Gradient-recalled Echo Sequence Research Articles

3D MRI of the Spine.

Three-dimensional (3D) magnetic resonance imaging of the spine is now clinically feasible due to technological advancements. Its advantages over two-dimensional imaging include higher in-plane spatial resolution and the ability for reformation in any plane that enables time savings in image acquisition and aids more accurate interpretation. Multispectral 3D techniques for imaging around metal are sometimes useful for evaluating anatomy adjacent to spinal fixation hardware. 3D gradient-recalled echo sequences, including ultrashort or zero time to echo sequences, can provide osseous detail similar to conventional computed tomography.

Measurement of vertebral endplate bone marrow lesion (Modic change) composition with water\u2013fat MRI and relationship to patient-reported outcome measures

PurposeVertebral endplate bone marrow lesions (“Modic changes”, MC) are associated with chronic low back pain (CLBP). Bone marrow composition in MC is poorly understood. The goals of this study were to: (1) measure bone marrow fat fraction (BMF) in CLBP patients with MC using water–fat MRI and (2) assess the relationship between BMF measurements and patient-reported clinical characteristics.MethodsIn this cross-sectional study, 42 CLBP patients (men, n = 21; age, 48 ± 12.4 years) and 18 asymptomatic controls (men, n = 10; 42.7 ± 12.8 years) underwent 3 T MRI between January 2016 and July 2018. Imaging consisted of T1- and T2-weighted sequences to evaluate MC and spoiled gradient-recalled echo sequence with asymmetric echoes and least-squares fitting to measure BMF. BMF was compared between vertebrae with and without MC using mixed effects models. The relationship between the BMF measurements and patient-reported disability scores was examined using regression.ResultsTwenty-seven subjects (26 CLBP, 1 control) had MC, and MC presence coincided with significantly altered BMF. In MC 1, BMF was lower than endplates without MC (absolute difference −22.3%; p < 0.001); in MC 2, BMF was higher (absolute difference 21.0%; p < 0.001). Absolute BMF differences between affected and unaffected marrow were larger in patients with greater disability (p = 0.029–0.032) and were not associated with pain (p = 0.49–0.83).ConclusionBMF is significantly altered in MC. Water–fat MRI enables BMF measurements that may eventually form the basis for quantitative assessments of MC severity and progression.

Navigator-Guided Motion and B0 Correction of T2*-Weighted Magnetic Resonance Imaging Improves Multiple Sclerosis Cortical Lesion Detection.

Cortical lesions are common in multiple sclerosis (MS). T2*-weighted (T2*w) imaging at 7 T is relatively sensitive for cortical lesions, but quality is often compromised by motion and main magnetic field (B0) fluctuations. The aim of this study was to determine whether motion and B0 correction with a navigator-guided gradient-recalled echo sequence can improve cortical lesion detection in T2*w magnetic resonance imaging. In this prospective study, a gradient-recalled echo sequence incorporating a navigator allowing for motion and B0 field correction was applied to collect T2*w images at 7 T from adults with MS between August 2019 and March 2020. T2*-weighted images were acquired in 1 to 3 partially overlapping scans per individual and were reconstructed using global average B0 correction ("uncorrected") or motion correction and spatially linear B0 correction ("corrected"). Image quality rating and manual segmentation of cortical lesions were performed on uncorrected and corrected images. Lesions seen on a single scan were retrospectively evaluated on the complementary scan. The association of cortical lesions with clinical disability was assessed. Mixed models were used to determine the effect of correction on lesion detection as well as on the relationship between disability and lesion count. A total of 22 T2*w scans were performed on 11 adults with MS (mean [SD] age, 49 [11] years; 8 women). Quality improved for 20 of 22 scans (91%) after correction. A total of 69 cortical lesions were identified on uncorrected images (median per scan, 2; range, 0-11) versus 148 on corrected images (median per scan, 4.5; range, 0-25; rate ratio [RR], 2.1; P < 0.0001). For low-quality uncorrected scans with moderate to severe motion artifact (18/22, 82%), there was an improvement in cortical lesion detection with correction (RR, 2.5; P < 0.0001), whereas there was no significant change in cortical lesion detection for high-quality scans (RR, 1.3; P = 0.43). Navigator-guided motion and B0 correction substantially improves the overall image quality of T2*w magnetic resonance imaging at 7 T and increases its sensitivity for cortical lesions.

Catatonia associated with seizures due to parietal cavernoma.

Catatonia associated with seizures due to parietal cavernoma.

GCT-60. DEVELOPMENT OF MICROBLEEDING AFTER PROTON THERAPY FOR PATIENTS WITH GERM CELL TUMOR

BACKGROUNDProton therapy has been increasingly used to treat pediatric brain tumor. However, there were few reports about radiation-induced cerebral microbleeds(CMBs) and cavernous malformation among these patients. Here we evaluate the incidence and risk factor of CMBs with MR imaging.MATERIAL AND METHODWe retrospectively identified patients with germ cell tumor treated with whole ventricle irradiation of 30.6 Gy using proton therapy at the Tsukuba University Hospital between 2004 and 2017. CMBs were characterized by examination of MR imaging scan including susceptibility-weighted imaging and T2* weighed gradient-recalled echo sequence.RESULTThe mean age at the time of proton therapy was 14.5 years. The median follow-up duration was 62.3 months. Three patients were treated by local boost in addition to whole ventricle irradiation. CMBs were found in 78% at 5 years, and 88% at 10 years from irradiation. Over 80% of CMBs occurred in area of the brain exposed to 30 Gy.CONCLUSIONThis study indicated over 30 Gy irradiation may become a risk factor for development of CMBs. Although the correlation between development of CMBs and cognitive function, proton therapy might have an advantage to reduce late sequelae with decreasing irradiating dose to surrounding normal brain tissue.

Robust water-fat separation based on deep learning model exploring multi-echo nature of mGRE.

To design a new deep learning network for fast and accurate water-fat separation by exploring the correlations between multiple echoes in multi-echo gradient-recalled echo (mGRE) sequence and evaluate the generalization capabilities of the network for different echo times, field inhomogeneities, and imaging regions. A new multi-echo bidirectional convolutional residual network (MEBCRN) was designed to separate water and fat images in a fast and accurate manner for the mGRE data. This new MEBCRN network contains 2 main modules, the first 1 is the feature extraction module, which learns the correlations between consecutive echoes, and the other one is the water-fat separation module that processes the feature information extracted from the feature extraction module. The multi-layer feature fusion (MLFF) mechanism and residual structure were adopted in the water-fat separation module to increase separation accuracy and robustness. Moreover, we trained the network using in vivo abdomen images and tested it on the abdomen, knee, and wrist images. The results showed that the proposed network could separate water and fat images accurately. The comparison of the proposed network and other deep learning methods shows the advantage in both quantitative metrics and robustness for different TEs, field inhomogeneities, and images acquired for various imaging regions. The proposed network could learn the correlations between consecutive echoes and separate water and fat images effectively. The deep learning method has certain generalization capabilities for TEs and field inhomogeneity. Although the network was trained only in vivo abdomen images, it could be applied for different imaging regions.

Sample strategies for quantification of hepatic fat fraction mean MRI in healthy cats during body weight gain.

Hepatic fat fraction (HFF) can be non-invasively estimated with magnetic resonance imaging (MRI) multiple echo gradient recalled echo (GRE) sequence. The aim of this study was to test different methods of sampling strategies to quantify the HFF in healthy cats during body weight gain. Twelve healthy adult male cats were examined in a 3 Tesla MRI unit. Sequences included morphological images, and multiple echo GRE sequence. Cats were scanned at the beginning of the study and twice, each 20 weeks apart during body weight gain. HFF was calculated with 5 different methods of sampling on the multiple echo GRE sequence with different number, size and position of regions of interest (ROIs) and by 2 operators. Results indicated that HFF increased with increasing body weight, and the increase was appreciated with all the 5 methods. There was overall excellent agreement (interclass correlation coefficient = 0.820 (95% confidence interval:0.775–0.856)) between the 2 operators. HFF in the left lateral hepatic lobe was lower than in the other analyzed lobes. HFF measured on large free-hand drawn ROIs was higher than HFF measured with smaller ROIs size. This study proves that different sampling methods for quantification of HFF on multiple echo GRE sequence have overall excellent repeatability and ability to appreciate increased HFF.

Reliability and Reproducibility of Neuromelanin-Sensitive Imaging of the Substantia Nigra: A Comparison of Three Different Sequences.

BackgroundNeuromelanin‐sensitive MRI (NM‐MRI) of the substantia nigra provides a noninvasive way to acquire an indirect measure of dopamine functioning. Despite the potential of NM‐MRI as a candidate biomarker for dopaminergic pathology, studies about its reproducibility are sparse.PurposeTo assess the test–retest reproducibility of three commonly used NM‐MRI sequences and evaluate three analysis methods.Study TypeProspective study.PopulationA total of 11 healthy participants age between 20–27 years.Field Strength/Sequence3.0T; NM‐MRI gradient recalled echo (GRE) with magnetization transfer (MT) pulse; NM‐MRI turbo spin echo (TSE) with MT pulse; NM‐MRI TSE without MT pulse.AssessmentParticipants were scanned twice with a 3‐week interval. Manual analysis, threshold analysis, and voxelwise analysis were performed for volume and contrast ratio (CR) measurements.Statistical TestsIntraclass correlation coefficients (ICCs) were calculated for test–retest and inter‐ and intrarater variability.ResultsThe GRE sequence achieved the highest contrast and lowest variability (4.9–5.7%) and showed substantial to almost perfect test–retest ICC (0.72–0.90) for CR measurements. For volume measurements, the manual analysis showed a higher variability (10.7–17.9%) and scored lower test–retest ICCs (–0.13–0.73) than the other analysis methods. The threshold analysis showed higher test–retest ICC (0.77) than the manual analysis for the volume measurements.Data ConclusionNM‐MRI is a highly reproducible measure, especially when using the GRE sequence and CR measurements. Volume measurements appear to be more sensitive to inter/intrarater variability and variability in placement and orientation of the NM‐MRI slab. The threshold analysis appears to be the best alternative for volume analysis.Level of Evidence2Technical Efficacy Stage1

Integrated quantitative susceptibility and R2 * mapping for evaluation of liver fibrosis: An ex vivo feasibility study.

To develop a method for noninvasive evaluation of liver fibrosis, we investigated the differential sensitivities of quantitative susceptibility mapping (QSM) and R2 * mapping using corrections for the effects of liver iron. Liver fibrosis is characterized by excessive accumulation of collagen and other extracellular matrix proteins. While collagen increases R2 * relaxation, measures of R2 * for fibrosis are confounded by liver iron, which may be present in the liver over a wide range of concentrations. The diamagnetic collagen contribution to susceptibility values measured by QSM is much less than the contribution of highly paramagnetic iron. In 19 ex vivo liver explants with and without fibrosis, QSM (χ), R2 * and proton density fat fraction (PDFF) maps were constructed from multiecho gradient-recalled echo (mGRE) sequence acquisition at 3 T. Median parameter values were recorded and differences between the MRI parameters in nonfibrotic vs. advanced fibrotic/cirrhotic samples were evaluated using Mann-Whitney U tests and receiver operating characteristic analyses. Logistic regression with stepwise feature selection was employed to evaluate the utility of combined MRI measurements for detection of fibrosis. Median R2 * increased in fibrotic vs. nonfibrotic liver samples (P = .041), while differences in χ and PDFF were nonsignificant (P = .545 and P = .395, respectively). Logistic regression identified the combination of χ and R2 * significant for fibrosis detection (logit [prediction] = -8.45 + 0.23 R2 * - 28.8 χ). For this classifier, a highly significant difference between nonfibrotic vs. advanced fibrotic/cirrhotic samples was observed (P = .002). The model exhibited an AUC of 0.909 (P = .003) for detection of advanced fibrosis/cirrhosis, which was substantially higher compared with AUCs of the individual parameters (AUC 0.591-0.784). An integrated QSM and R2 * analysis of mGRE 3 T imaging data is promising for noninvasive diagnostic assessment of liver fibrosis.

Automatic Vertebral Body Segmentation Based on Deep Learning of Dixon Images for Bone Marrow Fat Fraction Quantification.

Background: Bone marrow fat (BMF) fraction quantification in vertebral bodies is used as a novel imaging biomarker to assess and characterize chronic lower back pain. However, manual segmentation of vertebral bodies is time consuming and laborious.Purpose: (1) Develop a deep learning pipeline for segmentation of vertebral bodies using quantitative water-fat MRI. (2) Compare BMF measurements between manual and automatic segmentation methods to assess performance.Materials and Methods: In this retrospective study, MR images using a 3D spoiled gradient-recalled echo (SPGR) sequence with Iterative Decomposition of water and fat with Echo Asymmetry and Least-squares estimation (IDEAL) reconstruction algorithm were obtained in 57 subjects (28 women, 29 men, mean age, 47.2 ± 12.6 years). An artificial network was trained for 100 epochs on a total of 165 lumbar vertebrae manually segmented from 31 subjects. Performance was assessed by analyzing the receiver operating characteristic curve, precision-recall, F1 scores, specificity, sensitivity, and similarity metrics. Bland-Altman analysis was used to assess performance of BMF fraction quantification using the predicted segmentations.Results: The deep learning segmentation method achieved an AUC of 0.92 (CI 95%: 0.9186, 0.9195) on a testing dataset (n = 24 subjects) on classification of pixels as vertebrae. A sensitivity of 0.99 and specificity of 0.80 were achieved for a testing dataset, and a mean Dice similarity coefficient of 0.849 ± 0.091. Comparing manual and automatic segmentations on fat fraction maps of lumbar vertebrae (n = 124 vertebral bodies) using Bland-Altman analysis resulted in a bias of only −0.605% (CI 95% = −0.847 to −0.363%) and agreement limits of −3.275% and +2.065%. Automatic segmentation was also feasible in 16 ± 1 s.Conclusion: Our results have demonstrated the feasibility of automated segmentation of vertebral bodies using deep learning models on water-fat MR (Dixon) images to define vertebral regions of interest with high specificity. These regions of interest can then be used to quantify BMF with comparable results as manual segmentation, providing a framework for completely automated investigation of vertebral changes in CLBP.

Two-Minute Quantitative Susceptibility Mapping From Three-Dimensional Echo-Planar Imaging: Accuracy, Reliability, and Detection Performance in Patients With Cerebral Microbleeds.

The aim of this study was to assess the accuracy, reliability, and cerebral microbleed (CMB) detection performance of 2-minute quantitative susceptibility mapping (QSM) from 3-dimensional echo-planar imaging (3D-EPI). Gadolinium phantom study was conducted using 3D-EPI, single-echo time (TE), and multi-TE gradient-recalled echo (GRE) sequences on two 3-T magnetic resonance (MR) scanners to assess the accuracy between measured and theoretical susceptibility values. The institutional review board approved this prospective study, and 40 healthy volunteers were enrolled with written consent between April 2018 and October 2019. Each underwent 3D-EPI, single-TE, and multi-TE GRE sequences consecutively on one 3-T MR scanner, and QSMs were calculated to assess the reliability of 3D-EPI QSM. Intraclass correlation coefficient (ICC), linear regression, and Bland-Altman plots were calculated. Patients with CMB who underwent both 3D-EPI and GRE QSM scans were retrospectively enrolled. Two radiologists evaluated images independently, and Cohen κ coefficients were calculated to compare CMB detection performance. Phantom study showed excellent validity of 3D-EPI QSM on both MR scanners: Skyra, R2 = 0.996, P < 0.001, ICC = 0.997, mean difference, -2 ppb (95% confidence interval [CI], -45 to 40 ppb); Prisma, R2 = 0.992, P < 0.001, ICC = 0.988, mean difference, 15 ppb (95% CI, -67 to 97 ppb). A human study of 40 healthy volunteers (59 ± 13 years, 25 women) showed excellent reliability with 3D-EPI QSM for both single-TE and multi-TE GRE (R2 = 0.981, P < 0.001, ICC = 0.988; R2 = 0.983, P < 0.001, ICC = 0.990, respectively), supported by a Bland-Altman mean difference of 4 ppb (95% CI, -15 to 23 ppb) for single-TE GRE and 3 ppb (95% CI, -15 to 20 ppb) for multi-TE GRE. The CMB detection performance evaluation from 38 patients (51 ± 20 years, 20 women) showed almost perfect agreement between 3D-EPI and GRE QSM for both raters (κ = 0.923 and 0.942, P < 0.001). Faster QSM from 3D-EPI demonstrated excellent accuracy, reliability, and CMB detection performance.

Image quality of the CAIPIRINHA-Dixon-TWIST-VIBE technique for ultra-fast breast DCE-MRI: Comparison with the conventional GRE technique

PurposeThe aim of this study was to evaluate image quality of the CAIPIRINHA-Dixon-TWIST-Volume-Interpolated Breath-hold Examination (CDT-VIBE) technique for ultra-fast breast dynamic contrast enhanced (DCE) MRI with respect to conventional Gradient-Recalled Echo (GRE) technique. MethodsA total of 58 patients underwent a DCE-MRI based on CDT-VIBE sequence (temporal resolution: 11.9 s), immediately followed by 1 phase of a conventional T1 weighted GRE sequence (acquisition time: 68 s). The Signal-to-Noise Ratio (SNR) on phantom images, lesion/parenchyma signal ratio (LPSR), image quality, and morphological characterization were compared between the last phase of CDT-VIBE and conventional GRE images. The image quality was assessed by visual grading analysis (VGA). Reader agreement was assessed using Kappa analysis. ResultsThere was no significant difference in SNR (phantom) or LPSR (patient) between CDT-VIBE and conventional GRE images (P > 0.05). Significant parallel acquisition technique (PAT) noise and mild blurriness was observed on CDT-VIBE images. Visual grading analysis (VGA) confirmed significantly worse ratings for CDT-VIBE compared to the conventional GRE sequence in terms of PAT noise, lesion’s internal feature clarity, and therefore overall image quality (area under contrast curve [AUC] values: 0.578 ‒ 0.764, P < 0.05), but edge sharpness and lesion conspicuity were equivalent (P > 0.05). Kappa analysis revealed good agreement on image quality scores (к = 0.725 ‒ 0.908) and on morphologic terms (к = 0.745–1.000). ConclusionThe CDT-VIBE sequence provides excellent spatial resolution and adequate image quality in ultra-fast breast DCE-MRI. Further improvement in PAT noise and internal structure blurriness may be necessary.

Optimizing neuromelanin contrast in the substantia nigra and locus coeruleus using a magnetization transfer contrast prepared 3D gradient recalled echo sequence

Neuromelanin (NM) loss in the substantia nigra (SN) and locus coeruleus (LC) is being investigated as an imaging biomarker for Parkinson’s disease (PD) using magnetization transfer contrast (MTC) magnetic resonance imaging. The MTC pulse operates in a way to suppress tissue with high macromolecular content thereby highlighting the presence of NM in the LC and the SN. The MTC pulse also leads to a reduction in the effective T1 of the tissue. In the past, a 3D gradient echo (GRE) sequence has usually been run with a single flip angle (FA) generally to highlight the T1 shortening effect when trying to visualize NM. We contend that the NM will be best seen with a low FA (relative to the Ernst angle) because the NM has high water content relative to the surrounding tissues. Therefore, the goal of this paper was to optimize the NM contrast in the SN and LC as a function of flip angle using a 3D GRE MTC strategically acquired gradient echo (STAGE) imaging approach. In order to accomplish this, short repeat time (62 ​ms), 3D GRE imaging data were collected for 7 different flip angles ranging from 5° to 40° for 14 healthy volunteers (age range 24–43 years, mean ​± ​SD ​= ​34.8 ​± ​6.0 years, 6 males). By measuring the contrast-to-noise ratio between these structures and the surrounding tissues, we found that the FA showing the best NM contrast was 15° - 20° for the SN and 20° - 25° for the LC. Using STAGE imaging with just two flip angles (15° and 30°) made it possible to quantify not only tissue properties such as T1 and proton density but also to generate synthetic MTC images at an arbitrary FA. These synthetic images make it possible to optimize the contrast for any changes in tissue property that might occur in the LC or SN as a function of age or disease. In conclusion, practically, two scans could be collected in roughly 7 ​min each for both FAs in a standard clinical imaging setting to evaluate the signal intensity and volume of the NM in the LC and SN.

Clinical implementation of MRI-based organs-at-risk auto-segmentation with convolutional networks for prostate radiotherapy

BackgroundStructure delineation is a necessary, yet time-consuming manual procedure in radiotherapy. Recently, convolutional neural networks have been proposed to speed-up and automatise this procedure, obtaining promising results. With the advent of magnetic resonance imaging (MRI)-guided radiotherapy, MR-based segmentation is becoming increasingly relevant. However, the majority of the studies investigated automatic contouring based on computed tomography (CT).PurposeIn this study, we investigate the feasibility of clinical use of deep learning-based automatic OARs delineation on MRI.Materials and methodsWe included 150 patients diagnosed with prostate cancer who underwent MR-only radiotherapy. A three-dimensional (3D) T1-weighted dual spoiled gradient-recalled echo sequence was acquired with 3T MRI for the generation of the synthetic-CT. The first 48 patients were included in a feasibility study training two 3D convolutional networks called DeepMedic and dense V-net (dV-net) to segment bladder, rectum and femurs. A research version of an atlas-based software was considered for comparison. Dice similarity coefficient, 95% Hausdorff distances (HD95), and mean distances were calculated against clinical delineations. For eight patients, an expert RTT scored the quality of the contouring for all the three methods. A choice among the three approaches was made, and the chosen approach was retrained on 97 patients and implemented for automatic use in the clinical workflow. For the successive 53 patients, Dice, HD95 and mean distances were calculated against the clinically used delineations.ResultsDeepMedic, dV-net and the atlas-based software generated contours in 60 s, 4 s and 10-15 min, respectively. Performances were higher for both the networks compared to the atlas-based software. The qualitative analysis demonstrated that delineation from DeepMedic required fewer adaptations, followed by dV-net and the atlas-based software. DeepMedic was clinically implemented. After retraining DeepMedic and testing on the successive patients, the performances slightly improved.ConclusionHigh conformality for OARs delineation was achieved with two in-house trained networks, obtaining a significant speed-up of the delineation procedure. Comparison of different approaches has been performed leading to the succesful adoption of one of the neural networks, DeepMedic, in the clinical workflow. DeepMedic maintained in a clinical setting the accuracy obtained in the feasibility study.

Altered Functional Connectivity of Hypothalamus in Lifelong Premature Ejaculation Patients.

As one of the most prevalent sexual dysfunctions in men, lifelong premature ejaculation (PE) often leads to patient distress. The hypothalamus is implicated in the ejaculatory control of healthy males. However, we do not know whether the hypothalamus-related intrinsic connectivity is altered in lifelong PE patients. To investigate abnormal intrinsic connectivity of the hypothalamus in lifelong PE patients compared with healthy controls (HCs). Prospective pilot study using cross-sectional data of patients and HCs. Forty-seven lifelong PE patients and 30 HCs were included in this study. 3.0T MRI scanner for T1 -weighted imaging using spoiled gradient recalled echo sequence and functional imaging using a single-shot gradient recalled echo sequence. Preprocessing of MRI data and hypothalamus-seeded functional connectivity (FC) computation were performed using DPABI4.1. The two-sample t-test within SPM12 was adopted to examine possible alterations of intrinsic connectivity of hypothalamus in lifelong PE patients compared with HCs including anxiety and depression scores as covariates (false discovery rate-corrected, P < 0.05). The correlation analysis was then used to assess possible associations between the imaging findings and clinical features in the patient group (Bonferroni-corrected, P < 0.05). Compared with HCs, lifelong PE patients had decreased hypothalamus-seeded FC in the left orbitofrontal cortex, bilateral insula, superior temporal cortex, superior temporal pole, middle temporal cortex, left fusiform, right parahippocampal gyrus, and right cerebellum. The intravaginal ejaculatory latency time positively correlated with the mean z-score from the hypothalamus-insula (r = 0.45) and hypothalamus-cerebellum (r = 0.48) intrinsic connectivity, separately. We have shown that hypothalamus-seeded FC alterations and the correlations between the aforementioned abnormal FC alterations and intravaginal ejaculatory latency time. The current findings may promote the understanding of the hypothalamus-related neural mechanisms involved in the abnormal ejaculatory information processing in lifelong PE patients. 1 TECHNICAL EFFICACY STAGE: 3 J. Magn. Reson. Imaging 2020;52:778-784.

Utilization of Novel High-Resolution, MRI-Based Vascular Imaging Modality for Preoperative Stereoelectroencephalography Planning in Children: A Technical Note

Introduction: Stereoelectroencephalography (SEEG) is a powerful intracranial diagnostic tool that requires accurate imaging for proper electrode trajectory planning to ensure efficacy and maximize patient safety. Computed tomography (CT) angiography and digital subtraction angiography are commonly used, but recent developments in magnetic resonance angiography allow for high-resolution vascular visualization without added risks of radiation. We report on the accuracy of electrode placement under robotic assistance planning utilizing a novel high-resolution magnetic resonance imaging (MRI)-based imaging modality. Methods: Sixteen pediatric patients between February 2014 and October 2017 underwent SEEG exploration for epileptogenic zone localization. A gadolinium-enhanced 3D T1-weighted spoiled gradient recalled echo sequence with minimum echo time and repetition time was applied for background parenchymal suppression and vascular enhancement. Electrode placement accuracy was determined by analyzing postoperative CT scans laid over preoperative virtual electrode trajectory paths. Entry point, target point, and closest vessel intersection were measured. Results: For any intersection along the trajectory path, 57 intersected vessels were measured. The mean diameter of an intersected vessel was 1.0343 ± 0.1721 mm, and 21.05% of intersections involved superficial vessels. There were 157 overall intersection + near-miss events. The mean diameter for an involved vessel was 1.0236 ± 0.0928 mm, and superficial vessels were involved in 20.13%. Looking only at final electrode target, 3 intersection events were observed. The mean diameter of an intersected vessel was 1.0125 ± 0.2227 mm. For intersection + near-miss events, 24 were measured. An involved vessel’s mean diameter was 1.1028 ± 0.2634 mm. For non-entry point intersections, 45 intersected vessels were measured. The mean diameter for intersected vessels was 0.9526 ± 0.0689 mm. For non-entry point intersections + near misses, 126 events were observed. The mean diameter for involved vessels was 0.9826 ± 0.1008 mm. Conclusion: We believe this novel sequence allows better identification of superficial and deeper subcortical vessels compared to conventional T1-weighted gadolinium-enhanced MRI.

Application of compressed sensing using chirp encoded 3D GRE and MPRAGE sequences

AbstractAn implementation of Non‐Fourier chirp‐encoding in 3D Gradient Recalled Echo (GRE), susceptibility‐weighted imaging (SWI) and Magnetization Prepared Rapid Gradient Echo (MPRAGE) sequences is presented with compressive sensing reconstruction. 3D GRE and MPRAGE sequences were designed, in which the phase encoding (PE) direction was encoded with spatially selective chirp encoding Radio Frequency (RF) pulses, while the slice and the readout directions were Fourier encoded using gradients. During each excitation along the PE direction, a different spatially‐selective RF excitation pulse was used to encode the PE direction with a complete set of unitary chirp encoding basis. Multichannel compressive sensing reconstruction on the undersampled in vivo data demonstrated that images reconstructed from chirp encoded data were able to preserve the spatial resolution better than the Fourier encoding. The mean Structural Similarity (SSIM) across five subjects at the acceleration factor of 6, for chirp encoded MPRAGE was 0.934 compared to 0.912 for Fourier encoded MPRAGE. The implementation of prospective undersampling demonstrated the feasibility of using chirp encoding in clinical practice for accelerated imaging. The minimum intensity projection of the compressive sensing (CS) reconstructed susceptibility weighted images revealed that chirp encoding is able to delineate small vessels better than the Fourier encoding with the SSIM of 0.960 for chirp encoding compared to the SSIM of 0.949 for the Fourier encoding. Improved performance of chirp encoding for CS reconstruction and SWI, along with the feasibility of implementation makes them a practical candidate for clinical MRI scans.

Magnetic Resonance Imaging Evaluation of Cerebral Microbleeds: A Comparative Analysis of Susceptibility Weighted Imaging and T2 Gradient Recalled Echo Sequences

Introduction: Cerebral Microbleeds (CMBs) are increasingly recognised as an important predictor of small vessel disease and cannot be detected on routine Computed Tomography (CT) or Magnetic Resonance Imaging (MRI) sequences. Aim: CMBs on MRI and to compare the sensitivity of Susceptibility Weighted Imaging (SWI) and T2* Gradient Recalled Echo (GRE) sequences in detection of these microbleeds. Also, to evaluate association between topography (size, number and location) of CMBs and various risk factors. Materials and Methods: This Prospective Observational analytical study comprised of 67 patients with CMBs who were evaluated with Siemens 1.5 Tesla MRI machine. T2*-weighted GRE sequence and SWI were taken in all the patients in addition to routine MRI sequences. Two observers blinded to clinical information, independently interpreted the T2*GRE and SWI sequences. Both observers recorded the topographical details of CMBs which included presence, number, size and location and their association with various risk factors (hypertension, diabetes, smoking and hyperlipidemia). Inter-rater agreement for the number of CMBs on SWI and T2*GRE was calculated using Cohen’s Kappa (κ) as measure of agreement. Intra-Class Correlation Coefficient (ICC) for reliability index in test-retest, intra-rater and inter-rater reliability was also analysed. The intra-rater reliabilities of each rater were compared. The correlations between CMBs and risk factors was performed with Pearson’s correlation Coefficient (r). The p-value &lt;0.05 was considered statistically significant. Results: The SWI with its Reverse Phase (RP) detected more number of CMBs as compared to T2*GRE. Majority of the subjects (71.6%) had more than five CMBs. CMBs ≥5 mm had a strong correlation with both hypertension and diabetes as compared to CMBs &lt;5 mm. There was a higher frequency of patients with lobar CMBs (89.6%) followed by the deep location (70.1%). An almost perfect agreement was found between both observers for number of CMBs on RP SWI with ‘κ’ value of 0.97a (0.96-0.98) in contrast to a weak agreement on RP T2*GRE with κ=0.52a (0.40-0.64). For SWI, an almost perfect reliability was found (ICC=0.998) as compared to a moderate reliability on T2*GRE (ICC=0.6826). An excellent reliability was seen for size of CMBs &lt;5 mm on RP SWI (ICC 0.998). Conclusion: SWI offered greater reliability and sensitivity for CMB detection as compared to the T2*GRE sequence and is presently the gold standard sequence of MRI for quantifying CMBs. The burden of CMBs may further indicate inappropriately treated hypertension and diabetes.

Cerebral microbleed incidence, relationship to amyloid burden: The Mayo Clinic Study of Aging.

To determine the incidence of cerebral microbleeds (CMBs) and the association of amyloid PET burden with incident CMBs. A total of 651 participants, age ≥50 years (55% male), underwent 3T MRI scans with ≥2 separate T2*-weighted gradient recalled echo sequences from October 2011 to August 2017. Eighty-seven percent underwent 11C Pittsburgh compound B (PiB) PET scans. Age-specific CMB incidence rates were calculated by using the piecewise exponential model. Using structural equation models (SEMs), we assessed the effect of amyloid load and baseline CMBs on future CMBs after considering the direct and indirect age, sex, vascular risk factors, and APOE effects. Participants' mean age (SD) was 69.8 (10.0) years at baseline MRI, and 111 participants (17%) had ≥1 baseline CMB. The mean (SD) of the time interval between scans was 2.7 (1.0) years. The overall population incidence rate for CMBs was 3.6/100 person-years and increased with age: from 1.5/100 new CMBs at age 50 to 11.6/100 person-years at age 90. Using the piecewise exponential model regression, the incidence rates increased with age and the presence of baseline CMBs. The SEMs showed that (1) increasing age at MRI or carrying an APOE4 allele was associated with more amyloid at baseline, and higher amyloid, particularly occipital amyloid load, in turn increased the risk of a new lobar CMB; and (2) the presence of CMBs at baseline increased the risk of a lobar CMB and had a larger effect size than amyloid load. Age and APOE4 carrier status act through amyloid load to increase the risk of subsequent lobar CMBs, but the presence of baseline CMBs is the most important risk factor for future CMBs.

Improved pulmonary 129 Xe ventilation imaging via 3D-spiral UTE MRI.

Hyperpolarized 129 Xe MRI characterizes regional lung ventilation in a variety of disease populations, with high sensitivity to airway obstruction in early disease. However, ventilation images are usually limited to a single breath-hold and most-often acquired using gradient-recalled echo sequences with thick slices (~10-15 mm), which increases partial-volume effects, limits ability to observe small defects, and suffers from imperfect slice selection. We demonstrate higher-resolution ventilation images, in shorter breath-holds, using FLORET (Fermat Looped ORthogonally Encoded Trajectories), a center-out 3D-spiral UTE sequence. In vivo human adult (N = 4; 2 healthy, 2 with cystic fibrosis) 129 Xe images were acquired using 2D gradient-recalled echo, 3D radial, and FLORET. Each sequence was acquired at its highest possible resolution within a 16-second breath-hold with a minimum voxel dimension of 3 mm. Images were compared using 129 Xe ventilation defect percentage, SNR, similarity coefficients, and vasculature cross-sections. The FLORET sequence obtained relative normalized SNR, 40% greater than 2D gradient-recalled echo (P = .012) and 26% greater than 3D radial (P = .067). Moreover, the FLORET images were acquired with 3-fold-higher nominal resolution in a 15% shorter breath-hold. Finally, vasculature was less prominent in FLORET, likely due to diminished susceptibility-induced dephasing at shorter TEs afforded by UTE sequences. The FLORET sequence yields higher SNR for a given resolution with a shorter breath-hold than traditional ventilation imaging techniques. This sequence more accurately measures ventilation abnormalities and enables reduced scan times in patients with poor compliance and severe lung disease.