An observational study in Stump, sponsored by Institut Bergonié. Recruiting at 1 site in France. Open to female participants. Per ClinicalTrials.gov, last updated 2026-01-15.
Sponsored by Institut Bergonié · Observational
Smooth muscle tumors of the uterus that do not fit the diagnostic criteria of benignity (such as leiomyomas) or malignancy (such as leiomyosarcomas) are called STUMP (smooth muscle tumor of uncertain malignant potential). A potential solution to this problem could be the application of predictive models using artificial intelligence (AI) to aid in the histopathological classification and prognosis of gynecological smooth muscle tumors. Deep learning using convolutional neural networks represents a specific class of machine learning, in which predictive models are trained by considering small groups of pixels in digital images and iteratively identifying salient features. In this study, we aim to develop deep learning models capable of accurately subclassifying and predicting the prognosis of gynecological smooth muscle tumors, based on histopathological features of hematoxylin and eosin (H\&E) slides. The aim is to develop a diagnostic and prognostic algorithm to help pathologists better classify and diagnose uterine smooth muscle tumors and predict their clinical course.
Institut Bergonié is the lead sponsor of 119 studies on the registry; 16 are open to participants now.
Counted across the registry records on this site, refreshed daily.
- Uterine smooth muscle tumors: leiomyomas, smooth muscle tumors of uncertain malignancy and leiomyossarcomas.
Go through the criteria one by one — yes, no or not sure — and take the list to your doctor or the study team. Kept in this browser only.
Exclusion Criteria:
Underlined terms in the criteria open these too. Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.
Malignancy means cancer. Criteria about another or earlier malignancy ask whether you have had a different cancer, usually within a set number of years.
Some are commonly allowed, such as treated skin cancers other than melanoma and early cancers removed completely — check the exceptions this study lists.
Cancer (malignancy)
Malignancy means cancer. Criteria about another or earlier malignancy ask whether you have had a different cancer, usually within a set number of years.
Some are commonly allowed, such as treated skin cancers other than melanoma and early cancers removed completely — check the exceptions this study lists.
Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.
Smooth muscle tumors of the uterus that do not fit the diagnostic criteria of benignity (such as leiomyomas) or malignancy (such as leiomyosarcomas) : smooth muscle tumor of uncertain malignant potential
Other: No intervention
Smooth muscle tumors of the uterus that do fit the diagnostic criteria of benignity (such as leiomyomas) or malignancy (such as leiomyosarcomas)
Other: No intervention
No intervention since this is an observational study
Develop deep learning models that can accurately subclassify gynaecologic smooth muscle tumours
This project aims to improve the diagnosis and prognosis of gynecologic smooth muscle tumors, including leiomyomas (LM), leiomyosarcomas (LMS), and smooth muscle tumors of uncertain malignant potential (STUMP). In detail, a workflow comprising 2 stages will be developed to automatically classify GSMT subtypes from whole-slide images and to predict progression-free survival for patients in the LMS and STUMP groups, thereby providing clinicians with a more effective tool to improve workflow quality.
Time frame: throughout the conduct of the study - an expected average of 6 months after data collection
Develop a prognostic tool for STUMP
Develop a model to predict progression-free survival for STUMP group based on the features extracted from Whole Slide Images.
Time frame: 6 months after receiving the data.
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