Accuracy of the Compressed Sensing Accelerated 3D-FLAIR Sequence for the Detection of MS Plaques at 3T

Acceleration of uterine 3D T2-weighted imaging by compressed SENSE-a multicentre study

OBJECTIVES

To find the optimal acceleration factor (AF) of the compressed SENSE (CS) technique for uterine isotropic high-resolution 3D T2-weighted imaging (3D-ISO-T2WI).

METHODS

A total of 91 female volunteers from the First Affiliated Hospital of Dalian Medical University, Chu Hsien-I Memorial Hospital and Tianjin Institute of Endocrinology, and The Fourth Hospital of Harbin were recruited. A total of 44 volunteers received uterus sagittal 3D-ISO-T2WI scans on 3.0T MRI device with different CS AFs (including SENSE3, CS3, CS4, CS5, CS6, and CS7), 51 received 3D-ISO-T2WI scans with different degrees of fat suppression (none, light, moderate, and severe), while 4 volunteers received both series of scans. Image quality was subjectively evaluated with a 3-point scoring system. Junction zone signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and myometrial SNR were also calculated. Intraclass correlation coefficients were used to analyse the consistency of the measurement results by 2 observers. Analysis of variance test or Friedman rank sum test was used to compare the differences in subjective scores, SNR, and CNR under different AFs/different degrees of fat suppression.

RESULTS

Images by AFs of CS3, CS4, and CS5 had the highest SNR and CNR. Among them, CS5 had the shortest scan time. CS5 also had one of the highest subjective scores. There was no significant difference in SNR and CNR among images acquired with different degrees of fat suppression. Also, images with moderate fat suppression had the highest subjective scores.

CONCLUSION

The CS5 combined with moderate fat suppression is recommended for routine female pelvic 3D-ISO-T2WI scan.

ADVANCES IN KNOWLEDGE

The CS5 has the highest image quality and has the shortest scan time, which is the best AF. Moderate fat suppression has the highest subjective scores. The CS5 and moderate fat suppression are the best combination for a female pelvic 3D-ISO-T2WI scan.

Deep learning for efficient reconstruction of highly accelerated 3D FLAIR MRI in neurological deficits

OBJECTIVE

To compare compressed sensing (CS) and the Cascades of Independently Recurrent Inference Machines (CIRIM) with respect to image quality and reconstruction times when 12-fold accelerated scans of patients with neurological deficits are reconstructed.

MATERIALS AND METHODS

Twelve-fold accelerated 3D T2-FLAIR images were obtained from a cohort of 62 patients with neurological deficits on 3 T MRI. Images were reconstructed offline via CS and the CIRIM. Image quality was assessed in a blinded and randomized manner by two experienced interventional neuroradiologists and one experienced pediatric neuroradiologist on imaging artifacts, perceived spatial resolution (sharpness), anatomic conspicuity, diagnostic confidence, and contrast. The methods were also compared in terms of self-referenced quality metrics, image resolution, patient groups and reconstruction time. In ten scans, the contrast ratio (CR) was determined between lesions and white matter. The effect of acceleration factor was assessed in a publicly available fully sampled dataset, since ground truth data are not available in prospectively accelerated clinical scans. Specifically, 451 FLAIR scans, including scans with white matter lesions, were adopted from the FastMRI database to evaluate structural similarity (SSIM) and the CR of lesions and white matter on ranging acceleration factors from four-fold up to 12-fold.

RESULTS

Interventional neuroradiologists significantly preferred the CIRIM for imaging artifacts, anatomic conspicuity, and contrast. One rater significantly preferred the CIRIM in terms of sharpness and diagnostic confidence. The pediatric neuroradiologist preferred CS for imaging artifacts and sharpness. Compared to CS, the CIRIM reconstructions significantly improved in terms of imaging artifacts and anatomic conspicuity (p < 0.01) for higher resolution scans while yielding a 28% higher SNR (p = 0.001) and a 5.8% lower CR (p = 0.04). There were no differences between patient groups. Additionally, CIRIM was five times faster than CS was. An increasing acceleration factor did not lead to changes in CR (p = 0.92), but led to lower SSIM (p = 0.002).

DISCUSSION

Patients with neurological deficits can undergo MRI at a range of moderate to high acceleration. DL reconstruction outperforms CS in terms of image resolution, efficient denoising with a modest reduction in contrast and reduced reconstruction times.

Ultrafast Brain MRI at 3 T for MS: Evaluation of a 51-Second Deep Learning-Enhanced T2-EPI-FLAIR Sequence

In neuroimaging, there is no equivalent alternative to magnetic resonance imaging (MRI). However, image acquisitions are generally time-consuming, which may limit utilization in some cases, e.g., in patients who cannot remain motionless for long or suffer from claustrophobia, or in the event of extensive waiting times. For multiple sclerosis (MS) patients, MRI plays a major role in drug therapy decision-making. The purpose of this study was to evaluate whether an ultrafast, T2-weighted (T2w), deep learning-enhanced (DL), echo-planar-imaging-based (EPI) fluid-attenuated inversion recovery (FLAIR) sequence (FLAIRUF) that has targeted neurological emergencies so far might even be an option to detect MS lesions of the brain compared to conventional FLAIR sequences. Therefore, 17 MS patients were enrolled prospectively in this exploratory study. Standard MRI protocols and ultrafast acquisitions were conducted at 3 tesla (T), including three-dimensional (3D)-FLAIR, turbo/fast spin-echo (TSE)-FLAIR, and FLAIRUF. Inflammatory lesions were grouped by size and location. Lesion conspicuity and image quality were rated on an ordinal five-point Likert scale, and lesion detection rates were calculated. Statistical analyses were performed to compare results. Altogether, 568 different lesions were found. Data indicated no significant differences in lesion detection (sensitivity and positive predictive value [PPV]) between FLAIRUF and axially reconstructed 3D-FLAIR (lesion size ≥3 mm × ≥2 mm) and no differences in sensitivity between FLAIRUF and TSE-FLAIR (lesion size ≥3 mm total). Lesion conspicuity in FLAIRUF was similar in all brain regions except for superior conspicuity in the occipital lobe and inferior conspicuity in the central brain regions. Further findings include location-dependent limitations of signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) as well as artifacts such as spatial distortions in FLAIRUF. In conclusion, FLAIRUF could potentially be an expedient alternative to conventional methods for brain imaging in MS patients since the acquisition can be performed in a fraction of time while maintaining good image quality.

Compressed SENSitivity Encoding (SENSE): Qualitative and Quantitative Analysis

BACKGROUND

This study aimed to qualitatively and quantitatively evaluate T1-TSE, T2-TSE and 3D FLAIR sequences obtained with and without Compressed-SENSE technique by assessing the contrast (C), the contrast-to-noise ratio (CNR) and the signal-to-noise ratio (SNR).

METHODS

A total of 142 MRI images were acquired: 69 with Compressed-SENSE and 73 without Compressed-SENSE. All the MRI images were contoured, spatially aligned and co-registered using 3D Slicer Software. Two radiologists manually drew 12 regions of interests on three different structures of CNS: white matter (WM), grey matter (GM) and cerebrospinal fluid (CSF).

RESULTS

C values were significantly higher in Compressed-SENSE T1-TSE compared to No Compressed-SENSE T1-TSE for three different structures of the CNS. C values were also significantly lower for Compressed-SENSE 3D FLAIR and Compressed-SENSE T2-TSE compared to the corresponding No Compressed-SENSE scans. While CNR values did not significantly differ in GM-WM between Compressed-SENSE and No Compressed-SENSE for the 3D FLAIR and T1-TSE sequences, the differences in GM-CSF and WM-CSF were always statistically significant.

CONCLUSION

Compressed-SENSE for 3D T2 FLAIR, T1w and T2w sequences enables faster MRI acquisition, reducing scan time and maintaining equivalent image quality. Compressed-SENSE is very useful in specific medical conditions where lower SAR levels are required without sacrificing the acquisition of helpful diagnostic sequences.

Deep Learning Reconstruction for DWIs by EPI and FASE Sequences for Head and Neck Tumors

BACKGROUND

Diffusion-weighted images (DWI) obtained by echo-planar imaging (EPI) are frequently degraded by susceptibility artifacts. It has been suggested that DWI obtained by fast advanced spin-echo (FASE) or reconstructed with deep learning reconstruction (DLR) could be useful for image quality improvements. The purpose of this investigation using in vitro and in vivo studies was to determine the influence of sequence difference and of DLR for DWI on image quality, apparent diffusion coefficient (ADC) evaluation, and differentiation of malignant from benign head and neck tumors.

METHODS

For the in vitro study, a DWI phantom was scanned by FASE and EPI sequences and reconstructed with and without DLR. Each ADC within the phantom for each DWI was then assessed and correlated for each measured ADC and standard value by Spearman's rank correlation analysis. For the in vivo study, DWIs obtained by EPI and FASE sequences were also obtained for head and neck tumor patients. Signal-to-noise ratio (SNR) and ADC were then determined based on ROI measurements, while SNR of tumors and ADC were compared between all DWI data sets by means of Tukey's Honest Significant Difference test.

RESULTS

For the in vitro study, all correlations between measured ADC and standard reference were significant and excellent (0.92 ≤ ρ ≤ 0.99, p < 0.0001). For the in vivo study, the SNR of FASE with DLR was significantly higher than that of FASE without DLR (p = 0.02), while ADC values for benign and malignant tumors showed significant differences between each sequence with and without DLR (p < 0.05).

CONCLUSION

In comparison with EPI sequence, FASE sequence and DLR can improve image quality and distortion of DWIs without significantly influencing ADC measurements or differentiation capability of malignant from benign head and neck tumors.

Compressed Sensitivity Encoding Artificial Intelligence Accelerates Brain Metastasis Imaging by Optimizing Image Quality and Reducing Scan Time

BACKGROUND AND PURPOSE

Accelerating the image acquisition speed of MR imaging without compromising the image quality is challenging. This study aimed to evaluate the feasibility of contrast-enhanced (CE) 3D T1WI and CE 3D-FLAIR sequences reconstructed with compressed sensitivity encoding artificial intelligence (CS-AI) for detecting brain metastases (BM) and explore the optimal acceleration factor (AF) for clinical BM imaging.

MATERIALS AND METHODS

Fifty-one patients with cancer with suspected BM were included. Fifty participants underwent different customized CE 3D-T1WI or CE 3D-FLAIR sequence scans. Compressed SENSE encoding acceleration 6 (CS6), a commercially available standard sequence, was used as the reference standard. Quantitative and qualitative methods were used to evaluate image quality. The SNR and contrast-to-noise ratio (CNR) were calculated, and qualitative evaluations were independently conducted by 2 neuroradiologists. After exploring the optimal AF, sample images were obtained from 1 patient by using both optimized sequences.

RESULTS

Quantitatively, the CNR of the CS-AI protocol for CE 3D-T1WI and CE 3D-FLAIR sequences was superior to that of the CS protocol under the same AF (P < .05). Compared with reference CS6, the CS-AI groups had higher CNR values (all P < .05), with the CS-AI10 scan having the highest value. The SNR of the CS-AI group was better than that of the reference for both CE 3D-T1WI and CE 3D-FLAIR sequences (all P < .05). Qualitatively, the CS-AI protocol produced higher image quality scores than did the CS protocol with the same AF (all P < .05). In contrast to the reference CS6, the CS-AI group showed good image quality scores until an AF of up to 10 (all P < .05). The CS-AI10 scan provided the optimal images, improving the delineation of normal gray-white matter boundaries and lesion areas (P < .05). Compared with the reference, CS-AI10 showed reductions in scan time of 39.25% and 39.93% for CE 3D-T1WI and CE 3D-FLAIR sequences, respectively.

CONCLUSIONS

CE 3D-T1WI and CE 3D-FLAIR sequences reconstructed with CS-AI for the detection of BM may provide a more effective alternative reconstruction approach than CS. CS-AI10 is suitable for clinical applications, providing optimal image quality and a shortened scan time.

Fast Quantitative Magnetic Resonance Imaging Evaluation of Hydrocephalus Using 3-Dimensional Fluid-Attenuated Inversion Recovery: Initial Experience

OBJECTIVE

This study aimed to demonstrate the initial experience of using fast quantitative magnetic resonance imaging (MRI) to evaluate hydrocephalus.

METHODS

A total of 109 brain MRI volumetry examinations (acquisition time, 7 minutes 30 seconds) were performed in 72 patients with hydrocephalus. From the measured ventricular system and brain volumes, ventricle-brain volume percentage was calculated to standardize hydrocephalus severity (processing time, <5 minutes). The obtained values were categorized into no, mild, and severe based on the fronto-occipital horn ratio (FOHR) and the ventricle-brain volume percentages reported in the literature. The measured volumes and percentages were compared between patients with mild hydrocephalus and those with severe hydrocephalus. The diagnostic performance of brain hydrocephalus MRI volumetry was evaluated using receiver operating characteristic curve analysis.

RESULTS

Ventricular volumes and ventricle-brain volume percentages were significantly higher in in patients with severe hydrocephalus than in those with mild hydrocephalus (FOHR-based severity: 352.6 ± 165.6 cm 3 vs 149.1 ± 78.5 cm 3 , P < 0.001, and 26.8% [20.8%-33.1%] vs 12.1% ± 6.0%, P < 0.001; percentage-based severity: 359.5 ± 143.3 cm 3 vs 137.0 ± 62.9 cm 3 , P < 0.001, and 26.8% [21.8%-33.1%] vs 11.3% ± 4.2%, P < 0.001, respectively), whereas brain volumes were significantly lower in patients with severe hydrocephalus than in those with mild hydrocephalus (FOHR-based severity: 878.1 ± 363.5 cm 3 vs 1130.1 cm 3 [912.1-1244.2 cm 3 ], P = 0.006; percentage-based severity: 896.2 ± 324.6 cm 3 vs 1142.3 cm 3 [944.2-1246.6 cm 3 ], P = 0.005, respectively). The ventricle-brain volume percentage was a good diagnostic parameter for evaluating the degree of hydrocephalus (area under the curve, 0.855; 95% confidence interval, 0.719-0.990; P < 0.001).

CONCLUSIONS

Brain MRI volumetry can be used to evaluate hydrocephalus severity and may provide guide interpretation because of its rapid acquisition and postprocessing times.

T1 and FLAIR signal intensities are related to tau pathology in dominantly inherited Alzheimer disease

Carriers of mutations responsible for dominantly inherited Alzheimer disease provide a unique opportunity to study potential imaging biomarkers. Biomarkers based on routinely acquired clinical MR images, could supplement the extant invasive or logistically challenging) biomarker studies. We used 1104 longitudinal MR, 324 amyloid beta, and 87 tau positron emission tomography imaging sessions from 525 participants enrolled in the Dominantly Inherited Alzheimer Network Observational Study to extract novel imaging metrics representing the mean (μ) and standard deviation (σ) of standardized image intensities of T1-weighted and Fluid attenuated inversion recovery (FLAIR) MR scans. There was an exponential decrease in FLAIR-μ in mutation carriers and an increase in FLAIR and T1 signal heterogeneity (T1-σ and FLAIR-σ) as participants approached the symptom onset in both supramarginal, the right postcentral and right superior temporal gyri as well as both caudate nuclei, putamina, thalami, and amygdalae. After controlling for the effect of regional atrophy, FLAIR-μ decreased and T1-σ and FLAIR-σ increased with increasing amyloid beta and tau deposition in numerous cortical regions. In symptomatic mutation carriers and independent of the effect of regional atrophy, tau pathology demonstrated a stronger relationship with image intensity metrics, compared with amyloid pathology. We propose novel MR imaging intensity-based metrics using standard clinical T1 and FLAIR images which strongly associates with the progression of pathology in dominantly inherited Alzheimer disease. We suggest that tau pathology may be a key driver of the observed changes in this cohort of patients.

Evaluation of late gadolinium enhancement cardiac MRI using deep learning reconstruction

BACKGROUND

Deep learning (DL)-based methods have been used to improve the imaging quality of magnetic resonance imaging (MRI) by denoising.

PURPOSE

To assess the effects of DL-based MR reconstruction (DLR) method on late gadolinium enhancement (LGE) image quality.

MATERIAL AND METHODS

A total of 85 patients who underwent cardiovascular magnetic resonance (CMR) examination, including LGE imaging using conventional construction and DLR with varying levels of noise reduction (NR) levels, were included. Both magnitude LGE (MLGE) and phase-sensitive LGE (PSLGE) images were reviewed independently by double-blinded observers who used a 5-point Likert scale for multiple measures regarding image quality. Meanwhile, the signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and edge sharpness of images were calculated and compared between conventional LGE imaging and DLR LGE imaging.

RESULTS

Both MLGE and PSLGE with DLR at 50% and 75% noise reduction levels received significantly higher scores than conventional imaging for overall imaging quality (all P < 0.01). In addition, the SNR, CNR, and edge sharpness of all DLR LGE imaging are higher than conventional imaging (all P < 0.01). The highest subjective score and best image quality is obtained when the DLR noise reduction level is at 75%.

CONCLUSION

DLR reduced image noise while improving image contrast and sharpness in the cardiovascular LGE imaging.

Evaluation of Artifact Appearance and Burden in Pediatric Brain Tumor MR Imaging with Compressed Sensing in Comparison to Conventional Parallel Imaging Acceleration

Clinical magnetic resonance imaging (MRI) aims for the highest possible image quality, while balancing the need for acceptable examination time, reasonable signal-to-noise ratio (SNR), and lowest artifact burden. With a recently introduced imaging acceleration technique, compressed sensing, the acquisition speed and image quality of pediatric brain tumor exams can be improved. However, little attention has been paid to its impact on method-related artifacts in pediatric brain MRI. This study assessed the overall artifact burden and artifact appearances in a standardized pediatric brain tumor MRI by comparing conventional parallel imaging acceleration with compressed sensing. This showed that compressed sensing resulted in fewer physiological artifacts in the FLAIR sequence, and a reduction in technical artifacts in the 3D T1 TFE sequences. Only a slight difference was noted in the T2 TSE sequence. A relatively new range of artifacts, which are likely technique-related, was noted in the 3D T1 TFE sequences. In conclusion, by equipping a basic pediatric brain tumor protocol for 3T MRI with compressed sensing, the overall burden of common artifacts can be reduced. However, attention should be paid to novel compressed-sensing-specific artifacts.

FDA-approved machine learning algorithms in neuroradiology: A systematic review of the current evidence for approval

Over the past decade, machine learning (ML) and artificial intelligence (AI) have become increasingly prevalent in the medical field. In the United States, the Food and Drug Administration (FDA) is responsible for regulating AI algorithms as "medical devices" to ensure patient safety. However, recent work has shown that the FDA approval process may be deficient. In this study, we evaluate the evidence supporting FDA-approved neuroalgorithms, the subset of machine learning algorithms with applications in the central nervous system (CNS), through a systematic review of the primary literature. Articles covering the 53 FDA-approved algorithms with applications in the CNS published in PubMed, EMBASE, Google Scholar and Scopus between database inception and January 25, 2022 were queried. Initial searches identified 1505 studies, of which 92 articles met the criteria for extraction and inclusion. Studies were identified for 26 of the 53 neuroalgorithms, of which 10 algorithms had only a single peer-reviewed publication. Performance metrics were available for 15 algorithms, external validation studies were available for 24 algorithms, and studies exploring the use of algorithms in clinical practice were available for 7 algorithms. Papers studying the clinical utility of these algorithms focused on three domains: workflow efficiency, cost savings, and clinical outcomes. Our analysis suggests that there is a meaningful gap between the FDA approval of machine learning algorithms and their clinical utilization. There appears to be room for process improvement by implementation of the following recommendations: the provision of compelling evidence that algorithms perform as intended, mandating minimum sample sizes, reporting of a predefined set of performance metrics for all algorithms and clinical application of algorithms prior to widespread use. This work will serve as a baseline for future research into the ideal regulatory framework for AI applications worldwide.

Subtractionless compressed-sensing-accelerated whole-body MR angiography using two-point Dixon fat suppression with single-pass half-reduced contrast dose: feasibility study and initial experience

PURPOSE

To investigate the feasibility and clinical utility of a compressed-sensing-accelerated subtractionless whole-body MRA (CS-WBMRA) protocol with only contrast injection for suspected arterial diseases, by comparison to conventional dual-pass subtraction-based whole-body MRA (conventional-WBMRA) and available computed tomography angiography (CTA).

MATERIALS AND METHODS

This prospective study assessed 86 patients (mean age, 56 years ± 16.4 [standard deviation]; 25 women) with suspected arterial diseases from May 2021 to December 2022, who underwent CS-WBMRA (n = 48, mean age, 55.9 years ± 16.4 [standard deviation]; 25 women) and conventional-WBMRA (n = 38, mean age, 48 years ± 17.4 [standard deviation]; 20 women) on a 3.0 T MRI after random group assignment based on the chronological order of enrolment. Of all enrolled patients administered the CS-WBMRA protocol, 35% (17/48) underwent CTA as required by clinical demands. Two experienced radiologists independently scored the qualitative image quality and venous enhancement contamination. Quantitative image assessment was carried out by determining and comparing the apparent signal-to-noise ratios (SNRs) and contrast-to-noise ratios (CNRs) of four representative arterial segments. The total examination time and contrast-dose were also recorded. The independent samples t-test or the Wilcoxon rank sum test was used for statistical analysis.

RESULTS

The overall scores of CS-WBMRA outperformed those of conventional-WMBRA (3.40 ± 0.60 vs 3.22 ± 0.55, P < 0.001). In total, 1776 and 1406 arterial segments in the CS-WBMRA and conventional-WBMRA group were evaluated. Qualitative image scores for 7 (of 15) vessel segments in the CS-WMBRA group had statistically significantly increased values compared to those of the conventional-WBMRA groups (P < 0.05). Scores from the other 8 segments showed similar image quality (P > 0.05) between the two protocols. In the quantitative analysis, overall apparent SNRs were significantly higher in the conventional-WBMRA group than in the CS-WBMRA group (214.98 ± 136.05 vs 164.90 ± 118.05; P < 0.001), while overall apparent CNRs were not significantly different in these two groups (CS vs conventional: 107.13 ± 72.323 vs 161.24 ± 118.64; P > 0.05). In the CS-WBMRA group, 7 of 1776 (0.4%) vessel segments were contaminated severely by venous enhancement, while in the convention-WBMRA group, 317 of 1406 (23%) were rated as severe contamination. In the CS-WBMRA group, total examination and reconstruction times were only 7 min and 10 min, respectively, vs 20 min and < 30 s for the conventional WBMRA group, respectively. The contrast agent dose used in the CS-WBMRA protocol was reduced by half compared to conventional-WBMRA protocol (18.7 ± 3.5 ml vs 37.2 ± 5.4 ml, P = 0.008).

CONCLUSION

The CS-WBMRA protocol provides excellent image quality and sufficient diagnostic accuracy for whole-body arterial disease, with relatively faster workflow and half-dose reduction of contrast agent, which has greater potential in clinical practice compared with conventional-WBMRA.

Clinical feasibility of CS-VIBE accelerates MRI techniques in diagnosing intracranial metastasis

Our objective was to evaluate and compare the diagnostic performance of post-contrast 3D compressed-sensing volume-interpolated breath-hold examination (CS-VIBE) and 3D T1 magnetization-prepared rapid-acquisition gradient-echo (MPRAGE) in detecting intracranial metastasis. Additionally, we analyzed and compared the image quality between the two. We enrolled 164 cancer patients who underwent contrast-enhanced brain MRI. Two neuroradiologists independently reviewed all the images. The signal-to-noise ratio (SNR), contrast-to noise ratio (CNR) were compared between two sequences. For patients with intracranial metastasis, we measured enhancement degree and CNR_{lesion/parenchyma} of the lesion. The overall image quality, motion artifact, gray-white matter discrimination and enhancing lesion conspicuity were analyzed. Both MPRAGE and CS-VIBE showed similar performance in diagnosing intracranial metastasis. Overall image quality of CS-VIBE was better with less motion artifact; however conventional MPRAGE was superior in enhancing lesion conspicuity. Overall, the SNR and CNR of conventional MPRAGE were higher than those of CS-VIBE. For 30 enhancing intracranial metastatic lesions, MPRAGE showed a lower CNR (p = 0.02) and contrast ratio (p = 0.03). MPRAGE and CS-VIBE were preferred in 11.6 and 13.4% of cases, respectively. In comparison with conventional MPRAGE, CS-VIBE achieved comparable image quality and visualization, with the scan time being half of that of MPRAGE.

Reverse encoding distortion correction for diffusion-weighted MRI: Efficacy for improving image quality and ADC evaluation for differentiating malignant from benign areas in suspected prostatic cancer patients

PURPOSE

The purpose of this study was to determine the influenceof reverse encoding distortion correction (RDC) on ADC measurement and its efficacy for improving image quality and diagnostic performance for differentiating malignant from benign prostatic areas on prostatic DWI.

METHODS

Forty suspected prostatic cancer patients underwent DWI with or without RDC (i.e. RDC DWI or DWI) using a 3 T MR system as well as pathological examinations. The pathological examination results indicated 86 areas were malignant while 86 out of 394 areas were computationally selected as benign. SNR for benign areas and muscle and ADCs for malignant and benign areas were determined by ROI measurements on each DWI. Moreover, overall image quality was assessed with a 5-point visual scoring system on each DWI. Paired t-test or Wilcoxon's signed rank test was performed to compare SNR and overall image quality for DWIs. ROC analysis was then used to compare the diagnostic performance, and sensitivity (SE), specificity (SP) and accuracy (AC) of ADC were compared between two DWI by means of McNemar's test.

RESULTS

SNR and overall image quality of RDC DWI showed significant improvements when compared with those of DWI (p < 0.05). Areas under the curve (AUC), SP and AC of DWI RDC DWI (AUC: 0.85, SP: 72.1%, AC: 79.1%) were significantly better than those of DWI (AUC: 0.79, p = 0.008; SP: 64%, p = 0.02; AC: 74.4%, p = 0.008).

CONCLUSION

RDC technique has the potential to improve image quality and ability to differentiate malignant from benign prostatic areas on DWIs of suspected prostatic cancer patients.

The clinical feasibility of artificial intelligence-assisted compressed sensing single-shot fluid-attenuated inversion recovery (ACS-SS-FLAIR) for evaluation of uncooperative patients with brain diseases: comparison with the conventional T2-FLAIR with parallel imaging

Background

Satisfactory magnetic resonance imaging (MRI) of those patients with involuntary head motion due to brain diseases is essential in avoiding missed diagnosis and guiding treatment.

Purpose

To investigate the clinical feasibility of artificial intelligence-assisted compressed sensing single-shot fluid-attenuated inversion recovery (ACS-SS-FLAIR) in evaluating patients with involuntary head motion due to brain diseases, compared with the conventional T2-FLAIR with parallel imaging (PI-FLAIR).

Material and Methods

A total of 33 uncooperative patients with brain disease were prospectively enrolled. Two readers independently reviewed images acquired with ACS-SS-FLAIR and PI-FLAIR at a 3.0-T MR scanner. In the aspects of qualitative evaluation of image quality, overall image quality and lesion conspicuity of ACS-SS-FLAIR and PI-FLAIR were assessed and then statistically compared by paired Wilcoxon rank-sum test. For quantitative evaluation, the relative contrast of lesion-to-cerebral parenchyma were calculated and compared.

Results

Overall image quality scores of ACS-SS-FLAIR evaluated by two readers were 2.94 ± 0.24 and 2.91 ± 0.29, respectively, both of which were significantly higher than that of PI-FLAIR, respectively ( P < 0.001 and <0.001). Lesion conspicuity scores of were 2.74 ± 0.47 and 2.79 ± 0.44, both of which were significantly higher than that of PI-FLAIR, respectively ( P < 0.001 and <0.001). In the quantitative evaluation for image quality, the relative contrast of lesion-to-cerebral parenchyma was 0.34 ± 0.09 in the ACS-SS-FLAIR sequence, significantly larger than that in the PI-FLAIR sequence ( P = 0.001).

Conclusion

The ACS-SS-FLAIR sequence is clinically feasible in the MRI workup of those patients with involuntary head motion due to brain diseases, showing shorter image acquisition time and better image quality compared with conventional PI-FLAIR.

3D Cube FLAIR plus HyperSense compressed sensing is superior to 2D T2WI FLAIR scanning regarding image quality, spatial resolution, detection rate for cortical microinfarcts

3-dimention (3D) Cube isotropic volumetric magnetic resonance imaging (MRI) facilitates comprehensive recognition of microinfarcts while it takes long scanning time. HyperSense compressed sensing is an emerging technique for accelerating MRI acquisition to reduce scanning time, while its application along with 3D Cube MRI for microinfarcts is seldom reported. Therefore, this study aimed to investigate the efficiency of 3D Cube FLAIR plus HyperSense compressed sensing technique versus conventional 2-dimention (2D) FLAIR scanning in the detection of cortical microinfarcts (CMIs). Totally 59 patients with cerebrovascular disease were enrolled then scanned by 3D Cube FLAIR plus HyperSense compressed sensing and 2D T2WI FLAIR sequences. The image quality scores, signal-to-noise ratio (SNR) for gray matter (GM), SNR for white matter (WM), their contrast-to-noise ratio (WM-to-GM CNR), detected number of CMIs were evaluated. 3D Cube FLAIR plus HyperSense showed a dramatically increased scores of uniformity, artifact, degree of lesion displacement, and overall image quality compared to 2D T2WI FLAIR. Meanwhile, it exhibited similar SNRwm and SNRgm, but a higher WM-to-GM contrast-to-noise ratio compared with 2D T2WI FLAIR. Furthermore, the scanning time of 3D Cube FLAIR plus HyperSense and 2D T2WI FLAIR were both set as 2.5 minutes. Encouragingly, 244 CMIs were detected by 3D Cube FLAIR plus HyperSense, which was higher compared to 2D T2WI FLAIR (106 detected CMIs). 3D Cube FLAIR plus HyperSense compressed sensing is superior to 2D T2WI FLAIR scanning regarding image quality, spatial resolution, detection rate for CMIs; meanwhile, it does not increase the scanning time. These findings may contribute to early detection and treatment of stroke.

Accelerated 3D T2-weighted images using compressed sensing for pediatric brain imaging

PURPOSE

The purpose of this study was to compare the image quality of the 3D T2-weighted images accelerated using conventional method (CAI-SPACE) with the images accelerated using compressed sensing (CS-SPACE) in pediatric brain imaging.

METHODS

A total of 116 brain MRI (53 with CAI-SPACE and 63 with CS-SPACE) were obtained from children 16 years old or younger. Quantitative image quality was evaluated using the apparent signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). The sequences were qualitatively evaluated for overall image quality, general artifact, cerebrospinal fluid (CSF)-related artifact, and grey-white matter differentiation. The two sequences were compared for the total and two age groups (< 24 months vs. ≥ 24 months).

RESULTS

Compressed sensing application in 3D T2-weighted imaging resulted in 8.5% reduction in scanning time. Quantitative image quality analysis showed higher apparent SNR (median [Interquartile range]; 29 [25] vs. 23 [14], P = 0.005) and CNR (0.231 [0.121] vs. 0.165 [0.120], P = 0.027) with CS-SPACE compared to CAI-SPACE. Qualitative image quality analysis showed better image quality with CS-SPACE for general (P = 0.024) and CSF-related artifact (P < 0.001). CSF-related artifacts reduction was prominent in the older age group (≥ 24 months). Overall image quality (P = 0.162) and grey-white matter differentiation (P = 0.397) were comparable between CAI-SPACE and CS-SPACE.

CONCLUSION

Compressed sensing application in 3D T2-weighted images modestly reduced acquisition time and lowered CSF-related artifact compared to conventional images of the pediatric brain.

Validation of a Denoising Method Using Deep Learning-Based Reconstruction to Quantify Multiple Sclerosis Lesion Load on Fast FLAIR Imaging

BACKGROUND AND PURPOSE

Accurate quantification of WM lesion load is essential for the care of patients with multiple sclerosis. We tested whether the combination of accelerated 3D-FLAIR and denoising using deep learning-based reconstruction could provide a relevant strategy while shortening the imaging examination.

MATERIALS AND METHODS

Twenty-eight patients with multiple sclerosis were prospectively examined using 4 implementations of 3D-FLAIR with decreasing scan times (4 minutes 54 seconds, 2 minutes 35 seconds, 1 minute 40 seconds, and 1 minute 15 seconds). Each FLAIR sequence was reconstructed without and with denoising using deep learning-based reconstruction, resulting in 8 FLAIR sequences per patient. Image quality was assessed with the Likert scale, apparent SNR, and contrast-to-noise ratio. Manual and automatic lesion segmentations, performed randomly and blindly, were quantitatively evaluated against ground truth using the absolute volume difference, true-positive rate, positive predictive value, Dice similarity coefficient, Hausdorff distance, and F1 score based on the lesion count. The Wilcoxon signed-rank test and 2-way ANOVA were performed.

RESULTS

Both image-quality evaluation and the various metrics showed deterioration when the FLAIR scan time was accelerated. However, denoising using deep learning-based reconstruction significantly improved subjective image quality and quantitative performance metrics, particularly for manual segmentation. Overall, denoising using deep learning-based reconstruction helped to recover contours closer to those from the criterion standard and to capture individual lesions otherwise overlooked. The Dice similarity coefficient was equivalent between the 2-minutes-35-seconds-long FLAIR with denoising using deep learning-based reconstruction and the 4-minutes-54-seconds-long reference FLAIR sequence.

CONCLUSIONS

Denoising using deep learning-based reconstruction helps to recognize multiple sclerosis lesions buried in the noise of accelerated FLAIR acquisitions, a possibly useful strategy to efficiently shorten the scan time in clinical practice.

Practical Aspects of novel MRI Techniques in Neuroradiology: Part 2 - Acceleration Methods and Implications for Individual Regions

BACKGROUND

 Recently introduced MRI techniques facilitate accelerated examinations or increased resolution with the same duration. Further techniques offer homogeneous image quality in regions with anatomical transitions. The question arises whether and how these techniques can be adopted for routine diagnostic imaging.

METHODS

 Narrative review with an educational focus based on current literature research and practical experiences of different professions involved (physicians, MRI technologists/radiographers, physics/biomedical engineering). Different hardware manufacturers are considered.

RESULTS AND CONCLUSIONS

 Compressed sensing and simultaneous multi-slice imaging are novel acceleration techniques with different yet complimentary applications. They do not suffer from classical signal-to-noise-ratio penalties. Combining 3 D and acceleration techniques facilitates new broader examination protocols, particularly for clinical brain imaging. In further regions of the nervous systems mainly specific applications appear to benefit from recent technological improvements.

KEY POINTS

  · New acceleration techniques allow for faster or higher resolution examinations.. · New brain imaging approaches have evolved, including more universal examination protocols.. · Other regions of the nervous system are dominated by targeted applications of recently introduced MRI techniques..

CITATION FORMAT

· Sundermann B, Billebaut B, Bauer J et al. Practical Aspects of novel MRI Techniques in Neuroradiology: Part 2 - Acceleration Methods and Implications for Individual Regions. Fortschr Röntgenstr 2022; DOI: 10.1055/a-1800-8789.

Comparison of compressed sensing and controlled aliasing in parallel imaging acceleration for 3D magnetic resonance imaging for radiotherapy preparation

Magnetic resonance imaging (MRI) for radiotherapy is often based on 3D acquisitions, but suffers from low signal-to-noise ratio due to immobilization device and flexible coil use. The aim of this study was to investigate if Compressed Sensing (CS) improves image quality for 3D Turbo Spin Echo acquisitions compared with Controlled Aliasing k-space-based parallel imaging in equivalent acquisition time for intracranial T1, T2-Fluid-Attenuated Inversion Recovery (FLAIR) and pelvic T2 imaging. Qualitative ratings suffered from large inter-rater variability. CS-T1 brain MRI was superior numerically and qualitatively. CS-T2-FLAIR brain MRI was numerically superior, but rater equivalent. CS-T2 pelvic MRI was equivalent without gain.

Contrast-Enhanced Fluid-Attenuated Inversion Recovery in Neuroimaging: A Narrative Review on Clinical Applications and Technical Advances

While contrast-enhanced fluid-attenuated inversion recovery (FLAIR) has long been regarded as an adjunct sequence to evaluate leptomeningeal disease in addition to contrast-enhanced T1-weighted imaging, it is gradually being used for more diverse pathologies beyond leptomeningeal disease. Contrast-enhanced FLAIR is known to be highly sensitive to low concentrations of gadolinium within the fluid. Accordingly, recent research has suggested the potential utility of contrast-enhanced FLAIR in various kinds of disease, such as Meniere's disease, seizure, stroke, traumatic brain injury, and brain metastasis, in addition to being used for visualizing glymphatic dysfunction. However, its potential applications have been reported sporadically in an unorganized manner. Furthermore, the exact mechanism for its superior sensitivity to low concentrations of gadolinium has not been fully understood. Rapidly developing magnetic resonance technology and unoptimized parameters for FLAIR may challenge its accurate application in clinical practice. This review provides the fundamental mechanism of contrast-enhanced FLAIR, systematically describes its current and potential clinical application, and elaborates on technical considerations for its optimization. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY STAGE: 5.

Deep Learning Reconstruction of Diffusion-weighted MRI Improves Image Quality for Prostatic Imaging

Background Deep learning reconstruction (DLR) may improve image quality. However, its impact on diffusion-weighted imaging (DWI) of the prostate has yet to be assessed. Purpose To determine whether DLR can improve image quality of diffusion-weighted MRI at b values ranging from 1000 sec/mm² to 5000 sec/mm² in patients with prostate cancer. Materials and Methods In this retrospective study, images of the prostate obtained at DWI with a b value of 0 sec/mm², DWI with a b value of 1000 sec/mm² (DWI₁₀₀₀), DWI with a b value of 3000 sec/mm² (DWI₃₀₀₀), and DWI with a b value of 5000 sec/mm² (DWI₅₀₀₀) from consecutive patients with biopsy-proven cancer from January to June 2020 were reconstructed with and without DLR. Image quality was assessed using signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) from region-of-interest analysis and qualitatively assessed using a five-point visual scoring system (1 [very poor] to 5 [excellent]) for each high-b-value DWI sequence with and without DLR. The SNR, CNR, and visual score for DWI with and without DLR were compared with the paired t test and the Wilcoxon signed rank test with Bonferroni correction, respectively. Apparent diffusion coefficients (ADCs) from DWI with and without DLR were also compared with the paired t test with Bonferroni correction. Results A total of 60 patients (mean age, 67 years; age range, 49-79 years) were analyzed. DWI with DLR showed significantly higher SNRs and CNRs than DWI without DLR (P < .001); for example, with DWI₁₀₀₀ the mean SNR was 38.7 ± 0.6 versus 17.8 ± 0.6, respectively (P < .001), and the mean CNR was 18.4 ± 5.6 versus 7.4 ± 5.6, respectively (P < .001). DWI with DLR also demonstrated higher qualitative image quality than DWI without DLR (mean score: 4.8 ± 0.4 vs 4.0 ± 0.7, respectively, with DWI₁₀₀₀ [P = .001], 3.8 ± 0.7 vs 3.0 ± 0.8 with DWI₃₀₀₀ [P = .002], and 3.1 ± 0.8 vs 2.0 ± 0.9 with DWI₅₀₀₀ [P < .001]). ADCs derived with and without DLR did not differ substantially (P > .99). Conclusion Deep learning reconstruction improves the image quality of diffusion-weighted MRI scans of prostate cancer with no impact on apparent diffusion coefficient quantitation with a 3.0-T MRI system. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Turkbey in this issue.

Compressed SENSE in Pediatric Brain Tumor MR Imaging : Assessment of Image Quality, Examination Time and Energy Release

Purpose

To compare the image quality, examination time, and total energy release of a standardized pediatric brain tumor magnetic resonance imaging (MRI) protocol performed with and without compressed sensitivity encoding (C-SENSE). Recently introduced as an acceleration technique in MRI, we hypothesized that C‑SENSE would improve image quality, reduce the examination time and radiofrequency-induced energy release compared with conventional examination in a pediatric brain tumor protocol.

Methods

This retrospective study included 22 patients aged 2.33–18.83 years with different brain tumor types who had previously undergone conventional MRI examination and underwent follow-up C‑SENSE examination. Both examinations were conducted with a 3.0-Tesla device and included pre-contrast and post-contrast T1-weighted turbo-field-echo, T2-weighted turbo-spin-echo, and fluid-attenuated inversion recovery sequences. Image quality was assessed in four anatomical regions of interest (tumor area, cerebral cortex, basal ganglia, and posterior fossa) using a 5-point scale. Reader preference between the standard and C‑SENSE images was evaluated. The total examination duration and energy deposit were compared based on scanner log file analysis.

Results

Relative to standard examinations, C‑SENSE examinations were characterized by shorter total examination times (26.1 ± 3.93 vs. 22.18 ± 2.31 min; P = 0.001), reduced total energy deposit (206.0 ± 19.7 vs. 92.3 ± 18.2 J/kg; P < 0.001), and higher image quality (overall P < 0.001).

Conclusion

C‑SENSE contributes to the improvement of image quality, reduction of scan times and radiofrequency-induced energy release relative to the standard protocol in pediatric brain tumor MRI.

Supplementary Information

The online version of this article (10.1007/s00062-021-01112-3) contains supplementary material, which is available to authorized users.

Iterative denoising accelerated 3D SPACE FLAIR sequence for brain MR imaging at 3T

PURPOSE

The purpose of this study was to prospectively evaluate image quality of three-dimensional fluid attenuated inversion recovery (3D-FLAIR) sequence acquired with a high acceleration factor and reconstructed with iterative denoising (ID) for brain magnetic resonance imaging (MRI) at 3-T.

MATERIAL AND METHODS

Patients with brain tumor who underwent brain MRI were consecutively included. Two 3D-FLAIR sequences were successively performed for each patient. A first conventional FLAIR acquisition (conv-FLAIR) was performed with an acceleration factor of 6. The second acquisition was performed with an increased acceleration factor of 9. Two series one without ID (acc-FLAIR) and one with ID (acc-FLAIR-ID) were reconstructed. Two neuroradiologists independently assessed image quality, deep brain nuclei visualization and white matter/gray matter (WM/GM) differentiation on a 4-point scale.

RESULTS

Thirty patients with brain tumor were consecutively included in this study. There were 16 women and 14 men with a mean age of 54 ± 17 (SD) years (range: 22-78 years). Scanning time of Acc-FLAIR-ID and Acc-FLAIR (4 min 40 sec) was 37% shorter than that of conv-FLAIR (2 min 50 sec) (P < 0.01). Improved image quality score was significantly different for both conv-FLAIR and acc-FLAIR-ID compared to acc-FLAIR (P < 0.01 for both). WM/GM differentiation score of conv-FLAIR was not significantly different compared to acc-FLAIR-ID (P = 0.10). Improved WM/GM differentiation score was different for both sequences compared to acc-FLAIR (P = 0.017 and P < 0.001). Deep brain nuclei visualization score was not different between conv-FLAIR and acc-FLAIR-ID (P = 0.71). However, the improved deep brain nuclei visualization score was significantly different for both sequences compared to acc-FLAIR (P < 0.001 for both).

CONCLUSION

Scanning time of 3D-FLAIR sequence using a high acceleration factor reconstructed with ID algorithm can be reduced by 37% while preserving image quality for brain MRI.

Intraindividual Comparison between the Contrast-Enhanced Golden-Angle Radial Sparse Parallel Sequence and the Conventional Fat-Suppressed Contrast-Enhanced T1-Weighted Spin-Echo Sequence for Head and Neck MRI

BACKGROUND AND PURPOSE

The golden-angle radial sparse parallel-volumetric interpolated breath-hold (GRASP-VIBE) sequence is a recently introduced imaging technique with high resolution. This study compared the image quality between conventional fat-suppressed T1-weighted TSE and GRASP-VIBE after gadolinium enhancement in the head and neck region.

MATERIALS AND METHODS

Data from 65 patients with clinical indications for head and neck MR imaging between September 2020 and January 2021 were retrospectively reviewed. Two radiologists assessed the overall image quality, overall artifacts, and image conspicuities in the oropharynx, hypopharynx, and cervical lymph nodes according to 5-point scores (best score: 5). Interobserver agreement was assessed using weighted κ statistics. The SNR and contrast-to-noise ratio were calculated and compared between the 2 sequences using a paired Wilcoxon signed rank test.

RESULTS

The analysis included 52 patients (mean age, 60 [SD, 14 ] years; male, 71.2% [37/52]) who were mostly diagnosed with head and neck malignancies (94.3% [50/52]). κ statistics ranged from slight agreement in cervical lymph node conspicuity (κ = 0.18) to substantial agreement in oropharyngeal mucosal conspicuity (κ = 0.80) (κ range, 0.18-0.80). Moreover, GRASP-VIBE demonstrated significantly higher mean scores in overall image quality (4.68 [SD, 0.41] versus 3.66 [SD, 0.73]), artifacts (4.47 [SD, 0.48] versus 3.58 [SD, 0.71]), oropharyngeal mucosal conspicuity (4.85 [SD, 0.41] versus 4.11 [SD, 0.79]), hypopharyngeal mucosal conspicuity (4.84 [SD, 0.34] versus 3.58 [SD, 0.81]), and cervical lymph node conspicuity (4.79 [SD, 0.32] versus 4.08 [SD, 0.64]) than fat-suppressed T1-weighted TSE (all, P < .001). Furthermore, GRASP-VIBE demonstrated a higher SNR (22.8 [SD, 11.5] versus 11.3 [SD, 5.6], P < .001) and contrast-to-noise ratio (4.7 [SD, 5.4] versus 2.3 [SD, 2.7], P = .059) than fat-suppressed T1-weighted TSE.

CONCLUSIONS

GRASP-VIBE provided better image quality with fewer artifacts than conventional fat-suppressed T1-weighted TSE for the head and neck regions.

Compressed-sensing accelerated magnetic resonance imaging of inner ear

Objective

To compare conventional method and compressed‐sensing (CS) accelerated 3D balanced fast field echo imaging (bFFE) of inner ear.

Methods

Twenty patients with suspected inner ear disease underwent CS accelerated 3D‐bFFE (CS‐bFFE) and conventional 3D‐bFFE (Con‐bFFE) by a 3T MRI. The overall image quality, motion artifacts, and image quality of specific structures of inner ear were assessed on ordinal scales by three radiologists who were blinded to the scan protocols. Kendall W test was used to evaluate interobserver agreement and Wilcoxon test was performed to compare the image quality and motion artifacts between CS‐bFFE and Con‐bFFE.

Results

The acquisition duration of CS‐bFFE (1 min 53 s) was 49% faster than Con‐bFFE. Three radiologists had good inter‐observer agreement of image quality (Kendall W value of 0.829 for CS‐bFFE and 0.815 for Con‐bFFE) and motion artifacts evaluation (Kendall W value of 0861 for CS‐bFFE and 0.707 for Con‐bFFE). The better overall image quality of CS‐bFFE was assessed (4.93 ± 0.23 for CS‐bFFE, 4.53 ± 0.70 for Con‐bFFE, Z = −2.254, p = 0.024). The image quality score of facial and cochlear nerve gained higher in CS‐bFFE (4.93 ± 0.23 for CS‐bFFE, 4.58 ± 0.64 for Con‐bFFE, Z = −2.094, p = 0.036). No significant difference of motion artifacts (p = 0.050) between CS‐bFFE and Con‐bFFE.

Conclusions

The CS‐bFFE improves image quality and reduces acquisition time significantly, and it is a feasible MRI protocol for inner ear imaging.

Diagnostic quality assessment of compressed SENSE accelerated magnetic resonance images in standard neuroimaging protocol: Choosing the right acceleration

PURPOSE

To investigate the impact of compressed sensing - sensitivity encoding (CS-SENSE) acceleration factor on the diagnostic quality of magnetic resonance images within standard brain protocol.

METHODS

Three routine clinical neuroimaging sequences were chosen for this study due to their long acquisition time: T2-weighted turbo spin echo (TSE), fluid - attenuated inversion recovery (FLAIR), and 3D time of flight (TOF). Fully sampled reference scans and multiple prospectively 2x to 5x undersampled CS scans were acquired. Retrospectively, undersampled scans were compared to fully sampled scans and visually assessed for image quality and diagnostic quality by three independent radiologists.

RESULTS

Images obtained with CS-SENSE accelerated acquisition were of diagnostically acceptable quality at up to 3x acceleration for T2 TSE (average qualitative score 3.53 on a 4-point scale, with the acquisition time reduction of 64%), up to 2x for FLAIR (average qualitative score 3.27, with the acquisition time reduction of 43%) and 4x acceleration for 3D TOF sequence (average qualitative score 3.13, with the acquisition time reduction of 73%). There were no substantial differences between the readers' diagnostic quality scores (p > 0.05).

CONCLUSIONS

CS-SENSE accelerated T2 TSE, FLAIR, and 3D TOF sequences of the brain show image quality similar to that of conventional acquisitions with reduced acquisition time. CS-SENSE can moderately reduce scan time, providing many benefits without losing the image quality.

CS-VIBE accelerates cranial nerve MR imaging for the diagnosis of facial neuritis: comparison of the diagnostic performance of post-contrast MPRAGE and CS-VIBE

OBJECTIVE

We aimed to compare the diagnostic performance of post-contrast 3D compressed sensing volume-interpolated breath-hold examination (CS-VIBE) and 3D T1 magnetization-prepared rapid-acquisition gradient-echo (MPRAGE) in detecting facial neuritis.

MATERIALS AND METHODS

Between February 2019 and September 2019, 60 patients (30 facial palsy patients and 30 controls) who underwent contrast-enhanced cranial nerve MRI with both conventional MPRAGE and CS-VIBE (scan time: 6 min 8 s vs. 2 min 48 s) were included in this retrospective study. All images were independently reviewed by three radiologists for the presence of facial neuritis. In patients with facial palsy, signal-to-noise ratio (SNR) of the pons, enhancement degree and contrast-to-noise ratio (CNR_nerve-CSF) of the facial nerve were measured. The overall image quality, artifacts, and facial nerve discrimination were analyzed. The sensitivity and specificity of both sequences were calculated with the clinical diagnosis as a reference.

RESULTS

CS-VIBE had comparable performance in the detection of facial neuritis to that of MPRAGE (sensitivity and specificity, 97.8% and 99.4% vs. 100.0% and 99.4% in pooled analysis; 97.8% and 98.9% vs. 100.0% and 98.9% in patents with facial palsy, p value > 0.05 for all). CS-VIBE showed significantly lower SNR (p value < 0.001 for all), but significantly higher CNR_nerve-CSF (p value < 0.05 for all) than MPRAGE. CS-VIBE also performed better in the overall image quality, artifacts, and facial nerve discrimination than MPRAGE (p value < 0.001 for all).

CONCLUSION

CS-VIBE achieved comparable diagnostic performance for facial neuritis compared to the conventional MPRAGE, with the scan time being half of that of MPRAGE.

KEY POINTS

• Post-contrast 3D CS-VIBE MRI is a reliable method for the diagnosis of facial neuritis. • CS-VIBE reduces the scan time of cranial nerve MRI by more than half compared to conventional T1-weighted image. • CS-VIBE had better performance in contrast-to-noise ratio and favorable image quality compared with conventional T1-weighted image.

Image Findings of Acute to Subacute Craniocervical Arterial Dissection on Magnetic Resonance Vessel Wall Imaging: A Systematic Review and Proportion Meta-Analysis

Background and Purpose: This systematic review and meta-analysis aimed to evaluate the pooled proportion of image findings of acute to subacute craniocervical arterial dissection (AD) direct signs on magnetic resonance vessel wall imaging (MR-VWI) and to identify factors responsible for the heterogeneity across the included studies.

Methods: A systematic literature search in the Ovid-MEDLINE and EMBASE databases was performed for studies published on the relevant topic before April 14, 2020. Pooled sensitivity and specificity values and their 95% confidence intervals (CIs) were calculated using bivariate random-effects modeling. Meta-regression analyses were also performed to determine factors influencing heterogeneity.

Results: Eleven articles with data for 209 patients with acute to subacute craniocervical AD who underwent MR-VWI were included in this systematic review and meta-analysis. The most common findings on MR-VWI were wall hematoma (84%; 95% CI, 71%−92%), abnormal enhancement (72%; 95% CI, 49%−88%), aneurysmal dilatation (71%, 95% CI, 53%−84%), and intimal flap or double lumen signs (49%; 95% CI, 29%−71%). Among the potential covariates of heterogeneity, the presence of contrast-enhanced T1-weighted imaging (CE-T1WI) within the MR-VWI sequence combination significantly affected the pooled proportion of the intimal flap or double lumen signs.

Conclusion: Wall hematoma and intimal flap or double lumen signs were the most common and least common direct sign image findings, respectively, on MR-VWI in patients with acute to subacute craniocervical AD. Furthermore, the absence of CE-T1WI in MR-VWI protocol was the cause of heterogeneity for the detection of the intimal flap or double lumen signs. This data may help improve MR-VWI interpretation and enhance the understanding of the radiologic diagnosis of craniocervical AD.

Evaluation of contrast and denoising effects related to imaging parameters of compressed sensitivity encoding in contrast-enhanced magnetic resonance imaging

To acquire reference data for setting an appropriate compressed sensitivity encoding (CS) for brain lesion detectability, the effects of contrast and noise on contrast-enhanced magnetic resonance imaging (MRI) were evaluated. Gadobutrol at various concentrations and manganese chloride tetrahydrate were used as a phantom. Various CS factors (0-10) and denoising levels (weak, medium, and strong) were assessed. The contrast amount decreased from CS7 in non-denoised images for 0.5-2 mmol/L solutions but slightly decreased from CS7 with denoising. The noise amount significantly increased with an increasing CS factor. Generally, there was a significant difference in the denoising level and rate across all CS factors in the case of the 2 and 0 mmol/L solutions. When the CS factor was increased without denoising, the integrated noise power spectrum (NPS) increased and decreased in the high-frequency and low-frequency areas, respectively. These data can be used to establish settings based on the degree of denoising.

Reproducibility of radiomic features in SENSE and compressed SENSE: impact of acceleration factors

OBJECTIVES

To investigate the impact of acceleration factors on reproducibility of radiomic features in sensitivity encoding (SENSE) and compressed SENSE (CS), compare between SENSE and CS, and identify reproducible radiomic features.

METHODS

Three-dimensional turbo spin echo T1-weighted imaging was performed in 14 healthy volunteers (mean age, 57 years; range, 33-67 years; 7 men) under SENSE and CS with accelerator factors of 5.5, 6.8, and 9.7. Eight anatomical locations (brain parenchyma, salivary glands, masseter muscle, tongue, pharyngeal mucosal space, eyeballs) were evaluated. Reproducibility of radiomic features was evaluated by calculating concordance correlation coefficient (CCC) in reference to the original image (SENSE with acceleration factor of 3.5). Reproducibility of radiomic features among acceleration factors and between SENSE and CS was compared.

RESULTS

Proportion of radiomic features with CCC > 0.85 in reference to the original image was lower with higher acceleration factors in both SENSE and CS across all anatomical locations (p < .001). Proportion of radiomic features with CCC > 0.85 in reference to the original image was higher in SENSE compared with CS (SENSE, 6.7-7.3% vs CS, 4.4-5.0%; p < .001). Run percentage of gray-level run-length matrix (GLRLM) with wavelet D showed CCC > 0.85 in reference to the original image in both SENSE and CS at acceleration factor of 9.7 in the highest number of anatomical locations.

CONCLUSIONS

Higher acceleration factors resulted in lower reproducibility of radiomic features in both SENSE and CS, and SENSE showed higher reproducibility of radiomic features than CS in reference to the original image. Run percentage of GLRLM with wavelet D was identified as the most reproducible feature.

KEY POINTS

• Reproducibility of radiomic features in reference to the original image was lower with higher acceleration factors in both sensitivity encoding (SENSE) and compressed SENSE (CS) across all anatomical locations (p < .001). • SENSE showed higher proportions of radiomic features with CCC > 0.85 in reference to the original image (SENSE, 6.7-7.3% vs CS, 4.4-5.0%; p < .001) compared with CS. • Run percentage of gray-level run-length matrix (GLRLM) with wavelet D showed CCC > 0.85 in reference to the original image in both SENSE and CS with the highest acceleration factor.

Clear and Consistent Imaging of Hippocampal Internal Architecture With High Resolution Multiple Image Co-registration and Averaging (HR-MICRA)

Magnetic resonance imaging of hippocampal internal architecture (HIA) at 3T is challenging. HIA is defined by layers of gray and white matter that are less than 1 mm thick in the coronal plane. To visualize HIA, conventional MRI approaches have relied on sequences with high in-plane resolution (≤0.5 mm) but comparatively thick slices (2–5 mm). However, thicker slices are prone to volume averaging effects that result in loss of HIA clarity and blurring of the borders of the hippocampal subfields in up to 61% of slices as has been reported. In this work we describe an approach to hippocampal imaging that provides consistently high HIA clarity using a commonly available sequence and post-processing techniques that is flexible and may be applicable to any MRI platform. We refer to this approach as High Resolution Multiple Image Co-registration and Averaging (HR-MICRA). This approach uses a variable flip angle turbo spin echo sequence to repeatedly acquire a whole brain T2w image volume with high resolution in three dimensions in a relatively short amount of time, and then co-register the volumes to correct for movement and average the repeated scans to improve SNR. We compared the averages of 4, 9, and 16 individual scans in 20 healthy controls using a published HIA clarity rating scale. In the body of the hippocampus, the proportion of slices with good or excellent HIA clarity was 90%, 83%, and 67% for the 16x, 9x, and 4x HR-MICRA images, respectively. Using the 4x HR-MICRA images as a baseline, the 9x HR-MICRA images were 2.6 times and 16x HR-MICRA images were 3.2 times more likely to have high HIA ratings (p < 0.001) across all hippocampal segments (head, body, and tail). The thin slices of the HR-MICRA images allow reformatting in any plane with clear visualization of hippocampal dentation in the sagittal plane. Clear and consistent visualization of HIA will allow application of this technique to future hippocampal structure research, as well as more precise manual or automated segmentation.

Interpretation of fluid-attenuated inversion recovery vascular hyperintensity in stroke

Fluid-attenuation inversion recovery (FLAIR) vascular hyperintensity (FVH) is a common presentation on brain magnetic resonance images of patients with acute ischemic stroke. This sign is known as a sluggish collateral flow. Although FVH represents the large ischemic penumbra and collateral circulation, the clinical significance of FVH has not been established. Varying protocols for FLAIR, treatment differences, and heterogeneity of endpoints across studies have complicated the interpretation of FVH in patients with acute stroke. In this review article, we describe the mechanism of FVH, as well as its association with functional outcome, perfusion-weighted images, and large artery stenosis. In addition, we review the technological variables that affect FVH and discuss the future perspectives.

Optimal acceleration factor for image acquisition in turbo spin echo: diffusion-weighted imaging with compressed sensing

In this study, the change in the image quality and apparent diffusion coefficient (ADC) with increase in the acceleration factor (AF) was analyzed and the most optimal AF was determined to reduce the scan time while preserving the image quality. The AF was changed from 2 to 20 in the MR acquisitions. The similarities between the accelerated and reference images were determined based on the structural similarity (SSIM) index for DWI image and coefficient of variation (%CV) for ADC. The SSIM index decreased significantly when the AF ≥ 8 compared with when the AF = 2 (p < 0.05). In the reference image, the %CV of the ADC increased significantly when the AF ≥ 10 (p < 0.01). In conclusion, a remarkable decrease in the image quality and ADC was observed when the AF was > 8. Thus, an AF < 8 would be optimal for reducing the scan time while preserving the image quality.

Compressed sensing and parallel imaging accelerated T2 FSE sequence for head and neck MR imaging: Comparison of its utility in routine clinical practice

PURPOSE

To directly compare the capability of compressed sensing (CS) and parallel imaging (PI) accelerated T2 FSE (Fast Spin Echo) sequence with PI for head and neck MR imaging.

METHODS

Thirty consecutive patients with various head and neck diseases (15 men and 15 women, mean age 53 ± 22 years) underwent MR imaging by PI with CS and by PI. Reduction factors were as follows: PI with CS, 3 and PI, 1.5. Examination times for PI with CS and PI were all recorded. For quantitative image quality assessment, signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated. For qualitative assessment, two investigators assessed overall image quality, artifacts and diagnostic confidence level using a 5-point scoring system, and final scores were determined by consensus of two readers. Mean examination time and all indexes were compared by means of paired t-test and Wilcoxon signed-rank test. Inter-observer agreement for each qualitative index was assessed in terms of kappa statistics.

RESULTS

Mean examination time for PI with CS (83.5 ± 11.0 s) was significantly shorter than that for PI (173.0 ± 54.4 s, p < 0.0001). SNR and CNR of PI with CS were significantly better than those with PI (mean SNR; 11.2 ± 3.6 vs 8.9 ± 2.6, median of CNR; 7.4 vs. 6.1, p < 0.0001). All inter-observer agreements were assessed as significant and substantial (0.62 < κ < 0.81).

CONCLUSION

PI with CS accelerated T2 weighted sequence performs equally well or even slightly better than its PI accelerated, conventional counterpart at reduced scan times in the context of head and neck MR imaging.

Compressed sensing and deep learning reconstruction for women's pelvic MRI denoising: Utility for improving image quality and examination time in routine clinical practice

PURPOSE

To demonstrate the utility of compressed sensing with parallel imaging (Compressed SPEEDER) and AiCE compared with that of conventional parallel imaging (SPEEDER) for shortening examination time and improving image quality of women's pelvic MRI.

METHOD

Thirty consecutive patients with women's pelvic diseases (mean age 50 years) underwent T2-weighted imaging using Compressed SPEEDER as well as conventional SPEEDER reconstructed with and without AiCE. The examination times were recorded, and signal-to-noise ratio (SNR) was calculated for every patient. Moreover, overall image quality was assessed using a 5-point scoring system, and final scores for all patients were determined by consensus of two readers. Mean examination time, SNR and overall image quality were compared among the four data sets by Wilcoxon signed-rank test.

RESULTS

Examination times for Compressed SPEEDER with and without AiCE were significantly shorter than those for conventional SPEEDER with and without AiCE (with AiCE: p < 0.0001, without AiCE: p < 0.0001). SNR of Compressed SPEEDER and of SPEEDER with AiCE was significantly superior to that of Compressed SPEEDER without AiCE (vs. Compressed SPEEDER, p = 0.01; vs. SPEEDER, p = 0.009). Overall image quality of Compressed SPEEDER with AiCE and of SPEEDER with and without AiCE was significantly higher than that of Compressed SPEEDER without AiCE (vs. Compressed SPEEDER with AiCE, p < 0.0001; vs. SPEEDER with AiCE, p < 0.0001; SPEEDER without AiCE, p = 0.0003).

CONCLUSION

Image quality and shorten examination time for T2-weighted imaging in women's pelvic MRI can be significantly improved by using Compressed SPEEDER with AiCE in comparison with conventional SPEEDER, although other sequences were not tested.

Accelerating Brain 3D T1-Weighted Turbo Field Echo MRI Using Compressed Sensing-Sensitivity Encoding (CS-SENSE)

PURPOSE

To evaluate the clinical application of the accelerated 3D T1-weighted turbo field echo (T1W-TFE) using the compressed sensing-sensitivity encoding (CS-SENSE) and identify the appropriate acceleration factor.

METHODS

33 healthy controls (HC), 10 multiple sclerosis (MS) and 10 Alzheimer's disease (AD) patients were prospectively recruited. A conventional 3D T1W-TFE sequence and accelerated sequences with CS-SENSE factors of 3, 4.5, 6 and with SENSE factors of 3, 4.5 were acquired for all participants on a 3.0T MR system. The visual evaluation was independently assessed by two experienced radiologists. Quantitative image quality metrics and intraclass correlation coefficients (ICCs) between the conventional and the accelerated sequences were performed at the voxel level. Group comparisons were performed between HC and AD or MS patients.

RESULTS

There were no significant differences in the visual image quality metrics between conventional sequence and CS-SENSE factor of 3. The sequences with CS-SENSE factor of 6 and SENSE factors of 3, 4.5 showed significantly decreased overall image quality. The ICC values based on the voxel level of each accelerated scan and conventional scan were high (>0.9, 85.2%). For different accelerated sequences, AD and MS patients showed consistent results with the conventional sequence in gray matter atrophy when compared to HC.

CONCLUSIONS

CS-SENSE factor of 3 is the appropriate parameter to accelerate the 3D T1W-TFE (65% time reduction) with preserved visual image quality. The voxel-based analysis demonstrated high ICCs for brain volume measurements in the majority of brain regions, implying the feasibility of the accelerated technique.

Diagnostic value of 3D-FLAIR magnetic resonance sequence in detection of white matter brain lesions in multiple sclerosis

Background

MS is common demyelinating disease in which standard T2 and 2D-FLAIR MRI sequences play important role in its diagnosis. Recently, 3D-FLAIR sequence is used and has a role that is evaluated compared to standard sequences.

Results

This study was performed on 20 selected MS patients. Brain MRI was performed using routinely used T2 and 2D FLAIR sequences, and 3D-FLAIR sequence was added. 3D-FLAIR images were reformatted, and all images were blindly analyzed. Lesions were counted in each sequence and classified according to their location into supratentorial lesions including periventricular, deep white matter, and juxta-cortical, and infratentorial lesions and relative comparison of lesion number on 3D-FLAIR versus 2D-FLAIR and T2 imaging, respectively, were expressed as percentage gain or a loss.

3D-FLAIR sequence showed significantly more lesions compared to 2D FLAIR and T2 sequences in all locations with relative ratio of 29% and 41%, respectively, in periventricular region; 22% and 30%, respectively, in deep WM; 180% and 147%, respectively, in juxta-cortical region; and 80% and 13%, respectively, in infratentorial region.

Conclusion

3D-FLAIR sequence is of greater sensitivity than standard 2D-FLAIR and T2 sequences in MS brain lesions depiction, and it is recommended to be included in MR protocol of MS.

MRI Techniques to Decrease Imaging Times in Children

Long acquisition times can limit the use of MRI in pediatric patients, and the use of sedation or general anesthesia is frequently necessary to facilitate diagnostic examinations. The use of sedation or anesthesia has disadvantages including increased cost and imaging time and potential risks to the patient. Reductions in imaging time may decrease or eliminate the need for sedation or general anesthesia. Over the past decade, a number of imaging techniques that can decrease imaging time have become commercially available. These products have been used increasingly in clinical practice and include parallel imaging, simultaneous multisection imaging, radial k-space acquisition, compressed sensing MRI reconstruction, and automated protocol selection software. The underlying concepts, supporting data, current clinical applications, and available products for each of these strategies are reviewed in this article. In addition, emerging techniques that are still under investigation may provide further reductions in imaging time, including artificial intelligence-based reconstruction, gradient-controlled aliasing sampling and reconstruction, three-dimensional MR spectroscopy, and prospective motion correction. The preliminary results for these techniques are also discussed. ^©RSNA, 2020 See discussion on this article by Greer and Vasanawala.

Acceleration of Double Inversion Recovery Sequences in Multiple Sclerosis With Compressed Sensing

OBJECTIVE

The aim of this study was to assess the performance of double inversion recovery (DIR) sequences accelerated by compressed sensing (CS) in a clinical setting.

MATERIALS AND METHODS

We included 106 patients with MS (62 female [58%]; mean age, 44.9 ± 11.0 years) in this prospective study. In addition to a full magnetic resonance imaging protocol including a conventional SENSE accelerated DIR, we acquired a CS DIR (time reduction, 51%). We generated subtraction maps between the two DIR sequences to visualize focal intensity differences. Two neuroradiologists independently assessed these maps for intensity differences, which were categorized into definite MS lesions, possible lesions, or definite artifacts. Counts of focal intensity differences were compared using a Wilcoxon rank sum test. Moreover, conventional lesion counts were acquired for both sequences in independent readouts, and agreement between the DIR variants was assessed with intraclass correlation coefficients.

RESULTS

No hyperintensity that was rated as definite lesion was missed in the CS DIR. Two possible lesions were only detected in the conventional DIR, one only in the CS DIR (no significant difference, P = 0.57). The conventional DIR showed significantly more definite artifacts within the white matter (P = 0.024) and highly significantly more at the cortical-sulcal interface (P < 0.001). For both readers, intraclass correlation coefficient between the lesion counts in the two DIR variants was near perfect (0.985 for reader 1 and 0.981 for reader 2).

CONCLUSIONS

Compressed sensing can be used to substantially reduce scan time of DIR sequences without compromising diagnostic quality. Moreover, the CS accelerated DIR proved to be significantly less prone to imaging artifacts.

Three-dimensional MRI sequences in MS diagnosis and research

The most recent guidelines for magnetic resonance imaging (MRI) in multiple sclerosis (MS) recommend three-dimensional (3D) MRI sequences over their two-dimensional (2D) counterparts. This development has been made possible by advances in MRI scanner hardware and software. In this article, we review the 3D versions of conventional sequences, including T1-weighted, T2-weighted and fluid-attenuated inversion recovery (FLAIR), as well as more advanced scans, including double inversion recovery (DIR), FLAIR2, FLAIR*, phase-sensitive inversion recovery, and susceptibility weighted imaging (SWI).

Magnetic Resonance Imaging of the Brain Using Compressed Sensing - Quality Assessment in Daily Clinical Routine

PURPOSE

To assess the effect of compressed sensing (CS) on image quality and acquisition speed in routine brain magnetic resonance imaging (MRI).

METHODS

During a 2-month implementation period of CS, two senior neuroradiologists, one MRI physicist and one application specialist optimized the CS acceleration factor to reduce scan time and improve spatial resolution, while maintaining image quality. Afterwards, two neuroradiologists independently scored image quality on a 5-point Likert scale in 3‑dimensional (3D) fluid attenuation inversion recovery (FLAIR), 3D double inversion recovery (DIR), 3D T2, 3D T1, 3D T1 + gadoteric acid, axial T2, axial FLAIR, axial T2*, and 3D arterial time-of-flight MR angiography (art. TOF) sequences acquired during 1 week before (CS-) and after (CS+) the implementation of CS. Time of acquisition was recorded for all sequences.

RESULTS

A total of 51 CS- and 48 CS+ patients were included. The median scan time reduction was 29.3% (range 0.0-58.4%), median voxel size reduction was 10.5% (0.0-33.3%). The CS+ image quality was rated superior for 3D FLAIR (p < 0.001), 3D T2 (p = 0.001), and axial T2* sequences (p = 0.024). For all other sequences, no statistical difference in image quality was observed. Interreader agreement regarding image quality was good for all sequences (weighted Cohen's κ > 0.5).

CONCLUSION

The use of CS saves considerable imaging time while allowing to increase spatial resolution in routine clinical brain MRI without loss in image quality.

Compressed Sensing-Sensitivity Encoding (CS-SENSE) Accelerated Brain Imaging: Reduced Scan Time without Reduced Image Quality

BACKGROUND AND PURPOSE

Compressed sensing-sensitivity encoding is a promising MR imaging acceleration technique. This study compares the image quality of compressed sensing-sensitivity encoding accelerated imaging with conventional MR imaging sequences.

MATERIALS AND METHODS

Patients with known, treated, or suspected brain tumors underwent compressed sensing-sensitivity encoding accelerated 3D T1-echo-spoiled gradient echo or 3D T2-FLAIR sequences in addition to the corresponding conventional acquisition as part of their clinical brain MR imaging. Two neuroradiologists blinded to sequence and patient information independently evaluated both the accelerated and corresponding conventional acquisitions. The sequences were evaluated on 4- or 5-point Likert scales for overall image quality, SNR, extent/severity of artifacts, and gray-white junction and lesion boundary sharpness. SNR and contrast-to-noise ratio values were compared.

RESULTS

Sixty-six patients were included in the study. For T1-echo-spoiled gradient echo, image quality in all 5 metrics was slightly better for compressed sensing-sensitivity encoding than conventional images on average, though it was not statistically significant, and the lower bounds of the 95% confidence intervals indicated that compressed sensing-sensitivity encoding image quality was within 10% of conventional imaging. For T2-FLAIR, image quality of the compressed sensing-sensitivity encoding images was within 10% of the conventional images on average for 3 of 5 metrics. The compressed sensing-sensitivity encoding images had somewhat more artifacts (P = .068) and less gray-white matter sharpness (P = .36) than the conventional images, though neither difference was significant. There was no significant difference in the SNR and contrast-to-noise ratio. There was 25% and 35% scan-time reduction with compressed sensing-sensitivity encoding for FLAIR and echo-spoiled gradient echo sequences, respectively.

CONCLUSIONS

Compressed sensing-sensitivity encoding accelerated 3D T1-echo-spoiled gradient echo and T2-FLAIR sequences of the brain show image quality similar to that of standard acquisitions with reduced scan time. Compressed sensing-sensitivity encoding may reduce scan time without sacrificing image quality.