Magnetic resonance thermometry for hyperthermia in the oropharynx region.

Magnetic resonance thermometry (MRT) can measure in-vivo 3D-temperature changes in real-time and noninvasively. However, for the oropharynx region and the entire head and neck, motion potentially introduces large artifacts. Considering long treatment times of 60-90 min, this study aims to evaluate whether MRT around the oropharynx is clinically feasible for hyperthermia treatments and quantify the effects of breathing and swallowing on MRT performance. A 3D-ME-FGRE sequence was used in a phantom cooling down and around the oropharynx of five volunteers over ∼75 min. The imaging protocol consisted of imaging with acceleration (ARC = 2), number of image averages (NEX = 1,2 and 3). For volunteers, the acquisitions included a breath-hold scan and scans with deliberate swallowing. MRT performance was quantified in neck muscle, spinal cord and masseter muscle, using mean average error (MAE), mean error (ME) and spatial standard deviation (SD). In phantom, an increase in NEX leads to a significant decrease in SD, but MAE and ME were unchanged. No significant difference was found in volunteers between the different scans. There was a significant difference between the regions evaluated: neck muscle had the best MAE (=1.96 °C) and SD (=0.82 °C), followed by spinal cord (MAE = 3.17 °C, SD = 0.92 °C) and masseter muscle (MAE = 4.53 °C, SD = 1.16 °C). Concerning the ME, spinal cord did best, then neck muscle and masseter muscle, with values of -0.64 °C, 1.15 °C and -3.05 °C respectively. Breathing, swallowing, and different ways of imaging (acceleration and NEX) do not significantly influence the MRT performance in the oropharynx region. The ROI selected however, leads to significant differences.

Systematic review of reconstruction techniques for accelerated quantitative MRI.

PURPOSE: To systematically review the techniques that address undersampling artifacts in accelerated quantitative magnetic resonance imaging (qMRI). METHODS: A literature search was conducted using the Embase, Medline, Web of Science Core Collection, Coherence Central Register of Controlled Trials, and Google Scholar databases for studies, published before July 2022 proposing reconstruction techniques for accelerated qMRI. Studies are reviewed according to inclusion criteria, and included studies are categorized based on the methodology used. RESULTS: A total of 292 studies included in the review are categorized. A technical overview of each category is provided, and the categories are described in a unified mathematical framework. The distribution of the reviewed studies over time, application domain, and parameters of interest is illustrated. CONCLUSION: An increasing trend in the number of articles that propose new techniques for accelerated qMRI reconstruction indicates the importance of acceleration in qMRI. The techniques are mostly validated for relaxometry parameters and brain scans. The categories of techniques are compared based on theoretical grounds, highlighting existing trends and potential gaps in the field.

ADEPT: Accurate Diffusion Echo-Planar imaging with multi-contrast shoTs.

PURPOSE: To introduce a novel imaging and parameter estimation framework for accurate multi-shot diffusion MRI. THEORY AND METHODS: We propose a new framework called ADEPT (Accurate Diffusion Echo-Planar imaging with multi-contrast shoTs) that enables fast diffusion MRI by allowing diffusion contrast settings to change between shots in a multi-shot EPI acquisition (i.e., intra-scan modulation). The framework estimates diffusion parameter maps directly from the acquired intra-scan modulated k-space data, while simultaneously accounting for shot-to-shot phase inconsistencies. The performance of the estimation framework is evaluated using Monte Carlo simulation studies and in-vivo experiments and compared to that of reference methods that rely on parallel imaging for shot-to-shot phase correction. RESULTS: Simulation and real-data experiments show that ADEPT yields more accurate and more precise estimates of the diffusion metrics in multi-shot EPI data in comparison with the reference methods. CONCLUSION: ADEPT allows fast multi-shot EPI diffusion MRI without significantly degrading the accuracy and precision of the estimated diffusion maps.

Multidelay pseudocontinuous arterial spin labeling to measure blood flow in the head and neck.

Perfusion MRI is promising for the assessment, prediction, and monitoring of radiation toxicity in organs at risk in head and neck cancer. Arterial spin labeling (ASL) may be an attractive alternative for conventional perfusion MRI, that does not require the administration of contrast agents. However, currently, little is known about the characteristics and performance of ASL in healthy tissues in the head and neck region. Therefore, the purpose of this study was to optimize and evaluate multidelay pseudocontinuous ASL (pCASL) for the head and neck region and to explore nominal values and measurement repeatability for the blood flow (BF), and the transit time and T1 values needed for BF quantification in healthy tissues. Twenty healthy volunteers underwent a scan session consisting of four repeats of multidelay pCASL (postlabel delays: 1000, 1632, 2479 ms). Regions of interest were defined in the parotid glands, submandibular glands, tonsils, and the cerebellum (as a reference). Nominal values of BF were calculated as the average over four repeats per volunteer. The repeatability coefficient and within-subject coefficient of repeatability (wCV) of BF were calculated. The effect of T1 (map vs. cohort average) and transit time correction on BF was investigated. The mean BF (± SE) was 55.7 ± 3.1 ml/100 g/min for the parotid glands, 41.2 ± 2.8 ml/100 g/min for the submandibular glands, and 32.3 ± 2.2 ml/100 g/min for the tonsils. The best repeatability was found in the parotid glands (wCV = 13.3%-16.1%), followed by the submandibular glands and tonsils (wCV = 20.0%-24.6%). On average, the effect of T1 and transit time correction on BF was limited, although substantial bias occurred in individual acquisitions. In conclusion, we demonstrated the feasibility of BF measurements in the head and neck region using multidelay pCASL and reported on nominal BF values, BF repeatability, the effect of T1, and transit time in various tissues in the head and neck region.

Multi-echo gradient echo pulse sequences: which is best for PRFS MR thermometry guided hyperthermia?

PURPOSE: MR thermometry (MRT) enables noninvasive temperature monitoring during hyperthermia treatments. MRT is already clinically applied for hyperthermia treatments in the abdomen and extremities, and devices for the head are under development. In order to optimally exploit MRT in all anatomical regions, the best sequence setup and post-processing must be selected, and the accuracy needs to be demonstrated. METHODS: MRT performance of the traditionally used double-echo gradient-echo sequence (DE-GRE, 2 echoes, 2D) was compared to multi-echo sequences: a 2D fast gradient-echo (ME-FGRE, 11 echoes) and a 3D fast gradient-echo sequence (3D-ME-FGRE, 11 echoes). The different methods were assessed on a 1.5 T MR scanner (GE Healthcare) using a phantom cooling down from 59 °C to 34 °C and unheated brains of 10 volunteers. In-plane motion of volunteers was compensated by rigid body image registration. For the ME sequences, the off-resonance frequency was calculated using a multi-peak fitting tool. To correct for B0 drift, the internal body fat was selected automatically using water/fat density maps. RESULTS: The accuracy of the best performing 3D-ME-FGRE sequence was 0.20 °C in phantom (in the clinical temperature range) and 0.75 °C in volunteers, compared to DE-GRE values of 0.37 °C and 1.96 °C, respectively. CONCLUSION: For hyperthermia applications, where accuracy is more important than resolution or scan-time, the 3D-ME-FGRE sequence is deemed the most promising candidate. Beyond its convincing MRT performance, the ME nature enables automatic selection of internal body fat for B0 drift correction, an important feature for clinical application.

A unified model for reconstruction and R2* mapping of accelerated 7T data using the quantitative recurrent inference machine.

Quantitative MRI (qMRI) acquired at the ultra-high field of 7 Tesla has been used in visualizing and analyzing subcortical structures. qMRI relies on the acquisition of multiple images with different scan settings, leading to extended scanning times. Data redundancy and prior information from the relaxometry model can be exploited by deep learning to accelerate the imaging process. We propose the quantitative Recurrent Inference Machine (qRIM), with a unified forward model for joint reconstruction and R2*-mapping from sparse data, embedded in a Recurrent Inference Machine (RIM), an iterative inverse problem-solving network. To study the dependency of the proposed extension of the unified forward model to network architecture, we implemented and compared a quantitative End-to-End Variational Network (qE2EVN). Experiments were performed with high-resolution multi-echo gradient echo data of the brain at 7T of a cohort study covering the entire adult life span. The error in reconstructed R2* from undersampled data relative to reference data significantly decreased for the unified model compared to sequential image reconstruction and parameter fitting using the RIM. With increasing acceleration factor, an increasing reduction in the reconstruction error was observed, pointing to a larger benefit for sparser data. Qualitatively, this was following an observed reduction of image blurriness in R2*-maps. In contrast, when using the U-Net as network architecture, a negative bias in R2* in selected regions of interest was observed. Compressed Sensing rendered accurate, but less precise estimates of R2*. The qE2EVN showed slightly inferior reconstruction quality compared to the qRIM but better quality than the U-Net and Compressed Sensing. Subcortical maturation over age measured by a linearly increasing interquartile range of R2* in the striatum was preserved up to an acceleration factor of 9. With the integrated prior of the unified forward model, the proposed qRIM can exploit the redundancy among repeated measurements and shared information between tasks, facilitating relaxometry in accelerated MRI.

Dependency of R2 and R2 * relaxation on Gd-DTPA concentration in arterial blood: Influence of hematocrit and magnetic field strength.

Dynamic susceptibility contrast (DSC) MRI is clinically used to measure brain perfusion by monitoring the dynamic passage of a bolus of contrast agent through the brain. For quantitative analysis of the DSC images, the arterial input function is required. It is known that the original assumption of a linear relation between the R2(*) relaxation and the arterial contrast agent concentration is invalid, although the exact relation is as of yet unknown. Studying this relation in vitro is time-consuming, because of the widespread variations in field strengths, MRI sequences, contrast agents, and physiological conditions. This study aims to simulate the R2(*) versus contrast concentration relation under varying physiological and technical conditions using an adapted version of an open-source simulation tool. The approach was validated with previously acquired data in human whole blood at 1.5 T by means of a gradient-echo sequence (proof-of-concept). Subsequently, the impact of hematocrit, field strength, and oxygen saturation on this relation was studied for both gradient-echo and spin-echo sequences. The results show that for both gradient-echo and spin-echo sequences, the relaxivity increases with hematocrit and field strength, while the hematocrit dependency was nonlinear for both types of MRI sequences. By contrast, oxygen saturation has only a minor effect. In conclusion, the simulation setup has proven to be an efficient method to rapidly calibrate and estimate the relation between R2(*) and gadolinium concentration in whole blood. This knowledge will be useful in future clinical work to more accurately retrieve quantitative information on brain perfusion.

An optimal acquisition and post-processing pipeline for hybrid IVIM-DKI in head and neck.

PURPOSE: To optimize the diffusion-weighting b values and postprocessing pipeline for hybrid intravoxel incoherent motion diffusion kurtosis imaging in the head and neck region. METHODS: Optimized diffusion-weighting b value sets ranging between 5 and 30 b values were constructed by optimizing the Cramér-Rao lower bound of the hybrid intravoxel incoherent motion diffusion kurtosis imaging model. With this model, the perfusion fraction, pseudodiffusion coefficient, diffusion coefficient, and kurtosis were estimated. Sixteen volunteers were scanned with a reference b value set and 3 repeats of the optimized sets, of which 1 with volunteers swallowing on purpose. The effects of (1) b value optimization and number of b values, (2) registration type (none vs. intervolume vs. intra- and intervolume registration), and (3) manual swallowing artifact rejection on the parameter precision were assessed. RESULTS: The SD was higher in the reference set for perfusion fraction, diffusion coefficient, and kurtosis by a factor of 1.7, 1.5, and 2.3 compared to the optimized set, respectively. A smaller SD (factor 0.7) was seen in pseudodiffusion coefficient. The sets containing 15, 20, and 30 b values had comparable repeatability in all parameters, except pseudodiffusion coefficient, for which set size 30 was worse. Equal repeatability for the registration approaches was seen in all parameters of interest. Swallowing artifact rejection removed the bias when present. CONCLUSION: To achieve optimal hybrid intravoxel incoherent motion diffusion kurtosis imaging in the head and neck region, b value optimization and swallowing artifact image rejection are beneficial. The optimized set of 15 b values yielded the optimal protocol efficiency, with a precision comparable to larger b value sets and a 50% reduction in scan time.

Association Between T2* Relaxation Times Derived From Ultrashort Echo Time MRI and Symptoms During Exercise Therapy for Patellar Tendinopathy: A Large Prospective Study.

BACKGROUND: Exercise therapy is considered preferential treatment for patellar tendinopathy (PT). However, there is conflicting evidence for structural patellar tendon adaptation in response to exercise therapy and its association with symptoms is weak. PURPOSE: To assess the association between 1) T2* relaxation times and symptom severity; 2) baseline T2* and clinical outcome; and 3) longitudinal T2* changes and clinical outcome in athletes with PT performing exercise therapy. STUDY TYPE: Randomized controlled clinical trial. SUBJECTS: Seventy-six athletes (18-35 years) with clinically diagnosed and ultrasound-confirmed PT. FIELD STRENGTH/SEQUENCE: 3D gradient echo sequence (3.0 T). ASSESSMENT: Patients were enrolled in a randomized trial of progressive tendon-loading exercises (PTLE) versus eccentric exercise therapy (EET). Symptoms were assessed using the Victorian Institute of Sports Assessment (VISA-P) questionnaire. 3D-Ultrashort echo time (UTE)-MRI was acquired at baseline, 12 and 24 weeks. Voxel-wise T2* relaxation times were quantified using mono-exponential and bi-exponential models. T2* analysis was performed in three patellar tendon tissue compartments representing: aligned collagen, degenerative tissue, and interface. STATISTICAL TESTS: Adjusted general linear, mixed-linear models, and generalized estimating equations. RESULTS: We included 76 patients with PT (58 men, mean age 24 ± 4 years); 38 in the PTLE-group and 38 in the EET-group, of which 57 subjects remained eligible for analysis. T2* relaxation times were significantly associated with VISA-P in degenerative and interface tissues of the patellar tendon. No association was found between baseline T2* and VISA-P after 24 weeks (P > 0.29). The estimated mean T2* in degenerative tissue decreased from 14 msec (95%CI: 12-16) at baseline to 13 msec (95%CI: 11-15) at 12 weeks and to 13 msec (95%CI: 10-15) at 24 weeks. The significant decrease in T2* from baseline to 24 weeks was associated with improved clinical outcome. DATA CONCLUSION: Tissue-specific T2* relaxation times, identified with 3D-UTE-MRI, decreased significantly in athletes with patellar tendinopathy performing exercise therapy and this decrease was associated with improved clinical outcome. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 4.

Tissue-Specific T2 * Biomarkers in Patellar Tendinopathy by Subregional Quantification Using 3D Ultrashort Echo Time MRI.

BACKGROUND: Quantitative MRI of patellar tendinopathy (PT) can be challenging due to spatial variation of T2 * relaxation times. PURPOSE: 1) To compare T2 * quantification using a standard approach with analysis in specific tissue compartments of the patellar tendon. 2) To evaluate test-retest reliability of different methods for fitting ultrashort echo time (UTE)-relaxometry data. STUDY TYPE: Prospective. SUBJECTS: Sixty-five athletes with PT. FIELD STRENGTH/SEQUENCE: 3D UTE scans covering the patellar tendon were acquired using a 3.0T scanner and a 16-channel surface coil. ASSESSMENT: Voxelwise median T2 * was quantified with monoexponential, fractional-order, and biexponential fitting. We applied two methods for T2 * analysis: first, a standard approach by analyzing all voxels covering the proximal patellar tendon. Second, within subregions of the patellar tendon, by using thresholds on biexponential fitting parameter percentage short T2 * (0-30% for mostly long T2 *, 30-60% for mixed T2 *, and 60-100% for mostly short T2 *). STATISTICAL TESTS: Average test-retest reliability was assessed in three athletes using coefficients-of-variation (CV) and coefficients-of-repeatability (CR). RESULTS: With standard image analysis, we found a median [interquartile range, IQR] monoexponential T2 * of 6.43 msec [4.32-8.55] and fractional order T2 * 4.39 msec [3.06-5.78]. The percentage of short T2 * components was 52.9% [35.5-69.6]. Subregional monoexponential T2 * was 13.78 msec [12.11-16.46], 7.65 msec [6.49-8.61], and 3.05 msec [2.52-3.60] and fractional order T2 * 11.82 msec [10.09-14.44], 5.14 msec [4.25-5.96], and 2.19 msec [1.82-2.64] for 0-30%, 30-60%, and 60-100% short T2 *, respectively. Biexponential component short T2 * was 1.693 msec [1.417-2.003] for tissue with mostly short T2 * and long T2 * of 15.79 msec [13.47-18.61] for mostly long T2 *. The average CR (CV) was 2 msec (15%), 2 msec (19%) and 10% (22%) for monoexponential, fractional order and percentage short T2 *, respectively. DATA CONCLUSION: Patellar tendinopathy is characterized by regional variability in binding states of water. Quantitative multicompartment T2 * analysis in PT can be facilitated using a voxel selection method based on using biexponential fitting parameters. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY STAGE: 1 J. Magn. Reson. Imaging 2020;52:420-430.

Quantitative DCE-MRI demonstrates increased blood perfusion in Hoffa's fat pad signal abnormalities in knee osteoarthritis, but not in patellofemoral pain.

OBJECTIVE: Infrapatellar fat pad (IPFP) fat-suppressed T2 (T2FS) hyperintense regions on MRI are an important imaging feature of knee osteoarthritis (OA) and are thought to represent inflammation. These regions are also common in non-OA subjects, and may not always be linked to inflammation. Our aim was to evaluate quantitative blood perfusion parameters, as surrogate measure of inflammation, within T2FS-hyperintense regions in patients with OA, with patellofemoral pain (PFP) (supposed OA precursor), and control subjects. METHODS: Twenty-two knee OA patients, 35 PFP patients and 43 healthy controls were included and underwent MRI, comprising T2 and DCE-MRI sequences. T2FS-hyperintense IPFP regions were delineated and a reference region was drawn in adjacent IPFP tissue with normal signal intensity. After fitting the extended Tofts pharmacokinetic model, quantitative DCE-MRI perfusion parameters were compared between the two regions within subjects in each subgroup, using a paired Wilcoxon signed-rank test. RESULTS: T2FS-hyperintense IPFP regions were present in 16 of 22 (73%) OA patients, 13 of 35 (37%) PFP patients, and 14 of 43 (33%) controls. DCE-MRI perfusion parameters were significantly different between regions with and without a T2FS-hyperintense signal in OA patients, demonstrating higher Ktrans compared to normal IFPF tissue (0.039 min-1 versus 0.025 min-1, p = 0.017) and higher Ve (0.157 versus 0.119, p = 0.010). For PFP patients and controls no significant differences were found. CONCLUSIONS: IPFP T2FS-hyperintense regions are associated with higher perfusion in knee OA patients in contrast to identically appearing regions in PFP patients and controls, pointing towards an inflammatory pathogenesis in OA only. KEY POINTS: • Morphologically identical appearing T2FS-hyperintense infrapatellar fat pad regions show different perfusion in healthy subjects, subjects with patellofemoral pain, and subjects with knee osteoarthritis. • Elevated DCE-MRI perfusion parameters within T2FS-hyperintense infrapatellar fat pad regions in patients with osteoarthritis suggest an inflammatory pathogenesis in osteoarthritis, but not in patellofemoral pain and healthy subjects.

Dynamic contrast-enhanced MRI of the patellar bone: How to quantify perfusion.

PURPOSE: To identify the optimal combination of pharmacokinetic model and arterial input function (AIF) for quantitative analysis of blood perfusion in the patellar bone using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). MATERIALS AND METHODS: This method design study used a random subset of five control subjects from an Institutional Review Board (IRB)-approved case-control study into patellofemoral pain, scanned on a 3T MR system with a contrast-enhanced time-resolved imaging of contrast kinetics (TRICKS) sequence. We systematically investigated the reproducibility of pharmacokinetic parameters for all combinations of Orton and Parker AIF models with Tofts, Extended Tofts (ETofts), and Brix pharmacokinetic models. Furthermore, we evaluated if the AIF should use literature parameters, be subject-specific, or group-specific. Model selection was based on the goodness-of-fit and the coefficient of variation of the pharmacokinetic parameters inside the patella. This extends previous studies that were not focused on the patella and did not evaluate as many combinations of arterial and pharmacokinetic models. RESULTS: The vascular component in the ETofts model could not reliably be recovered (coefficient of variation [CV] of vp >50%) and the Brix model parameters showed high variability of up to 20% for kel across good AIF models. Compared to group-specific AIF, the subject-specific AIF's mostly had higher residual. The best reproducibility and goodness-of-fit were obtained by combining Tofts' pharmacokinetic model with the group-specific Parker AIF. CONCLUSION: We identified several good combinations of pharmacokinetic models and AIF for quantitative analysis of perfusion in the patellar bone. The recommended combination is Tofts pharmacokinetic model combined with a group-specific Parker AIF model. LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2018;47:848-858.

Blood perfusion of patellar bone measured by dynamic contrast-enhanced MRI in patients with patellofemoral pain: A case-control study.

BACKGROUND: Altered perfusion might play an important role in the pathophysiology of patellofemoral pain (PFP), a common knee complaint with unclear pathophysiology. PURPOSE: To investigate differences in dynamic contrast-enhanced (DCE)-MRI perfusion parameters between patients with PFP and healthy control subjects. POPULATION/SUBJECTS/PHANTOM/SPECIMEN/ANIMAL MODEL: Thirty-five adult patients with PFP and 44 healthy adult control subjects. FIELD STRENGTH/SEQUENCE: 3T DCE-MRI consisting of a sagittal, anterior-posterior, frequency-encoded, fat-suppressed 3D spoiled gradient-echo sequence with intravenous contrast administration. ASSESSMENT: Patellar bone volumes of interest (VOIs) were delineated by a blinded observer. Quantitative perfusion parameters (kep and ktrans ) were calculated from motion-compensated DCE-MRI data by fitting Tofts' model. Weighted mean and unweighted median values of kep and ktrans were computed within the patellar bone VOIs. STATISTICAL TESTS: Differences in patellar bone perfusion parameters were compared between groups by linear regression analyses, adjusted for confounders. RESULTS: Mean differences of weighted mean and unweighted median were 0.0039 (95% confidence interval [CI] -0.0013; 0.0091) and 0.0052 (95% CI -0.0078; 0.018) for ktrans , and 0.046 (95% CI -0.021; 0.11) and 0.069 (95% CI -0.017; 0.15) for kep , respectively. All perfusion parameters were not significantly different between groups (P-values: 0.32; 0.47 for ktrans , and 0.24; 0.15) for kep . However, a significant difference in variance between populations was observed for ktrans (P-value 0.007). DATA CONCLUSION: Higher patellar bone perfusion parameters were found in patients with PFP when compared to healthy control subjects, but these differences were not statistically significant. This result, and the observed significant difference in ktrans variance, warrant further research. LEVEL OF EVIDENCE: 1 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2018;47:1344-1350.

Super-resolution T1 estimation: Quantitative high resolution T1 mapping from a set of low resolution T1 -weighted images with different slice orientations.

PURPOSE: Quantitative T1 mapping is a magnetic resonance imaging technique that estimates the spin-lattice relaxation time of tissues. Even though T1 mapping has a broad range of potential applications, it is not routinely used in clinical practice as accurate and precise high resolution T1 mapping requires infeasibly long acquisition times. METHOD: To improve the trade-off between the acquisition time, signal-to-noise ratio and spatial resolution, we acquire a set of low resolution T1 -weighted images and directly estimate a high resolution T1 map by means of super-resolution reconstruction. RESULTS: Simulation and in vivo experiments show an increased spatial resolution of the T1 map, while preserving a high signal-to-noise ratio and short scan time. Moreover, the proposed method outperforms conventional estimation in terms of root-mean-square error. CONCLUSION: Super resolution T1 estimation enables resolution enhancement in T1 mapping with the use of standard (inversion recovery) T1 acquisition sequences. Magn Reson Med 77:1818-1830, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Diffusion MRI microstructure models with in vivo human brain Connectome data: results from a multi-group comparison.

A large number of mathematical models have been proposed to describe the measured signal in diffusion-weighted (DW) magnetic resonance imaging (MRI). However, model comparison to date focuses only on specific subclasses, e.g. compartment models or signal models, and little or no information is available in the literature on how performance varies among the different types of models. To address this deficiency, we organized the 'White Matter Modeling Challenge' during the International Symposium on Biomedical Imaging (ISBI) 2015 conference. This competition aimed to compare a range of different kinds of models in their ability to explain a large range of measurable in vivo DW human brain data. Specifically, we assessed the ability of models to predict the DW signal accurately for new diffusion gradients and b values. We did not evaluate the accuracy of estimated model parameters, as a ground truth is hard to obtain. We used the Connectome scanner at the Massachusetts General Hospital, using gradient strengths of up to 300 mT/m and a broad set of diffusion times. We focused on assessing the DW signal prediction in two regions: the genu in the corpus callosum, where the fibres are relatively straight and parallel, and the fornix, where the configuration of fibres is more complex. The challenge participants had access to three-quarters of the dataset and their models were ranked on their ability to predict the remaining unseen quarter of the data. The challenge provided a unique opportunity for a quantitative comparison of diverse methods from multiple groups worldwide. The comparison of the challenge entries reveals interesting trends that could potentially influence the next generation of diffusion-based quantitative MRI techniques. The first is that signal models do not necessarily outperform tissue models; in fact, of those tested, tissue models rank highest on average. The second is that assuming a non-Gaussian (rather than purely Gaussian) noise model provides little improvement in prediction of unseen data, although it is possible that this may still have a beneficial effect on estimated parameter values. The third is that preprocessing the training data, here by omitting signal outliers, and using signal-predicting strategies, such as bootstrapping or cross-validation, could benefit the model fitting. The analysis in this study provides a benchmark for other models and the data remain available to build up a more complete comparison in the future.

Super-resolution reconstruction of diffusion parameters from diffusion-weighted images with different slice orientations.

PURPOSE: Diffusion MRI is hampered by long acquisition times, low spatial resolution, and a low signal-to-noise ratio. Recently, methods have been proposed to improve the trade-off between spatial resolution, signal-to-noise ratio, and acquisition time of diffusion-weighted images via super-resolution reconstruction (SRR) techniques. However, during the reconstruction, these SRR methods neglect the q-space relation between the different diffusion-weighted images. METHOD: An SRR method that includes a diffusion model and directly reconstructs high resolution diffusion parameters from a set of low resolution diffusion-weighted images was proposed. Our method allows an arbitrary combination of diffusion gradient directions and slice orientations for the low resolution diffusion-weighted images, optimally samples the q- and k-space, and performs motion correction with b-matrix rotation. RESULTS: Experiments with synthetic data and in vivo human brain data show an increase of spatial resolution of the diffusion parameters, while preserving a high signal-to-noise ratio and low scan time. Moreover, the proposed SRR method outperforms the previous methods in terms of the root-mean-square error. CONCLUSION: The proposed SRR method substantially increases the spatial resolution of MRI that can be obtained in a clinically feasible scan time.

Three-dimensional quantitative T1 and T2 mapping of the carotid artery: Sequence design and in vivo feasibility.

PURPOSE: A novel three-dimensional (3D) T1 and T2 mapping protocol for the carotid artery is presented. METHODS: A 3D black-blood imaging sequence was adapted allowing carotid T1 and T2 mapping using multiple flip angles and echo time (TE) preparation times. B1 mapping was performed to correct for spatially varying deviations from the nominal flip angle. The protocol was optimized using simulations and phantom experiments. In vivo scans were performed on six healthy volunteers in two sessions, and in a patient with advanced atherosclerosis. Compensation for patient motion was achieved by 3D registration of the inter/intrasession scans. Subsequently, T1 and T2 maps were obtained by maximum likelihood estimation. RESULTS: Simulations and phantom experiments showed that the bias in T1 and T2 estimation was < 10% within the range of physiological values. In vivo T1 and T2 values for carotid vessel wall were 844 ± 96 and 39 ± 5 ms, with good repeatability across scans. Patient data revealed altered T1 and T2 values in regions of atherosclerotic plaque. CONCLUSION: The 3D T1 and T2 mapping of the carotid artery is feasible using variable flip angle and variable TE preparation acquisitions. We foresee application of this technique for plaque characterization and monitoring plaque progression in atherosclerotic patients.

Influence of image registration on apparent diffusion coefficient images computed from free-breathing diffusion MR images of the abdomen.

BACKGROUND: To evaluate the influence of image registration on apparent diffusion coefficient (ADC) images obtained from abdominal free-breathing diffusion-weighted MR images (DW-MRIs). METHODS: A comprehensive pipeline based on automatic three-dimensional nonrigid image registrations is developed to compensate for misalignments in DW-MRI datasets obtained from five healthy subjects scanned twice. Motion is corrected both within each image and between images in a time series. ADC distributions are compared with and without registration in two abdominal volumes of interest (VOIs). The effects of interpolations and Gaussian blurring as alternative strategies to reduce motion artifacts are also investigated. RESULTS: Among the four considered scenarios (no processing, interpolation, blurring and registration), registration yields the best alignment scores. Median ADCs vary according to the chosen scenario: for the considered datasets, ADCs obtained without processing are 30% higher than with registration. Registration improves voxelwise reproducibility at least by a factor of 2 and decreases uncertainty (Fréchet-Cramér-Rao lower bound). Registration provides similar improvements in reproducibility and uncertainty as acquiring four times more data. CONCLUSION: Patient motion during image acquisition leads to misaligned DW-MRIs and inaccurate ADCs, which can be addressed using automatic registration.

Super-resolution reconstruction of late gadolinium-enhanced MRI for improved myocardial scar assessment.

PURPOSE: To develop and validate a method for improving image resolution of late gadolinium-enhanced (LGE) magnetic resonance imaging (MRI) for accurate assessment of myocardial scar. MATERIALS AND METHODS: In a cohort of 37 postinfarction patients, LGE was performed prior to ventricular tachycardia catheter ablation therapy at 1.5T. A super-resolution reconstruction (SRR) technique was applied to the three anisotropic views: short-axis (SA), two-chamber, and four-chamber, to reconstruct a single isotropic volume. For compensation of the interscan heart motion, a joint localized gradient-correlation-based scheme was developed. Scar was identified as either core or gray zone in both the SRR and original SA volumes, and evaluated based on the clinically established bipolar voltage range of the in vivo electroanatomical voltage mapping (EAVM). RESULTS: Compared to the SA volume, the SRR method resulted in significantly (P < 0.05) reduced myocardial scar gray zone sizes (10.5 ± 8.8 g vs. 9.2 ± 8.1 g) and improved agreement of the bipolar voltage range of scar gray zone (0.99 ± 0.65 mV vs. 1.46 ± 1.15 mV). CONCLUSION: We propose an SRR method to automatically reconstruct a high-quality isotropic LGE volume from three orthogonal views. Analysis of the in vivo EAVM demonstrated improved myocardial scar assessment from the SRR volume compared with the SA LGE alone.

Three-dimensional inversion recovery manganese-enhanced MRI of mouse brain using super-resolution reconstruction to visualize nuclei involved in higher brain function.

The visualization of activity in mouse brain using inversion recovery spin echo (IR-SE) manganese-enhanced MRI (MEMRI) provides unique contrast, but suffers from poor resolution in the slice-encoding direction. Super-resolution reconstruction (SRR) is a resolution-enhancing post-processing technique in which multiple low-resolution slice stacks are combined into a single volume of high isotropic resolution using computational methods. In this study, we investigated, first, whether SRR can improve the three-dimensional resolution of IR-SE MEMRI in the slice selection direction, whilst maintaining or improving the contrast-to-noise ratio of the two-dimensional slice stacks. Second, the contrast-to-noise ratio of SRR IR-SE MEMRI was compared with a conventional three-dimensional gradient echo (GE) acquisition. Quantitative experiments were performed on a phantom containing compartments of various manganese concentrations. The results showed that, with comparable scan times, the signal-to-noise ratio of three-dimensional GE acquisition is higher than that of SRR IR-SE MEMRI. However, the contrast-to-noise ratio between different compartments can be superior with SRR IR-SE MEMRI, depending on the chosen inversion time. In vivo experiments were performed in mice receiving manganese using an implanted osmotic pump. The results showed that SRR works well as a resolution-enhancing technique in IR-SE MEMRI experiments. In addition, the SRR image also shows a number of brain structures that are more clearly discernible from the surrounding tissues than in three-dimensional GE acquisition, including a number of nuclei with specific higher brain functions, such as memory, stress, anxiety and reward behavior.