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Article ; Online: Implementation of GAN-Based, Synthetic T2-Weighted Fat Saturated Images in the Routine Radiological Workflow Improves Spinal Pathology Detection

Sarah Schlaeger / Katharina Drummer / Malek El Husseini / Florian Kofler / Nico Sollmann / Severin Schramm / Claus Zimmer / Jan S. Kirschke / Benedikt Wiestler

Diagnostics, Vol 13, Iss 974, p

2023 Volume 974

Abstract: 1) Background and Purpose: In magnetic resonance imaging (MRI) of the spine, T2-weighted (T2-w) fat-saturated (fs) images improve the diagnostic assessment of pathologies. However, in the daily clinical setting, additional T2-w fs images are frequently ... ...

Abstract	(1) Background and Purpose: In magnetic resonance imaging (MRI) of the spine, T2-weighted (T2-w) fat-saturated (fs) images improve the diagnostic assessment of pathologies. However, in the daily clinical setting, additional T2-w fs images are frequently missing due to time constraints or motion artifacts. Generative adversarial networks (GANs) can generate synthetic T2-w fs images in a clinically feasible time. Therefore, by simulating the radiological workflow with a heterogenous dataset, this study’s purpose was to evaluate the diagnostic value of additional synthetic, GAN-based T2-w fs images in the clinical routine. (2) Methods: 174 patients with MRI of the spine were retrospectively identified. A GAN was trained to synthesize T2-w fs images from T1-w, and non-fs T2-w images of 73 patients scanned in our institution. Subsequently, the GAN was used to create synthetic T2-w fs images for the previously unseen 101 patients from multiple institutions. In this test dataset, the additional diagnostic value of synthetic T2-w fs images was assessed in six pathologies by two neuroradiologists. Pathologies were first graded on T1-w and non-fs T2-w images only, then synthetic T2-w fs images were added, and pathologies were graded again. Evaluation of the additional diagnostic value of the synthetic protocol was performed by calculation of Cohen’s ĸ and accuracy in comparison to a ground truth (GT) grading based on real T2-w fs images, pre- or follow-up scans, other imaging modalities, and clinical information. (3) Results: The addition of the synthetic T2-w fs to the imaging protocol led to a more precise grading of abnormalities than when grading was based on T1-w and non-fs T2-w images only (mean ĸ GT versus synthetic protocol = 0.65; mean ĸ GT versus T1/T2 = 0.56; p = 0.043). (4) Conclusions: The implementation of synthetic T2-w fs images in the radiological workflow significantly improves the overall assessment of spine pathologies. Thereby, high-quality, synthetic T2-w fs images can be virtually generated by a GAN ...
Keywords	magnetic resonance imaging ; spine ; generative adversarial network ; T2-w fat saturated images ; data augmentation ; Medicine (General) ; R5-920
Subject code	610
Language	English
Publishing date	2023-03-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: AI-based detection of contrast-enhancing MRI lesions in patients with multiple sclerosis

Sarah Schlaeger / Suprosanna Shit / Paul Eichinger / Marco Hamann / Roland Opfer / Julia Krüger / Michael Dieckmeyer / Simon Schön / Mark Mühlau / Claus Zimmer / Jan S. Kirschke / Benedikt Wiestler / Dennis M. Hedderich

Insights into Imaging, Vol 14, Iss 1, Pp 1-

2023 Volume 11

Abstract: Abstract Background Contrast-enhancing (CE) lesions are an important finding on brain magnetic resonance imaging (MRI) in patients with multiple sclerosis (MS) but can be missed easily. Automated solutions for reliable CE lesion detection are emerging; ... ...

Abstract	Abstract Background Contrast-enhancing (CE) lesions are an important finding on brain magnetic resonance imaging (MRI) in patients with multiple sclerosis (MS) but can be missed easily. Automated solutions for reliable CE lesion detection are emerging; however, independent validation of artificial intelligence (AI) tools in the clinical routine is still rare. Methods A three-dimensional convolutional neural network for CE lesion segmentation was trained externally on 1488 datasets of 934 MS patients from 81 scanners using concatenated information from FLAIR and T1-weighted post-contrast imaging. This externally trained model was tested on an independent dataset comprising 504 T1-weighted post-contrast and FLAIR image datasets of MS patients from clinical routine. Two neuroradiologists (R1, R2) labeled CE lesions for gold standard definition in the clinical test dataset. The algorithmic output was evaluated on both patient- and lesion-level. Results On a patient-level, recall, specificity, precision, and accuracy of the AI tool to predict patients with CE lesions were 0.75, 0.99, 0.91, and 0.96. The agreement between the AI tool and both readers was within the range of inter-rater agreement (Cohen’s kappa; AI vs. R1: 0.69; AI vs. R2: 0.76; R1 vs. R2: 0.76). On a lesion-level, false negative lesions were predominately found in infratentorial location, significantly smaller, and at lower contrast than true positive lesions (p < 0.05). Conclusions AI-based identification of CE lesions on brain MRI is feasible, approaching human reader performance in independent clinical data and might be of help as a second reader in the neuroradiological assessment of active inflammation in MS patients. Critical relevance statement Al-based detection of contrast-enhancing multiple sclerosis lesions approaches human reader performance, but careful visual inspection is still needed, especially for infratentorial, small and low-contrast lesions. Graphical Abstract
Keywords	Magnetic resonance imaging ; Multiple sclerosis ; Contrast-enhancing lesions ; Artificial intelligence ; Clinical decision support ; Medical physics. Medical radiology. Nuclear medicine ; R895-920
Subject code	610 ; 616
Language	English
Publishing date	2023-07-01T00:00:00Z
Publisher	SpringerOpen
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Faster and Better

Tom Finck / Julia Moosbauer / Monika Probst / Sarah Schlaeger / Madeleine Schuberth / David Schinz / Mehmet Yiğitsoy / Sebastian Byas / Claus Zimmer / Franz Pfister / Benedikt Wiestler

Diagnostics, Vol 12, Iss 452, p

How Anomaly Detection Can Accelerate and Improve Reporting of Head Computed Tomography

2022 Volume 452

Abstract: Background: Most artificial intelligence (AI) systems are restricted to solving a pre-defined task, thus limiting their generalizability to unselected datasets. Anomaly detection relieves this shortfall by flagging all pathologies as deviations from a ... ...

Abstract	Background: Most artificial intelligence (AI) systems are restricted to solving a pre-defined task, thus limiting their generalizability to unselected datasets. Anomaly detection relieves this shortfall by flagging all pathologies as deviations from a learned norm. Here, we investigate whether diagnostic accuracy and reporting times can be improved by an anomaly detection tool for head computed tomography (CT), tailored to provide patient-level triage and voxel-based highlighting of pathologies. Methods: Four neuroradiologists with 1–10 years of experience each investigated a set of 80 routinely acquired head CTs containing 40 normal scans and 40 scans with common pathologies. In a random order, scans were investigated with and without AI-predictions. A 4-week wash-out period between runs was included to prevent a reminiscence effect. Performance metrics for identifying pathologies, reporting times, and subjectively assessed diagnostic confidence were determined for both runs. Results: AI-support significantly increased the share of correctly classified scans (normal/pathological) from 309/320 scans to 317/320 scans ( p = 0.0045), with a corresponding sensitivity, specificity, negative- and positive- predictive value of 100%, 98.1%, 98.2% and 100%, respectively. Further, reporting was significantly accelerated with AI-support, as evidenced by the 15.7% reduction in reporting times (65.1 ± 8.9 s vs. 54.9 ± 7.1 s; p < 0.0001). Diagnostic confidence was similar in both runs. Conclusion: Our study shows that AI-based triage of CTs can improve the diagnostic accuracy and accelerate reporting for experienced and inexperienced radiologists alike. Through ad hoc identification of normal CTs, anomaly detection promises to guide clinicians towards scans requiring urgent attention.
Keywords	machine learning ; neuroradiology ; computed tomography ; decision support ; anomaly detection ; classification ; Medicine (General) ; R5-920
Subject code	333
Language	English
Publishing date	2022-02-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Association of Thigh Muscle Strength with Texture Features Based on Proton Density Fat Fraction Maps Derived from Chemical Shift Encoding-Based Water–Fat MRI

Michael Dieckmeyer / Stephanie Inhuber / Sarah Schläger / Dominik Weidlich / Muthu R. K. Mookiah / Karupppasamy Subburaj / Egon Burian / Nico Sollmann / Jan S. Kirschke / Dimitrios C. Karampinos / Thomas Baum

Diagnostics, Vol 11, Iss 2, p

2021 Volume 302

Abstract: Purpose: Based on conventional and quantitative magnetic resonance imaging (MRI), texture analysis (TA) has shown encouraging results as a biomarker for tissue structure. Chemical shift encoding-based water–fat MRI (CSE-MRI)-derived proton density fat ... ...

Abstract	Purpose: Based on conventional and quantitative magnetic resonance imaging (MRI), texture analysis (TA) has shown encouraging results as a biomarker for tissue structure. Chemical shift encoding-based water–fat MRI (CSE-MRI)-derived proton density fat fraction (PDFF) of thigh muscles has been associated with musculoskeletal, metabolic, and neuromuscular disorders and was demonstrated to predict muscle strength. The purpose of this study was to investigate PDFF-based TA of thigh muscles as a predictor of thigh muscle strength in comparison to mean PDFF. Methods: 30 healthy subjects (age = 30 ± 6 years; 15 females) underwent CSE-MRI of the lumbar spine at 3T, using a six-echo 3D spoiled gradient echo sequence. Quadriceps (EXT) and ischiocrural (FLEX) muscles were segmented to extract mean PDFF and texture features. Muscle flexion and extension strength were measured with an isokinetic dynamometer. Results: Of the eleven extracted texture features, Variance(global) showed the highest significant correlation with extension strength ( p < 0.001, R 2 adj = 0.712), and Correlation showed the highest significant correlation with flexion strength ( p = 0.016, R 2 adj = 0.658). Multivariate linear regression models identified Variance(global) and sex, but not PDFF, as significant predictors of extension strength (R 2 adj = 0.709; p < 0.001), while mean PDFF, sex, and BMI, but none of the texture features, were identified as significant predictors of flexion strength (R 2 adj = 0.674; p < 0.001). Conclusions: Prediction of quadriceps muscle strength can be improved beyond mean PDFF by means of TA, indicating the capability to quantify muscular fat infiltration patterns.
Keywords	magnetic resonance imaging ; texture analysis ; proton density fat fraction ; thigh muscles ; muscle strength ; Medicine (General) ; R5-920
Language	English
Publishing date	2021-02-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Texture Features of Proton Density Fat Fraction Maps from Chemical Shift Encoding-Based MRI Predict Paraspinal Muscle Strength

Michael Dieckmeyer / Stephanie Inhuber / Sarah Schlaeger / Dominik Weidlich / Muthu Rama Krishnan Mookiah / Karupppasamy Subburaj / Egon Burian / Nico Sollmann / Jan S. Kirschke / Dimitrios C. Karampinos / Thomas Baum

Diagnostics, Vol 11, Iss 2, p

2021 Volume 239

Abstract: Texture analysis (TA) has shown promise as a surrogate marker for tissue structure, based on conventional and quantitative MRI sequences. Chemical-shift-encoding-based MRI (CSE-MRI)-derived proton density fat fraction (PDFF) of paraspinal muscles has ... ...

Abstract	Texture analysis (TA) has shown promise as a surrogate marker for tissue structure, based on conventional and quantitative MRI sequences. Chemical-shift-encoding-based MRI (CSE-MRI)-derived proton density fat fraction (PDFF) of paraspinal muscles has been associated with various medical conditions including lumbar back pain (LBP) and neuromuscular diseases (NMD). Its application has been shown to improve the prediction of paraspinal muscle strength beyond muscle volume. Since mean PDFF values do not fully reflect muscle tissue structure, the purpose of our study was to investigate PDFF-based TA of paraspinal muscles as a predictor of muscle strength, as compared to mean PDFF. We performed 3T-MRI of the lumbar spine in 26 healthy subjects (age = 30 ± 6 years; 15 females) using a six-echo 3D spoiled gradient echo sequence for chemical-shift-encoding-based water–fat separation. Erector spinae (ES) and psoas (PS) muscles were segmented bilaterally from level L2–L5 to extract mean PDFF and texture features. Muscle flexion and extension strength was measured with an isokinetic dynamometer. Out of the eleven texture features extracted for each muscle, Kurtosis(global) of ES showed the highest significant correlation ( r = 0.59, p = 0.001) with extension strength and Variance(global) of PS showed the highest significant correlation ( r = 0.63, p = 0.001) with flexion strength. Using multivariate linear regression models, Kurtosis(global) of ES and BMI were identified as significant predictors of extension strength (R 2 adj = 0.42; p < 0.001), and Variance(global) and Skewness(global) of PS were identified as significant predictors of flexion strength (R 2 adj = 0.59; p = 0.001), while mean PDFF was not identified as a significant predictor. TA of CSE-MRI-based PDFF maps improves the prediction of paraspinal muscle strength beyond mean PDFF, potentially reflecting the ability to quantify the pattern of muscular fat infiltration. In the future, this may help to improve the pathophysiological understanding, diagnosis, ...
Keywords	magnetic resonance imaging ; texture analysis ; proton density fat fraction ; paraspinal muscles ; muscle strength ; Medicine (General) ; R5-920
Subject code	610 ; 796
Language	English
Publishing date	2021-02-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Association of quadriceps muscle, gluteal muscle, and femoral bone marrow composition using chemical shift encoding-based water-fat MRI

Michael Dieckmeyer / Florian Zoffl / Lioba Grundl / Stephanie Inhuber / Sarah Schlaeger / Egon Burian / Claus Zimmer / Jan S. Kirschke / Dimitrios C. Karampinos / Thomas Baum / Nico Sollmann

European Radiology Experimental, Vol 4, Iss 1, Pp 1-

a preliminary study in healthy young volunteers

2020 Volume 8

Abstract: Abstract Background We investigated the composition of the gluteal (gluteus maximus, medius, and minimus) and quadriceps (rectus femoris, vastus lateralis, medialis, and intermedius) muscle groups and its associations with femoral bone marrow using ... ...

Abstract	Abstract Background We investigated the composition of the gluteal (gluteus maximus, medius, and minimus) and quadriceps (rectus femoris, vastus lateralis, medialis, and intermedius) muscle groups and its associations with femoral bone marrow using chemical shift encoding-based water-fat magnetic resonance imaging (CSE-MRI) to improve our understanding of muscle-bone interaction. Methods Thirty healthy volunteers (15 males, aged 30.5 ± 4.9 years [mean ± standard deviation]; 15 females, aged 29.9 ± 7.1 years) were recruited. A six-echo three-dimensional spoiled gradient-echo sequence was used for 3-T CSE-MRI at the thigh and hip region. The proton density fat fraction (PDFF) of the gluteal and quadriceps muscle groups as well as of the femoral head, neck, and greater trochanter bone marrow were extracted and averaged over both sides. Results PDFF values of all analysed bone marrow compartments were significantly higher in men than in women (p ≤ 0.047). PDFF values of the analysed muscles showed no significant difference between men and women (p ≥ 0.707). After adjusting for age and body mass index, moderate significant correlations of PDFF values were observed between the gluteal and quadriceps muscle groups (r = 0.670) and between femoral subregions (from r = 0.613 to r = 0.655). Regarding muscle-bone interactions, only the PDFF of the quadriceps muscle and greater trochanter bone marrow showed a significant correlation (r = 0.375). Conclusions The composition of the muscle and bone marrow compartments at the thigh and hip region in young, healthy subjects seems to be quite distinct, without evidence for a strong muscle-bone interaction.
Keywords	Bone marrow ; Femur ; Healthy volunteers ; Magnetic resonance imaging ; Muscles ; Medical physics. Medical radiology. Nuclear medicine ; R895-920
Subject code	616
Language	English
Publishing date	2020-06-01T00:00:00Z
Publisher	SpringerOpen
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Quantitative Muscle MRI in Patients with Neuromuscular Diseases—Association of Muscle Proton Density Fat Fraction with Semi-Quantitative Grading of Fatty Infiltration and Muscle Strength at the Thigh Region

Sarah Schlaeger / Nico Sollmann / Agnes Zoffl / Edoardo Aitala Becherucci / Dominik Weidlich / Elisabeth Kottmaier / Isabelle Riederer / Tobias Greve / Federica Montagnese / Marcus Deschauer / Benedikt Schoser / Claus Zimmer / Dimitrios C. Karampinos / Jan S. Kirschke / Thomas Baum

Diagnostics, Vol 11, Iss 1056, p

2021 Volume 1056

Abstract: 1) Background and Purpose: The skeletal muscles of patients suffering from neuromuscular diseases (NMD) are affected by atrophy, hypertrophy, fatty infiltration, and edematous changes. Magnetic resonance imaging (MRI) is an important tool for diagnosis ... ...

Abstract	(1) Background and Purpose: The skeletal muscles of patients suffering from neuromuscular diseases (NMD) are affected by atrophy, hypertrophy, fatty infiltration, and edematous changes. Magnetic resonance imaging (MRI) is an important tool for diagnosis and monitoring. Concerning fatty infiltration, T 1 -weighted or T 2 -weighted DIXON turbo spin echo (TSE) sequences enable a qualitative assessment of muscle involvement. To achieve higher comparability, semi-quantitative grading scales, such as the four-point Mercuri scale, are commonly applied. However, the evaluation remains investigator-dependent. Therefore, effort is being invested to develop quantitative MRI techniques for determination of imaging markers such as the proton density fat fraction (PDFF). The present work aims to assess the diagnostic value of PDFF in correlation to Mercuri grading and clinically determined muscle strength in patients with myotonic dystrophy type 2 (DM2), limb girdle muscular dystrophy type 2A (LGMD2A), and adult Pompe disease. (2) Methods: T 2 -weighted two-dimensional (2D) DIXON TSE and chemical shift encoding-based water-fat MRI were acquired in 13 patients (DM2: n = 5; LGMD2A: n = 5; Pompe disease: n = 3). Nine different thigh muscles were rated in all patients according to the Mercuri grading and segmented to extract PDFF values. Muscle strength was assessed according to the British Medical Research Council (BMRC) scale. For correlation analyses between Mercuri grading, muscle strength, and PDFF, the Spearman correlation coefficient (r s ) was computed. (3) Results: Mean PDFF values ranged from 7% to 37% in adults with Pompe disease and DM2 and up to 79% in LGMD2A patients. In all three groups, a strong correlation of the Mercuri grading and PDFF values was observed for almost all muscles ( r s > 0.70, p < 0.05). PDFF values correlated significantly to muscle strength for muscle groups responsible for knee flexion ( r s = −0.80, p < 0.01). (4) Conclusion: In the small, investigated patient cohort, PDFF offers ...
Keywords	chemical shift encoding-based water-fat MRI ; neuromuscular diseases ; proton density fat fraction ; quantitative MRI ; thigh musculature ; muscle strength ; Medicine (General) ; R5-920
Subject code	610
Language	English
Publishing date	2021-06-01T00:00:00Z
Publisher	MDPI AG
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Article ; Online: Correction to

Stephanie Inhuber / Nico Sollmann / Sarah Schlaeger / Michael Dieckmeyer / Egon Burian / Caroline Kohlmeyer / Dimitrios C. Karampinos / Jan S. Kirschke / Thomas Baum / Florian Kreuzpointner / Ansgar Schwirtz

European Radiology Experimental, Vol 3, Iss 1, Pp 1-

Associations of thigh muscle fat infiltration with isometric strength measurements based on chemical shift encoding-based water-fat magnetic resonance imaging

2019 Volume 1

Abstract: After publication of this article [1], it is noticed it contained some errors in the Methods section. ...

Abstract	After publication of this article [1], it is noticed it contained some errors in the Methods section.
Keywords	Medical physics. Medical radiology. Nuclear medicine ; R895-920
Language	English
Publishing date	2019-12-01T00:00:00Z
Publisher	SpringerOpen
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Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Associations of thigh muscle fat infiltration with isometric strength measurements based on chemical shift encoding-based water-fat magnetic resonance imaging

European Radiology Experimental, Vol 3, Iss 1, Pp 1-

2019 Volume 10

Abstract: Abstract Background Assessment of the thigh muscle fat composition using magnetic resonance imaging (MRI) can provide surrogate markers in subjects suffering from various musculoskeletal disorders including knee osteoarthritis or neuromuscular diseases. ... ...

Abstract	Abstract Background Assessment of the thigh muscle fat composition using magnetic resonance imaging (MRI) can provide surrogate markers in subjects suffering from various musculoskeletal disorders including knee osteoarthritis or neuromuscular diseases. However, little is known about the relationship with muscle strength. Therefore, we investigated the associations of thigh muscle fat with isometric strength measurements. Methods Twenty healthy subjects (10 females; median age 27 years, range 22–41 years) underwent chemical shift encoding-based water-fat MRI, followed by bilateral extraction of the proton density fat fraction (PDFF) and calculation of relative cross-sectional area (relCSA) of quadriceps and ischiocrural muscles. Relative maximum voluntary isometric contraction (relMVIC) in knee extension and flexion was measured with a rotational dynamometer. Correlations between PDFF, relCSA, and relMVIC were evaluated, and multivariate regression was applied to identify significant predictors of muscle strength. Results Significant correlations between the PDFF and relMVIC were observed for quadriceps and ischiocrural muscles bilaterally (p = 0.001 to 0.049). PDFF, but not relCSA, was a statistically significant (p = 0.001 to 0.049) predictor of relMVIC in multivariate regression models, except for left-sided relMVIC in extension. In this case, PDFF (p = 0.005) and relCSA (p = 0.015) of quadriceps muscles significantly contributed to the statistical model with R 2 adj = 0.548. Conclusion Chemical shift encoding-based water-fat MRI could detect changes in muscle composition by quantifying muscular fat that correlates well with both extensor and flexor relMVIC of the thigh. Our results help to initiate early, individualised treatments to maintain or improve muscle function in subjects who do not or not yet show pathological fatty muscle infiltration.
Keywords	Healthy volunteers ; Magnetic resonance imaging ; Muscle contraction (isometric) ; Muscle strength ; Thigh ; Medical physics. Medical radiology. Nuclear medicine ; R895-920
Subject code	796 ; 610
Language	English
Publishing date	2019-11-01T00:00:00Z
Publisher	SpringerOpen
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Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: B1-insensitive T2 mapping of healthy thigh muscles using a T2-prepared 3D TSE sequence.

Elisabeth Klupp / Dominik Weidlich / Sarah Schlaeger / Thomas Baum / Barbara Cervantes / Marcus Deschauer / Hendrik Kooijman / Ernst J Rummeny / Claus Zimmer / Jan S Kirschke / Dimitrios C Karampinos

PLoS ONE, Vol 12, Iss 2, p e

2017 Volume 0171337

Abstract: PURPOSE:To propose a T2-prepared 3D turbo spin echo (T2prep 3D TSE) sequence for B1-insensitive skeletal muscle T2 mapping and compare its performance with 2D and 3D multi-echo spin echo (MESE) for T2 mapping in thigh muscles of healthy subjects. METHODS: ...

Abstract	PURPOSE:To propose a T2-prepared 3D turbo spin echo (T2prep 3D TSE) sequence for B1-insensitive skeletal muscle T2 mapping and compare its performance with 2D and 3D multi-echo spin echo (MESE) for T2 mapping in thigh muscles of healthy subjects. METHODS:The performance of 2D MESE, 3D MESE and the proposed T2prep 3D TSE in the presence of transmit B1 and B0 inhomogeneities was first simulated. The thigh muscles of ten young and healthy subjects were then scanned on a 3 T system and T2 mapping was performed using the three sequences. Transmit B1-maps and proton density fat fraction (PDFF) maps were also acquired. The subjects were scanned three times to assess reproducibility. T2 values were compared among sequences and their sensitivity to B1 inhomogeneities was compared to simulation results. Correlations were also determined between T2 values, PDFF and B1. RESULTS:The left rectus femoris muscle showed the largest B1 deviations from the nominal value (from 54.2% to 92.9%). Significant negative correlations between T2 values and B1 values were found in the left rectus femoris muscle for 3D MESE (r = -0.72, p<0.001) and 2D MESE (r = -0.71, p<0.001), but not for T2prep 3D TSE (r = -0.32, p = 0.09). Reproducibility of T2 expressed by root mean square coefficients of variation (RMSCVs) were equal to 3.5% in T2prep 3D TSE, 2.6% in 3D MESE and 2.4% in 2D MESE. Significant differences between T2 values of 3D sequences (T2prep 3D TSE and 3D MESE) and 2D MESE were found in all muscles with the highest values for 2D MESE (p<0.05). No significant correlations were found between PDFF and T2 values. CONCLUSION:A strong influence of an inhomogeneous B1 field on the T2 values of 3D MESE and 2D MESE was shown, whereas the proposed T2prep 3D TSE gives B1-insensitive and reproducible thigh muscle T2 mapping.
Keywords	Medicine ; R ; Science ; Q
Subject code	610
Language	English
Publishing date	2017-01-01T00:00:00Z
Publisher	Public Library of Science (PLoS)
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