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.
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AI-rewrites the medical criteria so a patient or caregiver can understand them. Always confirm with the trial site.
Diagnostic accuracy - ROC analysis of accuracy, sensitivity and specificity of AI algorithms for distinguishing between benign and malignant soft tissue lesions
Timeframe: 3 years