Ultrafast imaging: Principles, pitfalls, solutions, and applications

Screening for pancreatic cancer in high-risk individuals using MRI: optimization of scan techniques to detect small lesions

Pancreatic cancer has a dismal prognosis in the general population. However, early detection and treatment of disease in high-risk individuals can improve survival, as patients with localized disease and especially patients with lesions smaller than 10 mm show greatly improved 5-year survival rates. To achieve early detection through MRI surveillance programs, optimization of imaging is required. Advances in MRI technologies in both hardware and software over the years have enabled reliable detection of pancreatic cancer at a small size and early stage. Standardization of dedicated imaging protocols for the pancreas are still lacking. In this review we discuss state of the art scan techniques, sequences, reduction of artifacts and imaging strategies that enable early detection of lesions. Furthermore, we present the imaging features of small pancreatic cancers from a large cohort of high-risk individuals. Refinement of MRI techniques, increased scan quality and the use of artificial intelligence may further improve early detection and the prognosis of pancreatic cancer in a screening setting.

Localization of contrast-enhanced breast lesions in ultrafast screening MRI using deep convolutional neural networks

OBJECTIVES

To develop a deep learning-based method for contrast-enhanced breast lesion detection in ultrafast screening MRI.

MATERIALS AND METHODS

A total of 837 breast MRI exams of 488 consecutive patients were included. Lesion's location was independently annotated in the maximum intensity projection (MIP) image of the last time-resolved angiography with stochastic trajectories (TWIST) sequence for each individual breast, resulting in 265 lesions (190 benign, 75 malignant) in 163 breasts (133 women). YOLOv5 models were fine-tuned using training sets containing the same number of MIP images with and without lesions. A long short-term memory (LSTM) network was employed to help reduce false positive predictions. The integrated system was then evaluated on test sets containing enriched uninvolved breasts during cross-validation to mimic the performance in a screening scenario.

RESULTS

In five-fold cross-validation, the YOLOv5x model showed a sensitivity of 0.95, 0.97, 0.98, and 0.99, with 0.125, 0.25, 0.5, and 1 false positive per breast, respectively. The LSTM network reduced 15.5% of the false positive prediction from the YOLO model, and the positive predictive value was increased from 0.22 to 0.25.

CONCLUSIONS

A fine-tuned YOLOv5x model can detect breast lesions on ultrafast MRI with high sensitivity in a screening population, and the output of the model could be further refined by an LSTM network to reduce the amount of false positive predictions.

CLINICAL RELEVANCE STATEMENT

The proposed integrated system would make the ultrafast MRI screening process more effective by assisting radiologists in prioritizing suspicious examinations and supporting the diagnostic workup.

KEY POINTS

• Deep convolutional neural networks could be utilized to automatically pinpoint breast lesions in screening MRI with high sensitivity. • False positive predictions significantly increased when the detection models were tested on highly unbalanced test sets with more normal scans. • Dynamic enhancement patterns of breast lesions during contrast inflow learned by the long short-term memory networks helped to reduce false positive predictions.

Rapid Whole-Knee Quantification of Cartilage Using T1, T2*, and TRAFF2 Mapping With Magnetic Resonance Fingerprinting

OBJECTIVE

Quantitative Magnetic Resonance Imaging (MRI) holds great promise for the early detection of cartilage deterioration. Here, a Magnetic Resonance Fingerprinting (MRF) framework is proposed for comprehensive and rapid quantification of T1, T2*, and TRAFF2 with whole-knee coverage.

METHODS

A MRF framework was developed to achieve quantification of Relaxation Along a Fictitious Field in the 2nd rotating frame of reference ( TRAFF2) along with T1 and T2*. The proposed sequence acquires 65 measurements of 25 high-resolution slices, interleaved with 7 inversion pulses and 40 RAFF2 trains, for whole-knee quantification in a total acquisition time of 3:25 min. Comparison with reference T1, T2*, and TRAFF2 methods was performed in phantom and in seven healthy subjects at 3 T. Repeatability (test-retest) with and without repositioning was also assessed.

RESULTS

Phantom measurements resulted in good agreement between MRF and the reference with mean biases of -54, 2, and 5 ms for T1, T2*, and TRAFF2, respectively. Complete characterization of the whole-knee cartilage was achieved for all subjects, and, for the femoral and tibial compartments, a good agreement between MRF and reference measurements was obtained. Across all subjects, the proposed MRF method yielded acceptable repeatability without repositioning ( R2 ≥ 0.94) and with repositioning ( R2 ≥ 0.57) for T1, T2*, and TRAFF2.

SIGNIFICANCE

The short scan time combined with the whole-knee coverage makes the proposed MRF framework a promising candidate for the early assessment of cartilage degeneration with quantitative MRI, but further research may be warranted to improve repeatability after repositioning and assess clinical value in patients.

Optimizing variable flip angles in magnetization-prepared gradient-echo sequences for efficient 3D-T1ρ mapping

PURPOSE

To optimize the choice of the flip angles of magnetization-prepared gradient-echo sequences for improved accuracy, precision, and speed of 3D-T1ρ mapping.

METHODS

We propose a new optimization approach for finding variable flip-angle values that improve magnetization-prepared gradient-echo sequences used for 3D-T1ρ mapping. This new approach can improve the accuracy and SNR, while reducing filtering effects. We demonstrate the concept in the three different versions of the magnetization-prepared gradient-echo sequences that are typically used for 3D-T1ρ mapping and evaluate their performance in model agarose phantoms (n = 4) and healthy volunteers (n = 5) for knee joint imaging. We also tested the optimization with sequence parameters targeting faster acquisitions.

RESULTS

Our results show that optimized variable flip angle can improve the accuracy and the precision of the sequences, seen as a reduction of the mean of normalized absolute difference from about 5%-6% to 3%-4% in model phantoms and from 15%-16% to 11%-13% in the knee joint, and improving SNR from about 12-28 to 22-32 in agarose phantoms and about 7-14 to 13-17 in healthy volunteers. The optimization can also compensate for the loss in quality caused by making the sequence faster. This results in sequence configurations that acquire more data per unit of time with SNR and mean of normalized absolute difference measurements close to its slower versions.

CONCLUSION

The optimization of the variable flip angle can be used to increase accuracy and precision, and to improve the speed of the typical imaging sequences used for quantitative 3D-T1ρ mapping of the knee joint.

The investigation of reduced field-of-view diffusion-weighted imaging (DWI) in patients with nasopharyngeal carcinoma: comparison with conventional DWI

BACKGROUND

Field-of-view optimized and constrained undistorted single-shot imaging (FOCUS) is a new sequence that shows enhanced anatomical details, improving the diffusion-weighted (DW) images.

PURPOSE

To investigate the value of FOCUS diffusion-weighted imaging (DWI) in the evaluation of nasopharyngeal carcinoma (NPC) and compare it with the single-shot echo planner imaging (SS-EPI) DWI approach.

MATERIAL AND METHODS

A total of 87 patients with NPC underwent magnetic resonance imaging, including FOCUS and SS-EPI DWI sequences. The signal-to-noise ratio (SNR), signal-intensity ratio (SIR), contrast-to-noise ratio (CNR), and apparent diffusion coefficient (ADC) values of the nasopharyngeal lesions were measured and compared. According to the clinical stages of patients, T and N were divided into early and advanced stage groups, respectively. The mean ADC values of the two techniques were computed, and the area under the curve (AUC) was estimated to calculate the diagnostic efficiency.

RESULTS

Subjective and objective image qualitative values of FOCUS were significantly higher than those of SS-EPI. The ADC values for FOCUS of early T and N stages were significantly lower than those of the advanced stages.

CONCLUSION

FOCUS provides significantly better image quality in NPC compared to SS-EPI, with lower ADC values for early-stage disease than late-stage disease.

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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Non-Invasive Intracranial Pressure Monitoring and Its Applicability in Spaceflight

INTRODUCTION: Neuro-ophthalmic findings collectively defined as Spaceflight-Associated Neuro-ocular Syndrome (SANS) are one of the leading health priorities in astronauts engaging in long duration spaceflight or prolonged microgravity exposure. Though multifactorial in etiology, similarities to terrestrial idiopathic intracranial hypertension (IIH) suggest these changes may result from an increase or impairing in intracranial pressure (ICP). Finding a portable, accessible, and reliable method of monitoring ICP is, therefore, crucial in long duration spaceflight. A review of recent literature was conducted on the biomedical literature search engine PubMed using the search term “non-invasive intracranial pressure”. Studies investigating accuracy of noninvasive and portable methods were assessed. The search retrieved different methods that were subsequently grouped by approach and technique. The majority of publications included the use of ultrasound-based methods with variable accuracies. One of which, noninvasive ICP estimation by optical nerve sheath diameter measurement (nICP_ONSD), presented the highest statistical correlation and prediction values to invasive ICP, with area under the curve (AUC) ranging from 0.75 to 0.964. One study even considers a combination of ONSD with transcranial Doppler (TCD) for an even higher performance. Other methods, such as near-infrared spectroscopy (NIRS), show positive and promising results [good statistical correlation with invasive techniques when measuring cerebral perfusion pressure (CPP): r = 0.83]. However, for its accessibility, portability, and accuracy, ONSD seems to present itself as the up to date, most reliable, noninvasive ICP surrogate and a valuable spaceflight asset.Félix H, Santos Oliveira E. Non-invasive intracranial pressure monitoring and its applicability in spaceflight. Aerosp Med Hum Perform. 2022; 93(6):517–531.

Differential Subsampling with Cartesian Ordering-MRA for Classifying Residual Treated Aneurysms

BACKGROUND AND PURPOSE

Differential Subsampling with Cartesian Ordering (DISCO), an ultrafast high-spatial-resolution head MRA, has been introduced. We aimed to determine the diagnostic performance of DISCO-MRA in grading residual aneurysm in comparison with TOF-MRA in patients with treated intracranial aneurysms.

MATERIALS AND METHODS

Patients with endovascular treatment and having undergone DISCO-MRA, TOF-MRA, and DSA were included for review. The voxel size and acquisition time were 0.75 × 0.75 × 1 mm³/6 seconds for DISCO-MRA and 0.6 × 0.6 × 1 mm³/6 minutes for TOF-MRA. Residual aneurysms were determined using the Modified Raymond-Roy Classification on TOF-MRA and DISCO-MRA by 2 neuroradiologists independently and were compared against DSA as the reference standard. Statistical analysis was performed using the κ statistic and the χ² test.

RESULTS

Sixty-eight treated intracranial aneurysms were included. The intermodality agreement was κ = 0.82 (95% CI, 0.67-0.97) between DISCO and DSA and 0.44 (95% CI, 0.28-0.61) between TOF and DSA. Modified Raymond-Roy Classification scores matched DSA scores in 60/68 cases (88%; χ² = 144.4, P < .001 for DISCO and 46/68 cases (68%; χ² = 65.0, P < .001) for TOF. The diagnostic accuracy for the detection of aneurysm remnants was higher for DISCO (0.96; 95% CI, 0.88-0.99) than for TOF (0.79; 95% CI, 0.68-0.88).

CONCLUSIONS

In patients with endovascularly treated intracranial aneurysms, DISCO-MRA provides superior diagnostic performance in comparison with TOF-MRA in delineating residual aneurysms in a fraction of the time.

DualMMP-GAN: Dual-scale multi-modality perceptual generative adversarial network for medical image segmentation

Multi-modality magnetic resonance imaging (MRI) can reveal distinct patterns of tissue in the human body and is crucial to clinical diagnosis. But it still remains a challenge to obtain diverse and plausible multi-modality MR images due to expense, noise, and artifacts. For the same lesion, different modalities of MRI have big differences in context information, coarse location, and fine structure. In order to achieve better generation and segmentation performance, a dual-scale multi-modality perceptual generative adversarial network (DualMMP-GAN) is proposed based on cycle-consistent generative adversarial networks (CycleGAN). Dilated residual blocks are introduced to increase the receptive field, preserving structure and context information of images. A dual-scale discriminator is constructed. The generator is optimized by discriminating patches to represent lesions with different sizes. The perceptual consistency loss is introduced to learn the mapping between the generated and target modality at different semantic levels. Moreover, generative multi-modality segmentation (GMMS) combining given modalities with generated modalities is proposed for brain tumor segmentation. Experimental results show that the DualMMP-GAN outperforms the CycleGAN and some state-of-the-art methods in terms of PSNR, SSMI, and RMSE in most tasks. In addition, dice, sensitivity, specificity, and Hausdorff95 obtained from segmentation by GMMS are all higher than those from a single modality. The objective index obtained by the proposed methods are close to upper bounds obtained from real multiple modalities, indicating that GMMS can achieve similar effects as multi-modality. Overall, the proposed methods can serve as an effective method in clinical brain tumor diagnosis with promising application potential.

Alternating Learning Approach for Variational Networks and Undersampling Pattern in Parallel MRI Applications

This work proposes an alternating learning approach to learn the sampling pattern (SP) and the parameters of variational networks (VN) in accelerated parallel magnetic resonance imaging (MRI). We investigate four variations of the learning approach, that alternates between improving the SP, using bias-accelerated subset selection, and improving parameters of the VN, using ADAM. The variations include the use of monotone or non-monotone alternating steps and systematic reduction of learning rates. The algorithms learn an effective pair to be used in future scans, including an SP that captures fewer k-space samples in which the generated undersampling artifacts are removed by the VN reconstruction. The quality of the VNs and SPs obtained by the proposed approaches is compared against different methods, including other kinds of joint learning methods and state-of-art reconstructions, on two different datasets at various acceleration factors (AF). We observed improvements visually and in three different figures of merit commonly used in deep learning (RMSE, SSIM, and HFEN) on AFs from 2 to 20 with brain and knee joint datasets when compared to the other approaches. The improvements ranged from 1% to 62% over the next best approach tested with VNs. The proposed approach has shown stable performance, obtaining similar learned SPs under different initial training conditions. We observe that the improvement is not only due to the learned sampling density, it is also due to the learned position of samples in k-space. The proposed approach was able to learn effective pairs of SPs and reconstruction VNs, improving 3D Cartesian accelerated parallel MRI applications.

Cerebral hemodynamics and capillary dysfunction in late-onset major depressive disorder

In major depressive disorder (MDD), perfusion changes in cortico-limbic pathways are interpreted as altered neuronal activity, but they could also signify changes in neurovascular coupling due to altered capillary function. To examine capillary function in late-onset MDD, 22 patients and 22 age- and gender-matched controls underwent perfusion MRI. We measured normalized cerebral blood flow (nCBF), cerebral blood volume (nCBV), and relative transit-time heterogeneity (RTH). Resulting brain oxygenation was estimated in terms of oxygen tension and normalized metabolic rate of oxygen (nCMRO₂). Patients revealed signs of capillary dysfunction (elevated RTH) in the anterior prefrontal cortex and ventral anterior cingulate cortex bilaterally and in the left insulate cortex compared to controls, bilateral hypometabolism (parallel reductions of nCBV, nCBF, and CMRO₂) but preserved capillary function in the subthalamic nucleus and globus pallidus bilaterally, and hyperactivity with preserved capillary function (increased nCBF) in the cerebellum and brainstem. Our data support that perfusion changes in deep nuclei and cerebellum reflect abnormally low and high activity, respectively, in MDD patients, but suggest that microvascular pathology affects neurovascular coupling in ventral circuits. We speculate that microvascular pathology is important for our understanding of etiology of late-onset MDD as well as infererences about resulting brain activity changes.

Fast data-driven learning of parallel MRI sampling patterns for large scale problems

In this study, a fast data-driven optimization approach, named bias-accelerated subset selection (BASS), is proposed for learning efficacious sampling patterns (SPs) with the purpose of reducing scan time in large-dimensional parallel MRI. BASS is applicable when Cartesian fully-sampled k-space measurements of specific anatomy are available for training and the reconstruction method for undersampled measurements is specified; such information is used to define the efficacy of any SP for recovering the values at the non-sampled k-space points. BASS produces a sequence of SPs with the aim of finding one of a specified size with (near) optimal efficacy. BASS was tested with five reconstruction methods for parallel MRI based on low-rankness and sparsity that allow a free choice of the SP. Three datasets were used for testing, two of high-resolution brain images ([Formula: see text]-weighted images and, respectively, [Formula: see text]-weighted images) and another of knee images for quantitative mapping of the cartilage. The proposed approach has low computational cost and fast convergence; in the tested cases it obtained SPs up to 50 times faster than the currently best greedy approach. Reconstruction quality increased by up to 45% over that provided by variable density and Poisson disk SPs, for the same scan time. Optionally, the scan time can be nearly halved without loss of reconstruction quality. Quantitative MRI and prospective accelerated MRI results show improvements. Compared with greedy approaches, BASS rapidly learns effective SPs for various reconstruction methods, using larger SPs and larger datasets; enabling better selection of sampling-reconstruction pairs for specific MRI problems.

Imaging and its Impact on Defining the Oligometastatic State

Successful treatment of oligometastatic disease (OMD) is facilitated through timely detection and localization of disease, both at the time of initial diagnosis (synchronous OMD) and following the initial therapy (metachronous OMD). Hence, imaging plays an indispensable role in management of patients with OMD. However, the challenges and complexities of OMD management are also reflected in the imaging of this entity. While innovations and advances in imaging technology have made a tremendous impact in disease detection and management, there remain substantial and unaddressed challenges for earlier and more accurate establishment of OMD state. This review will provide an overview of the available imaging modalities and their inherent strengths and weaknesses, with a focus on their role and potential in detection and evaluation of OMD in different organ systems. Furthermore, we will review the role of imaging in evaluation of OMD for malignancies of various primary organs, such as the lung, prostate, colon/rectum, breast, kidney, as well as neuroendocrine tumors and gynecologic malignancies. We aim to provide a practical overview about the utilization of imaging for clinicians who play a role in the care of those with, or at risk for OMD.

T1-weighted and T2-weighted MRI image synthesis with convolutional generative adversarial networks

Background

The objective of this study was to propose an optimal input image quality for a conditional generative adversarial network (GAN) in T1-weighted and T2-weighted magnetic resonance imaging (MRI) images.

Materials and methods

A total of 2,024 images scanned from 2017 to 2018 in 104 patients were used. The prediction framework of T1-weighted to T2-weighted MRI images and T2-weighted to T1-weighted MRI images were created with GAN. Two image sizes (512 × 512 and 256 × 256) and two grayscale level conversion method (simple and adaptive) were used for the input images. The images were converted from 16-bit to 8-bit by dividing with 256 levels in a simple conversion method. For the adaptive conversion method, the unused levels were eliminated in 16-bit images, which were converted to 8-bit images by dividing with the value obtained after dividing the maximum pixel value with 256.

Results

The relative mean absolute error (rMAE ) was 0.15 for T1-weighted to T2-weighted MRI images and 0.17 for T2-weighted to T1-weighted MRI images with an adaptive conversion method, which was the smallest. Moreover, the adaptive conversion method has a smallest mean square error (rMSE) and root mean square error (rRMSE), and the largest peak signal-to-noise ratio (PSNR) and mutual information (MI). The computation time depended on the image size.

Conclusions

Input resolution and image size affect the accuracy of prediction. The proposed model and approach of prediction framework can help improve the versatility and quality of multi-contrast MRI tests without the need for prolonged examinations.

Dynamic Contrast Enhancement (DCE) MRI-Derived Renal Perfusion and Filtration: Basic Concepts

Dynamic contrast-enhanced (DCE) MRI monitors the transit of contrast agents, typically gadolinium chelates, through the intrarenal regions, the renal cortex, the medulla, and the collecting system. In this way, DCE-MRI reveals the renal uptake and excretion of the contrast agent. An optimal DCE-MRI acquisition protocol involves finding a good compromise between whole-kidney coverage (i.e., 3D imaging), spatial and temporal resolution, and contrast resolution. By analyzing the enhancement of the renal tissues as a function of time, one can determine indirect measures of clinically important single-kidney parameters as the renal blood flow, glomerular filtration rate, and intrarenal blood volumes. Gadolinium-containing contrast agents may be nephrotoxic in patients suffering from severe renal dysfunction, but otherwise DCE-MRI is clearly useful for diagnosis of renal functions and for assessing treatment response and posttransplant rejection.Here we introduce the concept of renal DCE-MRI, describe the existing methods, and provide an overview of preclinical DCE-MRI applications to illustrate the utility of this technique to measure renal perfusion and glomerular filtration rate in animal models.This publication is based upon work from the COST Action PARENCHIMA, a community-driven network funded by the European Cooperation in Science and Technology (COST) program of the European Union, which aims to improve the reproducibility and standardization of renal MRI biomarkers. This introduction is complemented by two separate publications describing the experimental procedure and data analysis.

Fast multicomponent 3D-T1ρ relaxometry

NMR relaxometry can provide information about the relaxation of the magnetization in different tissues, increasing our understanding of molecular dynamics and biochemical composition in biological systems. In general, tissues have complex and heterogeneous structures composed of multiple pools. As a result, bulk magnetization returns to its original state with different relaxation times, in a multicomponent relaxation. Recovering the distribution of relaxation times in each voxel is a difficult inverse problem; it is usually unstable and requires long acquisition time, especially on clinical scanners. MRI can also be viewed as an inverse problem, especially when compressed sensing (CS) is used. The solution of these two inverse problems, CS and relaxometry, can be obtained very efficiently in a synergistically combined manner, leading to a more stable multicomponent relaxometry obtained with short scan times. In this paper, we will discuss the details of this technique from the viewpoint of inverse problems.

3D fast low-angle shot (FLASH) technique for 3T contrast-enhanced brain MRI in the inpatient and emergency setting: comparison with 3D magnetization-prepared rapid gradient echo (MPRAGE) technique

PURPOSE

To retrospectively evaluate the diagnostic performance of a 1-min contrast-enhanced 3D-FLASH pulse sequence for detecting intracranial enhancing lesions compared to standard contrast-enhanced 3D-MPRAGE pulse sequence.

METHODS

Contrast-enhanced 3D-FLASH (acquisition time 49 s) and contrast-enhanced 3D-MPRAGE (4 min 35 s) pulse sequences were performed consecutively in 110 inpatient/emergency department 3T MRI brain examinations and analyzed by two independent neuroradiologist readers. For each sequence, the readers recorded (1) number of enhancing intracranial lesions; (2) intracranial susceptibility artifact (presence or absence; mm depth of intracranial signal loss); and (3) motion artifact (none, mild, moderate, severe). Inter and intra-reader agreement and reader accuracy relative to a reference standard were determined, and sequence comparison with respect to susceptibility and motion artifacts was performed.

RESULTS

There was substantial intra-reader, inter-sequence agreement [reader 1, κ = 0.70 (95% CI: [0.60, 0.81]); reader 2, κ = 0.70 (95% CI: [0.59, 0.82])] and substantial intra-sequence, inter-reader agreement [3D-MPRAGE assessment, κ = 0.76 (95% CI: [0.66, 0.86]); 3D-FLASH assessment, κ = 0.86 (95% CI: [0.77, 0.94]) for detection of intracranial enhancing lesions. For both readers, the diagnostic accuracy of 3D-FLASH and 3D-MPRAGE was similar (3D-MPRAGE: 86.4 and 88.1%; 3D-FLASH: 88.2 and 84.5%), with no inter-sequence diagnostic accuracy discordancy between the sequences for either reader. 3D-FLASH was associated with less susceptibility artifact (p < 0.001 both readers) and less motion artifact (p < 0.001 both readers).

CONCLUSION

On 3T brain MRI in the inpatient and emergency department setting, 1-min 3D-FLASH pulse sequence achieved comparable diagnostic performance to 4.5 min 3D-MPRAGE pulse sequence for detecting enhancing intracranial lesions, with reduced susceptibility and motion artifacts.

Positron emission tomography/MRI for cardiac diseases assessment

Functional imaging tools have emerged in the last few decades and are increasingly used to assess the function of the human heart in vivo. Positron emission tomography (PET) is used to evaluate myocardial metabolism and blood flow. Magnetic resonance imaging (MRI) is an essential tool for morphological and functional evaluation of the heart. In cardiology, PET is successfully combined with CT for hybrid cardiac imaging. The effective integration of two imaging modalities allows simultaneous data acquisition combining functional, structural and molecular imaging. After PET/CT has been successfully accepted for clinical practices, hybrid PET/MRI is launched. This review elaborates the current evidence of PET/MRI in cardiovascular imaging and its expected clinical applications for a comprehensive assessment of cardiovascular diseases while highlighting the advantages and limitations of this hybrid imaging approach.

MRI Cross-Modality Image-to-Image Translation

We present a cross-modality generation framework that learns to generate translated modalities from given modalities in MR images. Our proposed method performs Image Modality Translation (abbreviated as IMT) by means of a deep learning model that leverages conditional generative adversarial networks (cGANs). Our framework jointly exploits the low-level features (pixel-wise information) and high-level representations (e.g. brain tumors, brain structure like gray matter, etc.) between cross modalities which are important for resolving the challenging complexity in brain structures. Our framework can serve as an auxiliary method in medical use and has great application potential. Based on our proposed framework, we first propose a method for cross-modality registration by fusing the deformation fields to adopt the cross-modality information from translated modalities. Second, we propose an approach for MRI segmentation, translated multichannel segmentation (TMS), where given modalities, along with translated modalities, are segmented by fully convolutional networks (FCN) in a multichannel manner. Both of these two methods successfully adopt the cross-modality information to improve the performance without adding any extra data. Experiments demonstrate that our proposed framework advances the state-of-the-art on five brain MRI datasets. We also observe encouraging results in cross-modality registration and segmentation on some widely adopted brain datasets. Overall, our work can serve as an auxiliary method in medical use and be applied to various tasks in medical fields.

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.

Magnetic resonance fingerprinting for simultaneous renal T1 and T 2 * mapping in a single breath-hold

PURPOSE

To evaluate the use of magnetic resonance fingerprinting (MRF) for simultaneous quantification of T 1 and T 2 ∗ in a single breath-hold in the kidneys.

METHODS

The proposed kidney MRF sequence was based on MRF echo-planar imaging. Thirty-five measurements per slice and overall 4 slices were measured in 15.4 seconds. Group matching was performed for in-line quantification of T 1 and T 2 ∗ . Images were acquired in a phantom and 8 healthy volunteers in coronal orientation. To evaluate our approach, region of interests were drawn in the kidneys to calculate mean values and standard deviations of the T 1 and T 2 ∗ times. Precision was calculated across multiple repeated MRF scans. Gaussian filtering is applied on baseline images to improve SNR and match stability.

RESULTS

T 1 and T 2 ∗ times acquired with MRF in the phantom showed good agreement with reference measurements and conventional mapping methods with deviations of less than 5% for T 1 and less than 10% for T 2 ∗ . Baseline images in vivo were free of artifacts and relaxation times yielded good agreement with conventional methods and literature (deviation T 1 : 7 ± 4 % , T 2 ∗ : 6 ± 3 % ).

CONCLUSIONS

In this feasibility study, the proposed renal MRF sequence resulted in accurate T 1 and T 2 ∗ quantification in a single breath-hold.

Reconstruction techniques for cardiac cine MRI

The present survey describes the state-of-the-art techniques for dynamic cardiac magnetic resonance image reconstruction. Additionally, clinical relevance, main challenges, and future trends of this image modality are outlined. Thus, this paper aims to provide a general vision about cine MRI as the standard procedure in functional evaluation of the heart, focusing on technical methodologies.

Time optimal control-based RF pulse design under gradient imperfections

Purpose

This study incorporates a gradient system imperfection model into an optimal control framework for radio frequency (RF) pulse design.

Theory and Methods

The joint design of minimum‐time RF and slice selective gradient shapes is posed as an optimal control problem. Hardware limitations such as maximal amplitudes for RF and slice selective gradient or its slew rate are included as hard constraints to assure practical applicability of the optimized waveforms. In order to guarantee the performance of the optimized waveform with possible gradient system disturbances such as limited system bandwidth and eddy currents, a measured gradient impulse response function (GIRF) for a specific system is integrated into the optimization.

Results

The method generates optimized RF and pre‐distorted slice selective gradient shapes for refocusing that are able to fully compensate the modeled imperfections of the gradient system under investigation. The results nearly regenerate the optimal results of an idealized gradient system. The numerical Bloch simulations are validated by phantom and in‐vivo experiments on 2 3T scanners.

Conclusions

The presented design approach demonstrates the successful correction of gradient system imperfections within an optimal control framework for RF pulse design.

Reduced field-of-view diffusion-weighted MRI in patients with cervical cancer

OBJECTIVE

Diffusion-weighted imaging (DWI) with reduced field-of-view (FOV) has been shown to provide high spatial resolution with reduced distorsion in the spinal cord, breast, pancreas, and prostate gland. Therefore, we performed this study to evaluate the qualitative image quality and quantitative ADC value of reduced FOV DWI in patients with cervical cancer in comparison with conventional DWI.

METHODS

This study retrospectively included 22 patients (mean age, 53.9 years) with biopsy-proven cervical cancer who underwent pelvic MR imaging including conventional DWI and reduced FOV DWI before therapy. Two observers independently rated image quality for reduced FOV DWI and conventional DWI regarding anatomic detail, lesion conspicuity, presence of artifacts, and overall image quality using the following 4-point scale. Quantitative analysis was performed by measuring the ADC value of the tumor. The Wilcoxon signed-rank test was used to compare qualitative scores and mean ADC value between two DWI sequences.

RESULTS

Reduced FOV DWI achieved significantly better anatomic detail, lesion conspicuity, presence of artifacts, and overall image quality compared to conventional DWI (p < 0.05). There was no significant difference in mean tumor ADC value between the two DWI sequences (0.990 × 10^-3 mm² s^-1 ± 0.364 at reduced FOV DWI vs 1.253 × 10^-3 mm² s^-1 ± 0.387 at conventional DWI) (p = 0.067).

CONCLUSION

Reduced FOV DWI shows better image quality in terms of anatomic detail and lesion conspicuity with fewer artifacts compared to conventional DWI. Advance in knowledge: Reduced FOV DWI may enhance diagnostic performance for evaluation of cervical cancer.

Diagnostic Performance of a 10-Minute Gadolinium-Enhanced Brain MRI Protocol Compared with the Standard Clinical Protocol for Detection of Intracranial Enhancing Lesions

BACKGROUND AND PURPOSE

The development of new MR imaging scanners with stronger gradients and improvement in coil technology, allied with emerging fast imaging techniques, has allowed a substantial reduction in MR imaging scan times. Our goal was to develop a 10-minute gadolinium-enhanced brain MR imaging protocol with accelerated sequences and to evaluate its diagnostic performance compared with the standard clinical protocol.

MATERIALS AND METHODS

Fifty-three patients referred for brain MR imaging with contrast were scanned with a 3T scanner. Each MR image consisted of 5 basic fast precontrast sequences plus standard and accelerated versions of the same postcontrast T1WI sequences. Two neuroradiologists assessed the image quality and the final diagnosis for each set of postcontrast sequences and compared their performances.

RESULTS

The acquisition time of the combined accelerated pre- and postcontrast sequences was 10 minutes and 15 seconds; and of the fast postcontrast sequences, 3 minutes and 36 seconds, 46% of the standard sequences. The 10-minute postcontrast axial T1WI had fewer image artifacts (P < .001) and better overall diagnostic quality (P < .001). Although the 10-minute MPRAGE sequence showed a tendency to have more artifacts than the standard sequence (P = .08), the overall diagnostic quality was similar (P = .66). Moreover, there was no statistically significant difference in the diagnostic performance between the protocols. The sensitivity, specificity, and accuracy values for the 10-minute protocol were 100.0%, 88.9%, and 98.1%.

CONCLUSIONS

The 10-minute brain MR imaging protocol with contrast is comparable in diagnostic performance with the standard protocol in an inpatient motion-prone population, with the additional benefits of reducing acquisition times and image artifacts.

A kernel method for higher temporal resolution MRI using the partial separability (PS) model

The partial separability (PS) model for spatiotemporal signals has been exploited effectively for sparse (k, t)-space sampling in dynamic magnetic resonance imaging (MRI). However, the training data for defining the temporal subspace is reordered by using a projection strategy in the conventional PS model-based method, which results in a suboptimal temporal resolution imaging. To address this issue, a kernel method was presented in this work to reorder the training data to realize a higher temporal resolution MRI. Numerical simulation results show that the MRI temporal resolution could be further improved and the dynamic change of motion object could be accurately captured by the proposed method. In vivo cardiac cine MRI results demonstrate that the proposed method can reconstruct better MR images with higher temporal resolution (up to 8.4 ms per snapshot). This study may find use in ultra-high resolution dynamic MRI.

Comparing an accelerated 3D fast spin-echo sequence (CS-SPACE) for knee 3-T magnetic resonance imaging with traditional 3D fast spin-echo (SPACE) and routine 2D sequences

PURPOSE

To compare a faster, new, high-resolution accelerated 3D-fast-spin-echo (3D-FSE) acquisition sequence (CS-SPACE) to traditional 2D and high-resolution 3D sequences for knee 3-T magnetic resonance imaging (MRI).

MATERIALS AND METHODS

Twenty patients received knee MRIs that included routine 2D (T1, PD ± FS, T2-FS; 0.5 × 0.5 × 3 mm³; ∼10 min), traditional 3D FSE (SPACE-PD-FS; 0.5 × 0.5 × 0.5 mm³; ∼7.5 min), and accelerated 3D-FSE prototype (CS-SPACE-PD-FS; 0.5 × 0.5 × 0.5 mm³; ∼5 min) acquisitions on a 3-T MRI system (Siemens MAGNETOM Skyra). Three musculoskeletal radiologists (MSKRs) prospectively and independently reviewed the studies with graded surveys comparing image and diagnostic quality. Tissue-specific signal-to-noise ratios (SNR) and contrast-to-noise ratios (CNR) were also compared.

RESULTS

MSKR-perceived diagnostic quality of cartilage was significantly higher for CS-SPACE than for SPACE and 2D sequences (p < 0.001). Assessment of diagnostic quality of menisci and synovial fluid was higher for CS-SPACE than for SPACE (p < 0.001). CS-SPACE was not significantly different from SPACE but had lower assessments than 2D sequences for evaluation of bones, ligaments, muscles, and fat (p ≤ 0.004). 3D sequences had higher spatial resolution, but lower overall assessed contrast (p < 0.001). Overall image quality from CS-SPACE was assessed as higher than SPACE (p = 0.007), but lower than 2D sequences (p < 0.001). Compared to SPACE, CS-SPACE had higher fluid SNR and CNR against all other tissues (all p < 0.001).

CONCLUSIONS

The CS-SPACE prototype allows for faster isotropic acquisitions of knee MRIs over currently used protocols. High fluid-to-cartilage CNR and higher spatial resolution over routine 2D sequences may present a valuable role for CS-SPACE in the evaluation of cartilage and menisci.

Prospective motion correction in functional MRI

Due to the intrinsic low sensitivity of BOLD-fMRI long scanning is required. Subject motion during fMRI scans reduces statistical significance of the activation maps and increases the prevalence of false activations. Motion correction is therefore an essential tool for a successful fMRI data analysis. Retrospective motion correction techniques are now commonplace and are incorporated into a wide range of fMRI analysis toolboxes. These techniques are advantageous due to robustness, sequence independence and have minimal impact on the fMRI study setup. Retrospective techniques however, do not provide an accurate intra-volume correction, nor can these techniques correct for the spin-history effects. The application of prospective motion correction in fMRI appears to be effective in reducing false positives and increasing sensitivity when compared to retrospective techniques, particularly in the cases of substantial motion. Especially advantageous in this regard is the combination of prospective motion correction with dynamic distortion correction. Nevertheless, none of the recent methods are able to recover activations in presence of motion that are comparable to no-motion conditions, which motivates further research in the area of adaptive dynamic imaging.

Ultrafast multi-slice spatiotemporally encoded MRI with slice-selective dimension segmented

As a recently emerging method, spatiotemporally encoded (SPEN) magnetic resonance imaging (MRI) has a high robustness to field inhomogeneity and chemical shift effect. It has been broadened from single-slice scanning to multi-slice scanning. In this paper, a novel multi-slice SPEN MRI method was proposed. In this method, the slice-selective dimension was segmented to lower the specific absorption rate (SAR) and improve the image quality. This segmented method, dubbed SeSPEN method, was theoretically analyzed and demonstrated with phantom, lemon and in vivo rat brain experiments. The experimental results were compared with the results obtained from the spin-echo EPI, spin-echo SPEN method and multi-slice global SPEN method proposed by Frydman and coauthors (abbr. GlSPEN method). All the SPEN images were super-resolved reconstructed using deconvolution method. The results indicate that the SeSPEN method retains the advantage of SPEN MRI with respect to resistance to field inhomogeneity and can provide better signal-to-noise ratio than multi-slice GlSPEN MRI technique. The SeSPEN method has comparable SAR to the GlSPEN method while the T1 signal attenuation effect is alleviated. The proposed method will facilitate the multi-slice SPEN MRI to scan more slices within one scan with better image quality.

Development of a symmetric echo planar imaging framework for clinical translation of rapid dynamic hyperpolarized 13 C imaging

PURPOSE

To develop symmetric echo planar imaging (EPI) and a reference scan framework for hyperpolarized ¹³ C metabolic imaging.

METHODS

Symmetric, ramp-sampled EPI with partial Fourier reconstruction was implemented on a 3T scanner. The framework for acquiring a reference scan on the ¹ H channel and applied to ¹³ C data was described and validated in both phantoms and in vivo metabolism of [1-¹³ C]pyruvate.

RESULTS

Ramp-sampled, symmetric EPI provided a substantial increase in the signal-to-noise ratio of the phantom experiments. The reference scan acquired on the ¹ H channel yielded ¹³ C phantom images that varied in mean signal intensity <2%, compared with ¹³ C images reconstructed with a reference scan directly measured on the ¹³ C channel. The structural similarity index and dynamic time course from in vivo ¹³ C data further support the application of a ¹ H reference scan to ¹³ C data to mitigate Nyquist ghost artifacts.

CONCLUSION

Ramp-sampled, symmetric EPI with spectral-spatial excitation of a single metabolite provides a fast, robust, and clinically efficacious approach to acquire hyperpolarized ¹³ C dynamic molecular imaging data. The gains of this efficient sampling, combined with partial Fourier methods, enables large matrix sizes required for human studies. Magn Reson Med 77:826-832, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Accelerating PS model-based dynamic cardiac MRI using compressed sensing

High spatiotemporal resolution MRI is a challenging topic in dynamic MRI field. Partial separability (PS) model has been successfully applied to dynamic cardiac MRI by exploiting data redundancy. However, the model requires substantial preprocessing data to accurately estimate the model parameters before image reconstruction. Since compressed sensing (CS) is a potential technique to accelerate MRI by reducing the number of acquired data, the combination of PS and CS, named as Stepped-SparsePS, was introduced to accelerate the preprocessing data acquisition of PS in this work. The proposed Stepped-SparsePS method sequentially reconstructs a set of aliased dynamic images in each channel based on PS model and then the final dynamic images from the aliased images using CS. The results from numerical simulations and in vivo experiments demonstrate that Stepped-SparsePS could significantly reduce data acquisition time while preserving high spatiotemporal resolution.

A 3D MR-acquisition scheme for nonrigid bulk motion correction in simultaneous PET-MR

PURPOSE

Positron emission tomography (PET) is a highly sensitive medical imaging technique commonly used to detect and assess tumor lesions. Magnetic resonance imaging (MRI) provides high resolution anatomical images with different contrasts and a range of additional information important for cancer diagnosis. Recently, simultaneous PET-MR systems have been released with the promise to provide complementary information from both modalities in a single examination. Due to long scan times, subject nonrigid bulk motion, i.e., changes of the patient's position on the scanner table leading to nonrigid changes of the patient's anatomy, during data acquisition can negatively impair image quality and tracer uptake quantification. A 3D MR-acquisition scheme is proposed to detect and correct for nonrigid bulk motion in simultaneously acquired PET-MR data.

METHODS

A respiratory navigated three dimensional (3D) MR-acquisition with Radial Phase Encoding (RPE) is used to obtain T1- and T2-weighted data with an isotropic resolution of 1.5 mm. Healthy volunteers are asked to move the abdomen two to three times during data acquisition resulting in overall 19 movements at arbitrary time points. The acquisition scheme is used to retrospectively reconstruct dynamic 3D MR images with different temporal resolutions. Nonrigid bulk motion is detected and corrected in this image data. A simultaneous PET acquisition is simulated and the effect of motion correction is assessed on image quality and standardized uptake values (SUV) for lesions with different diameters.

RESULTS

Six respiratory gated 3D data sets with T1- and T2-weighted contrast have been obtained in healthy volunteers. All bulk motion shifts have successfully been detected and motion fields describing the transformation between the different motion states could be obtained with an accuracy of 1.71 ± 0.29 mm. The PET simulation showed errors of up to 67% in measured SUV due to bulk motion which could be reduced to less than 10% with the proposed motion compensation approach.

CONCLUSIONS

A MR acquisition scheme which yields both high resolution 3D anatomical data and highly accurate nonrigid motion information without an increase in scan time is presented. The proposed method leads to a strong improvement in both MR and PET image quality and ensures an accurate assessment of tracer uptake.

Activation of brain areas following ankle dorsiflexion versus plantar flexion: Functional magnetic resonance imaging verification

Changes in activated areas of the brain during ankle active dorsiflexion and ankle active plantar flexion were observed in six healthy subjects using functional magnetic resonance imaging. Excited areas of ankle active dorsiflexion involved the bilateral primary motor area and the primary somatosensory area, as well as the bilateral supplementary sensory area, the primary visual area, the right second visual area, and the vermis of cerebellum. Excited areas of ankle active plantar flexion included the ipsilateral supplementary motor area, the limbic system, and the contralateral corpus striatum. Fine movements of the cerebral cortex control the function of the ankle dorsiflexion to a larger extent than ankle plate flexion, and the function of ankle plate flexion is more controlled by the subcortical area.

Real-time measurement of alveolar size and population using phase contrast x-ray imaging

Herein a propagation-based phase contrast x-ray imaging technique for measuring particle size and number is presented. This is achieved with an algorithm that utilizes the Fourier space signature of the speckle pattern associated with the images of particles. We validate this algorithm using soda-lime glass particles, demonstrating its effectiveness on random and non-randomly packed particles. This technique is then applied to characterise lung alveoli, which are difficult to measure dynamically in vivo with current imaging modalities due to inadequate temporal resolution and/or depth of penetration and field-of-view. We obtain an important result in that our algorithm is able to measure changes in alveolar size on the micron scale during ventilation and shows the presence of alveolar recruitment/de-recruitment in newborn rabbit kittens. This technique will be useful for ventilation management and lung diagnostic procedures.

Correlation imaging with arbitrary sampling trajectories

The presented work aims to develop a generalized linear approach to image reconstruction with arbitrary sampling trajectories for high-speed MRI. This approach is based on a previously developed image reconstruction framework, "correlation imaging". In the presented work, correlation imaging with arbitrary sampling trajectories is implemented in a multi-dimensional hybrid space that is formed from the physical sampling space and a virtually defined space. By introducing an undersampling trajectory with both uniformity and randomness in the hybrid space, correlation imaging may take advantage of multiple image reconstruction mechanisms including coil sensitivity encoding, data sparsity and information sharing. This hybrid-space implementation is demonstrated in multi-slice 2D imaging, multi-scan imaging, and radial dynamic imaging. Since more information is used in image reconstruction, it is found that hybrid-space correlation imaging outperforms several conventional techniques. The presented approach will benefit clinical MRI by enabling correlation imaging to be used to accelerate multi-scan clinical protocols that need different sampling trajectories in different scans.

Readout-segmented echo-planar imaging for diffusion-weighted imaging in the pelvis at 3T-A feasibility study

RATIONALE AND OBJECTIVES

Diffusion-weighted imaging (DWI) of the pelvis at 3T is prone to artifacts that diminish the image quality. Readout-segmented echo-planar imaging (RS-EPI) is a new DWI technique that can reduce the artifacts associated with standard single-shot echo-planar imaging (SS-EPI) DWI. The purpose of this study was to evaluate the feasibility and image quality of RS-EPI in pelvic DWI compared to SS-EPI on a 3T imaging system.

MATERIALS AND METHODS

Thirty patients underwent pelvic DWI on a 3T scanner with SS-EPI and RS-EPI techniques. Two blinded readers independently assessed each set of images for geometric distortion, image blurring, ghosting artifacts, lesion conspicuity, and overall image quality on a 7-point scale. Qualitative image scores were compared using paired Wilcoxon signed rank test. Interreader correlation was assessed by Spearman rank correlation.

RESULTS

Geometric distortion, imaging blurring, ghosting artifacts, lesion conspicuity, and overall image quality were rated significantly better by both readers for RS-EPI technique (P < .01 for all parameters). There was moderate-high correlation between the readers (r = 0.649-0.752) for all parameters apart from lesion conspicuity (r = 0.351). Both readers preferred the RS-EPI set of DWI images in most of the cases (reader 1: 0.87, 95% CI 0.74-0.99; reader 2: 0.77, 95% CI 0.61-0.93). Mean difference and limits of agreement between apparent diffusion coefficient (ADC) values obtained from the two methods were 0.01 (-0.08, 0.10) × 10(-3) mm(2)/s.

CONCLUSIONS

RS-EPI DWI images showed improved image quality compared to SS-EPI technique at 3T. RS-EPI is a feasible technique in the pelvis for producing high-resolution DWI.

Visualization of the amygdalo-hippocampal border and its structural variability by 7T and 3T magnetic resonance imaging

The amygdala and the hippocampus are two adjacent structures in the medial temporal lobe that have been broadly investigated in functional and structural neuroimaging due to their central importance in sensory perception, emotion, and memory. Exact demarcation of the amygdalo-hippocampal border (AHB) is, however, difficult in conventional structural imaging. Recent evidence suggests that, due to this difficulty, functional activation sites with high probability of being located in the hippocampus may erroneously be assigned to the amygdala, and vice versa. In the present study, we investigated the potential of ultra-high-field magnetic resonance imaging (MRI) in single sessions for detecting the AHB in humans. We show for the first time the detailed structure of the AHB as it can be visualized in T1-weighted 7T in vivo images at 0.5-mm(3) isotropic resolution. Compared to data acquired at 3T, 7T images revealed considerably more structural detail in the AHB region. Thus, we observed a striking inter-hemispheric and interindividual variability of the exact anatomical configuration of the AHB that points to the necessity of individual imaging of the AHB as a prerequisite for accurate anatomical assignment in this region. The findings of the present study demonstrate the usefulness of ultra-high-field structural MRI to resolve anatomical ambiguities of the human AHB. Highly accurate morphometric and functional investigations in this region at 7T may allow addressing such hitherto unexplored issues as whether the structural configuration of the AHB is related to functional differences in amygdalo-hippocampal interaction.

An aliasing artifacts reducing approach with random undersampling for spatiotemporally encoded single-shot MRI

Compared to the echo planar imaging (EPI), spatiotemporally encoded (SPEN) single-shot MRI holds better immunity to the field inhomogeneity, while retaining comparable spatial and temporal resolutions after the super-resolved reconstruction. Though various reconstruction methods have been proposed, the reconstructed SPEN images usually contain aliasing artifacts because of vast undersampling. A hybrid scheme based on random sampling, singular value decomposition (SVD) and compressed sensing (CS) was introduced to reduce these aliasing artifacts and improve the image quality. The efficiency of this hybrid scheme was demonstrated by numerical simulations and experiments on water phantom and in vivo rat brain. The hybrid scheme provided herein would benefit the SPEN approach in vast undersampling situation.

Highlights of the 16th annual scientific sessions of the Society for Cardiovascular Magnetic Resonance

The 16th Annual Scientific Sessions of the Society for Cardiovascular Magnetic Resonance (SCMR) took place in San Francisco, USA at the end of January 2013. With a faculty of experts from across the world, this congress provided a wealth of insight into cutting-edge research and technological development. This review article intends to provide a highlight of what represented the most significant advances in the field of cardiovascular magnetic resonance (CMR) during this year's meeting.

An efficient de-convolution reconstruction method for spatiotemporal-encoding single-scan 2D MRI

Spatiotemporal-encoding single-scan MRI method is relatively insensitive to field inhomogeneity compared to EPI method. Conjugate gradient (CG) method has been used to reconstruct super-resolved images from the original blurred ones based on coarse magnitude-calculation. In this article, a new de-convolution reconstruction method is proposed. Through removing the quadratic phase modulation from the signal acquired with spatiotemporal-encoding MRI, the signal can be described as a convolution of desired super-resolved image and a point spread function. The de-convolution method proposed herein not only is simpler than the CG method, but also provides super-resolved images with better quality. This new reconstruction method may make the spatiotemporal-encoding 2D MRI technique more valuable for clinic applications.

MRI temporal acceleration techniques

In recent years, there has been an explosive growth of magnetic resonance imaging (MRI) techniques that allow faster scan speed by exploiting temporal or spatiotemporal redundancy of the images. These techniques improve the performance of dynamic imaging significantly across multiple clinical applications, including cardiac functional examinations, perfusion imaging, blood flow assessment, contrast-enhanced angiography, functional MRI, and interventional imaging, among others. The scan acceleration permits higher spatial resolution, increased temporal resolution, shorter scan duration, or a combination of these benefits. Along with the exciting developments is a dizzying proliferation of acronyms and variations of the techniques. The present review attempts to summarize this rapidly growing topic and presents conceptual frameworks to understand these techniques in terms of their underlying mechanics and connections. Techniques from view sharing, keyhole, k-t, to compressed sensing are covered.

Joint reconstruction of image and motion in MRI: implicit regularization using an adaptive 3D mesh

Magnetic resonance images are affected by motion artefacts due to breathing and cardiac beating that occur during the acquisition. Methods for joint reconstruction of image and motion have been proposed recently. Such optimization problems are ill-conditioned, therefore regularization methods are required such as motion smoothness constraints using the Tikhonov method. However with Tikhonov methods the solution often relies on a good choice of the regularization parameter micron, especially in large parameter search spaces (e.g., in 3D reconstructions). In this paper, we propose an adaptive, implicit regularization method which results in subject-specific, spatially varying smoothness constraints on the motion model. It is based on the idea of solving for motion only in certain key points that form a mesh. A practical algorithm is proposed for generating this mesh automatically. The proposed method is shown to have a better convergence rate than the Tikhonov method, both in silico and in vivo. The accuracy of the reconstructed image and motion is also improved.

Correlation imaging for multiscan MRI with parallel data acquisition

A new approach to high-speed magnetic resonance imaging (MRI) that uses all the data acquired in a multiscan imaging session is presented. This approach accelerates MRI data acquisition by statistically estimating correlation functions from images with different contrast and/or resolution. In multiscan MRI with parallel data acquisition, the estimation of correlation functions is dynamically improved as imaging proceeds. This allows imaging acceleration factors to be increased in subsequent scans, thereby reducing the total time of a multiscan MRI protocol. Furthermore, the correlation function estimates bring information about both coil sensitivity and anatomical structure into image reconstruction, thereby offering the ability to speed up MRI beyond the parallel imaging acceleration limit posed by a coil array alone. In this study, the feasibility of correlation imaging is demonstrated experimentally using brain and spine imaging protocols. The ability of correlation imaging to achieve an aggregate acceleration factor in excess of the number of coil elements in the phase encoding direction is also demonstrated.