NCT05161949: ATENA

Artificial inTelligence in eNdometriosis-related ovArian Cancer and Precision Surgery in eNdometriosis-related ovArian Cancer

Status unknown Last updated 17 December 2021

What this trial tests

trial in Patients With Suspected Ovarian Carcinoma in 240 participants. Status unknown.

Timeline

29 November 2021

Primary endpoint
30 July 2023

28 November 2023

Quick facts

Lead sponsor	IRCCS Azienda Ospedaliero-Universitaria di Bologna
Status	Status unknown
Study type	OBSERVATIONAL
Enrollment	240
Start date	29 November 2021
Primary completion	30 July 2023
Estimated completion	28 November 2023
Sites	1 location across Italy

Conditions studied

• Patients With Suspected Ovarian Carcinoma — all drugs for Patients With Suspected Ovarian Carcinoma →
• Non Oncological Patients or With Endometriosis — all drugs for Non Oncological Patients or With Endometriosis →

Sponsor

IRCCS Azienda Ospedaliero-Universitaria di Bologna — full company profile →

Who can join

Adults 18 to 90, female only, with Patients With Suspected Ovarian Carcinoma or Non Oncological Patients or With Endometriosis. Patients with the condition only — healthy volunteers not accepted.

Sponsor's own description

Endometriosis (EMS) is a chronic, invaliding, inflammatory gynaecological condition affecting 10-15% of women in reproductive age. EMS is characterized by lesions of endometrial-like tissue outside the uterus involving pelvic peritoneum and ovaries. In addition, distant foci are sometimes observed. Unfortunately, the aetiology of the EMS is little known. Although non-malignant, EMS shares similar features with cancer, such as development of local and distant foci, resistance to apoptosis and invasion of other tissues with subsequent damage to the target organs. Moreover, patients with EMS (particularly ovarian EMS) showed high risk (about 3 to 10 times) of developing epithelial ovarian cancer (EOC). Epidemiologic, morphological and molecular studies reported endometrioma as the precursor of EOC, including clear cell (CCC) endometrioid carcinoma which are both called "EMS-related ovarian carcinoma (EROC)". To date, it remains unclear why benign EMS causes malignant transformation. This multi-step process, unlike high-grade serous carcinomas, offers the possibility to identify the carcinoma precursors enabling an early diagnosis and in the early stages of the disease.

EOC is the most lethal female gynecological cancer with 25% 5-year overall survival (OS), due to the lack of effective screening tools, and rapidly spreads over the entire peritoneal surface (carcinosis) thus involving all abdominal organs. Diagnosis and clinical staging of EOC is currently performed by qualitative image evaluation although the sensitivity/specificity is suboptimal. To date, diagnostic, staging, and prognostic factors are strongly correlated with subjective assessment training and clinician experience.

Genomic analysis based on Next Generation Sequencing (NGS) has revealed the presence of cancer-associated gene mutations in EMS. Moreover, the chronic inflammatory process of EMS involves many factors, such as hormones, cytokines, glycoproteins, and angiogenic factors, which are expected to become early EMS biomarkers.

A promising new branch of cancer research is the use of artificial intelligence (AI) to recognize new image patterns and texture and/or detecting novel biomarkers to improve the early identification of EROC patients. AI has never been used for EROC and we want to investigate whether these methods/techniques can support and even improve current diagnostics and risk assessment. AI will be used to construct a new 3D risk assessment model based on images and volume of interest

Publications & conference data

4 peer-reviewed publications reference this trial (live from Europe PMC):

1. Analysis of computer-aided diagnostics in the preoperative diagnosis of ovarian cancer: a systematic review.
   Koch AH, Jeelof LS, Muntinga CLP, Gootzen TA, et al · · 2023 · cited 13× · PMID 36790570 · DOI 10.1186/s13244-022-01345-x
2. Two possible entities of endometriosis-associated ovarian cancer: correlated or incidental?
   Mezzapesa F, Dondi G, Coada CA, De Leo A, et al · · 2025 · cited 11× · PMID 39955191 · DOI 10.1016/j.ijgc.2025.101634
3. MicroRNA profiling reveals potential biomarkers for the early transformation of endometriosis towards endometriosis-correlated ovarian cancer.
   Ravegnini G, Coadă CA, Mantovani G, De Leo A, et al · · 2025 · cited 2× · PMID 40147159 · DOI 10.1016/j.tranon.2025.102367
4. Application of ultrasound in combination with other methods in gynecological disease: artificial intelligence, surgery, and drugs.
   Shi S, Dai C, Liu D, Liu X. · · 2025 · PMID 40958876 · DOI 10.3389/fonc.2025.1567024