Tibial and femoral articular cartilage exhibit opposite outcomes for T1ρ and T2* relaxation times in response to acute compressive loading in healthy knees

Abnormal loading is thought to play a key role in the disease progression of cartilage, but our understanding of how cartilage compositional measurements respond to acute compressive loading in-vivo is limited. Ten healthy subjects were scanned at two timepoints (7 ± 3 days apart) with a 3 T magnetic resonance imaging (MRI) scanner. Scanning sessions included T1ρ and T2* acquisitions of each knee in two conditions: unloaded (traditional MRI setup) and loaded in compression at 40 % bodyweight as applied by an MRI-compatible loading device. T1ρ and T2* parameters were quantified for contacting cartilage (tibial and femoral) and non-contacting cartilage (posterior femoral condyle) regions. Significant effects of load were found in contacting regions for both T1ρ and T2*. The effect of load (loaded minus unloaded) in femoral contacting regions ranged from 4.1 to 6.9 ms for T1ρ, and 3.5 to 13.7 ms for T2*, whereas tibial contacting regions ranged from -5.6 to -1.7 ms for T1ρ, and -2.1 to 0.7 ms for T2*. Notably, the responses to load in the femoral and tibial cartilage revealed opposite effects. No significant differences were found in response to load between the two visits. This is the first study that analyzed the effects of acute loading on T1ρ and T2* measurements in human femoral and tibial cartilage separately. The results suggest the effect of acute compressive loading on T1ρ and T2* was: 1) opposite in the femoral and tibial cartilage; 2) larger in contacting regions than in non-contacting regions of the femoral cartilage; and 3) not different visit-to-visit.

Unconstrained quantitative magnetization transfer imaging: disentangling T1 of the free and semi-solid spin pools

Since the inception of magnetization transfer (MT) imaging, it has been widely assumed that Henkelman's two spin pools have similar longitudinal relaxation times, which motivated many researchers to constrain them to each other. However, several recent publications reported a T 1 s of the semi-solid spin pool that is much shorter than T 1 f of the free pool. While these studies tailored experiments for robust proofs-of-concept, we here aim to quantify the disentangled relaxation processes on a voxel-by-voxel basis in a clinical imaging setting, i.e., with an effective resolution of 1.24mm isotropic and full brain coverage in 12min. To this end, we optimized a hybrid-state pulse sequence for mapping the parameters of an unconstrained MT model. We scanned four people with relapsing-remitting multiple sclerosis (MS) and four healthy controls with this pulse sequence and estimated T 1 f ≈ 1.84 s and T 1 s ≈ 0.34 s in healthy white matter. Our results confirm the reports that T 1 s ≪ T 1 f and we argue that this finding identifies MT as an inherent driver of longitudinal relaxation in brain tissue. Moreover, we estimated a fractional size of the semi-solid spin pool of m 0 s ≈ 0.212 , which is larger than previously assumed. An analysis of T 1 f in normal-appearing white matter revealed statistically significant differences between individuals with MS and controls.

Anisotropy of T2 and T1ρ relaxation time in articular cartilage at 3 T

PURPOSE

The anisotropy of R2 and R1ρ relaxation rates in articular cartilage contains information about the collagenous structure of the tissue. Here we determine and study the anisotropic and isotropic components of T2 and T1ρ relaxation parameters in articular cartilage with a clinical 3T MRI device. Furthermore, a visual representation of the topographical variation in anisotropy is given via anisotropy mapping.

METHODS

Eight bovine stifle joints were imaged at 22 orientations with respect to the main magnetic field using T2, continuous-wave (CW) T1ρ, and adiabatic T1ρ mapping sequences. Relaxation rates were separated into isotropic and anisotropic relaxation components using a previously established relaxation anisotropy model. Pixel-wise anisotropy values were determined from the relaxation-time maps using Michelson contrast.

RESULTS

The relaxation rates obtained from the samples displayed notable variation depending on the sample orientation, magnetization preparation, and cartilage layer. R2 demonstrated significant anisotropy, whereas CW-R1ρ (300 Hz) and CW-R1ρ (500 Hz) displayed a low degree of anisotropy. Adiabatic R1ρ was largely isotropic. In the deep cartilage regions, relaxation rates were generally faster and more anisotropic than in the cartilage closer to the tissue surface. The isotropic relaxation rate components were found to have similar values regardless of measurement sequence.

CONCLUSIONS

The fitted relaxation model for T2 and T1ρ demonstrated varying amounts anisotropy, depending on magnetization preparation, and studied the articular cartilage layer. Anisotropy mapping of full joints showed varying amounts of anisotropy depending on the quantitative MRI parameter and topographical location, and in the case of T2, showed systematic changes in anisotropy across cartilage depth.

Quantitative whole-body muscle MRI in idiopathic inflammatory myopathies including polymyositis with mitochondrial pathology: indications for a disease spectrum

OBJECTIVE

Inflammatory myopathies (IIM) include dermatomyositis (DM), sporadic inclusion body myositis (sIBM), immune-mediated necrotizing myopathy (IMNM), and overlap myositis (OLM)/antisynthetase syndrome (ASyS). There is also a rare variant termed polymyositis with mitochondrial pathology (PM-Mito), which is considered a sIBM precursor. There is no information regarding muscle MRI for this rare entity. The aim of this study was to compare MRI findings in IIM, including PM-Mito.

METHODS

This retrospective analysis included 41 patients (7 PM-Mito, 11 sIBM, 11 PM/ASyS/OLM, 12 IMNM) and 20 healthy controls. Pattern of muscle involvement was assessed by semiquantitative evaluation, while Dixon method was used to quantify muscular fat fraction.

RESULTS

The sIBM typical pattern affecting the lower extremities was not found in the majority of PM-Mito-patients. Intramuscular edema in sIBM and PM-Mito was limited to the lower extremities, whereas IMNM and PM/ASyS/OLM showed additional edema in the trunk. Quantitative assessment showed increased fat content in sIBM, with an intramuscular proximo-distal gradient. Similar changes were also found in a few PM-Mito- and PM/ASyS/OLM patients. In sIBM and PM-Mito, mean fat fraction of several muscles correlated with clinical involvement.

INTERPRETATION

As MRI findings in patients with PM-Mito relevantly differed from sIBM, the attribution of PM-Mito as sIBM precursor should be critically discussed. Some patients in PM/ASyS/OLM and PM-Mito group showed MR-morphologic features predominantly observed in sIBM, indicative of a spectrum from PM/ASyS/OLM toward sIBM. In some IIM subtypes, MRI may serve as a biomarker of disease severity.

Radiation damping at clinical field strength: Characterization and compensation in quantitative measurements

PURPOSE

In any MR experiment, the bulk magnetization acts on itself, caused by the induced current in the RF receiver circuit that generates an oscillating damping field. This effect, known as "radiation damping" (RD), is usually weak and, therefore, unconsidered in MRI, but can affect quantitative studies performed with dedicated coils that provide a high SNR. The current work examined RD in a setup for investigations of small tissue specimens including a quantitative characterization of the spin-coil system.

THEORY AND METHODS

A custom-made Helmholtz coil (radius and spacing 16 mm) was interfaced to a transmit-receive (Tx/Rx) switch with integrated passive feedback for modulation or suppression of RD similar to preamplifier decoupling. Pulse sequences included pulse-width arrays to demonstrate the absence/ presence of RD and difference techniques employing gradient pulses or composite RF pulses to quantify RD effects during free precession and transmission, respectively. Experiments were performed at 3T in small samples of MnCl2 solution.

RESULTS

Significant RD effects may impact RF pulse application and evolution periods. Effective damping time constants were comparable to typical T2 * times or echo spacings in multi-echo sequences. Measurements of the phase relation showed that deviations from the commonly assumed 90° angle between the damping field and the transverse magnetization may occur.

CONCLUSION

Radiation damping may affect the accuracy of quantitative MR measurements performed with dedicated RF coils. Efficient mitigation can be achieved hardware-based or by appropriate consideration in the pulse sequence.

Quantitative MRI versus perioperative arthroscopy to measure stage 1 ruptures of the supraspinatus tendon for surgical planning

BACKGROUND

Accurate preoperative assessment of supraspinatus tendon tear (STT) size is important for surgical planning. Our aims were to evaluate the correlation between stage 1 STT size measured preoperatively by quantitative (q)MRI and size measured perioperatively by arthroscopy. The concordance between preoperative tear size and the surgical plan was also assessed.

METHODS

This prospective, non-randomized, non-controlled, interventional study was carried out in patients with a stable stage 1 STT. Three months before surgery, STT size was measured in the sagittal and coronal planes by a radiologist by qMRI (1.5T). Three months later, the surgeon measured the size of the tear again on the same qMRI scans and decided on the most appropriate surgical plan. During arthroscopy, the surgeon measured the size of the tear again using a graduated sensor hook and carried out the repair. STT size measured preoperatively was compared to that measured by arthroscopy and the concordance between preoperative STT size and the surgical plan was determined.

RESULTS

Sixty-seven patients were included (mean age: 59.5 ± 8.9 years; 58.2% female). These was good concordance between STT size measured by qMRI vs. arthroscopy in the coronal plane (concordance correlation coefficient (CCC) =0.36 [95%CI: 0.16‒0.53]; Pearson's correlation coefficient =0.42 [95%CI: 0.2‒0.6]; P=0.0004) and in the sagittal plane (CCC =0.51 [95%CI: 0.33‒0.65]; Pearson's correlation coefficient =0.57 [95%CI: 0.38‒0.71]; P<0.0001). Preoperative STT size concurred with the surgical plan in 85% of patients.

CONCLUSION

There was good concordance between STT size measured by qMRI and that measured perioperatively by arthroscopy. However, preoperative STT size measured by qMRI did not concur with the surgical plan in 15% of patients and in these patients the surgical procedure had to be revised during surgery.

Intrauterine exposure to SARS-CoV-2 infection and early newborn brain development

Epidemiologic studies suggest that prenatal exposures to certain viruses may influence early neurodevelopment, predisposing offspring to neuropsychiatric conditions later in life. The long-term effects of maternal COVID-19 infection in pregnancy on early brain development, however, remain largely unknown. We prospectively enrolled infants in an observational cohort study for a single-site study in the Washington, DC Metropolitan Area from June 2020 to November 2021 and compared these infants to pre-pandemic controls (studied March 2014-February 2020). The primary outcomes are measures of cortical morphometry (tissue-specific volumes), along with global and regional measures of local gyrification index, and sulcal depth. We studied 210 infants (55 infants of COVID-19 unexposed mothers, 47 infants of COVID-19-positive mothers, and 108 pre-pandemic healthy controls). We found increased cortical gray matter volume (182.45 ± 4.81 vs. 167.29 ± 2.92) and accelerated sulcal depth of the frontal lobe (5.01 ± 0.19 vs. 4.40 ± 0.13) in infants of COVID-19-positive mothers compared to controls. We found additional differences in infants of COVID-19 unexposed mothers, suggesting both maternal viral exposures, as well as non-viral stressors associated with the pandemic, may influence early development and warrant ongoing follow-up.

Rapid whole brain 3D T2 mapping respiratory-resolved Double-Echo Steady State (DESS) sequence with improved repeatability

PURPOSE

To propose a quantitative 3D double-echo steady-state (DESS) sequence that offers rapid and repeatable T2 mapping of the human brain using different encoding schemes that account for respiratory B0 variation.

METHODS

A retrospective self-gating module was firstly implemented into the standard DESS sequence in order to suppress the respiratory artifact via data binning. A compressed-sensing trajectory (CS-DESS) was then optimized to accelerate the acquisition. Finally, a spiral Cartesian encoding (SPICCS-DESS) was incorporated to further disrupt the coherent respiratory artifact. These different versions were compared to a standard DESS sequence (fully DESS) by assessing the T2 distribution and repeatability in different brain regions of eight volunteers at 3 T.

RESULTS

The respiratory artifact correction was determined to be optimal when the data was binned into seven respiratory phases. Compared to the fully DESS, T2 distribution was improved for the CS-DESS and SPICCS-DESS with interquartile ranges reduced significantly by a factor ranging from 2 to 12 in the caudate, putamen, and thalamus regions. In the gray and white matter areas, average absolute test-retest T2 differences across all volunteers were respectively 3.5 ± 2% and 3.1 ± 2.1% for the SPICCS-DESS, 4.6 ± 4.6% and 4.9 ± 5.1% for the CS-DESS, and 15% ± 13% and 7.3 ± 5.6% for the fully DESS. The SPICCS-DESS sequence's acquisition time could be reduced by half (<4 min) while maintaining its efficient T2 mapping.

CONCLUSION

The respiratory-resolved SPICCS-DESS sequence offers rapid, robust, and repeatable 3D T2 mapping of the human brain, which can be especially effective for longitudinal monitoring of cerebral pathologies.

Microstructural and Metabolic Changes in Normal Aging Human Brain Studied with Combined Whole-Brain MR Spectroscopic Imaging and Quantitative MR Imaging

PURPOSE

This study aimed to detect age-related brain metabolic and microstructural changes in healthy human brains by the use of whole-brain proton magnetic resonance spectroscopic imaging (1H‑MRSI) and quantitative MR imaging (qMRI).

METHODS

In this study, 60 healthy participants with evenly distributed ages (between 21 and 69 years) and sex underwent MRI examinations at 3T including whole-brain 1H‑MRSI. The concentrations of the metabolites N‑acetylaspartate (NAA), choline-containing compounds (Cho), total creatine and phosphocreatine (tCr), glutamine and glutamate (Glx), and myo-inositol (mI), as well as the brain relaxation times T2, T2' and T1 were measured in 12 regions of interest (ROI) in each hemisphere. Correlations between measured parameters and age were estimated with linear regression analysis and Pearson's correlation test.

RESULTS

Significant age-related changes of brain regional metabolite concentrations and tissue relaxation times were found: NAA decreased in eight of twelve ROIs, Cho increased in three ROIs, tCr in four ROIs, and mI in three ROIs. Glx displayed a significant decrease in one ROI and an increase in another ROI. T1 increased in four ROIs and T2 in one ROI, while T2' decreased in two ROIs. A negative correlation of tCr concentrations with T2' relaxation time was found in one ROI as well as the positive correlations of age-related T1 relaxation time with concentrations of tCr, mI, Glx and Cho in another ROI.

CONCLUSION

Normal aging in human brain is associated with coexistent brain regional metabolic alterations and microstructural changes, which may be related to age-related decline in cognitive, affective and psychomotor domains of life in the older population.

Compositional and Functional MRI of Skeletal Muscle: A Review

Due to its exceptional sensitivity to soft tissues, MRI has been extensively utilized to assess anatomical muscle parameters such as muscle volume and cross-sectional area. Quantitative Magnetic Resonance Imaging (qMRI) adds to the capabilities of MRI, by providing information on muscle composition such as fat content, water content, microstructure, hypertrophy, atrophy, as well as muscle architecture. In addition to compositional changes, qMRI can also be used to assess function for example by measuring muscle quality or through characterization of muscle deformation during passive lengthening/shortening and active contractions. The overall aim of this review is to provide an updated overview of qMRI techniques that can quantitatively evaluate muscle structure and composition, provide insights into the underlying biological basis of the qMRI signal, and illustrate how qMRI biomarkers of muscle health relate to function in healthy and diseased/injured muscles. While some applications still require systematic clinical validation, qMRI is now established as a comprehensive technique, that can be used to characterize a wide variety of structural and compositional changes in healthy and diseased skeletal muscle. Taken together, multiparametric muscle MRI holds great potential in the diagnosis and monitoring of muscle conditions in research and clinical applications. EVIDENCE LEVEL: 5 TECHNICAL EFFICACY: Stage 2.

Arthritis Foundation/HSS Workshop on Hip Osteoarthritis, Part 2: Detecting Hips at Risk: Early Biomechanical and Structural Mechanisms

Far more publications are available for osteoarthritis of the knee than of the hip. Recognizing this research gap, the Arthritis Foundation (AF), in partnership with the Hospital for Special Surgery (HSS), convened an in-person meeting of thought leaders to review the state of the science of and clinical approaches to hip osteoarthritis. This article summarizes the recommendations gleaned from 5 presentations given in the "early hip osteoarthritis" session of the 2023 Hip Osteoarthritis Clinical Studies Conference, which took place on February 17 and 18, 2023, in New York City. It also summarizes the workgroup recommendations from a small-group discussion on clinical research gaps.

Probing muscle recovery following downhill running using precise mapping of MRI T2 relaxation times

PURPOSE

Postexercise recovery rate is a vital component of designing personalized training protocols and rehabilitation plans. Tracking exercise-induced muscle damage and recovery requires sensitive tools that can probe the muscles' state and composition noninvasively.

METHODS

Twenty-four physically active males completed a running protocol consisting of a 60-min downhill run on a treadmill at -10% incline and 65% of maximal heart rate. Quantitative mapping of MRI T2 was performed using the echo-modulation-curve algorithm before exercise, and at two time points: 1 h and 48 h after exercise.

RESULTS

T2 values increased by 2%-4% following exercise in the primary mover muscles and exhibited further elevation of 1% after 48 h. For the antagonist muscles, T2 values increased only at the 48-h time point (2%-3%). Statistically significant decrease in the SD of T2 values was found following exercise for all tested muscles after 1 h (16%-21%), indicating a short-term decrease in the heterogeneity of the muscle tissue.

CONCLUSION

MRI T2 relaxation time constitutes a useful quantitative marker for microstructural muscle damage, enabling region-specific identification for short-term and long-term systemic processes, and sensitive assessment of muscle recovery following exercise-induced muscle damage. The variability in T2 changes across different muscle groups can be attributed to their different role during downhill running, with immediate T2 elevation occurring in primary movers, followed by delayed elevation in both primary and antagonist muscle groups, presumably due to secondary damage caused by systemic processes.

Adaptive model-based Magnetic Resonance

PURPOSE

Conventional sequences are static in nature, fixing measurement parameters in advance in anticipation of a wide range of expected tissue parameter values. We set out to design and benchmark a new, personalized approach-termed adaptive MR-in which incoming subject data is used to update and fine-tune the pulse sequence parameters in real time.

METHODS

We implemented an adaptive, real-time multi-echo (MTE) experiment for estimating T₂ s. Our approach combined a Bayesian framework with model-based reconstruction. It maintained and continuously updated a prior distribution of the desired tissue parameters, including T₂ , which was used to guide the selection of sequence parameters in real time.

RESULTS

Computer simulations predicted accelerations between 1.7- and 3.3-fold for adaptive multi-echo sequences relative to static ones. These predictions were corroborated in phantom experiments. In healthy volunteers, our adaptive framework accelerated the measurement of T₂ for n-acetyl-aspartate by a factor of 2.5.

CONCLUSION

Adaptive pulse sequences that alter their excitations in real time could provide substantial reductions in acquisition times. Given the generality of our proposed framework, our results motivate further research into other adaptive model-based approaches to MRI and MRS.

Early MRI-based quantitative outcomes are associated with a positive functional performance trajectory from 6 to 24 months post-ACL surgery

PURPOSE

Quantitative magnetic resonance imaging (qMRI) has been used to determine the failure properties of ACL grafts and native ACL repairs and/or restorations. How these properties relate to future clinical, functional, and patient-reported outcomes remain unknown. The study objective was to investigate the relationship between non-contemporaneous qMRI measures and traditional outcome measures following Bridge-Enhanced ACL Restoration (BEAR). It was hypothesized that qMRI parameters at 6 months would be associated with clinical, functional, and/or patient-reported outcomes at 6 months, 24 months, and changes from 6 to 24 months post-surgery.

METHODS

Data of BEAR patients (n = 65) from a randomized control trial of BEAR versus ACL reconstruction (BEAR II Trial; NCT02664545) were utilized retrospectively for the present analysis. Images were acquired using the Constructive Interference in Steady State (CISS) sequence at 6 months post-surgery. Single-leg hop test ratios, arthrometric knee laxity values, and International Knee Documentation Committee (IKDC) subjective scores were determined at 6 and 24 months post-surgery. The associations between traditional outcomes and MRI measures of normalized signal intensity, mean cross-sectional area (CSA), volume, and estimated failure load of the healing ACL were evaluated based on bivariate correlations and multivariable regression analyses, which considered the potential effects of age, sex, and body mass index.

RESULTS

CSA (r = 0.44, p = 0.01), volume (r = 0.44, p = 0.01), and estimated failure load (r = 0.48, p = 0.01) at 6 months were predictive of the change in single-leg hop ratio from 6 to 24 months in bivariate analysis. CSA (βstandardized = 0.42, p = 0.01), volume (βstandardized = 0.42, p = 0.01), and estimated failure load (βstandardized = 0.48, p = 0.01) remained significant predictors when considering the demographic variables. No significant associations were observed between MRI variables and either knee laxity or IKDC when adjusting for demographic variables. Signal intensity was also not significant at any timepoint.

CONCLUSION

The qMRI-based measures of CSA, volume, and estimated failure load were predictive of a positive functional outcome trajectory from 6 to 24 months post-surgery. These variables measured using qMRI at 6 months post-surgery could serve as prospective markers of the functional outcome trajectory from 6 to 24 months post-surgery, aiding in rehabilitation programming and return-to-sport decisions to improve surgical outcomes and reduce the risk of reinjury.

LEVEL OF EVIDENCE

Level II.

Generalizability of Deep Learning Segmentation Algorithms for Automated Assessment of Cartilage Morphology and MRI Relaxometry

BACKGROUND

Deep learning (DL)-based automatic segmentation models can expedite manual segmentation yet require resource-intensive fine-tuning before deployment on new datasets. The generalizability of DL methods to new datasets without fine-tuning is not well characterized.

PURPOSE

Evaluate the generalizability of DL-based models by deploying pretrained models on independent datasets varying by MR scanner, acquisition parameters, and subject population.

STUDY TYPE

Retrospective based on prospectively acquired data.

POPULATION

Overall test dataset: 59 subjects (26 females); Study 1: 5 healthy subjects (zero females), Study 2: 8 healthy subjects (eight females), Study 3: 10 subjects with osteoarthritis (eight females), Study 4: 36 subjects with various knee pathology (10 females).

FIELD STRENGTH/SEQUENCE

A 3-T, quantitative double-echo steady state (qDESS).

ASSESSMENT

Four annotators manually segmented knee cartilage. Each reader segmented one of four qDESS datasets in the test dataset. Two DL models, one trained on qDESS data and another on Osteoarthritis Initiative (OAI)-DESS data, were assessed. Manual and automatic segmentations were compared by quantifying variations in segmentation accuracy, volume, and T2 relaxation times for superficial and deep cartilage.

STATISTICAL TESTS

Dice similarity coefficient (DSC) for segmentation accuracy. Lin's concordance correlation coefficient (CCC), Wilcoxon rank-sum tests, root-mean-squared error-coefficient-of-variation to quantify manual vs. automatic T2 and volume variations. Bland-Altman plots for manual vs. automatic T2 agreement. A P value < 0.05 was considered statistically significant.

RESULTS

DSCs for the qDESS-trained model, 0.79-0.93, were higher than those for the OAI-DESS-trained model, 0.59-0.79. T2 and volume CCCs for the qDESS-trained model, 0.75-0.98 and 0.47-0.95, were higher than respective CCCs for the OAI-DESS-trained model, 0.35-0.90 and 0.13-0.84. Bland-Altman 95% limits of agreement for superficial and deep cartilage T2 were lower for the qDESS-trained model, ±2.4 msec and ±4.0 msec, than the OAI-DESS-trained model, ±4.4 msec and ±5.2 msec.

DATA CONCLUSION

The qDESS-trained model may generalize well to independent qDESS datasets regardless of MR scanner, acquisition parameters, and subject population.

EVIDENCE LEVEL

1 TECHNICAL EFFICACY: Stage 1.

A method for measuring B0 field inhomogeneity using quantitative double-echo in steady-state

PURPOSE

To develop and validate a method forB 0 $$ {B}_0 $$ mapping for knee imaging using the quantitative Double-Echo in Steady-State (qDESS) exploiting the phase difference (Δ θ $$ \Delta \theta $$ ) between the two echoes acquired. Contrary to a two-gradient-echo (2-GRE) method,Δ θ $$ \Delta \theta $$ depends only on the first echo time.

METHODS

Bloch simulations were applied to investigate robustness to noise of the proposed methodology and all imaging studies were validated with phantoms and in vivo simultaneous bilateral knee acquisitions. Two phantoms and five healthy subjects were scanned using qDESS, water saturation shift referencing (WASSR), and multi-GRE sequences.Δ B 0 $$ \Delta {B}_0 $$ maps were calculated with the qDESS and the 2-GRE methods and compared against those obtained with WASSR. The comparison was quantitatively assessed exploiting pixel-wise difference maps, Bland-Altman (BA) analysis, and Lin's concordance coefficient (ρ c $$ {\rho}_c $$ ). For in vivo subjects, the comparison was assessed in cartilage using average values in six subregions.

RESULTS

The proposed method for measuringΔ B 0 $$ \Delta {B}_0 $$ inhomogeneities from a qDESS acquisition providedΔ B 0 $$ \Delta {B}_0 $$ maps that were in good agreement with those obtained using WASSR.Δ B 0 $$ \Delta {B}_0 $$ ρ c $$ {\rho}_c $$ values were≥ $$ \ge $$ 0.98 and 0.90 in phantoms and in vivo, respectively. The agreement between qDESS and WASSR was comparable to that of a 2-GRE method.

CONCLUSION

The proposed method may allow B0 correction for qDESST 2 $$ {T}_2 $$ mapping using an inherently co-registeredΔ B 0 $$ \Delta {B}_0 $$ map without requiring an additional B0 measurement sequence. More generally, the method may help shorten knee imaging protocols that require an auxiliaryΔ B 0 $$ \Delta {B}_0 $$ map by exploiting a qDESS acquisition that also providesT 2 $$ {T}_2 $$ measurements and high-quality morphological imaging.

Inline dual-echo T2 quantification in brain using a fast mapping reconstruction technique

T2 mapping from 2D proton density and T2-weighted images (PD-T2) using Bloch equation simulations can be time consuming and introduces a latency between image acquisition and T2 map production. A fast T2 mapping reconstruction method is investigated and compared with a previous modeling approach to reduce computation time and allow inline T2 maps on the MRI console. Brain PD-T2 images from five multiple sclerosis patients were used to compare T2 map reconstruction times between the new subtraction method and the Euclidean norm minimization technique. Bloch equation simulations were used to create the lookup table for decay curve matching in both cases. Agreement of the two techniques used Bland-Altman analysis for investigating individual subsets of data and all image points in the five volumes (meta-analysis). The subtraction method resulted in an average reduction of computation time for single slices from 134 s (minimization method) to 0.44 s. Comparing T2 values between the subtraction and minimization methods resulted in a confidence interval ranging from -0.06 to 0.06 ms (95% of values were within ± 0.06 ms between the techniques). Using identical reconstruction code based on the subtraction method, inline T2 maps were produced from PD-T2 images directly on the scanner console. The excellent agreement between the two methods permits the subtraction technique to be interchanged with the previous method, reducing computation time and allowing inline T2 map reconstruction based on Bloch simulations directly on the scanner.

What happens in the brain?

A new imaging method reveals previously undetected structural differences that may contribute to developmental language disorder.

Quantitative MRI reveals differences in striatal myelin in children with DLD

Developmental language disorder (DLD) is a common neurodevelopmental disorder characterised by receptive or expressive language difficulties or both. While theoretical frameworks and empirical studies support the idea that there may be neural correlates of DLD in frontostriatal loops, findings are inconsistent across studies. Here, we use a novel semiquantitative imaging protocol - multi-parameter mapping (MPM) - to investigate microstructural neural differences in children with DLD. The MPM protocol allows us to reproducibly map specific indices of tissue microstructure. In 56 typically developing children and 33 children with DLD, we derived maps of (1) longitudinal relaxation rate R1 (1/T1), (2) transverse relaxation rate R2* (1/T2*), and (3) Magnetization Transfer saturation (MTsat). R1 and MTsat predominantly index myelin, while R2* is sensitive to iron content. Children with DLD showed reductions in MTsat values in the caudate nucleus bilaterally, as well as in the left ventral sensorimotor cortex and Heschl's gyrus. They also had globally lower R1 values. No group differences were noted in R2* maps. Differences in MTsat and R1 were coincident in the caudate nucleus bilaterally. These findings support our hypothesis of corticostriatal abnormalities in DLD and indicate abnormal levels of myelin in the dorsal striatum in children with DLD.

Muscle quantitative MRI in adult SMA patients on nusinersen treatment: a longitudinal study

The recent approval of disease-modifying therapies for spinal muscular atrophy (SMA) raised the need of alternative outcome measures to evaluate treatment efficacy. In this study, we investigated the potential of muscle quantitative MRI (qMRI) as a biomarker of disease progression in adult SMA3 patients during nusinersen treatment. Six adult SMA3 patients (age ranging from 19 to 65 years) underwent 2-point Dixon muscle qMRI at beginning of nusinersen treatment (T0) and after 14 months (T14) to evaluate the muscle fat fraction (FF) at thigh and leg levels; patients were clinically assessed at T0 and T14 with the Hammersmith Functional Rating Scale Expanded (HFMSE), the Revised Upper Limb Module (RULM) and the 6-minute walk test (6MWT). At T0, vastus lateralis muscle displayed the highest mean FF (67.5%), while tibialis anterior was the most preserved one (mean FF = 35.2%). At T0, a slightly significant correlation of FF with HFMSE (p = 0.042) and disease duration (p = 0.042) at thigh level and only with HFMSE (p = 0.042) at leg level was found. At T14, no significant change of mean FF values at thigh and leg muscles was found compared to T0. Conversely, a statistically significant (p = 0.042) improvement of HFMSE was reported at T14. We observed no significant change of FF in thigh and leg muscles after 14 months of nusinersen therapy despite a significant clinical improvement of HFMSE. Further studies with longer follow-up and larger cohorts are needed to better investigate the role of qMRI as marker of disease progression in SMA patients.

Vendor-neutral sequences and fully transparent workflows improve inter-vendor reproducibility of quantitative MRI

PURPOSE

We developed an end-to-end workflow that starts with a vendor-neutral acquisition and tested the hypothesis that vendor-neutral sequences decrease inter-vendor variability of T1, magnetization transfer ratio (MTR), and magnetization transfer saturation-index (MTsat) measurements.

METHODS

We developed and deployed a vendor-neutral 3D spoiled gradient-echo (SPGR) sequence on three clinical scanners by two MRI vendors. We then acquired T1 maps on the ISMRM-NIST system phantom, as well as T1, MTR, and MTsat maps in three healthy participants. We performed hierarchical shift function analysis in vivo to characterize the differences between scanners when the vendor-neutral sequence is used instead of commercial vendor implementations. Inter-vendor deviations were compared for statistical significance to test the hypothesis.

RESULTS

In the phantom, the vendor-neutral sequence reduced inter-vendor differences from 8% to 19.4% to 0.2% to 5% with an overall accuracy improvement, reducing ground truth T1 deviations from 7% to 11% to 0.2% to 4%. In vivo, we found that the variability between vendors is significantly reduced (p = 0.015) for all maps (T1, MTR, and MTsat) using the vendor-neutral sequence.

CONCLUSION

We conclude that vendor-neutral workflows are feasible and compatible with clinical MRI scanners. The significant reduction of inter-vendor variability using vendor-neutral sequences has important implications for qMRI research and for the reliability of multicenter clinical trials.

Myeloarchitectonic plasticity in elite golf players' brains

Human neuroimaging studies have demonstrated that exercise influences the cortical structural plasticity as indexed by gray or white matter volume. It remains elusive, however, whether exercise affects cortical changes at the finer‐grained myelination structure level. To answer this question, we scanned 28 elite golf players in comparison with control participants, using a novel neuroimaging technique—quantitative magnetic resonance imaging (qMRI). The data showed myeloarchitectonic plasticity in the left temporal pole of the golf players: the microstructure of this brain region of the golf players was better proliferated than that of control participants. In addition, this myeloarchitectonic plasticity was positively related to golfing proficiency. Our study has manifested that myeloarchitectonic plasticity could be induced by exercise, and thus, shed light on the potential benefits of exercise on brain health and cognitive enhancement.

Circumventing the curse of dimensionality in magnetic resonance fingerprinting through a deep learning approach

Magnetic resonance fingerprinting (MRF) is a rapidly developing approach for fast quantitative MRI. A typical drawback of dictionary-based MRF is an explosion of the dictionary size as a function of the number of reconstructed parameters, according to the "curse of dimensionality", which determines an explosion of resource requirements. Neural networks (NNs) have been proposed as a feasible alternative, but this approach is still in its infancy. In this work, we design a deep learning approach to MRF using a fully connected network (FCN). In the first part we investigate, by means of simulations, how the NN performance scales with the number of parameters to be retrieved in comparison with the standard dictionary approach. Four MRF sequences were considered: IR-FISP, bSSFP, IR-FISP-B₁ , and IR-bSSFP-B₁ , the latter two designed to be more specific for B1+ parameter encoding. Estimation accuracy, memory usage, and computational time required to perform the estimation task were considered to compare the scalability capabilities of the dictionary-based and the NN approaches. In the second part we study optimal training procedures by including different data augmentation and preprocessing strategies during training to achieve better accuracy and robustness to noise and undersampling artifacts. The study is conducted using the IR-FISP MRF sequence exploiting both simulations and in vivo acquisitions. Results demonstrate that the NN approach outperforms the dictionary-based approach in terms of scalability capabilities. Results also allow us to heuristically determine the optimal training strategy to make an FCN able to predict T₁ ,  T₂ , and M₀ maps that are in good agreement with those obtained with the original dictionary approach. k-SVD denoising is proposed and found to be critical as a preprocessing step to handle undersampled data.

Correcting inter-scan motion artifacts in quantitative R1 mapping at 7T

PURPOSE

Inter-scan motion is a substantial source of error in R 1 estimation methods based on multiple volumes, for example, variable flip angle (VFA), and can be expected to increase at 7T where B 1 fields are more inhomogeneous. The established correction scheme does not translate to 7T since it requires a body coil reference. Here we introduce two alternatives that outperform the established method. Since they compute relative sensitivities they do not require body coil images.

THEORY

The proposed methods use coil-combined magnitude images to obtain the relative coil sensitivities. The first method efficiently computes the relative sensitivities via a simple ratio; the second by fitting a more sophisticated generative model.

METHODS

R 1 maps were computed using the VFA approach. Multiple datasets were acquired at 3T and 7T, with and without motion between the acquisition of the VFA volumes. R 1 maps were constructed without correction, with the proposed corrections, and (at 3T) with the previously established correction scheme. The effect of the greater inhomogeneity in the transmit field at 7T was also explored by acquiring B 1 + maps at each position.

RESULTS

At 3T, the proposed methods outperform the baseline method. Inter-scan motion artifacts were also reduced at 7T. However, at 7T reproducibility only converged on that of the no motion condition if position-specific transmit field effects were also incorporated.

CONCLUSION

The proposed methods simplify inter-scan motion correction of R 1 maps and are applicable at both 3T and 7T, where a body coil is typically not available. The open-source code for all methods is made publicly available.

MULTI-parametric MR imaging with fLEXible design (MULTIPLEX)

PURPOSE

To introduce a gradient echo (GRE) -based method, namely MULTIPLEX, for single-scan 3D multi-parametric MRI with high resolution, signal-to-noise ratio (SNR), accuracy, efficiency, and acquisition flexibility.

THEORY

With a comprehensive design with dual-repetition time (TR), dual flip angle (FA), multi-echo, and optional flow modulation features, the MULTIPLEX signals contain information on radiofrequency (RF) B_1t fields, proton density, T₁ , susceptibility and blood flows, facilitating multiple qualitative images and parametric maps.

METHODS

MULTIPLEX was evaluated on system phantom and human brains, via visual inspection for image contrasts and quality or quantitative evaluation via simulation, phantom scans and literature comparison. Region-of-interest (ROI) analysis was performed on parametric maps of the system phantom and brain scans, extracting the mean and SD of the T₁ , T2∗ , proton density (PD), and/or quantitative susceptibility mapping (QSM) values for comparison with reference values or literature.

RESULTS

One MULTIPLEX scan offers multiple sets of images, including but not limited to: composited PDW/T₁ W/ T2∗ W, aT₁ W, SWI, MRA (optional), B_1t map, T₁ map, T2∗ / R2∗ maps, PD map, and QSM. The quantitative error of phantom T₁ , T2∗ and PD mapping were <5%, and those in brain scans were in good agreement with literature. MULTIPLEX scan times for high resolution (0.68 × 0.68 × 2 mm³ ) whole brain coverage were about 7.5 min, while processing times were <1 min. With flow modulation, additional MRA images can be obtained without affecting the quality or accuracy of other images.

CONCLUSION

The proposed MUTLIPLEX method possesses great potential for multi-parametric MR imaging.

Longitudinal Quantitative MRI Evaluation of Muscle Involvement in Amyotrophic Lateral Sclerosis

Background: Biomarkers of disease progression and outcome measures are still lacking for patients with amyotrophic lateral sclerosis (ALS). Muscle MRI can be a promising candidate to track longitudinal changes and to predict response to the therapy in clinical trials. Objective: Our aim is to apply quantitative muscle MRI in the evaluation of disease progression, focusing on thigh and leg muscles of patients with ALS, and to explore the correlation between radiological and clinical scores. Methods: We enrolled newly diagnosed patients with ALS, longitudinally scored using the ALS Functional Rating Scale-Revised (ALSFRS-R), who underwent a 3T muscle MRI protocol including a 6-point Dixon gradient-echo sequence and multi-echo turbo spin echo (TSE) T2-weighted sequence for quantification of fat fraction (FF), cross-sectional area (CSA), and water T2 (wT2). A total of 12 muscles of the thigh and six muscles of the leg were assessed by the manual drawing of 18 regions of interest (ROIs), for each side. A group of 11 age-matched healthy controls (HCs) was enrolled for comparison. Results: 15 patients (M/F 8/7; mean age 62.2 years old, range 29-79) diagnosed with possible (n = 2), probable (n = 12), or definite (n = 1) ALS were enrolled. Eleven patients presented spinal onset, whereas four of them had initial bulbar involvement. All patients performed MRI at T0, nine of them at T1, and seven of them at T2. At baseline, wT2 was significantly elevated in ALS subjects compared to HCs for several muscles of the thigh and mainly for leg muscles. By contrast, FF was elevated in few muscles, and mainly at the level of the thigh. The applied mixed effects model showed that FF increased significantly in the leg muscles over time (mainly in the triceps surae) and that wT2 decreased significantly in line with worsening in the leg subscore of ALSFRS-R, mainly at the leg level and in the anterior and medial compartment of the thigh. Conclusions: Quantitative MRI represents a non-invasive tool that is able to outline the trajectory of pathogenic modifications at the muscle level in ALS. In particular, wT2 was found to be increased early in the clinical history of ALS and also tended to decrease over time, also showing a positive correlation with leg subscore of ALSFRS-R.

Clinical phenotype modulates brain's myelin and iron content in temporal lobe epilepsy

Temporal lobe epilepsy (TLE) is associated with brain pathology extending beyond temporal lobe structures. We sought to look for informative patterns of brain tissue properties in TLE that go beyond the established morphometry differences. We hypothesised that volume differences, particularly in hippocampus, will be paralleled by changes in brain microstructure. The cross-sectional study included TLE patients (n = 25) from a primary care center and sex-/age-matched healthy controls (n = 55). We acquired quantitative relaxometry-based magnetic resonance imaging (MRI) data yielding whole-brain maps of grey matter volume, magnetization transfer (MT) saturation, and effective transverse relaxation rate R2* indicative for brain tissue myelin and iron content. For statistical analysis, we used the computational anatomy framework of voxel-based morphometry and voxel-based quantification. There was a positive correlation between seizure activity and MT saturation measures in the ipsilateral hippocampus, paralleled by volume differences bilaterally. Disease duration correlated positively with iron content in the mesial temporal lobe, while seizure freedom was associated with a decrease of iron in the very same region. Our findings demonstrate the link between TLE clinical phenotype and brain anatomy beyond morphometry differences to show the impact of disease burden on specific tissue properties. We provide direct evidence for the differential effect of clinical phenotype characteristics on processes involving tissue myelin and iron in mesial temporal lobe structures. This study offers a proof-of-concept for the investigation of novel imaging biomarkers in focal epilepsy.

Determining the longitudinal accuracy and reproducibility of T1 and T2 in a 3T MRI scanner

Purpose

To determine baseline accuracy and reproducibility of T₁ and T₂ relaxation times over 12 months on a dedicated radiotherapy MRI scanner.

Methods

An International Society of Magnetic Resonance in Medicine/National Institute of Standards and Technology (ISMRM/NIST) System Phantom was scanned monthly on a 3T MRI scanner for 1 year. T₁ was measured using inversion recovery (T₁‐IR) and variable flip angle (T₁‐VFA) sequences and T₂ was measured using a multi‐echo spin echo (T₂‐SE) sequence. For each vial in the phantom, accuracy errors (%bias) were determined by the relative differences in measured T₁ and T₂ times compared to reference values. Reproducibility was measured by the coefficient of variation (CV) of T₁ and T₂ measurements across monthly scans. Accuracy and reproducibility were mainly assessed on vials with relaxation times expected to be in physiological ranges at 3T.

Results

A strong linear correlation between measured and reference relaxation times was found for all sequences tested (R² > 0.997). Baseline bias (and CV[%]) for T₁‐IR, T₁‐VFA and T₂‐SE sequences were +2.0% (2.1), +6.5% (4.2), and +8.5% (1.9), respectively.

Conclusions

The accuracy and reproducibility of T₁ and T₂ on the scanner were considered sufficient for the sequences tested. No longitudinal trends of variation were deduced, suggesting less frequent measurements are required following the establishment of baselines.

3D Automated Segmentation of Lower Leg Muscles Using Machine Learning on a Heterogeneous Dataset

Quantitative MRI combines non-invasive imaging techniques to reveal alterations in muscle pathophysiology. Creating muscle-specific labels manually is time consuming and requires an experienced examiner. Semi-automatic and fully automatic methods reduce segmentation time significantly. Current machine learning solutions are commonly trained on data from healthy subjects using homogeneous databases with the same image contrast. While yielding high Dice scores (DS), those solutions are not applicable to different image contrasts and acquisitions. Therefore, the aim of our study was to evaluate the feasibility of automatic segmentation of a heterogeneous database. To create a heterogeneous dataset, we pooled lower leg muscle images from different studies with different contrasts and fields-of-view, containing healthy controls and diagnosed patients with various neuromuscular diseases. A second homogenous database with uniform contrasts was created as a subset of the first database. We trained three 3D-convolutional neuronal networks (CNN) on those databases to test performance as compared to manual segmentation. All networks, training on heterogeneous data, were able to predict seven muscles with a minimum average DS of 0.75. U-Net performed best when trained on the heterogeneous dataset (DS: 0.80 ± 0.10, AHD: 0.39 ± 0.35). ResNet and DenseNet yielded higher DS, when trained on a heterogeneous dataset (both DS: 0.86), as compared to a homogeneous dataset (ResNet DS: 0.83, DenseNet DS: 0.76). In conclusion, a CNN trained on a heterogeneous dataset achieves more accurate labels for predicting a heterogeneous database of lower leg muscles than a CNN trained on a homogenous dataset. We propose that a large heterogeneous database is needed, to make automated segmentation feasible for different kinds of image acquisitions.

Reproducibility of manual segmentation in muscle imaging

Purpose

To assess the reproducibility of a manual muscle MRI segmentation method that follows a specific set of recommendations developed in our center.

Materials and methods

Nine healthy volunteers underwent a muscle MRI examination that included a TSE T2 sequence of the thighs. Muscle segmentation was performed by three operators: an expert operator (OP1) with 3 years of experience and two radiology residents (OP2 and 3) who were both given basic segmentation instructions, whereas only OP2 underwent additional supervised training from OP1. Intra- and inter-operator Dice similarity coefficient (DSC) was calculated.

Results

OP1 showed the highest average intra-operator DSC values (0.885), whereas OP2 had higher average DSC (0.856) compared to OP3 (0.818). The highest inter-operator agreement was observed between Operators 1 and 2 (0.814) and the lowest between OP2 and OP3 (0.702). Confidence interval (CI) analysis showed that the most experienced operator also had the least variability in drawing the ROIs, whereas OP2 showed both higher intra-operator reproducibility compared to OP3 and higher inter-operator agreement with OP1. The muscles that showed the least reproducibility were the semimembranosus and the short head of the biceps femoris.

Discussion

Following specific recommendations such as these ones derived from our single-center experience leads to an overall high reproducibility of manual muscle segmentation and is helpful in improving both intra-operator and inter-operator reproducibility in less experienced operators.

A deep learning approach for magnetic resonance fingerprinting: Scaling capabilities and good training practices investigated by simulations

MR fingerprinting (MRF) is an innovative approach to quantitative MRI. A typical disadvantage of dictionary-based MRF is the explosive growth of the dictionary as a function of the number of reconstructed parameters, an instance of the curse of dimensionality, which determines an explosion of resource requirements. In this work, we describe a deep learning approach for MRF parameter map reconstruction using a fully connected architecture. Employing simulations, we have investigated how the performance of the Neural Networks (NN) approach scales with the number of parameters to be retrieved, compared to the standard dictionary approach. We have also studied optimal training procedures by comparing different strategies for noise addition and parameter space sampling, to achieve better accuracy and robustness to noise. Four MRF sequences were considered: IR-FISP, bSSFP, IR-FISP-B₁, and IR-bSSFP-B₁. A comparison between NN and the dictionary approaches in reconstructing parameter maps as a function of the number of parameters to be retrieved was performed using a numerical brain phantom. Results demonstrated that training with random sampling and different levels of noise variance yielded the best performance. NN performance was at least as good as the dictionary-based approach in reconstructing parameter maps using Gaussian noise as a source of artifacts: the difference in performance increased with the number of estimated parameters because the dictionary method suffers from the coarse resolution of the parameter space sampling. The NN proved to be more efficient in memory usage and computational burden, and has great potential for solving large-scale MRF problems.

Myeloarchitectonic Asymmetries of Language Regions in the Human Brain

One prominent theory in neuroscience and psychology assumes that cortical regions for language are left hemisphere lateralized in the human brain. In the current study, we used a novel technique, quantitative magnetic resonance imaging (qMRI), to examine interhemispheric asymmetries in language regions in terms of macromolecular tissue volume (MTV) and quantitative longitudinal relaxation time (T1) maps in the living human brain. These two measures are known to reflect cortical myeloarchitecture from the microstructural perspective. One hundred and fifteen adults (55 male, 60 female) were examined for their myeloarchitectonic asymmetries of language regions. We found that the cortical myeloarchitecture of inferior frontal areas including the pars opercularis, pars triangularis, and pars orbitalis is left lateralized, while that of the middle temporal gyrus, Heschl’s gyrus, and planum temporale is right lateralized. Moreover, the leftward lateralization of myelination structure is significantly correlated with language skills measured by phonemic and speech tone awareness. This study reveals for the first time a mixed pattern of myeloarchitectonic asymmetries, which calls for a general theory to accommodate the full complexity of principles underlying human hemispheric specialization.

A Comparison of Quantitative R1 and Cortical Thickness in Identifying Age, Lifespan Dynamics, and Disease States of the Human Cortex

Brain development and aging are complex processes that unfold in multiple brain regions simultaneously. Recently, models of brain age prediction have aroused great interest, as these models can potentially help to understand neurological diseases and elucidate basic neurobiological mechanisms. We test whether quantitative magnetic resonance imaging can contribute to such age prediction models. Using R1, the longitudinal rate of relaxation, we explore lifespan dynamics in cortical gray matter. We compare R1 with cortical thickness, a well-established biomarker of brain development and aging. Using 160 healthy individuals (6-81 years old), we found that R1 and cortical thickness predicted age similarly, but the regions contributing to the prediction differed. Next, we characterized R1 development and aging dynamics. Compared with anterior regions, in posterior regions we found an earlier R1 peak but a steeper postpeak decline. We replicate these findings: firstly, we tested a subset (N = 10) of the original dataset for whom we had additional scans at a lower resolution; and second, we verified the results on an independent dataset (N = 34). Finally, we compared the age prediction models on a subset of 10 patients with multiple sclerosis. The patients are predicted older than their chronological age using R1 but not with cortical thickness.

Quantitative MRI: Defining repeatability, reproducibility and accuracy for prostate cancer imaging biomarker development

INTRODUCTION

Quantitative MRI (qMRI) parameters have been increasingly used to develop predictive models to accurately monitor treatment response in prostate cancer after radiotherapy. To reliably detect changes in signal due to treatment response, predictive models require qMRI parameters with high repeatability and reproducibility. The purpose of this study was to measure qMRI parameter uncertainties in both commercial and in-house developed phantoms to guide the development of robust predictive models for monitoring treatment response.

MATERIALS AND METHODS

ADC, T1, and R2* values were acquired across three 3 T scanners with a prostate-specific qMRI protocol using the NIST/ISMRM system phantom, RSNA/NIST diffusion phantom, and an in-house phantom. A B1 field map was acquired to correct for flip angle inhomogeneity in T1 maps. All sequences were repeated in each scan to assess within-session repeatability. Weekly scans were acquired on one scanner for three months with the in-house phantom. Between-session repeatability was measured with test-retest scans 6-months apart on all scanners with all phantoms. Accuracy, defined as percentage deviation from reference value for ADC and T1, was evaluated using the system and diffusion phantoms. Repeatability and reproducibility coefficients of variation (%CV) were calculated for all qMRI parameters on all phantoms.

RESULTS

Overall, repeatability CV of ADC was <2.40%, reproducibility CV was <3.98%, and accuracy ranged between -8.0% to 2.7% across all scanners. Applying B1 correction on T1 measurements significantly improved the repeatability and reproducibility (p<0.05) but increased error in accuracy (p<0.001). Repeatability and reproducibility of R2* was <4.5% and <7.3% respectively in the system phantom across all scanners.

CONCLUSION

Repeatability, reproducibility, and accuracy in qMRI parameters from a prostate-specific protocol was estimated using both commercial and in-house phantoms. Results from this work will be used to identify robust qMRI parameters for use in the development of predictive models to longitudinally monitor treatment response for prostate cancer in current and future clinical trials.

A Perspective on MR Fingerprinting

This article reviews the basic concept of MR fingerprinting (MRF) with the goal of highlighting MRF's key contributions, putting them in the context of other quantitative MRI literature, and refining MRF's terminology. The article discusses the robustness and flexibility of MRF's signature dictionary-matching reconstruction along with more advanced MRF reconstructions. A key feature of MRF is the lack of assumptions about the signal evolution, which gives scientists the flexibility to tailor sequences for their needs. The article argues that the concept of unique fingerprints does not capture the requirements for successful parameter mapping and that an analysis of the signal's derivatives with respect to biophysical parameters, such as relaxation times, is more informative, as it allows one to evaluate the efficiency of a pulse sequence. The article points at the source of MRF's efficiency, namely, flip angle variations at the time scale of the relaxation times, and reveals that MRF's advantages are strongest at long scan times, as required for 3D imaging. Further, it outlines how MRF's flexibility can be used to design mutually tailored pulse sequences and biophysical models with the goal of improving the reproducibility of parameter mapping biological tissue. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY STAGE: 1.

Quantitative Muscle MRI Protocol as Possible Biomarker in Becker Muscular Dystrophy

PURPOSE

Aim of this study is to compare Quantitative Magnetic Resonance Imaging (qMRI) measures between Becker Muscular Dystrophy (BMD) and Healthy Subjects (HS) and to correlate these parameters with clinical scores.

METHODS

Ten BMD patients (mean age ±standard deviation: 38.7 ± 15.0 years) and ten age-matched HS, were investigated through magnetic resonance imaging (MRI) at thigh and calf levels, including: 1) a standard axial T1-weighted sequence; 2) a volumetric T2-weighted sequence; 3) a multiecho spin-echo sequence; 4) a 2-point Dixon sequence; 5) a Diffusion Tensor Imaging (DTI) sequence.

RESULTS

Mean Fat Fraction (FF), T2-relaxation time and Fractional Anisotropy (FA) DTI at thigh and calf levels were significantly higher in BMD patients than in HS (p-values < 0.01). FF at thigh and calf levels significantly correlated with North Star Ambulatory Assessment (NSAA) score (p-values < 0.01) and6 Minutes Walking Test (6MWT) (p-values < 0.01), whereas only calf muscle FF was significantly associated with time to get up from floor (p-value = 0.01). T2 significantly correlated with NSAA score (p-value < 0.01), 6MWT (p-value = 0.02) and time to get up from floor (p-value < 0.01) only at calf level. Among DTI values, only FA in thigh and calf muscles significantly correlated with NSAA score, 6MWT and 10-m walk (all p-values < 0.05); only FA in calf muscles significantly correlated with time to get up from floor (p = 0.01).

CONCLUSIONS

Muscle FF, T2-relaxometry and DTI, seem to be a promising biomarker to assess BMD disease severity, although further studies are needed to evaluate changes over the time.

Potential clinical impact of multiparametric quantitative MR spectroscopy in neurological disorders: A review and analysis

PURPOSE

Unlike conventional MR spectroscopy (MRS), which only measures metabolite concentrations, multiparametric MRS also quantifies their longitudinal (T1 ) and transverse (T2 ) relaxation times, as well as the radiofrequency transmitter inhomogeneity (B1+ ). To test whether knowledge of these additional parameters can improve the clinical utility of brain MRS, we compare the conventional and multiparametric approaches in terms of expected classification accuracy in differentiating controls from patients with neurological disorders.

THEORY AND METHODS

A literature review was conducted to compile metabolic concentrations and relaxation times in a wide range of neuropathologies and regions of interest. Simulations were performed to construct receiver operating characteristic curves and compute the associated areas (area under the curve) to examine the sensitivity and specificity of MRS for detecting each pathology in each region. Classification accuracy was assessed using metabolite concentrations corrected using population-averages for T1 , T2 , and B1+ (conventional MRS); using metabolite concentrations corrected using per-subject values (multiparametric MRS); and using an optimal linear multiparametric estimator comprised of the metabolites' concentrations and relaxation constants (multiparametric MRS). Additional simulations were conducted to find the minimal intra-subject precision needed for each parameter.

RESULTS

Compared with conventional MRS, multiparametric approaches yielded area under the curve improvements for almost all neuropathologies and regions of interest. The median area under the curve increased by 0.14 over the entire dataset, and by 0.24 over the 10 instances with the largest individual increases.

CONCLUSIONS

Multiparametric MRS can substantially improve the clinical utility of MRS in diagnosing and assessing brain pathology, motivating the design and use of novel multiparametric sequences.

Example dataset for the hMRI toolbox

The hMRI toolbox is an open-source toolbox for the calculation of quantitative MRI parameter maps from a series of weighted imaging data, and optionally additional calibration data. The multi-parameter mapping (MPM) protocol, incorporating calibration data to correct for spatial variation in the scanner's transmit and receive fields, is the most complete protocol that can be handled by the toolbox. Here we present a dataset acquired with such a full MPM protocol, which is made freely available to be used as a tutorial by following instructions provided on the associated toolbox wiki pages, which can be found at http://hMRI.info, and following the theory described in: hMRI – A toolbox for quantitative MRI in neuroscience and clinical research [1].

Multiparametric quantitative MRI assessment of thigh muscles in limb-girdle muscular dystrophy 2A and 2B

INTRODUCTION

The aim of this study was to apply quantitative MRI (qMRI) to assess structural modifications in thigh muscles of subjects with limb girdle muscular dystrophy (LGMD) 2A and 2B with long disease duration.

METHODS

Eleven LGMD2A, 9 LGMD2B patients and 11 healthy controls underwent a multi-parametric 3T MRI examination of the thigh. The protocol included structural T1-weighted images, DIXON sequences for fat fraction calculation, T2 values quantification and diffusion MRI. Region of interest analysis was performed on 4 different compartments (anterior compartment, posterior compartment, gracilis, sartorius).

RESULTS

Patients showed high levels of fat infiltration as measured by DIXON sequences. Sartorius and anterior compartment were more infiltrated in LGMD2B than LGMD2A patients. T2 values were mildly reduced in both disorders. Correlations between clinical scores and qMRI were found.

CONCLUSIONS

qMRI measures may help to quantify muscular degeneration, but careful interpretation is needed when fat infiltration is massive. Muscle Nerve 58: 550-558, 2018.

Towards in vivo focal cortical dysplasia phenotyping using quantitative MRI

Focal cortical dysplasias (FCDs) are a range of malformations of cortical development each with specific histopathological features. Conventional radiological assessment of standard structural MRI is useful for the localization of lesions but is unable to accurately predict the histopathological features. Quantitative MRI offers the possibility to probe tissue biophysical properties in vivo and may bridge the gap between radiological assessment and ex-vivo histology. This review will cover histological, genetic and radiological features of FCD following the ILAE classification and will explain how quantitative voxel- and surface-based techniques can characterise these features. We will provide an overview of the quantitative MRI measures available, their link with biophysical properties and finally the potential application of quantitative MRI to the problem of FCD subtyping. Future research linking quantitative MRI to FCD histological properties should improve clinical protocols, allow better characterisation of lesions in vivo and tailored surgical planning to the individual.

•

In vivo lesion phenotyping is crucial for FCD prognosis and surgical planning.

•

Structural MRI can detect lesions but cannot predict all histological features.

•

qMRI provides in vivo biomarkers for biophysical properties linked to histology.

•

Multivariate analyses of morphometry and qMRI measures improve FCD phenotyping.

Quantitative MR Imaging of Brain Tissue and Brain Pathologies

Measurement of basic quantitative magnetic resonance (MR) parameters (e.g., relaxation times T1, T2*, T2 or respective rates R (1/T)) corrected for radiofrequency (RF) coil bias yields different conventional and new tissue contrasts as well as volumes for tissue segmentation. This approach also provides quantitative measures of microstructural and functional tissue changes. We herein demonstrate some prospects of quantitative MR imaging in neurological diagnostics and science.

DCEMRI.jl: a fast, validated, open source toolkit for dynamic contrast enhanced MRI analysis

We present a fast, validated, open-source toolkit for processing dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) data. We validate it against the Quantitative Imaging Biomarkers Alliance (QIBA) Standard and Extended Tofts-Kety phantoms and find near perfect recovery in the absence of noise, with an estimated 10-20× speedup in run time compared to existing tools. To explain the observed trends in the fitting errors, we present an argument about the conditioning of the Jacobian in the limit of small and large parameter values. We also demonstrate its use on an in vivo data set to measure performance on a realistic application. For a 192 × 192 breast image, we achieved run times of <1 s. Finally, we analyze run times scaling with problem size and find that the run time per voxel scales as O(N (1.9)), where N is the number of time points in the tissue concentration curve. DCEMRI.jl was much faster than any other analysis package tested and produced comparable accuracy, even in the presence of noise.

What's new in the use of MRI in the orthopaedic trauma patient?

MRI has been established as an essential tool for accurate diagnosis in patients with musculoskeletal trauma. Its major advantages include excellent soft tissue contrast, high spatial resolution and lack of ionizing radiation. Although plain radiographs remain the basic tool for diagnosis and treatment planning in bone fractures assisted by CT in pelvic, spine and large joints injuries, there are specific circumstances that require MRI. For instance, tendinous, ligamentous, intraarticular structures such as the cartilage and menisci, and intramedullary injury are seen mostly with MRI. Volumetric 3D techniques are now commercially available and provide higher spatial resolution which improves anatomic detail, allows multiplanar reformations and reduces the acquisition time. Newer applications on quantitative rather than morphologic imaging, such as relaxometry and diffusion tensor imaging, may be of paramount importance in treatment planning in the near future. Software improvements reduce metal induced artefacts, allowing thus imaging of the postoperative patient with metallic implants. A tendency towards a structured reporting pattern and standardised medical communication needs to be further explored for the benefit of orthopaedic surgeons, radiologists and patients.

MR parameter quantification with magnetization-prepared double echo steady-state (MP-DESS)

PURPOSE

The mapping of MR relaxation times and proton density has been the subject of research in medical imaging for many years, as it offers the possibility for longitudinal investigation of disease and the correlation with related biochemical processes. The purpose of this study is to provide a fast mapping protocol, which simultaneously acquires MR relaxation times and relative proton density without compromising accuracy and precision.

METHODS

This work presents a novel magnetization-prepared double echo steady-state (MP-DESS) sequence, which was designed to be sensitive to parameter variations of interest, and insensitive to variations of confounding variables. It provides high sensitivity against variations of the MR relaxation times, high acquisition efficiency, and it is insensitive to off-resonance. Accurate phase graph modeling of the MP-DESS signal is used to obtain unbiased parameter estimates.

RESULTS

The approach is validated in phantom and in vivo measurements. A whole-brain acquisition of 1.4-mm isotropic resolution was acquired in 15 min. Comparisons to gold-standard methods suggest a mapping precision of 5% for T1 and M0 , and below 10% for T2.

CONCLUSION

A new quantitative imaging technique is introduced that allows fast and isotropic simultaneous MR parameter mapping of T1, T2, and M0.

Quantitative multi-parameter mapping of R1, PD(*), MT, and R2(*) at 3T: a multi-center validation

Multi-center studies using magnetic resonance imaging facilitate studying small effect sizes, global population variance and rare diseases. The reliability and sensitivity of these multi-center studies crucially depend on the comparability of the data generated at different sites and time points. The level of inter-site comparability is still controversial for conventional anatomical T1-weighted MRI data. Quantitative multi-parameter mapping (MPM) was designed to provide MR parameter measures that are comparable across sites and time points, i.e., 1 mm high-resolution maps of the longitudinal relaxation rate (R1 = 1/T1), effective proton density (PD(*)), magnetization transfer saturation (MT) and effective transverse relaxation rate (R2(*) = 1/T2(*)). MPM was validated at 3T for use in multi-center studies by scanning five volunteers at three different sites. We determined the inter-site bias, inter-site and intra-site coefficient of variation (CoV) for typical morphometric measures [i.e., gray matter (GM) probability maps used in voxel-based morphometry] and the four quantitative parameters. The inter-site bias and CoV were smaller than 3.1 and 8%, respectively, except for the inter-site CoV of R2(*) (<20%). The GM probability maps based on the MT parameter maps had a 14% higher inter-site reproducibility than maps based on conventional T1-weighted images. The low inter-site bias and variance in the parameters and derived GM probability maps confirm the high comparability of the quantitative maps across sites and time points. The reliability, short acquisition time, high resolution and the detailed insights into the brain microstructure provided by MPM makes it an efficient tool for multi-center imaging studies.

Atlas-based and DTI-guided quantification of human brain cerebral blood flow: feasibility, quality assurance, spatial heterogeneity and age effects

Accurate and noninvasive quantification of regional cerebral blood perfusion (CBF) of the human brain tissue would advance the study of the complex interplay between human brain structure and function, in both health and disease. Despite the plethora of works on CBF in gray matter, a detailed quantitative white matter perfusion atlas has not been presented on healthy adults using the International Consortium for Brain Mapping atlases. In this study, we present a host of assurance measures such as temporal stability, spatial heterogeneity and age effects of regional and global CBF in selected deep, cortical gray matter and white matter tracts identified and quantified using diffusion tensor imaging (DTI). We utilized whole brain high-resolution DTI combined with arterial spin labeling to quantify regional CBF on 15 healthy adults aged 23.2-57.1years. We present total brain and regional CBF, corresponding volume, mean diffusivity and fractional anisotropy spatial heterogeneity, and dependence on age as additional quality assurance measures to compare with published trends using both MRI and nuclear medicine methods. Total CBF showed a steady decrease with age in gray matter (r=-0.58; P=.03), whereas total CBF of white matter did not significantly change with age (r=0.11; P=.7). This quantitative report offers a preliminary baseline of CBF, volume and DTI measurements for the design of future multicenter and clinical studies utilizing noninvasive perfusion and DT-MRI.