefficient (ICC), while compartment-specific agreement was evaluated using Cohen's and Fleiss' κ statistics. Reporting time was recorded for each reader. Perceived clinical utility and practical limitations were assessed through a structured questionnaire administered to 10 clinicians and 10 surgeons involved in multidisciplinary endometriosis care.
RESULTS
The dPEI was applicable across all cases and readers. Interobserver agreement for the global score was low-to-moderate (ICC = 0.44) and was influenced by reader experience, with higher concordance between senior and intermediate radiologists than between pairs including the junior reader. Agreement was higher in central compartments and lower in lateral and extrapelvic compartments. Reporting time decreased with increasing reader experience and demonstrated a clear learning effect, remaining below 30 min for all readers. Clinicians rated the dPEI as useful for disease stratification and multidisciplinary communication, whereas surgeons reported limited usefulness for advanced surgical planning, mainly due to the lack of quantitative descriptors.
CONCLUSION
The dPEI is a feasible and intuitive MRI-based staging system whose performance is influenced by reader experience, while remaining easy to apply and associated with a rapid learning curve. These characteristics support its use as a complementary structured reporting tool in routine clinical practice and suggest a potential role as an educational and training instrument in deep pelvic endometriosis imaging.
MeSH
Endometriosis, Radiologists, Radiology, Learning, Surgeons