MR fingerprinting (MRF) is a promising method for quantitative characterization of tissues. Often, voxel-wise measurements are made, assuming a single tissue-type per voxel. Alternatively, the... Show moreMR fingerprinting (MRF) is a promising method for quantitative characterization of tissues. Often, voxel-wise measurements are made, assuming a single tissue-type per voxel. Alternatively, the Sparsity Promoting Iterative Joint Non-negative least squares Multi-Component MRF method (SPIJN-MRF) facilitates tissue parameter estima-tion for identified components as well as partial volume segmentations. The aim of this paper was to evaluate the accuracy and repeatability of the SPIJN-MRF parameter estimations and partial volume segmentations. This was done (1) through numerical simulations based on the BrainWeb phantoms and (2) using in vivo acquired MRF data from 5 subjects that were scanned on the same week-day for 8 consecutive weeks. The partial volume segmen-tations of the SPIJN-MRF method were compared to those obtained by two conventional methods: SPM12 and FSL. SPIJN-MRF showed higher accuracy in simulations in comparison to FSL-and SPM12-based segmentations: Fuzzy Tanimoto Coefficients (FTC) comparing these segmentations and Brainweb references were higher than 0.95 for SPIJN-MRF in all the tissues and between 0.6 and 0.7 for SPM12 and FSL in white and gray matter and between 0.5 and 0.6 in CSF. For the in vivo MRF data, the estimated relaxation times were in line with literature and minimal variation was observed. Furthermore, the coefficient of variation (CoV) for estimated tissue volumes with SPIJN-MRF were 10.5% for the myelin water, 6.0% for the white matter, 5.6% for the gray matter, 4.6% for the CSF and 1.1% for the total brain volume. CoVs for CSF and total brain volume measured on the scanned data for SPIJN-MRF were in line with those obtained with SPM12 and FSL. The CoVs for white and gray mat-ter volumes were distinctively higher for SPIJN-MRF than those measured with SPM12 and FSL. In conclusion, the use of SPIJN-MRF provides accurate and precise tissue relaxation parameter estimations taking into account intrinsic partial volume effects. It facilitates obtaining tissue fraction maps of prevalent tissues including myelin water which can be relevant for evaluating diseases affecting the white matter. Show less
The recent FLAME trial has demonstrated improved local control of intermediate to high-risk prostate cancer after focal dose escalation of the visible tumor. To visualize the tumor, MRI... Show moreThe recent FLAME trial has demonstrated improved local control of intermediate to high-risk prostate cancer after focal dose escalation of the visible tumor. To visualize the tumor, MRI examinations were taken in which prostate tissue characteristics were visualized. Since this treatment strategy improves the clinical outcome of the patient, a technical analysis of the FLAME dataset is useful for the further optimization of focal dose escalation strategies.Delineation of the prostate tumor appeared to be performed differently in the participating radiotherapy departments. Considering the impact on the realized tumor dose, this analysis demonstrated the need for guidelines of tumor delineation on MRI. Due to the complex nature of the treatment plans, in addition a prediction model was developed, which identified patients for which a higher tumor dose could be planned.The application of MRI was also investigated for ‘dose painting by numbers’, in which MRI values are translated to prescription dose without interference of manual tumor delineations. Dose prescription based on MRI appeared robust to daily patient variations, a prerequisite for further development of ‘dose painting by numbers’. However, because of the absence of significant tumor changes during the treatment course, MRI was considered not suitable for early adaptive treatment. Show less
