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Abstract #2124

Visualizing uterine fibroid perfusion after MR-HIFU ablations using T2-corrected IVIM and deep learning-based fitting – an explorative study.

Derk J. Slotman1,2, Lambertus W. Bartels2, Ingrid M. Nijholt1, Edwin Heijman3,4, Martijn Froeling2, and Martijn F. Boomsma1
1Radiology, Isala Zwolle, Zwolle, Netherlands, 2Image Sciences Institute, Imaging & Oncology Division, University Medical Center Utrecht, Utrecht, Netherlands, 3Faculty of Medicine and University Hospital of Cologne, Institute of Diagnostic and Interventional Radiology, University of Cologne, Cologne, Germany, 4High Tech Campus, Philips Research Eindhoven, Eindhoven, Netherlands

Synopsis

Blood volume fraction maps derived from diffusion weighted imaging using intravoxel incoherent motion (IVIM) modeling may be an alternative to contrast-enhanced imaging for visualization of local uterine fibroid perfusion, during magnetic resonance-guided high intensity focused ultrasound (MR-HIFU) ablation procedures. In this study, blood volume fraction maps calculated with a T2-corrected IVIM model were compared to T2-uncorrected parameter maps using two fitting techniques. Based on general inspection, T2-corrected parameter maps from deep learning-based fitting were visually the most appealing. A preliminary evaluation showed a linear association between NPVs delineated on blood volume fraction maps and gadolinium contrast-enhanced T1w scans.

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