Novel Applications for Sarcoma Assessment

NCT06073314 | Completed

• 1 other identifier: MP23/150492
• Study Type: observational
• Target: 186
• Locations: 1 country
• Sites: 1

Brief Summary

This research aims to improve the way of deciding whether a lump in soft tissue such as fat or muscle is a type of cancer called a soft tissue sarcoma, or if it is benign (non-cancerous). To do this the investigators will use routine clinical MRI scans, additional quantitative MRI scans and artificial intelligence. The aims of this research are: To develop AI algorithms that can accurately classify soft tissue masses as benign or malignant using routine and quantitative MR images. To classify malignant soft tissue masses into their pathological grade. Compare different AI models on external, unseen testing sets to determine which offers the best performance. Participants will be asked if they can spend up to a maximum of 10 extra minutes in an MRI scanner so that the extra images can be acquired. A small subset of participants will be invited back so the investigators can check the reproducibility of the images and the AI software.

Conditions

Sarcoma

Keywords

MRI; Diffusion weighted imaging; Radiomics; Deep Learning; Machine Learning; Quantitative MRI

Outcome Measures

Primary Outcomes (1)

• Diagnostic accuracy - ROC analysis of accuracy, sensitivity and specificity of AI algorithms for distinguishing between benign and malignant soft tissue lesions

  AI algorithms will be trained to distinguish between benign and malignant soft tissue lesions. To assess the accuracy of these algorithms, sensitivity and specificity of the algorithm will be calculated using the patients diagnosis from biopsy/surgical resection as the gold standard.

  3 years

Secondary Outcomes (1)

• Classification accuracy - ROC analysis of accuracy, sensitivity and specificity of AI algorithms for classifying malignant lesions into their pathological grade

  3 years

Study Arms (1)

Original cohort

This cohort will have a maximum of 10 minutes of quantitative MRI sequences added on to the end of the clinical standard MRI scan

Diagnostic Test: Quantitative MRI

Interventions

Quantitative MRI DIAGNOSTIC_TEST

Patients will be asked to remain in the scanner for an additional 10 minutes while we acquire additional quantitative MR images

Original cohort

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Patients who have been referred for MRI for a soft tissue mass that may be a soft tissue sarcoma, and have not yet undergone treatment for the lesion.

You may qualify if:

• Patients with a soft tissue mass that are discussed at the sarcoma multi-disciplinary meeting
• Undergoing MRI as part of their standard of care
• Participant is willing and able to give informed consent for participation in the trial.

You may not qualify if:

• Patient has already had the mass, or part of the mass, surgically removed prior to their MRI scan
• Contraindication to MRI (e.g. presence of contraindicated implants e.g. cardiac pacemakers, claustrophobia).

Sponsors & Collaborators

• The Leeds Teaching Hospitals NHS Trust: lead

Study Sites (1)

Leeds Teaching Hospitals

Leeds, United Kingdom

Location

MeSH Terms

Conditions

Sarcoma

Condition Hierarchy (Ancestors)

Neoplasms, Connective and Soft Tissue; Neoplasms by Histologic Type; Neoplasms

Study Design

• Study Type: observational
• Observational Model: OTHER
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: September 12, 2023
• First Posted: October 10, 2023
• Study Start: August 9, 2023
• Primary Completion: October 30, 2025
• Study Completion: March 31, 2026
• Last Updated: April 14, 2026

Record last verified: 2023-04

Data Sharing

• IPD Sharing: Will not share

Locations

GB (1)