Sparse Reconstruction Techniques in Magnetic Resonance Imaging: Methods, Applications, and Challenges to Clinical Adoption

Fast 3D fMRI acquisition with high spatial resolutions over a reduced FOV

PURPOSE

To develop and demonstrate a fast 3D fMRI acquisition technique with high spatial resolution over a reduced FOV, named k-t 3D reduced FOV imaging (3D-rFOVI).

METHODS

Based on 3D gradient-echo EPI, k-t 3D-rFOVI used a 2D RF pulse to reduce the FOV in the in-plane phase-encoding direction, boosting spatial resolution without increasing echo train length. For image acceleration, full sampling was applied in the central k-space region along the through-slab direction (kz) for all time frames, while randomized undersampling was used in outer kz regions at different time frames. Images were acquired at 3T and reconstructed using a method based on partial separability. fMRI detection sensitivity of k-t 3D-rFOVI was quantitively analyzed with simulation data. Human visual fMRI experiments were performed to evaluate k-t 3D-rFOVI and compare it with a commercial multiband EPI sequence.

RESULTS

The simulation data showed that k-t 3D-rFOVI can detect 100% of fMRI activations with an acceleration factor (R) of 2 and ˜80% with R = 6. In the human fMRI data acquired with 1.5-mm spatial resolution and 800-ms volume TR (TRvol), k-t 3D-rFOVI with R = 4 detected 46% more activated voxels in the visual cortex than the multiband EPI. Additional fMRI experiments showed that k-t 3D-rFOVI can achieve TRvol of 480 ms with R = 6, while reliably detecting visual activation.

CONCLUSIONS

k-t 3D-rFOVI can simultaneously achieve a high spatial resolution (1.5-mm isotropically) and short TRvol (480-ms) at 3T. It offers a robust acquisition technique for fast fMRI studies over a focused brain volume.

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.

Modern acceleration in musculoskeletal MRI: applications, implications, and challenges

Magnetic resonance imaging (MRI) is crucial for accurately diagnosing a wide spectrum of musculoskeletal conditions due to its superior soft tissue contrast resolution. However, the long acquisition times of traditional two-dimensional (2D) and three-dimensional (3D) fast and turbo spin-echo (TSE) pulse sequences can limit patient access and comfort. Recent technical advancements have introduced acceleration techniques that significantly reduce MRI times for musculoskeletal examinations. Key acceleration methods include parallel imaging (PI), simultaneous multi-slice acquisition (SMS), and compressed sensing (CS), enabling up to eightfold faster scans while maintaining image quality, resolution, and safety standards. These innovations now allow for 3- to 6-fold accelerated clinical musculoskeletal MRI exams, reducing scan times to 4 to 6 min for joints and spine imaging. Evolving deep learning-based image reconstruction promises even faster scans without compromising quality. Current research indicates that combining acceleration techniques, deep learning image reconstruction, and superresolution algorithms will eventually facilitate tenfold accelerated musculoskeletal MRI in routine clinical practice. Such rapid MRI protocols can drastically reduce scan times by 80-90% compared to conventional methods. Implementing these rapid imaging protocols does impact workflow, indirect costs, and workload for MRI technologists and radiologists, which requires careful management. However, the shift from conventional to accelerated, deep learning-based MRI enhances the value of musculoskeletal MRI by improving patient access and comfort and promoting sustainable imaging practices. This article offers a comprehensive overview of the technical aspects, benefits, and challenges of modern accelerated musculoskeletal MRI, guiding radiologists and researchers in this evolving field.

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.

AI-accelerated prostate MRI: a systematic review

BACKGROUND

Prostate cancer ranks among the most prevalent cancers affecting men globally. While conventional MRI serves as a diagnostic tool, its extended acquisition time, associated costs, and strain on healthcare systems, underscore the necessity for more efficient methods. The emergence of AI-acceleration in prostate MRI offers promise to mitigate these challenges.

METHODS

A systematic review of studies looking at AI-accelerated prostate MRI was conducted, with a focus on acquisition time along with various qualitative and quantitative measurements.

RESULTS

Two primary findings were observed. Firstly, all studies indicated that AI-acceleration in MRI achieved notable reductions in acquisition times without compromising image quality. This efficiency offers potential clinical advantages, including reduced scan durations, improved scheduling, diminished patient discomfort, and economic benefits. Secondly, AI demonstrated a beneficial effect in reducing or maintaining artefact levels in T2-weighted images despite this accelerated acquisition time. Inconsistent results were found in all other domains, which were likely influenced by factors such as heterogeneity in methodologies, variability in AI models, and diverse radiologist profiles. These variances underscore the need for larger, more robust studies, standardization, and diverse training datasets for AI models.

CONCLUSION

The integration of AI-acceleration in prostate MRI thus far shows some promising results for efficient and enhanced scanning. These advancements may fill current gaps in early detection and prognosis. However, careful navigation and collaborative efforts are essential to overcome challenges and maximize the potential of this innovative and evolving field.

ADVANCES IN KNOWLEDGE

This article reveals overall significant reductions in acquisition time without compromised image quality in AI-accelerated prostate MRI, highlighting potential clinical and diagnostic advantages.

Breath-hold High-resolution T1-weighted Gradient Echo Liver MR Imaging with Compressed Sensing Obtained during the Gadoxetic Acid-enhanced Hepatobiliary Phase: Image Quality and Lesion Visibility Compared with a Standard T1-weighted Sequence

PURPOSE

To evaluate the feasibility of breath-hold (BH) high-resolution (HR) T1-weighted gradient echo hepatobiliary phase (HBP) imaging using compressed sensing (CS) in gadoxetic acid-enhanced liver MRI in comparison with standard HBP imaging using parallel imaging (PI).

METHODS

The study included 122 patients with liver tumors with hypointensity in the HBP who underwent both HR HBP imaging with CS and standard HBP imaging with PI. Two radiologists evaluated the liver edge sharpness, hepatic vessel conspicuity, bile duct conspicuity, image noise, and overall image quality, as well as the lesion conspicuity on HR and standard HBP imaging and the contrast-enhanced (CE) MR cholangiography (MRC) image quality reconstructed from HBP images. As a quantitative analysis, the SNR of the liver and the liver to lesion signal intensity ratio (LLSIR) were also determined.

RESULTS

The liver edge sharpness, hepatic vessel conspicuity, bile duct conspicuity, and overall image quality as well as the lesion conspicuity and the LLSIR on HR HBP imaging with CS were significantly higher than those on standard HBP imaging (all of P < 0.001). The image quality of CE-MRC reconstructed from HR HBP imaging with CS was also significantly higher than that from standard HBP imaging (P < 0.001). Conversely, the SNR of liver in standard HBP was significantly higher than that in HR HBP with CS (P < 0.001).

CONCLUSION

BH HR HBP imaging with CS provided an improved overall image quality, lesion conspicuity, and CE-MRC visualization when compared with standard HBP imaging without extending the acquisition time.

Evaluation of Compressed SENSE on Image Quality and Reduction of MRI Acquisition Time: A Clinical Validation Study

RATIONALE AND OBJECTIVES

To evaluate the effect of compressed SENSE (CS) in clinical settings on scan time reduction and image quality.

MATERIALS AND METHODS

Ninety-five magnetic resonance imaging (MRI) scans from different anatomical regions were acquired, consisting of a standard protocol sequence (SS) and sequence accelerated with CS. Anonymized paired sequences were randomly displayed and rated by six blinded subspecialty radiologists. Side-by-side evaluation on perceived sharpness, perceived signal-to-noise-ratio (SNR), lesion conspicuity, and artifacts were compared and scored on a five-point Likert scale, and individual image quality was evaluated on a four-point Likert scale.

RESULTS

CS reduced overall scan time by 32% while maintaining acceptable MRI quality for all regions. The largest time savings were seen in the spine (mean = 68 seconds, 44% reduction) followed by the brain (mean = 86 seconds, 37% reduction). The sequence with maximum time savings was intracranial 3D-time-of-flight magnetic resonance angiography (202 seconds, 56% reduction). CS was mildly inferior to SS on perceived sharpness, perceived SNR, and lesion conspicuity (mean scores = 2.32-2.96, P < .001 [1: SS superior; 3: equivalent; 5: CS superior]). CS was equivalent to SS for joint and body scans on overall image quality (CS = 3.02-3.37, SS = 3.04-3.68, P > .05, [1: lowest quality and 4: highest quality]). The overall image quality of CS was slightly less for brain and spine scans (mean CS = 2.79-3.05, mean SS = 3.13-3.43, P = .021) but still diagnostic. Good overall clinical acceptance for CS (88%) was noted with full clinical acceptance for body scans (100%) and high acceptance for other regions (68%-95%).

CONCLUSION

CS significantly reduced MR acquisition time while maintaining acceptable image quality. The implementation of CS may improve departmental workflows and enhance patient care.

Iterative Denoising Accelerated 3D FLAIR Sequence for Hydrops MR Imaging at 3T

BACKGROUND AND PURPOSE

3D FLAIR sequences have become the criterion standard for identifying endolymphatic hydrops, but scan time remains an important limitation to their widespread use. Our purpose was to evaluate the diagnostic performance and image quality of an accelerated 3D FLAIR sequence combined with an iterative denoising algorithm.

MATERIALS AND METHODS

This was a retrospective study performed on 30 patients with clinical suspicion of endolymphatic hydrops who underwent 3T MR imaging 4 hours after gadolinium injection using two 3D FLAIR sequences. The first (conventional FLAIR) was accelerated with a conventional turbo factor of 187. The second was accelerated with an increased turbo factor of 263, resulting in a 33% scan time reduction (5 minutes 36 seconds versus 8 minutes 15 seconds, respectively). A sequence was reconstructed in-line immediately after the accelerated 3D FLAIR acquisition from the same raw data with iterative denoising (accelerated-FLAIR iterative denoising). The signal intensity ratio image quality score and endolymphatic hydrops diagnosis were evaluated.

RESULTS

The mean signal intensity ratio for symptomatic and asymptomatic ears of accelerated-FLAIR iterative denoising was significantly higher than the mean SNR of conventional FLAIR (29.5 versus 19 and 25.9 versus 16.3, P < .001). Compared with the conventional FLAIR sequence, the image-quality score was higher with accelerated-FLAIR iterative denoising (mean image-quality score, 3.8 [SD, 0.4] versus 3.3 [SD, 0.6] for accelerated-FLAIR iterative denoising and conventional FLAIR, respectively, P = .003). There was no significant difference in the diagnosis of endolymphatic hydrops between the 2 sequences. Interreader agreement was good-to-excellent.

CONCLUSIONS

The iterative denoising algorithm applied to an accelerated 3D FLAIR sequence for exploration of endolymphatic hydrops enabled significantly reducing the scan time without compromising image quality and diagnostic performance.

Brain morphometry in older adults with and without dementia using extremely rapid structural scans

T1-weighted structural MRI is widely used to measure brain morphometry (e.g., cortical thickness and subcortical volumes). Accelerated scans as fast as one minute or less are now available but it is unclear if they are adequate for quantitative morphometry. Here we compared the measurement properties of a widely adopted 1.0 mm resolution scan from the Alzheimer's Disease Neuroimaging Initiative (ADNI = 5'12'') with two variants of highly accelerated 1.0 mm scans (compressed-sensing, CSx6 = 1'12''; and wave-controlled aliasing in parallel imaging, WAVEx9 = 1'09'') in a test-retest study of 37 older adults aged 54 to 86 (including 19 individuals diagnosed with a neurodegenerative dementia). Rapid scans produced highly reliable morphometric measures that largely matched the quality of morphometrics derived from the ADNI scan. Regions of lower reliability and relative divergence between ADNI and rapid scan alternatives tended to occur in midline regions and regions with susceptibility-induced artifacts. Critically, the rapid scans yielded morphometric measures similar to the ADNI scan in regions of high atrophy. The results converge to suggest that, for many current uses, extremely rapid scans can replace longer scans. As a final test, we explored the possibility of a 0'49'' 1.2 mm CSx6 structural scan, which also showed promise. Rapid structural scans may benefit MRI studies by shortening the scan session and reducing cost, minimizing opportunity for movement, creating room for additional scan sequences, and allowing for the repetition of structural scans to increase precision of the estimates.

The argument for utilising magnetic resonance imaging as a tool for monitoring lung structure and function in pediatric patients

INTRODUCTION

Although historically challenging to perform in the lung, technological advancements have made Magnetic Resonance Imaging (MRI) increasingly applicable for pediatric pulmonary imaging. Furthermore, a wide array of functional imaging techniques has become available that may be leveraged alongside structural imaging for increasingly sensitive biomarkers, or as outcome measures in the evaluation of novel therapies.

AREAS COVERED

In this review, recent technical advancements and modern methodologies for structural and functional lung MRI are described. These include ultrashort echo time (UTE) MRI, free-breathing contrast agent-free, functional lung MRI, and hyperpolarized gas MRI, amongst other techniques. Specific examples of the application of these methods in children are provided, principally drawn from recent research in asthma, bronchopulmonary dysplasia, and cystic fibrosis.

EXPERT OPINION

Pediatric lung MRI is rapidly growing, and is well poised for clinical utilization, as well as continued research into early disease detection, disease processes, and novel treatments. Structure/function complementarity makes MRI especially attractive as a tool for increased adoption in the evaluation of pediatric lung disease. Looking toward the future, novel technologies, such as low-field MRI and artificial intelligence, mitigate some of the traditional drawbacks of lung MRI and will aid in improving access to MRI in general, potentially spurring increased adoption and demand for pulmonary MRI in children.

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.

Rapid whole-brain myelin imaging with selective inversion recovery and compressed SENSE

PURPOSE

Quantitative magnetization transfer (QMT) using selective inversion recovery (SIR) can quantify the macromolecular-to-free proton pool size ratio (PSR), which has been shown to relate closely with myelin content. Currently clinical applications of SIR have been hampered by long scan times. In this work, the acceleration of SIR-QMT using CS-SENSE (compressed sensing SENSE) was systematically studied.

THEORY AND METHODS

Phantoms of varied concentrations of bovine serum albumin and human scans were first conducted to evaluate the SNR, precision of SIR-QMT parameters, and scan time. Based on these results, an optimized CS-SENSE factor of 8 was determined and the test-retest repeatability was further investigated.

RESULTS

A whole-brain SIR imaging of 6 min can be achieved. Bland-Altman analyses indicated excellent agreement between the test and retest sessions with a difference in mean PSR of 0.06% (and a difference in mean R_1f of -0.001 s^-1 ). In addition, the assessment of the intraclass correlation coefficient (ICC) revealed high reliability in nearly all the white matter and gray matter regions. In white matter regions, the ICC was 0.93 (95% confidence interval [CI]: 0.88-0.96, p < 0.001) for PSR, and 0.90 (95% CI: 0.83-0.94, p < 0.001) for R_1f . In gray matter, ICC was 0.84 (95% CI: 0.66-0.93, p < 0.001) in PSR, and 0.98 (95% CI: 0.95-0.99, p < 0.001) for R_1f . The method also showed excellent capability to detect focal lesions in multiple sclerosis.

CONCLUSION

Rapid, reliable, and sensitive whole-brain SIR imaging can be achieved using CS-SENSE, which is expected to significantly promote widespread clinical translation.

Comparisons of Hepatobiliary Phase Imaging Using Combinations of Parallel Imaging and Variable Degrees of Compressed Sensing With Use of Parallel Imaging Alone

OBJECTIVE

This study aimed to compare the image quality in the hepatobiliary phase images of gadoxetic acid-enhanced liver magnetic resonance imaging using parallel imaging (PI) and compressed sensing (CS) reconstruction, using variable CS factors with the standard method using the PI technique.

METHODS

In this study, 64 patients who underwent gadoxetic acid-enhanced liver magnetic resonance imaging at 3.0 T were enrolled. Hepatobiliary phase images were acquired 6 times using liver acquisition with volume acceleration (LAVA) and CS reconstruction with 5 CS factors 1.4, 1.6, 1.8, 2.0, and 2.5 (LAVA-CS 1.4, 1.6, 1.8, 2.0, and 2.5) and standard LAVA (LAVA-noCS). For objective analysis, the signal intensity ratios (SIRs) of the liver-to-spleen (SIRliver/spleen), liver-to-portal vein (SIRliver/portal vein), and liver-to-fat (SIRliver/fat) were estimated. For subjective analysis, 2 radiologists independently evaluated the quality of all the images.

RESULTS

The objective analysis demonstrated no significant difference in all evaluation parameters of all the images. Subjective analysis revealed that the scores of all evaluation items were higher for LAVA-noCS images than for LAVA-CS images, and only LAVA-CS 1.4 did not significantly differ from LAVA-noCS in all evaluation items (P = 1.00 in 2 readers).

CONCLUSIONS

A CS factor of 1.4 in the hepatobiliary phase image with combined PI and CS can reduce the scan time without degrading the image quality compared with the standard method.

Latest Advances in Image Acceleration: All Dimensions are Fair Game

Magnetic resonance imaging (MRI) is a versatile modality that can generate high-resolution images with a variety of tissue contrasts. However, MRI is a slow technique and requires long acquisition times, which increase with higher temporal and spatial resolution and/or when multiple contrasts and large volumetric coverage is required. In order to speedup MR data acquisition, several approaches have been introduced in the literature. Most of these techniques acquire less data than required and exploit intrinsic redundancies in the MR images to recover the information that was not sampled. This article presents a review of MR acquisition and reconstruction methods that have exploited redundancies in the temporal, spatial, and contrast/parametric dimensions to accelerate image data acquisition, focusing on cardiac and abdominal MR imaging applications. The review describes how each of these dimensions has been separately exploited for speeding up MR acquisition to then discuss more advanced techniques where multiple dimensions are exploited together for further reducing scan times. Finally, future directions for multidimensional image acceleration and remaining technical challenges are discussed. EVIDENCE LEVEL: 5 TECHNICAL EFFICACY: 1.

Simultaneous multi-parametric acquisition and reconstruction techniques in cardiac magnetic resonance imaging: Basic concepts and status of clinical development

Simultaneous multi-parametric acquisition and reconstruction techniques (SMART) are gaining attention for their potential to overcome some of cardiovascular magnetic resonance imaging's (CMR) clinical limitations. The major advantages of SMART lie within their ability to simultaneously capture multiple "features" such as cardiac motion, respiratory motion, T1/T2 relaxation. This review aims to summarize the overarching theory of SMART, describing key concepts that many of these techniques share to produce co-registered, high quality CMR images in less time and with less requirements for specialized personnel. Further, this review provides an overview of the recent developments in the field of SMART by describing how they work, the parameters they can acquire, their status of clinical testing and validation, and by providing examples for how their use can improve the current state of clinical CMR workflows. Many of the SMART are in early phases of development and testing, thus larger scale, controlled trials are needed to evaluate their use in clinical setting and with different cardiac pathologies.

Emerging Techniques and Future Directions: Fast and Portable Magnetic Resonance Imaging

Fast MRI and portable MRI are emerging as promising technologies to improve the speed, efficiency, and availability of MR imaging. Fast MRI methods are increasingly being adopted to create screening protocols for the diagnosis and management of acute pathology in the emergency department. Faster imaging can facilitate timely diagnosis, reduce motion artifacts, and improve departmental MR operations. Point-of-care and portable MRI are emerging technologies that require radiologists to reenvision the role of MRI as a tool with greater accessibility, fewer siting constraints, and the ability to provide valuable diagnostic information at the bedside. Recently introduced commercially available pulse sequences and new MRI scanners are bringing these technologies closer to the patient's clinical setting, and we expect their use to only increase over the coming decade. This article provides an overview of these emerging technologies for emergency radiologists.

State of the Art and Future Opportunities in MRI-Guided Robot-Assisted Surgery and Interventions

Magnetic resonance imaging (MRI) can provide high-quality 3-D visualization of target anatomy, surrounding tissue, and instrumentation, but there are significant challenges in harnessing it for effectively guiding interventional procedures. Challenges include the strong static magnetic field, rapidly switching magnetic field gradients, high-power radio frequency pulses, sensitivity to electrical noise, and constrained space to operate within the bore of the scanner. MRI has a number of advantages over other medical imaging modalities, including no ionizing radiation, excellent soft-tissue contrast that allows for visualization of tumors and other features that are not readily visible by other modalities, true 3-D imaging capabilities, including the ability to image arbitrary scan plane geometry or perform volumetric imaging, and capability for multimodality sensing, including diffusion, dynamic contrast, blood flow, blood oxygenation, temperature, and tracking of biomarkers. The use of robotic assistants within the MRI bore, alongside the patient during imaging, enables intraoperative MR imaging (iMRI) to guide a surgical intervention in a closed-loop fashion that can include tracking of tissue deformation and target motion, localization of instrumentation, and monitoring of therapy delivery. With the ever-expanding clinical use of MRI, MRI-compatible robotic systems have been heralded as a new approach to assist interventional procedures to allow physicians to treat patients more accurately and effectively. Deploying robotic systems inside the bore synergizes the visual capability of MRI and the manipulation capability of robotic assistance, resulting in a closed-loop surgery architecture. This article details the challenges and history of robotic systems intended to operate in an MRI environment and outlines promising clinical applications and associated state-of-the-art MRI-compatible robotic systems and technology for making this possible.

Gradient-echo-train-based sub-millisecond periodic event encoded dynamic imaging with random (k, t)-space undersampling: k-t get-SPEEDI

Purpose

The gradient‐echo‐train‐based Sub‐millisecond Periodic Event Encoded Dynamic Imaging (get‐SPEEDI) technique provides ultrahigh temporal resolutions (∼0.6 ms) for detecting rapid physiological activities, but its practical adoption can be hampered by long scan times. This study aimed at developing a more efficient variant of get‐SPEEDI for reducing the scan time without degrading temporal resolution or image quality.

Methods

The proposed pulse sequence, named k‐t get‐SPEEDI, accelerated get‐SPEEDI acquisition by undersampling the k‐space phase‐encoding lines semi‐randomly. At each time frame, k‐space was fully sampled in the central region whereas randomly undersampled in the outer regions. A time‐series of images was reconstructed using an algorithm based on the joint partial separability and sparsity constraints. To demonstrate the performance of k‐t get‐SPEEDI, images of human aortic valve opening and closing were acquired with 0.6‐ms temporal resolution and compared with those from conventional get‐SPEEDI.

Results

k‐t get‐SPEEDI achieved a 2‐fold scan time reduction over the conventional get‐SPEEDI (from ∼6 to ∼3 min), while achieving comparable SNRs and contrast‐to‐noise ratio (CNRs) for visualizing the dynamic process of aortic valve: SNR/CNR ≈ 70/38 vs. 73/39 in the k‐t and conventional get‐SPEEDI scans, respectively. The time courses of aortic valve area also matched well between these two sequences with a correlation coefficient of 0.86.

Conclusions

The k‐t get‐SPEEDI pulse sequence was able to half the scan time without compromising the image quality and ultrahigh temporal resolution. Additional scan time reduction may also be possible, facilitating in vivo adoptions of SPEEDI techniques.

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An Investigation of 2D Spine Magnetic Resonance Imaging (MRI) with Compressed Sensing (CS)

OBJECTIVE

To investigate the feasibility of compressed sensing MRI (CS-MRI) in the application of 2D spinal imaging and compare its performance with conventional MR imaging (non-CS-MRI).

METHODS

The CS imaging protocol was optimized on 5 volunteers. Non-CS-MRI and CS-MRI of 2D sagittal T1 weighted imaging (WI), Sag T2WI, and axial T2WI were performed for 71 patients (22 cervical, 8 thoracic, 41 lumbar MRI). Paired t tests were conducted to compare the total scan time. Three radiologists assessed image quality and lesion diagnosis independently. A Kendall W test was performed to assess interobserver agreement of the image quality scores and lesion diagnosis between readers. A nonparametric test (Wilcoxon test) was performed to compare the image quality. For lesion diagnosis, the interobserver and interstudy agreements were evaluated by kappa analysis. Paired t tests were conducted for SNR and CNR comparison.

RESULTS

The mean scan time for spine CS-MRI (4 min 28.7 s ± 34.6 s) was significantly shorter than that with non-CS-MRI (7 min 21.3 s ± 38.7 s, t =  - 47.464, P < 0.0001). CS-MRI achieved higher SNR and CNR than Non-CS-MRI in image quality assessment. Interobserver agreements of lesion diagnosis were excellent between non-CS-MRI and CS-MRI (kappa value from 0.913 to 1.000, P < 0.001). Interstudy agreements of lesion assessments were also excellent (kappa value = 1.000, with P < 0.001).

CONCLUSION

CS-MRI spine imaging can significantly reduce the scan time, while maintaining comparable imaging quality to non-CS-MRI.

Sparse Damage Detection with Complex Group Lasso and Adaptive Complex Group Lasso

Sparsity-based methods have recently come to the foreground of damage detection applications posing a robust and efficient alternative for traditional approaches. At the same time, low-frequency inspection is known to enable global monitoring with waves propagating over large distances. In this paper, a single sensor complex Group Lasso methodology for the problem of structural defect localization by means of compressive sensing and complex low-frequency response functions is presented. The complex Group Lasso methodology is evaluated on composite plates with induced scatterers. An adaptive setting of the methodology is also proposed to further enhance resolution. Results from both approaches are compared with a full-array, super-resolution MUSIC technique of the same signal model. Both algorithms are shown to demonstrate high and competitive performance.

Comprehensive Account of Sodium Imaging and Spectroscopy for Brain Research

Sodium (²³Na) is a vital component of neuronal cells and plays a key role in various signal transmission processes. Hence, information on sodium distribution in the brain using magnetic resonance imaging (MRI) provides useful information on neuronal health. ²³Na MRI and MR spectroscopy (MRS) improve the diagnosis, prognosis, and clinical monitoring of neurological diseases but confront some inherent limitations that lead to low signal-to-noise ratio, longer scan time, and diminished partial volume effects. Recent advancements in multinuclear MR technology have helped in further exploration in this domain. We aim to provide a comprehensive description of ²³Na MRI and MRS for brain research including the following aspects: (a) theoretical background for understanding ²³Na MRI and MRS fundamentals; (b) technological advancements of ²³Na MRI with respect to pulse sequences, RF coils, and sodium compartmentalization; (c) applications of ²³Na MRI in the early diagnosis and prognosis of various neurological disorders; (d) structural-chronological evolution of sodium spectroscopy in terms of its numerous applications in human studies; (e) the data-processing tools utilized in the quantitation of sodium in the respective anatomical regions.

Generative adversarial network-based post-processed image super-resolution technology for accelerating brain MRI: comparison with compressed sensing

BACKGROUND

It is unclear whether deep-learning-based super-resolution technology (SR) or compressed sensing technology (CS) can accelerate magnetic resonance imaging (MRI) .

PURPOSE

To compare SR accelerated images with CS images regarding the image similarity to reference 2D- and 3D gradient-echo sequence (GRE) brain MRI.

MATERIAL AND METHODS

We prospectively acquired 1.3× and 2.0× faster 2D and 3D GRE images of 20 volunteers from the reference time by reducing the matrix size or increasing the CS factor. For SR, we trained the generative adversarial network (GAN), upscaling the low-resolution images to the reference images with twofold cross-validation. We compared the structural similarity (SSIM) index of accelerated images to the reference image. The rate of incorrect answers of a radiologist discriminating faster and reference image was used as a subjective image similarity (ISM) index.

RESULTS

The SR demonstrated significantly higher SSIM than the CS (SSIM=0.9993-0.999 vs. 0.9947-0.9986; P < 0.001). In 2D GRE, it was challenging to discriminate the SR image from the reference image, compared to the CS (ISM index 40% vs. 17.5% in 1.3×; P = 0.039 and 17.5% vs. 2.5% in 2.0×; P = 0.034). In 3D GRE, the CS revealed a significantly higher ISM index than the SR (22.5% vs. 2.5%; P = 0.011) in 2.0 × faster images. However, the ISM index was identical for the 2.0× CS and 1.3× SR (22.5% vs. 27.5%; P = 0.62) with comparable time costs.

CONCLUSION

The GAN-based SR outperformed CS in image similarity with 2D GRE for MRI acceleration. In addition, CS was more advantageous in 3D GRE than SR.

Image quality and acquisition time assessments for phase oversampling in compressed sensing sensitivity encoding: Comparison with conventional SENSE

This study compared sensitivity encoding (SENSE) and compressed sensing sensitivity encoding (CS-SENSE) for phase oversampling distance and assessed its impact on image quality and image acquisition time. The experiment was performed with a large diameter phantom using 16-channel anterior body coils. All imaging data were divided into three groups according to the parallel imaging technique and oversampling distances: groups A (SENSE with phase oversampling distance of 150 mm), B (CS-SENSE with phase oversampling distance of 100 mm), and C (CS-SENSE with phase oversampling distance of 75 mm). No statistically significant differences were observed among groups A, B, and C regarding both T2 and T1 turbo spin-echo (TSE) sequences using an acceleration factor (AF) of 2 (p = 0.301 and 0.289, respectively). In comparison with AF 2 of group A, the scan time of AF 2 of groups B and C was reduced by 11.2% and 23.5% (T2 TSE) and 15.8% and 22.7% (T1 TSE), respectively, while providing comparable image quality. Significant image noise and aliasing artifact were more evident at AF ≥ 2 in group A compared with groups B and C. CS-SENSE with a less phase oversampling distance can reduce image acquisition time without image quality degradation compared with that of SENSE, despite the increase in aliasing artifact as the AF increased in both CS-SENSE and SENSE.

Compressed Sensing in Sodium Magnetic Resonance Imaging: Techniques, Applications, and Future Prospects

Sodium (²³ Na) yields the second strongest nuclear magnetic resonance (NMR) signal in biological tissues and plays a vital role in cell physiology. Sodium magnetic resonance imaging (MRI) can provide insights into cell integrity and tissue viability relative to pathologies without significant anatomical alternations, and thus it is considered to be a potential surrogate biomarker that provides complementary information for standard hydrogen (¹ H) MRI in a noninvasive and quantitative manner. However, sodium MRI suffers from a relatively low signal-to-noise ratio and long acquisition times due to its relatively low NMR sensitivity. Compressed sensing-based (CS-based) methods have been shown to accelerate sodium imaging and/or improve sodium image quality significantly. In this manuscript, the basic concepts of CS and how CS might be applied to improve sodium MRI are described, and the historical milestones of CS-based sodium MRI are briefly presented. Representative advanced techniques and evaluation methods are discussed in detail, followed by an expose of clinical applications in multiple anatomical regions and diseases as well as thoughts and suggestions on potential future research prospects of CS in sodium MRI. EVIDENCE LEVEL: 5 TECHNICAL EFFICACY: Stage 1.

Prognosis in patients with coronary heart disease and breath-holding limitations: a free-breathing cardiac magnetic resonance protocol at 3.0 T

Background and purpose

Conventional cardiac magnetic resonance (CCMR) imaging is usually performed with breath-holding (BH), which is adverse in patients with BH limitations. We explored the ability of a free-breathing CMR (fCMR) protocol to prognosticate in patients with coronary heart diseases (CHD) and limited BH ability.

Methods

Sixty-seven patients with CHD and limited BH abilities were prospectively enrolled in this study. All patients underwent comprehensive fCMR imaging at 3.0 T. The fCMR protocols included compressed sensing (CS) single-shot cine acceleration imaging, and motion-corrected (MOCO), single-shot late gadolinium enhancement (LGE) imaging. Image quality (IQ) of the cine and LGE images was evaluated based on the 5-point Likert scale. The value of fMRI in providing a prognosis in patients with CHD was assessed. Statistical methods included the T test, Mann–Whitney test, Kappa test, Kaplan–Meier curve, Log-rank test, Cox proportional hazard regression analysis, and receiver operating characteristic curves.

Results

All IQ scores of the short axis CS-cine and both the short and long axes MOCO LGE images were ≥ 3 points. Over a median follow-up of 31 months (range 3.8–38.2), 25 major adverse cardiovascular events (MACE) occurred. In the univariate analysis, infarction size (IS), left ventricular ejection fraction (LVEF), 3D-Global peak longitudinal strain (3D-GPLS), heart failure classification were significantly associated with MACE. When the significantly univariate MACE predictors, added to the multivariate analysis, which showed IS (HR 1.02; 95% CI 1.00–1.05; p = 0.048) and heart failure with preserved EF (HR 0.20; 95% CI 0.04–0.98; p = 0.048) correlated positively with MACE. The optimal cutoff value for LVEF, 3D-GPLS, and IS in predicting MACE was 34.2%, − 5.7%, and 26.1% respectively, with a sensitivity of 90.5%, 64%, and 96.0% and specificity of 72%, 95.2%, and 85.7% respectively.

Conclusions

The fCMR protocol can be used to make prognostic assessments in patients with CHD and BH limitations by calculating IS and LVEF.

Joint total variation-based reconstruction of multiparametric magnetic resonance images for mapping tissue types

Multispectral analysis of coregistered multiparametric magnetic resonance (MR) images provides a powerful method for tissue phenotyping and segmentation. Acquisition of a sufficiently varied set of multicontrast MR images and parameter maps to objectively define multiple normal and pathologic tissue types can require long scan times. Accelerated MRI on clinical scanners with multichannel receivers exploits techniques such as parallel imaging, while accelerated preclinical MRI scanning must rely on alternate approaches. In this work, tumor-bearing mice were imaged at 7 T to acquire k-space data corresponding to a series of images with varying T1-, T2- and T2*-weighting. A joint reconstruction framework is proposed to reconstruct a series of T1-weighted images and corresponding T1 maps simultaneously from undersampled Cartesian k-space data. The ambiguity introduced by undersampling was resolved by using model-based constraints and structural information from a reference fully sampled image as the joint total variation prior. This process was repeated to reconstruct T2-weighted and T2*-weighted images and corresponding maps of T2 and T2* from undersampled Cartesian k-space data. Validation of the reconstructed images and parameter maps was carried out by computing tissue-type maps, as well as maps of the proton density fat fraction (PDFF), proton density water fraction (PDwF), fat relaxation rate ( R2f*) and water relaxation rate ( R2w*) from the reconstructed data, and comparing them with ground truth (GT) equivalents. Tissue-type maps computed using 18% k-space data were visually similar to GT tissue-type maps, with dice coefficients ranging from 0.43 to 0.73 for tumor, fluid adipose and muscle tissue types. The mean T1 and T2 values within each tissue type computed using only 18% k-space data were within 8%-10% of the GT values from fully sampled data. The PDFF and PDwF maps computed using 27% k-space data were within 3%-15% of GT values and showed good agreement with the expected values for the four tissue types.

On Hallucinations in Tomographic Image Reconstruction

Tomographic image reconstruction is generally an ill-posed linear inverse problem. Such ill-posed inverse problems are typically regularized using prior knowledge of the sought-after object property. Recently, deep neural networks have been actively investigated for regularizing image reconstruction problems by learning a prior for the object properties from training images. However, an analysis of the prior information learned by these deep networks and their ability to generalize to data that may lie outside the training distribution is still being explored. An inaccurate prior might lead to false structures being hallucinated in the reconstructed image and that is a cause for serious concern in medical imaging. In this work, we propose to illustrate the effect of the prior imposed by a reconstruction method by decomposing the image estimate into generalized measurement and null components. The concept of a hallucination map is introduced for the general purpose of understanding the effect of the prior in regularized reconstruction methods. Numerical studies are conducted corresponding to a stylized tomographic imaging modality. The behavior of different reconstruction methods under the proposed formalism is discussed with the help of the numerical studies.

3D Whole-Body MRI of the Musculoskeletal System

With its outstanding soft tissue contrast, spatial resolution, and multiplanar capacities, magnetic resonance imaging (MRI) has become a widely used technique. Whole-body MRI (WB-MRI) has been introduced among diagnostic methods for the staging and follow-up assessment in oncologic patients, and international guidelines recommend its use. In nononcologic applications, WB-MRI is as a promising imaging tool in inflammatory diseases, such as seronegative arthritis and inflammatory myopathies. Technological advances have facilitated the introduction of three-dimensional (3D) almost isotropic sequences in MRI examinations covering the whole body. The possibility to reformat 3D images in any plane with equal or almost equal resolution offers comprehensive understanding of the anatomy, easier disease detection and characterization, and finally contributes to correct treatment planning. This article illustrates the basic principles, advantages, and limitations of the 3D approach in WB-MRI examinations and provides a short review of the literature.

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.

Comparison of Compressed Sensing and Gradient and Spin-Echo in Breath-Hold 3D MR Cholangiopancreatography: Qualitative and Quantitative Analysis

While magnetic resonance cholangiopancreatography (MRCP) is routinely used, compressed sensing MRCP (CS-MRCP) and gradient and spin-echo MRCP (GRASE-MRCP) with breath-holding (BH) may allow sufficient image quality with shorter acquisition times. This study qualitatively and quantitatively compared BH-CS-MRCP and BH-GRASE-MRCP and evaluated their clinical effectiveness. Data from 59 consecutive patients who underwent both BH-CS-MRCP and BH-GRASE-MRCP were qualitatively analyzed using a five-point Likert-type scale. The signal-to-noise ratio (SNR) of the common bile duct (CBD), contrast-to-noise ratio (CNR) of the CBD and liver, and contrast ratio between periductal tissue and the CBD were measured. Paired t-test, Wilcoxon signed-rank test, and McNemar’s test were used for statistical analysis. No significant differences were found in overall image quality or duct visualization of the CBD, right and left 1st level intrahepatic duct (IHD), cystic duct, and proximal pancreatic duct (PD). BH-CS-MRCP demonstrated higher background suppression and better visualization of right (p = 0.004) and left 2nd level IHD (p < 0.001), mid PD (p = 0.003), and distal PD (p = 0.041). Image quality degradation was less with BH-GRASE-MRCP than BH-CS-MRCP (p = 0.025). Of 24 patients with communication between a cyst and the PD, 21 (87.5%) and 15 patients (62.5%) demonstrated such communication on BH-CS-MRCP and BH-GRASE-MRCP, respectively. SNR, contrast ratio, and CNR of BH-CS-MRCP were higher than BH-GRASE-MRCP (p < 0.001). Both BH-CS-MRCP and BH-GRASE-MRCP are useful imaging methods with sufficient image quality. Each method has advantages, such as better visualization of small ducts with BH-CS-MRCP and greater time saving with BH-GRASE-MRCP. These differences allow diverse choices for visualization of the pancreaticobiliary tree in clinical practice.

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.

Super-resolution head and neck MRA using deep machine learning

PURPOSE

To probe the feasibility of deep learning-based super-resolution (SR) reconstruction applied to nonenhanced MR angiography (MRA) of the head and neck.

METHODS

High-resolution 3D thin-slab stack-of-stars quiescent interval slice-selective (QISS) MRA of the head and neck was obtained in eight subjects (seven healthy volunteers, one patient) at 3T. The spatial resolution of high-resolution ground-truth MRA data in the slice-encoding direction was reduced by factors of 2 to 6. Four deep neural network (DNN) SR reconstructions were applied, with two based on U-Net architectures (2D and 3D) and two (2D and 3D) consisting of serial convolutions with a residual connection. SR images were compared to ground-truth high-resolution data using Dice similarity coefficient (DSC), structural similarity index measure (SSIM), arterial diameter, and arterial sharpness measurements. Image review of the optimal DNN SR reconstruction was done by two experienced neuroradiologists.

RESULTS

DNN SR of up to twofold and fourfold lower-resolution (LR) input volumes provided images that resembled those of the original high-resolution ground-truth volumes for intracranial and extracranial arterial segments, and improved DSC, SSIM, arterial diameters, and arterial sharpness relative to LR volumes (P < .001). The 3D DNN SR outperformed 2D DNN SR reconstruction. According to two neuroradiologists, 3D DNN SR reconstruction consistently improved image quality with respect to LR input volumes (P < .001).

CONCLUSION

DNN-based SR reconstruction of 3D head and neck QISS MRA offers the potential for up to fourfold reduction in acquisition time for neck vessels without the need to commensurately sacrifice spatial resolution.

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.

[Cardiac magnetic resonance imaging : Trends and developments]

BACKGROUND

In its almost 25 years of clinical use, cardiac magnetic resonance imaging (CMR) has been developed for a wide range of indications due to the development of robust techniques and their comprehensive validation. CMR-based assessment of cardiac volumes and systolic ventricular function as well as the characterization of focal myocardial scars belongs today to standard cardiac imaging. More recently, the introduction of accelerated acquisition techniques, quantitative myocardial T1- and T2-mapping methods and 4‑dimensional (4D) flow measurements as well as new postprocessing techniques such as myocardial feature tracking have attracted attention.

METHODS

This review is based on a comprehensive literature search in the PubMed database on new CMR techniques and their clinical application.

RESULTS AND CONCLUSION

This article provides an overview of the latest technical developments in the field of CMR and their possible applications based on the most important clinical MR issues.

Magnetic resonance imaging with submillisecond temporal resolution

PURPOSE

To demonstrate an MRI technique-Submillisecond Periodic Event Encoded Dynamic Imaging (SPEEDI)-for capturing cyclic dynamic events with submillisecond temporal resolution.

METHODS

The SPEEDI technique is based on an FID or an echo signal in which each time point in the signal is used to sample a distinct k-space raster, followed by repeated FIDs or echoes to produce the remaining k-space data in each k-space raster. All acquisitions are synchronized with a cyclic event, resulting in a set of time-resolved images of the cyclic event with a temporal resolution determined by the dwell time. In SPEEDI, spatial encoding is accomplished by phase encoding. The SPEEDI technique was demonstrated in two experiments at 3 T to (1) visualize fast-changing electric currents that mimicked the waveform of an action potential, and (2) characterize rapidly decaying eddy currents in an MRI system, with a temporal resolution of 0.2 ms and 0.4 ms, respectively. In both experiments, compressed sensing was incorporated to reduce the scan times. Phase difference maps related to the dynamics of electric currents or eddy currents were then obtained.

RESULTS

In the first experiment, time-resolved phase maps resulting from the action potential-mimicking current waveform were successfully obtained and agreed well with theoretical calculations (normalized RMS error = 0.07). In the second experiment, spatially resolved eddy current phase maps revealed time constants (27.1 ± 0.2 ms, 41.1 ± 3.5 ms, and 34.8 ± 0.7 ms) that matched well with those obtained from an established method using point sources (26.4 ms, 41.2 ms and 34.8 ms). For both experiments, phase maps from fully sampled and compressed-sensing-accelerated k-space data exhibited a high structural similarity (> 0.8) despite a two-fold to three-fold acceleration.

CONCLUSIONS

We have illustrated that SPEEDI can provide submillisecond temporal resolution. This capability will likely lead to future exploration of ultrafast, cyclic biomedical processes using MRI.

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.

Dynamic MRI reconstruction with end-to-end motion-guided network

Temporal correlation in dynamic magnetic resonance imaging (MRI), such as cardiac MRI, is informative and important to understand motion mechanisms of body regions. Modeling such information into the MRI reconstruction process produces temporally coherent image sequence and reduces imaging artifacts and blurring. However, existing deep learning based approaches neglect motion information during the reconstruction procedure, while traditional motion-guided methods are hindered by heuristic parameter tuning and long inference time. We propose a novel dynamic MRI reconstruction approach called MODRN and an end-to-end improved version called MODRN(e2e), both of which enhance the reconstruction quality by infusing motion information into the modeling process with deep neural networks. The central idea is to decompose the motion-guided optimization problem of dynamic MRI reconstruction into three components: Dynamic Reconstruction Network, Motion Estimation and Motion Compensation. Extensive experiments have demonstrated the effectiveness of our proposed approach compared to other state-of-the-art approaches.

Cardiac Magnetic Resonance Quantification of Structure-Function Relationships in Heart Failure

Classification of heart failure is based on the left ventricular ejection fraction (EF): preserved EF, midrange EF, and reduced EF. There remains an unmet need for further heart failure phenotyping of ventricular structure-function relationships. Because of high spatiotemporal resolution, cardiac magnetic resonance (CMR) remains the reference modality for quantification of ventricular contractile function. The authors aim to highlight novel frameworks, including theranostic use of ferumoxytol, to enable more efficient evaluation of ventricular function in heart failure patients who are also frequently anemic, and to discuss emerging quantitative CMR approaches for evaluation of ventricular structure-function relationships in heart failure.

Accelerating CEST MRI in the mouse brain at 9.4 T by exploiting sparsity in the Z-spectrum domain

PURPOSE

Chemical exchange saturation transfer (CEST) is an MR contrast modality offering an enhanced sensitivity for the detection of dilute metabolites with exchangeable protons. Quantitative analysis requires the acquisition of a number of images (usually between 20 and 50 RF offsets) per Z-spectrum, leading to long acquisition times of the order of 5-40 min in practice. In this work, we explore the possibility of employing sparsity in the Z-spectrum domain (irradiation offset dimension) to provide an accelerated acquisition scheme without compromising the quality of reconstructed CEST spectra.

METHOD AND THEORY

Ex vivo and in vivo data were acquired on an experimental, small animal 9.4 T system. Three different reconstruction methods were tested: k-Z SPARSE, k-Z SLR and k-Z principal component analysis (PCA) using retrospective undersampling with net acceleration factors R = 2, 3, 5. The quality of the reconstructed data was compared with respect to CEST spectra and full magnetization transfer ratio (MTR) asymmetry maps.

RESULTS

In both phantom and in vivo data, CEST spectra and the resulting MTR asymmetry maps were reconstructed without significant deterioration in data quality. For a low acceleration factor (R = 2, 3) all applied methods resulted in similar data quality, while for high acceleration factor (R = 5) only k-Z PCA and k-Z SLR could be used. Loss in spatial resolution was observed in reconstruction with k-Z PCA for all acceleration factors. An example of prospective undersampling with acceleration factor R = 3 and k-Z PCA reconstruction demonstrates improved CEST maps when compared with fully sampled data acquisition with either three times longer scan duration or threefold prolonged acquisition window per frequency offset.

CONCLUSION

The acquisition time of CEST spectra can be significantly accelerated by exploiting the sparsity of the Z-domain. For prospective and retrospective analysis using k-Z PCA, an acceleration factor of up to R = 3 can be used without significant loss in data quality.

Sparse MR Image Reconstruction Considering Rician Noise Models: A CNN Approach

Compressive sensing (CS) provides a potential platform for acquiring slow and sequential data, as in magnetic resonance (MR) imaging. However, CS requires high computational time for reconstructing MR images from sparse k-space data, which restricts its usage for high speed online reconstruction and wireless communications. Another major challenge is removal of Rician noise from magnitude MR images which changes the image characteristics, and thus affects the clinical usefulness. The work carried out so far predominantly models MRI noise as a Gaussian type. The use of advanced noise models primarily Rician type in CS paradigm is less explored. In this work, we develop a novel framework to reconstruct MR images with high speed and visual quality from noisy sparse k-space data. The proposed algorithm employs a convolutional neural network (CNN) to denoise MR images corrupted with Rician noise. To extract local features, the algorithm exploits signal similarities by processing similar patches as a group. An imperative reduction in the run time has been achieved as the CNN has been trained on a GPU with Convolutional Architecture for Fast Feature Embedding framework making it suitable for online reconstruction. The CNN based reconstruction also eliminates the necessity of optimization and prediction of noise level while denoising, which is the major advantage over existing state-of-the-art-techniques. Analytical experiments have been carried out with various undersampling schemes and the experimental results demonstrate high accuracy and consistent peak signal to noise ratio even at 20-fold undersampling. High undersampling rates provide scope for wireless transmission of k-space data and high speed reconstruction provides applicability of our algorithm for remote health monitoring.

Combined signal averaging and compressed sensing: impact on quality of contrast-enhanced fat-suppressed 3D turbo field-echo imaging for pharyngolaryngeal squamous cell carcinoma

PURPOSE

To determine whether combined signal averaging and compressed sensing (CS averaging) improves the image quality of contrast-enhanced fat-suppressed T1-weighted three-dimensional turbo field-echo (FS T1W 3D-TFE) for evaluation of pharyngolaryngeal squamous cell carcinoma (PLSCC).

METHODS

This retrospective study included 27 patients with PLSCC. In all patients, contrast-enhanced FS T1W 3D-TFE imaging with CS averaging (number of excitations, 7) and that without CS averaging (number of excitations, 1) were obtained during the same acquisition time. Overall image quality, mucosal enhancement, vessel clarity, motion artifact, lesion conspicuity, and lesion edge sharpness were qualitatively evaluated using a 5-point scale. Images with and without CS averaging were compared using the Wilcoxon signed-rank test. Signal-to-noise ratio (SNR) of the lesion and the muscle structure were compared between the two imaging methods using a paired t-test.

RESULTS

Compared with the images without CS averaging, those with CS averaging showed significantly better overall image quality (p = 0.002), mucosal enhancement (p = 0.009), vessel clarity (p = 0.003), muscle edge clarity (p = 0.002), lesion conspicuity (p = 0.002), and lesion edge sharpness (p = 0.001); and less motion artifact (p < 0.001). The SNRs of the lesion and of the muscle structure were significantly higher for images with CS averaging than those without CS averaging (p < 0.001).

CONCLUSION

CS averaging improves the image quality of contrast-enhanced FS T1W 3D-TFE MR images for evaluation of PLSCC without requiring additional acquisition time.

Technological Advances of Magnetic Resonance Imaging in Today's Health Care Environment

Today's health care environment is shifting rapidly, driven by demographic change and high economic pressures on the system. Furthermore, modern precision medicine requires highly accurate and specific disease diagnostics in a short amount of time. Future imaging technology must adapt to these challenges.Demographic change necessitates scanner technologies tailored to the needs of an aging and increasingly multimorbid patient population. Accordingly, examination times have to be short enough that diagnostic images can be generated even for patients who can only lie in the scanner for a short time because of pain or with low breath-hold capacity.For economic reasons, the rate of nondiagnostic scans due to artifacts should be reduced as far as possible. As imaging plays an increasingly pivotal role in clinical-therapeutic decision making, magnetic resonance (MR) imaging facilities are confronted with an ever-growing number of patients, emphasizing the need for faster acquisitions while maintaining image quality.Lastly, modern precision medicine requires high and standardized image quality as well as quantifiable data in order to develop image-based biomarkers on which subsequent treatment management can rely.In recent decades, a variety of approaches have addressed the challenges of high throughput, demographic change, and precision medicine in MR imaging. These include field strength, gradient, coil and sequence development, as well as an increasing consideration of artificial intelligence. This article reviews state-of-the art MR technology and discusses future implementation from the perspective of what we know today.

Breath-hold compressed-sensing 3D MR cholangiopancreatography compared to free-breathing 3D MR cholangiopancreatography: prospective study of image quality and diagnostic performance in pancreatic disorders

PURPOSE

To compare image quality and diagnostic performance of three magnetic resonance cholangiopancreatography (MRCP) protocols in patients with suspected pancreatic abnormalities: free-breathing standard 3D-MRCP (STD), free-breathing compressed sensing 3D-MRCP (CS), and CS 3D-MRCP with acquisition during a single breath-hold > 20 s (BH-CS).

METHODS

Informed consent was obtained. We performed 57 MRCPs in 56 prospectively included patients (29 men, median age 59 years). The three protocols were performed in random order. Acquisition time was recorded. Two radiologists blinded to the protocols used 5-point scales to assess image quality parameters (overall image quality, amount of artifacts, background suppression, bile and pancreatic duct visualization) and diagnostic performance (anatomical variants, duct abnormalities, cystic lesions).

RESULTS

Acquisition time was 279 s with STD, 176 s with CS (-37%), and 22 s with BH-CS (-93%). STD and BH-CS were not significantly different for overall image quality, artifacts, or background suppression. The BH-CS group had fewer non-diagnostic scans (3% vs. 19% with STD and 21% with CS, p < 0.05), higher-quality scans (78% vs. 66% with STD and 58% with CS, p < 0.05), and milder artifacts (2% vs. 18% with STD and 16% with CS, p < 0.05). The main pancreatic duct was better visualized with BH-CS compared to STD (p = 0.015) and CS (p < 0.001). Diagnostic performance did not differ across the three protocols. There were fewer indeterminate scans in the BH-CS group.

CONCLUSION

3T BH-CS is reliable, saves time, and is not associated with decreases in image quality or diagnostic performance compared to STD and CS.

23 Na-MRI as a Noninvasive Biomarker for Cancer Diagnosis and Prognosis

The influx of sodium (Na⁺) ions into a resting cell is regulated by Na⁺ channels and by Na⁺/H⁺ and Na⁺/Ca²⁺ exchangers, whereas Na⁺ ion efflux is mediated by the activity of Na⁺/K⁺‐ATPase to maintain a high transmembrane Na⁺ ion gradient. Dysfunction of this system leads to changes in the intracellular sodium concentration that promotes cancer metastasis by mediating invasion and migration. In addition, the accumulation of extracellular Na⁺ ions in cancer due to inflammation contributes to tumor immunogenicity. Thus, alterations in the Na⁺ ion concentration may potentially be used as a biomarker for malignant tumor diagnosis and prognosis. However, current limitations in detection technology and a complex tumor microenvironment present significant challenges for the in vivo assessment of Na⁺ concentration in tumor. ²³Na‐magnetic resonance imaging (²³Na‐MRI) offers a unique opportunity to study the effects of Na⁺ ion concentration changes in cancer. Although challenged by a low signal‐to‐noise ratio, the development of ultrahigh magnetic field scanners and specialized sodium acquisition sequences has significantly advanced ²³Na‐MRI. ²³Na‐MRI provides biochemical information that reflects cell viability, structural integrity, and energy metabolism, and has been shown to reveal rapid treatment response at the molecular level before morphological changes occur. Here we review the basis of ²³Na‐MRI technology and discuss its potential as a direct noninvasive in vivo diagnostic and prognostic biomarker for cancer therapy, particularly in cancer immunotherapy. We propose that ²³Na‐MRI is a promising method with a wide range of applications in the tumor immuno‐microenvironment research field and in cancer immunotherapy monitoring.

Level of Evidence

2

Technical Efficacy

Stage 2