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Purpose: To determine the prevalence and determinants of radiologic imaging requests that are of inadequate quality according to the Reason for exam Imaging Reporting and Data System (RI-RADS)., Methods: This study included a random sample of 673 radiologic examinations performed at a tertiary care center. The quality of each imaging request was graded according to RI-RADS. Ordinal regression analysis was performed to determine the association of RI-RADS grade with patient age, gender, and hospital status, indication for imaging, requesting specialty, imaging modality, body region, time of examination, and relationship with previous imaging within the past one year., Results: RI-RADS grades A (adequate request), B (barely adequate request), C (considerably limited request), and D (deficient request) were assigned to 159 (23.6 %), 166 (24.7 %), 214 (31.8 %), and 134 (19.9 %) of cases, respectively. Indication for imaging, requesting specialty, and body region were independently significantly associated with RI-RADS grades. Specifically, routine preoperative imaging (odds ratio [OR]: 3.422, P = 0.030) and transplantation imaging requests (OR: 8.710, P = 0.000) had a higher risk of poorer RI-RADS grades, whereas infection/inflammation as indication for imaging (OR: 0.411, P = 0.002), pediatrics as requesting specialty (OR: 0.400, P = 0.007), and head (OR: 0.384, P = 0.017), spine (OR: 0.346, P = 0.016), and upper extremity (OR: 0.208, P = 0.000) as body regions had a lower risk of poorer RI-RADS grades., Conclusion: The quality of radiologic imaging requests is inadequate in >75 % of cases, and is affected by several factors. The data from this study can be used as a baseline and benchmark for further investigation and improvement., (Copyright © 2021 The Author(s). Published by Elsevier B.V. All rights reserved.)

Quantification of amyloid load with positron emission tomography can be useful to assess Alzheimer's Disease in-vivo. However, quantification can be affected by the image processing methodology applied. This study's goal was to address how amyloid quantification is influenced by different semi-automatic image processing pipelines. Images were analysed in their Native Space and Standard Space; non-rigid spatial transformation methods based on maximum a posteriori approaches and tissue probability maps (TPM) for regularisation were explored. Furthermore, grey matter tissue segmentations were defined before and after spatial normalisation, and also using a population-based template. Five quantification metrics were analysed: two intensity-based, two volumetric-based, and one multi-parametric feature. Intensity-related metrics were not substantially affected by spatial normalisation and did not significantly depend on the grey matter segmentation method, with an impact similar to that expected from test-retest studies (≤10%). Yet, volumetric and multi-parametric features were sensitive to the image processing methodology, with an overall variability up to 45%. Therefore, the analysis should be carried out in Native Space avoiding non-rigid spatial transformations. For analyses in Standard Space, spatial normalisation regularised by TPM is preferred. Volumetric-based measurements should be done in Native Space, while intensity-based metrics are more robust against differences in image processing pipelines., Competing Interests: The authors have declared that no competing interests exist.

Objectives: Currently, multiple sclerosis is treated with anti-inflammatory therapies, but these treatments lack efficacy in progressive disease. New treatment strategies aim to repair myelin damage and efficacy evaluation of such new therapies would benefit from validated myelin imaging techniques. Several MRI methods for quantification of myelin density are available now. This systematic review aims to analyse the performance of these MRI methods., Methods: Studies comparing myelin quantification by MRI with histology, the current gold standard, or assessing reproducibility were retrieved from PubMed/MEDLINE and Embase (until December 2019). Included studies assessed both myelin histology and MRI quantitatively. Correlation or variance measurements were extracted from the studies. Non-parametric tests were used to analyse differences in study methodologies., Results: The search yielded 1348 unique articles. Twenty-two animal studies and 13 human studies correlated myelin MRI with histology. Eighteen clinical studies analysed the reproducibility. Overall bias risk was low or unclear. All MRI methods performed comparably, with a mean correlation between MRI and histology of R 2 =0.54 (SD=0.30) for animal studies, and R 2 =0.54 (SD=0.18) for human studies. Reproducibility for the MRI methods was good (ICC=0.75-0.93, R 2 =0.90-0.98, COV=1.3-27%), except for MTR (ICC=0.05-0.51)., Conclusions: Overall, MRI-based myelin imaging methods show a fairly good correlation with histology and a good reproducibility. However, the amount of validation data is too limited and the variability in performance between studies is too large to select the optimal MRI method for myelin quantification yet., Competing Interests: Declaration of Competing Interest The authors declare no competing interests., (Copyright © 2020 The Author(s). Published by Elsevier Inc. All rights reserved.)

Purpose: The aim of this work is to investigate the impact of tissue classification in magnetic resonance imaging (MRI)-guided positron emission tomography (PET) attenuation correction (AC) for whole-body (WB) Patlak net uptake rate constant (K i ) imaging in PET/MRI studies., Procedures: WB dynamic PET/CT data were acquired for 14 patients. The CT images were utilized to generate attenuation maps (μ-map CTAC ) of continuous attenuation coefficient values (A coeff ). The μ-map CTAC were then segmented into four tissue classes (μ-map 4-classes ), namely background (air), lung, fat, and soft tissue, where a predefined A coeff was assigned to each class. To assess the impact of bone for AC, the bones in the μ-map CTAC were then assigned a predefined soft tissue A coeff (0.1 cm -1 ) to produce an AC μ-map without bones (μ-map no-bones ). Thereafter, both WB static SUV and dynamic PET images were reconstructed using μ-map CTAC , μ-map 4-classes , and μ-map no-bones (PET CTAC, PET 4-classes , and PET no-bones ), respectively. WB indirect and direct parametric K i images were generated using Patlak graphical analysis. Malignant lesions were delineated on PET images with an automatic segmentation method that uses an active contour model (MASAC). Then, the quantitative metrics of the metabolically active tumor volume (MATV), target-to-background (TBR), contrast-to-noise ratio (CNR), peak region-of-interest (ROI peak ), maximum region-of-interest (ROI max ), mean region-of-interest (ROI mean ), and metabolic volume product (MVP) were analyzed. The Wilcoxon test was conducted to assess the difference between PET 4-classes and PET no-bones against PET CTAC for all images. The same test was also adopted to compare the differences between SUV, indirect K i , and direct K i images for each evaluated AC method., Results: No significant differences in MATV, TBR, and CNR were observed between PET 4-classes and PET CTAC for either SUV or K i images. PET 4-classes significantly overestimated ROI peak , ROI max , ROI mean , as well as MVP scores compared with PET CTAC in both SUV and K i images. SUV images exhibited the highest median relative errors for PET 4-classes with respect to PET CTAC (RE 4-classes ): 6.91 %, 6.55 %, 5.90 %, and 6.56 % for ROI peak , ROI max , ROI mean , and MVP, respectively. On the contrary, K i images showed slightly reduced RE 4-classes (indirect 5.52 %, 5.95 %, 4.43 %, and 5.70 %, direct 6.61 %, 6.33 %, 5.53 %, and 4.96 %) for ROI peak , ROI max , ROI mean , and MVP, respectively. A higher TBR was observed on indirect and direct K i images relative to SUV, while direct K i images demonstrated the highest CNR., Conclusions: Four-tissue class AC may impact SUV and K i parameter estimation but only to a limited extent, thereby suggesting that WB Patlak K i imaging for dynamic WB PET/MRI studies is feasible. Patlak K i imaging can enhance TBR, thereby facilitating lesion segmentation and quantification. However, patient-specific A coeff for each tissue class should be used when possible to address the high inter-patient variability of A coeff distributions.

Microvascular changes are increasingly recognised not only as primary drivers of radiotherapy treatment response in brain tumours, but also as an important contributor to short- and long-term (cognitive) side effects arising from irradiation of otherwise healthy brain tissue. As overall survival of patients with brain tumours is increasing, monitoring long-term sequels of radiotherapy-induced microvascular changes in the context of their potential predictive power for outcome, such as cognitive disability, has become increasingly relevant. Ideally, radiotherapy-induced significant microvascular changes in otherwise healthy brain tissue should be identified as early as possible to facilitate adaptive radiotherapy and to proactively start treatment to minimise the influence on these side-effects on the final outcome. Although MRI is already known to be able to detect significant long-term radiotherapy induced microvascular effects, more recently advanced MR imaging biomarkers reflecting microvascular integrity and function have been reported and might provide a more accurate and earlier detection of microvascular changes. However, the use and validation of both established and new techniques in the context of monitoring early and late radiotherapy-induced microvascular changes in both target-tissue and healthy tissue currently are minimal at best. This review aims to summarise the performance and limitations of existing methods and future opportunities for detection and quantification of radiotherapy-induced microvascular changes, as well as the relation of these findings with key clinical parameters., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Medical magnetic resonance imaging (MRI) produces high-resolution anatomical images of the human body, but has limited capacity to provide useful molecular information. The light-responsive, liposomal MRI contrast agent described herein could be used to provide an intrinsic theranostic aspect to MRI and enable tracking the distribution and cargo release of drug delivery systems upon light-triggered activation.

Purpose: To determine the frequency of locally recurrent Ewing sarcoma on surveillance MRI and the outcome of these patients., Materials and Methods: This retrospective single-center study included all patients with newly diagnosed Ewing sarcoma who underwent surveillance MRI of the primary tumor location after primary treatment between 1997 and 2016., Results: Thirty-two patients underwent a total of 176 local surveillance MRI scans, yielding an average of 5.5 ± 4.4 MRI scans per patient. Follow-up time of surveillance MRI after completion of primary treatment ranged between 1 and 111 months. Surveillance MRI detected five (15.6%) locally recurrent Ewing sarcomas, at 2, 4, 6, 6, and 7 months after completion of primary treatment, of whom three also had simultaneous recurrent (metastatic) disease elsewhere. Two patients had recurrent metastatic disease without any signs of locally recurrent disease on surveillance MRI. All five patients with locally recurrent disease on surveillance MRI died, at 2, 4, 5, 8, and 9 months after local recurrence detection. Patients with locally recurrent disease had a significantly worse overall survival than patients without locally recurrent disease (log-rank test, P < 0.0001)., Conclusions: A limited number of patients have locally recurrent Ewing sarcoma on surveillance MRI. These patients often have simultaneous recurrent (metastatic) disease elsewhere, and their outcome is poor. Moreover, some patients present without locally recurrent disease on MRI but disease recurrence elsewhere. Therefore, surveillance MRI currently seems to have little value and should be reconsidered, also given the costs and the repeated exposure of surviving patients to gadolinium-based contrast agents.

Background: Although cardiac MR and T 1 mapping are increasingly used to diagnose diffuse fibrosis based cardiac diseases, studies reporting T 1 values in healthy and diseased myocardium, particular in nonischemic cardiomyopathies (NICM) and populations with increased cardiovascular risk, seem contradictory., Purpose: To determine the range of native myocardial T 1 value ranges in patients with NICM and populations with increased cardiovascular risk., Study Type: Systemic review and meta-analysis., Population: Patients with NICM, including hypertrophic cardiomyopathy (HCM) and dilated cardiomyopathy (DCM), and patients with myocarditis (MC), iron overload, amyloidosis, Fabry disease, and populations with hypertension (HT), diabetes mellitus (DM), and obesity. FIELD STRENGTH/SEQUENCE: (Shortened) modified Look-Locker inversion-recovery MR sequence at 1.5 or 3T., Assessment: PubMed and Embase were searched following the PRISMA guidelines., Statistical Tests: The summary of standard mean difference (SMD) between the diseased and a healthy control populations was generated using a random-effects model in combination with meta-regression analysis., Results: The SMD for HCM, DCM, and MC patients were significantly increased (1.41, 1.48, and 1.96, respectively, P < 0.01) compared with healthy controls. The SMD for HT patients with and without left-ventricle hypertrophy (LVH) together was significantly increased (0.19, P = 0.04), while for HT patients without LVH the SMD was zero (0.03, P = 0.52). The number of studies on amyloidosis, iron overload, Fabry disease, and HT patients with LVH did not meet the requirement to perform a meta-analysis. However, most studies reported a significantly increased T 1 for amyloidosis and HT patients with LVH and a significant decreased T 1 for iron overload and Fabry disease patients., Data Conclusions: Native T 1 mapping by using an (Sh)MOLLI sequence can potentially assess myocardial changes in HCM, DCM, MC, iron overload, amyloidosis, and Fabry disease compared to controls. In addition, it can help to diagnose left-ventricular remodeling in HT patients., Level of Evidence: 2 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2018;47:891-912., (© 2017 The Authors Journal of Magnetic Resonance Imaging published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine.)