Search Results (137)

Objectives: Methamphetamine (MA) abuse during adolescence can have a significant impact on brain development. On the other hand, regular exercise is known to promote brain health and may have neuroprotective effects. The purpose of this study is to compare brain volumes in three different adolescent groups: those with active methamphetamine use disorder (MUD), adolescent athletes who regularly exercise, and healthy control adolescents. Methods: This MRI study involved three groups of adolescents: 10 with active MUD (9 males, 1 female), nine licensed runner adolescents (three males, six females), and 10 healthy adolescents (5 males, 5 females). Brain volumes were analyzed using T1-weighted images from a 3.0 Tesla MRI scanner, and then segmented automatically with vol2Brain. Statistical analyses included ANCOVA with sex as a covariate and LSD post hoc tests performed using SPSS Statistics 23. Results: Adolescents with MUD showed a 10% increase in total white matter volume compared to the athlete group. Conversely, cortical gray matter volume was reduced by 4% compared to the healthy control group and by 7% compared to the athlete group. The frontal and insular cortices in the MUD group had significantly diminished volumes compared to the athlete group. Overall, individuals with MUD had decreased gray matter volumes and increased white matter volumes in their brains. The brain volumetric differences between the MUD group and the athlete group were statistically significant. Conclusions: The brains of those with MUD displayed a reduction in gray matter volume and an increase in white matter volume, indicating damage from MA on the developing adolescent brain. The volumetric disparities between the MUD and athlete groups were found to be significantly different, suggesting a possible neuroprotective factor of exercise. Further studies are required to explore the potential of exercise-based interventions in alleviating the harmful effects of MA abuse. Full article

Introduction: Sepsis-associated encephalopathy (SAE) is an acute brain dysfunction secondary to systemic infection, occurring without direct central nervous system involvement. Despite its clinical relevance, reliable biomarkers for diagnosing SAE and assessing its severity remain limited. This study aimed to evaluate the feasibility of amide proton transfer-weighted (APTw) chemical exchange saturation transfer (CEST) MRI as a non-invasive molecular imaging technique for detecting metabolic alterations related to neuroinflammation in SAE. Using a lipopolysaccharide (LPS)-induced rat model, we focused on hippocampal changes associated with neuronal inflammation. Materials and Methods: Twenty-one Sprague–Dawley rats (8 weeks old, male) were divided into three groups: control (CTRL, n = 7), LPS-induced sepsis at 5 mg/kg (LPS05, n = 7), and 10 mg/kg (LPS10, n = 7). Sepsis was induced via a single intraperitoneal injection of LPS. APTw imaging was performed using a 7 T preclinical MRI system, and signal quantification in the hippocampus was conducted using the magnetization transfer ratio asymmetry analysis. Results and Discussion: APTw imaging at 7 T demonstrated significantly elevated hippocampal APTw signals in SAE model rats (LPS05 and LPS10) compared to the control (CTRL) group: CTRL (−1.940 ± 0.207%) vs. LPS05 (−0.472 ± 0.485%) (p < 0.001) and CTRL vs. LPS10 (−0.491 ± 0.279%) (p < 0.001). However, no statistically significant difference was observed between the LPS05 and LPS10 groups (p = 0.994). These results suggest that APTw imaging can effectively detect neuroinflammation-related metabolic alterations in the hippocampus. Conclusion: Our findings support the feasibility of APTw CEST imaging as a non-invasive molecular MRI technique for SAE, with potential applications in diagnosis, disease monitoring, and therapeutic evaluation. Full article

Background/Objectives: The purpose of this study was to identify the most effective MRI techniques for detecting and characterising neck paragangliomas (NPGLs), which are highly vascularised tumors. Methods: Five readers were asked which MRI sequence among T2-WI, contrast-enhanced fat-suppressed T1-WI, pcASL, and TRICKS made them most confident in diagnosing paraganglioma. To evaluate concordance among the readers, the Fleiss K value was calculated. Sensitivity, specificity, and negative predictive values were calculated for each observer separately, and from all values, a mean was calculated. Results: The final cohort consisted of 28 patients (11 diagnosed with head-and-neck paragangliomas (HNPGLs)) of whom 7 were histologically confirmed and 4 identified based on a positive family history; 11 patients were undergoing familial screening (8 with HNPGLs and 3 without), and 6 patients had surgically confirmed vagal schwannomas. None of the schwannomas showed any increase in signal on pcASL sequences or arterial enhancement on TRICKS acquisition. The best concordance among readers was reached for pcASL and combined pcASL-TRICKS images (K = 1). Conclusions: The combined use of pcASL and TRICKS should be considered essential in a standardised protocol for characterising NPGLs. Full article

Background: Uterine fibroids are the most common tumors in gynecology, detected in up to 80% of patients at various points in their lives. Uterine sarcomas account for 3% to 7% of all uterine cancers. The diagnosis of uterine fibroids is possible through ultrasonography (US), but this method has many limitations. More accurate examinations include magnetic resonance imaging (MRI) and positron emission tomography (PET) scans. Methods: This study evaluates MRI and PET in differentiating uterine fibroids from sarcomas. MRI uses T2-weighted and diffusion-weighted imaging (DWI), while PET assesses metabolism and estrogen receptor activity using [18F] fluorodeoxyglucose (FDG) and 16α-[18F]-fluoro-17β-estradiol (FES). Results: MRI allows for the identification of uterine fibroids when they exhibit good delineation and low intensity in T2-weighted images and DWI. Uterine sarcoma is characterized by moderate to high signal intensity on T2-weighted imaging, irregular borders, high signal intensity at high DWI values, and a decreased apparent diffusion coefficient. PET imaging with FDG and FES is a useful tool in differentiating uterine fibroids from sarcomas. Uterine sarcomas exhibit greater FDG uptake than smooth muscle fibroids, although cases of similar uptake do occur. On the other hand, FES provides information about estrogen receptors (ERs). Conclusions: Future research should focus on conducting standardized imaging studies, which would facilitate the inclusion of larger patient cohorts. This, in turn, would enable the development of specific diagnostic guidelines, ultimately leading to more accurate diagnoses and reducing the difficulty of differentiating these tumors through imaging. Full article

Background: Inflammatory arthritides (IAs) are systemic inflammatory syndromes that can affect diverse body tissues. Central nervous system involvement has been reported, but is considered rare. We investigated the relationship between cardiac and subclinical brain involvement in patients with IAs. Methods: We consecutively enrolled 25 patients with IAs and 31 as disease controls with non-autoimmune cardiovascular diseases (CVDs) reporting cardiac symptoms. Each participant underwent combined brain/heart magnetic resonance imaging (MRI). We also recruited 25 consecutive asymptomatic healthy controls without CVDs who underwent brain MRI. MRI scans were performed on a 1.5 T system. We investigated cardiac function/tissue characterization and the presence/localization of white matter hyperintensities (WMHs). Results: All groups had similar ages (p = 0.267), and 16 (64%) patients with IAs vs. 7 (23%) disease controls vs. 16 (64%) healthy controls were women (p = 0.001). WMHs were detected in ≥1 brain area in 15 (60%) patients with IAs and 16 (53%) disease controls (p = 0.620). WMHs were significantly less prevalent amongst healthy controls [two (8%)] compared to patients with IAs (p < 0.001). Amongst patients with IAs, an increased cardiac T2 ratio was associated with an increased probability of WMH occurrence [OR per 0.1 unit change (95% CI): 1.29 (1.05–1.59), p = 0.016], while a higher cardiac T2 ratio (per 0.1 unit change) and extracellular volume fraction (ECV) were associated with higher WMH lesion burdens [β (95% CI): 0.12 (0.03–0.20), p = 0.008 and 0.25 (0.00–0.49), p = 0.049, respectively]. Conclusions: Patients with IAs and cardiac symptoms had significantly higher subclinical WMH burdens compared to age/sex-matched healthy controls. Myocardial edema was associated with a greater WMH burden, potentially suggesting shared pathophysiologic substrates. Full article

(1) Background: Neoadjuvant chemotherapy (NAC) is an integral part of breast cancer management, and response to NAC is an important prognostic factor associated with improved survival outcomes. However, the current standard for response assessment relies on post-surgical histopathological analysis, which limits early therapeutic decision-making and treatment personalization. This study aimed to develop and evaluate a machine learning model that integrates pre-treatment MRI radiomics and clinical features to predict response to NAC in breast cancer patients. (2) Methods: In this study, a machine learning model was developed to predict breast cancer response to NAC using pre-treatment magnetic resonance imaging (MRI) radiomics and clinical data. Radiomic features were extracted from contrast-enhanced T1-weighted (CE-T1) and T2-weighted (T2) MRI sequences using both intratumoral and peritumoral segmentations. Furthermore, this study uniquely examined two response assessment criteria: (1) pathologic complete response (pCR) versus non-pCR, and (2) clinical response versus non-response. A total of 254 patients with biopsy-confirmed breast cancer who completed NAC were included. Radiomic features (n = 400) and clinical features (n = 7) were analyzed to build a predictive model employing the XGBoost classifier. Performance was measured in terms of accuracy, precision, sensitivity, specificity, F1-score, and AUC. (3) Results: The integration of radiomic features with clinical data significantly enhanced the predictive performance. For pCR and non-pCR prediction, the combined features model achieved an accuracy of 80% and AUC of 0.85, outperforming both the clinical features model (Accuracy = 68%, AUC = 0.81) and radiomic features model (Accuracy = 66%, AUC = 0.60). Similarly, for the clinical response and non-response prediction, the combined features model achieved an Accuracy of 74% and AUC of 0.75, outperforming both the clinical features model (Accuracy = 63%, AUC = 0.68) and radiomic features model (Accuracy = 66%, AUC = 0.57). (4) Conclusions: These findings highlight the synergistic effect of integrating clinical data and MRI-based radiomics to improve pre-treatment NAC response prediction, which has the potential to enable more precise and personalized treatment strategies. Full article

Goal: This study evaluates the feasibility and outcome of a personalized MRI-based liver SBRT treatment planning platform with the SPION contrast agent Ferumoxytol^® (Sandoz Inc.; Princeton, NJ, USA) to maintain a superior real-time visualization of liver tumors and volumes of functional hepatic parenchyma for radiotherapy planning throughout multi-fractionated liver SBRT with online plan adaptations on an Elekta Unity 1.5 T MR-Linac (Elekta; Stockholm, Sweden). Materials and Methods: Patients underwent SPION-enhanced MRI on the Elekta Unity MR-Linac for improved tumor and functional hepatic parenchyma visualization. An automated contouring algorithm was applied for the delineation and subsequent guided avoidance of functional liver parenchyma volumes (FLVs) on the SPION-enhanced MR-Linac. Radiation dose constraints were adapted exclusively to FLV. Local control, toxicity, and survival were assessed with at least 6-month radiographic follow-up. Pre- and post-transplant outcomes were analyzed in the subset of patients with HCC and hepatic cirrhosis who completed SBRT as a bridge to liver transplant. Model of End-Stage Liver Disease (MELD-Na) was used to score hepatic function before and after SBRT. Results: With a median follow-up of 23 months (range: 3–40 months), 23 HCC patients (26 lesions treated) and 9 patients (14 lesions treated) with hepatic metastases received SBRT (mean dose: 48 Gy, range: 36–54 Gy) in 1–5 fractions. Nearly all patients in this study had pe-existing liver conditions, including hepatic cirrhosis (23), prior TACE (7), prior SBRT (18), or history of hepatic resection (2). Compared to the non-contrast images, SPIONs improved tumor visibility on post-SPION images on the background of negatively enhancing functionally active hepatic parenchyma. Prolonged SPION-contrast retention within hepatic parenchyma enabled per-fraction treatment adaptation throughout the entire multi-fraction treatment course. FLV loss (53%, p < 0.0001) was observed in cirrhotic patients, but functional and anatomic liver volumes remained consistent in non-cirrhotic patients. Mean dose to FLV was maintained within the liver threshold tolerance to radiation in all patients after the optimization of Step-and-Shoot Intensity-Modulated Radiotherapy (SS-IMRT) on the SPION-enhanced MRI-Linac. No radiation-induced liver disease was observed within 6 months post-SBRT, and the MELD-Na score in cirrhotic patients was not significantly elevated at 3-month intervals after SBRT completion. Conclusions: SPION Ferumoxytol^® administered intravenously as an alternative MRI contrast agent on the day of SBRT planning produces a long-lasting contrast effect between tumors and functional hepatic parenchyma for precision targeting and guided avoidance during the entire course of liver SBRT, enabling fast and accurate online plan adaptation on the 1.5 T Elekta Unity MR-Linac. This approach demonstrates a safe and effective bridging therapy for patients with hepatic cirrhosis, leading to low toxicity and favorable transplant outcomes. Full article

The literature reports on radiofrequency (RF) transmit (Tx) elements tailored for ultrahigh-field (UHF) magnetic resonance imaging (MRI) showed confounded reproducibility due to variations in simulation tools, modeling assumptions, and meshing techniques. This study proposes a standardized methodology to improve reproducibility and consistency across research sites (testers) and simulation tools (testing conditions). The methodology includes detailed simulation workflow and performance metrics for RF Tx elements. The impact of the used mesh setting is assessed. Following the methodology, a reproducibility study was conducted using CST Microwave Studio Suite, HFSS, and Sim4Life. The methodology and simulations were ultimately validated through 7 T MRI phantom experiments. The reproducibility study showed consistent performance with less than 6% standard deviation for B₁⁺ fields and 12% for peak SAR averaged over 10 g tissue (pSAR_10g). The SAR efficiency metric (|B₁⁺|/√pSAR_10g) was particularly robust (<5%). The simulated and experimental |B₁⁺| maps showed good qualitative agreement. This study demonstrates the feasibility of a standardized methodology for achieving reproducible RF Tx element electromagnetic field simulations. By following the FAIR principles including making the framework publicly available, we promote transparency and collaboration within the MRI community, supporting the advancement of technological innovation and improving patient safety in UHF-MRI. Full article

Background: Breast reconstruction (BR) following mastectomy plays a critical role in restoring breast contour and improving patients’ quality of life. Acellular dermal matrices (ADMs) have emerged as valuable adjuncts in BR, providing structural support and enhancing soft tissue integration. However, their radiological characteristics remain underexplored, leading to potential misinterpretation and diagnostic challenges. This study aims to evaluate the imaging features of ADM in post-mastectomy patients using conventional imaging modalities, identifying its temporal evolution and clinical implications for radiologists and surgeons. Materials and Methods: This single-centre retrospective study included breast cancer patients who underwent mastectomy followed by ADM-assisted BR. Patients were monitored using standardised radiological follow-up protocols, including digital mammography (DM) and ultrasound (US), at 6 (T0), 12 (T1), and 18 months (T2) postoperatively. The primary outcomes assessed were the presence and evolution of ADM-related imaging findings, differentiation between normal ADM integration and pathological changes, and the role of different imaging modalities in ADM evaluation. Results: Sixty-three patients met the inclusion criteria and underwent radiological follow-up. At T0, ADM was identified in 16% of cases, primarily as a peri-capsular hypoechoic thickening on US and a linear peri-implant density on DM. At T1, these findings were partially resolved, with 11% of cases still displaying peri-capsular changes. By T2, imaging signs of ADM were further reduced, with only 7% of cases showing residual peri-capsular thickening or pseudonodular formations. No ADM-related complications, graft rejection, or implant loss were detected. These findings suggest a progressive integration of ADM into the host tissue over time, with characteristic imaging changes that must be recognised to avoid misdiagnosis or unnecessary interventions. Conclusions: ADM exhibits a dynamic radiological evolution in post-mastectomy BR, with its imaging characteristics gradually fading. Recognising these features is critical for radiologists and surgeons to ensure accurate interpretation and optimised patient management. A structured imaging follow-up protocol, incorporating US as the primary modality and MRI in cases of inconclusive findings, is recommended to improve diagnostic accuracy. Future multicentre studies with extended follow-up and advanced imaging techniques are necessary to refine radiological criteria and further explore ADM integration patterns. A multidisciplinary approach is essential to enhance clinical decision-making, reduce unnecessary interventions, and optimise patient outcomes in ADM-assisted BR. Full article

Background/Objectives: Interest in diversity is growing worldwide. Today, an understanding and social acceptance of diverse people is becoming increasingly important. Therefore, in this study, we aimed to clarify the relationship between an individual’s gray matter volume (GMV), which is thought to reflect brain health, and their understanding of diversity (gender, sexuality (LGBTQ), and origin). Methods: GMV was determined as the value of the Gray Matter Brain Healthcare Quotient (GM-BHQ) based on MRI image analysis. Meanwhile, participants’ understanding and acceptance of diversity was calculated based on their answers to the psychological questions included in the World Values Survey Wave 7 (WVS7). Results: Our analysis indicated that, in the group of participants with the highest understanding of diversity (PHUD. n = 11), not only the GMV at the whole brain level (t = 2.587, p = 0.027, Cohen’s d = 0.780) but also the GMV of the central executive network (CEN: t = 2.700, p= 0.022, Cohen’s d = 0.814) and saliency network (SN: t = 3.100, p = 0.011, Cohen’s d = 0.935) were shown to be significantly higher than the theoretical value estimated from sex, age, and BMI at the 5% level. In addition, the GMV of the default mode network (DMN: t = 2.063, p = 0.066, Cohen’s d = 0.622) was also higher than the theoretical value at the 10% level. Meanwhile, in the group of others (n = 10), there was no significant difference from the theoretical value. These differences between PHUD and others were also observed when comparing the two with and without controlling for educational and occupational covariates at the 5% or 10% levels. Conclusions: These results suggest that understanding diversity requires a healthy brain, centered on three networks that govern rational judgment, emotion regulation, other-awareness, self-awareness, and the valuing of actions. This is the first study to show that brain structure is related to an understanding and acceptance of the diversity of people. Full article

Background/Objectives: Diabetes-related pancreatic changes on MRI remain unclear. Thus, we evaluated the pancreatic changes on MRI in patients with both type 1 diabetes (T1D) and type 2 diabetes (T2D) using multiparametric MRI. Methods: This prospective study involved patients with T1D or T2D who underwent upper abdominal 3-T MRI. Additionally, patients without impaired glucose metabolism were retrospectively included as a control. The imaging data included pancreatic anteroposterior (AP) diameter, pancreas-to-muscle signal intensity ratio (SIR) on fat-suppressed T1-weighted image (FS-T1WI), apparent diffusion coefficient (ADC) value, T1 value on T1 map, proton density fat fraction (PDFF), and mean secretion grade of pancreatic juice flow on cine-dynamic magnetic resonance cholangiopancreatography (MRCP). The MR measurements were compared using one-way analysis of variance and the Kruskal–Wallis test. Results: Sixty-one patients with T1D (n = 7) or T2D (n = 54) and 21 control patients were evaluated. The pancreatic AP diameters were significantly smaller in patients with T1D than in patients with T2D (p < 0.05). The average SIR on FS-T1WI was significantly lower in patients with T1D than in controls (p < 0.001). The average ADC and T1 values of the pancreas were significantly higher in patients with T1D than in patients with T2D (p < 0.01) and controls (p < 0.05). The mean secretion grade of pancreatic juice flow was significantly lower in patients with T1D than in controls (p = 0.019). The average PDFF of the pancreas was significantly higher in patients with T2D than in controls (p = 0.029). Conclusions: Patients with T1D had reduced pancreas size, increased pancreatic T1 and ADC values, and decreased pancreatic juice flow on cine-dynamic MRCP, whereas patients with T2D had increased pancreatic fat content. Full article

Objectives: We wished to compare the diagnostic performance of texture analysis (TA) against that of a visual qualitative assessment in identifying early sacroiliitis (nr-axSpA). Methods: A total of 92 participants were retrospectively included at our university hospital institution, comprising 30 controls and 62 patients with axSpA, including 32 with nr-axSpA and 30 with r-axSpA, who underwent MR examination of the sacroiliac joints. MRI at 3T of the lumbar spine and the sacroiliac joint was performed using oblique T1-weighted (W), fluid-sensitive, fat-saturated (Fs) T2WI images. The modified New York criteria for AS were used. Patients were classified into the nr-axSpA group if their digital radiography (DR) and/or CT results within 7 days from the MR examination showed a DR and/or CT grade < 2 for the bilateral sacroiliac joints or a DR and/or CT grade < 3 for the unilateral sacroiliac joint. Patients were classified into the r-axSpA group if their DR and/or CT grade was 2 to 3 for the bilateral sacroiliac joints or their DR and/or CT grade was 3 for the unilateral sacroiliac joint. Patients were considered to have a confirmed diagnosis if their DR or CT grade was 4 for the sacroiliac joints and were thereby excluded. A control group of healthy individuals matched in terms of age and sex to the patients was included in this study. First, two readers independently qualitatively scored the oblique coronal T1WI and FsT2WI non-enhanced sacroiliac joint images. The diagnostic efficacies of the two readers were judged and compared using an assigned Likert score, conducting a Kappa consistency test of the diagnostic results between two readers. Texture analysis models (the T1WI-TA model and the FsT2WI-TA model) were constructed through feature extraction and feature screening. The qualitative and quantitative results were evaluated for their diagnostic performance and compared against a clinical reference standard. Results: The qualitative scores of the two readers could significantly distinguish between the healthy controls and the nr-axSpA group and the nr-axSpA and r-axSpA groups (both p < 0.05). Both TA models could significantly distinguish between the healthy controls and the nr-axSpA group and the nr-axSpA group and the r-axSpA group (both p < 0.05). There was no significant difference in the differential diagnoses of the two TA models between the healthy controls and the nr-axSpA group (AUC: 0.934 vs. 0.976; p = 0.1838) and between the nr-axSpA and r-axSpA groups (AUC: 0.917 vs. 0.848; p = 0.2592). In terms of distinguishing between the healthy control and nr-axSpA groups, both the TA models were superior to the qualitative scores of the two readers (all p < 0.05). In terms of distinguishing between the nr-axSpA and r-axSpA groups, the T1WI-TA model was superior to the qualitative scores of the two readers (p = 0.023 and p = 0.007), whereas there was no significant difference between the fsT2WI-TA model and the qualitative scores of the two readers (p = 0.134 and p = 0.065). Conclusions: Based on MR imaging, the T1WI-TA and fsT2WI-TA models were highly effective for the early diagnosis of sacroiliac joint arthritis. The T1WI-TA model significantly improved the early diagnostic efficacy for sacroiliac arthritis compared to that of the qualitative scores of the readers, while the efficacy of the fsT2WI-TA model was comparable to that of the readers. Full article

Background/Objectives: Cartilage injuries and osteoarthritis are prevalent public health problems, due to their disabling nature and economic impact. Mesenchymal stromal cells (MSCs) isolated from different tissues have the immunomodulatory capacity to regulate local joint environment. This translational study aims to compare cartilage restoration from MSCs from the synovial membrane (SM) and dental pulp (DP) by a tissue-engineered construct with Good Manufacturing Practices. Methods: A controlled experimental study was conducted on fourteen miniature pigs, using scaffold-free Tissue Engineering Constructs (TECs) from DP and SM MSCs, with a 6-month follow-up. Total thickness cartilage defects were created in both hind knees; one side was left untreated and the other received a TEC from either DP (n = 7) or SM (n = 7). An MRI assessed the morphology using the MOCART scoring system, T2 mapping evaluated water, and collagen fiber composition, and histological analysis was performed using the ICRS-2 score. Results: The untreated group had a mean MOCART value of 46.2 ± 13.4, while the SM-treated group was 65.7 ± 15.5 (p < 0.05) and the DP-treated group was 59.0 ± 7.9 (n.s.). The T2 mapping indicated a mean value of T2 of 54.9 ± 1.9 for native cartilage, with the untreated group at 50.9 ± 2.4 (p < 0.05). No difference was found between the T2 value of native cartilage and the treated groups. The ICRS-2 mean values were 42.1 ± 14.8 for the untreated group, 64.3 ± 19.0 for SM (p < 0.05), and 54.3 ± 12.2 for DP (n.s.). Conclusion: MRI and histological analysis indicated that TEC treatment led to superior cartilage coverage and quality compared to the defect group. TECs from SM demonstrated better results than the defect group in the histological assessment. Full article

The implementation of clinical 7T MRI presents both opportunities and challenges for advanced medical imaging. This tutorial provides practical considerations and experiences with 7T MRI in clinical settings. We first explore the history and evolution of MRI technology, highlighting the benefits of increased signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and susceptibility at 7T. Technical challenges such as increased susceptibility artifacts and RF inhomogeneity are also discussed, along with innovative adaptations. This review also discusses hardware and software considerations, including new parallel transmission head coils and advanced image processing techniques to optimize image quality. Safety considerations, such as managing tissue heating and susceptibility to artifacts, are also discussed. Additionally, clinical applications of 7T MRI are examined, focusing on neurological conditions such as epilepsy, multiple sclerosis, and vascular imaging. Emerging trends in the use of 7T MRI for spectroscopy, perfusion imaging, and multinuclear imaging are explored, with insights into the future of ultra-high-field MRI in clinical practice. This review aims to provide clinicians, technologists, and researchers with a roadmap for successfully implementing 7T MRI in both research and clinical environments. Full article

Introduction. Post-coronavirus disease-2019 (COVID-19) patients may develop cardiac symptoms. We hypothesized that cardiovascular magnetic resonance (CMR) can assess the background of post-COVID-19 cardiac symptoms using multi-parametric evaluation. We aimed to conduct an investigation of symptomatic patients with post-COVID-19 syndrome using CMR (INSPIRE-CMR). Methods. INSIPRE-CMR is a retrospective multicenter study including 174 patients from five centers referred for CMR due to cardiac symptoms. CMR was performed using 3.0 T/1.5 T system (24%/76%, respectively). Myocardial inflammation was determined by the updated Lake Louise criteria. Results. Further, 174 patients with median age of 40 years (IQR: 26–54), 72 (41%) were women, and 17 (9.7%) had a history of autoimmune disease, muscular dystrophy, or cancer. In total, 149 (86%) patients were late gadolinium enhanced (LGE)-positive with a non-ischemic pattern, and of those evaluated with the updated Lake Louise criteria, 141/145 (97%) had ≥1 pathologic T1 index. Based on the T2-criterion, 62/173 (36%) patients had ≥1 pathologic T2 index. Collectively, 48/145 (33%) patients had both positive T1- and T2-criterion. A positive T2-criterion or a combination of a positive T1- and T2-criterion were significantly more common amongst patients with severe COVID-19 [45 (31%) vs. 17 (65%), p = 0.001 and 32 (27%) vs. 16 (64%), p < 0.001, respectively]. During the one-year evaluation, available for 65/174 patients, shortness of breath, chest pain, and arrhythmia were identified in 7 (4%), 15 (8.6%), and 43 (24.7%), respectively. CMR evaluation, available in a minority of them, showed mildly reduced LVEF, while nat T1 mapping and EVC remained at levels higher than the normal values of the local MRI units. Conclusions. The majority of post-COVID-19 patients with cardiac symptoms presented non-ischemic LGE and abnormalities in T1 and T2-based indices. Multi-parametric CMR reveals important information on post-COVID-19 patients, supporting its role in short/long-term evaluation. Full article