A multiparametric alternative to short inversion-time inversion recovery for imaging inflammation: T2water and fat fraction measurement using chemical shift-encoded turbo spin-echo MRI.

PURPOSE: Short-inversion-time inversion-recovery MRI is used widely for imaging bone and soft-tissue inflammation in rheumatic inflammatory diseases, but there is no widely available quantitative equivalent of this sequence. This limits our ability to objectively assess inflammation and distinguish it from other processes. To address this, we investigate the use of the widely available Dixon turbo spin echo (TSE Dixon) sequence as a practical approach to simultaneous water-specific T2 (T2water ) and fat fraction (FF) measurement. METHODS: We use a series of TSE Dixon acquisitions with varying effective TEs (TEeff ) to quantify T2water and FF. The validity of this approach is assessed in a series of phantom and in vivo experiments, with reference values provided by Carr-Purcell-Meiboom-Gill acquisitions, MRS, and phantoms. The effect of inflammation on parameter values is evaluated in patients with spondyloarthritis. RESULTS: The T2water estimates obtained from TSE Dixon were accurate compared with the reference values from Carr-Purcell-Meiboom-Gill and spectroscopy in both fat-free environments and in the presence of fat. FF measurements with T2water correction from TSE Dixon were accurate from 0% to 60% FF and were not confounded by T2water variations. In vivo imaging produced good quality images that were artifact free, produced plausible T2 values, separating and quantifying the effect of inflammation on T2water and FF. CONCLUSION: The T2water and FF measurements based on TSE Dixon with effective TE increments are accurate over a range of T2 and FF values and could provide a widely available quantitative alternative to the short-inversion-time inversion-recovery sequence for imaging inflamed tissue.

Steps on the Path to Clinical Translation: A workshop by the British and Irish Chapter of the ISMRM.

The British and Irish Chapter of the International Society for Magnetic Resonance in Medicine (BIC-ISMRM) held a workshop entitled "Steps on the path to clinical translation" in Cardiff, UK, on 7th September 2022. The aim of the workshop was to promote discussion within the MR community about the problems and potential solutions for translating quantitative MR (qMR) imaging and spectroscopic biomarkers into clinical application and drug studies. Invited speakers presented the perspectives of radiologists, radiographers, clinical physicists, vendors, imaging Contract/Clinical Research Organizations (CROs), open science networks, metrologists, imaging networks, and those developing consensus methods. A round-table discussion was held in which workshop participants discussed a range of questions pertinent to clinical translation of qMR imaging and spectroscopic biomarkers. Each group summarized their findings via three main conclusions and three further questions. These questions were used as the basis of an online survey of the broader UK MR community.

Arterial Spin Labeling MRI in Carotid Stenosis: Arterial Transit Artifacts May Predict Symptoms.

BackgroundStenosis of the internal carotid artery has a higher risk for stroke. Many investigations have focused on structure and plaque composition as signs of plaque vulnerability, but few studies have analyzed hemodynamic changes in the brain as a risk factor.PurposeTo use 3-T MRI methods including contrast material-enhanced MR angiography, carotid plaque imaging, and arterial spin labeling (ASL) to identify imaging parameters that best help distinguish between asymptomatic and symptomatic participants with carotid stenosis.Materials and MethodsParticipants with carotid stenosis from two ongoing prospective studies who underwent ASL and carotid plaque imaging with use of 3-T MRI in the same setting from 2014 to 2018 were studied. Participants were assessed clinically for recent symptoms (transient ischemic attack or stroke) and divided equally into symptomatic and nonsymptomatic groups. Reviewers were blinded to the symptomatic status and MRI scans were analyzed for the degree of stenosis, plaque surface structure, presence of intraplaque hemorrhage (IPH), circle of Willis collaterals, and the presence and severity of arterial transit artifacts (ATAs) at ASL imaging. MRI findings were correlated with symptomatic status by using t tests and the Fisher exact test.ResultsA total of 44 participants (mean age, 71 years ± 10 [standard deviation]; 31 men) were evaluated. ATAs were seen only in participants with greater than 70% stenosis (16 of 28 patients; P < .001) and were associated with absence of anterior communicating artery (13 of 16 patients; P = .003). There was no association between history of symptoms and degree of stenosis (27 patients with ≥70% stenosis and 17 patients with <70%; P = .54), IPH (12 patients with IPH and 32 patients without IPH; P = .31), and plaque surface structure (17 patients with irregular or ulcerated plaque and 27 with smooth plaque; P = .54). Participants with ATAs (n = 16) were more likely to be symptomatic than were those without ATAs (n = 28) (P = .004). Symptomatic status also was associated with the severity of ATAs (P = .002).ConclusionArterial transit artifacts were the only factor associated with recent ischemic symptoms in participants with carotid stenosis. The degree of stenosis, plaque ulceration, and intraplaque hemorrhage were not associated with symptomatic status.© RSNA, 2020Online supplemental material is available for this article.See also the editorial by Zaharchuk in this issue.

A scan-specific quality control acquisition for clinical whole-body (WB) MRI protocols.

Objective.Image quality in whole-body MRI (WB-MRI) may be degraded by faulty radiofrequency (RF) coil elements or mispositioning of the coil arrays. Phantom-based quality control (QC) is used to identify broken RF coil elements but the frequency of these acquisitions is limited by scanner and staff availability. This work aimed to develop a scan-specific QC acquisition and processing pipeline to detect broken RF coil elements, which is sufficiently rapid to be added to the clinical WB-MRI protocol. The purpose of this is to improve the quality of WB-MRI by reducing the number of patient examinations conducted with suboptimal equipment.Approach.A rapid acquisition (14 s additional acquisition time per imaging station) was developed that identifies broken RF coil elements by acquiring images from each individual coil element and using the integral body coil. This acquisition was added to one centre's clinical WB-MRI protocol for one year (892 examinations) to evaluate the effect of this scan-specific QC. To demonstrate applicability in multi-centre imaging trials, the technique was also implemented on scanners from three manufacturers.Main results. Over the course of the study RF coil elements were flagged as potentially broken on five occasions, with the faults confirmed in four of those cases. The method had a precision of 80% and a recall of 100% for detecting faulty RF coil elements. The coil array positioning measurements were consistent across scanners and have been used to define the expected variation in signal.Significance. The technique demonstrated here can identify faulty RF coil elements and positioning errors and is a practical addition to the clinical WB-MRI protocol. This approach was fully implemented on systems from two manufacturers and partially implemented on a third. It has potential to reduce the number of clinical examinations conducted with suboptimal hardware and improve image quality across multi-centre studies.

Filtration-Histogram Based Magnetic Resonance Texture Analysis (MRTA) for the Distinction of Primary Central Nervous System Lymphoma and Glioblastoma.

Primary central nervous system lymphoma (PCNSL) has variable imaging appearances, which overlap with those of glioblastoma (GBM), thereby necessitating invasive tissue diagnosis. We aimed to investigate whether a rapid filtration histogram analysis of clinical MRI data supports the distinction of PCNSL from GBM. Ninety tumours (PCNSL n = 48, GBM n = 42) were analysed using pre-treatment MRI sequences (T1-weighted contrast-enhanced (T1CE), T2-weighted (T2), and apparent diffusion coefficient maps (ADC)). The segmentations were completed with proprietary texture analysis software (TexRAD version 3.3). Filtered (five filter sizes SSF = 2-6 mm) and unfiltered (SSF = 0) histogram parameters were compared using Mann-Whitney U non-parametric testing, with receiver operating characteristic (ROC) derived area under the curve (AUC) analysis for significant results. Across all (n = 90) tumours, the optimal algorithm performance was achieved using an unfiltered ADC mean and the mean of positive pixels (MPP), with a sensitivity of 83.8%, specificity of 8.9%, and AUC of 0.88. For subgroup analysis with >1/3 necrosis masses, ADC permitted the identification of PCNSL with a sensitivity of 96.9% and specificity of 100%. For T1CE-derived regions, the distinction was less accurate, with a sensitivity of 71.4%, specificity of 77.1%, and AUC of 0.779. A role may exist for cross-sectional texture analysis without complex machine learning models to differentiate PCNSL from GBM. ADC appears the most suitable sequence, especially for necrotic lesion distinction.