Turbo Spin-echo Sequence Research Articles

Placental Area in the Lower Uterine Segment, Cervical Length, and Clinical Outcome in Pregnancies With Complete Placenta Previa.

Complete placenta previa is associated with a higher percentage of adverse clinical outcomes and magnetic resonance imaging (MRI) is widely used in the preoperative examination of patients with placenta previa. To evaluate the effectiveness of the placental area in the lower uterine segment and cervical length in identifying the adverse maternal-fetal outcomes in women with complete placenta previa. Retrospective. A total of 141 pregnant women (median age, 32; age range, 24-40 years) with complete placenta previa were examined by MRI to evaluate the uteroplacental condition. A 3 T with T1 -weighted imaging (T1 WI), T2 -weighted imaging (T2 WI), and half-Fourier acquisition single-shot turbo spin echo (HASTE) sequence. The association of the placental area in the lower uterine segment and cervical length measured using MRI with the risk of massive intraoperative hemorrhage (MIH) and maternal-fetal perinatal outcomes were determined. The adverse neonatal outcomes (preterm delivery, respiratory distress syndrome [RDS], admission to neonatal intensive care unit [NICU]) were analyzed in different groups. The t-test, Mann-Whitney U test, Chi-square, Fisher's exact test, and receiver operating characteristic (ROC) curve were used, and a P < 0.05 indicated a statistically significant difference. The mean operation time, intraoperative blood loss, and intraoperative blood transfusing were significantly higher in patients with large placental area and short cervix than in patients with the small placental area and long cervix, respectively. The incidence of adverse neonatal outcomes was significantly higher in the large placenta area group and short cervix group than in the small placenta group area and long cervix group, respectively, such as preterm delivery, RDS, and NICU. By combining placental area with cervical length sensitivity and specificity increased to 93% and 92%, respectively, for the identification of MIH > 2000 mL with area under the receiver operating curve (AUC) 0.941. Large placental area and short cervical length may be associated with a high risk of MIH and adverse maternal-fetal perinatal outcomes in patients with complete placenta previa. 2.

Using Machine Learning Methods to Assess Lymphovascular Invasion and Survival in Breast Cancer: Performance of Combining Preoperative Clinical and MRI Characteristics.

Preoperative assessment of lymphovascular invasion (LVI) in invasive breast cancer (IBC) is of high clinical relevance for treatment decision-making and prognosis. To investigate the associations of preoperative clinical and magnetic resonance imaging (MRI) characteristics with LVI and disease-free survival (DFS) by using machine learning methods in patients with IBC. Retrospective. Five hundred and seventy-five women (range: 24-79 years) with IBC who underwent preoperative MRI examinations at two hospitals, divided into the training (N=386) and validation datasets (N=189). Axial fat-suppressed T2-weighted turbo spin-echo sequence and dynamic contrast-enhanced with fat-suppressed T1-weighted three-dimensional gradient echo imaging. MRI characteristics (clinical T stage, breast edema score, MRI axillary lymph node status, multicentricity or multifocality, enhancement pattern, adjacent vessel sign, and increased ipsilateral vascularity) were reviewed independently by three radiologists. Logistic regression (LR), eXtreme Gradient Boosting (XGBoost), k-Nearest Neighbor (KNN), and Support Vector Machine (SVM) algorithms were used to establish the models by combing preoperative clinical and MRI characteristics for assessing LVI status in the training dataset, and the methods were further applied in the validation dataset. The LVI score was calculated using the best-performing of the four models to analyze the association with DFS. Chi-squared tests, variance inflation factors, receiver operating characteristics (ROC), Kaplan-Meier curve, log-rank, Cox regression, and intraclass correlation coefficient were performed. The area under the ROC curve (AUC) and hazard ratios (HR) were calculated. A P-value <0.05 was considered statistically significant. The model established by the XGBoost algorithm had better performance than LR, SVM, and KNN models, achieving an AUC of 0.832 (95% confidence interval [CI]: 0.789, 0.876) in the training dataset and 0.838 (95% CI: 0.775, 0.901) in the validation dataset. The LVI score established by the XGBoost model was an independent indicator of DFS (adjusted HR: 2.66, 95% CI: 1.22-5.80). The XGBoost model based on preoperative clinical and MRI characteristics may help to investigate the LVI status and survival in patients with IBC. 3 TECHNICAL EFFICACY: Stage 2.

Deep Learning MRI Reconstruction for Accelerating Turbo Spin Echo Hand and Wrist Imaging: A Comparison of Image Quality, Visualization of Anatomy, and Detection of Common Pathologies with Standard Imaging

Magnetic resonance imaging (MRI) of the hand and wrist is a routine MRI examination and takes about 15-20 minutes, which can lead to problems resulting from the relatively long scan time, such as decreased image quality due to motion artifacts and lower patient throughput. The objective of this study was to evaluate a deep learning (DL) reconstruction for turbo spin echo (TSE) sequences of the hand and wrist regarding image quality, visualization of anatomy, and diagnostic performance concerning common pathologies. Twenty-one patients (mean age: 43 ± 19 [19-85] years, 10 men, 11 female) were prospectively enrolled in this study between October 2020 and June 2021. Each participant underwent two MRI protocols: first, standard fully sampled TSE sequences reconstructed with a standard GRAPPA reconstruction (TSES) and second, prospectively undersampled TSE sequences using a conventional parallel imaging undersampling pattern reconstructed with a DL reconstruction (TSEDL). Both protocols were acquired consecutively in one examination. Two experienced MSK-imaging radiologists qualitatively evaluated the images concerning image quality, noise, edge sharpness, artifacts, and diagnostic confidence, as well as the delineation of anatomical structures (triangular fibrocartilage complex, tendon of the extensor carpi ulnaris muscle, extrinsic and intrinsic ligaments, median nerve, cartilage) using a five-point Likert scale and assessed common pathologies. Wilcoxon signed-rank test and kappa statistics were performed to compare the sequences. Overall image quality, artifacts, delineation of anatomical structures, and diagnostic confidence of TSEDL were rated to be comparable to TSES (p > 0.05). Additionally, TSEDL showed decreased image noise (4.90, median 5, IQR 5-5) compared to TSES (4.52, median 5, IQR 4-5, p < 0.05) and improved edge sharpness (TSEDL: 4.10, median 4, IQR 3.5-5; TSES: 3.57, median 4, IQR 3-4; p < 0.05). Inter- and intrareader agreement was substantial to almost perfect (κ=0.632-1.000) for the detection of common pathologies. Time of acquisition could be reduced by more than 60% with the protocol using TSEDL. Compared to TSES, TSEDL provided decreased noise and increased edge sharpness, equal image quality, delineation of anatomical structures, detection of pathologies, and diagnostic confidence. Therefore, TSEDL may be clinically relevant for hand and wrist imaging, as it reduces examination time by more than 60%, thus increasing patient comfort and patient throughput.

MRI features can help to confirm a diagnosis of progressive myelomalacia, but may not be accurate in dogs lacking characteristic clinical signs at the time of imaging.

Progressive myelomalacia (PMM) is a fatal sequela of acute thoracolumbar intervertebral disc extrusion in dogs, with unpredictable onset in the days after the inciting injury. No single reliable diagnostic test is currently available. Magnetic resonance imaging (MRI) features such as T2-weighted spinal cord hyperintensity and loss of subarachnoid signal in a half-Fourier single-shot turbo spin echo (HASTE) sequence have been associated with PMM, but are sometimes present in other dogs with severe deficits. Magnetic resonance imaging findings in 22 dogs with a clinical or histopathologic diagnosis of PMM and 38 deep pain-negative paraplegic dogs were compared in a retrospective case-control study. Length of T2-weighted hyperintense spinal cord change and HASTE signal loss were significantly associated with clinically evident PMM (P=.0019 and P=.0085), however, there were no significant differences between groups when analysis was restricted to dogs not yet showing clinical signs of PMM. The PMM group also had significantly shorter compressive lesions than the control group (P=0.026), suggesting a possible role of more severe focal pressure at the extrusion site. A segment of total loss of contrast enhancement in the venous sinuses and meninges, a feature not previously described, was more common in the PMM group and the difference approached significance (P=0.054). Findings show that MRI features can support the diagnosis in dogs with clinical evidence of PMM,andabsence of these features supports absence of PMM at time of imaging. However, their absencedoes not reliably differentiate dogs with imminent progressive myelomalacia from other dogs with severe deficits following intervertebral disc extrusion.

Automatic detection of Gibbs artefact in MR images with transfer learning approach.

Quality control of magnetic resonance imaging includes image validation, which covers also artefact detection. The daily manual review of magnetic resonance images for possible artefacts can be time-consuming, so automated methods for computer-assisted quality assessment of magnetic resonance imaging need to be developed. The aim of this study was to develop automatic detection of Gibbs artefacts in magnetic resonance imaging using a deep learning method called transfer learning, and to demonstrate the potential of this approach for the development of an automatic quality control tool for the detection of such artefacts in magnetic resonance imaging. The magnetic resonance image dataset of the scanned phantom for quality assurance was created using a turbo spin-echo pulse sequence in the transverse plane. Images were created to include Gibbs artefacts of varying intensities. The images were annotated by two independent reviewers. The annotated dataset was used to develop a method for Gibbs artefact detection using the transfer learning approach. The VGG-16, VGG-19, and ResNet-152 convolutional neural networks were used as pre-trained networks for transfer learning and compared using 5-fold cross-validation. All accuracies of the classification models were above 97%, while the AUC values were all above 0.99, confirming the high quality of the constructed models. We show that transfer learning can be successfully used to detect Gibbs artefacts on magnetic resonance images. The main advantages of transfer learning are that it can be applied on small training datasets, the procedures to build the models are not so complicated, and they do not require much computational power. This shows the potential of transfer learning for the more general task of detecting artefacts in magnetic resonance images of patients, which consequently can improve and speed up the process of quality assessment in medical imaging practice.

Prostatic urinary tract visualization with super-resolution deep learning models.

In urethra-sparing radiation therapy, prostatic urinary tract visualization is important in decreasing the urinary side effect. A methodology has been developed to visualize the prostatic urinary tract using post-urination magnetic resonance imaging (PU-MRI) without a urethral catheter. This study investigated whether the combination of PU-MRI and super-resolution (SR) deep learning models improves the visibility of the prostatic urinary tract. We enrolled 30 patients who had previously undergone real-time-image-gated spot scanning proton therapy by insertion of fiducial markers. PU-MRI was performed using a non-contrast high-resolution two-dimensional T2-weighted turbo spin-echo imaging sequence. Four different SR deep learning models were used: the enhanced deep SR network (EDSR), widely activated SR network (WDSR), SR generative adversarial network (SRGAN), and residual dense network (RDN). The complex wavelet structural similarity index measure (CW-SSIM) was used to quantitatively assess the performance of the proposed SR images compared to PU-MRI. Two radiation oncologists used a 1-to-5 scale to subjectively evaluate the visibility of the prostatic urinary tract. Cohen's weighted kappa (k) was used as a measure of agreement of inter-operator reliability. The mean CW-SSIM in EDSR, WDSR, SRGAN, and RDN was 99.86%, 99.89%, 99.30%, and 99.67%, respectively. The mean prostatic urinary tract visibility scores of the radiation oncologists were 3.70 and 3.53 for PU-MRI (k = 0.93), 3.67 and 2.70 for EDSR (k = 0.89), 3.70 and 2.73 for WDSR (k = 0.88), 3.67 and 2.73 for SRGAN (k = 0.88), and 4.37 and 3.73 for RDN (k = 0.93), respectively. The results suggest that SR images using RDN are similar to the original images, and the SR deep learning models subjectively improve the visibility of the prostatic urinary tract.

Free-breathing BLADE fat-suppressed T2 weighted turbo spin echo sequence for distinguishing lung cancer from benign pulmonary nodules or masses: A pilot study

ObjectiveDiffusion Weighted Imaging (DWI) can be used to differentiate benign and malignant pulmonary nodules or masses, while T2WI is also of great value in the differential diagnosis of them. For example, T2WI can be used to differentiate abscess from lung cancer. The study aims to quantitatively evaluate the efficacy of free-breathing BLADE fat-suppressed T2 weighted turbo spin echo sequence (BLADE T2WI) for differentiating lung cancer (LC) and benign pulmonary nodule or mass (BPNM). MethodsA total of 291 patients with LC (197 males, 94 females; mean age 63.2 years) and 74 BPNM patients (53 males, 21 females; mean age 62.8 years) who underwent BLADE T2WI at 3-T MRI between November 2016 and May 2022were included in this retrospective study. Two radiologists independently blinded observed the MR images and measured the T2 contrast ratio (T2CR). Mann-Whitney U test was used to compare T2CR values between the two groups, ROC curves were used to evaluate the diagnostic efficacy of BLADE T2WI. ResultsThe two radiologists had good inter-observer consistency for T2CR (ICC = 0.958). The T2CR of BPNM was significantly higher than LC (all p < 0.001); the cut-off value of T2CR was 2.135, and the sensitivity, specificity, and accuracy of diagnosis were 75.6%, 63.5%, and 73.2%, respectively. Moreover, T2CR correctly diagnosed 220 LC cases (220/291 = 75.6%) and 47 BPNM cases (47/74 = 63.5%). ConclusionThe T2CR value of MR non-enhanced BLADE T2WI can be easily obtained and can quantitatively distinguish BPNM from LC, thus avoiding misdiagnosis caused by lack of work experience.

An unsupervised deep learning-based image translation method for retrospective motion correction of high resolution kidney MRI

A primary challenge for in vivo kidney magnetic resonance imaging (MRI) is the presence of different types of involuntary physiological motion, affecting the diagnostic utility of acquired images due to severe motion artifacts. Existing prospective and retrospective motion correction methods remain ineffective when dealing with complex large amplitude nonrigid motion artifacts. Here, we introduce an unsupervised deep learning-based image to image translation method between motion-affected and motion-free image domains, for correction of rigid-body, respiratory and nonrigid motion artifacts in vivo kidney MRI.High resolution (i.e., 156 × 156 × 370 μm) ex vivo 3 Tesla MRI scans of 13 porcine kidneys (because of their anatomical homology to human kidney) were conducted using a 3D T2-weighted turbo spin echo sequence. Rigid-body, respiratory and nonrigid motion-affected images were then simulated using the magnitude-only ex vivo motion-free image set. Each 2D coronal slice of motion-affected and motion-free image volume was then divided into patches of 128 × 128 for training the model. We proposed to add normalised cross-correlation loss to cycle consistency generative adversarial network structure (NCC-CycleGAN), to enforce edge alignment between motion-corrected and motion-free image domains.Our NCC-CycleGAN motion correction model demonstrated high performance with an in-tissue structural similarity index measure of 0.77 ± 0.08, peak signal-to-noise ratio of 26.67 ± 3.44 and learned perceptual image patch similarity of 0.173 ± 0.05 between the reconstructed motion-corrected and ground truth motion-free images. This corresponds to a significant respective average improvement of 34%, 23% and 39% (p < 0.05; paired t-test) for the three metrics to correct the three different types of simulated motion artifacts.We demonstrated the feasibility of developing an unsupervised deep learning-based method for efficient automated retrospective kidney MRI motion correction, while preserving microscopic tissue structures in high resolution imaging.

Microvascular morphology alteration using relaxation rate change with gadolinium-based magnetic resonance imaging contrast agent in patients with Alzheimer’s disease

Conventional magnetic resonance imaging (MRI) techniques cannot demonstrate microvascular alterations in mild Alzheimer's disease (AD). Thus, the diagnosis of microvascular pathology commonly relies on postmortem. The purpose of this study was to evaluate alterations of microvascular structures in patients with AD using a 3T clinical MRI system with a commercially available contrast agent. Eleven patients with AD and 11 cognitively normal (CN) controls were included in this cross-sectional prospective study. R2 and R2* relaxation rate changes (∆R2 and ∆R2*) before and after a Gadolinium (Gd)-based contrast agent injection were calculated from images obtained with a multi-echo turbo spin-echo sequence and multi-echo gradient-echo sequence to obtain microvascular index maps of blood volume fraction (BVf), mean vessel diameter (mVD), vessel size index (VSI), mean vessel density (Q), and microvessel-weighted imaging (MvWI). Two-sample t-test was used to compare those values between the two groups. Correlation analysis was performed to evaluate the relationship between those values and age. BVfs at the corpus callosum and at the thalamus were significantly increased in the AD group (P=0.024 and P=0.005, respectively). BVf at the gray matter (P=0.020) and white matter area (P=0.012) were also significantly increased in the AD group compared with the CN group. MvWIs at the hippocampus and parahippocampal gyrus were significantly increased in the AD group compared with the CN group (P=0.020 and P=0.006, respectively). Voxel-based analysis showed both mVD and VSI were significantly decreased at the prefrontal lobe in the AD group. Q were not significant difference between CN and AD groups. MvWI were significantly positively correlated with age. Microvascular index was a useful non-invasive method to evaluate microvascular morphology alteration. The microvascular morphology of AD was manifested as increasing BVf and microvessel-weighted.

An MRI Study Combining Virtual Brain Grafting and Surface-Based Morphometry Analysis to Investigate Contralateral Alterations in Cortical Morphology in Patients With Diffuse Low-Grade Glioma.

The human brain has ability to reorganize itself in response to glioma. However, the mechanism of cortical reorganization remains unclear. To investigate alterations in cortical thickness and local gyration index (LGI) in patients with unilateral frontal lobe diffuse low-grade glioma (DLGG). Retrospective. Ninety-nine patients with histopathologically proven DLGG invading the left frontal lobe (LF; N=56) or the right frontal lobe (RF; N=43), and healthy controls (HC; N=53). 3.0 T, 3D T1-weighted images and gadolinium enhanced T1-weighted images using magnetization-prepared rapid gradient echo sequence, T2-weighted images, and fluid-attenuated inversion recovery using turbo spin echo sequence. In patients with DLGG, virtual brain grafting combined with Freesurfer was utilized to enable automated cortical thickness and LGI calculation. In HC, standard FreeSurfer pipeline was applied to calculate these measures. Radiomic features were extracted from glioma using Pyradiomic software. General linear model and Pearson's correlation analysis. A P value <0.05 was considered statistically significant. For LF patients, there was significantly increased cortical thickness in the rostral middle frontal gyrus, significantly reduced cortical thickness in the precentral gyrus and hypogyrification in the lingual and medial orbitofrontal (MOF) gyrus in contralateral hemisphere. For RF patients, there was significantly increased cortical thickness in the middle temporal, lateral occipital extending to isthmus cingulate gyrus, significantly reduced cortical thickness in the precentral gyrus and hypogyrification in the lingual gyrus in the contralateral hemisphere. A negative association between four textural features of DLGG and LGI in the right MOF gyrus of LF group was found (r=-0.609, -0.442, -0.545, and -0.417, respectively). Cortical thickness compensation was shown in contralateral homotopic location and some distant contralateral regions. Additionally, there was decreased cortical thickness in the contralateral precentral gyrus and hypogyrification in contralateral lingual gyrus. 4 TECHNICAL EFFICACY: Stage 2.

Comparison of a deep learning-accelerated T2-weighted turbo spin echo sequence and its conventional counterpart for female pelvic MRI: reduced acquisition times and improved image quality

ObjectivesTo investigate the feasibility of a deep learning-accelerated T2-weighted turbo spin echo (TSE) sequence (T2DL) applied to female pelvic MRI, using standard T2-weighted TSE (T2S) as reference.MethodsIn total, 24 volunteers and 48 consecutive patients with benign uterine diseases were enrolled. Patients in the menstrual phase were excluded. T2S and T2DL sequences in three planes were performed for each participant. Quantitative image evaluation was conducted by calculating the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). Image geometric distortion was evaluated by measuring the diameters in all three directions of the uterus and lesions. Qualitative image evaluation including overall image quality, artifacts, boundary sharpness of the uterine zonal layers, and lesion conspicuity were assessed by three radiologists using a 5-point Likert scale, with 5 indicating the best quality. Comparative analyses were conducted for the two sequences.ResultsT2DL resulted in a 62.7% timing reduction (1:54 min for T2DL and 5:06 min for T2S in axial, sagittal, and coronal imaging, respectively). Compared to T2S, T2DL had significantly higher SNR (p ≤ 0.001) and CNR (p ≤ 0.007), and without geometric distortion (p = 0.925–0.981). Inter-observer agreement regarding qualitative evaluation was excellent (Kendall’s W > 0.75). T2DL provided superior image quality (all p < 0.001), boundary sharpness of the uterine zonal layers (all p < 0.001), lesion conspicuity (p = 0.002, p < 0.001, and p = 0.021), and fewer artifacts (all p < 0.001) in sagittal, axial, and coronal imaging.ConclusionsCompared with standard TSE, deep learning-accelerated T2-weighted TSE is feasible to reduce acquisition time of female pelvic MRI with significant improvement of image quality.

Simultaneous Multislice Accelerated TSE for Improved Spatiotemporal Resolution and Diagnostic Accuracy in Magnetic Resonance Neurography: A Feasibility Study.

This study aims to evaluate the utility of simultaneous multislice (SMS) acceleration for routine magnetic resonance neurography (MRN) at 3 T. Patients with multiple sclerosis underwent MRN of the sciatic nerve consisting of a standard fat-saturated T2-weighted turbo spin echo (TSE) sequence using integrated parallel acquisition technique (PAT2) acceleration and 2 T2 TSE sequences using a combination of PAT-SMS acceleration (1) to reduce scan time (PAT2-SMS2; SMS-TSE FAST ) and (2) for time neutral increase of in-plane resolution (PAT1-SMS2; SMS-TSE HR ). Acquisition times were 5:29 minutes for the standard T2 TSE, 3:12 minutes for the SMS-TSE FAST , and 5:24 minutes for the SMS-TSE HR . Six qualitative imaging parameters were analyzed by 2 blinded readers using a 5-point Likert scale and T2 nerve lesions were quantified, respectively. Qualitative and quantitative image parameters were compared, and both interrater and intrarater reproducibility were statistically assessed. In addition, signal-to-noise ratio/contrast-to-noise ratio (CNR) was obtained in healthy controls using the exact same imaging protocol. A total of 15 patients with MS (mean age ± standard deviation, 38.1 ± 11 years) and 10 healthy controls (mean age, 29.1 ± 7 years) were enrolled in this study. CNR analysis was highly reliable (intraclass correlation coefficient, 0.755-0.948) and revealed a significant CNR decrease for the sciatic nerve for both SMS protocols compared with standard T2 TSE (SMS-TSE FAST /SMS-TSE HR , -39%/-55%; P ≤ 0.01). Intrarater and interrater reliability of qualitative image review was good to excellent (κ: 0.672-0.971/0.617-0.883). Compared with the standard T2 TSE sequence, both SMS methods were shown to be superior in reducing pulsatile flow artifacts ( P < 0.01). Ratings for muscle border sharpness, detailed muscle structures, nerve border sharpness, and nerve fascicular structure did not differ significantly between the standard T2 TSE and the SMS-TSE FAST ( P > 0.05) and were significantly better for the SMS-TSE HR than for standard T2 TSE ( P < 0.001). Muscle signal homogeneity was mildly inferior for both SMS-TSE FAST ( P > 0.05) and SMS-TSE HR ( P < 0.001). A significantly higher number of T2 nerve lesions were detected by SMS-TSE HR ( P ≤ 0.01) compared with the standard T2 TSE and SMS-TSE FAST , whereas no significant difference was observed between the standard T2 TSE and SMS-TSE FAST . Implementation of SMS offers either to substantially reduce acquisition time by over 40% without significantly impeding image quality compared with the standard T2 TSE or to increase in-plane resolution for a high-resolution approach and improved depiction of T2 nerve lesions while keeping acquisition times constant. This addresses the specific needs of MRN by providing different imaging approaches for 2D clinical MRN.

Prevalence and distribution of aortic plaque by sex and age group among community-dwelling adults

Rationale and objectivesAtherosclerosis of the aorta is associated with increased risk of cardiovascular mortality and vascular events. We aim to describe the prevalence and distribution of non-calcified atherosclerotic plaque in the descending aorta as quantified by noncontrast cardiovascular magnetic resonance (CMR) in a community-dwelling cohort of adults. Materials and methodsWe used CMR to quantify noncalcified aortic plaque in 1726 participants (aged 65 ± 9 years, 46.7% men) from the Cohort Study Offspring cohort. ECG-gated, fat-suppressed, T2-weighted, black blood turbo spin echo sequence was used to acquire 36 transverse slices covering the descending aorta from just below the arch to the aortoiliac bifurcation. Plaque was defined as discrete luminal protrusions ≥1 mm; these were manually traced, then summed to determine total descending aortic plaque (DAP) and segmental thoracic and abdominal aortic plaque (TAP, AAP). Participants were stratified by sex and age group (<55, 55–64, 65–74, ≥75y). A healthy referent group (without clinical cardiovascular disease, smoking, diabetes, impaired renal function; (N = 768, 43.8% men) was used to determine upper 90th percentile cutpoints for DAP and AAP which were then applied to the overall study cohort. ResultsPrevalence of DAP was similar between men (47.3%) and women (48.9%), p = 0.50, as was AAP prevalence (men: 44.5%, women: 46.7%, p = 0.16); TAP was less prevalent in both sexes (men: 8.9%, women: 7.1%, p = 0.15). Both prevalence and burden of DAP, AAP and TAP increased with advancing age. ConclusionNoncalcified plaque prevalence, visualized on CMR, in community-dwelling adults is similar between the sexes, and both prevalence and burden of aortic plaque increase with greater age.

Normative Values of Neuromelanin-Sensitive MRI Signal in Older Adults Obtained Using a Turbo Spin Echo Sequence.

The integrity and function of catecholamine neurotransmitter systems can be assessed using neuromelanin-sensitive MRI (NM-MRI). The relevance of this method to neurodegenerative and psychiatric disorders is becoming increasingly evident, and it has potential as a clinical biomarker. To support future application of NM-MRI as a clinical biomarker by defining the normative range of NM-MRI signal and volume metrics in cognitively normal older adults. Prospective. A total of 152 cognitively normal older adults aged 53-86 years old, including 41 participants who had follow-up NM-MRI data collected 9-16months later. A 3.0 T; NM-MRI turbo spin echo and T1-weighted magnetization-prepared rapid acquisition with gradient echo sequences. NM-MRI images were processed to yield summary measures of volume and signal (contrast-to-noise ratio, CNR) for the substantia nigra (SN) and locus coeruleus (LC) using a recently developed software employing a fully automated algorithm. Change in these metrics over time was also assessed. Mean and standard deviation of NM-MRI metrics were calculated; change over time was tested for significance using 1-sample t-tests. P values < 0.05 were considered statistically significant. At baseline SN signal (CNR) was 10.02% (left) and 10.28% (right) and LC signal was 24.71% (left) and 20.42% (right). Baseline SN volume was 576 mm3 (left) and 540 mm3 (right) and LC volume was 6.31 mm3 (left) and 6.30 mm3 (right). The only NM-MRI metric showing significant change was a decrease in left SN volume (t40 =-2.57, P=0.014). We report normative values for NM-MRI signal and volume in the SN and LC of cognitively normal older adults and explore their change over time. These values may help future efforts to use NM-MRI as a clinical biomarker by facilitating identification of patients with extreme NM-MRI values. 1.

In vivo T1 mapping of neonatal brain tissue at 64 mT.

Ultralow-field (ULF) point-of-care MRI systems allow image acquisition without interrupting medical provision, with neonatal clinical care being an important potential application. The ability to measure neonatal brain tissue T1 is a key enabling technology for subsequent structural image contrast optimization, as well as being a potential biomarker for brain development. Here we describe an optimized strategy for neonatal T1 mapping at ULF. Examinations were performed on a 64-mT portable MRI system. A phantom validation experiment was performed, and a total of 33 in vivo exams were acquired from 28 neonates with postmenstrual age ranging from 31+4 to 49+0 weeks. Multiple inversion-recovery turbo spin-echo sequences were acquired with differing inversion and repetition times. An analysis pipeline incorporating inter-sequence motion correction generated proton density and T1 maps. Regions of interest were placed in the cerebral deep gray matter, frontal white matter, and cerebellum. Weighted linear regression was used to predict T1 as a function of postmenstrual age. Reduction of T1 with postmenstrual age is observed in all measured brain tissue; the change in T1 per week and 95% confidence intervals is given by dT1 =-21 ms/week [-25, -16] (cerebellum), dT1 =-14 ms/week [-18, -10] (deep gray matter), and dT1 =-35 ms/week [-45, -25] (white matter). Neonatal T1 values at ULF are shorter than those previously described at standard clinical field strengths, but longer than those of adults at ULF. T1 reduces with postmenstrual age and is therefore a candidate biomarker for perinatal brain development.

Risk Factors for Cerebrovascular Events in Moyamoya Angiopathy Using 4D Flow MRI: A Pilot Study.

Little is known about internal carotid artery (ICA) hemodynamics in patients with moyamoya angiopathy (MMA) and its role in cerebrovascular events. To characterize ICA hemodynamics in MMA patients by 4D flow MRI and investigate its relationship with cerebrovascular events. Prospective. Seventy MMA patients (50 years old ± 9, 30 males). Time-resolved three-directional velocity encoded fast field echo sequence (4D flow) MRI, T1-weighted fast field echo sequence, T2 weighted turbo spin echo sequence, diffusion weighted echo planar imaging; T2-weighted fluid-attenuated inversion recovery turbo spin echo sequence, susceptibility weighted fast field echo sequence, and time-of-flight MR angiography fast field echo sequence at 3.0T. ICA hemodynamics (maximum and average velocity [Vmax , Vavg ], average blood flow [Flowavg ], and wall shear stress) were analyzed based on 4D flow data. Cerebral infarction, defined as the occurrence of events, in 124 brain hemispheres was determined according to clinical symptoms and conventional brain MR imaging. The independent-samples T test was used to evaluate differences in ICA hemodynamics between infarcted and non-infarcted hemispheres. Binary logistic regression was performed to investigate the relationship between ICA hemodynamics and events. A P value < 0.05 was considered statistically significant. Sixty-one infarcted hemispheres (eight hemispheres with acute ischemic damage, 30 with chronic ischemic damage, and 23 with chronic hemorrhagic damage) had cerebrovascular events and 63 non-infarcted hemispheres did not. The hemodynamic parameters in the infarcted hemispheres (Vmax : P < 0.001; Vavg : P=0.003; and Flowavg : P=0.004) were significantly lower than those in the non-infarcted hemispheres. However, Vmax (P=0.052), Vavg (P=0.107), and Flowavg (P=0.074) were not significantly different among hemispheres with acute ischemic lesions, chronic ischemic lesions and chronic hemorrhagic lesions. Vmax (odds ratio 3.033, 95% CI: 1.075-8.562) was independently associated with cerebrovascular events. Vmax maybe a higher risk factor of cerebrovascular events in MMA patients. 2 TECHNICAL EFFICACY STAGE: 3.

Sodium and quantitative hydrogen parameter changes in muscle tissue after eccentric exercise and in delayed-onset muscle soreness assessed with magnetic resonance imaging.

The objective of the current study was to assess sodium (23 Na) and quantitative proton (1 H) parameter changes in muscle tissue with magnetic resonance imaging (MRI) after eccentric exercise and in delayed-onset muscle soreness (DOMS). Fourteen participants (mean age: 25 ± 4 years) underwent 23 Na/1 H MRI of the calf muscle on a 3-T MRI system before exercise (t0), directly after eccentric exercise (t1), and 48 h postintervention (t2). In addition to tissue sodium concentration (TSC), intracellular-weighted sodium (ICwS) signal was acquired using a three-dimensional density-adapted radial projection readout with an additional inversion recovery preparation module. Phantoms containing saline solution served as references to quantify sodium concentrations. The 1 H MRI protocol consisted of a T1 -weighted turbo spin echo sequence, a T2 -weighted turbo inversion recovery, as well as water T2 mapping and water T1 mapping. Additionally, blood serum creatine kinase (CK) levels were assessed at baseline and 48 h after exercise. The TSC and ICwS of exercised muscles increased significantly from t0 to t1 and decreased significantly from t1 to t2. In the soleus muscle (SM), ICwS decreased below baseline values at t2. In the tibialis anterior muscle (TA), TSC and ICwS remained at baseline levels at each measurement point. However, high-CK participants (i.e., participants with a more than 10-fold CK increase, n = 3) displayed different behavior, with 2- to 4-fold increases in TSC values in the medial gastrocnemius muscle (MGM) at t2. 1 H water T1 relaxation times increased significantly after 48 h in the MGM and SM. 1 H water T2 relaxation times and muscle volume increased in the MGM at t2. Sodium MRI parameters and water relaxation times peaked at different points. Whereas water relaxation times were highest at t2, sodium MRI parameters had already returned to baseline values (or even below baseline values, for low-CK participants) by this point. The observed changes in ion concentrations and water relaxation time parameters could enable a better understanding of the physiological processes during DOMS and muscle regeneration. In the future, this might help to optimize training and to reduce associated sports injuries.

Prenatal diagnosis of fetal ectopia cordis by fetal cardiovascular magnetic resonance imaging.

The purpose of this retrospective study was to report our cases of fetal ectopia cordis (EC) and to evaluate the utility of fetal cardiovascular magnetic resonance imaging (MRI) for the diagnosis of this rare anomaly. This retrospective study included 11 fetuses with EC. The multiplane steady-state free precession (SSFP) sequence, single-shot turbo spin-echo sequence and non-gated SSFP cine cardiovascular magnetic resonance were used to evaluate the fetal heart and abdomen. The 11 fetal cases with EC were examined by fetal cardiovascular MRI and confirmed by postnatal or post-mortem findings. Of these 11 cases, two were isolated thoracic EC, six had pentalogy of Cantrell, and three had an omphalocele and EC. Among all 11 fetuses, nine were associated with congenital heart defects. In four cases, fetal MRI added additional information compared to fetal ultrasound, however, in two cases, fetal MRI missed the diagnosis of a ventricular septal defect noted by echocardiography. Fetal MRI combined with prenatal echocardiography can improve the accuracy of the prenatal diagnosis of EC.

Evaluation of HASTE T2 weighted image with reduced echo time for detecting focal liver lesions in patients at risk of developing hepatocellular carcinoma

PurposeTo compare the image quality and performance of half-Fourier acquisition single-shot turbo spin echo (HASTE) sequences, using compressed sensing (HASTE-CS) and deep-learning based reconstruction (HASTE-DL) in detecting focal liver lesions (FLLs), to those of T2-weighted image using BLADE sequence (T2WI) in patients at risk of developing hepatocellular carcinoma (HCC). Materials and methodsThis retrospective study included patients at risk of developing HCC who underwent liver MRI including HASTE-DL, HASTE-CS, T2WI and DWI between January and June 2020. Three radiologists independently reviewed the image quality along with FLL detection in the three T2-based sequences and DWI. Reference lesion characterization was done using the complete set of MRI sequences according to the Liver Imaging Reporting and Data System (LI-RADS) v2018. ResultsA total of 227 patients with 88 of whom had FLLs (n = 194, mean size 11.7 ± 10.9 mm) were included. HASTE-DL yielded the highest overall image quality, followed by HASTE-CS and T2WI (3.4 ± 0.5, 3.1 ± 0.6, 2.4 ± 0.5, respectively, P < 0.001 for all). In the detection of FLLs, HASTE-DL showed significantly higher sensitivity than T2WI (51.5 % vs 43.6 %, P = 0.007) whereas HASTE-CS and T2WI bore respectively little difference (P > 0.017) on per-patient basis. For LR-4, -5, -M lesions, HASTE-DL had significantly higher figure of merit than that of T2WI (0.58 vs 0.52, P < 0.001) in per-lesion basis. ConclusionHASTE-DL demonstrated better image quality and higher performance for FLL detection than conventional T2WI in patients at risk of developing HCC.

Quantification of Prostate Cancer Metabolism Using 3D Multiecho bSSFP and Hyperpolarized [1-13 C] Pyruvate: Metabolism Differs Between Tumors of the Same Gleason Grade.

Three-dimensional (3D) multiecho balanced steady-state free precession (ME-bSSFP) has previously been demonstrated in preclinical hyperpolarized (HP) 13 C-MRI in vivo experiments, and it may be suitable for clinical metabolic imaging of prostate cancer (PCa). To validate a signal simulation framework for the use of sequence parameter optimization. To demonstrate the feasibility of ME-bSSFP for HP 13 C-MRI in patients. To evaluate the metabolism in PCa measured by ME-bSSFP. Retrospective single-center cohort study. Phantoms containing aqueous solutions of [1-13 C] lactate (2.3M) and [13 C] urea (8M). Eight patients (mean age 67 ± 6 years) with biopsy-confirmed Gleason 3 + 4 (n=7) and 4 + 3 (n=1) PCa. FIELD STRENGTH/SEQUENCES: 1 H MRI at 3T with T2 -weighted turbo spin-echo sequence used for spatial localization and spoiled dual gradient-echo sequence used for B0 -field measurement. ME-bSSFP sequence for 13 C MR spectroscopic imaging with retrospective multipoint IDEAL metabolite separation. The primary endpoint was the analysis of pyruvate-to-lactate conversion in PCa and healthy prostate regions of interest (ROIs) using model-free area under the curve (AUC) ratios and a one-directional kinetic model (kP ). The secondary objectives were to investigate the correlation between simulated and experimental ME-bSSFP metabolite signals for HP 13 C-MRI parameter optimization. Pearson correlation coefficients with 95% confidence intervals and paired t-tests. The level of statistical significance was set at P < 0.05. Strong correlations between simulated and empirical ME-bSSFP signals were found (r > 0.96). Therefore, the simulation framework was used for sequence optimization. Whole prostate metabolic HP 13 C-MRI, observing the conversion of pyruvate into lactate, with a temporal resolution of 6seconds was demonstrated using ME-bSSFP. Both assessed metrics resulted in significant differences between PCa (mean ± SD) (AUC=0.33 ± 012, kP =0.038 ± 0.014) and healthy (AUC=0.15 ± 0.10, kP =0.011 ± 0.007) ROIs. Metabolic HP 13 C-MRI in the prostate using ME-bSSFP allows for differentiation between aggressive PCa and healthy tissue. 2 TECHNICAL EFFICACY: Stage 1.