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In this work, we introduce spatial and chemical saturation options for artefact reduction in magnetic resonance fingerprinting (MRF) and assess their impact on T 1 and T 2 mapping accuracy. An existing radial MRF pulse sequence was modified to enable spatial and chemical saturation. Phantom experiments were performed to demonstrate flow artefact reduction and evaluate the accuracy of the T 1 and T 2 maps. As an in vivo demonstration, MRF of the prostate was performed on an asymptomatic volunteer using saturation modules to reduce flow-related artefacts. T 1 , T 2 and B 1 + maps obtained with and without saturation modules were compared. Application of spatial saturation in prostate MRF reduced streaking artefacts from the femoral vessels. When saturation is enabled T 1 accuracy is preserved, and T 2 accuracy remains acceptable up to approximately 100 ms. Chemical and spatial saturation can be incorporated into MRF sequences with limited impact on T 1 accuracy. Further sequence optimisation may be needed to accurately estimate long T 2 components. Spatial saturation modules have potential in prostate MRF applications as a means to reduce flow-related artefacts., (© 2025 The Author(s). NMR in Biomedicine published by John Wiley & Sons Ltd.)

High acceleration factors in radial magnetic resonance fingerprinting (MRF) of the prostate lead to strong streak-like artefacts from flow in the femoral blood vessels, possibly concealing important anatomical information. Region-optimised virtual (ROVir) coils is a beamforming-based framework to create virtual coils that maximise signal in a region of interest while minimising signal in a region of interference. In this study, the potential of removing femoral flow streak artefacts in prostate MRF using ROVir coils is demonstrated in silico and in vivo. The ROVir framework was applied to radial MRF k-space data in an automated pipeline designed to maximise prostate signal while minimising signal from the femoral vessels. The method was tested in 15 asymptomatic volunteers at 3 T. The presence of streaks was visually assessed and measurements of whole prostate T 1 , T 2 and signal-to-noise ratio (SNR) with and without streak correction were examined. In addition, a purpose-built simulation framework in which blood flow through the femoral vessels can be turned on and off was used to quantitatively evaluate ROVir's ability to suppress streaks in radial prostate MRF. In vivo it was shown that removing selected ROVir coils visibly reduces streak-like artefacts from the femoral blood flow, without increasing the reconstruction time. On average, 80% of the prostate SNR was retained. A similar reduction of streaks was also observed in silico, while the quantitative accuracy of T 1 and T 2 mapping was retained. In conclusion, ROVir coils efficiently suppress streaking artefacts from blood flow in radial MRF of the prostate, thereby improving the visual clarity of the images, without significant sacrifices to acquisition time, reconstruction time and accuracy of quantitative values. This is expected to help enable T 1 and T 2 mapping of prostate cancer in clinically viable times, aiding differentiation between prostate cancer from noncancer and healthy prostate tissue., (© 2024 The Authors. NMR in Biomedicine published by John Wiley & Sons Ltd.)

Objective: Signal intensity normalization is necessary to reduce heterogeneity in T2-weighted (T2W) magnetic resonance imaging (MRI) for quantitative analysis of multicenter data. AutoRef is an automated dual-reference tissue normalization method that normalizes transversal prostate T2W MRI by creating a pseudo-T2 map. The aim of this study was to evaluate the accuracy of pseudo-T2s and multicenter standardization performance for AutoRef with three pairs of reference tissues: fat/muscle (AutoRef F ), femoral head/muscle (AutoRef FH ) and pelvic bone/muscle (AutoRef PB )., Materials and Methods: T2s measured by multi-echo spin echo (MESE) were compared to AutoRef pseudo-T2s in the whole prostate (WP) and zones (PZ and TZ/CZ/AFS) for seven asymptomatic volunteers with a paired Wilcoxon signed-rank test. AutoRef normalization was assessed on T2W images from a multicenter evaluation set of 1186 prostate cancer patients. Performance was measured by inter-patient histogram intersections of voxel intensities in the WP before and after normalization in a selected subset of 80 cases., Results: AutoRef FH pseudo-T2s best approached MESE T2s in the volunteer study, with no significant difference shown (WP: p = 0.30, TZ/CZ/AFS: p = 0.22, PZ: p = 0.69). All three AutoRef versions increased inter-patient histogram intersections in the multicenter dataset, with median histogram intersections of 0.505 (original data), 0.738 (AutoRef FH ), 0.739 (AutoRef F ) and 0.726 (AutoRef PB )., Discussion: All AutoRef versions reduced variation in the multicenter data. AutoRef FH pseudo-T2s were closest to experimentally measured T2s., (© 2022. The Author(s).)