T1 Inversion Recovery Research Articles

Ultrafast T1-T1ρ NMR for Correlating Different Motional Regimes of Molecules.

Nuclear magnetic resonance (NMR) relaxation times provide detailed information about molecular motions and local chemical environments. Longitudinal T1 relaxation time is most often sensitive to relatively fast, nano- to picosecond ranges of molecular motion. Rotating frame T1ρ relaxation time reflects a much slower, micro- to millisecond range of motion, and the motional regime can be tuned by changing spin-lock field strength. Conventional methods for measuring T1 and T1ρ relaxation times are time-consuming, since experiments must be repeated many times with incremented magnetization recovery or decay delay. In this work, we introduce two novel and efficient NMR methods to correlate the T1 and T1ρ relaxation times. The first method, IR-SPICY, combines the conventional T1 inversion recovery (IR) with the single-scan T1ρ detection-based spin-lock cycle (SPICY). The second method, ultrafast (UF) IR-SPICY, allows measurement of whole two-dimensional T1-T1ρ correlation data in a single scan, in a couple of seconds, based on spatial encoding of the T1 dimension. We demonstrate the performance of the methods by studying relaxation of water in porous silica and hydrogel samples, latter acting as a model of the articular cartilage extracellular matrix. The methods allow correlating different molecular motional regimes, potentially providing unprecedented information about various chemical and biochemical systems, such as structures and fluid dynamics in porous materials, macromolecular changes in tissues, and protein dynamics. One to three orders of magnitude shortened experiment time enable the studies of changing or degrading samples. Furthermore, the single-scan approach may significantly facilitate the use of modern nuclear-spin hyperpolarization techniques to enhance the sensitivity of T1-T1ρ measurements by several orders of magnitude.

Prediction of early recurrence of adult-type diffuse gliomas following radiotherapy using multi-modal magnetic resonance images.

Adult-type diffuse gliomas are among the central nervous system's most aggressive malignant primary neoplasms. Despite advancements in systemic therapies and technological improvements in radiation oncology treatment delivery, the survival outcome for these patients remains poor. Fast and accurate assessment of tumor response to oncologic treatments is crucial, as it can enable the early detection of recurrent or refractory gliomas, thereby allowing timely intervention with life-prolonging salvage therapies. Radiomics is a developing field with great potential to improve medical image interpretation. This study aims to apply a radiomics-based predictive model for classifying response to radiotherapy within the first 3 months post-treatment. Ninety-five patients were selected from the Burdenko Glioblastoma Progression Dataset. Tumor regions were delineated in the axial plane on contrast-enhanced T1(CE T1W) and T2 fluid-attenuated inversion recovery (T2_FLAIR) magnetic resonance imaging (MRI). Hand-crafted radiomic (HCR) features, including first- and second-order features, were extracted using PyRadiomics (3.7.6) in Python (3.10). Then, recursive feature elimination with a random forest (RF) classifier was applied for feature dimensionality reduction. RF and support vector machine (SVM) classifiers were built to predict treatment outcomes using the selected features. Leave-one-out cross-validation was employed to tune hyperparameters and evaluate the models. For each segmented target, 186 HCR features were extracted from the MRI sequence. Using the top-ranked radiomic features from a combination of CE T1W and T2_FLAIR, an optimized classifier achieved the highest averaged area under the curve (AUC) of 0.829±0.075 using the RF classifier. The HCR features of CE T1W produced the worst outcomes among all models (0.603±0.024 and 0.615±0.075 for RF and SVM classifiers, respectively). We developed and evaluated a radiomics-based predictive model for early tumor response to radiotherapy, demonstrating excellent performance supported by high AUC values. This model, harnessing radiomic features from multi-modal MRI, showed superior predictive performance compared to single-modal MRI approaches. These results underscore the potential of radiomics in clinical decision support for this disease process.

Improved Dementia Prediction in Cerebral Small Vessel Disease Using Deep Learning-Derived Diffusion Scalar Maps From T1.

Cerebral small vessel disease is the most common pathology underlying vascular dementia. In small vessel disease, diffusion tensor imaging is more sensitive to white matter damage and better predicts dementia risk than conventional magnetic resonance imaging sequences, such as T1 and fluid attenuation inversion recovery, but diffusion tensor imaging takes longer to acquire and is not routinely available in clinical practice. As diffusion tensor imaging-derived scalar maps-fractional anisotropy (FA) and mean diffusivity (MD)-are frequently used in clinical settings, one solution is to synthesize FA/MD from T1 images. We developed a deep learning model to synthesize FA/MD from T1. The training data set consisted of 4998 participants with the highest white matter hyperintensity volumes in the UK Biobank. Four external validations data sets with small vessel disease were included: SCANS (St George's Cognition and Neuroimaging in Stroke; n=120), RUN DMC (Radboud University Nijmegen Diffusion Tensor and Magnetic Resonance Imaging Cohort; n=502), PRESERVE (Blood Pressure in Established Cerebral Small Vessel Disease; n=105), and NETWORKS (n=26), along with 1000 normal controls from the UK Biobank. The synthetic maps resembled ground-truth maps (structural similarity index >0.89 for MD maps and >0.80 for FA maps across all external validation data sets except for SCANS). The prediction accuracy of dementia using whole-brain median MD from the synthetic maps is comparable to the ground truth (SCANS ground-truth c-index, 0.822 and synthetic, 0.821; RUN DMC ground truth, 0.816 and synthetic, 0.812) and better than white matter hyperintensity volume (SCANS, 0.534; RUN DMC, 0.710). We have developed a fast and generalizable method to synthesize FA/MD maps from T1 to improve the prediction accuracy of dementia in small vessel disease when diffusion tensor imaging data have not been acquired.

Can a fast T2-Dixon sequence surpass the time obstacle of whole-body MRI in the evaluation of skeletal metastases?

BackgroundWhole-body magnetic resonance imaging (WB-MRI) has shown its accuracy in the diagnosis of skeletal metastases in patients with known primary solid cancers. The standard protocol was a combination of T1 and short tau inversion recovery (STIR) sequences. Herein, this study was conducted to elucidate the role of the T2-Dixon sequence as a rapid alternative to the standard protocol with the assessment of its diagnostic accuracy and comparability to the established methodology.MethodsThis prospective study included 30 patients with primary solid malignancies who underwent WB-MRI. The sequences obtained were T1WI, STIR, and T2-Dixon (fat-only and water-only images). Skeletal metastases were evaluated in each sequence. Results were compared between the T1-STIR combination and T2-Dixon fat and water reconstructions.ResultsThe sensitivity of fat and water reconstructions from a single T2-Dixon in the detection of lytic skeletal metastases was marginally superior to a combination of T1WI and STIR sequences (0–7%). Detection of mixed lesions demonstrated equally high sensitivity in both protocols. Sclerotic metastases detection in WB-MRI showed low sensitivity in both protocols. However, specificity surpassed 95% for all lesion types in both protocols. Overall image quality was favored (in 87–90% of patients) in T2-Dixon images. The overall estimated acquisition timing using T2-Dixon appeared to be approximately half that of the standard T1-STIR combination.ConclusionsWB-MRI using T2-Dixon fat and water reconstructions showed similar accuracy to T1WI and STIR combination in the evaluation of skeletal metastases in patients with primary solid cancers with significantly shorter acquisition time.

MRI-Derived Modeling of Disease Progression Patterns in Patients With Temporal Lobe Epilepsy.

Temporal lobe epilepsy (TLE) is assumed to follow a steady course that is similar across patients. To date, phenotypic and temporal diversities of TLE evolution remain unknown. In this study, we aimed at simultaneously characterizing these sources of variability based on cross-sectional data. We studied consecutive patients with TLE referred for evaluation by neurologists to the Montreal Neurological Institute epilepsy clinic, who underwent in-patient video EEG monitoring and multimodal imaging at 3 Tesla, comprising 3D T1 and fluid-attenuated inversion recovery and 2D diffusion-weighted MRI. The cohort included patients with drug-resistant epilepsy and patients with drug-responsive epilepsy. The neuropsychological evaluation included Wechsler Adult Intelligence Scale-III and Leonard tapping task. The control group consisted of participants without TLE recruited through advertisement and who underwent the same MRI acquisition as patients. Based on surface-based analysis of key MRI markers of pathology (gray matter morphology and white matter microstructure), the Subtype and Stage Inference algorithm estimated subtypes and stages of brain pathology to which individual patients were assigned. The number of subtypes was determined by running the algorithm 100 times and estimating mean and SD of disease trajectories and the consistency of patients' assignments based on 1,000 bootstrap samples. Effect of normal aging was subtracted from patients. We examined associations with clinical and cognitive parameters and utility for individualized predictions. We studied 82 patients with TLE (52 female, mean age 35 ± 10 years; 11 drug-responsive) and 41 control participants (23 male, mean age 32 ± 8 years). Among 57 operated, 43/37/20 had Engel-I outcome/hippocampal sclerosis/hippocampal isolated gliosis, respectively. We identified 3 trajectory subtypes: S1 (n = 35), led by ipsilateral hippocampal atrophy and gliosis, followed by white-matter damage; S2 (n = 27), characterized by bilateral neocortical atrophy, followed by ipsilateral hippocampal atrophy and gliosis; and S3 (n = 20), typified by bilateral limbic white-matter damage, followed by bilateral hippocampal gliosis. Patients showed high assignability to their subtypes and stages (>90% bootstrap agreement). S1 had the highest proportions of patients with early disease onset (effect size d = 0.27 vs S2, d = 0.73 vs S3), febrile convulsions (χ2 = 3.70), drug resistance (χ2 = 2.94), a positive MRI (χ2 = 8.42), hippocampal sclerosis (χ2 = 7.57), and Engel-I outcome (χ2 = 1.51), pFDR < 0.05 across all comparisons. S2 and S3 exhibited the intermediate and lowest proportions, respectively. Verbal IQ and digit span were lower in S1 (d = 0.65 and d = 0.50, pFDR < 0.05) and S2 (d = 0.76 and d = 1.09, pFDR < 0.05), compared with S3. We observed progressive decline in sequential motor tapping in S1 and S3 (T = -3.38 and T = -4.94, pFDR = 0.027), compared with S2 (T = 2.14, pFDR = 0.035). S3 showed progressive decline in digit span (T = -5.83, p = 0.021). Supervised classifiers trained on subtype and stage outperformed subtype-only and stage-only models predicting drug response in 73% ± 1.0% (vs 70% ± 1.4% and 63% ± 1.3%) and 76% ± 1.6% for Engel-I outcome (vs 71% ± 0.8% and 72% ± 1.1%), pFDR < 0.05 across all comparisons. Cross-sectional MRI-derived models provide reliable prognostic markers of TLE disease evolution, which follows distinct trajectories, each associated with divergent patterns of hippocampal and whole-brain structural alterations, as well as cognitive and clinical profiles.

Brain Magnetic Resonance Imaging in Wilson's Disease-Significance and Practical Aspects-A Narrative Review.

Wilson's disease (WD) is a genetic disorder of copper metabolism with pathological copper accumulation in many organs, resulting in clinical symptoms, mostly hepatic and neuropsychiatric. As copper accumulates in the brain during WD, and almost 50% of WD patients at diagnosis present with neurological symptoms, neuroimaging studies (especially brain magnetic resonance imaging (MRI)) are part of WD diagnosis. The classical sequences (T1, T2, and fluid-attenuated inversion recovery) were used to describe brain MRI; however, with the development of neuroradiology, several papers proposed the use of new MRI sequences and techniques like susceptibility-weighted images, T2*, diffusion MRI, tractography, volumetric assessment and post-processing brain MRI analysis of paramagnetic accumulation-quantitative susceptibility mapping. Based on these neuroradiological data in WD, currently, brain MRI semiquantitative scale and the pathognomonic neuroradiological brain MRI signs in WD were proposed. Further, the volumetric studies and brain iron accumulation MRI analysis suggested brain atrophy and iron accumulation as biomarkers of neurological WD disease severity. All these results highlight the significance of brain MRI examinations in WD. Due to the extreme progress of these studies, based on the available literature, the authors present the current state of knowledge about the significance, practical aspects, and future directions of brain MRI in WD.

Assessment of image quality and diagnostic accuracy for cervical spondylosis using T2w-STIR sequence with a deep learning-based reconstruction approach.

To investigate potential of enhancing image quality, maintaining interobserver consensus, and elevating disease diagnostic efficacy through the implementation of deep learning-based reconstruction (DLR) processing in 3.0T cervical spine fast magnetic resonance imaging (MRI) images, compared with conventional images. The 3.0T cervical spine MRI images of 71 volunteers were categorized into two groups: sagittal T2-weighted short T1 inversion recovery without DLR (Sag T2w-STIR) and with DLR (Sag T2w-STIR-DLR). The assessment covered artifacts, perceptual signal-to-noise ratio, clearness of tissue interfaces, fat suppression, overall image quality, and the delineation of spinal cord, vertebrae, discs, dopamine, and joints. Spanning canal stenosis, neural foraminal stenosis, herniated discs, annular fissures, hypertrophy of the ligamentum flavum or vertebral facet joints, and intervertebral disc degeneration were evaluated by three impartial readers. Sag T2w-STIR-DLR images exhibited markedly superior performance across quality indicators (median = 4 or 5) compared to Sag T2w-STIR sequences (median = 3 or 4) (p < 0.001). No statistically significant differences were observed between the two sequences in terms of diagnosis and grading (p > 0.05). The interobserver agreement for Sag T2w-STIR-DLR images (0.604-0.931) was higher than the other (0.545-0.853), Sag T2w-STIR-DLR (0.747-1.000) demonstrated increased concordance between reader 1 and reader 3 in comparison to Sag T2w-STIR (0.508-1.000). Acquisition time diminished from 364 to 197s through the DLR scheme. Our investigation establishes that 3.0T fast MRI images subjected to DLR processing present heightened image quality, bolstered diagnostic performance, and reduced scanning durations for cervical spine MRI compared with conventional sequences.

Native and Gd-EOB-DTPA-Enhanced T1 mapping for Assessment of Liver Fibrosis in NAFLD: Comparative Analysis of Modified Look-Locker Inversion Recovery and Water-specific T1 mapping

Rationale and ObjectivesTo investigate the diagnostic performance of water-specific T1 mapping for staging liver fibrosis in a non-alcoholic fatty liver disease (NAFLD) rabbit model, in comparison to Modified Look-Locker Inversion recovery (MOLLI) T1 mapping. Materials and methodsSixty rabbits were randomly divided into the control group (12 rabbits) and NAFLD model groups (8 rabbits per subgroup) corresponding to different durations of high-fat high cholesterol diet feeding. All rabbits underwent MRI examination including MOLLI T1 mapping and 3D multi-echo variable flip angle (VFAME- GRE) sequences were acquired before and 20min after the administration of Gd- EOB-DTPA. Histological assessments were performed to evaluate steatosis, inflammation, ballooning, and fibrosis. Statistical analysis included the intraclass correlation coefficient, analysis of variance, spearman correlation, multiple linear regression, and receiver operating characteristic curve. ResultsA moderate correlation was observed between conventional native T1 and MRI-PDFF (r=-0.513, P<0.001), as well as between conventional native T1 and liver steatosis grades (r=-0.319, P=0.016). However, no significant correlation was found between the native wT1 and PDFF (r=0.137, P=0.314), or between the native wT1 and steatosis grades (r=0.106, P=0.435). In the multiple regression analysis, liver fibrosis, and hepatocellular ballooning were identified as independent factors influencing native wT1 in this study (R2=0.545, P<0.05), while steatosis was independently associated with conventional native T1 (R2=0.321, P<0.005). The AUC values for native T1, native wT1, HBP T1, and HBP wT1 were 0.549(0.410-0.682), 0.811(0.684-0.903), 0.775(0.644-0.876), and 0.752(0.619-0.858) for F1 or higher, 0.581(0.441-0.711), 0.828(0.704-0.916), 0.832(0.708-0.919), and 0.854(0.734-0.934) for F2 or higher, respectively. ConclusionThe native wT1 may provide a more reliable assessment of early liver fibrosis in the context of NAFLD compared to conventional native T1.

Application of Short T1 Inversion Recovery Sequence in Increased Signal Intensity Following Cervical Spondylotic Myelopathy

To compare magnetic resonance (MR) short T1 inversion recovery (STIR) sequence with MR T2-weighted (T2W) sequence for detecting increased signal intensity (ISI) and assessing outcomes of ISI in cervical spondylotic myelopathy (CSM). Data of patients with CSM who showed ISI on MR imaging and had undergone cervical spine surgery were retrospectively reviewed. STIR and T2W images were examined to assess signal intensity ratio (SIR), length and grading of the ISI, maximal spinal cord compression (MSCC), canal narrowing ratio (CNR), and ligamentum flavum hypertrophy (LFH). The patients were divided into good and poor groups based on their outcomes. Chi-square tests and variance analysis were used to assess intergroup differences. Univariate and multivariate logistic regression analyses were performed to identify risk factors for poor outcomes, and receiver operating characteristic curves were plotted to detect prognostic effects. SIR and ISI lengths were significantly different between the STIR and T2 images. In the univariate logistic regression analysis, age, diabetes, SIRT2, SIRSTIR, and ISISTIR grading were significant factors. Accordingly, in the multivariate logistic regression analysis, age, diabetes, SIRT2, and SIRSTIR were included in the model. Among patients with diabetes, we observed a significant difference between SIRT2 and SIRSTIR. The STIR sequence demonstrated superior capability to the T2W sequence in detecting ISI; however, there was no obvious difference in predicted outcomes. STIR sequence has a better prognostic value than T2W sequence in patients with diabetes who have CSM. ISI grading based on the STIR sequence may be a clinically valuable indicator.

Conversion of T2-Weighted Magnetic Resonance Images of Cervical Spine Trauma to Short T1 Inversion Recovery (STIR) Images by Generative Adversarial Network.

The short T1 inversion recovery (STIR) sequence is advantageous for visualizing ligamentous injuries, but the STIR sequence may be missing in some cases. The purpose of this study was to generate synthetic STIR images from MRI T2-weighted images (T2WI) of patients with cervical spine trauma using a generative adversarial network (GAN). Methods: A total of 969 pairs of T2WI and STIR images were extracted from 79 patients with cervical spine trauma. The synthetic model was trained 100 times, and the performance of the model was evaluated with five-fold cross-validation. Results: As for quantitative validation, the structural similarity score was 0.519±0.1 and the peak signal-to-noise ratio score was 19.37±1.9 dB. As for qualitative validation, the incorporation of synthetic STIR images generated by a GAN alongside T2WI substantially enhances sensitivity in the detection of interspinous ligament injuries, outperforming assessments reliant solely on T2WI. The GAN model can generate synthetic STIRs from T2 images of cervical spine trauma using image-to-image conversion techniques. The use of a combination of synthetic STIR images generated by a GAN and T2WI improves sensitivity in detecting interspinous ligament injuries compared to assessments that use only T2WI.

MRI and Blood-based Biomarkers Are Associated With Surgery in Children and Adults With Ileal Crohn's Disease.

Despite advances in medical therapy, many children and adults with ileal Crohn's disease (CD) progress to fibrostenosis requiring surgery. We aimed to identify MRI and circulating biomarkers associated with the need for surgical management. This prospective, multicenter study included pediatric and adult CD cases undergoing ileal resection and CD controls receiving medical therapy. Noncontrast research MRI examinations measured bowel wall 3-dimensional magnetization transfer ratio normalized to skeletal muscle (normalized 3D MTR), modified Look-Locker inversion recovery (MOLLI) T1 relaxation, intravoxel incoherent motion (IVIM) diffusion-weighted imaging metrics, and the simplified magnetic resonance index of activity (sMaRIA). Circulating biomarkers were measured on the same day as the research MRI and included CD64, extracellular matrix protein 1 (ECM1), and granulocyte-macrophage colony-stimulating factor (GM-CSF) autoantibodies (Ab). Associations between MRI and circulating biomarkers and need for ileal resection were tested using univariate and multivariable LASSO regression. Our study sample included 50 patients with CD undergoing ileal resection and 83 patients with CD receiving medical therapy; mean participant age was 23.9 ± 13.1 years. Disease duration and treatment exposures did not vary between the groups. Univariate biomarker associations with ileal resection included log GM-CSF Ab (odds ratio [OR], 2.87; P = .0009), normalized 3D MTR (OR, 1.05; P = .002), log MOLLI T1 (OR, 0.01; P = .02), log IVIM perfusion fraction (f; OR, 0.38; P = .04), and IVIM apparent diffusion coefficient (ADC; OR, 0.3; P = .001). The multivariable model for surgery based upon correctedAkaike information criterion included age (OR, 1.03; P = .29), BMI (OR, 0.91; P = .09), log GM-CSF Ab (OR, 3.37; P = .01), normalized 3D MTR (OR, 1.07; P = .007), sMaRIA (OR, 1.14; P = .61), luminal narrowing (OR, 10.19; P = .003), log C-reactive protein (normalized; OR, 2.75; P = .10), and hematocrit (OR, 0.90; P = .13). After accounting for clinical and MRI measures of severity, normalized 3D MTR and GM-CSF Ab are associated with the need for surgery in ileal CD.

Preoperative Differentiation of HER2-Zero and HER2-Low from HER2-Positive Invasive Ductal Breast Cancers Using BI-RADS MRI Features and Machine Learning Modeling.

Accurate determination of human epidermal growth factor receptor 2 (HER2) is important for choosing optimal HER2 targeting treatment strategies. HER2-low is currently considered HER2-negative, but patients may be eligible to receive new anti-HER2 drug conjugates. To use breast MRI BI-RADS features for classifying three HER2 levels, first to distinguish HER2-zero from HER2-low/positive (Task-1), and then to distinguish HER2-low from HER2-positive (Task-2). Retrospective. 621 invasive ductal cancer, 245 HER2-zero, 191 HER2-low, and 185 HER2-positive. For Task-1, 488 cases for training and 133 for testing. For Task-2, 294 cases for training and 82 for testing. 3.0 T; 3D T1-weighted DCE, short time inversion recovery T2, and single-shot EPI DWI. Pathological information and BI-RADS features were compared. Random Forest was used to select MRI features, and then four machine learning (ML) algorithms: decision tree (DT), support vector machine (SVM), k-nearest neighbors (k-NN), and artificial neural nets (ANN), were applied to build models. Chi-square test, one-way analysis of variance, and Kruskal-Wallis test were performed. The P values <0.05 were considered statistically significant. For ML models, the generated probability was used to construct the ROC curves. Peritumoral edema, the presence of multiple lesions and non-mass enhancement (NME) showed significant differences. For distinguishing HER2-zero from non-zero (low + positive), multiple lesions, edema, margin, and tumor size were selected, and the k-NN model achieved the highest AUC of 0.86 in the training set and 0.79 in the testing set. For differentiating HER2-low from HER2-positive, multiple lesions, edema, and margin were selected, and the DT model achieved the highest AUC of 0.79 in the training set and 0.69 in the testing set. BI-RADS features read by radiologists from preoperative MRI can be analyzed using more sophisticated feature selection and ML algorithms to build models for the classification of HER2 status and identify HER2-low. Stage 2.

Repeat it without me: Crowdsourcing the T1 mapping common ground via the ISMRM reproducibility challenge.

T1 mapping is a widely used quantitative MRI technique, but its tissue-specific values remain inconsistent across protocols, sites, and vendors. The ISMRM Reproducible Research and Quantitative MR study groups jointly launched a challenge to assess the reproducibility of a well-established inversion-recovery T1 mapping technique, using acquisition details from a seminal T1 mapping paper on a standardized phantom and in human brains. The challenge used the acquisition protocol from Barral et al. (2010). Researchers collected T1 mapping data on the ISMRM/NIST phantom and/or in human brains. Data submission, pipeline development, and analysis were conducted using open-source platforms. Intersubmission and intrasubmission comparisons were performed. Eighteen submissions (39 phantom and 56 human datasets) on scanners by three MRI vendors were collected at 3 T (except one, at 0.35 T). The mean coefficient of variation was 6.1% for intersubmission phantom measurements, and 2.9% for intrasubmission measurements. For humans, the intersubmission/intrasubmission coefficient of variation was 5.9/3.2% in the genu and 16/6.9% in the cortex. An interactive dashboard for data visualization was also developed: https://rrsg2020.dashboards.neurolibre.org. The T1 intersubmission variability was twice as high as the intrasubmission variability in both phantoms and human brains, indicating that the acquisition details in the original paper were insufficient to reproduce a quantitative MRI protocol. This study reports the inherent uncertainty in T1 measures across independent research groups, bringing us one step closer to a practical clinical baseline of T1 variations in vivo.

Fast magnetization transfer saturation imaging of the brain using MP2RAGE T1 mapping.

Magnetization transfer saturation (MTsat) mapping is commonly used to examine the macromolecular content of brain tissue. This study compared variable flip angle (VFA) T1 mapping against compressed-sensing MP2RAGE (csMP2RAGE) T1 mapping for accelerating MTsat imaging. VFA, MP2RAGE, and csMP2RAGE were compared against inversion-recovery T1 in an aqueous phantom at 3 T. The same 1-mm VFA, MP2RAGE, and csMP2RAGE protocols were acquired in 4 healthy subjects to compare T1 and MTsat. Bloch-McConnell simulations were used to investigate differences between the phantom and in vivo T1 results. Ten healthy controls were imaged twice with the csMP2RAGE MTsat protocol to quantify repeatability. The MP2RAGE and csMP2RAGE protocols were 13.7% and 32.4% faster than the VFA protocol, respectively. At these scan times, all approaches provided strong repeatability and accurate T1 times (< 5% difference) in the phantom, but T1 accuracy was more impacted by T2 for VFA than for MP2RAGE. In vivo, VFA estimated longer T1 times than MP2RAGE and csMP2RAGE. Simulations suggest that the differences in the T1 measured using VFA, MP2RAGE, and inversion recovery could be explained by the magnetization-transfer effects. In the test-retest experiment, we found that the csMP2RAGE has a minimum detectable change of 2.3% for T1 mapping and 7.8% for MTsat imaging. We demonstrated that MP2RAGE can be used in place of VFA T1 mapping in an MTsat protocol. Furthermore, a shorter scan time and high repeatability can be achieved using the csMP2RAGE sequence.

MRI Extracellular Volume Fraction in Liver Fibrosis-A Comparison of Different Time Points and Blood Pool Measurements.

Extracellular volume (ECV) correlates with the degree of liver fibrosis. To analyze the performance of liver MRI-based ECV evaluations with different blood pool measurements at different time points. Prospective. 73 consecutive patients (n = 31 females, mean age 56 years) with histopathology-proven liver fibrosis. 3T acquisition within 90 days of biopsy, including shortened modified look-locker inversion recovery T1 mapping. Polygonal regions of interest were manually drawn in the liver, aorta, vena cava, and in the main, left and right portal vein on four slices before and after Gd-DOTA administration at 5/10/15 minutes. ECV was calculated 1) on one single slice on portal bifurcation level, and 2) averaged over all four slices. Parameters were compared between patients with fibrosis grades F0-2 and F3-F4 with the Mann-Whitney U and fishers exact test. ROC analysis was used to assess the performance of the parameters to predict F3-4 fibrosis. A P-value <0.05 was considered statistically significant. ECV was significantly higher in F3-4 fibrosis (35.4% [33.1%-37.6%], 36.1% [34.2%-37.5%], and 37.0% [34.8%-39.2%] at 5/10/15 minutes) than in patients with F0-2 fibrosis (33.3% [30.8%-34.8%], 33.7% [31.6%-34.7%] and 34.9% [32.2%-36.0%]; AUC = 0.72-0.75). Blood pool T1 relaxation times in the aorta and vena cava were longer on the upper vs. lower slices at 5 minutes, but not at 10/15 minutes. AUC values were similar when measured on a single slice (AUC = 0.69-0.72) or based on blood pool measurements in the cava or portal vein (AUC = 0.63-0.67 and AUC = 0.65-0.70). Liver ECV is significantly higher in F3-4 fibrosis compared to F0-2 fibrosis with blood pool measurements performed in the aorta, inferior vena cava, and portal vein at 5, 10, and 15 minutes. However, a smaller variability was observed for blood pool measurements between slices at 15 minutes. 1 TECHNICAL EFFICACY: Stage 3.

Comparison of Dentatorubrothalamic Tractography Methods Based on the Anatomy of the Rubral Wing.

Precise localization of the dentatorubrothalamic (DRT) tract can facilitate anatomic targeting in MRI-guided high-intensity focused ultrasound (HIFU) thalamotomy and thalamic deep brain stimulation for tremor. The anatomic segment of DRT fibers adjacent to the ventral intermediate nucleus of the thalamus (VIM), referred to as the rubral wing (RW), may be directly visualized on the fast gray matter acquisition T1 inversion recovery. We compared reproducibility, lesion overlap, and clinical outcomes when reconstructing the DRT tract using a novel anatomically defined RW region of interest, DRT-RW, to an existing tractography method based on the posterior subthalamic area region of interest (DRT-PSA). We reviewed data of 23 patients with either essential tremor (n = 18) or tremor-predominant Parkinson's disease (n = 5) who underwent HIFU thalamotomy, targeting the VIM. DRT tractography, ipsilateral to the lesion, was created based on either DRT-PSA or DRT-RW. Volume sections of each tract were created and dice similarity coefficients were used to measure spatial overlap between the 2 tractographies. Post-HIFU lesion size and location (on postoperative T2 MRI) was correlated with tremor outcomes and side effects for both DRT tractography methods and the RW itself. DRT-PSA passed through the RW and DRT-RW intersected with the ROIs of the DRT-PSA in all 23 cases. A higher percentage of the RW was ablated in patients who achieved tremor control (18.9%, 95% CI 15.1, 22.7) vs those without tremor relief (6.7%, 95% CI% 0, 22.4, P = .017). In patients with tremor control 6 months postoperatively (n = 12), those with side effects (n = 6) had larger percentages of their tracts ablated in comparison with those without side effects in both DRT-PSA (44.8, 95% CI 31.8, 57.8 vs 24.2%, 95% CI 12.4, 36.1, P = .025) and DRT-RW (35.4%, 95% CI 21.5, 49.3 vs 21.7%, 95% CI 12.7, 30.8, P = .030). Tractography of the DRT could be reconstructed by direct anatomic visualization of the RW on fast gray matter acquisition T1 inversion recovery-MRI. Anatomic planning is expected to be quicker, more reproducible, and less operator-dependent.

MRI AND BLOOD-BASED BIOMARKERS ASSOCIATED WITH SURGICAL MANAGEMENT IN CHILDREN AND ADULTS WITH SMALL BOWEL CROHN'S DISEASE

Abstract BACKGROUND Despite advances in medical therapy, many children and adults with ileal Crohn’s Disease (CD) progress to fibrostenosis requiring surgery. Prior studies have identified circulating and imaging biomarkers associated with strictures, although their associations with need for surgery are not well-established. PURPOSE We aimed to identify MRI and circulating biomarkers associated with the need for surgical management in chidlren and adults with ileal CD. METHODS This prospective, multi-center study included pediatric and adult CD cases undergoing ileal resection (n=50), and CD controls receiving medical therapy (n=83). Noncontrast research MRI examinations measured bowel wall three-dimensional magnetization transfer ratio normalized to skeletal muscle (normalized 3D MTR), modified Look-Locker inversion recovery (MOLLI) T1 relaxation, intravoxel incoherent motion (IVIM) diffusion-weighted imaging metrics, and the simplified magnetic resonance index of activity (sMaRIA) (Figure 1). Circulating biomarkers included CD64, ECM1, and GM-CSF autoantibodies (Ab). Clinical variables, including demographics, anthropometrics, and routine clinical laboratory data (e.g., CRP, fecal calprotectin), also were obtained at the research visit. Associations between MRI and circulating biomarkers and need for ileal resection were tested using univariate and multivariable LASSO regression. RESULTS Mean participant age was 23.9±13.1 years. Disease duration and treatment exposures did not vary between the groups. Univariate biomarker associations with ileal resection included log GM-CSF Ab (odds ratio [OR]=2.87; p=0.0009), normalized 3D MTR (OR=1.05; p=0.002), log MOLLI T1 (OR=0.01; p=0.02), log IVIM perfusion fraction (f) (OR=0.38; p=0.04), and IVIM apparent diffusion coefficient (ADC) (OR=0.3; p=0.001). MRI and circulating biomarker Tukey box plots are presented in Figure 2. The multivariable model for surgery based upon AICc criteria included age (OR=1.03; p=0.29), BMI (OR=0.91; p=0.09), log GM-CSF Ab (OR=3.37; p=0.01), normalized 3D MTR (OR=1.07; p=0.007), sMaRIA (OR=1.14; p=0.61), luminal narrowing (OR=10.19; p=0.003), log CRP (normalized) (OR=2.75; p=0.10), and hematocrit (OR=0.90; p=0.13). CONCLUSION After accounting for clinical and MRI measures of severity, normalized 3D MTR and GM-CSF Ab are associated with need for surgery in ileal CD. GM-CSF autoantibodies and MRI biomarker sequences may be useful for guiding management decisions in CD patients. Figure 1 Research MRI images from a surgical Crohn’s disease patient with stricturing behavior involving the terminal ileum. A and B. Coronal and axial fat-saturated T2-weighted single-shot fast spin-echo (SSFSE) images show wall thickening and luminal narrowing of the terminal ileum (arrows) with more proximal bowel dilation measuring greater than 3 cm. C. Axial 3D magnetization transfer images – MT pulse on (bottom image, arrow), MT pulse off (top image, arrow). D. Axial modified Look-Locker inversion recovery (MOLLI) T1 relaxation image (arrow). E. Representative axial intravoxel incoherent motion diffusion-weighted images with increasing b-values (left to right, arrows). Figure 2 Variation in circulating and imaging biomarkers in Crohn’s disease patients with medical and surgical management. Ctrl: non-IBD healthy controls; Med: CD patients with nonsurgical medical management; Surg: CD patients with surgical management.

Liver T1 Mapping Derived From Cardiac Magnetic Resonance Imaging: A Potential Prognostic Marker in Idiopathic Dilated Cardiomyopathy.

Hepatic alterations are common aftereffects of heart failure (HF) and ventricular dysfunction. The prognostic value of liver injury markers derived from cardiac MRI studies in nonischemic dilated cardiomyopathy (DCM) patients is unclear. Evaluate the prognostic performance of liver injury markers derived from cardiac MRI studies in DCM patients. Prospective. Three hundred fifty-six consecutive DCM patients diagnosed according to ESC guidelines (age 48.7 ± 14.2 years, males 72.6%). Steady-state free precession, modified Look-Locker inversion recovery T1 mapping and phase sensitive inversion recovery late gadolinium enhancement (LGE) sequences at 3 T. Clinical characteristics, conventional MRI parameters (ventricular volumes, function, mass), native myocardial and liver T1, liver extracellular volume (ECV), and myocardial LGE presence were assessed. Patients were followed up for a median duration of 48.3 months (interquartile range 42.0-69.9 months). Primary endpoints included HF death, sudden cardiac death, heart transplantation, and HF readmission; secondary endpoints included HF death, sudden cardiac death, and heart transplantation. Models were developed to predict endpoints and the incremental value of including liver parameters assessed. Optimal cut-off value was determined using receiver operating characteristic curve and Youden method. Survival analysis was performed using Kaplan-Meier and Cox proportional hazard. Discriminative power of models was compared using net reclassification improvement and integrated discriminatory index. P value <0.05 was considered statistically significant. 47.2% patients reached primary endpoints; 25.8% patients reached secondary endpoints. Patients with elevated liver ECV (cut-off 34.4%) had significantly higher risk reaching primary and secondary endpoints. Cox regression showed liver ECV was an independent prognostic predictor, and showed independent prognostic value for primary endpoints and long-term HF readmission compared to conventional clinical and cardiac MRI parameters. Liver ECV is an independent prognostic predictor and may serve as an innovative approach for risk stratification for DCM. 1 TECHNICAL EFFICACY: Stage 2.

Validation of single reference variable flip angle (SR-VFA) dynamic T1 mapping with T2 * correction using a novel rotating phantom.

To validate single reference variable flip angle (SR-VFA) dynamic T1 mapping with and without T2 * correction against inversion recovery (IR) T1 measurements. A custom cylindrical phantom with three concentric compartments was filled with variably doped agar to produce a smooth spatial gradient of the T1 relaxation rate as a function of angle across each compartment. IR T1 , VFA T1 , and B1 + measurements were made on the phantom before rotation, and multi-echo stack-of-radial dynamic images were acquired during rotation via an MRI-compatible motor. B1 + -corrected SR-VFA and SR-VFA-T2 * T1 maps were computed from the sliding window reconstructed images and compared against rotationally registered IR and VFA T1 maps to determine the percentage error. Both VFA and SR-VFA-T2 * T1 maps fell within 10% of IR T1 measurements for a low rotational speed, with a mean accuracy of 2.3% ± 2.6% and 2.8% ± 2.6%, respectively. Increasing rotational speed was found to decrease the accuracy due to increasing temporal smoothing over ranges where the T1 change had a nonconstant slope. SR-VFA T1 mapping was found to have similar accuracy as the SR-VFA-T2 * and VFA methods at low TEs (˜<2 ms), whereas accuracy degraded strongly with later TEs. T2 * correction of the SR-VFA T1 maps was found to consistently improve accuracy and precision, especially at later TEs. SR-VFA-T2 * dynamic T1 mapping was found to be accurate against reference IR T1 measurements within 10% in an agar phantom. Further validation is needed in mixed fat-water phantoms and in vivo.

Accuracy of free-breathing multi-parametric SASHA in identifying T1 and T2 elevations in pediatric orthotopic heart transplant patients.

T1/T2 parametric mapping may reveal patterns of elevation ("hotspots") in myocardial diseases, such as rejection in orthotopic heart transplant (OHT) patients. This study aimed to evaluate the diagnostic accuracy of free-breathing (FB) multi-parametric SAturation recovery single-SHot Acquisition (mSASHA) T1/T2 mapping in identifying hotspots present on conventional Breath-held Modified Look-Locker Inversion recovery (BH MOLLI) T1 and T2-prepared balanced steady-state free-precession (BH T2p-bSSFP) maps in pediatric OHT patients. Pediatric OHT patients underwent noncontrast 1.5T CMR with BH MOLLI T1 and T2p-bSSFP and prototype FB mSASHA T1/T2 mapping in 8 short-axis slices. FB and BH T1/T2 hotspots were segmented using semi-automated thresholding (ITK-SNAP) and their 3D coordinate locations were collected (3-Matic, Materialise, Leuven, Belgium). Receiver operator characteristic curve analysis and measures of central tendency were utilized. 40 imaging datasets from 23 pediatric OHT patients were obtained. FB mSASHA yielded a sensitivity of 82.8% for T1 and 80% for T2 maps when compared to the standard BH MOLLI, as well as 100% specificity for both T1 and T2 maps. When identified on both FB and BH maps, hotspots overlapped in all cases, with an average long axis offset between FB and BH hotspot centers of 5.8mm (IQR 3.5-8.2) on T1 and 5.9mm (IQR 3.5-8.2) on T2 maps. FB mSASHA T1/T2 maps can identify hotspots present on conventional BH T1/T2 maps in pediatric patients with OHT, with high sensitivity, specificity, and overlap in 3D space. Free-breathing mapping may improve patient comfort and facilitate OHT assessment in younger patient populations.