Multi-echo Magnetic Resonance Imaging Research Articles

Influence of echo time on pulmonary ventilation and perfusion derived by phase-resolved functional lung (PREFUL) MRI using multi-echo ultrashort echo time acquisition.

Non-contrast enhanced 1H magnetic resonance imaging (MRI) is promising for ventilation/perfusion (V/Q) assessment of the lung but the influence of the echo time (TE) on V/Q parameters is lacking. Therefore, the purpose of this study was to investigate the influence of different TEs on pulmonary V/Q parameters derived by phase-resolved functional lung (PREFUL) MRI using a multi-echo ultrashort TE (UTE) acquisition. A 2D multi-echo UTE sequence with radial center out readout and tiny golden angle increment was developed. Forty-eight participants were enrolled in this study: 25 healthy subjects, six patients with asthma, and 17 patients with pulmonary fibrosis. Participants underwent two acquisitions of 2D multi-echo UTE MRI with three TEs per acquisition (TE1-6: 0.07, 0.82, 1.72, 2.47, 3.37, and 4.12 ms). Regional ventilation (RVent), flow-volume loop cross-correlation metric (FVL-CM), and normalized perfusion-weighted signal (QN) maps were calculated. V/Q defect percentages (VDP/QDP) were determined. To assess repeatability, the measurement was repeated in healthy subjects. Median and interquartile range of RVent, FVL-CM, QN, VDP, and QDP were calculated. To assess significant differences between parameters obtained at different TEs, Friedman's test and Dunnett's test were performed. Pearson correlation coefficients between RVent derived at TE1 and the difference in RVent between TE2,3 and TE1 were calculated. For repeatability assessment, coefficient of variation (CoV) and intraclass correlation coefficient (ICC) were determined. Significant differences were found comparing V/Q parameters obtained at TE3-6 compared to TE1. CoV increased with TE. For ICC, values between 0.35 (QDP at TE1) and 0.83 (VDPRVent at TE2) were obtained for T1,2. Statistically significant differences for ventilation and perfusion parameters derived by PREFUL were found for TE3-6 compared to TE1. All V/Q parameters were well repeatable for TE1-2. With increasing TE and respiratory volume, RVent shows a T2*-dependency leading to biased ventilation assessment compared to TE1.

MRI assessment of adipose tissue fatty acid composition in the UK Biobank and its association with diet and disease.

This study aimed to assess the fatty acid (FA) composition of abdominal subcutaneous and visceral adipose tissue (ASAT and VAT, respectively) in the UK Biobank imaging cohort (N = 33,823) using magnetic resonance imaging (MRI). We measured the fractions of saturated, monounsaturated, and polyunsaturated FA (fSFA, fMUFA, and fPUFA, respectively) in ASAT and VAT from multiecho MRI scans. We selected a subcohort of participants who followed a vegan and an omnivore diet (N = 36) to validate the effect of diet on adipose tissue. In the wider imaging cohort, we examined the relationships between adipose tissue FA composition and various traits related to disease and body size. We measured adipose tissue FA composition for over 33,000 participants, revealing higher fSFA and fPUFA and lower fMUFA in VAT (p < 0.00016). fMUFA and fPUFA were higher in ASAT and lower in VAT for women (p < 0.00016). Vegan participants exhibited lower fSFA in both ASAT and VAT (p < 0.00016). VAT fSFA and fMUFA showed significant associations with disease, as well as anthropometric variables. This extensive analysis revealed the relationships between adipose tissue FA composition and a range of factors in a diverse population, highlighting the importance of studying body adipose tissue beyond its quantity.

Liver PDFF estimation using a multi-decoder water-fat separation neural network with a reduced number of echoes

ObjectiveTo accurately estimate liver PDFF from chemical shift-encoded (CSE) MRI using a deep learning (DL)-based Multi-Decoder Water-Fat separation Network (MDWF-Net), that operates over complex-valued CSE-MR images with only 3 echoes.MethodsThe proposed MDWF-Net and a U-Net model were independently trained using the first 3 echoes of MRI data from 134 subjects, acquired with conventional 6-echoes abdomen protocol at 1.5 T. Resulting models were then evaluated using unseen CSE-MR images obtained from 14 subjects that were acquired with a 3-echoes CSE-MR pulse sequence with a shorter duration compared to the standard protocol. Resulting PDFF maps were qualitatively assessed by two radiologists, and quantitatively assessed at two corresponding liver ROIs, using Bland Altman and regression analysis for mean values, and ANOVA testing for standard deviation (STD) (significance level: .05). A 6-echo graph cut was considered ground truth.ResultsAssessment of radiologists demonstrated that, unlike U-Net, MDWF-Net had a similar quality to the ground truth, despite it considered half of the information. Regarding PDFF mean values at ROIs, MDWF-Net showed a better agreement with ground truth (regression slope = 0.94, R2 = 0.97) than U-Net (regression slope = 0.86, R2 = 0.93). Moreover, ANOVA post hoc analysis of STDs showed a statistical difference between graph cuts and U-Net (p < .05), unlike MDWF-Net (p = .53).ConclusionMDWF-Net showed a liver PDFF accuracy comparable to the reference graph cut method, using only 3 echoes and thus allowing a reduction in the acquisition times.Clinical relevance statementWe have prospectively validated that the use of a multi-decoder convolutional neural network to estimate liver proton density fat fraction allows a significant reduction in MR scan time by reducing the number of echoes required by 50%.Key Points• Novel water-fat separation neural network allows for liver PDFF estimation by using multi-echo MR images with a reduced number of echoes.• Prospective single-center validation demonstrated that echo reduction leads to a significant shortening of the scan time, compared to standard 6-echo acquisition.• Qualitative and quantitative performance of the proposed method showed no significant differences in PDFF estimation with respect to the reference technique.

A knowledge interaction learning for multi-echo MRI motion artifact correction towards better enhancement of SWI

Patient movement during Magnetic Resonance Imaging (MRI) scan can cause severe degradation of image quality. In Susceptibility Weighted Imaging (SWI), several echoes are typically measured during a single repetition period, where the earliest echoes show less contrast between various tissues, while the later echoes are more susceptible to artifacts and signal dropout. In this paper, we propose a knowledge interaction paradigm that jointly learns feature details from multiple distorted echoes by sharing their knowledge with unified training parameters, thereby simultaneously reducing motion artifacts of all echoes. This is accomplished by developing a new scheme that boosts a Single Encoder with Multiple Decoders (SEMD), which assures that the generated features not only get fused but also learned together. We called the proposed method Knowledge Interaction Learning between Multi-Echo data (KIL-ME-based SEMD). The proposed KIL-ME-based SEMD allows to share information and gain an understanding of the correlations between the multiple echoes. The main purpose of this work is to correct the motion artifacts and maintain image quality and structure details of all motion-corrupted echoes towards generating high-resolution susceptibility enhanced contrast images, i.e., SWI, using a weighted average of multi-echo motion-corrected acquisitions. We also compare various potential strategies that might be used to address the problem of reducing artifacts in multi-echoes data. The experimental results demonstrate the feasibility and effectiveness of the proposed method, reducing the severity of motion artifacts and improving the overall clinical image quality of all echoes with their associated SWI maps. Significant improvement of image quality is observed using both motion-simulated test data and actual volunteer data with various motion severity strengths. Eventually, by enhancing the overall image quality, the proposed network can increase the effectiveness of the physicians' capability to evaluate and correctly diagnose brain MR images.

P.32 Impact of age on muscle volume and T2-relaxation time during adulthood in mice using quantitative MRI

Overall ageing is associated with a loss of muscle volume and function over time; nevertheless, detailed changes of muscle tissue are incompletely understood. In this preliminary study, magnetic resonance imaging (MRI) was used to assess the effect of age on muscle volume and T2. A cohort of 13 C57Bl/6J Rj male mice was followed from 2.5 to 17 months of age. MRI acquisitions were done at 7 Tesla using a 1H surface cryoprobe. Muscle volume and T2 of the anterior compartment (TA+EDL: tibialis anterior + extensor digitorum longus) were assessed by cross sectional area (CSA) from high-resolution gradient-echo axial images and from a multi-slice multi echo MRI sequence, respectively. Student's paired t test and ANOVA were used for statistical analysis (p < 0.05). Body weight increased up to 12 months and stayed constant until 17 months of age. Muscle volume reached its maximum at 9 months of age. The maximum CSA of TA+EDL muscles, measured on a single slice, decreased significantly from 9 to 17 months of age (8±0.5 mm² at 9 m/o vs 7.1±0.4 mm² at 17 m/o). In parallel, muscle T2 increased significantly from 2.5 to 17 months of age (T2 at 2.5 m/o = 21.5 ±0.2 ms vs T2 at 17 m/o = 22.6±0.3 ms) and from 2.5 to 6 months of age (T2 at 6 m/o = 22.3±0.4 ms). A similar tendency was also observed between 9 and 17 months of age (T2 at 9 m/o = 22± 0.5; p = 0.054). Repeated acquisitions of high-resolution images allowed for longitudinal follow-up of muscle volume from 2.5 up to 17 months of age in mice. The onset of muscle ageing seems to be around 9 months whereas body weight still increases up to 12 months. Muscle T2 increased significantly with age over the timespan of the study. In young ages (2.5 to 6 m/o), T2 increase probably reflects slight changes of histological water compartmentation related to tissue maturation. Ongoing experiments will refine this longitudinal follow-up and provide data at older ages.

Deep Learning Staging of Liver Iron Content From Multiecho MR Images.

MRI represents the most established liver iron content (LIC) evaluation approach by estimation of liver T2* value, but it is dependent on the choice of the measurement region and the software used for image analysis. To develop a deep-learning method for unsupervised classification of LIC from magnitude T2* multiecho MR images. Retrospective. A total of 1069 thalassemia major patients enrolled in the core laboratory of the Myocardial Iron Overload in Thalassemia (MIOT) network, which were included in the training (80%) and test (20%) sets. Twenty patients from different MRI vendors included in the external test set. A5 T, T2* multiecho magnitude images. Four deep-learning convolutional neural networks (HippoNet-2D, HippoNet-3D, HippoNet-LSTM, and an ensemble network HippoNet-Ensemble) were used to achieve unsupervised staging of LIC using five classes (normal, borderline, middle, moderate, severe). The training set was employed to construct the deep-learning model. The performance of the LIC staging model was evaluated in the test set and in the external test set. The model's performances were assessed by evaluating the accuracy, sensitivity, and specificity with respect to the ground truth labels obtained by T2* measurements and by comparison with operator-induced variability originating from different region of interest (ROI) placements. The network's performances were evaluated by single-class accuracy, specificity, and sensitivity and compared by one-way repeated measures analysis of variance (ANOVA) and one-way ANOVA. HippoNet-Ensemble reached an accuracy significantly higher than the other networks, and a sensitivity and specificity higher than HippoNet-LSTM. Accuracy, sensitivity, and specificity values for the LIC stages were: normal: 0.96/0.93/0.97, borderline: 0.95/0.85/0.98, mild: 0.96/0.88/0.98, moderate: 0.95/0.89/0.97, severe: 0.97/0.95/0.98. Correctly staging of cases was in the range of 85%-95%, depending on the LIC class. Multiclass accuracy was 0.90 against 0.92 for the interobserver variability. The proposed HippoNet-Ensemble network can perform unsupervised LIC staging and achieves good prognostic performance. 4 TECHNICAL EFFICACY: Stage 2.

Semi-automatic tumor segmentation of rectal cancer based on functional magnetic resonance imaging.

Tumor delineation is required both for radiotherapy planning and quantitative imaging biomarker purposes. It is a manual, time- and labor-intensive process prone to inter- and intraobserver variations. Semi or fully automatic segmentation could provide better efficiency and consistency. This study aimed to investigate the influence of including and combining functional with anatomical magnetic resonance imaging (MRI) sequences on the quality of automatic segmentations. T2-weighted (T2w), diffusion weighted, multi-echo T2*-weighted, and contrast enhanced dynamic multi-echo (DME) MR images of eighty-one patients with rectal cancer were used in the analysis. Four classical machine learning algorithms; adaptive boosting (ADA), linear and quadratic discriminant analysis and support vector machines, were trained for automatic segmentation of tumor and normal tissue using different combinations of the MR images as input, followed by semi-automatic morphological post-processing. Manual delineations from two experts served as ground truth. The Sørensen-Dice similarity coefficient (DICE) and mean symmetric surface distance (MSD) were used as performance metric in leave-one-out cross validation. Using T2w images alone, ADA outperformed the other algorithms, yielding a median per patient DICE of 0.67 and MSD of 3.6mm. The performance improved when functional images were added and was highest for models based on either T2w and DME images (DICE: 0.72, MSD: 2.7mm) or all four MRI sequences (DICE: 0.72, MSD: 2.5mm). Machine learning models using functional MRI, in particular DME, have the potential to improve automatic segmentation of rectal cancer relative to models using T2w MRI alone.

Favorable fatty acid composition in adipose tissue in healthy Iraqi- compared to Swedish-born men — a pilot study using MRI assessment

ABSTRACT Middle Eastern immigrants are at high-risk for insulin resistance. Fatty acid composition (FAC) plays an important role in the development of insulin resistance but has not been investigated in people of Middle Eastern ancestry. Here, the aim was to assess the FAC in visceral and subcutaneous adipose tissue (VAT and SAT) in healthy Iraqi- and Swedish-born men using a magnetic resonance imaging (MRI) method.This case-control study included 23 Iraqi- and 15 Swedish-born middle-aged men, without cardiometabolic disease. Using multi-echo MRI of the abdomen, the fractions of saturated, monounsaturated, and polyunsaturated fatty acids (fSFA, fMUFA, and fPUFA) were estimated in VAT and SAT. SAT was further analyzed in deep and superficial compartments (dSAT and sSAT). In all depots, fPUFA was significantly higher and fSFA significantly lower in Iraqi men, independently of age and BMI. In both Iraqi- and Swedish-born men, higher fPUFA and lower fMUFA were found in sSAT vs. dSAT. Among Iraqi men only, higher fPUFA and lower fMUFA were found in SAT vs. VAT.Iraqi-born men presented a more favorable abdominal FAC compared to Swedish-born men. This MRI method also revealed different FACs in different abdominal depots. Our results may reflect a beneficial FAC in Middle Eastern immigrants.

Multi-Center, Multi-Vendor Reproducibility and Calibration of MRI-Based R2* for Liver Iron Quantification

Introduction: Excessive accumulation of iron is caused by a variety of conditions, including hereditary hemochromatosis and transfusional hemosiderosis. If untreated, iron overload can lead to damage in those organs where iron accumulates. Therefore, accurate and reproducible evaluation of body iron stores is needed to guide diagnosis, grading, and treatment monitoring of iron overload. While serum ferritin is the simplest means to assess body iron, it is also an acute phase reactant and therefore is not a reliable biomarker of body iron. Liver iron concentration (LIC) is directly and linearly related to total body iron stores. As such, LIC is widely recognized as a useful surrogate biomarker for the evaluation of iron overload. Liver biopsy is limited by its invasive nature and is contraindicated in many patients (eg. thrombocytopenia) due to bleeding risk. Magnetic resonance imaging (MRI) is a standard of care tool to measure LIC. Arguably the most practical method is R2* MRI due to its speed and ease of use, but the cross-vendor reproducibility of R2*-based LIC estimation remains unknown. Therefore, we evaluated the reproducibility and calibration of R2*-based LIC measurement via a single-breath-hold, confounder-corrected R2*-MRI at both 1.5T and 3T, through a multi-center, multi-vendor study.Methods: Four centers (University of Wisconsin-Madison, University of Texas-Southwestern, Johns Hopkins University, and Stanford University) using MRI scanners of different vendors (GE, Philips, and Siemens) participated in this HIPAA-compliant IRB-approved prospective cross-sectional study. This study recruited subjects with known or suspected iron overload from a variety of etiologies, including hereditary hemochromatosis, transfusional hemosiderosis (due to non-malignant or malignant conditions), and chronic liver disease. Subjects with were recruited for same day multiecho gradient-echo MRI for R2* mapping at both 1.5T and 3T (UW, UTSW, Stanford: 3.0T; JHU: 2.89T). R2* maps were reconstructed from the raw multiecho images and analyzed at a single center. Spin-echo MRI were also performed at 1.5T according to a standardized protocol (FerriScan, Resonance Health, Australia) and processed by a commercial algorithm to obtain FDA-approved reference standard LIC estimates. R2*-vs.-LIC calibrations were generated across centers and field strengths using linear regression and compared using F-tests. A predicted 2.89T calibration was interpolated from the 1.5T and 3.0T calibrations, and compared to the measured (JHU) calibration. Receiver operating characteristic (ROC) curve analysis was performed to determine the diagnostic accuracy of R2* MRI for detection of clinically relevant LIC thresholds.Results: A total of 200 subjects were recruited and successfully scanned for this study. We confirmed a linear relationship between R2* and LIC. All calibrations within the same field strength (see Figure 1) were highly reproducible showing no statistically significant center-specific differences (F > 3.0461). Pooled calibrations for 1.5T, 2.89T, and 3.0T were generated. At either field strength and for each of the LIC thresholds under consideration (1.8, 3.2, 7.0, 15.0 mg/g), estimated areas under the ROC curve (AUCs) of 0.98 or higher were observed.Discussion and Conclusions: In conclusion, confounder-corrected R2* MRI enables accurate and reproducible quantification of liver iron overload, over clinically relevant ranges of LIC. The data generated in this study provide the necessary calibrations for broad dissemination of R2*-based LIC quantification. [Display omitted] DisclosuresHernando: Calimetrix: Current holder of individual stocks in a privately-held company. Pedrosa: Merck: Honoraria; Bayer Healthcare: Honoraria; Health Tech International: Current holder of stock options in a privately-held company. Vasanawala: HeartVista: Current holder of individual stocks in a privately-held company; InkSpace: Current holder of individual stocks in a privately-held company; Arterys: Current holder of individual stocks in a privately-held company. Reeder: Bayer: Research Funding; Pfizer: Research Funding; Calimetrix, LLC: Current holder of individual stocks in a privately-held company; Reveal Pharmaceuticals: Current holder of individual stocks in a privately-held company; Elucent Medical: Current holder of individual stocks in a privately-held company; Cellectar Biosciences: Current holder of individual stocks in a privately-held company; HeartVista: Current holder of individual stocks in a privately-held company.

Electrical impedance tomography for non-invasive identification of fatty liver infiltrate in overweight individuals

Non-alcoholic fatty liver disease (NAFLD) is one of the most common causes of cardiometabolic diseases in overweight individuals. While liver biopsy is the current gold standard to diagnose NAFLD and magnetic resonance imaging (MRI) is a non-invasive alternative still under clinical trials, the former is invasive and the latter costly. We demonstrate electrical impedance tomography (EIT) as a portable method for detecting fatty infiltrate. We enrolled 19 overweight subjects to undergo liver MRI scans, followed by EIT measurements. The MRI images provided the a priori knowledge of the liver boundary conditions for EIT reconstruction, and the multi-echo MRI data quantified liver proton-density fat fraction (PDFF%) to validate fat infiltrate. Using the EIT electrode belts, we circumferentially injected pairwise current to the upper abdomen, followed by acquiring the resulting surface-voltage to reconstruct the liver conductivity. Pearson’s correlation analyses compared EIT conductivity or MRI PDFF with body mass index, age, waist circumference, height, and weight variables. We reveal that the correlation between liver EIT conductivity or MRI PDFF with demographics is statistically insignificant, whereas liver EIT conductivity is inversely correlated with MRI PDFF (R = −0.69, p = 0.003, n = 16). As a pilot study, EIT conductivity provides a portable method for operator-independent and cost-effective detection of hepatic steatosis.

MRI-based synthetic CT shows equivalence to conventional CT for the morphological assessment of the hip joint.

This study evaluated the accuracy of synthetic computed tomography (sCT), as compared to CT, for the 3D assessment of the hip morphology. Thirty male patients with asymptomatic hips, referred for magnetic resonance (MR) imaging and CT, were included in this retrospective study. sCT images were generated from three‐dimensional radiofrequency‐spoiled T1‐weighted multi‐echo gradient‐echo MR images using a commercially available deep learning‐enabled software and were compared with CT images through mean error and surface distance computation and by means of eight clinical morphometric parameters relevant for hip care. Parameters included center‐edge angle (CEA), sharp angle, acetabular index, extrusion index, femoral head center‐to‐midline distance, acetabular version (AV), and anterior and posterior acetabular sector angles. They were measured by two senior orthopedic surgeons and a radiologist in‐training on CT and sCT images. The reliability and agreement of CT‐ and sCT‐based measurements were assessed using intraclass correlation coefficients (ICCs) for absolute agreement, Bland–Altman plots, and two one‐sided tests for equivalence. The surface distance between CT‐ and sCT‐based bone models were on average submillimeter. CT‐ and sCT‐based measurements showed moderate to excellent interobserver and intraobserver correlation (0.56 < ICC < 0.99). In particular, the inter/intraobserver agreements were good for AV (ICC > 0.75). For CEA, the intraobserver agreement was good (ICC > 0.75) and the interobserver agreement was moderate (ICC > 0.69). Limits of agreements were similar between intraobserver CT and intermodal measurements. All measurements were found statistically equivalent, with average intermodal differences within the intraobserver limits of agreement. In conclusion, sCT and CT were equivalent for the assessment of the hip joint bone morphology.

Favorable Fatty Acid Composition in Adipose Tissue in Healthy Iraqi- Compared to Swedish-Born Men Assessed by MRI

Background: Middle Eastern immigrants are at high-risk for insulin resistance. Fatty acid composition (FAC) plays an important role in the development of insulin resistance but has not been investigated in people of Middle Eastern ancestry. Here, the aim was to assess the FAC in visceral and subcutaneous adipose tissue (VAT and SAT) in healthy Iraqi- and Swedish-born men using a magnetic resonance imaging (MRI) method. Methods: This case-control study included 23 Iraqi- and 15 Swedish-born middle-aged men, without cardiometabolic disease. Using multi-echo MRI of the abdomen, the fractions of saturated, monounsaturated, and polyunsaturated fatty acids (fSFA,f MUFA , and fPUFA , respectively) were estimated in VAT and SAT. SAT was further analyzed in deep and superficial compartments (dSAT and sSAT). Findings: In all investigated adipose tissue depots, fPUFA was significantly higher (p <0.001) and f significantly lower (p <0.001) in Iraqi men, independently of age and BMI. In both Iraqi- and Swedish-born men, higher fPUFA and lower fMUFA were found in sSAT vs. dSAT. Among Iraqi men only, higher f PUFA and lower f MUFA were found in SAT vs. VAT (p <0.001). Interpretations: Iraqi-born men presented a more favorable abdominal adipose tissue FAC compared to Swedish-born men. This MRI method also revealed differences in FAC comparing different abdominal adipose tissue depots. Our results may reflect a beneficial FAC in Middle Eastern immigrants which needs to be further investigated. Funding: Lund University; the Swedish Research Council; the Swedish Foundation for Strategic Research; MAS Foundation for Fighting Cancer; the Cancer Research Foundation, Oncology Department, SUS Malmo. Declaration of Interest: None to declare. Ethical Approval: Approval for the study was granted from the Ethical Review Board of Lund University (2015/507).

Quantitative Susceptibility Mapping of Venous Vessels in Neonates with Perinatal Asphyxia.

Cerebral venous oxygen saturation can be used as an indirect measure of brain health, yet it often requires either an invasive procedure or a noninvasive technique with poor sensitivity. We aimed to test whether cerebral venous oxygen saturation could be measured using quantitative susceptibility mapping, an MR imaging technique, in 3 distinct groups: healthy term neonates, injured term neonates, and preterm neonates. We acquired multiecho gradient-echo MR imaging data in 16 neonates with perinatal asphyxia and moderate or severe hypoxic-ischemic encephalopathy (8 term age: average, 40.0 [SD, 0.8] weeks' gestational age; 8 preterm, 33.5 [SD, 2.0] weeks' gestational age) and in 8 healthy term-age controls (39.3 [SD, 0.6] weeks, for a total of n = 24. Data were postprocessed as quantitative susceptibility mapping images, and magnetic susceptibility was measured in cerebral veins by thesholding out 99.95% of lower magnetic susceptibility values. The mean magnetic susceptibility value of the cerebral veins was found to be 0.36 (SD, 0.04) ppm in healthy term neonates, 0.36 (SD, 0.06) ppm in term injured neonates, and 0.29 (SD, 0.04) ppm in preterm injured neonates. Correspondingly, the derived cerebral venous oxygen saturation values were 73.6% (SD, 2.8%), 71.5% (SD, 7.4%), and 72.2% (SD, 5.9%). There was no statistically significant difference in cerebral venous oxygen saturation among the 3 groups (P = .751). Quantitative susceptibility mapping-derived oxygen saturation values in preterm and term neonates agreed well with values in past literature. Cerebral venous oxygen saturation in preterm and term neonates with hypoxic-ischemic encephalopathy, however, was not found to be significantly different between neonates or healthy controls.

Determination of paramagnetic ferrous gel sensitivity in low energy x-ray beam produced by a miniature accelerator.

The INTRABEAM Carl Zeiss Surgical system (Oberkochen, Germany) is a miniature accelerator producing low energy photons (50 keV maximum). The published dosimetric characterization of the INTRABEAM was based on detectors (radiochromic films or ionization chambers) not allowing measuring the absorbed dose in the first millimeters of the irradiated medium, where the dose is actually prescribed. This study aims at determining with Magnetic Resonance Imaging (MRI) the sensitivity of a paramagnetic gel in order to measure the dose deposit produced with the INTRABEAM from 0 to 20 mm. Although spherical applicators are mostly used with the INTRABEAM system for breast applications, this study focuses on surface applicators that are of interest for cutaneous carcinomas. The irradiations at 12 different dose levels (between 2 Gy and 50 Gy at the gel surface) were performed with the INTRABEAM and a 4 cm surface applicator. The gel used in this study is a new « sensitive » material. In order to compare gel sensitivity at low energy with high energy, gels were irradiated by an 18 MV photon beam produced by a Varian Clinac 2100 CD. T2 weighted multi echo MRI sequences were performed with 16 echo times. The T2 signal versus echo times was fitted with a mono-exponential function with 95% confidence interval. The calibration curve determined at low energy is a linear function (r2 = 0.9893) with a sensitivity of 0.0381 s-1.Gy-1, a similar linear function was obtained at high energy (0.0372 s-1.Gy-1 with r2 = 0.9662). The calibration curve at low energy was used to draw isodose maps from the MR images. The PDD (Percent Depth Dose) determined in the gel is within 5%-1mm of the ionization chamber PDD except for one point. The dosimetric sensitivity of this new paramagnetic ferrous gel was determined with MRI measurements. It allowed measuring the dose distribution specifically in the first millimeters for an irradiation with the INTRABEAM miniature accelerator equipped with a surface applicator.

Reconstructing multi-echo magnetic resonance images via structured deep dictionary learning

Multi-echo magnetic resonance (MR) images are acquired by changing the echo times (for T2 weighted) or relaxation times (for T1 weighted) of scans. The resulting (multi-echo) images are usually used for quantitative MR imaging. Acquiring MR images is a slow process and acquiring multi scans of the same cross section for multi-echo imaging is even slower. In order to accelerate the scan, compressed sensing (CS) based techniques have been advocating partial K-space (Fourier domain) scans; the resulting images are reconstructed via structured CS algorithms. In recent times, it has been shown that instead of using off-the-shelf CS, better results can be obtained by adaptive reconstruction algorithms based on structured dictionary learning. In this work, we show that the reconstruction results can be further improved by using structured deep dictionaries. Experimental results on real datasets show that by using our proposed technique the scan-time can be cut by half compared to the state-of-the-art.

Baseline structural tissue pathology is not strongly associated with longitudinal change in transverse relaxation time (T2) in knees without osteoarthritis

PurposeTo evaluate whether baseline MRI-defined structural abnormalities are associated with subsequent change in laminar femorotibial cartilage transverse relaxation time (T2) of participants without radiographic signs, symptoms or risk factors for knee osteoarthritis (OA). MethodWe studied all right knees with longitudinal MRI data of the refined Osteoarthritis Initiative Healthy Reference cohort. Baseline osteophytes, effusion-synovitis, Hoffa-synovitis, bone marrow lesions, cartilage lesions, and meniscus morphology and - extrusion were scored semiquantitatively from MR images by an expert reader. Deep and superficial layer cartilage T2 was computed in the medial and lateral femorotibial compartment (MFTC/LFTC) at baseline and at 1- and 4-year follow-up from multi-echo spin-echo MR images. Statistical analyses were performed using UNIANOVA. Results82 participants (age 54.1 ± 7.2y, BMI 24.2 ± 3.0 kg/m²; 61% women, bilateral Kellgren-Lawrence 0) were studied. Number of baseline MRI pathologies was not significantly associated with longitudinal change in MFTC or LFTC cartilage T2 over 1 or 4 years. Feature-specific analyses suggested that presence of baseline MFTC osteophytes may be associated with prolongation in superficial MFTC cartilage T2 over one (0.8 vs. 0.0 ms, p = 0.02) and four years (2.3 vs. 0.9 ms, p = 0.01), and that MFTC meniscal damage or extrusion may be associated with prolongation in deep layer T2 times over the first year (0.7 vs. 2.1 ms, p = 0.02). ConclusionsOur study does not provide evidence that, in knees without radiographic OA, baseline structural MRI abnormalities are strongly related to compositional progression during normal aging and/or the potentially earliest phases of the disease as measured by cartilage T2.

T2* and quantitative susceptibility mapping in an equine model of post-traumatic osteoarthritis: assessment of mechanical and structural properties of articular cartilage

To investigate the potential of quantitative susceptibility mapping (QSM) and T2* relaxation time mapping to determine mechanical and structural properties of articular cartilage via univariate and multivariate analysis. Samples were obtained from a cartilage repair study, in which surgically induced full-thickness chondral defects in the stifle joints of seven Shetland ponies caused post-traumatic osteoarthritis (14 samples). Control samples were collected from non-operated joints of three animals (6 samples). Magnetic resonance imaging (MRI) was performed at 9.4T, using a 3-D multi-echo gradient echo sequence. Biomechanical testing, digital densitometry (DD) and polarized light microscopy (PLM) were utilized as reference methods. To compare MRI parameters with reference parameters (equilibrium and dynamic moduli, proteoglycan content, collagen fiber angle and -anisotropy), depth-wise profiles of MRI parameters were acquired at the biomechanical testing locations. Partial least squares regression (PLSR) and Spearman's rank correlation were utilized in data analysis. PLSR indicated a moderate-to-strong correlation (ρ=0.49-0.66) and a moderate correlation (ρ=0.41-0.55) between the reference values and T2* relaxation time and QSM profiles, respectively (excluding superficial-only results). PLSR correlations were noticeably higher than direct correlations between bulk MRI and reference parameters. 3-D parametric surface maps revealed spatial variations in the MRI parameters between experimental and control groups. Quantitative parameters from 3-D multi-echo gradient echo MRI can be utilized to predict the properties of articular cartilage. With PLSR, especially the T2* relaxation time profile appeared to correlate with the properties of cartilage. Furthermore, the results suggest that degeneration affects the QSM-contrast in the cartilage. However, this change in contrast is not easy to quantify.

Molecular Imaging of Immune Cell Dynamics During De- and Remyelination in the Cuprizone Model of Multiple Sclerosis by [18F]DPA-714 PET and MRI.

Background: Activation and dysregulation of innate, adaptive and resident immune cells in response to damage determine the pathophysiology of demyelinating disorders. Among the plethora of involved cells, microglia/macrophages and astrocytes play an important role in the pathogenesis of demyelinating disorders. The in-depth investigation of the spatio-temporal profile of these cell types in vivo may inform about the exact disease state and localization as well as may allow to monitor therapeutic modulation of the components of the neuroinflammatory response during the course of multiple sclerosis (MS).In this study, we aimed to non-invasively decipher the degree and temporal profile of neuroinflammation (TSPO - [18F]DPA-714 PET) in relation to selected magnetic resonance imaging (MRI) parameters (T2 maps) in the cuprizone (CPZ)-induced model of demyelination.Methods: C57Bl6 (n=30) mice were fed with a standard chow mixed with 0.2% (w/w) CPZ for 4 (n=10; demyelination) and 6 weeks (n=10; spontaneous remyelination). The degree of neuroinflammation at de- and remyelination was assessed by [18F]DPA-714 PET, multi-echo T2 MRI, autoradiography and immunohistochemistry.Results: CPZ-induced brain alterations were confirmed by increase of T2 relaxation times in both white and grey matter after 3 and 5 weeks of CPZ. Peak [18F]DPA-714 was found in the corpus callosum (CC, white matter), the hippocampus (HC, grey matter) and thalamus (grey matter) after 4 weeks of CPZ treatment and declined after 6 weeks of CPZ. Ex vivo autoradiography and dedicated immunofluorescence showed demyelination/remyelination with corresponding increased/decreased TSPO levels in the CC and hippocampus, confirming the spatial distribution of [18F]DPA-714 in vivo. The expression of TSPO microglia and astrocytes is time-dependent in this model. Microglia predominantly express TSPO at demyelination, while the majority of astrocytes express TSPO during remyelination.The combination of PET- and MRI-based imaging biomarkers demonstrated the regional and temporal development of the CPZ model-associated neuroinflammatory response in grey and white matter regions.Conclusions: The combination of [18F]DPA-714 PET and T2 mapping may allow to further elucidate the regional and temporal profile of inflammatory signals depending on the myelination status, although the underlying inflammatory microenvironment changes. A combination of the described imaging biomarkers may facilitate the development of patient-tailored strategies for immunomodulatory and neuro-restorative therapies in MS.

T2-relaxation mapping and fat fraction assessment to objectively quantify clinical activity in thyroid eye disease: an initial feasibility study.

Imaging in thyroid eye disease (TED) is used to exclude other diagnoses, assess for apical crowding and plan surgery. But to quantify TED activity objectively, subjective clinical scoring assessments remain the norm. Magnetic resonance imaging (MRI) T2-relaxation times correlate with extra-ocular muscle (EOM) inflammation, but are confounded by signal from fat. We investigated whether T2-relaxation mapping in combination with fat fraction (FF) measurements could quantify disease activity in EOMs objectively. Sixty-two TED patients and six controls were enroled for coronal short tau inversion recovery (STIR), T2 multi-echo fast-spin echo and multi-echo fast-gradient echo MRI of the orbits. STIR signal intensity ratios (SIRs), T2-relaxation times and percentage FF were derived for inferior, lateral, superior and medial recti bilaterally. Twelve patients were re-scanned following immunosuppressive treatment. The results found a positive correlation for all subjects between T2 and SIR (p < 0.001), but only mean T2 differed significantly between patients and controls (p < 0.001). We measured FF in EOMs for the first time and found it greater in TED (p < 0.001). There was also a significant reduction in mean T2 after treatment, with a corresponding reduction in the clinical activity score (CAS) in almost all patients. We show that T2-relaxation times differentiate between normal and inflamed EOMs and are responsive to treatment. Combined, uniquely, with FF measurement in EOMs, an objective, quantitative marker of inflammation in TED-affected muscles could be derived. T2-relaxation times mirrored improvements in CAS after treatment, occasionally preceding them. Rarely, they diverged, suggesting limitations in the CAS as a disease burden marker.

Accuracy of Automated Liver Contouring, Fat Fraction, and R2* Measurement on Gradient Multiecho Magnetic Resonance Images.

This study aimed to evaluate the performance of an automated workflow of volumetric liver proton density fat fraction (PDFFvol) and R2* quantification with automated inline liver volume (LV) segmentation. Dual-echo and multiecho Dixon magnetic resonance images were evaluated in 74 consecutive patients (group A, PDFF < 10%; B, PDFF ≥ 10%; C, R2* ≥ 100 s; D, post-hemihepatectomy). The values of PDFFvol and R2*vol measurements across the LV were generated on multiecho images in an automated fashion based on inline liver segmentation on dual-echo images. Similar measurements were performed manually. Using the inline algorithm, the mis-segmented LV was highest in group D (80%). There were no significant differences between automated and manual measurements of PDFFvol. Automated R2*vol was significantly lower than manual R2*vol in group A (P = 0.004). Inline LV segmentation performed well in patients without and with hepatic steatosis. In cases with iron overload and post-hemihepatectomy, extrahepatic areas were erroneously included to a greater extent, with a tendency toward overestimation of PDFFvol.