US Radiomics in Advanced Cervical Cancer

This is a retrospective, multicenter observational study aimed at evaluating the role of ultrasound-based radiomics in patients with locally advanced cervical cancer (LACC). The study will analyze pre-treatment ultrasound images to identify radiomic features that may predict treatment response and disease recurrence.

A total of 220 patients treated with exclusive chemoradiotherapy or neoadjuvant chemoradiotherapy followed by radical surgery between 2011 and 2024 will be included. Using clinical and imaging data, machine learning models will be developed to distinguish between responders and non-responders, and to identify patients at higher risk of relapse.

The goal is to improve personalized care in LACC by integrating radiomic analysis into treatment planning and follow-up strategies.

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Key information

Conditions

Uterine Cervical Neoplasms Chemoradiotherapy Female Urogenital Diseases Female Urogenital Diseases and Pregnancy Complications Genital Diseases Genital Diseases, Female Genital Neoplasms, Female Locally Advanced Cervical Cancer Machine Learning Neoplasms Neoplasms by Site Radiomics Ultrasound Imaging Urogenital Diseases Urogenital Neoplasms Uterine Cervical Diseases Uterine Diseases Uterine Neoplasms

Age range

18 year and older

Sex eligibility

Female

Study type

Observational

Primary location

Fondazione Policlinico Universitario Agostino Gemelli IRCCS

Roma, 00168, Italy

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

Female patients aged ≥18 years

Histologically confirmed diagnosis of locally advanced cervical cancer (FIGO 2018 stage IB3-IVA, excluding IIA1)

Histologic subtypes: squamous cell carcinoma, adenocarcinoma, or adenosquamous carcinoma

Underwent transvaginal or transrectal ultrasound prior to treatment

At least one pre-treatment DICOM ultrasound image of the primary tumor available

Treated with either exclusive chemoradiotherapy or neoadjuvant chemoradiotherapy followed by radical surgery

Completed at least 12 months of follow-up after primary treatment

Signed informed consent (or equivalent declaration)

Exclusion criteria

Age <18 years

Only printed ultrasound images available

Ultrasound images with poor tumor visualization or with text/markers obscuring the tumor

Treatment and study plan

Radiomic Analysis of Ultrasound Images

Other

Quantitative analysis of pre-treatment ultrasound images of the primary cervical tumor to extract radiomic features. These features will be used to develop and validate machine learning models for predicting treatment response and disease relapse in patients with locally advanced cervical cancer (LACC).

Other names: Radiomics, Ultrasound-based Radiomics, Radiomic Feature Extraction

Primary outcomes

Performance of ultrasound-based radiomic models in predicting treatment response in patients with locally advanced cervical cancer.

Time frame: Up to 12 months after primary treatment.

Evaluation of the diagnostic accuracy (AUC, sensitivity, specificity, F1-score) of radiomic models based on pre-treatment ultrasound images in distinguishing responder vs. non-responder patients to primary treatment (exclusive chemoradiotherapy or neoadjuvant chemoradiotherapy followed by radical surgery). Models will be developed and validated using retrospective data.

Sponsors and collaborators

Lead sponsor

Fondazione Policlinico Universitario Agostino Gemelli IRCCS

Other

Registry information

Official study title

Role of Radiomics Applied to Ultrasound in Patients With Locally Advanced Cervical Cancer: a Retrospective Multicenter Study

Acronym: RU-LACC

Important dates

Study start: 2025
Primary completion: 2025
Study completion: 2025
First posted: May 22, 2025
Registry last updated: May 22, 2025

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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