qMRI Parameters Research Articles

Correlation of magnetic resonance imaging and computed tomography with biological factor expression and lymph node metastasis in aggressive prostate cancer.

This paper focused on probing the correlation of magnetic resonance imaging (MRI) and computed tomography (CT) manifestations with biological factor expression and lymph node metastasis (LNM) in aggressive prostate cancer (PCa). A total of 136 PCa patients underwent surgical treatment, and received CT and MRI examinations before surgery, whereby the apparent diffusion coefficient (ADC) values of quantitative MRI (qMRI) parameters were obtained. Patients were categorized into the non-aggressive PCa group and aggressive PCa group according to the postoperative pathological results and Gleason scores. The expression of biological factors [prostate-specific antigen (PSA), proliferating cell nuclear antigen (PCNA), p27, and ki-67] in both groups was tested. CT and MRI manifestations of aggressive PCa patients were analyzed. The qMRI parameters, biological factors levels and LNM were compared in two groups; the relationships between CT and MRI manifestations, qMRI parameters and positive expression of biological factors and LNM were probed in two groups. In the aggressive PCa group, MRI and CT presented different degrees of abnormal prostate changes. In the aggressive PCa group, PSA and p27 expression and ADC values were lower, and PCNA and ki-67, and LNM rates were higher. Patients' LNM rate was higher than that of ≤ 2 cm when the tumor diameter was > 2 cm. ADC values were positively correlated with PSA and p27 positive expression, and negatively correlated with PCNA, ki-67 and LNM in the aggressive PCa group. MRI and CT manifestations of aggressive PCa had certain characteristics; MRI manifestations and qMRI possessed a correlation with biological factors and LNM; ADC could be employed to assess the aggressiveness of PCa.

Pre- and post-skeletal muscle biopsy quantitative magnetic resonance imaging reveals correlations with histopathological findings.

Quantitative muscle magnetic resonance imaging (MRI) is a promising non-invasive method in the diagnostic workup as well as follow-up of neuromuscular disorders. The aim of this study was to correlate quantitative MRI (qMRI) parameters to histopathological changes in skeletal muscle tissue and thus to verify the data from our pilot study. Twenty-six patients (eight females, 46.4 ± 15.1 years) were examined within 72 h before and within 24 h after a skeletal muscle biopsy using quantitative muscle MRI. Post-biopsy MRI was employed to pinpoint the exact localization of the biopsy. qMRI parameters including fat fraction, water T2 relaxation time and diffusion metrics including fractional anisotropy, mean diffusivity, axial diffusivity and radial diffusivity were extracted from the localization of the biopsy and correlated with histopathological findings. Additionally, three different segmentation masks were applied to the qMRI dataset, to evaluate whether the whole muscle represents the exact biopsy location. Fat fraction and water T2 relaxation time in qMRI correlated significantly with the fat fraction in the muscle biopsy and histopathological inflammatory markers. Fractional anisotropy correlated with the quantity of type 2 fibres, whilst mean diffusivity correlated with p62. No differences were found using different segmentation masks in qMRI. In this follow-up study, the results from our previous study were verified regarding the correlation of qMRI parameters with histopathological features in muscle biopsies, indicating that qMRI serves as a suitable non-invasive method in the follow-up of patients with neuromuscular disorders. If post-biopsy MRI is not available, whole muscle volume can be used for histopathological correlations.

Quantitative muscle MRI in sporadic inclusion body myositis (sIBM): A prospective cohort study.

Sporadic inclusion body myositis (sIBM) is the predominant idiopathic inflammatory myopathy (IIM) in older people. Limitations of classical clinical assessments have been discussed as possible explanations for failed clinical trials, underlining the need for more sensitive outcome measures. Quantitative muscle MRI (qMRI) is a promising candidate for evaluating and monitoring sIBM. Longitudinal assessment of qMRI in sIBM patients. We evaluated fifteen lower extremity muscles of 12 sIBM patients (5 females, mean age 69.6, BMI 27.8) and 12 healthy age- and gender-matched controls. Seven patients and matched controls underwent a follow-up evaluation after one year. Clinical assessment included testing for muscle strength with Quick Motor Function Measure (QMFM), IBM functional rating scale (IBM-FRS), and gait analysis (6-minute walking distance). 3T-MRI scans of the lower extremities were performed, including a Dixon-based sequence, T2 mapping and Diffusion Tensor Imaging. The qMRI-values fat-fraction (FF), water T2 relaxation time (wT2), fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (λ1), and radial diffusivity (RD) were analysed. Compared to healthy controls, significant differences for all qMRI parameters averaged over all muscles were found in sIBM using a MANOVA (p < 0.001). In low-fat muscles (FF < 10%), a significant increase of wT2 and FA with an accompanying decrease of MD, λ1, and RD was observed (p≤0.020). The highest correlation with clinical assessments was found for wT2 values in thigh muscles (r≤-0.634). Significant changes of FF (+3.0%), wT2 (+0.6 ms), MD (-0.04 10-3mm2/s), λ1 (-0.05 10-3mm2/s), and RD (-0.03 10-3mm2/s) were observed in the longitudinal evaluation of sIBM patients (p≤0.001). FA showed no significant change (p = 0.242). qMRI metrics correlate with clinical findings and can reflect different ongoing pathophysiological mechanisms. While wT2 is an emerging marker of disease activity, the role of diffusion metrics, possibly reflecting changes in fibre size and intracellular deposits, remains subject to further investigations.

Prospective longitudinal cohort study of quantitative muscle magnetic resonance imaging in a healthy control population.

Quantitative muscle magnetic resonance imaging (qMRI) is a valuable methodology for assessing muscular injuries and neuromuscular disorders. Notably, muscle diffusion tensor imaging (DTI) gives insights into muscle microstructural and macrostructural characteristics. However, the long-term reproducibility and robustness of these measurements remain relatively unexplored. The purpose of this prospective longitudinal cohort study was to assess the long-term robustness and range of variation of qMRI parameters, especially DTI metrics, in the lower extremity muscles of healthy controls under real-life conditions. Twelve volunteers (seven females, age 44.1 ± 12.1 years, body mass index 23.3 ± 2.0 kg/m2) underwent five leg muscle MRI sessions every 20 ± 4 weeks over a total period of 1.5 years. A multiecho gradient-echo Dixon-based sequence, a multiecho spin-echo T2-mapping sequence, and a spin-echo echo planar imaging diffusion-weighted sequence were acquired bilaterally with a Philips 3-T Achieva MR System using a 16-channel torso coil. Fifteen leg muscles were segmented in both lower extremities. qMRI parameters, including fat fraction (FF), water T2 relaxation time, and the diffusion metrics fractional anisotropy (FA) and mean diffusivity (MD), were evaluated. Coefficients of variance (wsCV) and intraclass correlation coefficients (ICCs) were calculated to assess the reproducibility of qMRI parameters. The standard error of measurement (SEM) and the minimal detectable change (MDC) were calculated to determine the range of variation. All tests were applied to all muscles and, subsequently, to each muscle separately. wsCV showed good reproducibility (≤ 10%) for all qMRI parameters in all muscles. The ICCs revealed excellent agreement between time points (FF = 0.980, water T2 = 0.941, FA = 0.952, MD = 0.948). Random measurement errors assessed by SEM and the MDC were low (< 12%). In conclusion, in this study, we showed that qMRI parameters in healthy volunteers living normal lives are stable over 18 months, thereby defining a benchmark for the expected range of variation over time.

Quantitative muscle magnetic resonance imaging in limb-girdle muscular dystrophy type R1 (LGMDR1): A prospective longitudinal cohort study.

Limb-girdle muscular dystrophy (LGMD) type R1 (LGMDR1) is the most common subtype of LGMD in Europe. Prospective longitudinal data, including clinical assessments and new biomarkers such as quantitative magnetic resonance imaging (qMRI), are needed to evaluate the natural course of the disease and therapeutic options. We evaluated eight thigh and seven leg muscles of 13 LGMDR1 patients (seven females, mean age 36.7 years, body mass index 23.9 kg/m2) and 13 healthy age- and gender-matched controls in a prospective longitudinal design over 1 year. Clinical assessment included testing for muscle strength with quick motor function measure (QMFM), gait analysis and patient questionnaires (neuromuscular symptom score, activity limitation [ACTIVLIM]). MRI scans were performed on a 3-T MRI scanner, including a Dixon-based sequence, T2 mapping and diffusion tensor imaging. The qMRI values of fat fraction (FF), water T2 relaxation time (T2), fractional anisotropy, mean diffusivity, axial diffusivity and radial diffusivity were analysed. Within the clinical outcome measures, significant deterioration between baseline and follow-up was found for ACTIVLIM (p= 0.029), QMFM (p= 0.012). Analysis of qMRI parameters of the patient group revealed differences between time points for both FF and T2 when analysing all muscles (FF: p< 0.001; T2: p= 0.016). The highest increase of fat replacement was found in muscles with an FF of between 10% and 50% at baseline. T2 in muscles with low-fat replacement increased significantly. No significant differences were found for the diffusion metrics. Significant correlations between qMRI metrics and clinical assessments were found at baseline and follow-up, while only T2 changes in thigh muscles correlated with changes in ACTIVLIM over time (ρ = -0.621, p< 0.05). Clinical assessments can show deterioration of the general condition of LGMDR1 patients. qMRI measures can give additional information about underlying pathophysiology. Further research is needed to establish qMRI outcome measures for clinical trials.

Evaluation of Neuromuscular Diseases and Complaints by Quantitative Muscle MRI.

Background: Quantitative muscle MRI (qMRI) is a promising tool for evaluating and monitoring neuromuscular disorders (NMD). However, the application of different imaging protocols and processing pipelines restricts comparison between patient cohorts and disorders. In this qMRI study, we aim to compare dystrophic (limb-girdle muscular dystrophy), inflammatory (inclusion body myositis), and metabolic myopathy (Pompe disease) as well as patients with post-COVID-19 conditions suffering from myalgia to healthy controls. Methods: Ten subjects of each group underwent a 3T lower extremity muscle MRI, including a multi-echo, gradient-echo, Dixon-based sequence, a multi-echo, spin-echo (MESE) T2 mapping sequence, and a spin-echo EPI diffusion-weighted sequence. Furthermore, the following clinical assessments were performed: Quick Motor Function Measure, patient questionnaires for daily life activities, and 6-min walking distance. Results: Different involvement patterns of conspicuous qMRI parameters for different NMDs were observed. qMRI metrics correlated significantly with clinical assessments. Conclusions: qMRI metrics are suitable for evaluating patients with NMD since they show differences in muscular involvement in different NMDs and correlate with clinical assessments. Still, standardisation of acquisition and processing is needed for broad clinical use.

Towards tumour hypoxia imaging: Incorporating relative oxygen extraction fraction mapping of prostate with multi-parametric quantitative MRI on a 1.5T MR-linac.

Hypoxia plays a central role in tumour radioresistance. Reliable tumour hypoxia imaging would allow the monitoring of tumour response and a more personalized adaptation of radiotherapy planning. Here, we showed a proof of concept of the feasibility and repeatability of relative oxygen extraction fraction (rOEF) mapping of prostate using multi-parametric quantitative MRI (qMRI) achieved for the first time on a 1.5T MR-linac. T2, T2* relaxation times maps, and intra-voxel incoherent motion (IVIM) parametric maps mapping were computed on a 29 years old healthy volunteer. R2' and rOEF maps werecalculated based on a multi-parametric model. Long-term repeatability and repeatability coefficient (RC) were determined for each parameter according to QIBA recommendations. Mean values for the entire healthy prostate were 0.99 ± 0.14 × 10-3 mm/s2, 81 ± 2.1 × 10-3 mm/s2, 21.6 ± 3.6%, 92.7 ± 19.7 ms and 62.4 ± 17.3 ms for Dslow, Dfast, f, T2 and T2*, respectively. R2' and rOEF in the prostate were 6.1 ± 3.4 s-1 and 18.2 ± 10.1% respectively. The RC of rOEF was 4.43%. Long-term repeatability of quantitative parameters based on a test-retest ranged from 2 to 18%. qMRI parameters are measurable and repeatable on 1.5T MR LINAC. From T2, T2* and IVIM parameters maps, we were able to obtain a rOEF mapping of the prostate.These results are the first step to a non-invasive imaging of tumour hypoxia during radiotherapy leading to a biological image-guided adaptive radiotherapy.

Cortical microstructural involvement in cerebral small vessel disease

BackgroundIn cerebral small vessel disease (CSVD), cortical atrophy occurs at a later stage compared to microstructural abnormalities and therefore cannot be used for monitoring short-term disease progression. We aimed to investigate whether cortical diffusion tensor imaging (DTI) and quantitative (q) magnetic resonance imaging (MRI) are able to detect early microstructural involvement of the cerebral cortex in CSVD. Materials and Methods33 CSVD patients without significant cortical or whole-brain atrophy and 16 healthy control subjects were included and underwent structural MRI, DTI and high-resolution qMRI with T2, T2* and T2′ mapping at 3 T as well as comprehensive cognitive assessment. After tissue segmentation and reconstruction of the cortical boundaries with the Freesurfer software, DTI and qMRI parameters were saved as surface datasets and averaged across all vertices. ResultsCortical diffusivity and quantitative T2 values were significantly increased in patients compared to controls (p < 0.05). T2 values correlated significantly positively with white matter hyperintensity (WMH) volume (p < 0.01). Both cortical diffusivity and T2 showed significant negative associations with axonal damage to the white matter fiber tracts (p < 0.05). ConclusionsCortical diffusivity and quantitative T2 mapping are suitable to detect microstructural involvement of the cerebral cortex in CSVD and represent promising imaging biomarkers for monitoring disease progression and effects of therapeutical interventions in clinical studies.

Assessment of training-associated changes of the lumbar back muscle using a multiparametric MRI protocol.

Adaptations in muscle physiology due to long-term physical training have been monitored using various methods: ranging from invasive techniques, such as biopsy, to less invasive approaches, such as electromyography (EMG), to various quantitative magnetic resonance imaging (qMRI) parameters. Typically, these latter parameters are assessed immediately after exercise. In contrast, this work assesses such adaptations in a set of qMRI parameters obtained at rest in the lumbar spine muscles of volunteers. To this end, we developed a multiparametric measurement protocol to extract quantitative values of (water) T2, fat fraction, T1, and Intra Voxel Incoherent Motion (IVIM) diffusion parameters in the lumbar back muscle. The protocol was applied to 31 healthy subjects divided into three differently trained cohorts: two groups of athletes (endurance athletes and powerlifters) and a control group with a sedentary lifestyle. Significant differences in muscle water T2, fat fraction, and pseudo-diffusion coefficient linked to microcirculatory blood flow in muscle tissue were found between the trained and untrained cohorts. At the same time, diffusion coefficients (resolved along different directions) provided additional differentiation between the two groups of athletes. Specifically, the strength-trained athletes showed lower axial and higher radial diffusion components compared to the endurance-trained cohort, which may indicate muscle hypertrophy. In conclusion, utilizing multiparametric information revealed new insights into the potential of quantitative MR parameters to detect and quantify long-term effects associated with training in differently trained cohorts, even at rest.

A comprehensive protocol for quantitative magnetic resonance imaging of the brain at 3 Tesla.

Quantitative MRI (qMRI) has been shown to be clinically useful for numerous applications in the brain and body. The development of rapid, accurate, and reproducible qMRI techniques offers access to new multiparametric data, which can provide a comprehensive view of tissue pathology. This work introduces a multiparametric qMRI protocol along with full postprocessing pipelines, optimized for brain imaging at 3 Tesla and using state-of-the-art qMRI tools. The total scan time is under 50 minutes and includes eight pulse-sequences, which produce range of quantitative maps including T1, T2, and T2* relaxation times, magnetic susceptibility, water and macromolecular tissue fractions, mean diffusivity and fractional anisotropy, magnetization transfer ratio (MTR), and inhomogeneous MTR. Practical tips and limitations of using the protocol are also provided and discussed. Application of the protocol is presented on a cohort of 28 healthy volunteers and 12 brain regions-of-interest (ROIs). Quantitative values agreed with previously reported values. Statistical analysis revealed low variability of qMRI parameters across subjects, which, compared to intra-ROI variability, was x4.1 ± 0.9 times higher on average. Significant and positive linear relationship was found between right and left hemispheres' values for all parameters and ROIs with Pearson correlation coefficients of r>0.89 (P<0.001), and mean slope of 0.95 ± 0.04. Finally, scan-rescan stability demonstrated high reproducibility of the measured parameters across ROIs and volunteers, with close-to-zero mean difference and without correlation between the mean and difference values (across map types, mean P value was 0.48 ± 0.27). The entire quantitative data and postprocessing scripts described in the manuscript are publicly available under dedicated GitHub and Figshare repositories. The quantitative maps produced by the presented protocol can promote longitudinal and multi-center studies, and improve the biological interpretability of qMRI by integrating multiple metrics that can reveal information, which is not apparent when examined using only a single contrast mechanism.

Muscle diffusion MRI reveals autophagic buildup in a mouse model for Pompe disease

Quantitative muscle MRI is increasingly important in the non-invasive evaluation of neuromuscular disorders and their progression. Underlying histopathotological alterations, leading to changes in qMRI parameters are incompletely unraveled. Early microstructural differences of unknown origin reflected by Diffusion MRI in non-fat infiltrated muscles were detected in Pompe patients. This study employed a longitudinal approach with a Pompe disease mouse model to investigate the histopathological basis of these changes. Monthly scans of Pompe (Gaa6neo/6neo) and wildtype mice (age 1–8 months) were conducted using diffusion MRI, T2-mapping, and Dixon-based water-fat imaging on a 7 T scanner. Immunofluorescence studies on quadriceps muscles were analyzed for lysosomal accumulations and autophagic buildup and correlated with MRI outcome measures. Fat fraction and water-T2 did not differ between groups and remained stable over time. In Pompe mice, fractional anisotropy increased, while mean diffusivity (MD) and radial diffusivity (RD) decreased in all observed muscles. Autophagic marker and muscle fibre diameter revealed significant negative correlations with reduced RD and MD, while lysosomal marker did not show any change or correlation. Using qMRI, we showed diffusion changes in muscles of presymptomatic Pompe mice without fat-infiltrated muscles and correlated them to autophagic markers and fibre diameter, indicating diffusion MRI reveals autophagic buildup.

Differential Response in Quantitative MRI Parameters Detected in Head and Neck Cancer Patients Treated with Concurrent Immunotherapy during Hypo-Fractionated MR-gRT

Recently, multiple clinical trials have demonstrated success of PD-1/PD-L1-targeted immune checkpoint inhibition (ICI) in recurrent and metastatic head and neck cancer (HNC). However, three large clinical trials combining PD-1/PD-L1-targeted ICI with RT or chemo-RT (CRT) in the definitive management of HNC have shown no benefit of combination therapy with ICI over RT or CRT alone. Our overarching hypotheses are: i) hypo-fractionation may ultimately better synergize with ICI compared to conventional RT regimens, and ii) immunologic changes in the tumor microenvironment may be detectable using quantitative MRI (qMRI) parameters collected during RT. Seven patients treated with hypo-fractionated MR-guided RT of 50 Gy in 15 fractions (DEHART, NCT04477759) were included in the study. Four patients (Group 1) were treated with concurrent atezolizumab (a monoclonal antibody) and three patients (Group 2) were treated with RT alone. Daily DWI, T1 mapping, and T2 mapping sequences were acquired on a 1.5T MR-Linac in the idle time during adaptive plan generation. Median ADC, T1, T2, and Dslow (derived from b-values 150 and 550 s/mm2) values were extracted from physician-defined GTV and manually constructed posterior paraspinal muscle contours, the latter serving as a control. Wilcoxon signed rank tests were conducted using pre/post treatment data for each qMRI parameter. GTV ADC, Dslow, T2, and T1 increased for both patient groups over the course of treatment with significant differences in ADC, Dslow, and T2 detected between fractions 1 and 15 for all patients studied (p = 0.0156, p = 0.0156, and p = 0.0469, respectively). No significant differences were detected in control qMRI parameters pre/post treatment. No significant differences in ADC, Dslow, and T2 were detected between groups' fractions 1 and 15 in these small cohorts. However, interestingly, we observed a differential change in the increase of median GTV T2 and Dslow values during fractions 10-12 in Group 1 compared to Group 2, suggesting this time interval may prime the anti-tumor immune response. Combining hypo-fractionated RT with ICI leads to a differential response in quantitative MRI (qMRI) parameters in HNC patients. These results suggest that qMRI parameter changes ten days following the start of RT may reflect a critical juncture in the anti-tumoral immune response when ICI is combined with hypo-fractionated RT.

Focal epilepsy without overt epileptogenic lesions: no evidence of microstructural brain tissue damage in multi-parametric quantitative MRI.

In patients with epilepsies of structural origin, brain atrophy and pathological alterations of the tissue microstructure extending beyond the putative epileptogenic lesion have been reported. However, in patients without any evidence of epileptogenic lesions on diagnostic magnetic resonance imaging (MRI), impairment of the brain microstructure has been scarcely elucidated. Using multiparametric quantitative (q) magnetic resonance imaging MRI, we aimed to investigate diffuse impairment of the microstructural tissue integrity in MRI-negative focal epilepsy patients. 27 MRI-negative patients with focal epilepsy (mean age 33.1 ± 14.2 years) and 27 matched healthy control subjects underwent multiparametric qMRI including T1, T2, and PD mapping at 3 T. After tissue segmentation based on synthetic anatomies, mean qMRI parameter values were extracted from the cerebral cortex, the white matter (WM) and the deep gray matter (GM) and compared between patients and control subjects. Apart from calculating mean values for the qMRI parameters across the respective compartments, voxel-wise analyses were performed for each tissue class. There were no significant differences for mean values of quantitative T1, T2, and PD obtained from the cortex, the WM and the deep GM between the groups. Furthermore, the voxel-wise analyses did not reveal any clusters indicating significant differences between patients and control subjects for the qMRI parameters in the respective compartments. Based on the employed methodology, no indication for an impairment of the cerebral microstructural tissue integrity in MRI-negative patients with focal epilepsy was found in this study. Further research will be necessary to identify relevant factors and mechanisms contributing to microstructural brain tissue damage in various subgroups of patients with epilepsy.

T1ρ and T2* measurements in small and knee-sized magnetic resonance imaging phantoms: Effect of phantom size and position relative to isocenter

ObjectiveQuantitative magnetic resonance imaging (qMRI) parameters such as T1ρ and T2* characterize changes in cartilage matrix composition prior to cartilage loss. However, T1ρ and T2* measurement reliability in phantoms that mimic in vivo knee size and position within the scanner bore (left or right side of isocenter) is unknown. This study aimed to quantify sources of variance, and the systematic differences between left and right positions in T1ρ and T2* in small vials of a commercially available phantom and a knee-sized phantom. MethodsPhantoms were imaged 100 mm to the left and right of isocenter on five days using 3D MAPSS (T1ρ) and 3D gradient echo (T2*) sequences at 3T. Variance component analysis estimated the variability attributable to slice, side, vial, and day. Measurement error was quantified with 95% confidence intervals (CI). Paired t-tests evaluated systematic differences between the left and right imaging locations (p<.05). ResultsAveraged across days the left-to-right phantom positions produced differences of 0.1 ms (p<.0001) for T1ρ and -0.8 ms (p<.0001) for T2* in the knee-sized phantoms, and differences ranged from -1.5 ± 0.3 ms (p=.0004) to -0.4 ± 0.4 ms (p=.045) for T1ρ and -3.3 ± 2.5 ms (p<.0001) to 2.3 ± 1.5 ms (p<.0001) for T2* in the small vial phantoms. The total variance for T2* was much less for the knee-sized phantom (0.9) than the small-vial pairs with the same concentration (7.0). ConclusionsThis study revealed a position and phantom size dependence on qMRI parameters not reported previously. Future studies and quality control acquisitions should consider position within the MR scanner and phantom size in their design.

Multiparametric Quantitative MRI of Peripheral Nerves in the Leg: A Reliability Study.

Patients with polyneuropathies typically have demyelination and/or axonal degeneration in peripheral nerves. Currently, there is a lack of imaging biomarkers to track the changes in these pathologies. To develop and evaluate the reliability of a multiparametric quantitative magnetic resonance imaging (qMRI) method of peripheral nerves in the leg. Prospective. Seventeen healthy volunteers (36.2 ± 13.8 years old, 9 males) with 10 of them scanned twice for test-retest. 3 T, three-dimensional gradient echo and diffusion tensor imaging. A qMRI protocol and processing pipeline was established for quantifying the following nerve parameters that are sensitive to myelin and axonal pathologies: magnetization transfer (MT) ratio (MTR), MT saturation index (MTsat), T2 *, T1 , proton density (PD), fractional anisotropy (FA), and mean/axial/radial diffusivities (MD, AD, and RD). The qMRI protocol also measures the volume of nerve fascicles (fVOL) and the fat fraction (FF) of muscles. The intersession reproducibility and inter-rater reliability of each qMRI parameter were assessed by Bland-Altman analysis and intraclass correlation coefficient (ICC). Pairwise Pearson correlation analyses were performed to investigate the intrinsic association between qMRI parameters. Distal-to-proximal variations were evaluated by paired t-tests with Bonferroni-Holm multiple comparison corrections. P < 0.05 was considered statistically significant. The MTR, MTsat, T2 *, T1 , PD, FA, AD, and fVOL of the sciatic and tibial nerves, and the FF of leg muscles, had an overall good-to-excellent test-retest agreement (ICC varying from 0.78 to 0.99). All the qMRI parameters had good-to-excellent inter-rater reliability (ICC > 0.80). The data demonstrated a pattern of distal-to-proximal changes of an increased nerve MTsat and FA, and a decreased nerve T1 , PD, MD, and RD, as well as a significantly increased muscle FF. The proposed multiparametric qMRI method of the peripheral nerves is highly reproducible and provided healthy control data which will be used in developing monitoring biomarkers in patients with polyneuropathies. 1 TECHNICAL EFFICACY: Stage 2.

Multiparametric quantitative MRI reveals progressive cortical damage over time in clinically stable relapsing-remitting MS

BackgroundIn relapsing-remitting multiple sclerosis (RRMS), cortical grey matter pathology relevantly contributes to long-term disability. Still, diffuse cortical inflammation cannot be detected with conventional MRI.ObjectiveWe aimed to assess microstructural damage of...

Using quantitative magnetic resonance imaging to track cerebral alterations in multiple sclerosis brain: A longitudinal study.

Quantitative MRI quantifies tissue microstructural properties and supports the characterization of cerebral tissue damages. With an MPM protocol, 4 parameter maps are constructed: MTsat, PD, R1 and R2*, reflecting tissue physical properties associated with iron and myelin contents. Thus, qMRI is a good candidate for in vivo monitoring of cerebral damage and repair mechanisms related to MS. Here, we used qMRI to investigate the longitudinal microstructural changes in MS brain. Seventeen MS patients (age 25-65, 11 RRMS) were scanned on a 3T MRI, in two sessions separated with a median of 30 months, and the parameters evolution was evaluated within several tissue classes: NAWM, NACGM and NADGM, as well as focal WM lesions. An individual annual rate of change for each qMRI parameter was computed, and its correlation to clinical status was evaluated. For WM plaques, three areas were defined, and a GLMM tested the effect of area, time points, and their interaction on each median qMRI parameter value. Patients with a better clinical evolution, that is, clinically stable or improving state, showed positive annual rate of change in MTsat and R2* within NAWM and NACGM, suggesting repair mechanisms in terms of increased myelin content and/or axonal density as well as edema/inflammation resorption. When examining WM lesions, qMRI parameters within surrounding NAWM showed microstructural modifications, even before any focal lesion is visible on conventional FLAIR MRI. The results illustrate the benefit of multiple qMRI data in monitoring subtle changes within normal appearing brain tissues and plaque dynamics in relation with tissue repair or disease progression.

Quantitative muscle MRI displays clinically relevant myostructural abnormalities in long-term ICU-survivors: a case–control study

BackgroundLong-term data on ICU-survivors reveal persisting sequalae and a reduced quality-of-life even after years. Major complaints are neuromuscular dysfunction due to Intensive care unit acquired weakness (ICUAW). Quantitative MRI (qMRI) protocols can quantify muscle alterations in contrast to standard qualitative MRI-protocols.MethodsUsing qMRI, the aim of this study was to analyse persisting myostructural abnormalities in former ICU patients compared to controls and relate them to clinical assessments. The study was conducted as a cohort/case–control study. Nine former ICU-patients and matched controls were recruited (7 males; 54.8y ± 16.9; controls: 54.3y ± 11.1). MRI scans were performed on a 3T-MRI including a mDTI, T2 mapping and a mDixonquant sequence. Water T2 times, fat-fraction and mean values of the eigenvalue (λ1), mean diffusivity (MD), radial diffusivity (RD) and fractional anisotropy (FA) were obtained for six thigh and seven calf muscles bilaterally. Clinical assessment included strength testing, electrophysiologic studies and a questionnaire on quality-of-life (QoL). Study groups were compared using a multivariate general linear model. qMRI parameters were correlated to clinical assessments and QoL questionnaire using Pearson´s correlation.ResultsqMRI parameters were significantly higher in the patients for fat-fraction (p < 0.001), water T2 time (p < 0.001), FA (p = 0.047), MD (p < 0.001) and RD (p < 0.001). Thighs and calves showed a different pattern with significantly higher water T2 times only in the calves. Correlation analysis showed a significant negative correlation of muscle strength (MRC sum score) with FA and T2-time. The results were related to impairment seen in QoL-questionnaires, clinical testing and electrophysiologic studies.ConclusionqMRI parameters show chronic next to active muscle degeneration in ICU survivors even years after ICU therapy with ongoing clinical relevance. Therefore, qMRI opens new doors to characterize and monitor muscle changes of patients with ICUAW. Further, better understanding on the underlying mechanisms of the persisting complaints could contribute the development of personalized rehabilitation programs.

Radiomics and machine learning applied to STIR sequence for prediction of quantitative parameters in facioscapulohumeral disease.

Quantitative Muscle MRI (qMRI) is a valuable and non-invasive tool to assess disease involvement and progression in neuromuscular disorders being able to detect even subtle changes in muscle pathology. The aim of this study is to evaluate the feasibility of using a conventional short-tau inversion recovery (STIR) sequence to predict fat fraction (FF) and water T2 (wT2) in skeletal muscle introducing a radiomic workflow with standardized feature extraction combined with machine learning algorithms. Twenty-five patients with facioscapulohumeral muscular dystrophy (FSHD) were scanned at calf level using conventional STIR sequence and qMRI techniques. We applied and compared three different radiomics workflows (WF1, WF2, WF3), combined with seven Machine Learning regression algorithms (linear, ridge and lasso regression, tree, random forest, k-nearest neighbor and support vector machine), on conventional STIR images to predict FF and wT2 for six calf muscles. The combination of WF3 and K-nearest neighbor resulted to be the best predictor model of qMRI parameters with a mean absolute error about ± 5 pp for FF and ± 1.8 ms for wT2. This pilot study demonstrated the possibility to predict qMRI parameters in a cohort of FSHD subjects starting from conventional STIR sequence.

Quantitative MRI maps of human neocortex explored using cell type-specific gene expression analysis.

Quantitative magnetic resonance imaging (qMRI) allows extraction of reproducible and robust parameter maps. However, the connection to underlying biological substrates remains murky, especially in the complex, densely packed cortex. We investigated associations in human neocortex between qMRI parameters and neocortical cell types by comparing the spatial distribution of the qMRI parameters longitudinal relaxation rate (${R_{1}}$), effective transverse relaxation rate (${R_{2}}^{\ast }$), and magnetization transfer saturation (MTsat) to gene expression from the Allen Human Brain Atlas, then combining this with lists of genes enriched in specific cell types found in the human brain. As qMRI parameters are magnetic field strength-dependent, the analysis was performed on MRI data at 3T and 7T. All qMRI parameters significantly covaried with genes enriched in GABA- and glutamatergic neurons, i.e. they were associated with cytoarchitecture. The qMRI parameters also significantly covaried with the distribution of genes enriched in astrocytes (${R_{2}}^{\ast }$ at 3T, ${R_{1}}$ at 7T), endothelial cells (${R_{1}}$ and MTsat at 3T), microglia (${R_{1}}$ and MTsat at 3T, ${R_{1}}$ at 7T), and oligodendrocytes and oligodendrocyte precursor cells (${R_{1}}$ at 7T). These results advance the potential use of qMRI parameters as biomarkers for specific cell types.