Improved nerve conspicuity with water-weighting and denoising in two-point Dixon magnetic resonance neurography

BackgroundT₂-weighted, two-point Dixon fast-spin-echo (FSE) is an effective technique for magnetic resonance neurography (MRN) that can provide quantitative assessment of muscle denervation. Low signal-to-noise ratio and inadequate fat suppression, however, can impede accurate interpretation.PurposeTo quantify effects of principal component analysis (PCA) denoising on tissue signal intensities and fat fraction (FF) and to determine qualitative image quality improvements from both denoising and water-weighting (WW) algorithms to improve nerve conspicuity and fat suppression.Study typeProspective.SubjectsTwenty-one subjects undergoing MR neurography evaluation (11/10 male/female, mean age = 46.3±13.7 years) with 60 image volumes. Twelve subjects (23 image volumes) were determined to have muscle denervation based on diffusely elevated T₂ signal intensity.Field strength/sequence3 T, 2D, two-point Dixon FSE.AssessmentQualitative assessment included overall image quality, nerve conspicuity, fat suppression, pulsation and ringing artifacts by 3 radiologists separately on a three-point scale (1 = poor, 2 = average, 3 = excellent). Quantitative measurements for FF and signal intensity relative to normal muscle were made for nerve, abnormal muscle and subcutaneous fat.Statistical testsLinear and ordinal regression models were used for quantitative and qualitative comparisons, respectively; 95% confidence intervals (CIs) and p-values for pairwise comparisons were adjusted using the Holm-Bonferroni method. Inter-rater agreement was assessed using Gwet's agreement coefficient (AC₂).ResultsSimulations showed PCA-denoising reduced FF error from 2.0% to 1.0%, and from 7.6% to 3.1% at noise levels of 10% and 30%, respectively. In human subjects, PCA-denoising did not change signal levels and FF quantitatively. WW decreased fat signal significantly (−83.6%, p < 0.001). Nerve conspicuity was improved by WW (odds ratio, OR = 5.8, p < 0.001). Fat suppression was improved by both PCA (OR = 3.6, p < 0.001) and WW (OR = 2.2, p < 0.001). Overall image quality was improved by PCA + WW (OR = 1.7, p = 0.04).ConclusionsWW and PCA-denoising improved nerve conspicuity and fat suppression in MR neurography. Denoising can potentially provide improved accuracy of FF maps for assessing fat-infiltrated muscle.     

Accuracy and reproducibility of automated white matter hyperintensities segmentation with lesion segmentation tool: A European multi-site 3T study

Brain vascular damage accumulate in aging and often manifest as white matter hyperintensities (WMHs) on MRI. Despite increased interest in automated methods to segment WMHs, a gold standard has not been achieved and their longitudinal reproducibility has been poorly investigated. The aim of present work is to evaluate accuracy and reproducibility of two freely available segmentation algorithms. A harmonized MRI protocol was implemented in 3T-scanners across 13 European sites, each scanning five volunteers twice (test-retest) using 2D-FLAIR. Automated segmentation was performed using Lesion segmentation tool algorithms (LST): the Lesion growth algorithm (LGA) in SPM8 and 12 and the Lesion prediction algorithm (LPA). To assess reproducibility, we applied the LST longitudinal pipeline to the LGA and LPA outputs for both the test and retest scans. We evaluated volumetric and spatial accuracy comparing LGA and LPA with manual tracing, and for reproducibility the test versus retest. Median volume difference between automated WMH and manual segmentations (mL) was −0.22[IQR = 0.50] for LGA-SPM8, −0.12[0.57] for LGA-SPM12, −0.09[0.53] for LPA, while the spatial accuracy (Dice Coefficient) was 0.29[0.31], 0.33[0.26] and 0.41[0.23], respectively. The reproducibility analysis showed a median reproducibility error of 20%[IQR = 41] for LGA-SPM8, 14% [31] for LGA-SPM12 and 10% [27] with the LPA cross-sectional pipeline. Applying the LST longitudinal pipeline, the reproducibility errors were considerably reduced (LGA: 0%[IQR = 0], p < 0.001; LPA: 0% [3], p < 0.001) compared to those derived using the cross-sectional algorithms. The DC using the longitudinal pipeline was excellent (median = 1) for LGA [IQR = 0] and LPA [0.02]. LST algorithms showed moderate accuracy and good reproducibility. Therefore, it can be used as a reliable cross-sectional and longitudinal tool in multi-site studies.     

Machine learning based quantification of ejection and filling parameters by fully automated dynamic measurement of left ventricular volumes from cardiac magnetic resonance images

BackgroundAlthough analysis of cardiac magnetic resonance (CMR) images provides accurate and reproducible measurements of left ventricular (LV) volumes, these measurements are usually not performed throughout the cardiac cycle because of lack of tools that would allow such analysis within a reasonable timeframe. A fully-automated machine-learning (ML) algorithm was recently developed to automatically generate LV volume-time curves. Our aim was to validate ejection and filling parameters calculated from these curves using conventional analysis as a reference.MethodsWe studied 21 patients undergoing clinical CMR examinations. LV volume-time curves were obtained using the ML-based algorithm (Neosoft), and independently using slice-by-slice, frame-by-frame manual tracing of the endocardial boundaries. Ejection and filling parameters derived from these curves were compared between the two techniques. For each parameter, Bland-Altman bias and limits of agreement (LOA) were expressed in percent of the mean measured value.ResultsTime-volume curves were generated using the automated ML analysis within 2.5 ± 0.5 min, considerably faster than the manual analysis (43 ± 14 min per patient, including ~10 slices with 25–32 frames per slice). Time-volume curves were similar between the two techniques in magnitude and shape. Size and function parameters extracted from these curves showed no significant inter-technique differences, reflected by high correlations, small biases (<10%) and mostly reasonably narrow LOA.ConclusionML software for dynamic LV volume measurement allows fast and accurate, fully automated analysis of ejection and filling parameters, compared to manual tracing based analysis. The ability to quickly evaluate time-volume curves is important for a more comprehensive evaluation of the patient's cardiac function.     

Automated analysis of immediate reliability of T2 and T2* relaxation times of hip joint cartilage from 3 T MR examinations

BackgroundMagnetic resonance (MR) T2 and T2* mapping sequences allow in vivo quantification of biochemical characteristics within joint cartilage of relevance to clinical assessment of conditions such as hip osteoarthritis (OA).PurposeTo evaluate an automated immediate reliability analysis of T2 and T2* mapping from MR examinations of hip joint cartilage using a bone and cartilage segmentation pipeline based around focused shape modelling.Study typeTechnical validation.Subjects17 asymptomatic volunteers (M: F 7:10, aged 22–47 years, mass 50–90 kg, height 163-189 cm) underwent unilateral hip joint MR examinations. Automated analysis of cartilage T2 and T2* data immediate reliability was evaluated in 9 subjects (M: F 4: 5) for each sequence.Field strength/sequenceA 3 T MR system with a body matrix flex-coil was used to acquire images with the following sequences: T2 weighted 3D-trueFast Imaging with Steady-State Precession (water excitation; 10.18 ms repetition time (TR); 4.3 ms echo time (TE); Voxel Size (VS): 0.625 × 0.625 × 0.65 mm; 160 mm field of view (FOV); Flip Angle (FA): 30 degrees; Pixel Bandwidth (PB): 140 Hz/pixel); a multi-echo spin echo (MESE) T2 mapping sequence (TR/TE: 2080/18–90 ms (5 echoes); VS: 4 × 0.78 × 0.78 mm; FOV: 200 mm; FA: 180 degrees; PB: 230 Hz/pixel) and a MESE T2* mapping sequence (TR/TE: 873/3.82–19.1 ms (5 echoes); VS: 3 × 0.625 × 0.625 mm; FOV: 160 mm; FA: 25 degrees; PB: 250 Hz/pixel).AssessmentAutomated cartilage segmentation and quantitative analysis provided T2 and T2* data from test-retest MR examinations to assess immediate reliability.Statistical testsCoefficient of variation (CV) and intraclass correlations (ICC_{2, 1}) to analyse automated T2 and T2* mapping reliability focusing on the clinically important superior cartilage regions of the hip joint.ResultsComparisons between test-retest T2 and (T2*) data revealed mean CV's of 3.385% (1.25%), mean ICC_{2, 1}′s of 0.871 (0.984) and median mean differences of −1.139ms (+0.195ms).ConclusionThe T2 and T2* times from automated analyses of hip cartilage from test-retest MR examinations had high (T2) and excellent (T2*) immediate reliability.     

Should abbreviated breast MRI be compliant with American College of Radiology requirements for MRI accreditation?

ObjectiveTo evaluate non-inferiority and diagnostic performance of an American College of Radiology compliant abbreviated MRI protocol (AB-MRI) compared with standard-of-care breast MRI (SOC-BMRI) in patients with increased breast cancer risk.Material and methodsWomen with increased lifetime breast cancer risk by American Cancer Society guidelines underwent breast MRI at a single institution between October 2015 and February 2018. AB-MRI was acquired at 3.0 T with T2-weighted extended fast spin echo triple-echo Dixon and pre- and post-contrast 3D dual-echo fast spoiled gradient echo two-point Dixon sequences with an 8-channel breast coil 1–7 days after SOC-BMRI. Three readers independently reviewed AB-MRI and assigned BI-RADS categories for maximum intensity projection images (AB1), dynamic contrast-enhanced (DCE) images (AB2), and DCE and non-contrast T2 and fat-only images (AB3). These scores were compared to those from SOC-BMRI.ResultsCancer yield was 14 per 1000 (women-years) in 73 women aged 26–75 years (mean 53.5 years). AB-MRI acquisition times (mean 9.63 min) and table times (mean 15.07 min) were significantly shorter than those of SOC-BMRI (means 19.46 and 36.3 min, respectively) (p < .001). Accuracy, sensitivity, specificity, and positive and negative predictive values were identical for AB3 and SOC-BMRI (93%, 100%, 93%, 16.7%, and 100%, respectively). AB-MRI with AB1 and AB2 had significantly lower specificity (AB1 = 73.6%, AB2 = 77.8%), positive predictive values (AB1 = 5%, AB2 = 5.9%), and accuracy (AB1 = 74%, AB2 = 78%) than those of SOC-BMRI (p = .002 for AB1, p = .01 for AB2).ConclusionAB-MRI was acquired significantly faster than SOC-BMRI and its diagnostic performance was non-inferior. Inclusion of T2 and fat-only images was necessary to achieve non-inferiority by multireader evaluation.     

A fast method for the quantification of fat fraction and relaxation times: Comparison of five sites of bone marrow

PurposeBone marrow is found either as red bone marrow, which mainly contains haematopoietic cells, or yellow bone marrow, which mainly contains adipocytes. In adults, red bone marrow is principally located in the axial skeleton. A recent study has introduced a method to simultaneously estimate the fat fraction (FF), the T1 and T2* relaxation times of water (T1w, T2*w) and fat (T1f and T2*f) in the vertebral bone marrow. The aim of the current study was to measure FF, T1w, T1f, T2*w and T2*f in five sites of bone marrow, and to assess the presence of regional variations.MethodsMRI experiments were performed at 1.5 T on five healthy volunteers (31.6 ± 15.6 years) using a prototype chemical-shift-encoded 3D multi-gradient-echo sequence (VIBE) acquired with two flip angles. Acquisitions were performed in the shoulders, lumbar spine and pelvis, with acquisition times of < 25 seconds per sequence. Signal intensities of magnitude images of the individual echoes were used to fit the signal and compute FF, T1w, T1f, T2*w and T2*f in the humerus, sternum, vertebra, ilium and femur.ResultsRegional variations of fat fraction and relaxation times were observed in these sites, with higher fat fraction and longer T1w in the epiphyses of long bones. A high correlation between FF and T1w was measured in these bones (R = 0.84 in the humerus and R = 0.84 in the femur). In most sites, there was a significant difference between water and fat relaxation times, attesting the relevance of measuring these parameters separately.ConclusionThe method proposed in the current study allowed for measurements of FF, T1w, T1f, T2*w and T2*f in five sites of bone marrow. Regional variations of these parameters were observed and a strong negative correlation between the T1 of water and the fat fraction in bones with high fat fractions was found.     

Preliminary quantitative analysis of vertebral microenvironment changes in type 2 diabetes mellitus using FOCUS IVIM-DWI and IDEAL-IQ sequences

PurposeTo explore the application of intravoxel incoherent motion diffusion-weighted imaging(IVIM-DWI) on account of field-of-view optimized and constrained undistorted single shot (FOCUS) and iteraterative decomposition of water and fat with echo asymmetry and least-squares estimation quantitation(IDEAL-IQ) sequences in evaluating the vertebral microenvironment changes of type 2 diabetes mellitus(T2DM) patients and the correlation with bone mineral density(BMD).Method128 T2DM patients (mean age 63.4 ± 5.28 years) underwent both dual-energy X-ray absorptiometry (DEXA) and spine MRI. The FOCUS IVIM-DWI and IDEAL-IQ derived parameters of the vertebral body(L1, L2, L3, L4)were measured on corresponding maps of the lumbar spine. The subjects were divided into 3 groups according to T-scores as follows: normal (n = 37), osteopenia (n = 43), and osteoporosis(n = 48) group.One-way analysis of variance (ANOVA) were used to compare the vertebral parameters(ADC_slow, ADC_fast, f, FF, R2*) among three BMD cohorts.Receiver operating characteristic (ROC) analyses and Spearman's rank correlation were performed to test the diagnostic performance and the correlation between them respectively.ResultsThere were significant differences in vertebral ADC_slow, ADC_fast, FF and R2* between the three groups (P < 0.05).Statistically, BMD was moderately negatively correlated with FF (r = −0.584, P < 0.001) and weakly positively with ADC_slow (r = 0.334, P < 0.001), meanwhile moderately positively correlated with R2*(r = 0.509, P < 0.001) and ADC_fast(0.545, P < 0.001).ADC_fast was moderately negatively correlated with FF (r = −0.417, P < 0.001), weakly positively correlated with R2*(0.359, P < 0.001).Compared with the area under the curve (AUC) of ADC_slow, ADC_fast, FF and R2*, the AUC of ADC_fast was higher in identifying between normal and abnormal(osteopenia and osteoporosis), normal from osteopenia, while the AUC of FF was higher in identifying osteopenia from osteoporosis.ConclusionsFOCUS IVIM-DWI and IDEAL-IQ of lumbar spine might be useful to evaluate the vertebral microenvironment changes of T2DM patients.     

Noninvasive assessment of abdominal adipose tissues and quantification of hepatic and pancreatic fat fractions in type 2 diabetes mellitus

The purpose of this study was to evaluate adipose tissue distributions and hepatic and pancreatic fat contents using a 6-point Dixon MRI technique in type 2 diabetes mellitus (T2DM), and to assess associations between fat distributions and biochemical markers of insulin resistance. Intra-abdominal MRI was investigated in 14 T2DM patients, 13 age- and sex-matched healthy controls (HC) and 11 young HC using a 3 T Prisma MRI scanner. All T2DM subjects completed a fasting comprehensive metabolic panel, and demographic measurements were taken according to standardized methodologies. We observed excellent correlation (R² = 0.94) between hepatic fat fraction quantified using 6-point Dixon MRI and gold standard MRS, establishing the accuracy and reliability of the Dixon technique. Significantly increased visceral adipose tissue (VAT) volumes were found in T2DM patients compared to age-matched HC (1569.81 ± 670.62 cm³ vs. 1106.60 ± 566.85 cm³, p = .04). We also observed a trend of increasing subcutaneous adipose tissues (SAT), and total abdominal fat (TAT) volumes in T2DM compared to age-matched HC. Hepatic fat fraction percentage (HFF%) was 44.6% higher in T2DM compared to age-matched HC and 64.4% higher compared to young HC. Pancreatic fat fractions in the head and body/tail were higher in T2DM patients compared to both healthy cohorts. We also observed correlations between fat contents of the liver and pancreas in T2DM patients, and association between biochemical markers of T2DM with HFF, indicating a risk for non-alcoholic fatty liver disease among T2DM. In summary, this study provides evidence of T2DM patients having increased liver and pancreatic fat, as well as increased adipose tissues.     

Relationship between Perceived Leg Length Discrepancy at One Month and Preoperative Hip Abductor Muscle Elasticity in Patients after Total Hip Arthroplasty

Objective: Preoperative factors related to perceived leg length discrepancy (PLLD) after total hip arthroplasty (THA) are not well studied. This study aimed to examine the preoperative factors, including hip abductor modulus, related to PLLD one month after THA. Methods: The study included 73 patients diagnosed with osteoarthritis secondary to developmental dysplasia of the hip and a posterior approach to surgery. Multiple logistic regression analysis was performed using the presence or absence of PLLD as the dependent variable and preoperative hip abductor''s modulus of elasticity, pain, hip abduction range of motion, hip abductor muscle strength and pelvic obliquity as the independent variable. Additionally, receiver operating characteristic curves were used for the extracted variables for calculating the cutoffs, sensitivity, specificity and area under the curve (AUC) to determine the presence or absence of PLLD. The significance level was set at p<0.05. Results: The hip abductor modulus (odds ratio=1.13; 95% confidence interval=1.06-1.21; p<0.001) was selected as a preoperative factor. The cutoff value to determine the presence or absence of a PLLD was 16.32 kPa. The sensitivity and specificity were 81.8% and 72.5%, respectively, and the AUC was 0.8137. Conclusion: The hip abductor muscle elastic modulus affected PLLD one month after THA. If the preoperative hip abductor elastic modulus is higher than the cutoff value, it may affect the appearance of PLLD at one month postoperatively.     

The NMDA antagonist memantine affects training induced motor cortex plasticity – a study using transcranial magnetic stimulation [ISRCTN65784760]

Background  

Training of a repetitive synchronised movement of two limb muscles leads to short-term plastic changes in the primary motor cortex, which can be assessed by transcranial magnetic stimulation (TMS) mapping. We used this paradigm to study the effect of memantine, a NDMA antagonist, on short-term motor cortex plasticity in 20 healthy human subjects, and we were especially interested in possible differential effects of different treatment regimens. In a randomised double-blinded cross over study design we therefore administered placebo or memantine either as a single dosage or as an ascending dosage over 8 days. Before and after one hour of motor training, which consisted of a repetitive co-contraction of the abductor pollicis brevis (APB) and the deltoid muscle, we assessed the motor output map of the APB muscle by TMS under the different conditions.     

Quantitative Dixon MRI sequences to relate muscle atrophy and fatty degeneration with range of motion and muscle force in brachial plexus injury

BackgroundAssessment of muscle atrophy and fatty degeneration in brachial plexus injury (BPI) could yield valuable insight into pathophysiology and could be used to predict clinical outcome. The objective of this study was to quantify and relate fat percentage and cross-sectional area (CSA) of the biceps to range of motion and muscle force of traumatic brachial plexus injury (BPI) patients.MethodsT1-weighted TSE sequence and three-point Dixon images of the affected and non-affected biceps brachii were acquired on a 3 Tesla magnetic resonance scanner to determine the fat percentage, total and contractile CSA of 20 adult BPI patients. Regions of interest were drawn by two independent investigators to determine the inter-observer reliability. Paired Students' t-test and multivariate analysis were used to relate fat percentage, total and contractile CSA to active flexion and biceps muscle force.ResultsThe mean fat percentage 12 ± 5.1% of affected biceps was higher than 6 ± 1.0% of the non-affected biceps (p < 0.001). The mean contractile CSA 8.1 ± 5.1 cm² of the affected biceps was lower than 19.4 ± 4.9 cm² of the non-affected biceps (p < 0.001). The inter-observer reliability was excellent (ICC 0.82 to 0.96). The contractile CSA contributed most to the reduction in active flexion and muscle force.ConclusionQuantitative measurement of fat percentage, total and contractile CSA using three-point Dixon sequences provides an excellent reliability and relates with active flexion and muscle force in BPI.     

Group delay method for MRI aortic pulse wave velocity measurements in clinical protocols with low temporal resolution: Validation in a heterogeneous cohort

BackgroundMRI assessment of aortic pulse wave velocity (PWV) helps predict the risk of vascular events, but the recommended phase contrast sampling rate is faster than what is utilized in most clinical sequences. There are many existing MRI databases obtained for assessment of cardiac output using lower temporal frequency sampling where information might be obtained about aortic stiffness (PWV). In this work, we sought to evaluate whether the Group Delay (GD) method can generate a reproducible measure of stiffness and describe expected age-related stiffening of the aortic arch using lower sampling rates in standard clinical sequences.MethodsPhase contrast (PC) MRI was obtained on the ascending and descending aortic arch in a heterogeneous adult cohort (n = 23; 9 women) spanning over a wide range of ages (ages 24–89, mean 49.4 ± 18.4). Data was collected with standard cardiac MRI protocols for cardiac output evaluation (repetition time = 7.8 ms, views-per-segment = 4, encoding velocity = 200 cm/s). Pulse wave transit times (TT) were computed using the GD method, two other validated automated approaches (cross correlation TT Algorithm by Gaddum and Segment by Medviso), and the manual tangent method. Pressure waveforms from tonometry and flow waveforms from PC MRI were used to assess wave reflections.ResultsGroup Delay and TT-Algorithm showed significant and high retest reproducibility (r = 0.86 for both) as well as high PWV correlation with age (r = 0.93, P-value < 0.00005 and r = 0.96, P-value < 0.00005 respectively) and with each other (r = 0.94, P-value < 0.00001, RMSE = 0.94 m/s). Arbitrary altering of the image acquisition trigger in the GD method introduced error of 10%–13%, but the TT-algorithm error range was 11%–25%.ConclusionGroup Delay enables reproducible assessment of transit time to derive PWV from low temporal resolution clinical cardiac MRI sequences that can also identify age-related stiffening.     

Estimating cerebral venous oxygenation in human fetuses with ventriculomegaly using quantitative susceptibility mapping

Rationale and objectivesThe goal of this study was to estimate venous blood oxygen saturation (SvO2) in the superior sagittal sinus (SSS) in fetal brains with ventriculomegaly (VM) using quantitative susceptibility mapping (QSM).Materials and methodsA radiofrequency spoiled gradient echo sequence was used to evaluate data on 19 fetuses with VM (gestational age(GA): median = 29.9 weeks (range 23 to 37.3 weeks)) and 20 healthy fetuses (GA: median = 30.9 (range 22.7 to 38.7 weeks)) at 1.5 T. Susceptibility weighted images encompassing the entire fetal brain were acquired within 1 min. An iterative, geometry constraint-based thresholded k-space division algorithm was used for generating QSM data of the fetal brain. The venous oxygen saturation was calculated using the magnetic susceptibility of the SSS obtained from the QSM data. Mixed-model analysis of variance and interobserver variability assessment were used to analyze the results.ResultsThe median SvO2 values in the entire VM cohort as well as for second and third trimester fetuses (with interquartile range) were: 67.8% (63.2%, 73.6%), 73.1% (69.1%, 77.3%) and 63.8% (59.4%, 68.1%), respectively. The corresponding median SvO2 value in the healthy control group was: 65.3% (58.3%, 68.2%), 67.5% (61.7%, 69.2%) and 60.8% (53.6%, 68.2%), respectively. However, the difference of SvO2 between VM and control groups was not significant at the p = 0.05 level (p = 0.076). The SvO2 was found decreasing significantly with GA in the healthy control group (p < 0.05).ConclusionsWe report for the first time the estimation of cerebral SvO2 in human fetuses with VM using QSM. This measure of oxygen saturation might be beneficial in assessing and monitoring the metabolic status of the fetus in various clinical conditions.     

Measuring extraocular muscle volume using dynamic contours

The effect of medical treatment on extraocular muscle enlargement in thyroid associated ophthalmopathy (TAO) may be monitored by measuring the change in volume of the extraocular muscles on serial orbital MRI examinations. In theory, 3D image sets offer the opportunity to minimise errors due to poor repositioning and partial volume effects. This study describes an automated technique for estimating extraocular muscle volumes from 3D datasets. Operator input is minimal and the technique is robust. Verification of the technique on both simulated and real datasets is described. For simulated image sets, both automated segmentation and manual outlining produced estimates of volume which were on average 4% less than "true" volume. For real patient data, extraocular muscle volumes measured by the automated technique were 1.6% (SD 13%) less than volumes measured by manual outlining. Coefficient of variation for repeat outlining of the same image dataset for the automated technique was 1.0%, compared with 4% for manual outlining. The manual technique took an experienced operator approximately 20 min to perform, compared to 7 min for the automated technique. The automated method is therefore rapid, reproducible and at least as accurate as other available methods.     

Three-dimensional adiabatic inversion recovery prepared ultrashort echo time cones (3D IR-UTE-Cones) imaging of cortical bone in the hip

PurposeWe present three-dimensional adiabatic inversion recovery prepared ultrashort echo time Cones (3D IR-UTE-Cones) imaging of cortical bone in the hip of healthy volunteers using a clinical 3T scanner.MethodsA 3D IR-UTE-Cones sequence, based on a short pulse excitation followed by a 3D Cones trajectory, with a nominal TE of 32 μs, was employed for high contrast morphological imaging of cortical bone in the hip of heathy volunteers. Signals from soft tissues such as muscle and marrow fat were suppressed via adiabatic inversion and signal nulling. T₂^⁎ value of the cortical bone was also calculated based on 3D IR-UTE-Cones acquisitions with a series of TEs ranging from 0.032 to 0.8 ms. A total of four healthy volunteers were recruited for this study. Average T₂^⁎ values and the standard deviation for four regions of interests (ROIs) at the greater trochanter, the femoral neck, the femoral head and the lesser trochanter were calculated.ResultsThe 3D IR-UTE-Cones sequence provided efficient suppression of soft tissues with excellent image contrast for cortical bone visualization in all volunteer hips. Exponential single component decay was observed for all ROIs, with averaged T₂^⁎ values ranging from 0.33 to 0.45 ms, largely consistent with previously reported T₂^⁎ values of cortical bone in the tibial midshaft.ConclusionsThe 3D IR-UTE-Cones sequence allows in vivo volumetric imaging and quantitative T₂^⁎ measurement of cortical bone in the hip using a clinical 3T scanner.     

Correlation between Hepatic Fat Content Using 3-Echo 3-D Dixon Method and Intravoxel Incoherent Motion (IVIM) Perfusion MR Imaging

Fat accumulates as droplets in the hepatocyte swelling, distortion of microcirculatory anatomy and compression of sinus. This study aims to investigate the correlation between the T2*-corrected fat fraction (FF) value acquired via gradient echo with a low flip angle and parenchymal pseudorandom blood perfusion (P _fraction), microcirculation (D _fast), and slow component of diffusion (D _slow), acquired via intravoxel incoherent motion (IVIM), and to investigate the blood microcirculation and diffusion components of liver parenchyma, according to fat deposition. A total of 126 patients underwent 3-T magnetic resonance imaging, including a 3-echo three-dimensional (3-D) gradient echo sequence with T2*-corrected Dixon reconstruction and IVIM sequence. Pearson’s correlation analysis was conducted to investigate the correlation of the FF obtained via the Dixon method with the apparent diffusion coefficient (ADC), D _slow, P _fraction, and D _fast obtained via IVIM. Correlation analysis was also conducted for the IVIM mapping images. A confidence level of p < 0.05 was set. A negative correlation was found between the T2*-corrected FF acquired using the 3-echo 3-D Dixon method and D _slow acquired via IVIM (r = ?0.181, p < 0.05). It was likely due to the increased extracellular collagen deposition and increased intracellular fat droplets during the progression of liver fibrosis.     

Clinical feasibility of 3D-QALAS – Single breath-hold 3D myocardial T1- and T2-mapping

PurposeTo investigate the in-vivo precision and clinical feasibility of 3D-QALAS - a novel method for simultaneous three-dimensional myocardial T1- and T2-mapping.MethodsTen healthy subjects and 23 patients with different cardiac pathologies underwent cardiovascular 3 T MRI examinations including 3D-QALAS, MOLLI and T2-GraSE acquisitions. Precision was investigated in the healthy subjects between independent scans, between dependent scans and as standard deviation of consecutive scans. Clinical feasibility of 3D-QALAS was investigated for native and contrast enhanced myocardium in patients. Data were analyzed using mean value and 95% confidence interval, Pearson correlation, Paired t-tests, intraclass correlation and Bland-Altman analysis.ResultsAverage myocardial relaxation time values and SD from eight repeated acquisitions within the group of healthy subjects were 1178 ± 18.5 ms (1.6%) for T1 with 3D-QALAS, 52.7 ± 1.2 ms (2.3%) for T2 with 3D-QALAS, 1145 ± 10.0 ms (0.9%) for T1 with MOLLI and 49.2 ± 0.8 ms (1.6%) for T2 with GraSE.Myocardial T1 and T2 relaxation times obtained with 3D-QALAS correlated very well with reference methods; MOLLI for T1 (r = 0.994) and T2-GraSE for T2 (r = 0.818) in the 23 patients. Average native/post-contrast myocardial T1 values from the patients were 1166.2 ms/411.8 ms for 3D-QALAS and 1174.4 ms/438.9 ms for MOLLI. Average native myocardial T2 values from the patients were 53.2 ms for 3D-QALAS and 54.4 ms for T2-GraSE.ConclusionsRepeated independent and dependent scans together with the intra-scan repeatability, demonstrated all a very good precision for the 3D-QALAS method in healthy volunteers. This study shows that 3D T1 and T2 mapping in the left ventricle is feasible in one breath hold for patients with different cardiac pathologies using 3D-QALAS.     

Segmentation of whole breast and fibroglandular tissue using nnU-Net in dynamic contrast enhanced MR images

PurposeSegmentation of the whole breast and fibroglandular tissue (FGT) is important for quantitatively analyzing the breast cancer risk in the dynamic contrast-enhanced magnetic resonance (DCE-MR) images. The purpose of this study is to improve the accuracy and efficiency of the segmentation of the whole breast and FGT in 3-D fat-suppressed DCE-MR images with a versatile deep learning (DL) framework.MethodsWe randomly collected 100 breast DCE-MR scans from Shanghai Cancer Hospital of Fudan University. The MR scans in the dataset were different in both the spatial resolution and the MR scanners employed. Furthermore, four breast density categories were assessed by radiologists based on Breast Imaging Reporting and Data System (BI-RADS) of American College of Radiology. The dataset was separated into the training and the testing sets, while keeping a balanced distribution of scans with different imaging parameters and density categories. The nnU-Net has been recently proposed to automatically adapt preprocessing strategies and network architectures for a given medical image dataset, thus showing a great potential in the systematic adaptation of DL methods to different datasets. In this study, we applied the nnU-Net to segment the whole breast and FGT in 3-D fat-suppressed DCE-MR images. Five-fold cross validation was employed to train and validate the segmentation method.ResultsThe segmentation performance was evaluated with the volume and surface agreement metrics between the DL-based automatic and the manually delineated masks, as quantified with the following measures: the average Dice volume overlap (0.968 ± 0.017 and 0.877 ± 0.081), the average surface distances (0.201 ± 0.080 mm and 0.310 ± 0.043 mm), and the Pearson correlation coefficient of masks (0.995 and 0.972) between the automatic and the manually delineated masks, as calculated for the whole breast and the FGT segmentation, respectively. The correlation coefficient between the breast densities obtained with the DL-based segmentation and the manual delineation was 0.981. There was a positive bias of 0.8% (DL-based relative to manual) in breast density measurement with the Bland-Altman plot. The execution time of the DL-based segmentation was approximately 20 s for the whole breast segmentation and 15 s for the FGT segmentation.ConclusionsOur DL-based segmentation framework using nnU-Net could robustly achieve high accuracy and efficiency across variable MR imaging settings without extra pre- or post-processing procedures. It would be useful for developing DCE-MR-based CAD systems to quantify breast cancer risk and to be integrated into the clinical workflow.     

Quantifying global-brain metabolite level changes with whole-head proton MR spectroscopy at 3 T

Background and purposeTo assess the sensitivity of non-localized, whole-head ¹H-MRS to an individual's serial changes in total-brain NAA, Glx, Cr and Cho concentrations — metabolite metrics often used as surrogate markers in neurological pathologies.Materials and methodsIn this prospective study, four back-to-back (single imaging session) and three serial (successive sessions) non-localizing, ~3 min ¹H-MRS (TE/TR/TI = 5/10⁴/940 ms) scans were performed on 18 healthy young volunteers: 9 women, 9 men: 29.9 ± 7.6 [mean ± standard deviation (SD)] years old. These were analyzed by calculating a within-subject coefficient of variation (CV = SD/mean) to assess intra- and inter-scan repeatability and prediction intervals. This study was Health Insurance Portability and Accountability Act compliant. All subjects gave institutional review board-approved written, informed consent.ResultsThe intra-scan CVs for the NAA, Glx, Cr and Cho were: 3.9 ± 1.8%, 7.3 ± 4.6%, 4.0 ± 3.4% and 2.5 ± 1.6%, and the corresponding inter-scan (longitudinal) values were: 7.0 ± 3.1%, 10.6 ± 5.6%, 7.6 ± 3.5% and 7.0 ± 3.9%. This method is shown to have 80% power to detect changes of 14%, 27%, 26% and 19% between two serial measurements in a given individual.ConclusionsSubject to the assumption that in neurological disorders NAA, Glx, Cr and Cho changes represent brain-only pathology and not muscles, bone marrow, adipose tissue or epithelial cells, this approach enables us to quantify them, thereby adding specificity to the assessment of the total disease load. This will facilitate monitoring diffuse pathologies with faster measurement, more extensive (~90% of the brain) spatial coverage and sensitivity than localized ¹H-MRS.