Liver Investigation: Testing Marker Utility in Steatohepatitis (LITMUS): Assessment & validation of imaging modality performance across the NAFLD spectrum in a prospectively recruited cohort study (the LITMUS imaging study): Study protocol.

Non-alcoholic fatty liver disease (NAFLD) is the liver manifestation of the metabolic syndrome with global prevalence reaching epidemic levels. Despite the high disease burden in the population only a small proportion of those with NAFLD will develop progressive liver disease, for which there is currently no approved pharmacotherapy. Identifying those who are at risk of progressive NAFLD currently requires a liver biopsy which is problematic. Firstly, liver biopsy is invasive and therefore not appropriate for use in a condition like NAFLD that affects a large proportion of the population. Secondly, biopsy is limited by sampling and observer dependent variability which can lead to misclassification of disease severity. Non-invasive biomarkers are therefore needed to replace liver biopsy in the assessment of NAFLD. Our study addresses this unmet need. The LITMUS Imaging Study is a prospectively recruited multi-centre cohort study evaluating magnetic resonance imaging and elastography, and ultrasound elastography against liver histology as the reference standard. Imaging biomarkers and biopsy are acquired within a 100-day window. The study employs standardised processes for imaging data collection and analysis as well as a real time central monitoring and quality control process for all the data submitted for analysis. It is anticipated that the high-quality data generated from this study will underpin changes in clinical practice for the benefit of people with NAFLD. Study Registration: clinicaltrials.gov: NCT05479721.

Assessment of intravoxel incoherent motion MRI with an artificial capillary network: analysis of biexponential and phase-distribution models.

PURPOSE: To systematically analyze intravoxel incoherent motion (IVIM) MRI in a perfusable capillary phantom closely matching the geometry of capillary beds in vivo and to compare the validity of the biexponential pseudo-diffusion and the recently introduced phase-distribution IVIM model. METHODS: IVIM-MRI was performed at 12 different flow rates ( 0.2⋯2.4mL/min ) in a capillary phantom using 4 different DW-MRI sequences (2 with monopolar and 2 with flow-compensated diffusion-gradient schemes, with up to 16b values between 0 and 800s/mm2 ). Resulting parameters from the assessed IVIM models were compared to results from optical microscopy. RESULTS: The acquired data were best described by a static and a flowing compartment modeled by the phase-distribution approach. The estimated signal fraction f of the flowing compartment stayed approximately constant over the applied flow rates, with an average of f=0.451±0.023 in excellent agreement with optical microscopy ( f=0.454±0.002 ). The estimated average particle flow speeds v=0.25⋯2.7mm/s showed a highly significant linear correlation to the applied flow. The estimated capillary segment length of approximately 189um agreed well with optical microscopy measurements. Using the biexponential model, the signal fraction f was substantially underestimated and displayed a strong dependence on the applied flow rate. CONCLUSION: The constructed phantom facilitated the detailed investigation of IVIM-MRI methods. The results demonstrate that the phase-distribution method is capable of accurately characterizing fluid flow inside a capillary network. Parameters estimated using the biexponential model, specifically the perfusion fraction f , showed a substantial bias because the model assumptions were not met by the underlying flow pattern.

Technical Note: Quantitative dynamic contrast-enhanced MRI of a 3-dimensional artificial capillary network.

PURPOSE: Variability across devices, patients, and time still hinders widespread recognition of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) as quantitative biomarker. The purpose of this work was to introduce and characterize a dedicated microchannel phantom as a model for quantitative DCE-MRI measurements. METHODS: A perfusable, MR-compatible microchannel network was constructed on the basis of sacrificial melt-spun sugar fibers embedded in a block of epoxy resin. Structural analysis was performed on the basis of light microscopy images before DCE-MRI experiments. During dynamic acquisition the capillary network was perfused with a standard contrast agent injection system. Flow-dependency, as well as inter- and intrascanner reproducibility of the computed DCE parameters were evaluated using a 3.0 T whole-body MRI. RESULTS: Semi-quantitative and quantitative flow-related parameters exhibited the expected proportionality to the set flow rate (mean Pearson correlation coefficient: 0.991, P < 2.5e-5). The volume fraction was approximately independent from changes of the applied flow rate through the phantom. Repeatability and reproducibility experiments yielded maximum intrascanner coefficients of variation (CV) of 4.6% for quantitative parameters. All evaluated parameters were well in the range of known in vivo results for the applied flow rates. CONCLUSION: The constructed phantom enables reproducible, flow-dependent, contrast-enhanced MR measurements with the potential to facilitate standardization and comparability of DCE-MRI examinations.

Radiomic Analysis Reveals Prognostic Information in T1-Weighted Baseline Magnetic Resonance Imaging in Patients With Glioblastoma.

OBJECTIVES: The aim of this study was to investigate whether radiomic analysis with random survival forests (RSFs) can predict overall survival from T1-weighted contrast-enhanced baseline magnetic resonance imaging (MRI) scans in a cohort of glioblastoma multiforme (GBM) patients with uniform treatment. MATERIALS AND METHODS: This retrospective study was approved by the institutional review board and informed consent was waived. The MRI scans from 66 patients with newly diagnosed GBM from a previous prospective study were analyzed. Tumors were segmented manually on contrast-enhanced 3-dimensional T1-weighted images. Using these segmentations, P = 208 quantitative image features characterizing tumor shape, signal intensity, and texture were calculated in an automated fashion. On this data set, an RSF was trained using 10-fold cross validation to establish a link between image features and overall survival, and the individual risk for each patient was predicted. The mean concordance index was assessed as a measure of prediction accuracy. Association of individual risk with overall survival was assessed using Kaplan-Meier analysis and a univariate proportional hazards model. RESULTS: Mean overall survival was 14 months (range, 0.8-85 months). Mean concordance index of the 10-fold cross-validated RSF was 0.67. Kaplan-Meier analysis clearly distinguished 2 patient groups with high and low predicted individual risk (P = 5.5 × 10). Low predicted individual mortality was found to be a favorable prognostic factor for overall survival in a univariate Cox proportional hazards model (hazards ratio, 1.038; 95% confidence interval, 1.015-1.062; P = 0.0059). CONCLUSIONS: This study demonstrates that baseline MRI in GBM patients contains prognostic information, which can be accessed by radiomic analysis using RSFs.

Dynamic Contrast-Enhanced Magnetic Resonance Imaging Suggests Normal Perfusion in Normal-Appearing White Matter in Multiple Sclerosis.

OBJECTIVES: Multiple sclerosis (MS) is a chronic, inflammatory disease of the central nervous system and has been associated with reduced perfusion in normal-appearing white matter (NAWM). The magnitude of this hypoperfusion is unclear. The present study aims to quantify NAWM perfusion with dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) in patients with relapsing-remitting (RR) MS and in a control group. MATERIALS AND METHODS: The statistical power of a DCE-MRI acquisition to reveal hypoperfusion in MS was estimated using a Monte Carlo simulation: synthetic tissue curves with a contrast-to-noise ratio of 8 were generated for MS patients and control group using perfusion values reported in previous studies. A compartment-uptake model was fitted to these curves, yielding estimates of cerebral blood flow (CBF), cerebral blood volume (CBV), and permeability-surface area product (PS). This was repeated 1000 times. Mean and standard deviation of the resulting distributions were used to calculate the statistical power of a DCE-MRI study to detect perfusion differences between 16 control subjects and 24 MS subjects.In an institutional review board-approved study, patients with RR-MS (n = 24; mean age, 36 years; 17 women, mean Enhanced Disability Status Scale score, 3.25) and patients without history or symptoms of neurological disorder (n = 16; mean age, 49 years; 9 women) underwent a DCE-MRI examination with a previously established MRI protocol (3D SPGR sequence; 2.1 seconds temporal resolution; 44 slices; spatial resolution, 1.7 × 1.7 × 3 mm). Regions were defined manually in the middle cerebral artery; in the frontal, periventricular, and occipital NAWM; in the pons; and in the thalamus, and CBF, CBV, and PS were quantified using a compartment-uptake model.Parameter differences between MS and control groups were evaluated using a mixed linear model with subjects as random effect and controlling for age and sex. A P value of less than 0.05 was considered to indicate statistical significance. RESULTS: For all but one of previously reported effect sizes, the simulation study estimated a statistical power of 80% to 100% to detect reduced CBF in MS. In the patient study, mean (standard deviation) CBF in NAWM was 11.0 (15.1) and 10.4 (8.2) mL/100 mL per minute in the MS and control groups, respectively. Mean CBV in NAWM was 0.50 (0.45) mL/100 mL in the MS group and 0.48 (0.28) mL/100 mL in the control group. Mean values of PS in NAWM were 0.002 mL (0.027)/100 mL per minute in the control group and -0.001 (0.015) mL/100 mL per minute in the MS patients. Differences between patient groups were not statistically significant for CBF, CBV, mean transit time, and PS (P = 0.44, P = 0.20, P = 0.78, P = 0.66, respectively). In both groups, the influence of age on any parameter was nonsignificant. Cerebral blood flow and CBV in the thalamus and pons were significantly higher than in NAWM regions (P < 1e-4); mean transit time was significantly shorter than in NAWM (P < 1e-4). Permeability-surface area product was not significantly different from zero (P > 0.25) in all evaluated regions. CONCLUSIONS: Despite high statistical power, we could not confirm previous reports of NAWM hypoperfusion in MS. This indicates that, at least in our patient cohort, potential hypoperfusion is much less pronounced than reported in previous studies.

Intravoxel Incoherent Motion Magnetic Resonance Imaging in Partially Nephrectomized Kidneys.

OBJECTIVE: The aim of this study was to investigate the effects of partial nephrectomy (PN) in kidneys with solid renal masses on the apparent diffusion coefficient (ADC) and on intravoxel incoherent motion (IVIM)-based parameters using diffusion-weighted magnetic resonance imaging (DWI). METHODS: Fifteen patients with renal masses underwent DWI before and 1 week after PN on a clinical 3 T scanner using a single-shot echo planar imaging sequence with 10 diffusion weightings. Motion-corrected images were quantified using a monoexponential model fit to calculate ADCs and a segmented biexponential fit to calculate IVIM parameters f (perfusion fraction), Dslow and Dfast ("slow" and "fast" diffusion coefficients), as well as the pseudoflow (PF) Dfast × f. The median values derived from multislice (minimum of 3 slices) regions of interest encompassing the kidney cortex were used for statistical analysis. Estimated glomerular filtration rate values were calculated based on serum creatinine levels on each examination day using the Modification of Diet in Renal Disease formula. RESULTS: The follow-up measurement yielded significantly lower values in the partially nephrectomized kidneys compared with contralateral kidneys for the parameters ADC (P = 0.002), Dfast (P = 0.43), f (P = 0.001), and PF (P = 0.0008). Comparing baseline and follow-up, partially nephrectomized kidneys showed a significant decrease for ADC (P = 0.01), Dfast (P = 0.43), f (P = 0.002), and PF (P = 0.002). Nonnephrectomized kidneys expressed a significant increase for ADC (P = 0.01) and PF (P = 0.01). Follow-up Modification of Diet in Renal Disease showed positive correlations with all DWI parameters in the partially nephrectomized kidneys (ADC: r(2) = 0.63, P = 0.0004; Dfast: r(2) = 0.59, P = 0.0009; f: r(2) = 0.36, P = 0.018; PF: r(2) = 0.60, P = 0.00075) except for Dslow. CONCLUSIONS: Our study suggests that quantitative parameters derived from DWI are highly indicative of renal function. Apparent diffusion coefficients showed substantial differences in the renal cortex after PN, whereas an IVIM analysis delivered additional insight into kidney physiology. Quantitative DWI, particularly perfusion-related IVIM parameters, therefore demonstrated great potential as truly noninvasive biomarker to obtain information about single kidney function.

Monitoring early response to anti-angiogenic therapy: diffusion-weighted magnetic resonance imaging and volume measurements in colon carcinoma xenografts.

OBJECTIVES: To evaluate the use of diffusion-weighted MRI (DW-MRI) and volume measurements for early monitoring of antiangiogenic therapy in an experimental tumor model. MATERIALS AND METHODS: 23 athymic nude rats, bearing human colon carcinoma xenografts (HT-29) were examined before and after 6 days of treatment with regorafenib (n = 12) or placebo (n = 11) in a clinical 3-Tesla MRI. For DW-MRI, a single-shot EPI sequence with 9 b-values (10-800 s/mm2) was used. The apparent diffusion coefficient (ADC) was calculated voxelwise and its median value over a region of interest, covering the entire tumor, was defined as the tumor ADC. Tumor volume was determined using T2-weighted images. ADC and volume changes between first and second measurement were evaluated as classifiers by a receiver-operator-characteristic (ROC) analysis individually and combined using Fisher's linear discriminant analysis (FLDA). RESULTS: All ADCs and volumes are stated as median±standard deviation. Tumor ADC increased significantly in the therapy group (0.76±0.09×10(-3) mm2/s to 0.90±0.12×10(-3) mm2/s; p<0.001), with significantly higher changes of tumor ADC than in the control group (0.10±0.11×10(-3) mm2/s vs. 0.03±0.09×10(-3) mm2/s; p = 0.027). Tumor volume increased significantly in both groups (therapy: 347.8±449.1 to 405.3±823.6 mm3; p = 0.034; control: 219.7±79.5 to 443.7±141.5 mm3; p<0.001), however, the therapy group showed significantly reduced tumor growth (33.30±47.30% vs. 96.43±31.66%; p<0.001). Area under the curve and accuracy of the ADC-based ROC analysis were 0.773 and 78.3%; and for the volume change 0.886 and 82.6%. The FLDA approach yielded an AUC of 0.985 and an accuracy of 95.7%. CONCLUSIONS: Regorafenib therapy significantly increased tumor ADC after 6 days of treatment and also significantly reduced tumor growth. However, ROC analyses using each parameter individually revealed a lack of accuracy in discriminating between therapy and control group. The combination of both parameters using FLDA substantially improved diagnostic accuracy, thus highlighting the potential of multi-parameter MRI as an imaging biomarker for non-invasive early tumor therapy monitoring.