3T MR Research Articles

7T magnetic resonance angiographic imaging of basilar artery perforator aneurysms - initial experience of a non-invasive alternative to DSA.

Perforator aneurysms of the basilar artery (PABA) are rare causes of subarachnoid haemorrhage (SAH) and challenging to diagnose. We present two cases of SAH caused by PABA diagnosed by cone beam computed tomography angiography (CBCTA) and a novel non-invasive method - 7T magnetic resonance imaging (7T MRI). Two patients with SAH, diagnosed with PABA, were imaged on day 9 and 13 after onset, respectively, with CBCTA and 7T MR angiography (MRA) performed on the day after and at follow-up at 3 months. All four 7T MRI examinations in the two patients were technically successful with fully diagnostic images. No endovascular treatment was performed and control with 7T MRA at 3 months showed no remaining aneurysms. PABA can be imaged with 7T MRI - a novel non-invasive method, allowing non-invasive follow-up to monitor this rare cause of SAH.

High-Field Magnetic Resonance Imaging of the Temporomandibular Joint Low Agreement with Clinical Diagnosis in Asymptomatic Females.

(1) Background: The aim of this study was to investigate the agreement between a clinical diagnosis based on research diagnostic criteria/temporomandibular disorders (RDC/TMD) and high-field magnetic resonance imaging (MRI) findings of temporomandibular joints (TMJs) in asymptomatic females. (2) Methods: A prospective study on 100 females (200 TMJs) was performed, using clinical examinations (RDC/TMD) and same-day MRIs of TMJs on a 3T MR unit. The inclusion criteria were as follows: females, age > 18, the presence of upper and lower incisors, and an understanding of the Serbian language. Descriptive statistics (means and standard deviations) and ANOVA with a post hoc Tukey test for differences among the patient subgroups was performed. The agreement between the clinical and MRI findings was determined using Cohen's kappa coefficient (k < 0.21 slight, 0.21-0.4 fair, 0.41-0.6 moderate, 0.61-0.8 substantial, and 0.81-1 almost perfect). The statistical significance was set at p ≤ 0.05. (3) Results: Normal findings were observed in 86.7%, disc dislocation (DD) was observed in 9.2%, and arthralgia/osteoarthritis/osteoarthrosis was observed in 2.6% of TMJs using RDC/TMD. On the MRI, normal findings were observed in 50.5%, disc dislocation was observed in 16.3%, and arthralgia/osteoarthritis/osteoarthrosis was observed in 23.5% of TMJs. The anterior DD with reduction showed fair agreement of the clinical and MRI findings (k = 0.240, p < 0.001) compared with the DD without reduction (k = 0.355, p < 0.001). Both showed high specificity (94.9% and 99.4%) but low sensitivity (24.2% and 25.0%). The sensitivity in osteoarthritic changes was low (4.8%), but the specificity remained high (96.2%). (4) Conclusions: The sensitivity of the clinical examination remains low compared with 3T MRI, especially in osteoarthritic changes and anterior DD with reduction. However, the number of false positive diagnoses using RDC/TMD is low in asymptomatic patients. RDC/TMD remains a sensible method for establishing a clinical diagnosis and avoiding the overtreatment of asymptomatic patients.

Changes of basal forebrain volume along the Alzheimer’s disease continuum in Down syndrome

AbstractBackgroundAtrophy of basal forebrain (BF) cholinergic neurons is an early event in Alzheimer’s disease (AD) and is associated with cognitive impairment. Down syndrome (DS) is now recognized as a genetically determined form of AD. Therefore, people with DS represent a priority population to study biomarkers of AD pathology and neurodegeneration. Degeneration of BF neurons occurs both in sporadic AD and in DS brains with advanced AD pathology. However, the dynamics of BF atrophy and its changes with age and AT(N) biomarkers have not been studied in DS.MethodWe included 246 adults with DS (mean age 43.2 ±11.0 years; 43% female). Volumes of antero‐medial and posterior areas of the BF (amBF and pBF, respectively) were extracted from T1‐weighted 3T MR images using voxel‐based morphometry in SPM12 in combination with a stereotactic atlas of BF functional subdivisions (Figure 1). Differences in amBF and pBF volume in each AD clinical stage (Asymptomatic, Prodromal and Demented) were assessed with Kruskall‐Wallis and pairwise Wilcoxon tests. The relationship of BF volumes with age and AT(N) biomarkers in the cerebrospinal fluid (CSF) (amyloid‐β 42/40 ratio [aβ ratio], phosphorylated Tau 181 [pTau], total Tau [tTau] and neurofilament light [NFL]) was assessed in a subset of subjects (n = 161 [aβ ratio, pTau and tTau] and n = 95 [NFL]) with locally estimated scatterplot smoothing (LOESS) and linear regression in R, respectively.ResultVolumes of amBF and pBF decreased significantly with age (Figure 2), with a steeper decline during the fifth decade of life. BF volumes also declined with AD clinical stage (Figure 3), and had significant correlations with CSF aβ ratio (p&lt;0.001 r2 = 0.22), pTau (p&lt;0.001 r2 = 0.20), tTau (p&lt;0.001 r2 = 0.20) and NFL (p&lt;0.001 r2 = 0.33) (Figure 4).ConclusionIn DS, BF volume decreases with age, AT(N) biomarkers and along the cognitive stages of the AD continuum.

Characterization of pre-malignant lesions in patients with pediatric neurofibromatosis type 1 using a novel whole-body magnetic resonance imaging technique.

TPS10637 Background: Neurofibromatosis Type 1 (NF-1) patients can develop benign tumors, plexiform neuromas (PN), that may transform into malignant peripheral nerve sheath tumors (MPNST)(Tucker, et al. 2009). MPNST are rare; but in NF1, the lifetime incidence is 8-13% and MPSTs present at younger ages(Miettinen, et al. 2017). MPNST are aggressive tumors requiring full resection for best outcomes (Mautner, et al. 2008). Emerging data suggests whole-body MRI (WB-MRI) can identify NF patients with higher PN tumor burden and maybe at risk of developing MPNST. We have created a rapid, motion-robust quantitative WB-MRI technique that is likely suitable for pediatric patients. High-resolution multiparametric tissue mapping, including T1, T2, and ADC (apparent diffusion coefficient), are acquired concurrently in a single scan, as shown in prior studies (Christodoulou, et al. 2018, Ma, et al. 2020, Nguyen, et al. 2016, Wang, et al. 2020). This project will evaluate the feasibility and reproducibility of novel WB-MRI for the characterization of pre-malignant lesions in NF-1 patients. Methods: Trial Design: Pilot study of novel WB-MRI technique in pediatric NF-1 patients with a goal of 15 patients between the ages of 5-17 years. Trial MRI scans are performed at baseline, 1 month, and then 12 months (+/-3 months). A clinical 3T MR scanner (Siemens MAGNETOM Vida) performs a head-to-knee WB-MRI in 70 minutes. Signal-to-noise ratio (SNR) and imaging quality scores will be evaluated. The lesion volume and mean T1/T2/ADC are measured for each lesion on the corresponding quantitative maps based on manual ROI’s (regions of interest). To assess scan-rescan reproducibility, image quality metrics (SNR and quality score), lesion identification, and lesion characteristics (T1, T2, and ADC) will be compared between the baseline and the 1-month scan using a Bland-Altman analysis and Schuirman’s equivalence. The coefficient of variation (CV = 100 [SD/mean] %) values for each of the quantitative values will be calculated. To evaluate for lesion characterization, changes in the mean in each MRI quantitative metrics (T1, T2, and ADC) will be measured for each lesion on the baseline and 12-month visit. Spaghetti plots will be used to visualize the change over time, and the difference in mean will be tested using an appropriate parametric or nonparametric test depending on the results of tests on normality and homoscedasticity. Intervention: WB-MRI at baseline, 1 month, and 12 months (+/-3 months) Eligibility: 5 to 17 years old not requiring sedation; Clinically or molecularly diagnosed NF-1 including mosaic/segmental subjects; Not Eligible: allergy to animal dander, animal-instigated asthma, pregnant, breastfeeding, or have intrauterine device; Current Enrollment (February 2023): 5 subjects (One unable to finish a non-sedated MRI). Clinical trial information: NCT04763109 .

Vascular disease risk factors in multiple sclerosis: Effect on metabolism and brain volumes.

Vascular disease risk factors (VDRF) such as hypertension, hyperlipidemia, obesity, diabetes and heart disease likely play a role in disease progression in people with multiple sclerosis (PwMS) (Marrie, Rudick etal. 2010). Studies exploring the mechanistic connection between vascular disease and MS disease progression are scant. We hypothesized that phosphate energy metabolism impairment in PwMS with VDRFs (VDRF+) will be greater compared to PwMS without VDRFs (VDRF-) and is related to increased brain atrophy in VDRF+. To test this hypothesis, we planned to study the differences in the high energy phosphate (HEP) metabolites in cerebral gray matter as assessed by 31P magnetic resonance spectroscopic imaging (MRSI) and MRI brain volumetric in the VDRF+ and VDRF- PwMS at four different timepoints over a 3 yearlong period using a 7T MR system. We present here the results from the cross-sectional evaluation of HEP metabolites and brain volumes. We also evaluated the differences in clinical impairment, blood metabolic biomarkers and quality of life in VDRF+ and VDRF- PwMS in this cohort. Group differences in high energy phosphate metabolites were assessed from a volume of interest in the occipital region using linear mixed models. Brain parenchymal and white matter lesion volumes were determined from MR anatomic images. We present here the cross-sectional analysis of the baseline data collected as part of a longitudinal 3 yearlong study where we obtained baseline and subsequent 6-monthly clinical and laboratory data and annual 7T MRI volumetric and 31P MR spectroscopic imaging (MRSI) data on 52 PwMS with and without VDRF. Key clinical and laboratory outcomes included: body mass index (BMI), waist and thigh circumferences and disability [Expanded Disability Status Scale (EDSS)], safety (complete blood count with differential, complete metabolic), lipid panel including total cholesterol and HbA1C. We analyzed clinical and laboratory data for the group differences using student's t or χ2 test. We investigated relationship between phosphate metabolites and VDRF using mixed effect linear regression. Complete MRI data were available for 29 VDRF+, age 56.3 (6.8) years [mean (SD)] (83% female), and 23 VDRF-, age 52.5 (7.5) years (57% female) individuals with MS. The mean value of normalized adenosine triphosphate (ATP) (calculated as the ratio of ATP to total phosphate signal in a voxel) was decreased by 4.5% (p < .05) in VDRF+ compared to VDRF- MS group. White matter lesion (WML) volume fraction in VDRF+ individuals {0.007 (0.007)} was more than doubled compared to VDRF- participants {0.003 (0.006), p= .02}. We found significantly lower brain ATP and higher inorganic phosphate (Pi) in those PwMS with VDRFs compared to those without. ATP depletion may reflect mitochondrial dysfunction. Ongoing longitudinal data analysis from this study, not presented here, will evaluate the relationship of phosphate metabolites, brain atrophy and disease progression in PwMS with and without vascular disease.

Comparison of the metabolic profile of a healthy brain on two VIDA Siemens 3T MR tomographs

Comparison of the metabolic profile of a healthy brain on two VIDA Siemens 3T MR tomographs

Cortical thickness is related to cognitive-motor automaticity and attention allocation in individuals with Alzheimer’s disease: a regions of interest study

Alzheimer's disease (AD) is characterized by a distinct pattern of cortical thinning and resultant changes in cognition and function. These result in prominent deficits in cognitive-motor automaticity. The relationship between AD-related cortical thinning and decreased automaticity is not well-understood. We aimed to investigate the relationship between cortical thickness regions-of-interest (ROI) and automaticity and attention allocation in AD using hypothesis-driven and exploratory approaches. We performed an ROI analysis of 46 patients with AD. Data regarding MR images, demographic characteristics, cognitive-motor dual task performance, and cognition were extracted from medical records. Cortical thickness was calculated from MR T1 images using FreeSurfer. Data from the dual task assessment was used to calculate the combined dual task effect (cDTE), a measure of cognitive-motor automaticity, and the modified attention allocation index (mAAI). Four hierarchical multiple linear regression models were conducted regressing cDTE and mAAI separately on (1) hypothesis-generated ROIs and (2) exploratory ROIs. For cDTE, cortical thicknesses explained 20.5% (p = 0.014) and 25.9% (p = 0.002) variability in automaticity in the hypothesized ROI and exploratory models, respectively. The dorsal lateral prefrontal cortex (DLPFC) (β = - 0.479, p = 0.018) and superior parietal cortex (SPC) (β = 0.467, p = 0.003), and were predictors of automaticity. For mAAI, cortical thicknesses explained 20.7% (p = 0.025) and 28.3% (p = 0.003) variability in attention allocation in the hypothesized ROI and exploratory models, respectively. Thinning of SPC and fusiform gyrus were associated with motor prioritization (β = - 0.405, p = 0.013 and β = - 0.632, p = 0.004, respectively), whereas thinning of the DLPFC was associated with cognitive prioritization (β = 0.523, p = 0.022). Cortical thinning in AD was related to cognitive-motor automaticity and task prioritization, particularly in the DLPFC and SPC. This suggests that these regions may play a primary role in automaticity and attentional strategy during dual-tasking.

Study of compatibility between a 3T MR system and detector modules for a second-generation RF-penetrable TOF-PET insert for simultaneous PET/MRI.

Simultaneous positron emission tomography/magnetic resonance imaging (PET/MRI) has shown promise in acquiring complementary multiparametric information of disease. However, designing these hybrid imaging systems is challenging due to the propensity for mutual interference between the PET and MRI subsystems. Currently, there are integrated PET/MRI systems for clinical applications. For neurologic imaging, a brain-dedicated PET insert provides superior spatial resolution and sensitivity compared to body PETscanners. Our first-generation prototype brain PET insert ("PETcoil") demonstrated RF-penetrability and MR-compatibility. In the second-generation PETcoil system, all analog silicon photomultiplier (SiPM) signal digitization is moved inside the detectors, which results in substantially better PET detector performance, but presents a greater technical challenge for achieving MR-compatibility. In this paper, we report results from MR-compatibility studies of two fully assembled second-generation PET insert detectormodules. We studied the effect of the presence of the two second-generation TOF-PET insert detectors on parameters that affect MR image quality and evaluated TOF-PET detector performance under different MRI pulse sequenceconditions. With the presence of operating PET detectors, no RF noise peaks were induced in the MR images, but the relative average noise level was increased by 15%, which led to a 3.1 to 4.2-dB degradation in MR image signal-to-noise ratio (SNR). The relative homogeneity of MR images degraded by less than 1.5% with the two operating TOF-PET detectors present. The reported results also indicated that ghosting artifacts (percent signal ghosting (PSG) ⩽ 1%) and MR susceptibility artifacts (0.044 ppm) were insignificant. The PET detector data showed a relative change of less than 5% in detector module performance between running outside and within the MR bore under different MRI pulse sequences except for energy resolution in EPI sequence (13% relative difference). The PET detector operation did not cause any significant artifacts in MR images and the performance and time-of-flight (TOF) capability of the former were preserved under different tested MRconditions.

Quantitative MR Neurography in Multifocal Motor Neuropathy and Amyotrophic Lateral Sclerosis

The aim of this study was to assess the phenotype of multifocal motor neuropathy (MMN) and amyotrophic lateral sclerosis (ALS) in quantitative MR neurography. In this prospective study, 22 patients with ALS, 8 patients with MMN, and 10 healthy volunteers were examined with 3T MR neurography, using a high-resolution fat-saturated T2-weighted sequence, diffusion-tensor imaging (DTI), and a multi-echo T2-relaxometry sequence. The quantitative biomarkers fractional anisotropy (FA), radial and axial diffusivity (RD, AD), mean diffusivity (MD), cross-sectional area (CSA), T2-relaxation time, and proton spin density (PSD) were measured in the tibial nerve at the thigh and calf, and in the median, radial, and ulnar nerves at the mid-upper arm. MMN showed a characteristic imaging pattern of decreased FA (p = 0.018), increased RD (p = 0.014), increased CSA (p < 0.001), increased T2-relaxation time (p < 0.001), and increased PSD (p = 0.025) in the upper arm nerves compared to ALS and controls. ALS patients did not differ from controls in any imaging marker, nor were there any group differences in the tibial nerve (p > 0.05). MMN shows a characteristic pattern of quantitative DTI and T2-relaxometry parameters in the upper-arm nerves, primarily indicating demyelination. Peripheral nerve changes in ALS seem to be below the detection level of current state-of-the-art quantitative MR neurography.

Magnetic Resonance Imaging in Traumatic Brachial Plexus Injuries: A 6-Year Experience.

Background and Purpose: There is limited information in the literature on epidemiology of high-energy brachial plexus injuries evaluated with MR neurography (MRN). The aim of the present study is to describe the demographic characteristics of brachial plexus injuries secondary to motorcycle accident patients in the city of Fortaleza-Ceara, Brazil, and analyze the association of those data with the features of the brachial plexus lesions observed on MRN findings. Materials and Methods: A review of sixty medical charts and MRN findings of victims of motor vehicle accidents (MVA) in northeast, from November 2011 to November 2017. Demographic and imaging data collected included age, sex, laterality and level of the lesion and time interval between trauma and MRN examination. The MRN examinations were carried out on a GE 1.5T MR unit (Signa HDxT- General Electric, Milwaukee, USA) or on a Phillips 3T MR unit (Philips Achieva X-series - Philips Medical Systems, Best, The Netherlands). Dedicated multichannel phased-array coils. Results: The longest time interval from trauma to imaging was 330 days and between trauma and surgery was 692 days. Preganglionic lesions (avulsion) predominated, consisting of 52 patients (86.6%) reflecting the high energy trauma with upper limb traction from the neck. The lesions were most prevalent at the C6-C8 levels. Pseudomeningocele was identified in 62.9% of the preganglionic lesions and in only 1.6% of the postganglionic lesions. Regional muscle denervation changes were seen in all pre-ganglionic injuries and most of post-ganglionic injuries. Conclusions: MRN of the brachial plexus provides important insights into the distribution of neuromuscular lesions in high energy MVA trauma and these findings enrich the literature for researchers and clinicians focused on managing such patients and/or defining prognostic strategies.

Volumetric assessment of individual thalamic nuclei in patients with drug-naïve, first-episode major depressive disorder.

Despite the previous inconsistent findings of structural and functional abnormalities of the thalamus in patients with major depressive disorder (MDD), the disruption of the thalamic nuclei in the pathophysiology of this disorder has not yet been adequately studied. Therefore, we investigated the volumetric changes of thalamic subregions and their nuclei in drug-naïve, first-episode MDD patients. We also investigated the association between HAM-D scores, a clinical scale frequently used to evaluate the severity of depression and thalamic nuclei volumes in MDD patients. This study included 76 drug-naïve MDD patients and an equal number of healthy subjects. Magnetic resonance imaging (MRI) data were obtained using a 3T MR system and thalamic nuclei volumes were evaluated using FreeSurfer ver.7.11. The volumetric differences were compared by one-way analysis of covariance (ANCOVA) and to ensure that effects were not accounted for by other factors, age, sex, and ETICV variables were included as covariates. We observed significant volume reductions of the left whole thalamus (p < 0.003) and several thalamic nuclei mostly on the left side in the MDD group compared with healthy controls (HCs). Furthermore, we have revealed weak negative correlations between several thalamic nuclei volumes and HAM-D total and subscale scores. This is the first research study to investigate alterations of the various thalamic nuclei volumes in MDD patients compared with HCs. Moreover, we first analyzed the association between individual thalamic nuclei volumes and HAM-D subscale scores. Though our study may be restricted at certain levels, especially by the demographic difference between the two groups, they possibly contribute at a preliminary level to understanding the thalamic structural changes at its subregions in patients with drug-naïve, first-episode MDD.

Phenotyping Superagers Using Resting-State fMRI.

Superagers are defined as older adults with episodic memory performance similar or superior to that in middle-aged adults. This study aimed to investigate the key differences in discriminative networks and their main nodes between superagers and cognitively average elderly controls. In addition, we sought to explore differences in sensitivity in detecting these functional activities across the networks at 3T and 7T MR imaging fields. Fifty-five subjects 80 years of age or older were screened using a detailed neuropsychological protocol, and 31 participants, comprising 14 superagers and 17 cognitively average elderly controls, were included for analysis. Participants underwent resting-state-fMRI at 3T and 7T MR imaging. A prediction classification algorithm using a penalized regression model on the measurements of the network was used to calculate the probabilities of a healthy older adult being a superager. Additionally, ORs quantified the influence of each node across preselected networks. The key networks that differentiated superagers and elderly controls were the default mode, salience, and language networks. The most discriminative nodes (ORs > 1) in superagers encompassed areas in the precuneus posterior cingulate cortex, prefrontal cortex, temporoparietal junction, temporal pole, extrastriate superior cortex, and insula. The prediction classification model for being a superager showed better performance using the 7T compared with 3T resting-state-fMRI data set. Our findings suggest that the functional connectivity in the default mode, salience, and language networks can provide potential imaging biomarkers for predicting superagers. The 7T field holds promise for the most appropriate study setting to accurately detect the functional connectivity patterns in superagers.

Effects of fitting methods, high b-values and image quality on diffusion and perfusion quantification and reproducibility in the calf

PurposesThe study aimed to optimize diffusion-weighted imaging (DWI) image acquisition and analysis protocols in calf muscles by investigating the effects of different model-fitting methods, image quality, and use of high b-value and constraints on parameters of interest (POIs). The optimized modeling methods were used to select the optimal combinations of b-values, which will allow shorter acquisition time while achieving the same reliability as that obtained using 16 b-values. MethodsTest-retest baseline and high-quality DWI images of ten healthy volunteers were acquired on a 3T MR scanner, using 16 b-values, including a high b-value of 1200 s/mm2, and structural T1-weighted images for calf muscle delineation. Three and six different fitting methods were used to derive ADC from monoexponential (ME) model and Dd, fp, and Dp from intravoxel incoherent motion (IVIM) model, with or without the high b-value. The optimized ME and IVIM models were then used to determine the optimal combinations of b-values, obtainable with the least number of b-values, using the selection criteria of coefficient of variance (CV) ≤10% for all POIs. ResultsThe find minimum multivariate algorithm was more flexible and yielded smaller fitting errors. The 2-steps fitting method, with fixed Dd, performed the best for IVIM model. The inclusion of high b-value reduced outliers, while constraints improved 2-steps fitting only. ConclusionsThe optimal numbers of b-values for ME and IVIM models were nine and six b-values respectively. Test-retest reliability analyses showed that only ADC and Dd were reliable for calf diffusion evaluation, with CVs of 7.22% and 4.09%.

NEC-NET : Segmentation and Feature Extraction Network for the Neurocranium in Early Childhood.

In early life, the neurocranium undergoes rapid changes to accommodate the expanding brain. Neurocranial maturation can be disrupted by developmental abnormalities and environmental factors such as sleep position. To establish a baseline for the early detection of anomalies, it is important to understand how this structure typically grows in healthy children. Here, we designed a deep neural network pipeline NEC-NET, including segmentation and classification, to analyze the normative development of the neurocranium in T1 MR images from healthy children aged 12 to 60 months old. The pipeline optimizes the segmentation of the neurocranium and shows the preliminary results of age-based regional differences among infants.

Automatic Detection of Increased Signal Intensity from T2-Weighted Magnetic Resonance Images (MRIs) of Cervical Vertebra

Automatic detection of increased signal intensity (ISI) in spinal cord from T2-weighted magnetic resonance images (MRIs) of the cervical vertebra was design. To diagnose the conditions of spinal cord automatically and aid doctors in treating patients with cervical degenerative diseases. 724 MR T2 images were annotated by two doctors with ISI information and 245 MR T2 ones with the mask of cervical discs and spinal cord. The proposed approach contains three modules: (1) a module named region proposal to generate the ISI proposals. This module is based on three submodules: (a) a Mask R-CNN model to segment the cervical disc and spinal cord, (b) a rule-based algorithm for verifying the segmentation result, (c) an algorithm for getting the segment of spinal cord according to the verified segmentation result; (2) a feature extraction method based on Laplace operator to extract the feature of segments of spinal cord; (3) a classifier based on Linear Discriminant Analysis to classify the segments of spinal cord. Our ISI detection method achieved 31.9 AP in the test. And while using Fβ score (β = 1.3) the method got 85.4% recall and 2.16 FP per image. In this study, we proposed an approach based on Mask R-CNN to detect ISI on MR T2 images automatically and achieved good performance both in accuracy and speed.

Non-destructive classification of unlabeled cells: Combining an automated benchtop magnetic resonance scanner and artificial intelligence.

In order to treat degenerative diseases, the importance of advanced therapy medicinal products has increased in recent years. The newly developed treatment strategies require a rethinking of the appropriate analytical methods. Current standards are missing the complete and sterile analysis of the product of interest to make the drug manufacturing effort worthwhile. They only consider partial areas of the sample or product while also irreversibly damaging the investigated specimen. Two-dimensional T1 / T2 MR relaxometry meets these requirements and is therefore a promising in-process control during the manufacturing and classification process of cell-based treatments. In this study a tabletop MR scanner was used to perform two-dimensional MR relaxometry. Throughput was increased by developing an automation platform based on a low-cost robotic arm, resulting in the acquisition of a large dataset of cell-based measurements. Two-dimensional inverse Laplace transformation was used for post-processing, followed by data classification performed with support vector machines (SVM) as well as optimized artificial neural networks (ANN). The trained networks were able to distinguish non-differentiated from differentiated MSCs with a prediction accuracy of 85%. To increase versatility, an ANN was trained on 354 independent, biological replicates distributed across ten different cell lines, resulting in a prediction accuracy of up to 98% depending on data composition. The present study provides a proof of principle for the application of T1 / T2 relaxometry as a non-destructive cell classification method. It does not require labeling of cells and can perform whole mount analysis of each sample. Since all measurements can be performed under sterile conditions, it can be used as an in-process control for cellular differentiation. This distinguishes it from other characterization techniques, as most are destructive or require some type of cell labeling. These advantages highlight the technique's potential for preclinical screening of patient-specific cell-based transplants and drugs.

Downsizing of rectal cancer following neoadjuvant radiotherapy (5 × 5 Gy) and long interval surgery evaluated using MRI semiautomated volumetric measurements, a retrospective study.

Neoadjuvant conventional chemoradiation (CRT) is the standard treatment for primary locally non-curatively resectable rectal cancer, as tumor downsizing may allow R0 resectability. Short-term neoadjuvant radiotherapy (5x5 Gy) followed by an interval before surgery (SRT- delay) is an alternative for multimorbid patients who cannot tolerate CRT. This study examined the extent of tumor downsizing achieved with the SRT-delay approach in a limited cohort that underwent complete re-staging before surgery. Between March 2018 and July 2021, 26 patients with locally advanced primary adenocarcinoma (>uT3 or/and N+) of the rectum were treated with SRT-delay. 22 patients underwent initial staging and complete re-staging (CT, endoscopy, MRI). Tumor downsizing was assessed by staging and re-staging data and pathologic findings. Semiautomated measurement of tumor volume was performed using mint Lesion™ 1.8 software to evaluate tumor regression. The mean tumor diameter determined on sagittal T2 MRI images decreased significantly from 54.1 (23-78) mm at initial staging to 37.9 (18-65) mm at re-staging before surgery (p <0.001) and to 25.5 (7-58) mm at pathologic examination (p <0.001). This corresponds to a mean reduction in tumor diameter of 28.9 (4.3-60.7) % at re-staging and 51.1 (8.7-86.5) % at pathology. Mean tumor volume determined from transverse T2 MR images mint LesionTM 1.8 software significantly decreased from 27.5 (9.8 - 89.6) cm3 at initial staging to 13.1 (3.7 - 32.8) cm3 at re-staging (p <0.001), corresponding to a mean reduction of 50.8 (21.6 - 77) %. The frequency of positive circumferential resection margin (CRM) (less than 1mm) decreased from 45,5 % (10 patients) at initial staging to 18,2 % (4 patients) at re-staging. On pathologic examination, the CRM was negative in all cases. However, multivisceral resection for T4 tumors was required in 2 patients (9%). Tumor downstaging was noted in 15 of 22 patients after SRT-delay. In conclusion, the observed extent of downsizing is broadly comparable to the results of CRT, making SRT-delay a serious alternative for patients who cannot tolerate chemotherapy.

Characterization of visual processing in temporomandibular disorders using functional magnetic resonance imaging.

Many patients with chronic pain report hypersensitivity not only to noxious stimuli, but also to other modalities including innocuous touch, sound, and light, possibly due to differences in the processing of these stimuli. The goal of this study was to characterize functional connectivity (FC) differences between subjects with temporomandibular disorders (TMD) and pain-free controls during a visual functional magnetic resonance imaging (fMRI) task that included an unpleasant, strobing visual stimulus. We hypothesized the TMD cohort would exhibit maladaptations in brain networks consistent with multisensory hypersensitivities observed in TMD patients. This pilot study included 16 subjects, 10 with TMD and 6 pain-free controls. Clinical pain was characterized using self-reported questionnaires. Visual task-based fMRI data were collected on a 3T MR scanner and used to determine differences in FC via group independent component analysis. Compared to controls, subjects with TMD exhibited abnormally increased FC between the default mode network and lateral prefrontal areas involved in attention and executive function, and impaired FC between the frontoparietal network and higher order visual processing areas. The results indicate maladaptation of brain functional networks, likely due to deficits in multisensory integration, default mode network function, and visual attentionandengendered by chronic pain mechanisms.

Compensation cycle consistent generative adversarial networks (Comp-GAN) for synthetic CT generation from MR scans with truncated anatomy.

MR scans used in radiotherapy can be partially truncated due to the limited field of view (FOV), affecting dose calculation accuracy in MR-based radiation treatment planning. We proposed a novel Compensation-cycleGAN (Comp-cycleGAN) by modifying the cycle-consistent generative adversarial network (cycleGAN), to simultaneously create synthetic CT (sCT) images and compensate the missing anatomy from the truncated MR images. Computed tomography (CT) and T1 MR images with complete anatomy of 79 head-and-neck patients were used for this study. The original MR images were manually cropped 10-25mm off at the posterior head to simulate clinically truncated MR images. Fifteen patients were randomly chosen for testing and the rest of the patients were used for model training and validation. Both the truncated and original MR images were used in the Comp-cycleGAN training stage, which enables the model to compensate for the missing anatomy by learning the relationship between the truncation and known structures. After the model was trained, sCT images with complete anatomy can be generated by feeding only the truncated MR images into the model. In addition, the external body contours acquired from the CT images with full anatomy could be an optional input for the proposed method to leverage the additional information of the actual body shape for each test patient. The mean absolute error (MAE) of Hounsfield units (HU), peak signal-to-noise ratio (PSNR), and structural similarity index (SSIM) were calculated between sCT and real CT images to quantify the overall sCT performance. To further evaluate the shape accuracy, we generated the external body contours for sCT and original MR images with full anatomy. The Dice similarity coefficient (DSC) and mean surface distance (MSD) were calculated between the body contours of sCT and original MR images for the truncation region to assess the anatomy compensation accuracy. The average MAE, PSNR, and SSIM calculated over test patients were 93.1 HU/91.3 HU, 26.5dB/27.4dB, and 0.94/0.94 for the proposed Comp-cycleGAN models trained without/with body-contour information, respectively. These results were comparable with those obtained from the cycleGAN model which is trained and tested on full-anatomy MR images, indicating the high quality of the sCT generated from truncated MR images by the proposed method. Within the truncated region, the mean DSC and MSD were 0.85/0.89 and 1.3/0.7mm for the proposed Comp-cycleGAN models trained without/with body contour information, demonstrating good performance in compensating the truncated anatomy. We developed a novel Comp-cycleGAN model that can effectively create sCT with complete anatomy compensation from truncated MR images, which could potentially benefit the MRI-based treatment planning.

MRI-Based Radiomics Combined with Deep Learning for Distinguishing IDH-Mutant WHO Grade 4 Astrocytomas from IDH-Wild-Type Glioblastomas.

This study aimed to investigate the potential of quantitative radiomic data extracted from conventional MR images in discriminating IDH-mutant grade 4 astrocytomas from IDH-wild-type glioblastomas (GBMs). A cohort of 57 treatment-naïve patients with IDH-mutant grade 4 astrocytomas (n = 23) and IDH-wild-type GBMs (n = 34) underwent anatomical imaging on a 3T MR system with standard parameters. Post-contrast T1-weighted and T2-FLAIR images were co-registered. A semi-automatic segmentation approach was used to generate regions of interest (ROIs) from different tissue components of neoplasms. A total of 1050 radiomic features were extracted from each image. The data were split randomly into training and testing sets. A deep learning-based data augmentation method (CTGAN) was implemented to synthesize 200 datasets from the training sets. A total of 18 classifiers were used to distinguish two genotypes of grade 4 astrocytomas. From generated data using 80% training set, the best discriminatory power was obtained from core tumor regions overlaid on post-contrast T1 using the K-best feature selection algorithm and a Gaussian naïve Bayes classifier (AUC = 0.93, accuracy = 0.92, sensitivity = 1, specificity = 0.86, PR_AUC = 0.92). Similarly, high diagnostic performances were obtained from original and generated data using 50% and 30% training sets. Our findings suggest that conventional MR imaging-based radiomic features combined with machine/deep learning methods may be valuable in discriminating IDH-mutant grade 4 astrocytomas from IDH-wild-type GBMs.