Pulsation Artifacts Research Articles

Reducing blood flow pulsation artifacts in 3D time‐of‐flight angiography by locally scrambling the order of the acquisition at 3 T and 7 T

Reducing blood flow pulsation artifacts in <scp>3D</scp> time‐of‐flight angiography by locally scrambling the order of the acquisition at <scp>3</scp> T and <scp>7 T</scp>

Classification of Parkinson's disease by deep learning on midbrain MRI.

Susceptibility map weighted imaging (SMWI), based on quantitative susceptibility mapping (QSM), allows accurate nigrosome-1 (N1) evaluation and has been used to develop Parkinson's disease (PD) deep learning (DL) classification algorithms. Neuromelanin-sensitive (NMS) MRI could improve automated quantitative N1 analysis by revealing neuromelanin content. This study aimed to compare classification performance of four approaches to PD diagnosis: (1) N1 quantitative "QSM-NMS" composite marker, (2) DL model for N1 morphological abnormality using SMWI ("Heuron IPD"), (3) DL model for N1 volume using SMWI ("Heuron NI"), and (4) N1 SMWI neuroradiological evaluation. PD patients (n = 82; aged 65 ± 9 years; 68% male) and healthy-controls (n = 107; 66 ± 7 years; 48% male) underwent 3 T midbrain MRI with T2*-SWI multi-echo-GRE (for QSM and SMWI), and NMS-MRI. AUC was used to compare diagnostic performance. We tested for correlation of each imaging measure with clinical parameters (severity, duration and levodopa dosing) by Spearman-Rho or Kendall-Tao-Beta correlation. Classification performance was excellent for the QSM-NMS composite marker (AUC = 0.94), N1 SMWI abnormality (AUC = 0.92), N1 SMWI volume (AUC = 0.90), and neuroradiologist (AUC = 0.98). Reasons for misclassification were right-left asymmetry, through-plane re-slicing, pulsation artefacts, and thin N1. In the two DL models, all 18/189 (9.5%) cases misclassified by Heuron IPD were controls with normal N1 volumes. We found significant correlation of the SN QSM-NMS composite measure with levodopa dosing (rho = -0.303, p = 0.006). Our data demonstrate excellent performance of a quantitative QSM-NMS marker and automated DL PD classification algorithms based on midbrain MRI, while suggesting potential further improvements. Clinical utility is supported but requires validation in earlier stage PD cohorts.

Reducing blood flow pulsation artifacts in 3D time-of-flight angiography by locally scrambling the order of the acquisition at 3 T and 7 T.

Non-contrast-enhanced time of flight (TOF) is a standard method for magnetic resonance angiography used to depict vessel morphology. TOF is commonly performed with a 3D steady-state acquisition, employing a short repetition time to support high resolution imaging. At 7 T, TOF exhibits substantial increase in SNR and contrast, improving its clinical value. However, one of the remaining challenges, exacerbated at 7 T, is the presence of artifacts due to pulsatile blood flow, especially near major blood vessels. In this study we examine a method to significantly reduce these artifacts. We recently introduced a new "local-scrambling" approach that semi-randomizes the acquisition order of the phase encodes, to achieve a controllable cutoff frequency above which the artifacts are drastically reduced. With this approach, artifacts resulting from fast local fluctuations such as cardiac pulsation are significantly reduced. In this study, we explore the ability of this local-scrambling approach to reduce pulsatile blood flow artifacts in a 3D TOF acquisition. Cartesian line-by-line and center-out ordering, with and without local-scrambling, were compared in simulations and in human brain imaging at 3 and 7 T scanners. In the simulations the artifact intensity showed a 10-fold reduction using local-scrambling compared to line-by-line and 4-fold compared to center-out ordering. In vivo results show that artifacts are much more pronounced at 7 T compared to 3 T, and in both cases they are effectively reduced by local-scrambling. Local-scrambling improves image quality for both line-by-line and center-out ordering. This approach can easily be implemented in the scanner without any changes to the reconstruction.

Neuroradiological characteristics of hydrocephalus due to idiopathic extraventricular CSF pathways obstruction

The development of research on CSF flow disorders made it possible initially to divide hydrocephalus into «communicating» and «non-communicating», and subsequently to distinguish the concepts of «intraventricular» and «extraventricular» obstruction. Improvement of radiological imaging technologies has allowed determining the exact level of CSF obstruction. In some cases, CSF flow disorders combine signs of different forms of hydrocephalus. Their correct classification allows selecting the type of surgical treatment, which reduces the rate of complications and patient»s dependence on the doctor. Purpose of the research: To study the radiological signs of hydrocephalus in idiopathic obstruction at the level of the posterior cranial fossa cisterns. Materials and methods. This study included adult patients (18 years old and over) whose disease was idiopathic in nature. From 2007 to 2020, 289 patients diagnosed with idiopathic hydrocephalus were treated at the N. N. Burdenko National Medical Research Center of Neurosurgery. Of these, 65 patients (18.7 %) had clinical and radiological signs of extraventricular obstruction. The male to female ratio was 25 and 40 (38.5 % and 61.5 %), respectively. A variety of radiological signs were assessed and their origin and occurrence in various forms of idiopathic hydrocephalus were determined. Results. FOHR was the highest (compared with other forms of idiopathic hydrocephalus (mean 0.52)). Other ventricular indices were also high. None of them correlated with the patient»s condition. Ventral dislocation of the premamillary membrane was detected in 89.2 %. Turkish saddle was of normal size in 51 (78.4 %) patients, while its enlargement was found in 13 (20 %) patients. A change in the periventricular signal was noted in 18.4 %. Aqueduct and IV ventricle outlets were patent in all cases as evidenced by CSF pulsation artifacts in T2 3D CUBE. The cerebral aqueduct was dilated in 63 (96.9 %) patients. Enlargement of the cisterna magna associated with hypotrophy of the caudal cerebellum was noted in 90.7 %, and this sign was significant for extraventricular cisternal obstruction (p &lt;0.001). In addition to the T2 mode, the presence of sagittal sections in cisternography modes (FIESTA or CISS) was a prerequisite. By means of these modes, the ventral dislocation of the premamillary membrane was more clearly visualized, the presence of obstacles to the CSF flow in the cerebral aqueduct was excluded, and, most importantly, it was possible to determine the presence of additional membranes in the subarachnoid spaces between the ventral surface of the brain stem and the clivus. These were found in 100 % of the patients, which was also a significant pathognomonic sign (p &lt; 0.001). Conclusion. The MRI picture of hydrocephalus with obstruction at the level of the posterior cranial fossa cisterns has specific signs. It combines the signs of other forms of hydrocephalus, chronic disease in combination with symptoms of the CSF pathways obstruction. It can be classified into a separate form and both endoscopic and shunt surgery can be used for treatment.

Comparing 1.5 T and 3.0 T MR data for 3D visualization of neurovascular relationships in the posterior fossa

BackgroundNeurovascular relationships in the posterior fossa are more frequently investigated due to the increasing availability of 3.0 Tesla MRI. For an assessment with 3D visualization, no systematic analyzes are available so far and the question arises as to whether 3.0 Tesla MRI should be given preference over 1.5 Tesla MRI.MethodsIn a prospective study, a series of 25 patients each underwent MRI investigations with 3D-CISS and 3D-TOF at 1.5 and 3.0 Tesla. For both field strengths separately, blood vessel information from the TOF data was fused into the CISS data after segmentation and registration. Four visualizations were created for each field strength, with and without optimization before and after fusion, which were evaluated with a rating system and verified with the intraoperative situation.ResultsWhen only CISS data was used, nerves and vessels were better visualized at 1.5 Tesla. After fusion, flow and pulsation artifacts were reduced in both cases, missing vessel sections were supplemented at 3.0 Tesla and 3D visualization at 1.5 and 3.0 Tesla led to anatomically comparable results. By subsequent manual correction, the remaining artifacts were further eliminated, with the 3D visualization being significantly better at 3.0 Tesla, since the higher field strength led to sharper contours of small vessel and nerve structures.Conclusion3D visualizations at 1.5 Tesla are sufficiently detailed for planning microvascular decompression and can be used without restriction. Fusion further improves the quality of 3D visualization at 3.0 Tesla and enables an even more accurate delineation of cranial nerves and vessels.

Diagnostic Performance of 3D-NERVE as an Adjunct to Electromyography for the Assessment of Brachial Plexus Injury in Infants.

Objective: This study aimed to explore diagnostic performance of 3D-NERVE as an adjunct to electromyography for the assessment of brachial plexus injury in infants. Methods: Imaging of infants with brachial plexus injury using 3D-NERVE and/or 3D-STIR from 2019 to 2022 were reviewed. Images were evaluated between the 2 sequences for nerve-to-fat ratio, nerve-to-muscle ratio, muscle-to-fat ratio, fat suppression homogeneity, and display rate of brachial plexus branches. Results: This study included 37 infants who were referred for a clinical diagnosis of brachial plexus injury. A total of 21 infants accepted 3D-NERVE sequence scanning, and 16 infants accepted 3D-NERVE and 3D-STIR sequences scanning. The results of examination were generally consistent with electromyography. The 2 sequences were compared, yielding the following results. There were no pulsation artifacts (0/16), and 1 case with heterogeneous fat saturation (1/16) was seen on 3D-NERVE. There were no pulsation artifacts (0/16), and 5 cases with heterogeneous fat saturation (5/16) were seen on 3D-STIR. 3D-NERVE performed better (P < .05) for nerve-to-fat and nerve-to-muscle ratios compared with 3D-STIR, and no significant difference in the muscle-to-fat ratio (P > .05). The 3D-NERVE and STIR helped depict 100% (16/16) of the brachial roots and brachial plexus trunk. Brachial plexus bundles and brachial plexus branches were observed in 93.75% (15/16) and 68.75% (11/16) of the 3D-NERVE and 93.75% (15/16) and 62.5% (10/16) of the 3D-STIR, respectively. The differences were not statistically significant (P > .05). Conclusion: Nerve trauma was better visualized with the 3D-NERVE, which is an effective adjunct to electromyography for doctors to assess brachial plexus injury and consequently helps in better treatment planning.

Feature-guided deep learning reduces signal loss and increases lesion CNR in diffusion-weighted imaging of the liver

PurposeThis research aims to develop a feature-guided deep learning approach and compare it with an optimized conventional post-processing algorithm in order to enhance the image quality of diffusion-weighted liver images and, in particular, to reduce the pulsation-induced signal loss occurring predominantly in the left liver lobe. MethodsData from 40 patients with liver lesions were used. For the conventional approach, the best-suited out of five examined algorithms was chosen. For the deep learning approach, a U-Net was trained. Instead of learning “gold-standard” target images, the network was trained to optimize four image features (lesion CNR, vessel darkness, data consistency, and pulsation artifact reduction), which could be assessed quantitatively using manually drawn ROIs. A quality score was calculated from these four features. As an additional quality assessment, three radiologists rated different features of the resulting images. ResultsThe conventional approach could substantially increase the lesion CNR and reduce the pulsation-induced signal loss. However, the vessel darkness was reduced. The deep learning approach increased the lesion CNR and reduced the signal loss to a slightly lower extent, but it could additionally increase the vessel darkness. According to the image quality score, the quality of the deep-learning images was higher than that of the images obtained using the conventional approach. The radiologist ratings were mostly consistent with the quantitative scores, but the overall quality ratings differed among the readers. ConclusionUnlike the conventional algorithm, the deep-learning algorithm increased the vessel darkness. Therefore, it may be a viable alternative to conventional algorithms.

Comparison Between EPI DWI and PROPELLER DWI in Brain MR Imaging

EPI DWI is a routinely used sequence in brain imaging but it has limitations when it comes to SNR and artifact reduction. PROPELLER DWI has the benefit of improving image quality compared to EPI DWI. The aim of this study is to compare the EPI DWI sequence in brain MR imaging with the PROPELLER DWI sequence. The objective is to identify which sequence is more beneficial in brain imaging by evaluating image quality and the depiction of pathologies. A total of 101 patients (55 females and 46 males, mean age 56 years) underwent brain MRI examination on a 1.5 T scanner. EPI DWI and PROPELLER DWI sequences were acquired in every exam and were reviewed by 2 radiologists. The images were evaluated by performing a quantitative analysis based on Relative Contrast and a qualitative analysis (overall image quality, conspicuousness of lesions, artifact reduction, etc.). In both the qualitative and quantitative analysis PROPELLER DWI achieved better results than EPI DWI. PROPELLER DWI showed statistical significance in the overall image quality (P < 0.001), the elimination of susceptibility (P < 0.001) and flow pulsation artifacts (P < 0.001), as well as in the contrast between CSF with white (P < 0.001) and grey matter (P < 0.001). Also, PROPELLER DWI presented better delineation of pathologies like ischemic strokes, metastasis, tumors and vasogenic edemas than conventional EPI DWI. PROPELLER DWI was the preferred sequence during the image evaluation. Compared to EPI DWI, PROPELLER DWI managed to reduce susceptibility and flow pulsation whilst achieving higher image quality and lesion delineation and earlier depiction of ischemic strokes than the conventional EPI DWI. PROPELLER DWI may be incorporated in brain MR imaging replacing EPI DWI.

Pulsation artifact removal from intra-operatively recorded local field potentials using sparse signal processing and data-specific dictionary.

Neural recordings frequently get contaminated by ECG or pulsation artifacts. These large amplitude components can mask the neural patterns of interest and make the visual inspection process difficult. The current study describes a sparse signal representation strategy that targets to denoise pulsation artifacts in local field potentials (LFPs) recorded intraoperatively. To estimate the morphology of the artifact, we first detect the QRS-peaks from the simultaneously recorded ECG trace as an anchor point. After the LFP data has been epoched with respect to each beat, a pool of raw data segments of a specific length is generated. Using the K-singular value decomposition (K-SVD) algorithm, we constructed a data-specific dictionary to represent each contaminated LFP epoch in a sparse fashion. Since LFP is aligned to each QRS complex and the background neural activity is uncorrelated to the anchor points, we assumed that constructed dictionary will be formed to mainly represent the pulsation artifact. In this scheme, we performed an orthogonal matching pursuit to represent each LFP epoch as a linear combination of the dictionary atoms. The denoised LFP data is thus obtained by calculating the residual between the raw LFP and its approximation. We discuss and demonstrate the improvements in denoised data and compare the results with respect to principal component analysis (PCA). We noted that there is a comparable change in the signal for visual inspection to observe various oscillating patterns in the alpha and beta bands. We also see a noticeable compression of signal strength in the lower frequency band (<13 Hz), which was masked by the pulsation artifact, and a strong increase in the signal-to-noise ratio (SNR) in the denoised data.Clinical Relevance- Pulsation artifact can mask relevant neural activity patterns and make their visual inspection difficult. Using sparse signal representation, we established a new approach to reconstruct the quasiperiodic pulsation template and computed the residue signal to achieve noise-free neural activity.

3D Synthetic Brain MRI with Compressed Sensing: Can It Be a Promising Way Forward for Daily Neuroimaging?

Synthetic MRI can provide multiple contrast-weighted brain images with high resolution from a single scan via a 3D sequence using an interleaved Look-Locker acquisition sequence with a T2 preparation pulse (3D-QALAS). This study aimed to assess the diagnostic image quality of 3D synthetic MRI using compressed sensing (CS) in clinical practice. We retrospectively reviewed the imaging data of 47 patients who underwent brain MRI, including 3D synthetic MRI using CS in a single session, between December 2020 and February 2021. Two neuroradiologists independently evaluated the overall image quality, anatomic demarcation, and artifacts for synthetic 3D T1-weighted, T2-weighted, FLAIR, phase-sensitive inversion recovery (PSIR), and double inversion recovery images, using a 5-point Likert scale. The interobserver agreement between the two readers was assessed using percent agreement and weighted κ statistics. The overall image quality of 3D synthetic T1WI and PSIR was good to excellent, with easy or excellent anatomic demarcation and mild or no visible artifact. However, other 3D synthetic MRI-derived images showed insufficient image quality and anatomic demarcation with marked CSF pulsation artifacts. In particular, 3D synthetic FLAIR showed high-signal artifacts on the brain surface. 3D synthetic MRI, at its current status, cannot completely replace conventional brain MRI in daily clinical practice. However, 3D synthetic MRI can achieve scan-time reduction using CS and parallel imaging and may be useful for motion-prone or pediatric patients requiring 3D images where time-efficiency is important.

VALUE OF PERIODICALLY ROTATED OVERLAPPING PARALLEL LINES WITH ENHANCED RECONSTRUCTION TECHNIQUE COMPARED TO T2 WEIGHTED TURBO SPIN ECHO SEQUENCE ON ROTATOR CUFF INJURIES IN MRI SHOULDER.

Objective: The purpose of the study is to analyze the uses of conventional T2 sequences and PROPELLER technique in view of artifact reduction, increase the image quality and identify signs of pathology on shoulder magnetic resonance imaging. A total number of 36 Materials and Method: patients who underwent shoulder MRI with pain intolerance were included in the study. We used PROPELLER and without PROPELLER technology in the same participants. The MRI scans were evaluated separately by qualied musculoskeletal radiologists. Artifacts, overall image quality, and delineation of several anatomic structures were all investigated in relation to the diagnostic value of an MR arthrography examination. The signicance of propeller was analyzed by implementing Mann Whitney U test. The TSE sequences had worse pulsation artifacts and Results: better overall image quality than PROPELLER sequences. In both Coronal Oblique and Sagittal Oblique approach, delineation of all addressed anatomic structures was much better with PROPELLER sequences than with TSE. The PROPELLER approach for MRI of the Conclusion: shoulder minimizes the frequency of sequences with diagnostic impairment owing to motion artifacts and enhances picture quality when compared to traditional TSE sequences.

Deep learning reconstruction in pediatric brain MRI: comparison of image quality with conventional T2-weighted MRI.

Deep learning-based MRI reconstruction has recently been introduced to improve image quality. This study aimed to evaluate the performance of deep learning reconstruction in pediatric brain MRI. A total of 107 consecutive children who underwent 3.0T brain MRI were included in this study. T2-weighted brain MRI was reconstructed using the three different reconstruction modes: deep learning reconstruction, conventional reconstruction with an intensity filter, and original T2 image without a filter. Two pediatric radiologists independently evaluated the following image quality parameters of three reconstructed images on a 5-point scale: overall image quality, image noisiness, sharpness of gray-white matter differentiation, truncation artifact, motion artifact, cerebrospinal fluid and vascular pulsation artifacts, and lesion conspicuity. The subjective image quality parameters were compared among the three reconstruction modes. Quantitative analysis of the signal uniformity using the coefficient of variation was performed for each reconstruction. The overall image quality, noisiness, and gray-white matter sharpness were significantly better with deep learning reconstruction than with conventional or original reconstruction (all P < 0.001). Deep learning reconstruction had significantly fewer truncation artifacts than the other two reconstructions (all P < 0.001). Motion and pulsation artifacts showed no significant differences among the three reconstruction modes. For 36 lesions in 107 patients, lesion conspicuity was better with deep learning reconstruction than original reconstruction. Deep learning reconstruction showed lower signal variation compared to conventional and original reconstructions. Deep learning reconstruction can reduce noise and truncation artifacts and improve lesion conspicuity and overall image quality inpediatric T2-weighted brain MRI.

Reduction of the cardiac pulsation artifact and improvement of lesion conspicuity in flow-compensated diffusion images in the liver-A quantitative evaluation of postprocessing algorithms.

To enhance image quality of flow-compensated diffusion-weighted liver MRI data by increasing the lesion conspicuity and reducing the cardiac pulsation artifact using postprocessing algorithms. Diffusion-weighted image data of 40 patients with liver lesions had been acquired at 1.5T. These data were postprocessed with 5 different algorithms (weighted averaging, p-mean, percentile, outlier exclusion, and exception set). Four image properties of the postprocessed data were evaluated for optimizing the algorithm parameters. These properties were the lesion to tissue contrast-to-noise ratio (CNR), the reduction of the cardiac pulsation artifact, the data consistency, and the vessel darkness. They were combined into a total quality score ( set to 1 for the trace-weighted reference image), which was used to rate the image quality objectively. The weighted averaging algorithm performed best according to the total quality score ( ). The further ranking was outlier exclusion algorithm ( ), p-mean algorithm ( ), percentile algorithm ( ), and exception set algorithm ( ). All optimized algorithms except for the exception set algorithm corrected the pulsation artifact and increased the lesion CNR. Changes in were significant for all optimized algorithms except for the percentile algorithm. Liver ADC was significantly reduced (except for the exception set algorithm), particularly in the left lobe. Postprocessing algorithms should be used for flow-compensated liver DWI. The proposed weighted averaging algorithm seems to be suited best to increase the image quality of artifact-corrupted flow-compensated diffusion-weighted liver data.

Magnetic resonance tractography of the brachial plexus: step-by-step

BackgroundMagnetic resonance (MR) tractography of the brachial plexus (BP) is challenging due to different factors such as motion artifacts, pulsation artifacts, signal-to-noise ratio, spatial resolution; eddy currents induced geometric distortions, sequence parameters and choice of used coils. Notably challenging is the separation of the peripheral nerve bundles and skeletal muscles as both structures have similar fractional anisotropy values. We proposed an algorithm for robust visualization and assessment of BP root bundles using the segmentation of the spinal cord (SSC, C4-T1) as seed points for the initial starting area for the fibre tracking algorithm.MethodsTwenty-seven healthy volunteers and four patients with root avulsions underwent magnetic resonance imaging (MRI) examinations on a 3T MR scanner with optimized measurement protocols for diffusion-weighted images and coronal T2 weighted 3D short-term inversion recovery sampling perfection with application optimized contrast using varying flip angle evaluation sequences used for BP fibre reconstruction and MR neurography (MRN). The fibre bundles reconstruction was optimized in terms of eliminating the skeletal muscle fibres contamination using the SSC and the tracking threshold of the normalized quantitative anisotropy (NQA) on reconstruction of the BP. In our study, the NQA parameter has been used for fiber tracking instead of fractional anisotropy (FA). The diffusion data were processed in individual C4-T1 root bundles using the generalized q-sampling imaging (GQI) algorithm. Calculated diffusion parameters were statistically analysed using the two-sample t-test. The MRN was performed in MedINRIA and post-processed using the maximum intensity projection (MIP) method to demonstrate BP root bundles in multiple planes.ResultsIn control subjects, no significant effect of laterality in diffusion parameters was found (P>0.05) in the BP. In the central part of the BP, a significant difference between control subjects and patients at P=0.02 was found in the NQA values. Other diffusion parameters were not significantly different.ConclusionsUsing NQA instead of FA in the proposed algorithm allowed for a better separation of muscle and root nerve bundles. The presented algorithm yields a high quality reconstruction of the BP bundles that may be helpful both in research and clinical practice.

Flow-compensated diffusion encoding in MRI for improved liver metastasis detection.

Magnetic resonance (MR) diffusion-weighted imaging (DWI) is often used to detect focal liver lesions (FLLs), though DWI image quality can be limited in the left liver lobe owing to the pulsatile motion of the nearby heart. Flow-compensated (FloCo) diffusion encoding has been shown to reduce this pulsation artifact. The purpose of this prospective study was to intra-individually compare DWI of the liver acquired with conventional monopolar and FloCo diffusion encoding for assessing metastatic FLLs in non-cirrhotic patients. Forty patients with known or suspected multiple metastatic FLLs were included and measured at 1.5 T field strength with a conventional (monopolar) and a FloCo diffusion encoding EPI sequence (single refocused; b-values, 50 and 800 s/mm2). Two board-certified radiologists analyzed the DWI images independently. They issued Likert-scale ratings (1 = worst, 5 = best) for pulsation artifact severity and counted the difference of lesions visible at b = 800 s/mm² separately for small and large FLLs (i.e., < 1 cm or > 1 cm) and separately for left and right liver lobe. Differences between the two diffusion encodings were assessed with the Wilcoxon signed-rank test. Both readers found a reduction in pulsation artifact in the liver with FloCo encoding (p < 0.001 for both liver lobes). More small lesions were detected with FloCo diffusion encoding in both liver lobes (left lobe: six and seven additional lesions by readers 1 and 2, respectively; right lobe: five and seven additional lesions for readers 1 and 2, respectively). Both readers found one additional large lesion in the left liver lobe. Thus, flow-compensated diffusion encoding appears more effective than monopolar diffusion encoding for the detection of liver metastases.

Anterior Spinal Cord Ischemia due to an Acute Aortic Intramural Type B Hematoma

Anterior Spinal Cord Ischemia due to an Acute Aortic Intramural Type B Hematoma

Improvement of peripheral nerve visualization using a deep learning-based MR reconstruction algorithm

ObjectiveTo assess a new deep learning-based MR reconstruction method, “DLRecon,” for clinical evaluation of peripheral nerves. MethodsSixty peripheral nerves were prospectively evaluated in 29 patients (mean age: 49 ± 16 years, 17 female) undergoing standard-of-care (SOC) MR neurography for clinically suspected neuropathy. SOC-MRIs and DLRecon-MRIs were obtained through conventional and DLRecon reconstruction methods, respectively. Two radiologists randomly evaluated blinded images for outer epineurium conspicuity, fascicular architecture visualization, pulsation artifact, ghosting artifact, and bulk motion. ResultsDLRecon-MRIs were likely to score better than SOC-MRIs for outer epineurium conspicuity (OR = 1.9, p = 0.007) and visualization of fascicular architecture (OR = 1.8, p < 0.001) and were likely to score worse for ghosting (OR = 2.8, p = 0.004) and pulsation artifacts (OR = 1.6, p = 0.004). There was substantial to almost-perfect inter-reconstruction method agreement (AC = 0.73–1.00) and fair to almost-perfect interrater agreement (AC = 0.34–0.86) for all features evaluated. DLRecon-MRI had improved interrater agreement for outer epineurium conspicuity (AC = 0.71, substantial agreement) compared to SOC-MRIs (AC = 0.34, fair agreement). In >80% of images, the radiologist correctly identified an image as SOC- or DLRecon-MRI. DiscussionOuter epineurium and fascicular architecture conspicuity, two key morphological features critical to evaluating a nerve injury, were improved in DLRecon-MRIs compared to SOC-MRIs. Although pulsation and ghosting artifacts increased in DLRecon images, image interpretation was unaffected.

Spiral 2D T2-Weighted TSE Brain MR Imaging: Initial Clinical Experience.

Spiral MR imaging may enable improved image quality and higher scan speeds than Cartesian trajectories. We sought to compare a novel spiral 2D T2-weighted TSE sequence with a conventional Cartesian and an artifact-robust, non-Cartesian sequence named MultiVane for routine clinical brain MR imaging. Thirty-one patients were scanned with all 3 sequences (Cartesian, 4 minutes 14 seconds; MultiVane, 2 minutes 49 seconds; spiral, 2 minutes 12 seconds) on a standard clinical 1.5T MR scanner. Three readers described the presence and location of abnormalities and lesions and graded images qualitatively in terms of overall image quality, the presence of motion and pulsation artifacts, gray-white matter differentiation, lesion conspicuity, and subjective preference. Image quality was objectivized by measuring the SNR and the coefficients of variation for CSF, GM, and WM. Spiral achieved a scan time reduction of 51.9% and 21.9% compared with Cartesian and MultiVane, respectively. The number and location of lesions were identical among all sequences. As for the qualitative analysis, interreader agreement was high (Krippendorff α > .75). Spiral and MultiVane both outperformed the Cartesian sequence in terms of overall image quality, the presence of motion artifacts, and subjective preference (P < .001). In terms of the presence of pulsation artifacts, gray-white matter differentiation, and lesion conspicuity, all 3 sequences performed similarly well (P > .15). Spiral and MultiVane outperformed the Cartesian sequence in coefficient of variation WM and SNR (P < .01). Spiral 2D T2WI TSE is feasible for routine structural brain MR imaging and offers high-quality, artifact-robust brain imaging in short scan times.

Three - dimensional fluid attenuated inversion recovery sequence on 3 tesla magnetic resonace imaging in cranial nerve pathologies: Two case reports

Three - dimensional fluid attenuated inversion recovery sequence (3D-FLAIR) was introduced as a practical sequence which helps to reduce the cerebrospinal fluid pulsation and flow artefacts of conventional 2D acquisition and brings contiguous slices, ability in reformatting in variable planes which are typical features of 3D acquisition. 3D - FLAIR has been applied on assessing several neurologic pathologies. In this article, we introduce the application of 3D - FLAIR sequence without contrast enhancement on detecting abnormalities of cranial nerve pathology by presenting two cases, acute vestibular neuritis and facial nerve palsy. We suggest that 3D - FLAIR is the relatively useful sequence in detecting cranial nerve pathologies.

Evaluation of Ultrafast Wave-Controlled Aliasing in Parallel Imaging 3D-FLAIR in the Visualization and Volumetric Estimation of Cerebral White Matter Lesions.

Our aim was to evaluate an ultrafast 3D-FLAIR sequence using Wave-controlled aliasing in parallel imaging encoding (Wave-FLAIR) compared with standard 3D-FLAIR in the visualization and volumetric estimation of cerebral white matter lesions in a clinical setting. Forty-two consecutive patients underwent 3T brain MR imaging, including standard 3D-FLAIR (acceleration factor = 2, scan time = 7 minutes 50 seconds) and resolution-matched ultrafast Wave-FLAIR sequences (acceleration factor = 6, scan time = 2 minutes 45 seconds for the 20-channel coil; acceleration factor = 9, scan time = 1 minute 50 seconds for the 32-channel coil) as part of clinical evaluation for demyelinating disease. Automated segmentation of cerebral white matter lesions was performed using the Lesion Segmentation Tool in SPM. Student t tests, intraclass correlation coefficients, relative lesion volume difference, and Dice similarity coefficients were used to compare volumetric measurements among sequences. Two blinded neuroradiologists evaluated the visualization of white matter lesions, artifacts, and overall diagnostic quality using a predefined 5-point scale. Standard and Wave-FLAIR sequences showed excellent agreement of lesion volumes with an intraclass correlation coefficient of 0.99 and mean Dice similarity coefficient of 0.97 (SD, 0.05) (range, 0.84-0.99). Wave-FLAIR was noninferior to standard FLAIR for visualization of lesions and motion. The diagnostic quality for Wave-FLAIR was slightly greater than for standard FLAIR for infratentorial lesions (P < .001), and there were fewer pulsation artifacts on Wave-FLAIR compared with standard FLAIR (P < .001). Ultrafast Wave-FLAIR provides superior visualization of infratentorial lesions while preserving overall diagnostic quality and yields white matter lesion volumes comparable with those estimated using standard FLAIR. The availability of ultrafast Wave-FLAIR may facilitate the greater use of 3D-FLAIR sequences in the evaluation of patients with suspected demyelinating disease.