Application Of Magnetic Resonance Imaging Research Articles

A review of magnetic ordered materials in biomedical field: Constructions, applications and prospects

Magnetic ordered materials based on magnetic nanoparticles (MNPs) possessing distinct and tunable morphological characteristics, magnetic property and excellent magnetic anisotropy, have received tremendous attentions, especially in biomedical fields. This review clearly organized the construction routes used to prepare magnetic ordered materials, including magnetic field-induced arrangement and orderly manufacturing-based construction. By focusing on the most relevant and the latest advances related to the biomedical applications in cell fate research, bio-inspired fabrication, magnetic hyperthermia, and magnetic resonance imaging, the unique advantages of magnetic ordered materials are presented and highlighted compared with magnetic unordered assemblies. Although the biosafety of many MNPs has been approved by Food and Drug Administration, future developments of magnetic ordered materials should be still centered on the safety, functional and structural diversity for interdisciplinary research. The review was concluded with a compelling perspective outlook and non-trivial challenges in future investigation of magnetic ordered materials.

Diagnostic Value and Clinical Application of Diffusion-Weighted Magnetic Resonance Imaging for Female Pelvic Lesions.

Pelvic inflammatory disease refers to a group of infectious diseases of the female upper genital tract, often caused by ascending infection of vaginitis and cervicitis, causing endometritis, salpingitis, tubo-ovarian abscess, pelvic connective tissue inflammation, and/or pelvic peritonitis. PID is the most common and important infectious disease in nonpregnant women of childbearing age, and inflammation in multiple parts often coexists and affects each other. The functional MRI techniques currently used in pelvic floor muscle injury are magnetic resonance diffusion tensor imaging, T2 mapping, and magnetic resonance elastography. Diffusion tensor imaging is a new imaging and postprocessing technology developed on the basis of magnetic resonance diffusion-weighted imaging. Due to the lack of specificity of clinical symptoms, many subclinical patients are often not detected and diagnosed in time, so it is very difficult to accurately estimate the incidence of PID. This article retrospectively analyzed 72 patients with pelvic inflammatory disease confirmed by surgical pathology from February 2020 to 2022, who had undergone pelvic MRI examination before surgery, including 25 patients with chronic pelvic inflammation (hydrosalpinx), 25 patients with acute pelvic inflammation, and 47 cases (including 21 cases of hydrosalpinx, 19 cases of tubo-ovarian abscess, and 7 cases of pelvic abscess). The age range was 13 to 59 years old. The clinical data and MRI findings were analyzed, the ADC value of the cystic part of the lesion was measured, and the differences in age, maximum diameter of the lesion, thickness of the vessel wall/separation, and the ADC value of the cystic part of chronic and acute pelvic inflammation were compared. In this part of the cases, there were 25 cases of chronic pelvic inflammation and 47 cases of acute pelvic inflammation. The average ADC value of the cystic component of chronic inflammation was significantly higher than that of acute inflammation, which were (2.86 ± 0.20) × 10−3 mm2/s and (1.07 ± 0.38) ×10−3 mm2/s, respectively, P value <0.001.

Application of Multimodal Magnetic Resonance Imaging in Green Channel of Acute and Hyperacute Ischemic Stroke.

The purpose of this study was to observe the effects of multimodal magnetic resonance imaging (MRI) in the green channel of acute and hyperacute ischemic strokes, in order to better guide clinical treatment. The clinical data of 126 patients with acute and hyperacute ischemic stroke who received interventional treatment in the emergency green channel was collected retrospectively. The patients who received multimodal computed tomography (CT) were included in the CT group. Patients who underwent multimodal MRI examinations were included in the MRI group, and the door-to-needle time (DNT), neurological function, and prognosis of the two groups were compared. The result turned out that among the 126 patients included, 40 patients underwent CT examination (CT group) and 86 patients underwent MRI examination (MRI group). A comparison of general data between the CT group and the MRI group showed P > 0.05. The MRI group's DNT time (61.23 ± 9.32) min was shorter than that of the CT group (87.22 ± 14.26) min, P < 0.05. Through comparison, the P values of mRS scores and NIHSS scores in both groups were greater than 0.05. After treatment, the mRS score and NIHSS score of the MRI group was lower, with P < 0.05. According to the results of this study, it can be concluded that emergency multimodal MRI could shorten the DNT time of patients with acute and hyperacute ischemic stroke, reduce the degree of neurological impairment, and improve the prognosis.

COMPARISON OF INCIDENTALLY DETECTED RCC VS SYMPTOMATIC: A SINGLE CENTER EXPERIENCE.

OBJECTIVES: Renal cell carcinoma (RCC) is the most common malignancy of the kidney. Introduction and extensive application of modern imaging techniques, including ultrasonography, computed tomography(CT), and magnetic resonance imaging, have led to an increase in the number of incidentally discovered renal tumors. We analysed incidentally detected renal tumours with regard to their incidence, demographics and histopathology in a contemporary series and compared with symptomatic tumours. MATERIAL AND METHODS: The author reviewed the records of incidentally detected renal masses, treated surgically for suspicion of malignancy between January 2011 and March 2020.The incidence, demographics and histopathology were noted in both incidental and symptomatic tumours. RESULTS: Out of 244 renal masses, 67 cases were incidentally detected. Out of which, 48 (71.64 %) were men and 19 (28.36 %) were women, 34 ( 50.74%) were on the left side and 33 (49.26%) were on the right side. The mean size of incidental tumour was 6.2 cm, 27 (39.55%) partial nephrectomies were performed as compared to 10.1 % in symptomatic tumours (p=0.001%) . Out of these 67 renal masses, 7 (10.44 %) were benign, and 60 (89.56 %) were malignant. Among histopath subtypes, 47 ( 78.33%) were clear cell, 6 ( 10.00% ) were papillary, 3 ( 5.00% ) were chromophobe , 2 ( 3.33 % ) were collecting duct and 2 ( 3.33% ) were other malignancies. Fuhrman grade 2 was most common 31 (50.83 %) in these tumours . Stage T1 tumours were encountered in 93.3 % of incidental masses as compared to only 38.1% of symptomatic (p=0.001). CONCLUSIONS:The incidentally detected tumours are being diagnosed with increased frequency at lower stage (T1) and grade(grade 2).

Efficacy of 68Ga-PSMA-11 PET/CT with biparametric MRI in diagnosing prostate cancer and predicting risk stratification: a comparative study.

This retrospective study aimed to investigate the efficacy of the combined application of biparametric magnetic resonance imaging (bpMRI) and 68Ga-PSMA-11 positron emission computed tomography/computed tomography (bpMRI/PET) in the qualitative diagnosis of intermediate- to high-risk prostate cancer (PCa). The 105 patients with suspected PCa included in the study underwent bpMRI and PET/CT. BpMRI examinations included conventional sequences and diffusion-weighted imaging (DWI) sequences. Major lesions were qualitatively diagnosed according to the Prostate Imaging Reporting and Data System (PI-RADS). A PET/CT scan was started 60 min after intravenous 68Ga-PSMA-11 injection. The area with the highest radioactivity on PET/CT images was defined as the major lesion, and the maximum standard uptake value (SUVmax) was measured. All cases were confirmed by biopsy and pathology. Receiver operating characteristic curve (ROC) analysis was performed on the data to calculate sensitivity, specificity, and the Youden index. Of the 105 patients, 68 patients were diagnosed with PCa, and 37 patients had benign prostatic lesions. With a PI-RADS score ≥3 as the diagnostic threshold, the accuracy of bpMRI in identifying benign and malignant prostate lesions was similar to that of PET/CT (SUVmax threshold ≥10.9), and the Youden indices were 0.60 and 0.64, respectively. The sensitivity and specificity of bpMRI in the differential diagnosis of intermediate- to high-risk PCa versus low-risk PCa or benign lesions were 63% and 88%, respectively, and the Youden index was 0.51. With an SUVmax ≥12.9 as the diagnostic threshold, the sensitivity and specificity of PET/CT in the differential diagnosis of intermediate- to high-risk PCa versus low-risk PCa or benign lesions were 74% and 94%, respectively, and the Youden index was 0.68. The sensitivity and specificity of bpMRI/PET in diagnosing PCa were 94% and 81%, respectively, and the Youden index was 0.75. The sensitivity and specificity of bpMRI/PET in the differential diagnosis of intermediate- to high-risk PCa versus low-risk PCa or benign lesions were 80% and 88%, respectively, and the Youden index was 0.68. The combined application of bpMRI and PET improves the accuracy of the qualitative diagnosis of prostate lesions, and its diagnostic efficacy for risk stratification in patients with intermediate- to high-risk PCa is similar to that of PET/CT and higher than that of bpMRI alone.

Principles and Clinical Applications of Feature-Tracking Cardiac Magnetic Resonance Imaging: A Literature Review

Principles and Clinical Applications of Feature-Tracking Cardiac Magnetic Resonance Imaging: A Literature Review

Effect of Different Nursing Interventions on Discharged Patients with Cardiac Valve Replacement Evaluated by Deep Learning Algorithm-Based MRI Information.

This study was aimed to explore the application of cardiac magnetic resonance imaging (MRI) image segmentation model based on U-Net in the diagnosis of a valvular heart disease. The effect of continuous nursing on the survival of discharged patients with cardiac valve replacement was analyzed in this study. In this study, the filling completion operation, cross entropy loss function, and guidance unit were introduced and optimized based on the U-Net network. The heart MRI image segmentation model ML-Net was established. We compared the Dice, Hausdorff distance (HD), and percentage of area difference (PAD) values between ML-Net and other algorithms. The MRI image features of 82 patients with valvular heart disease who underwent cardiac valve replacement were analyzed. According to different nursing methods, they were randomly divided into the control group (routine nursing) and the intervention group (continuous nursing), with 41 cases in each group. The Glasgow Outcome Scale (GOS) score and the Self-rating Anxiety Scale (SAS) were compared between the two groups to assess the degree of anxiety of patients and the survival status at 6 months, 1 year, 2 years, and 3 years after discharge. The results showed that the Dice coefficient, HD, and PAD of the ML-Net algorithm were (0.896 ± 0.071), (5.66 ± 0.45) mm, and (15.34 ± 1.22) %, respectively. The Dice, HD, and PAD values of the ML-Net algorithm were all statistically different from those of the convolutional neural networks (CNN), fully convolutional networks (FCN), SegNet, and U-Net algorithms (P < 0.05). Atrial, ventricular, and aortic abnormalities can be seen in MRI images of patients with valvular heart disease. The cardiac blood flow signal will also be abnormal. The GOS score of the intervention group was significantly higher than that of the control group (P < 0.01). The SAS score was lower than that of the control group (P < 0.05). The survival rates of patients with valvular heart disease at 6 months, 1 year, 2 years, and 3 years after discharge were significantly higher than those in the control group (P < 0.05). The abovementioned results showed that an effective segmentation model for cardiac MRI images was established in this study. Continuous nursing played an important role in the postoperative recovery of discharged patients after cardiac valve replacement. This study provided a reference value for the diagnosis and prognosis of valvular heart disease.

Clinical Application of 4D Flow MR Imaging for the Abdominal Aorta.

Blood vessels can be regarded as autonomous organs. The endothelial cells on the vessel surface serve as mechanosensors or mechanoreceptors for the flow velocity and turbulence of the blood flow in terms of wall shear stress (WSS), thereby monitoring changes in the flow velocity. Accordingly, the endothelial cells regulate the flow velocity by releasing numerous mediators. Such regulatory systems also trigger atherosclerosis, where the WSS decreases or fluctuates to maintain the flow velocity or local WSS. As occurrences of abdominal aortic aneurysms and aortic dissection are closely related to atherosclerosis, understanding the hemodynamics of the abdominal aorta is necessary to obtain useful information concerning the pathogenesis, diagnosis, and interventions. 4D flow MRI is beneficial for measuring the hemodynamics through comprehensive retrospective flowmetry of the entire spatio-temporal distributions of the flow vectors. This section focuses on abdominal aortic aneurysms and aortic dissection as representative examples of abdominal aortic diseases. Their hemodynamic characteristics and how hemodynamics is involved in their progression are described, and how 4D flow MRI can contribute to their assessment is also explained.

Clinical Applications of 4D Flow MR Imaging in Aortic Valvular and Congenital Heart Disease.

4D flow MRI allows time-resolved 3D velocity-encoded phase-contrast imaging for 3D visualization and quantification of aortic and intracardiac flow. Radiologists should be familiar with the principles of 4D flow MRI and methods for evaluating blood flow qualitatively and quantitatively. The most substantial benefits of 4D flow MRI are that it enables the simultaneous comprehensive assessment of different vessels, and that retrospective analysis can be achieved in all vessels in any direction in the field of view, which is especially beneficial for patients with complicated congenital heart disease (CHD). For aortic valvular diseases, new parameters such as wall shear stress and energy loss may provide new prognostic values for 4D flow MRI. In this review, we introduce the clinical applications of 4D flow MRI for the visualization of blood flow and quantification of hemodynamic metrics in the setting of aortic valvular disease and CHD, including intracardiac shunt and coronary artery anomaly.

Clinical Application of 4D Flow MR Imaging to Pulmonary Hypertension.

Pulmonary hypertension (PH) is characterized by elevated pulmonary arterial pressure (PAP). Although right-heart catheterization is the gold standard method for the diagnosis of PH by definition, various less-invasive imaging tests have been used for screening, detection of underlying diseases-causing PH, and monitoring of diseases. Among them, 4D flow MRI is an emerging and unique imaging test that allows for comprehensive visualization of blood flow in the right heart and proximal pulmonary arteries. The characteristic blood flow pattern observed in patients with PH is vortical flow formation in the main pulmonary artery. Recent studies have proposed the use of these findings to determine not only the presence of PH but also estimate the mean PAP. Other applications of 4D flow MRI for PH include measurement of wall shear stress, helicity, and 3D flow balance in the pulmonary arteries. It is worth noting that 4D flow has also the potential for longitudinal follow-ups. In this review, the clinical definition of PH, summary of conventional imaging tests, characteristics of pulmonary arterial flow as shown by 4D flow MRI, and clinical application of 4D flow MRI in the management of patients with PH will be discussed.

Compression of volume-surface integral equation matrices via Tucker decomposition for magnetic resonance applications.

In this work, we propose a method for the compression of the coupling matrix in volume-surface integral equation (VSIE) formulations. VSIE methods are used for electromagnetic analysis in magnetic resonance imaging (MRI) applications, for which the coupling matrix models the interactions between the coil and the body. We showed that these effects can be represented as independent interactions between remote elements in 3D tensor formats, and subsequently decomposed with the Tucker model. Our method can work in tandem with the adaptive cross approximation technique to provide fast solutions of VSIE problems. We demonstrated that our compression approaches can enable the use of VSIE matrices of prohibitive memory requirements, by allowing the effective use of modern graphical processing units (GPUs) to accelerate the arising matrix-vector products. This is critical to enable numerical MRI simulations at clinical voxel resolutions in a feasible computation time. In this paper, we demonstrate that the VSIE matrix-vector products needed to calculate the electromagnetic field produced by an MRI coil inside a numerical body model with 1 mm3 voxel resolution, could be performed in ~ 33 seconds in a GPU, after compressing the associated coupling matrix from ~ 80 TB to ~ 43 MB.

Polarization Insensitive Broadband Zero Indexed Nano-Meta Absorber for Optical Region Applications

Broadband response metamaterial absorber (MMA) remains a challenge among researchers. A nanostructured new zero-indexed metamaterial (ZIM) absorber is presented in this study, constructed with a hexagonal shape resonator for optical region applications. The design consists of a resonator and dielectric layers made with tungsten and quartz (Fused). The proposed absorbent exhibits average absorption of more than 0.8972 (89.72%) within the visible wavelength of 450–600 nm and nearly perfect absorption of 0.99 (99%) at 461.61 nm. Based on computational analysis, the proposed absorber can be characterized as ZIM. The developments of ZIM absorbers have demonstrated plasmonic resonance characteristics and a perfect impedance match. The incidence obliquity in typically the range of 0°–90° both in TE and TM mode with maximum absorbance is more than 0.8972 (∼89.72%), and up to 45° angular stability is suitable for solar cell applications, like exploiting solar energy. The proposed structure prototype is designed and simulated by studying microwave technology numerical computer simulation (CST) tools. The finite integration technique (FIT) based simulator CST and finite element method (FEM) based simulator HFSS also helps validate the numerical data of the proposed ZIM absorber. The proposed MMA design is appropriate for substantial absorption, wide-angle stability, absolute invisible layers, magnetic resonance imaging (MRI), color images, and thermal imaging applications.

The olfactory bulb - gateway for SARS-Cov-2?

Introduction. Anosmia and ageusia are one of the most common and characteristic symptoms of severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) infection, with a frequency of almost 50% in patients in Western countries. Hypotheses proposing that the virus potentially affects the central nervous system (CNS) are on the rise. One hypothesis suggests that the virus enters via nasal mucosa and then enters the olfactory bulb via cribriform plate, with further dissemination to the CNS. Case report. A 34-year-old female patient experienced the loss of the sense of smell and taste about two months before testing positive for SARS-Cov-2. Coronavirus disease 2019 (COVID-19) presented with minor pneumonia and worsening anosmia and ageusia. After treatment, the patient recovered well, but anosmia and ageusia appeared again, varying in intensity, and since February 2021, they have become persistent. The case was evaluated by an otorhino-laryngologist, pulmonologist, and finally, a neurologist. In the meantime, the patient tested negative for SARS-Cov-2 and received two doses of the Sputnik V vaccine. Brain magnetic resonance imaging (MRI) was performed, and it clearly showed severe bilateral olfactory bulb atrophy. The patient has had anosmia and ageusia up to this day, and future MRI follow-up is planned. Conclusion. Loss of sense of smell and taste may be a predictor of further CNS dis-semination of the virus and possible neurological complications (which is still a subject of consideration). The olfactory bulb could be a gateway to COVID-19 intrusion into the CNS, and its atrophy could be an indicator of the process. Further investigation on this topic is required, including a wide application of MRI, in order to come to definite conclusions.

Alternating Learning Approach for Variational Networks and Undersampling Pattern in Parallel MRI Applications.

This work proposes an alternating learning approach to learn the sampling pattern (SP) and the parameters of variational networks (VN) in accelerated parallel magnetic resonance imaging (MRI). We investigate four variations of the learning approach, that alternates between improving the SP, using bias-accelerated subset selection, and improving parameters of the VN, using ADAM. The variations include the use of monotone or non-monotone alternating steps and systematic reduction of learning rates. The algorithms learn an effective pair to be used in future scans, including an SP that captures fewer k-space samples in which the generated undersampling artifacts are removed by the VN reconstruction. The quality of the VNs and SPs obtained by the proposed approaches is compared against different methods, including other kinds of joint learning methods and state-of-art reconstructions, on two different datasets at various acceleration factors (AF). We observed improvements visually and in three different figures of merit commonly used in deep learning (RMSE, SSIM, and HFEN) on AFs from 2 to 20 with brain and knee joint datasets when compared to the other approaches. The improvements ranged from 1% to 62% over the next best approach tested with VNs. The proposed approach has shown stable performance, obtaining similar learned SPs under different initial training conditions. We observe that the improvement is not only due to the learned sampling density, it is also due to the learned position of samples in k-space. The proposed approach was able to learn effective pairs of SPs and reconstruction VNs, improving 3D Cartesian accelerated parallel MRI applications.

Application of Magnetic Resonance Imaging of Patients with Concussion in Clinical Emergency.

Concussion syndrome is a common disease in neurosurgery, and its incidence ranks first among all traumatic brain injuries. Cognitive dysfunction is one of the most common functional impairments in concussion syndrome. Neuroimaging and content assessments on concussion patients and healthy control subjects are used in this study, which uses MRI technology to evaluate brain pictures of concussion patients. Moreover, this paper separately evaluates the scores of the concussion syndrome group and the healthy control group in multiple functional aspects and performs independent sample t-test after statistics of the two scores. In addition, this paper uses resting-state fMRI to study the changes in the functional connectivity of the medial prefrontal lobe in patients with PCS, which has certain significance in revealing cognitive dysfunction after concussion and has a certain effect on improving the clinical emergency diagnosis and treatment of concussion.

Designof an insertable cone-shaped gradient coil matrix for head imaging with a volumetric finite-difference method.

Matrix gradient coils have received increasing interest in generating arbitrary-shaped magnetic fields for various magnetic resonance imaging applications. In this paper, a novel cone-shaped matrix gradient coil is proposed to designa multifunctional insertable system for head imaging. Using a volumetric finite-difference-based method, the matrix coil is designed to have comprised several coil elements that can implement localized imaging and control eddy current, dissipated power, and minimum wire gap. With the lowest total dissipated power, various current configurations are selected to generate multiple gradient fields within a large, spheroidal region of interest (ROI) and two small spherical sub-ROIs. The numerical computation results show that the designed matrix coil offers high flexibility in generating a local gradient field capable of improving the local resolution. In addition, with enhanced coil performance, the cone-shaped structure provides a patient-friendly solution for head imaging.

Dynamic contrast-enhanced magnetic resonance imaging

This study aims to investigate the potential application of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to predict concurrent chemoradiation (CRT) in locally advanced esophageal carcinoma. This study involved 33 patients with locally advanced esophageal cancer and treated with CRT. The patients underwent DCE-MRI before CRT (pre) and 3 weeks after starting CRT (mid). The patients were categorized into two groups: complete response (CR) and non-complete response (non-CR) after 3 months of treatment. The quantitative parameters of DCE-MRI (Ktrans, Kep, and Ve), the changes and ratios of parameters (ΔKtrans, ΔKep, ΔVe, rΔKtrans, rΔKep, and rΔVe), and the relative ratio in the tumor area and a normal tube wall (rKtrans, rKep, and rVe) were calculated and compared between two timeframes in two groups, respectively. Moreover, the receiver operating characteristics (ROC) statistical analysis was used to assess the above parameters. We divided 33 patients into two groups: 22 in the CR group and 11 in the non-CR group. During the mid-CRT phase in the CR group, both Ktrans and Kep rapidly decreased, while only Kep decreased in the non-CR group. The pre-Ktrans and pre-Kep in the CR group were substantially higher compared to the non-CR group. Moreover, the rKtrans was also apparently observed as higher at pre-CRT in the CR group compared to the non-CR group. The ROC analysis demonstrated that the pre-Ktrans could be the best parameter to evaluate the treatment performance (AUC = 0.74). Pre-Ktrans could be a promising parameter to forecast how patients with locally advanced esophageal cancer will respond to CRT.

Magnetic Resonance Imaging in Animal Models of Alzheimer's Disease Amyloidosis.

Amyloid-beta (Aβ) plays an important role in the pathogenesis of Alzheimer’s disease. Aberrant Aβ accumulation induces neuroinflammation, cerebrovascular alterations, and synaptic deficits, leading to cognitive impairment. Animal models recapitulating the Aβ pathology, such as transgenic, knock-in mouse and rat models, have facilitated the understanding of disease mechanisms and the development of therapeutics targeting Aβ. There is a rapid advance in high-field MRI in small animals. Versatile high-field magnetic resonance imaging (MRI) sequences, such as diffusion tensor imaging, arterial spin labeling, resting-state functional MRI, anatomical MRI, and MR spectroscopy, as well as contrast agents, have been developed for preclinical imaging in animal models. These tools have enabled high-resolution in vivo structural, functional, and molecular readouts with a whole-brain field of view. MRI has been used to visualize non-invasively the Aβ deposits, synaptic deficits, regional brain atrophy, impairment in white matter integrity, functional connectivity, and cerebrovascular and glymphatic system in animal models of Alzheimer’s disease amyloidosis. Many of the readouts are translational toward clinical MRI applications in patients with Alzheimer’s disease. In this review, we summarize the recent advances in MRI for visualizing the pathophysiology in amyloidosis animal models. We discuss the outstanding challenges in brain imaging using MRI in small animals and propose future outlook in visualizing Aβ-related alterations in the brains of animal models.

Deep Learning Applications in Magnetic Resonance Imaging: Has the Future Become Present?

Deep learning technologies and applications demonstrate one of the most important upcoming developments in radiology. The impact and influence of these technologies on image acquisition and reporting might change daily clinical practice. The aim of this review was to present current deep learning technologies, with a focus on magnetic resonance image reconstruction. The first part of this manuscript concentrates on the basic technical principles that are necessary for deep learning image reconstruction. The second part highlights the translation of these techniques into clinical practice. The third part outlines the different aspects of image reconstruction techniques, and presents a review of the current literature regarding image reconstruction and image post-processing in MRI. The promising results of the most recent studies indicate that deep learning will be a major player in radiology in the upcoming years. Apart from decision and diagnosis support, the major advantages of deep learning magnetic resonance imaging reconstruction techniques are related to acquisition time reduction and the improvement of image quality. The implementation of these techniques may be the solution for the alleviation of limited scanner availability via workflow acceleration. It can be assumed that this disruptive technology will change daily routines and workflows permanently.

Cardiac CT and MRI radiomics: systematic review of the literature and radiomics quality score assessment.

To systematically review and evaluate the methodological quality of studies using magnetic resonance imaging (MRI) and computed tomography (CT) radiomics for cardiac applications. Multiple medical literature archives (PubMed, Web of Science, and EMBASE) were systematically searched to retrieve original studies focused on cardiac MRI and CT radiomics applications. Two researchers in consensus assessed each investigation using the radiomics quality score (RQS). Subgroup analyses were performed to assess whether the total RQS varied according to study aim, journal quartile, imaging modality, and first author category. From a total of 1961 items, 53 articles were finally included in the analysis. Overall, the studies reached a median total RQS of 7 (IQR, 4-12), corresponding to a percentage score of 19.4% (IQR, 11.1-33.3%). Item scores were particularly low due to lack of prospective design, cost-effectiveness analysis, and open science. Median RQS percentage score was significantly higher in papers where the first author was a medical doctor and in those published on first quartile journals. The overall methodological quality of radiomics studies in cardiac MRI and CT is still lacking. A higher degree of standardization of the radiomics workflow and higher publication standards for studies are required to allow its translation into clinical practice. • RQS has been recently proposed for the overall assessment of the methodological quality of radiomics-based studies. • The 53 included studies on cardiac MRI and CT radiomics applications reached a median total RQS of 7 (IQR, 4-12), corresponding to a percentage of 19.4% (IQR, 11.1-33.3%). • A more standardized methodology in the radiomics workflow is needed, especially in terms of study design, validation, and open science, in order to translate the results to clinical applications.