Quantitative MRI Research Articles

Data-driven normative values based on generative manifold learning for quantitative MRI

In medicine, abnormalities in quantitative metrics such as the volume reduction of one brain region of an individual versus a control group are often provided as deviations from so-called normal values. These normative reference values are traditionally calculated based on the quantitative values from a control group, which can be adjusted for relevant clinical co-variables, such as age or sex. However, these average normative values do not take into account the globality of the available quantitative information. For example, quantitative analysis of T1-weighted magnetic resonance images based on anatomical structure segmentation frequently includes over 100 cerebral structures in the quantitative reports, and these tend to be analyzed separately. In this study, we propose a global approach to personalized normative values for each brain structure using an unsupervised Artificial Intelligence technique known as generative manifold learning. We test the potential benefit of these personalized normative values in comparison with the more traditional average normative values on a population of patients with drug-resistant epilepsy operated for focal cortical dysplasia, as well as on a supplementary healthy group and on patients with Alzheimer’s disease.

An Illustrated Scoping Review of the Magnetic Resonance Imaging Characteristics of Canine and Feline Brain Tumors.

Magnetic resonance imaging (MRI) is used pervasively in veterinary practice for the antemortem diagnosis of intracranial tumors. Here, we provide an illustrated summary of the published MRI features of primary and secondary intracranial tumors of dogs and cats, following PRISMA scoping review guidelines. The PubMed and Web of Science databases were searched for relevant records, and input from stakeholders was solicited to select data for extraction. Sixty-seven studies of moderate to low-level evidence quality describing the MRI features of pathologically confirmed canine and feline brain tumors met inclusion criteria. Considerable variability in data inclusion and reporting, as well as low case numbers, prohibited comparative data analyses. Available data support a holistic MRI approach incorporating lesion number, location within the brain, shape, intrinsic signal appearances on multiparametric sequences, patterns of contrast enhancement, and associated secondary changes in the brain to prioritize differential imaging diagnoses, and often allows for accurate presumptive diagnosis of common intracranial tumors. Quantitative MRI techniques show promise for improving discrimination of neoplastic from non-neoplastic brain lesions, as well as differentiating brain tumor types and grades, but sample size limitations will likely remain a significant practical obstacle to the design of robustly powered radiomic studies. For many brain tumor variants, particularly in cats, there remains a need for standardized studies that correlate clinicopathologic and neuroimaging data.

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.

Surgical stabilization for degenerative lesions of the lumbar spine in patients with reduced bone mineral density: a systematic literature review

Objective. To analyze methods contributing to the improvement of clinical and radiological outcomes of surgical stabilization of the lumbar spine in conditions of reduced bone mineral density (BMD).Material and Methods. A search for publications presenting the results of clinical studies of surgical treatment of patients with degenerative lesions of the lumbar spine and reduced BMD was conducted in English and Russian in the MEDLINE and Russian Science Citation Index (RSCI) databases using key words “osteoporosis”, “osteopenia”, “spinal surgery”, “spinal fusion” and related terms in titles and abstracts with a search depth of 20 years. After applying the inclusion and exclusion criteria, 17 clinical studies were selected for analysis.Results. Among the large number of techniques and implant-associated factors affecting the success of surgical intervention for degenerative lesions of the lumbar spine and reduced BMD, high-quality clinical studies have proven the effectiveness of expandable screws, spinal fusion with cortical screw placement and cement augmentation with polymethyl methacrylate.Conclusion. The combination of techniques for cortical pedicle screw placement, cement augmentation and the use of expandable screws makes it possible to achieve results in surgical treatment of patients with degenerative lesions of the lumbar spine with reduced BMD comparable with those in patients with normal BMD. Of particular importance is the preoperative assessment of the regional state of bone tissue, which should be carried out using quantitative CT or MRI studies.

Quantitative 1H Magnetic Resonance Imaging on Normal and Pathologic Rat Bones by Solid-State 1H ZTE Sequence with Water and Fat Suppression.

Osteoporosis (OP) and osteomalacia (OM) are metabolic bone diseases characterized by mineral and matrix density changes. Quantitative bone matrix density differentiates OM from OP. MRI is a noninvasive and nonionizing imaging technique that can measure bone matrix density quantitatively in ex vivo and in vivo. To demonstrate water + fat suppressed 1H MRI to compute bone matrix density in ex vivo rat femurs in the preclinical model. Prospective. Fifteen skeletally mature female Sprague-Dawley rats, five per group (normal, ovariectomized (OVX), partially nephrectomized/vitamin D (Vit-D) deficient), 250-275 g, ∼15 weeks old. 7T, zero echo time sequence with water + fat (VAPOR) suppression capability, μCT imaging, and gravimetric measurements. Cortical and trabecular bone segments from normal and disease models were scanned in the same coil along with a dual calibration phantom for quantitative assessment of bone matrix density. ANOVA and linear regression were used for data analysis, with P-values <0.05 statistically significant. The MRI-derived three-density PEG pellet densities have a strong linear relationship with physical density measures (r2 = 0.99). The Vit-D group had the lowest bone matrix density for cortical bone (0.47 ± 0.16 g cm-3), whereas the OVX had the lowest bone matrix density for trabecular bone (0.26 ± 0.04 g cm-3). Gravimetry results confirmed these MRI-based observations for Vit-D cortical (0.51 ± 0.07 g cm-3) and OVX trabecular (0.26 ± 0.03 g cm-3) bone groups. Rat femur images were obtained using a modified pulse sequence and a custom-designed double-tuned (1H/31P) transmit-receive solenoid-coil on a 7T preclinical MRI scanner. Phantom experiments confirmed a strong linear relation between MRI-derived and physical density measures and quantitative bone matrix densities in rat femurs from normal, OVX, and Vit-D deficient/partially nephrectomized animals were computed. 2 TECHNICAL EFFICACY: Stage 2.

Automated rating of background parenchymal enhancement in MRI of extremely dense breasts without compromising the association with breast cancer in the DENSE trial

ObjectivesBackground parenchymal enhancement (BPE) on dynamic contrast-enhanced MRI (DCE-MRI) as rated by radiologists is subject to inter- and intrareader variability. We aim to automate BPE category from DCE-MRI. MethodsThis study represents a secondary analysis of the Dense Tissue and Early Breast Neoplasm Screening trial. 4553 women with extremely dense breasts who received supplemental breast MRI screening in eight hospitals were included. Minimal, mild, moderate and marked BPE rated by radiologists were used as reference. Fifteen quantitative MRI features of the fibroglandular tissue were extracted to predict BPE using Random Forest, Naïve Bayes, and KNN classifiers. Majority voting was used to combine the predictions. Internal-external validation was used for training and validation. The inverse-variance weighted mean accuracy was used to express mean performance across the eight hospitals. Cox regression was used to verify non inferiority of the association between automated rating and breast cancer occurrence compared to the association for manual rating. ResultsThe accuracy of majority voting ranged between 0.56 and 0.84 across the eight hospitals. The weighted mean prediction accuracy for the four BPE categories was 0.76. The hazard ratio (HR) of BPE for breast cancer occurrence was comparable between automated rating and manual rating (HR = 2.12 versus HR = 1.97, P = 0.65 for mild/moderate/marked BPE relative to minimal BPE). ConclusionIt is feasible to rate BPE automatically in DCE-MRI of women with extremely dense breasts without compromising the underlying association between BPE and breast cancer occurrence. The accuracy for minimal BPE is superior to that for other BPE categories.

Viscoelastic polyacrylamide MR elastography phantoms with tunable damping ratio independent of shear stiffness

Physiologically modeled test samples with known properties and characteristics, or phantoms, are essential for developing sensitive, repeatable, and accurate quantitative MRI techniques. Magnetic resonance elastography (MRE) is one such technique used to estimate tissue mechanical properties, and it is advantageous to use phantoms with independently tunable mechanical properties to benchmark the accuracy of MRE methods. Phantoms with tunable shear stiffness are commonly used for MRE, but tuning the viscosity or damping ratio has proven to be difficult. A promising candidate for MRE phantoms with tunable damping ratio is polyacrylamide (PAA). While pure PAA has very low attenuation, viscoelastic hydrogels have been made by entrapping linear polyacrylamide strands (LPAA) within the PAA network. In this study, we evaluate the use of LPAA/PAA gels as physiologically accurate phantoms with tunable damping ratio, independent of shear stiffness, via MRE. Phantoms were made with 15.3 wt% PAA while the LPAA concentration ranged from 4.5 wt% to 8.0 wt%. MRE was performed at 9.4 T with 400 Hz vibration on all phantoms revealing a strong, positive correlation between damping ratio and LPAA content (p < 0.001). There was no significant correlation between shear stiffness and LPAA content, confirming a constant PAA concentration yielded constant shear stiffness. Rheometry at 10 Hz was performed to verify the damping ratio of the phantoms. Nearly identical slopes for damping ratio versus LPAA content were found from both MRE and rheometry (0.0073 and 0.0075 respectively). Ultimately, this study validates the adaptation of polyacrylamide gels into physiologically-relevant MRE phantoms to enable testing of MRE estimates of damping ratio.

Quantitative MRI assessment of joint effusion using T2-relaxometry at 3 Tesla: a feasibility and reproducibility study

ObjectiveT2-relaxometry could differentiate between physiological and haemorrhagic joint effusion (≥ 5% blood) in vitro. Are quantitative T2-relaxation time measurements of synovial fluid feasible and reproducible in vivo in clinically bleed-free joints of men with haemophilia?Materials and methodsIn this cross-sectional study, we measured T2-relaxation times of synovial fluid in clinically bleed-free ankles, knees or elbows of men with severe haemophilia A using a T2-mapping sequence (duration ≤ 7 min) at 3 Tesla MRI. Manual and circular regions of interest (ROI) were drawn in the synovial fluid of each joint by two independent observers to measure T2-relaxation times. Measurement feasibility was expressed as the success rate of the measurements by both observers. The interobserver and intraobserver reproducibility of the measurements were evaluated by the intraclass correlation coefficient of absolute agreement (ICC) and the limits of agreement (LoA) from Bland Altman analysis.ResultsWe evaluated 39 clinically bleed-free joints (11 ankles, 12 knees, 16 elbows) of 39 men (median age, 24 years; range 17–33) with severe haemophilia A. The success rate of the T2-measurements was ≥ 90%. Interobserver reliability was good to excellent (manual ROI: ICC = 0.92, 95% CI 0.76–0.97; circular ROI: ICC = 0.82, 95% CI 0.66–0.91) and interobserver agreement was adequate (manual ROI: LoA = 71 ms; circular ROI: LoA = 146 ms). Intraobserver reliability was good to excellent (manual ROI: ICC = 0.78, 95% CI − 0.06–0.94; circular RO: ICC = 0.99, 95% CI 0.98–0.99) and intraobserver agreement was good (manual ROI: LoA = 63 ms; circular ROI: LoA = 41 ms).ConclusionT2-relaxometry of synovial fluid in haemophilia patients is feasible with good interobserver and intraobserver reproducibility.

A quantitative MRI-based approach to estimate the permeation and retention of nanomedicines in tumors

Despite the potential of the enhanced permeability and retention (EPR) effect in tumor passive targeting, many nanotherapeutics have failed to produce meaningful clinical outcomes due to the variable and challenging nature of the tumor microenvironment (TME) and EPR effect. This EPR variability across tumors and inconsistent translation of nanomedicines from preclinical to clinical settings necessitates a reliable method to assess its presence in individual tumors. This study aimed to develop a reliable and non-invasive approach to estimate the EPR effect in tumors using a clinically compatible quantitative magnetic resonance imaging (qMRI) technique combined with a nano-sized MRI contrast agent. A quantitative MR imaging was developed using a dynamic contrast-enhanced (DCE) MRI protocol. Then, the permeability and retention of the nano-sized MRI contrast agent were evaluated in three different ovarian xenograft tumor models. Results showed significant differences in EPR effects among the tumor models, with tumor growth influencing the calculated parameters of permeability (Ktrans) and retention (Ve) based on Tofts pharmacokinetic (PK) modeling. Our data indicate that the developed quantitative DCE-MRI method, combined with the Tofts PK modeling, provides a robust and non-invasive approach to screen tumors for their responsiveness to nanotherapeutics. These results imply that the developed qMRI method can be beneficial for personalized cancer treatments by ensuring that nanotherapeutics are administered only to patients with tumors showing sufficient EPR levels.

Scanning ultrasound-mediated memory and functional improvements do not require amyloid-β reduction.

A prevalent view in treating age-dependent disorders including Alzheimer's disease (AD) is that the underlying amyloid plaque pathology must be targeted for cognitive improvements. In contrast, we report here that repeated scanning ultrasound (SUS) treatment at 1 MHz frequency can ameliorate memory deficits in the APP23 mouse model of AD without reducing amyloid-β (Aβ) burden. Different from previous studies that had shown Aβ clearance as a consequence of blood-brain barrier (BBB) opening, here, the BBB was not opened as no microbubbles were used. Quantitative SWATH proteomics and functional magnetic resonance imaging revealed that ultrasound induced long-lasting functional changes that correlate with the improvement in memory. Intriguingly, the treatment was more effective at a higher frequency (1 MHz) than at a frequency within the range currently explored in clinical trials in AD patients (286 kHz). Together, our data suggest frequency-dependent bio-effects of ultrasound and a dissociation of cognitive improvement and Aβ clearance, with important implications for the design of trials for AD therapies.

CO2 cerebrovascular reactivity measured with CBF-MRI in older individuals: Association with cognition, physical function, amyloid and tau proteins

Vascular pathology is the second leading cause of cognitive impairment and represents a major contributing factor in mixed dementia. However, biomarkers for vascular cognitive impairment and dementia (VCID) are under-developed. Here we aimed to investigate the potential role of CO2 Cerebrovascular Reactivity (CVR) measured with phase-contrast quantitative flow MRI in cognitive impairment and dementia. Forty-five (69 ± 7 years) impaired (37 mild-cognitive-impairment and 8 mild-dementia by syndromic diagnosis) and 22 cognitively-healthy-control (HC) participants were recruited and scanned on a 3 T MRI. Biomarkers of AD pathology were measured in cerebrospinal fluid. We found that CBF-CVR was lower (p = 0.027) in the impaired (mean±SE, 3.70 ± 0.15%/mmHg) relative to HC (4.28 ± 0.21%/mmHg). After adjusting for AD pathological markers (Aβ42/40, total tau, and Aβ42/p-tau181), higher CBF-CVR was associated with better cognitive performance, including Montreal Cognitive Assessment, MoCA (p = 0.001), composite cognitive score (p = 0.047), and language (p = 0.004). Higher CBF-CVR was also associated with better physical function, including gait-speed (p = 0.006) and time for five chair-stands (p = 0.049). CBF-CVR was additionally related to the Clinical-Dementia-Rating, CDR, including global CDR (p = 0.026) and CDR Sum-of-Boxes (p = 0.015). CBF-CVR was inversely associated with hemoglobin A1C level (p = 0.017). In summary, CBF-CVR measured with phase-contrast MRI shows associations with cognitive performance, physical function, and disease-severity, independent of AD pathological markers.

Tendon evaluation with ultrashort echo time (UTE) MRI: a systematic review

Tendon disease ranks among the leading reasons patients consult their general practitioners, comprising approximately one-third of musculoskeletal appointments. Magnetic resonance imaging (MRI) is regarded as the gold standard for assessing tendons. Due to their short transverse relaxation time (T2), Tendons show up as a signal void in conventional MRI scans, which employ sequences with echo times (TEs) around several milliseconds. Ultrashort echo time (UTE) sequences utilize TEs that are 100–1,000 times shorter than those used in conventional sequences. This enables the direct visualization of tendons and assessment of their relaxation times, which is the basis for quantitative MRI. A systematic review was conducted on publications after 1990 in Google Scholar and PubMed databases. The search terms “ultrashort echo time,” “tendon,” and “UTE” were used to identify studies related to this investigation. This review discussed the current knowledge in quantitative UTE-MRI imaging of tendons. Quantitative UTE-T1, UTE-T2*, UTE-MT, and UTE-T1ρ techniques were described, and their reported applications in the literature were summarized in this review. We also discussed the advantages and challenges of these techniques and how these quantitative biomarkers may change in response to tendon pathology.

Machine learning models based on quantitative dynamic contrast-enhanced MRI parameters assess the expression levels of CD3+, CD4+, and CD8+ tumor-infiltrating lymphocytes in advanced gastric carcinoma.

To explore the effectiveness of machine learning classifiers based on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in predicting the expression levels of CD3+, CD4+, and CD8+ tumor-infiltrating lymphocytes (TILs) in patients with advanced gastric cancer (AGC). This study investigated 103 patients with confirmed AGC through DCE-MRI and immunohistochemical staining. Immunohistochemical staining was used to evaluate CD3+, CD4+, and CD8+ T-cell expression. Utilizing Omni Kinetics software, radiomics features (Ktrans, Kep, and Ve) were extracted and underwent selection via variance threshold, SelectKBest, and LASSO methods. Logistic regression (LR), support vector machine (SVM), random forest (RF), and eXtreme Gradient Boosting (XGBoost) are the four classifiers used to build four machine learning (ML) models, and their performance was evaluated using 10-fold cross-validation. The model's performance was evaluated and compared using the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity, positive predictive value, and negative predictive value. In terms of CD3+, CD4+, and CD8+ T lymphocyte prediction models, the random forest model outperformed the other classifier models in terms of CD4+ and CD8+ T cell prediction, with AUCs of 0.913 and 0.970 on the training set and 0.904 and 0.908 on the validation set, respectively. In terms of CD3+ T cell prediction, the logistic regression model fared the best, with AUCs on the training and validation sets of 0.872 and 0.817, respectively. Machine learning classifiers based on DCE-MRI have the potential to accurately predict CD3+, CD4+, and CD8+ tumor-infiltrating lymphocyte expression levels in patients with AGC.

Quantitative Characterization of Respiratory Patterns on Dynamic Higher Temporal Resolution MRI to Stratify Postacute Covid-19 Patients by Cardiopulmonary Symptom Burden.

Postacute Covid-19 patients commonly present with respiratory symptoms; however, a noninvasive imaging method for quantitative characterization of respiratory patterns is lacking. To evaluate if quantitative characterization of respiratory pattern on free-breathing higher temporal resolution MRI stratifies patients by cardiopulmonary symptom burden. Prospective analysis of retrospectively acquired data. A total of 37 postacute Covid-19 patients (25 male; median [interquartile range (IQR)] age: 58 [42-64] years; median [IQR] days from acute infection: 335 [186-449]). 0.55 T/two-dimensional coronal true fast imaging with steady-state free precession (trueFISP) at higher temporal resolution. Patients were stratified into three groups based on presence of no (N = 11), 1 (N = 14), or ≥2 (N = 14) cardiopulmonary symptoms, assessed using a standardized symptom inventory within 1 month of MRI. An automated lung postprocessing workflow segmented each lung in each trueFISP image (temporal resolution 0.2 seconds) and respiratory curves were generated. Quantitative parameters were derived including tidal lung area, rates of inspiration and expiration, lung area coefficient of variability (CV), and respiratory incoherence (departure from sinusoidal pattern) were. Pulmonary function tests were recorded if within 1 month of MRI. Qualitative assessment of respiratory pattern and lung opacity was performed by three independent readers with 6, 9, and 23 years of experience. Analysis of variance to assess differences in demographic, clinical, and quantitative MRI parameters among groups; univariable analysis and multinomial logistic regression modeling to determine features predictive of patient symptom status; Akaike information criterion to compare the quality of regression models; Cohen and Fleiss kappa (κ) to quantify inter-reader reliability. Two-sided 5% significance level was used. Tidal area and lung area CV were significantly higher in patients with two or more symptoms than in those with one or no symptoms (area: 15.4 cm2 vs. 12.9 cm2 vs. 12.8 cm2 ; CV: 0.072, 0.067, and 0.058). Respiratory incoherence was significantly higher in patients with two or more symptoms than in those with one or no symptoms (0.05 vs. 0.043 vs. 0.033). There were no significant differences in patient age (P = 0.19), sex (P = 0.88), lung opacity severity (P = 0.48), or pulmonary function tests (P = 0.35-0.97) among groups. Qualitative reader assessment did not distinguish between groups and showed slight inter-reader agreement (κ = 0.05-0.11). Quantitative respiratory pattern measures derived from dynamic higher-temporal resolution MRI have potential to stratify patients by symptom burden in a postacute Covid-19 cohort. 3 TECHNICAL EFFICACY: Stage 3.

Magnetic Resonance Imaging in Breast Cancer Tissue In Vitro after PDT Therapy.

Photodynamic therapy (PDT) is increasingly used in modern medicine. It has found application in the treatment of breast cancer. The most common cancer among women is breast cancer. We collected cancer cells from the breast from the material received after surgery. We focused on tumors that were larger than 10 mm in size. Breast cancer tissues for this quantitative non-contrast magnetic resonance imaging (MRI) study could be seen macroscopically. The current study aimed to present findings on quantitative non-contrast MRI of breast cancer cells post-PDT through the evaluation of relaxation times. The aim of this work was to use and optimize a 1.5 T MRI system. MRI tests were performed using a clinical scanner, namely the OPTIMA MR360 manufactured by General Electric HealthCare. The work included analysis of T1 and T2 relaxation times. This analysis was performed using the MATLAB package (produced by MathWorks). The created application is based on medical MRI images saved in the DICOM3.0 standard. T1 and T2 measurements were subjected to the Shapiro-Wilk test, which showed that both samples belonged to a normal distribution, so a parametric t-test for dependent samples was used to test for between-sample variability. The study included 30 sections tested in 2 stages, with consistent technical parameters. For T1 measurements, 12 scans were performed with varying repetition times (TR) and a constant echo time (TE) of 3 ms. For T2 measurements, 12 scans were performed with a fixed repetition time of 10,000 ms and varying echo times. After treating samples with PpIX disodium salt and bubbling with pure oxygen, PDT irradiation was applied. The cell relaxation time after therapy was significantly shorter than the cell relaxation time before PDT. The cells were exposed to PpIX disodium salt as the administered pharmacological substance. The study showed that the therapy significantly affected tumor cells, which was confirmed by a significant reduction in tumor cell relaxation time on the MRI results.

Study of the possibilities of non-invasive assessment of increased intracranial pressure according to MRI data on the example of patients with secondary intracranial hypertension

Modern methods of neuroimaging make it possible to develop approaches for assessing intracranial pressure as a replacement for the “gold standard” of invasive monitoring. Aim of the study was to investigate the possibility of using magnetic resonance (MR) characteristics to assess the increase in intracranial pressure in patients with secondary intracranial hypertension. Material and methods. Group 1 – 40 patients with brain tumors, group 2 – 15 patients with communicating hydrocephalus, control group – 36 individuals. The patients underwent MRI with measurement and evaluation of the optic nerve sheath diameter (ONSD), the optochiasmal cistern and the pituitary gland vertical sizes, and tortuosity of the ON. Patients of the 2nd group underwent a phase-contrast MRI with an assessment of the velocity and volumetric characteristics of blood and cerebrospinal fluid flows with the calculation of the intracranial compliance index (ICC). Using the FreeSurfer program, the brain volumes were estimated. Results and discussion. A statistically significant increase in ONSD was found in the groups of patients compared with the control group (by 24 %, p &lt; 0.05), decrease in the vertical size of the pituitary gland and an increase in the vertical size of the optochiasmal cistern (p &lt; 0.05), as well as ICC lowering in group 2 (by 1.7 times, p &lt; 0.05). Tortuosity of ON in group 1 was observed more often than in other groups. A statistically significant positive correlation between ONSD and brain volumes in group 1 (r = 0.55, p &lt; 0.05) and a negative correlation between brain volumes and ICC in group 2 (r = –0.86, p &lt; 0.05) has been found. Conclusions. Based on the presented results, we believe that the combined use of qualitative and quantitative MRI criteria can expand the diagnostic capabilities of non-invasive assessment of increased intracranial pressure.

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

ObjectiveInflammatory 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.MethodsThis 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.ResultsThe 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.InterpretationAs 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.

Optimisation of quantitative brain diffusion-relaxation MRI acquisition protocols with physics-informed machine learning

Diffusion-relaxation MRI aims to extract quantitative measures that characterise microstructural tissue properties such as orientation, size, and shape, but long acquisition times are typically required. This work proposes a physics-informed learning framework to extract an optimal subset of diffusion-relaxation MRI measurements for enabling shorter acquisition times, predict non-measured signals, and estimate quantitative parameters.In vivo and synthetic brain 5D-Diffusion-T1-T2∗-weighted MRI data obtained from five healthy subjects were used for training and validation, and from a sixth participant for testing. One fully data-driven and two physics-informed machine learning methods were implemented and compared to two manual selection procedures and Cramér–Rao lower bound optimisation.The physics-informed approaches could identify measurement-subsets that yielded more consistently accurate parameter estimates in simulations than other approaches, with similar signal prediction error. Five-fold shorter protocols yielded error distributions of estimated quantitative parameters with very small effect sizes compared to estimates from the full protocol. Selected subsets commonly included a denser sampling of the shortest and longest inversion time, lowest echo time, and high b-value.The proposed framework combining machine learning and MRI physics offers a promising approach to develop shorter imaging protocols without compromising the quality of parameter estimates and signal predictions.

A rapid multi-parametric quantitative MR imaging method to assess Parkinson’s disease: a feasibility study

BackgroundMULTIPLEX is a single-scan three-dimensional multi-parametric MRI technique that provides 1 mm isotropic T1-, T2*-, proton density- and susceptibility-weighted images and the corresponding quantitative maps. This study aimed to investigate its feasibility of clinical application in Parkinson’s disease (PD).Methods27 PD patients and 23 healthy control (HC) were recruited and underwent a MULTIPLEX scanning. All image reconstruction and processing were automatically performed with in-house C + + programs on the Automatic Differentiation using Expression Template platform. According to the HybraPD atlas consisting of 12 human brain subcortical nuclei, the region-of-interest (ROI) based analysis was conducted to extract quantitative parameters, then identify PD-related abnormalities from the T1, T2* and proton density maps and quantitative susceptibility mapping (QSM), by comparing patients and HCs.ResultsThe ROI-based analysis revealed significantly decreased mean T1 values in substantia nigra pars compacta and habenular nuclei, mean T2* value in subthalamic nucleus and increased mean QSM value in subthalamic nucleus in PD patients, compared to HCs (all p values < 0.05 after FDR correction). The receiver operating characteristic analysis showed all these four quantitative parameters significantly contributed to PD diagnosis (all p values < 0.01 after FDR correction). Furthermore, the two quantitative parameters in subthalamic nucleus showed hemicerebral differences in regard to the clinically dominant side among PD patients.ConclusionsMULTIPLEX might be feasible for clinical application to assist in PD diagnosis and provide possible pathological information of PD patients’ subcortical nucleus and dopaminergic midbrain regions.

GPU-accelerated Bloch simulations and MR-STAT reconstructions using the Julia programming language.

MR-STAT is a relatively new multiparametric quantitative MRI technique in which quantitative paramater maps are obtained by solving a large-scale nonlinear optimization problem. Managing reconstruction times is one of the main challenges of MR-STAT. In this work we leverage GPU hardware to reduce MR-STAT reconstruction times. A highly optimized, GPU-compatible Bloch simulation toolbox is developed as part of this work that can be utilized for other quantitative MRI techniques as well. The Julia programming language was used to develop a flexible yet highly performant and GPU-compatible Bloch simulation toolbox called BlochSimulators.jl. The runtime performance of the toolbox is benchmarked against other Bloch simulation toolboxes. Furthermore, a (partially matrix-free) modification of a previously presented (matrix-free) MR-STAT reconstruction algorithm is proposed and implemented using the Julia language on GPU hardware. The proposed algorithm is combined with BlochSimulators.jl and the resulting MR-STAT reconstruction times on GPU hardware are compared to previously presented MR-STAT reconstruction times. The BlochSimulators.jl package demonstrates superior runtime performance on both CPU and GPU hardware when compared to other existing Bloch simulation toolboxes. The GPU-accelerated partially matrix-free MR-STAT reconstruction algorithm, which relies on BlochSimulators.jl, allows for reconstructions of 68 seconds per two-dimensional (2D slice). By combining the proposed Bloch simulation toolbox and the partially matrix-free reconstruction algorithm, 2D MR-STAT reconstructions can be performed in the order of one minute on a modern GPU card. The Bloch simulation toolbox can be utilized for other quantitative MRI techniques as well, for example for online dictionary generation for MR Fingerprinting.