Stroke is a leading cause of death and disability worldwide. The reasons for increased stroke burden in developing countries are inadequately controlled risk factors resulting from poor public awareness and inadequate infrastructure. Computed tomography and MRI are common neuroimaging modalities used to assess stroke with diffusion-weighted MRI, in particular, being the recommended choice for acute stroke imaging. However, access to these imaging modalities is primarily restricted to major cities and high-income groups. In the case of stroke, the time-window of treatment to limit the damage is of a few hours and needs a point-of-care diagnosis. A low-cost MR system typically achieved at the ultra-low- and very-low-field would meet the need for a geographically accessible and portable solution. We review studies focused on accessible stroke imaging and recent developments in MR methodologies, including hardware, to image at low fields. We hypothesize that in the absence of a formal, rapid stroke triaging system, the value of timely on-site delivery of the scanner to the stroke patient can be significant. To this end, we discuss multiple recent hardware and methods developments in the low-field regime. Our review suggests a compelling need to explore further the trade-offs between high signal, contrast, and accessibility at low fields in low-income communities. LEVEL OF EVIDENCE: 4 TECHNICAL EFFICACY STAGE: 6.

Low-Field MRI of Stroke: Challenges and Opportunities.

Since uncontrolled growth of malignant masses introduces uneven shape irregularities and spiculations in the boundary, shape representing shift invariant features are essential to resolve the problem of discrimination. However, ambiguous nature of shape, size, margin, orientation of masses produces imprecise feature values. In this view, a new concept of extrema based feature characterization scheme is proposed for capturing radiating nature of mass morphology. Computation of extrema patterns needs only few algorithmic steps. Beside this, present study employs an automated enhancement procedure to improve the classification accuracy. Experimental results show that extrema characterization reduces the feature redundancy to produce high efficiency in reasonably low time.

Shift invariant extrema based feature analysis scheme to discriminate the spiculation nature of mammograms.

To assess the usefulness of combined diffusion kurtosis imaging (DKI) and dynamic contrast-enhanced MRI (DCE-MRI) in the differentiation of parotid gland tumors. Seventy patients with 80 parotid gland tumors who underwent DKI and DCE-MRI were retrospectively enrolled and divided into four groups: pleomorphic adenomas (PAs), Warthin tumors (WTs), other benign tumors (OBTs), and malignant tumors (MTs). DCE-MRI and DKI quantitative parameters were measured. The Kruskal–Wallis H test and post hoc test with Bonferroni correction and ROC curve were used for statistical analysis. WTs demonstrated the highest Kep value (median 1.89, interquartile range [1.46–2.31] min−1) but lowest Ve value (0.20, [0.15–0.25]) compared with PAs (Kep, 0.34 [0.21–0.55] min−1; Ve, 0.36 [0.24–0.43]), OBTs (Kep, 1.22 [0.27–1.67] min−1; Ve, 0.28 [0.25–0.41]), and MTs (Kep, 0.71 [0.50–1.23] min−1; Ve, 0.35 [0.26–0.45]) (all p < .05). MTs had the lower D value (1.10, [0.88–1.29] × 10−3 mm2/s) compared with PAs (1.81, [1.60–2.20] × 10−3 mm2/s) and OBTs (1.57, [1.32–1.89] × 10−3 mm2/s) (both p < .05). PAs had the lower Ktrans value (0.12, [0.07–0.18] min−1) compared with OBTs (0.28, [0.11–0.50] min−1) (p < .05). The cutoff values of combined Kep and Ve, D, and Ktrans to distinguish WTs, MTs, and PAs sequentially were 1.06 min−1, 0.28, 1.46 × 10−3 mm2/s, and 0.21 min−1, respectively (accuracy, 89% [71/80], 91% [73/80], 78% [62/80], respectively). The combined use of DKI and DCE-MRI may help differentiate parotid gland tumors. • The combined use of DKI and DCE-MRI could facilitate the understanding of the pathophysiological characteristics of parotid gland tumors.
 • A stepwise diagnostic diagram based on the combined use of DCE-MRI parameters and the diffusion coefficient is helpful for accurate preoperative diagnosis in parotid gland tumors and may further facilitate the clinical management of patients.

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Diffusion kurtosis imaging and dynamic contrast-enhanced MRI for the differentiation of parotid gland tumors.

Magnetic Resonance Imaging (MRI) is a medical imaging modality that provides excellent soft tissue contrast with high diagnostic value (Brown, Semelka, & Dale, 2015; McRobbie, Moore, Graves, & Prince, 2017; Rao, Venkatesan, & Geethanath, 2015; Webb & Kagadis, 2003). System simulators are important because of the inherent complexity of MRI. However, most existing MRI simulators are proprietary to manufacturing companies. In addition, typical existing open-source simulators do not support both system-wide simulation and pulse sequence deployment on multiple vendors (Supplementary table S1, Ravi et al. (2018)). An open-source, integrated, and vendor-neutral webtool will help MRI researchers around the world develop and share new methodology. Vendor-neutrality allows imaging methods to be applied on scanners from multiple companies and streamlines multi-site repeatability studies. This software should provide functionalities for rapidly prototyping MR methods, services for sharing computational resources, and educational features for under-served areas to develop their own MRI expertise (Obungoloch, 2019).

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Virtual Scanner: MRI on a Browser

Neuroimaging of certain pathologies requires both multi-parametric qualitative and quantitative imaging. The role of the quantitative MRI (qMRI) is well accepted but suffers from long acquisition times leading to patient discomfort, especially in geriatric and pediatric patients. Previous studies show that synthetic MRI can be used in order to reduce the scan time and provide qMRI as well as multi-contrast data. However, this approach suffers from artifacts such as partial volume and flow. In order to increase the scan efficiency (the number of contrasts and quantitative maps acquired per unit time), we designed, simulated, and demonstrated rapid, simultaneous, multi-contrast qualitative (T1 weighted, T1 fluid attenuated inversion recovery (FLAIR), T2 weighted, water, and fat), and quantitative imaging (T1 and T2 maps) through the approach of tailored MR fingerprinting (TMRF) to cover whole-brain in approximately four minutes. We performed TMRF on in vivo four healthy human brains and in vitro ISMRM/NIST phantom and compared with vendor supplied gold standard (GS) and MRF sequences. All scans were performed on a 3T GE Premier system and images were reconstructed offline using MATLAB. The reconstructed qualitative images were then subjected to custom DL denoising and gradient anisotropic diffusion denoising. The quantitative tissue parametric maps were reconstructed using a dense neural network to gain computational speed compared to dictionary matching. The grey matter and white matter tissues in qualitative and quantitative data for the in vivo datasets were segmented semi-automatically. The SNR and mean contrasts were plotted and compared across all three methods. The GS images show better SNR in all four subjects compared to MRF and TMRF (GS>TMRF>MRF). The T1 and T2 values of MRF are relatively overestimated as compared to GS and TMRF. The scan efficiency for TMRF is 1.72 min-1 which is higher compared to GS ( 0.32 min-1) and MRF (0.90 min-1).

Tailored Magnetic Resonance Fingerprinting

Accelerated dynamic contrast enhanced MRI based on region of interest compressed sensing.

Magnetic resonance imaging (MRI) is a well-established imaging modality capable of providing high resolution structural and functional images of tissues of in the human body. MRI is also relatively safer than some of the other imaging modalities such as X-ray CT and PET with respect to ionization. In this article, we discuss the basic working principles and role of MRI in the diagnosis of diseases of head and neck, breast, cardiac, abdomen and musculoskeletal system to provide an overview of the diagnostic and/or prognostic potential and capability of MRI in the clinic.

Rashmi Rao

Papers

Accelerated dynamic contrast enhanced MRI based on region of interest compressed sensing.

Role of MRI in medical diagnostics