Diffusion Tensor Imaging Shows Differences Between Myotonic Dystrophy Type 1 and Type 2

2021 ◽  
pp. 1-14
Author(s):  
R. Rehmann ◽  
C. Schneider-Gold ◽  
M. Froeling ◽  
A.K. Güttsches ◽  
M. Rohm ◽  
...  
Keyword(s):  
Diffusion Tensor Imaging ◽  
Myotonic Dystrophy ◽  
Diffusion Tensor ◽  
Healthy Controls ◽  
Muscle Involvement ◽  
Diffusion Parameters ◽  
Fat Fraction ◽  
Calf Muscles

Background: Myotonic Dystrophies type 1 and type 2 are hereditary myopathies with dystrophic muscle degeneration in varying degrees. Differences in muscle diffusion between both diseases have not been evaluated yet. Objective: To evaluate the ability to of muscle diffusion tensor imaging (mDTI) and Dixon fat-quantification to distinguish between Myotonic dystrophy (DM) type 1 and type 2 and if both diseases show distinct muscle involvement patterns. Methods: We evaluated 6 thigh and 7 calf muscles (both legs) of 10 DM 1 and 13 DM 2 and 28 healthy controls (HC) with diffusion tensor imaging, T1w and mDixonquant sequences in a 3T MRI scanner. The quantitative mDTI-values axial diffusivity (λ1), mean diffusivity (MD), radial diffusivity (RD) and fractional anisotropy (FA) as well as fat-fraction were analysed. CTG-Triplett repeat-length of DM 1 patients was correlated to diffusion metrics and fat-fraction. Results: mDTI showed significant differences between DM 1 and DM 2 vs. healthy controls in diffusion parameters of the thigh (all p < 0.001) except for FA (p = 0.0521 / 0.8337). In calf muscles mDTI showed significant differences between DM 1 and DM 2 patients (all p < 0.0001) as well as between DM 1 patients and controls (all p = 0.0001). Thigh muscles had a significant higher fat-fraction in both groups vs. controls (p < 0.05). There was no correlation of CTG triplet length with mDTI values and fat-fraction. Discussion: mDTI reveals specific changes of the diffusion parameters and fat-fraction in muscles of DM 1 and DM 2 patients. Thus, the quantitative MRI methods presented in this study provide a powerful tool in differential diagnosis and follow-up of DM 1 and DM 2, however, the data must be validated in larger studies.

scholarly journals Diffusion tensor imaging reveals widespread white matter abnormalities in children and adolescents with myotonic dystrophy type 1

2012 ◽  
Vol 260 (4) ◽  
pp. 1122-1131 ◽  
Author(s):  
Jeffrey R. Wozniak ◽  
Bryon A. Mueller ◽  
Christopher J. Bell ◽  
Ryan L. Muetzel ◽  
Kelvin O. Lim ◽  
...  
Keyword(s):  
Diffusion Tensor Imaging ◽  
White Matter ◽  
Children And Adolescents ◽  
Myotonic Dystrophy ◽  
Diffusion Tensor ◽  
Myotonic Dystrophy Type 1 ◽  
Myotonic Dystrophy Type ◽  
White Matter Abnormalities

G.P.14.06 Sleep disturbances in myotonic dystrophy type 2: A comparison with myotonic dystrophy type 1 and healthy controls

2009 ◽  
Vol 19 (8-9) ◽  
pp. 645
Author(s):  
A.A. Tieleman ◽  
H. Knoop ◽  
A. van de Logt ◽  
G. Bleijenberg ◽  
B.G.M. van Engelen ◽  
...  
Keyword(s):  
Myotonic Dystrophy ◽  
Sleep Disturbances ◽  
Myotonic Dystrophy Type 1 ◽  
Healthy Controls ◽  
Myotonic Dystrophy Type ◽  
Myotonic Dystrophy Type 2

scholarly journals Investigating Brain Microstructural Alterations in Type 1 and Type 2 Diabetes Using Diffusion Tensor Imaging: A Systematic Review

2021 ◽  
Vol 11 (2) ◽  
pp. 140
Author(s):  
Abdulmajeed Alotaibi ◽  
Christopher Tench ◽  
Rebecca Stevenson ◽  
Ghadah Felmban ◽  
Amjad Altokhis ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Systematic Review ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Diffusion Tensor Imaging ◽  
Diffusion Tensor ◽  
Microstructural Alterations ◽  
The Impact

Type 1 and type 2 diabetes mellitus have an impact on the microstructural environment and cognitive functions of the brain due to its microvascular/macrovascular complications. Conventional Magnetic Resonance Imaging (MRI) techniques can allow detection of brain volume reduction in people with diabetes. However, conventional MRI is insufficiently sensitive to quantify microstructural changes. Diffusion Tensor Imaging (DTI) has been used as a sensitive MRI-based technique for quantifying and assessing brain microstructural abnormalities in patients with diabetes. This systematic review aims to summarise the original research literature using DTI to quantify microstructural alterations in diabetes and the relation of such changes to cognitive status and metabolic profile. A total of thirty-eight published studies that demonstrate the impact of diabetes mellitus on brain microstructure using DTI are included, and these demonstrate that both type 1 diabetes mellitus and type 2 diabetes mellitus may affect cognitive abilities due to the alterations in brain microstructures.

scholarly journals High Inter-Rater Reliability of Manual Segmentation and Volume-Based Tractography in Healthy and Dystrophic Human Calf Muscle

Diagnostics ◽  
2021 ◽  
Vol 11 (9) ◽  
pp. 1521
Author(s):  
Johannes Forsting ◽  
Marlena Rohm ◽  
Martijn Froeling ◽  
Anne-Katrin Güttsches ◽  
Matthias Vorgerd ◽  
...  
Keyword(s):  
Diffusion Tensor ◽  
Neuromuscular Diseases ◽  
Healthy Controls ◽  
Manual Segmentation ◽  
Rater Reliability ◽  
Additional Information ◽  
Diffusion Parameters ◽  
Coefficients Of Variation ◽  
Human Calf ◽  
Calf Muscles

Background: Muscle diffusion tensor imaging (mDTI) is a promising surrogate biomarker in the evaluation of muscular injuries and neuromuscular diseases. Since mDTI metrics are known to vary between different muscles, separation of different muscles is essential to achieve muscle-specific diffusion parameters. The commonly used technique to assess DTI metrics is parameter maps based on manual segmentation (MSB). Other techniques comprise tract-based approaches, which can be performed in a previously defined volume. This so-called volume-based tractography (VBT) may offer a more robust assessment of diffusion metrics and additional information about muscle architecture through tract properties. The purpose of this study was to assess DTI metrics of human calf muscles calculated with two segmentation techniques—MSB and VBT—regarding their inter-rater reliability in healthy and dystrophic calf muscles. Methods: 20 healthy controls and 18 individuals with different neuromuscular diseases underwent an MRI examination in a 3T scanner using a 16-channel Torso XL coil. DTI metrics were assessed in seven calf muscles using MSB and VBT. Coefficients of variation (CV) were calculated for both techniques. MSB and VBT were performed by two independent raters to assess inter-rater reliability by ICC analysis and Bland-Altman plots. Next to analysis of DTI metrics, the same assessments were also performed for tract properties extracted with VBT. Results: For both techniques, low CV were found for healthy controls (≤13%) and neuromuscular diseases (≤17%). Significant differences between methods were found for all diffusion metrics except for λ1. High inter-rater reliability was found for both MSB and VBT (ICC ≥ 0.972). Assessment of tract properties revealed high inter-rater reliability (ICC ≥ 0.974). Conclusions: Both segmentation techniques can be used in the evaluation of DTI metrics in healthy controls and different NMD with low rater dependency and high precision but differ significantly from each other. Our findings underline that the same segmentation protocol must be used to ensure comparability of mDTI data.

Sign in / Sign up

Export Citation Format

Share Document