Abstract #2179

Evaluating IVIM and ADC Parameters to Differentiate Benign and Malignant Soft-Tissue Lesions

Matthew Marzetti^1,2, Philip Robinson³, Leanne Maguire³, Peter Duce³, Stefan Klein⁴, Martijn Starmans^4,5, Andrew Scarsbrook^3,6, and David Buckley²

¹Department of Medical Physics and Engineering, Leeds Teaching Hospitals NHS Trust, Leeds, United Kingdom, ²Biomedical Imaging, University of Leeds, Leeds, United Kingdom, ³Department of Radiology, Leeds Teaching Hospitals NHS Trust, Leeds, United Kingdom, ⁴Department of Radiology and Nuclear Medicine, Erasmus MC Cancer Institute, Rotterdam, Netherlands, ⁵Department of Surgical Oncology, Erasmus MC Cancer Institute, Rotterdam, Netherlands, ⁶Leeds Institute of Medical Research, University of Leeds, Leeds, United Kingdom

Synopsis

Keywords: IVIM, Diagnosis/Prediction, Soft-tissue cancer and sarcoma

Motivation: Patients with soft-tissue lesions often undergo biopsies to confirm diagnosis, as distinguishing benign from malignant ones with MRI is challenging. Intravoxel incoherent motion (IVIM) may increase the discriminatory power of MRI, which could reduce the number of biopsies leading to improved patient experience and efficiency for healthcare providers.

Goal(s): Differentiate malignant from benign soft-tissue lesions using diffusion weighted imaging (DWI)-derived parameters including IVIM.

Approach: Research-specific DWI scans were analysed using mono-exponential and IVIM fitting techniques. Parameters measured in lesions were compared between benign and malignant cases.

Results: Some IVIM-derived parameters demonstrated discriminatory potential, supporting further exploration and validation in a larger study.

Impact: This work uses quantitative MRI to differentiate benign from malignant soft-tissue lesions, aiming to reduce the need for soft-tissue biopsies. This could reduce the number of invasive procedures patients undergo and provide diagnoses faster, reducing patient anxiety, pain and discomfort.

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