Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
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.
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Responder Group | Patients with locally advanced cervical cancer who responded to primary treatment (either exclusive chemoradiotherapy or neoadjuvant chemoradiotherapy followed by radical surgery), as determined by clinical and/or histological assessment. |
| |
| Non-Responder Group | Patients with locally advanced cervical cancer who did not respond to primary treatment (either exclusive chemoradiotherapy or neoadjuvant chemoradiotherapy followed by radical surgery), based on residual disease findings or lack of clinical response. |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| 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). |
| Measure | Description | Time Frame |
|---|---|---|
| Performance of ultrasound-based radiomic models in predicting treatment response in patients with locally advanced cervical cancer. | 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. | Up to 12 months after primary treatment. |
Not provided
Not provided
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
Not provided
Not provided
Not provided
Patients with locally advanced cervical cancer (FIGO 2018 IB3-IVA, excluding IIA1), treated between 2011 and 2024, from multiple Italian centers. All participants underwent ultrasound before treatment and have available DICOM images for radiomic analysis.
Not provided
| Name | Affiliation | Role |
|---|---|---|
| Camilla Culcasi | Fondazione Policlinico Universitario Agostino Gemelli | Study Chair |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Fondazione Policlinico Universitario Agostino Gemelli IRCCS | Roma | 00168 | Italy |
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
| ID | Term |
|---|---|
| D002583 | Uterine Cervical Neoplasms |
| ID | Term |
|---|---|
| D014594 | Uterine Neoplasms |
| D005833 | Genital Neoplasms, Female |
| D014565 | Urogenital Neoplasms |
| D009371 | Neoplasms by Site |
Not provided
Not provided
Not provided
Not provided
Not provided
|
|
| D009369 |
| Neoplasms |
| D002577 | Uterine Cervical Diseases |
| D014591 | Uterine Diseases |
| D005831 | Genital Diseases, Female |
| D052776 | Female Urogenital Diseases |
| D005261 | Female Urogenital Diseases and Pregnancy Complications |
| D000091642 | Urogenital Diseases |
| D000091662 | Genital Diseases |