Search Results (86)

Background/Objectives: Spontaneous intracranial hypotension (SIH), caused by spinal cerebrospinal fluid (CSF) leakage, commonly presents with orthostatic headache and CSF hypovolemia. While CSF dynamics in the cerebral aqueduct are well studied, alterations in spinal CSF flow remain less defined. We aimed to quantitatively assess spinal CSF flow at C2 using phase-contrast (PC) MRI enhanced by artificial intelligence (AI) and to evaluate its utility for diagnosing SIH and predicting responses to epidural blood patch (EBP). Methods: We enrolled 31 patients with MRI-confirmed SIH and 26 age- and sex-matched healthy volunteers (HVs). All participants underwent ECG-gated cine PC-MRI at the C2 level and whole-spine MR myelography. AI-based segmentation using YOLOv4 and a pulsatility-based algorithm was used to extract quantitative CSF flow metrics. Between-group comparisons were analyzed using Mann–Whitney U tests, and receiver operating characteristic (ROC) analysis was used to evaluate diagnostic and predictive performance. Results: Compared to HVs, SIH patients showed significantly reduced CSF flow parameters across all metrics, including upward/downward mean flow, peak flow, total flow per cycle, and absolute stroke volume (all p < 0.001). ROC analysis revealed excellent diagnostic accuracy for multiple parameters, particularly downward peak flow (AUC = 0.844) and summation of peak flow (AUC = 0.841). Importantly, baseline CSF flow metrics significantly distinguished patients who required one versus multiple epidural blood patches (EBPs) (all p < 0.001). ROC analysis demonstrated that several parameters achieved near-perfect to perfect accuracy in predicting EBP success, with AUCs up to 1.0 and 100% sensitivity/specificity. Conclusions: AI-enhanced PC-MRI enables the robust, quantitative evaluation of spinal CSF dynamics in SIH. These flow metrics not only differentiate SIH patients from healthy individuals but also predict response to EBP treatment with high accuracy. Quantitative CSF flow analysis may support both diagnosis and personalized treatment planning in SIH. Full article

Background/Objectives: Attention Deficit Hyperactivity Disorder (ADHD) is a common neurodevelopmental disorder frequently associated with other neuropsychiatric conditions, characterized by high clinical heterogeneity and a complex genetic background. Recent studies suggest that copy number variations (CNVs) may contribute to ADHD susceptibility, particularly when involving genes related to brain development, attention regulation, and impulse control. This study investigated the association between CNVs and ADHD phenotype by identifying patients with and without potential pathogenic CNVs. Methods: We evaluated 152 well-characterized ADHD pediatric patients through comprehensive clinical assessments, including dysmorphic features, brain MRI, EEG patterns, and cognitive testing. CNVs were identified using array Comparative Genomic Hybridization (array-CGH). Participants were classified as carrying potentially causative CNVs (PC-CNVs), non-causative CNVs (NC-CNVs), or without CNVs (W-CNVs) and statistically compared across clinical and neurodevelopmental measures. Results: CNVs were identified in 81 participants (53%), comprising 13 with PC-CNVs (8.5%) and 68 with NC-CNVs (44.7%). ADHD symptoms were pronounced across all groups, but PC-CNVs showed a higher burden of comorbidities, suggesting a stronger genetic contribution to ADHD complexity. Significant differences were observed in oppositional behavior, inattentive symptoms, brain MRI findings, and developmental language anomalies. Several CNVs involved genes previously implicated in neurodevelopmental disorders, supporting a potential genetic contribution to the clinical complexity of ADHD. Conclusions: This exploratory study supports the role of CNVs in ADHD susceptibility and highlights the value of genetic screening for understanding clinical variability. Larger studies are needed to clarify genotype–phenotype correlations in ADHD and to guide personalized clinical management. 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

In prostate cancer (PCa) surgery, precise tumor margin identification remains challenging despite advances in surgical techniques. This study evaluates the combination of tumor-specific near-infrared imaging with the PSMA-targeting molecule PSMA-914 and optical endomicroscopy (NIR-pCLE) for single-cell-level tumor identification in a preclinical proof of concept. Methods: NIR-pCLE imaging of varying PSMA-914 concentrations was performed on PSMA-positive LNCaP and PSMA-negative PC-3 cells using Cellvizio^® 100 with pCLE Confocal Miniprobes™. To identify optimal PSMA-914 dosing for in vivo imaging, different doses (0–10 nmol) were evaluated using NIR-pCLE, Odyssey CLx imaging, and confocal microscopy in an LNCaP tumor-bearing xenograft model. A proof of concept mimicking a clinical workflow was performed using 5 nmol [⁶⁸Ga]Ga-PSMA-914 in LNCaP and PC-3 tumor xenografts, including PET/MRI, in/ex vivo NIR-pCLE imaging, and microscopic/macroscopic imaging. Results: NIR-pCLE detected PSMA-specific fluorescence at concentrations above 30 nM in vitro. The optimal dose was identified as 5 nmol PSMA-914 for NIR-pCLE imaging with cellular resolution in LNCaP xenografts. PET/MRI confirmed high tumor uptake and a favorable distribution profile of PSMA-914. NIR-pCLE imaging enabled real-time, single-cell-level detection of PSMA-positive tissue, visualizing tumor heterogeneity, confirmed by ex vivo microscopy and imaging. Conclusions: This preclinical proof of concept demonstrates the potential of intraoperative PSMA-specific NIR-pCLE imaging to visualize tissue structures in real time at cellular resolution. Clinical implementation could provide surgeons with valuable additional information, potentially advancing PCa patient care through improved surgical precision. Full article

While multi-parametric magnetic resonance imaging (mpMRI) is known to be a specific and reliable modality for the diagnosis of non-metastatic prostate cancer (PC), positron emission tomography (PET) using ⁶⁸Ga labeled ligands targeting the prostate-specific membrane antigen (PSMA) is known for its reliable detection of prostate cancer, being the most sensitive modality for the assessment of the extra-prostatic extension of the disease and the establishment of a diagnosis, even before biopsy. Background/Objectives: Here, we compared these modalities in regards to the localization of intraprostatic cancer lesions prior to local HDR brachytherapy. Methods: A cohort of 27 patients received both mpMRI and PSMA-PET/CT. Based on 24 intraprostatic segments, two readers each scored the risk of tumor-like alteration in each imaging modality. The detectability was evaluated using receiver operating characteristic (ROC) analysis. The histopathological findings from biopsy were used as the gold standard in each segment. In addition, we applied a patient-based “congruence” concept to quantify the interobserver and intermodality agreement. Results: For the ROC analysis, we included 447 segments (19 patients), with their respective histological references. The two readers of the MRI reached an AUC of 0.770 and 0.781, respectively, with no significant difference (p = 0.75). The PET/CT readers reached an AUC of 0.684 and 0.608, respectively, with a significant difference (p < 0.001). The segment-wise intermodality comparison showed a significant superiority of MRI (AUC = 0.815) compared to PET/CT (AUC = 0.690) (p = 0.006). Via a patient-based analysis, a superiority of MRI in terms of relative agreement with the biopsy result was observed (n = 19 patients). We found congruence scores of 83% (MRI) and 76% (PET/CT, p = 0.034), respectively. Using an adjusted “near total agreement” score (adjacent segments with positive scores of 4 or 5 counted as congruent), we found an increase in the agreement, with a score of 96.5% for MRI and 92.7% for PET/CT, with significant difference (p = 0.024). Conclusions: This study suggests that in a small collective of low-/intermediate risk prostate cancer, mpMRI is superior for the detection of intraprostatic lesions as compared to PSMA-PET/CT. We also found a higher relative agreement between MRI and biopsy as compared to that for PET/CT. However, further studies including a larger number of patients and readers are necessary to draw solid conclusions. Full article

Objective: Cerebral vascularization is made of the symmetrical arterial system, with muscular walls, and the venous system, more variable and dominated by sinuses and jugular veins. Factors like age and posture influence this network, complicating its study. Phase-contrast MRI is the gold standard for quantifying cerebral circulation. This study aimed to quantify the dynamics of the cerebral blood system using PC-MRI. Materials and Methods: Thirty-six healthy adults participated. Imaging was performed on a 3T MRI (Philips Achieva) in a supine position. Two slices were acquired: intracranial and extracranial. In-house software analyzed flow curves over a cardiac cycle. Each vessel’s contribution was evaluated. Results: Extracranial venous drainage was categorized as jugular-dominant, equivalent, or peripheral-dominant. A similar classification applied intracranially. Intracranial flows showed low variability (5–9%), while extracranial venous flows, especially in the internal jugular veins, had higher variability (17–21%). Some extracranial veins were absent. Conclusions: There is significant venous heterogeneity in the extracranial region. PC-MRI enables the quantification of cerebral dynamics. Full article

Applications of lanthanide chemistry have been successful in metallics and the petroleum industry. In the medical realm, lanthanides have shown utility in radiotherapy agents, photodynamic therapy agents, and magnetic resonance imaging (MRI) contrast agents. The lanthanide group elements have a few known biological roles, notably among some bacteria and the yeast Saccharomyces cerevisiae, which have been used as models for changes in gene expression. However, the systematic effects of lanthanide nitrates on eukaryotic cell model systems have not yet been reported. This study presents the first documented effects on cell viability, after acute incubations of various lanthanide nitrate salts, using axenic C6 glial or PC12 neuronal cells in vitro. Cultures were exposed to a 1 mM concentration of lanthanide nitrate salts for 24 h. In comparison to the saline control, several cultures demonstrated significantly lower cell viability, as measured by the MTT viability assay. Data were analyzed as an average absorbance of n = 4 replicate samples, corrected for the average absorbance of cell-free blanks. The reported results were normalized to the average of the saline control cells. Among the 13 lanthanides tested, Praseodymium, Holmium, Erbium, Thulium, and Ytterbium nitrates exhibited the most pronounced inhibitory effects, resulting in over 40% reduction in cell viability at 1 mM for either or both cell types. Recovery after lanthanide exposure also was cell-type-dependent as well as lanthanide-type-dependent, with Lutetium having the greatest effect on both cell types. PC12 cells displayed greater sensitivity for inhibition than the C6 cells with some of the lanthanides but not all. Furthermore, the controls of sodium nitrate and calcium nitrate showed only modest discernible impacts on cell viability for PC12 and C6 cells, highlighting the role of the lanthanides in influencing cell viability. Full article

Preclinical studies have shown that progenitor cells (PCs) are mobilized toward injured tissues to ameliorate damage and contribute to regeneration. The exogenous therapeutic administration of PCs in children affected by neonatal encephalopathy (NE) is a promising, yet underreported, topic. In this prospective study, we investigated whether endogenous circulating progenitor cells (CPCs) are involved in intrinsic regeneration mechanisms following neonatal brain injury. Thirteen full-term infants with moderate/severe NE, eleven with perinatal stress, and twelve controls were enrolled. Blood samples were collected on days 1, 3, 9, 18, and 45, as well as at 8 and 24 months of life, and were analyzed with a focus on Endothelial Progenitor Cells, Haematopoietic Stem Cells, and Very Small Embryonic-Like Stem Cells, in addition to chemotactic factors (erythropoietin, IGF-1, and SDF-1). Correlations between CPCs, chemotactic factors, and brain injury were assessed using serum levels of brain injury biomarkers (S100B and neuron-specific enolase), brain MRIs, and Bayley III developmental scores. Increased brain injury biomarkers were followed by the upregulation of SDF-1 receptor and erythropoietin and, finally, by elevated CPCs. These findings suggest a potential endogenous regenerative effort, primarily observed in the moderate encephalopathy group, but this is suppressed in cases of severe brain injury. Mimicking and enhancing endogenous regeneration pathways in cases of failure—regarding cell type and timeframe—could provide a novel therapeutic model. Full article

Background: Prostate cancer management optimally requires non-invasive, objective, quantitative, accurate evaluation of prostate tumors. The current research applies visual inspection and quantitative approaches, such as artificial intelligence (AI) based on deep learning (DL), to evaluate MRI. Recently, a different spectral/statistical approach has been used to successfully evaluate spatially registered biparametric MRIs for prostate cancer. This study aimed to further assess and improve the spectral/statistical approach through benchmarking and combination with AI. Methods: A zonal-aware self-supervised mesh network (Z-SSMNet) was applied to the same 42-patient cohort from previous spectral/statistical studies. Using the probability of clinical significance of prostate cancer (PCsPCa) and a detection map, the affiliated tumor volume, eccentricity was computed for each patient. Linear and logistic regression were applied to the International Society of Urological Pathology (ISUP) grade and PCsPCa, respectively. The R, p-value, and area under the curve (AUROC) from the Z-SSMNet output were computed. The Z-SSMNet output was combined with the spectral/statistical output for multiple-variate regression. Results: The R (p-value)–AUROC [95% confidence interval] from the Z-SSMNet algorithm relating ISUP to PCsPCa is 0.298 (0.06), 0.50 [0.08–1.0]; relating it to the average blob volume, it is 0.51 (0.0005), 0.37 [0.0–0.91]; relating it to total tumor volume, it is 0.36 (0.02), 0.50 [0.0–1.0]. The R (p-value)–AUROC computations showed a much poorer correlation for eccentricity derived from the Z-SSMNet detection map. Overall, DL/AI showed poorer performance relative to the spectral/statistical approaches from previous studies. Multi-variable regression fitted AI average blob size and SCR results at a level of R = 0.70 (0.000003), significantly higher than the results for the univariate regression fits for AI and spectral/statistical approaches alone. Conclusions: The spectral/statistical approaches performed well relative to Z-SSMNet. Combining Z-SSMNet with spectral/statistical approaches significantly enhanced tumor grade prediction, possibly providing an alternative to current prostate tumor assessment. Full article

Background: Evidence to help avoid unnecessary prostate biopsies is being actively pursued. Our goal was to develop and internally validate a nomogram for predicting clinically significant prostate cancer (csPC) in men with low suspicion of disease (prostate specific antigen [PSA] < 10 ng/mL, normal digital rectal examination [DRE]), in whom magnetic resonance imaging (MRI) findings are positive. Methods: Patients with no prior prostate cancer diagnosis who underwent MRI–ultrasound fusion biopsy of the prostate were retrospectively analyzed. Inclusion criteria were PSA < 10 ng/mL, normal DRE, Prostate Imaging Reporting And Data System (PIRADS) category ≥ 3, and no extraprostatic extension or seminal vesicle invasion reported on MRI. Associations between csPC diagnosis and patient or lesion characteristics were analyzed, and a multivariable model was developed. Internal validation of the model with 5-fold cross-validation and bootstrapping methods was performed. Results: Among 209 patients, 67 were diagnosed with csPC. Factors incorporated into the model for predicting csPC were age, 5-alpha reductase inhibitor use, PSA, prostate volume, PIRADS > 3, and lesion location in the peripheral zone. The model’s ROC AUC was 0.86, with consistent performance at internal validation (0.84 with cross-validation, 0.82 with bootstrapping). With an empirical threshold of <10% csPC probability to omit biopsy, 72 (50.7%) unnecessary biopsies would have been avoided, at the cost of missing 2 (3.0%) csPC cases. Conclusions: Our nomogram might serve as a valuable tool in refining selection criteria in men considered for prostate biopsy. The major limitation of the study is its retrospective character. Prospective, external validation of the model is warranted. Full article

(1) Background: Alterations in brain functional connectivity (FC) precede clinical symptoms of Alzheimer’s disease (AD) by decades, presenting opportunities for early diagnosis. However, conventional FC analyses measure correlations between brain regions and do not provide insights into directional, causal interactions. Causal functional connectivity (CFC), which infers directed interactions between regions, addresses this limitation. This study aims to identify disrupted CFC networks in AD compared to cognitively normal (CN) individuals. (2) Methods: The recently developed Time-aware PC (TPC) algorithm was employed to infer directed CFC from functional magnetic resonance imaging (fMRI) data. These results were compared with traditional correlation-based FC obtained via sparse partial correlation. Network-based Statistics (NBS) for directed networks was used to identify altered CFC sub-networks, with corrections for multiple comparisons applied at the 5% significance level. (3) Results: Key causal networks, including the inferior frontal gyrus, superior temporal gyrus, middle temporal gyrus, and cerebellum, showed significantly reduced strength in AD compared to CN (p = 0.0299; NBS corrected). Instead of detecting disruptions at the level of individual edges, this study identifies network-level alterations, revealing systemic disruptions in brain connectivity. (4) Conclusions: This study demonstrates the utility of CFC analysis in uncovering network-level disruptions in AD. The identified disrupted networks align with published medical literature and provide a framework for future studies with larger datasets. Full article

In amyloid brain PET, after parcellation using the finite element method (FEM)-based algorithm FreeSurfer and voxel-based algorithm PMOD, SUVr examples can be extracted and compared. This study presents the classification SUVr threshold in PET images of F-18 florbetaben (FBB), F-18 flutemetamol (FMM), and F-18 florapronol (FPN) and compares and analyzes the classification performance according to computational algorithm in each brain region. PET images were co-registered after the generated MRI was registered with standard template information. Using MATLAB script, SUVr was calculated using the built-in parcellation number labeled in the brain region. PMOD and FreeSurfer with different algorithms were used to load the PET image, and after registration in MRI, it was normalized to the MRI template. The volume and SUVr of the individual gray matter space region were calculated using an automated anatomical labeling atlas. The SUVr values of eight regions of the frontal cortex (FC), lateral temporal cortex (LTC), mesial temporal cortex (MTC), parietal cortex (PC), occipital cortex (OC), anterior and posterior cingulate cortex (GCA, GCP), and composite were calculated. After calculating the correlation of SUVr using the FreeSurfer and PMOD algorithms and calculating the AUC for amyloid-positive/negative subjects, the classification ability was calculated, and the SVUr threshold was calculated using the Youden index. The correlation coefficients of FreeSurfer and PMOD SUVr calculations of the eight regions of the brain cortex were FBB (0.95), FMM (0.94), and FPN (0.91). The SUVr threshold was SUVr(LTC,min) = 1.264 and SUVr(THA,max) = 1.725 when calculated using FPN-FreeSurfer, and SUVr(MTC,min) = 1.093 and SUVr(MCT,max) = 1.564 when calculated using FPN-PMOD. The AUC comparison showed that there was no statistically significant difference (p > 0.05) in the SUVr classification results using the three radiopharmaceuticals, specifically for the LTC and OC regions in the PMOD analysis, and the LTC and PC regions in the FreeSurfer analysis. The SUVr calculation using PMOD (voxel-based algorithm) has a strong correlation with the calculation using FreeSurfer (FEM-based algorithm); therefore, they complement each other. Quantitative classification analysis with high accuracy is possible using the suggested SUVr threshold. The SUVr classification performance was good in the order of FMM, FBB, and FPN, and showed a good classification performance in the LTC region regardless of the type of radiotracer and analysis algorithm. Full article

Introduction: Popliteal cysts (PCs) are occasionally accompanied by knee osteoarthritis (OA) and varus malalignment. However, whether concomitant arthroscopic excision of PCs with medial open-wedge high tibial osteotomy (MOWHTO) improves the osteoarthritic environment remains unclear. Therefore, this study assessed serial changes in C-size, medial meniscus extrusion (MME), and cartilage status for up to 2 years following an MOWHTO. Methods: This study retrospectively used serial magnetic resonance imaging (MRI) evaluations to assess 26 consecutive patients who underwent MOWHTO. Of the 26 patients, six with preoperative PCs were included. Based on the arthroscopic findings at the time of the MOWHTO, concomitant meniscal and chondral lesions, and whether or not partial meniscectomy was performed, were evaluated. All patients underwent second-look arthroscopy with plate removal 2 years postoperatively. The PC size, MME, and cartilage sub-scores in the medial compartment of the whole-organ MRI score (WORMS) were assessed by serial MRI preoperatively and at 3, 6, 18, and 24 months postoperatively. The recurrence of PCs and clinical outcomes, including the Rauschning–Lindgren grade, were also evaluated when serial MRI was performed. Moreover, changes in cartilage status were assessed using two-stage arthroscopy. Results: All patients underwent concomitant partial meniscectomy for medial meniscal tears in the posterior horn. A significant decrease in the mean size of preoperative PCs (27.4 ± 22.3 mm) was noted from 3 months postoperatively (8.7 ± 7.6 mm, p = 0.018), and thereafter. The mean size of PCs further decreased with time until 2 years (1.5 ± 4.0 mm, p = 0.018) following an MOWHTO with partial meniscectomy. Moreover, significant improvements in the MME and WORMS values were noted from 3 to 24 months postoperatively. Meanwhile, no PC recurrence occurred during the follow-up period and the preoperative Rauschning–Lindgren grade improved significantly with time after MOWHTO (p = 0.026). Furthermore, the two-stage arthroscopic assessments showed significant improvements in ICRS grade in the medial femoral condyle (p = 0.038). Conclusions: After an MOWHTO with partial meniscectomy, PCs decreased with time up to 2 years postoperatively; no recurrence occurred during the follow-up period, although cyst excision was not concomitantly performed. Furthermore, the reduction in PCs corresponded with improvements in MME and chondral lesions in the knee joint following the MOWHTO. Full article

Focal therapy offers a promising approach for treating localized prostate cancer (PC) with minimal invasiveness and potential cost benefits. High-intensity focused ultrasound (HIFU) and brachytherapy (BT) are among these options but lack long-term efficacy data. Patient follow-ups typically use biopsies and multiparametric MRI (mpMRI), which often miss recurrences. PET/CT with PSMA has emerged as a promising tool for detecting residual disease or recurrence post-treatment, offering higher sensitivity and specificity than traditional imaging. We retrospectively reviewed patients who underwent [⁶⁸Ga]Ga-PSMA-11 PET/CT for biochemical recurrence (BCR) after HIFU or brachytherapy from 2016 to 2024. Out of 22 patients, 32% had HIFU and 68% had brachytherapy. The median time from treatment to PET scan was 77 months, with a median PSA level of 3 ng/mL. [⁶⁸Ga]Ga-PSMA-11 PET/CT identified PC recurrence in 63.6% of cases. Of these, 50% showed prostate recurrence, 14% had lymph node involvement, and 28% had metastatic disease. Focal therapies like HIFU and brachytherapy are effective and minimally invasive options for localized PC. [⁶⁸Ga]Ga-PSMA-11 PET/CT is valuable for detecting recurrence or residual disease, enhancing post-treatment surveillance. Full article

Background: Accurate measurements of flow and ventricular volume and function are critical for clinical decision-making in cardiovascular medicine. Cardiac magnetic resonance (CMR) is the current gold standard for ventricular functional evaluation but is relatively expensive and time-consuming, thus limiting the scale of clinical applications. New volumetric acquisition techniques, such as four-dimensional flow (4D-flow) and three-dimensional volumetric cine (3D-cine) MRI, could potentially reduce acquisition time without loss in accuracy; however, this has not been formally tested on a large scale. Methods: 4DCarE (4D-flow MRI for cardiovascular evaluation) is a prospective, multi-centre study designed to test the non-inferiority of a compressed 20 min exam based on volumetric CMR compared with a conventional CMR exam (45–60 min). The compressed exam utilises 4D-flow together with a single breath-hold 3D-cine to provide a rapid, accurate quantitative assessment of the whole heart function. Outcome measures are (i) flow and chamber volume measurements and (ii) overall functional evaluation. Secondary analyses will explore clinical applications of 4D-flow-derived parameters, including wall shear stress, flow kinetic energy quantification, and vortex analysis in large-scale cohorts. A target of 1200 participants will enter the study across three sites. The analysis will be performed at a single core laboratory site. Pilot Results: We present a pilot analysis of 196 participants comparing flow measurements obtained by 4D-flow and conventional 2D phase contrast, which demonstrated moderate–good consistency in ascending aorta and main pulmonary artery flow measurements between the two techniques. Four-dimensional flow underestimated the flow compared with 2D-PC, by approximately 3 mL/beat in both vessels. Conclusions: We present the study protocol of a prospective non-inferiority study of a rapid cardiac MRI exam compared with conventional CMR. The pilot analysis supports the continuation of the study. Study Registration: This study is registered with the Australia and New Zealand Clinical Trials Registry (Registry number ACTRN12622000047796, Universal Trial Number: U1111-1270-6509, registered 17 January 2022—Retrospectively registered). Full article