Diffusion-weighted Imaging of the Chest: A Primer for Radiologists.

Diffusion-weighted imaging (DWI) is a fundamental sequence not only in neuroimaging but also in oncologic imaging and has emerging applications for MRI evaluation of the chest. DWI can be used in clinical practice to enhance lesion conspicuity, tissue characterization, and treatment response. While the spatial resolution of DWI is in the order of millimeters, changes in diffusion can be measured on the micrometer scale. As such, DWI sequences can provide important functional information to MRI evaluation of the chest but require careful optimization of acquisition parameters, notably selection of b values, application of parallel imaging, fat saturation, and motion correction techniques. Along with assessment of morphologic and other functional features, evaluation of DWI signal attenuation and apparent diffusion coefficient maps can aid in tissue characterization. DWI is a noninvasive noncontrast acquisition with an inherent quantitative nature and excellent reproducibility. The outstanding contrast-to-noise ratio provided by DWI can be used to improve detection of pulmonary, mediastinal, and pleural lesions, to identify the benign nature of complex cysts, to characterize the solid portions of cystic lesions, and to classify chest lesions as benign or malignant. DWI has several advantages over fluorine 18 (18F)-fluorodeoxyglucose PET/CT in the assessment, TNM staging, and treatment monitoring of lung cancer and other thoracic neoplasms with conventional or more recently developed therapies. © RSNA, 2023 Quiz questions for this article are available in the supplemental material. Supplemental material and the slide presentation from the RSNA Annual Meeting are available for this article.

Mutational spectrum of GNAL, THAP1 and TOR1A genes in isolated dystonia: study in a population from Spain and systematic literature review.

OBJECTIVE: We aimed to investigate the prevalence of TOR1A, GNAL and THAP1 variants as the cause of dystonia in a cohort of Spanish patients with isolated dystonia and in the literature. METHODS: A population of 2028 subjects (including 1053 patients with different subtypes of isolated dystonia and 975 healthy controls) from southern and central Spain was included. The genes TOR1A, THAP1 and GNAL were screened using a combination of high-resolution melting analysis and direct DNA resequencing. In addition, an extensive literature search to identify original articles (published before 10 August 2020) reporting mutations in TOR1A, THAP1 or GNAL associated to dystonia was performed. RESULTS: Pathogenic or likely pathogenic variants in TOR1A, THAP1 and GNAL were identified in 0.48%, 0.57% and 0.29% of our patients, respectively. Five patients carried the variation p.Glu303del in TOR1A. A very rare variant in GNAL (p.Ser238Asn) was found as a putative risk factor for dystonia. In the literature, variations in TOR1A, THAP1 and GNAL accounted for about 6%, 1.8% and 1.1% of published dystonia patients, respectively. CONCLUSIONS: There is a different genetic contribution to dystonia of these three genes in our patients (about 1.3% of patients) and in the literature (about 3.6% of patients), probably due the high proportion of adult-onset cases in our cohort. As regards age at onset, site of dystonia onset, and final distribution, in our population there is a clear differentiation between DYT-TOR1A and DYT-GNAL, with DYT-THAP1 likely to be an intermediate phenotype.

Myocardial inflammation and energetics by cardiac MRI: a review of emerging techniques.

The role of inflammation in cardiovascular pathophysiology has gained a lot of research interest in recent years. Cardiovascular Magnetic Resonance has been a powerful tool in the non-invasive assessment of inflammation in several conditions. More recently, Ultrasmall superparamagnetic particles of iron oxide have been successfully used to evaluate macrophage activity and subsequently inflammation on a cellular level. Current evidence from research studies provides encouraging data and confirms that this evolving method can potentially have a huge impact on clinical practice as it can be used in the diagnosis and management of very common conditions such as coronary artery disease, ischaemic and non-ischaemic cardiomyopathy, myocarditis and atherosclerosis. Another important emerging concept is that of myocardial energetics. With the use of phosphorus magnetic resonance spectroscopy, myocardial energetic compromise has been proved to be an important feature in the pathophysiological process of several conditions including diabetic cardiomyopathy, inherited cardiomyopathies, valvular heart disease and cardiac transplant rejection. This unique tool is therefore being utilized to assess metabolic alterations in a wide range of cardiovascular diseases. This review systematically examines these state-of-the-art methods in detail and provides an insight into the mechanisms of action and the clinical implications of their use.

Optimizing Diffusion-Tensor Imaging Acquisition for Spinal Cord Assessment: Physical Basis and Technical Adjustments.

Diffusion-tensor imaging (DTI) has been used in the assessment of the central nervous system for the past 3 decades and has demonstrated great utility for the functional assessment of normal and pathologic white matter. Recent technical advances have permitted the expansion of DTI applications to the spinal cord. MRI of the spinal cord has traditionally been limited to conventional sequences, which provide information regarding changes in the anatomic shape of a structure or its signal intensity, suggesting the presence of a pathologic entity. However, conventional MRI lacks the ability to provide pathophysiologic information. DTI of the spinal cord can deliver pathophysiologic information on a molecular basis and thereby has several adjunctive uses. These advantages have yet to be fully evaluated, and therefore spinal DTI lacks widespread adoption. The barriers to implementation include a lack of understanding of the underlying physics principles needed to make necessary technical adjustments to obtain diagnostic images, as well as the need for standardization of protocols and postprocessing methods. The authors provide a comprehensive review of the physics of spinal cord DTI and the technical adjustments required to obtain diagnostic images and describe tips and tricks for accurate postprocessing. The primary clinical applications for spinal cord DTI are reviewed. Online supplemental material is available for this article. ©RSNA, 2020 See discussion on this article by Smith.

Jacobian weighted temporal total variation for motion compensated compressed sensing reconstruction of dynamic MRI.

PURPOSE: To eliminate the need of spatial intraframe regularization in a recently reported dynamic MRI compressed-sensing-based reconstruction method with motion compensation and to increase its performance. THEORY AND METHODS: We propose a new regularization metric based on the introduction of a spatial weighting measure given by the Jacobian of the estimated deformations. It shows convenient discretization properties and, as a byproduct, it also provides a theoretical support to a result reported by others based on an intuitive design. The method has been applied to the reconstruction of both short and long axis views of the heart of four healthy volunteers. Quantitative image quality metrics as well as straightforward visual assessment are reported. RESULTS: Short and long axis reconstructions of cardiac cine MRI sequences have shown superior results than previously reported methods both in terms of quantitative metrics and of visual assessment. Fine details are better preserved due to the lack of additional intraframe regularization, with no significant image artifacts even for an acceleration factor of 12. CONCLUSIONS: The proposed Jacobian Weighted temporal Total Variation results in better reconstructions of highly undersampled cardiac cine MRI than previously proposed methods and sets a theoretical ground for forward and backward predictors used elsewhere. Magn Reson Med 77:1208-1215, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Nonrigid groupwise registration for motion estimation and compensation in compressed sensing reconstruction of breath-hold cardiac cine MRI.

PURPOSE: Compressed sensing methods with motion estimation and compensation techniques have been proposed for the reconstruction of accelerated dynamic MRI. However, artifacts that naturally arise in compressed sensing reconstruction procedures hinder the estimation of motion from reconstructed images, especially at high acceleration factors. This work introduces a robust groupwise nonrigid motion estimation technique applied to the compressed sensing reconstruction of dynamic cardiac cine MRI sequences. THEORY AND METHODS: A spatio-temporal regularized, groupwise, nonrigid registration method based on a B-splines deformation model and a least squares metric is used to estimate and to compensate the movement of the heart in breath-hold cine acquisitions and to obtain a quasistatic sequence with highly sparse representation in temporally transformed domains. RESULTS: Short axis in vivo datasets are used for validation, both original multicoil as well as DICOM data. Fully sampled data were retrospectively undersampled with various acceleration factors and reconstructions were compared with the two well-known methods k-t FOCUSS and MASTeR. The proposed method achieves higher signal to error ratio and structure similarity index for medium to high acceleration factors. CONCLUSIONS: Reconstruction methods based on groupwise registration show higher quality reconstructions for cardiac cine images than the pairwise counterparts tested.

Exome sequencing extends the phenotypic spectrum for ABHD12 mutations: from syndromic to nonsyndromic retinal degeneration.

OBJECTIVE: To identify the genetic causes underlying autosomal recessive retinitis pigmentosa (arRP) and to describe the associated phenotype. DESIGN: Case series. PARTICIPANTS: Three hundred forty-seven unrelated families affected by arRP and 33 unrelated families affected by retinitis pigmentosa (RP) plus noncongenital and progressive hearing loss, ataxia, or both, respectively. METHODS: A whole exome sequencing (WES) analysis was performed in 2 families segregating arRP. A mutational screening was performed in 378 additional unrelated families for the exon-intron boundaries of the ABHD12 gene. To establish a genotype-phenotype correlation, individuals who were homozygous or compound heterozygotes of mutations in ABHD12 underwent exhaustive clinical examinations by ophthalmologists, neurologists, and otologists. MAIN OUTCOME MEASURES: DNA sequence variants, best-corrected visual acuity, visual field assessments, electroretinogram responses, magnetic resonance imaging, and audiography. RESULTS: After a WES analysis, we identified 4 new mutations (p.Arg107Glufs*8, p.Trp159*, p.Arg186Pro, and p.Thr202Ile) in ABHD12 in 2 families (RP-1292 and W08-1833) previously diagnosed with nonsyndromic arRP, which cosegregated with the disease among the family members. Another homozygous mutation (p.His372Gln) was detected in 1 affected individual (RP-1487) from a cohort of 378 unrelated arRP and syndromic RP patients. After exhaustive clinical examinations by neurologists and otologists, the 4 affected members of the RP-1292 had no polyneuropathy or ataxia, and the sensorineural hearing loss and cataract were attributed to age or the normal course of the RP, whereas the affected members of the families W08-1833 and RP-1487 showed clearly symptoms associated with polyneuropathy, hearing loss, cerebellar ataxia, RP, and early-onset cataract (PHARC) syndrome. CONCLUSIONS: Null mutations in the ABHD12 gene lead to PHARC syndrome, a neurodegenerative disease including polyneuropathy, hearing loss, cerebellar ataxia, RP, and early-onset cataract. Our study allowed us to report 5 new mutations in ABHD12. This is the first time missense mutations have been described for this gene. Furthermore, these findings are expanding the spectrum of phenotypes associated with ABHD12 mutations ranging from PHARC syndrome to a nonsyndromic form of retinal degeneration.

Development of a prediction formula of Parkinson disease severity by optical coherence tomography.

The aims of this study were to assess the peripapillary retinal nerve fiber layer (RNFL) thickness in patients with Parkinson's disease (PD), to determine its correlation with disease severity, and to define a simple biomarker for predicting clinical severity. One hundred two eyes from 52 patients affected by PD were compared with 97 eyes from 50 age-comparable controls. In all patients, peripapillary RNFL thickness was measured by optical coherence tomography (OCT). We used the Unified Parkinson's Disease Rating Scale (UPDRS) total score and measured responses in the on medication state. Eyes from patients with PD had a statistically significant decrease in average peripapillary RNFL thickness compared with control eyes (P < 0.001). This reduction was observed in every quadrant (inferior, superior, nasal [P < 0.001], and temporal [P = 0.017]) in patients with PD. Furthermore, a strong inverse correlation was found between the PD severity measured according to the UPDRS score and the average peripapillary RNFL thickness (r = -0.615; P < 0.001) and PD duration (r = -0.303; P = 0.002). From these results, we defined a regression equation that predicts the UPDRS score from the above-mentioned variables: UPDRS = 81.6 + 29.6 * log PD duration (years) - 0.6 * RFNL thickness (µm). We observed that, as the evolution and severity of PD progress, the peripapillary RNFL layer thickness, as evaluated by OCT, gradually diminishes. These results suggest that the average peripapillary RNFL thickness measured by OCT might be useful as a biomarker to detect the early onset and progression of PD.

Lack of validation of variants associated with cervical dystonia risk: a GWAS replication study.

BACKGROUND: A recent genome-wide association study (GWAS) has identified a putative association, not statistically confirmed, of cervical dystonia within several regions in a British population. Hence, the authors proposed dysfunction of the ion channel NALCN (for sodium leak channel, nonselective) as a plausible cause of cervical dystonia. The objective of our study was to investigate the association of five single nucleotide polymorphisms (SNPs) previously reported with high signals as putative genetic risk factors for cervical dystonia in a British GWAS, including two located in the NALCN gene region. METHODS: We performed a case-control association study in a Spanish population. The SNPs selected for genotyping were two SNPS in the NALCN gene (rs61973742 and rs1338041), one SNP in the OR4X2 gene (rs67863238), one SNP in the COL4A1 region (rs619152), and one intergenic SNP (rs1249277). Genomic DNA was collected from 252 patients with cervical dystonia, with a mean age of 55.3 ± 14.1 years (mean age at onset, 43.5 ± 15.7 years), and 342 unrelated control subjects with a mean age of 56.3 ± 14.3 years. Genotyping of SNPs was performed using TaqMan assays and SimpleProbe assays. RESULTS: The SNP rs619152 had to be excluded because of assay failure. No significant differences were found in allele distribution between cases and controls for all analyzed SNPs. Therefore, we found no association with cervical dystonia for the analyzed SNPs in our Spanish population. CONCLUSIONS: We did not find any evidence supporting the association of NALCN with cervical dystonia, indicating that this gene is not implicated in the pathogenesis of this disorder in our cervical dystonia population.

Perampanel: Medical Alternative for Essential Tremor?

OBJECTIVES: The aim of this study was to assess the safety and efficacy of perampanel in patients with refractory essential tremor (ET). METHODS: We recruited patients from our movement disorders clinic with the diagnosis of severe refractory ET, and perampanel 4 mg at night was initiated.Assessments were conducted at baseline and after 1 month of treatment with perampanel 4 mg/d. Details about tolerance and effectiveness were collected. Clinical evaluation was conducted with the Fahn-Tolosa-Marín scale, and statistical analysis was carried out with Wilcoxon matched pairs signed rank test. RESULTS: This study included 18 patients with severe ET (11 females, 7 males; mean age: 75.1 ± 12.03 years; mean duration of ET: 17.4 ± 17.03 years). Perampanel significantly improved patients' average score with refractory ET ( P ≤ 0.0001). This improvement has been occasionally quite relevant. However, a proportion of patients did not tolerate perampanel because of several adverse effects including dizziness, ataxia, irritability, and instability. CONCLUSIONS: Perampanel had a markedly positive antitremor effect in patients with ET and could be an alternative treatment. However, this drug is not devoid of adverse effects.

Clinical impact of artificial intelligence-based solutions on imaging of the pancreas and liver.

Artificial intelligence (AI) has experienced substantial progress over the last ten years in many fields of application, including healthcare. In hepatology and pancreatology, major attention to date has been paid to its application to the assisted or even automated interpretation of radiological images, where AI can generate accurate and reproducible imaging diagnosis, reducing the physicians' workload. AI can provide automatic or semi-automatic segmentation and registration of the liver and pancreatic glands and lesions. Furthermore, using radiomics, AI can introduce new quantitative information which is not visible to the human eye to radiological reports. AI has been applied in the detection and characterization of focal lesions and diffuse diseases of the liver and pancreas, such as neoplasms, chronic hepatic disease, or acute or chronic pancreatitis, among others. These solutions have been applied to different imaging techniques commonly used to diagnose liver and pancreatic diseases, such as ultrasound, endoscopic ultrasonography, computerized tomography (CT), magnetic resonance imaging, and positron emission tomography/CT. However, AI is also applied in this context to many other relevant steps involved in a comprehensive clinical scenario to manage a gastroenterological patient. AI can also be applied to choose the most convenient test prescription, to improve image quality or accelerate its acquisition, and to predict patient prognosis and treatment response. In this review, we summarize the current evidence on the application of AI to hepatic and pancreatic radiology, not only in regard to the interpretation of images, but also to all the steps involved in the radiological workflow in a broader sense. Lastly, we discuss the challenges and future directions of the clinical application of AI methods.

The enduring enigma of sporadic chorea: A single center case series.

Chorea can have a wide variety of causes including neurodegenerative, pharmacological, structural, metabolic, infectious, immunologic and paraneoplastic processes. We reviewed the clinical records of patients with apparently sporadic choreic movements and no relevant family history, who presented to our neurology department (Hospital Fundación Jimenez Diaz) between 1991 and 2022. We detected 38 cases of apparent sporadic chorea (ASC); Our analysis revealed 5 cases of genetic chorea (including 3 cases with Huntington's disease) while 6 cases were autoimmune/hematological; 6 drug-related chorea, 5 metabolic-vascular, 5 due to miscellaneous conditions and 4 were of mixed etiology. No clear etiology was identified in 8 cases. The differential diagnosis of ASC is extensive and challenging. Highlights: Chorea can have a wide variety of genetic and sporadic causesWe reviewed the clinical records of patients with apparently sporadic chorea (ASC), who presented to our neurology department over the last 30 yearsWe detected 38 cases of apparent ASC; Our analysis revealed a wide array of different sporadic conditions and 5 cases of genetic choreaThe differential diagnosis of ASC is extensive and challenging.

Fast 4D elastic group-wise image registration. Convolutional interpolation revisited.

BACKGROUND AND OBJECTIVE: This paper proposes a new and highly efficient implementation of 3D+t groupwise registration based on the free-form deformation paradigm. METHODS: Deformation is posed as a cascade of 1D convolutions, achieving great reduction in execution time for evaluation of transformations and gradients. RESULTS: The proposed method has been applied to 4D cardiac MRI and 4D thoracic CT monomodal datasets. Results show an average runtime reduction above 90%, both in CPU and GPU executions, compared with the classical tensor product formulation. CONCLUSIONS: Our implementation, although fully developed for the metric sum of squared differences, can be extended to other metrics and its adaptation to multiresolution strategies is straightforward. Therefore, it can be extremely useful to speed up image registration procedures in different applications where high dimensional data are involved.

A clinically viable vendor-independent and device-agnostic solution for accelerated cardiac MRI reconstruction.

BACKGROUND AND OBJECTIVE: Recent research has reported methods that reconstruct cardiac MR images acquired with acceleration factors as high as 15 in Cartesian coordinates. However, the computational cost of these techniques is quite high, taking about 40 min of CPU time in a typical current machine. This delay between acquisition and final result can completely rule out the use of MRI in clinical environments in favor of other techniques, such as CT. In spite of this, reconstruction methods reported elsewhere can be parallelized to a high degree, a fact that makes them suitable for GPU-type computing devices. This paper contributes a vendor-independent, device-agnostic implementation of such a method to reconstruct 2D motion-compensated, compressed-sensing MRI sequences in clinically viable times. METHODS: By leveraging our OpenCLIPER framework, the proposed system works in any computing device (CPU, GPU, DSP, FPGA, etc.), as long as an OpenCL implementation is available, and development is significantly simplified versus a pure OpenCL implementation. In OpenCLIPER, the problem is partitioned in independent black boxes which may be connected as needed, while device initialization and maintenance is handled automatically. Parallel implementations of both a groupwise FFD-based registration method, as well as a multicoil extension of the NESTA algorithm have been carried out as processes of OpenCLIPER. Our platform also includes significant development and debugging aids. HIP code and precompiled libraries can be integrated seamlessly as well since OpenCLIPER makes data objects shareable between OpenCL and HIP. This also opens an opportunity to include CUDA source code (via HIP) in prospective developments. RESULTS: The proposed solution can reconstruct a whole 12-14 slice CINE volume acquired in 19-32 coils and 20 phases, with an acceleration factor of ranging 4-8, in a few seconds, with results comparable to another popular platform (BART). If motion compensation is included, reconstruction time is in the order of one minute. CONCLUSIONS: We have obtained clinically-viable times in GPUs from different vendors, with delays in some platforms that do not have correspondence with its price in the market. We also contribute a parallel groupwise registration subsystem for motion estimation/compensation and a parallel multicoil NESTA subsystem for l1-l2-norm problem solving.

Clinical Translation of Three-Dimensional Scar, Diffusion Tensor Imaging, Four-Dimensional Flow, and Quantitative Perfusion in Cardiac MRI: A Comprehensive Review.

Cardiovascular magnetic resonance (CMR) imaging is a versatile tool that has established itself as the reference method for functional assessment and tissue characterisation. CMR helps to diagnose, monitor disease course and sub-phenotype disease states. Several emerging CMR methods have the potential to offer a personalised medicine approach to treatment. CMR tissue characterisation is used to assess myocardial oedema, inflammation or thrombus in various disease conditions. CMR derived scar maps have the potential to inform ablation therapy-both in atrial and ventricular arrhythmias. Quantitative CMR is pushing boundaries with motion corrections in tissue characterisation and first-pass perfusion. Advanced tissue characterisation by imaging the myocardial fibre orientation using diffusion tensor imaging (DTI), has also demonstrated novel insights in patients with cardiomyopathies. Enhanced flow assessment using four-dimensional flow (4D flow) CMR, where time is the fourth dimension, allows quantification of transvalvular flow to a high degree of accuracy for all four-valves within the same cardiac cycle. This review discusses these emerging methods and others in detail and gives the reader a foresight of how CMR will evolve into a powerful clinical tool in offering a precision medicine approach to treatment, diagnosis, and detection of disease.

OpenCLIPER: An OpenCL-Based C++ Framework for Overhead-Reduced Medical Image Processing and Reconstruction on Heterogeneous Devices.

Medical image processing is often limited by the computational cost of the involved algorithms. Whereas dedicated computing devices (GPUs in particular) exist and do provide significant efficiency boosts, they have an extra cost of use in terms of housekeeping tasks (device selection and initialization, data streaming, synchronization with the CPU, and others), which may hinder developers from using them. This paper describes an OpenCL-based framework that is capable of handling dedicated computing devices seamlessly and that allows the developer to concentrate on image processing tasks. The framework handles automatically device discovery and initialization, data transfers to and from the device and the file system and kernel loading and compiling. Data structures need to be defined only once independently of the computing device; code is unique, consequently, for every device, including the host CPU. Pinned memory/buffer mapping is used to achieve maximum performance in data transfers. Code fragments included in the paper show how the computing device is almost immediately and effortlessly available to the users algorithms, so they can focus on productive work. Code required for device selection and initialization, data loading and streaming and kernel compilation is minimal and systematic. Algorithms can be thought of as mathematical operators (called processes), with input, output and parameters, and they may be chained one after another easily and efficiently. Also for efficiency, processes can have their initialization work split from their core workload, so process chains and loops do not incur in performance penalties. Algorithm code is independent of the device type targeted.

Space-time variant weighted regularization in compressed sensing cardiac cine MRI.

PURPOSE: To analyze the impact on image quality and motion fidelity of a motion-weighted space-time variant regularization term in compressed sensing cardiac cine MRI. METHODS: k-t SPARSE-SENSE with temporal total variation (tTV) is used as the base reconstruction algorithm. Motion in the dynamic image is estimated by means of a robust registration technique for non-rigid motion. The resulting deformation fields are used to leverage the regularization term. The results are compared with standard k-t SPARSE-SENSE with tTV regularization as well as with an improved version of this algorithm that makes use of tTV and temporal Fast Fourier Transform regularization in x-f domain. RESULTS: The proposed method with space-time variant regularization provides higher motion fidelity and image quality than the two previously reported methods. Difference images between undersampled reconstruction and fully sampled reference images show less systematic errors with the proposed approach. CONCLUSIONS: Usage of a space-time variant regularization offers reconstructions with better image quality than the state of the art approaches used for comparison.