Novel Applications for Sarcoma Assessment (NASA)

April 9, 2026 updated by: The Leeds Teaching Hospitals NHS Trust

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.

Study Overview

Status

Completed

Conditions

Intervention / Treatment

Detailed Description

This research's aim is 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 using artificial intelligence (AI).

Soft tissue sarcomas are a type of cancer that can appear anywhere in the body where there is soft tissue such as muscle or fat. While sarcomas are rare, benign lumps in soft tissue are common and it is currently very difficult to tell the difference between the two using imaging. This means many patients with benign masses are referred for painful biopsies and waiting lists for biopsies are long due to the large diagnostic workload.

This research aims to develop an AI algorithm that can differentiate between benign and malignant soft tissue masses. While an algorithm can be developed using existing routine data the researchers would like to investigate if adding quantitative MR images could make it more accurate.

Patients who are already having a scan for sarcoma will be asked if they consent to extra MR images being acquired. These images will be used to provide extra information to the AI. The extra images will add a maximum of 10 minutes to the patients' standard MRI scan, meaning patients will not need to make an extra trip or undergo any extra procedures. Study participants will not need to receive MR contrast as part of this research. The extra images will not be used to make a diagnosis during this research. A small subset of patients will be asked if they would be willing to come for a second scan so that the researchers can see how reliable the measurements are, but this will be entirely optional.

Study Type

Observational

Enrollment (Actual)

186

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

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.

Description

Inclusion Criteria:

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

Exclusion Criteria:

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

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

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

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Diagnostic accuracy - ROC analysis of accuracy, sensitivity and specificity of AI algorithms for distinguishing between benign and malignant soft tissue lesions
Time Frame: 3 years
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 Outcome Measures

Outcome Measure
Measure Description
Time Frame
Classification accuracy - ROC analysis of accuracy, sensitivity and specificity of AI algorithms for classifying malignant lesions into their pathological grade
Time Frame: 3 years
AI algorithms will be trained to distinguish between grade 1,2 and 3 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

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

The Leeds Teaching Hospitals NHS Trust

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

August 9, 2023

Primary Completion (Actual)

October 30, 2025

Study Completion (Actual)

March 31, 2026

Study Registration Dates

First Submitted

September 12, 2023

First Submitted That Met QC Criteria

October 2, 2023

First Posted (Actual)

October 10, 2023

Study Record Updates

Last Update Posted (Actual)

April 14, 2026

Last Update Submitted That Met QC Criteria

April 9, 2026

Last Verified

April 1, 2023

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • MP23/150492

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

IPD Plan Description

All data will be de-identified prior to being used in this research

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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