4 results on '"Laura Secondulfo"'
Search Results
2. A diffusion tensor-based method facilitating volumetric assessment of fiber orientations in skeletal muscle.
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Laura Secondulfo, Melissa T Hooijmans, Joep J Suskens, Valentina Mazzoli, Mario Maas, Johannes L Tol, Aart J Nederveen, and Gustav J Strijkers
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Medicine ,Science - Abstract
BackgroundThe purpose of this study was to develop a DTI-based method to quantitatively assess fiber angles and changes therein in leg muscles in order to facilitate longitudinal studies on muscle fiber architectural adaptations in healthy subjects.MethodsThe upper legs of five volunteers were scanned twice on the same day. The right lower legs of five volunteers were scanned twice with the ankle in three positions, i.e. -15° dorsiflexion, 0° neutral position, and 30° plantarflexion. The MRI protocols consisted of a noise scan, a 3-point mDixon scan and a DTI scan. Fiber-angle color maps were generated for four muscles in the upper legs and two muscles in the lower leg. Voxel-wise fiber angles (θ) were calculated from the angle between the principal eigenvector of the diffusion tensor and a reference line defined between the origo and insertion points of each muscle. Bland-Altman analysis, intraclass correlation coefficient (ICC), coefficient of variation (CV%), minimal detectable change (MDC), standard error (SE) and Friedman test were used for assessing the feasibility of this method and in order to have an indication of the repeatability and the sensitivity.ResultsBland-Altman analysis showed good repeatability (CV%ConclusionOur method facilitates fast inspection and quantification of muscle fiber angles in the lower and upper leg muscles in rest and detection of changes in lower-leg muscle fiber angles with varying ankle angles.
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- 2022
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3. Effect of two eccentric hamstring exercises on muscle architectural characteristics assessed with diffusion tensor MRI
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Jozef J. M. Suskens, Laura Secondulfo, Özgür Kiliç, Melissa T. Hooijmans, Gustaaf Reurink, Martijn Froeling, Aart J. Nederveen, Gustav J. Strijkers, Johannes L. Tol, Biomedical Engineering and Physics, Graduate School, Orthopedic Surgery and Sports Medicine, Amsterdam Movement Sciences, Radiology and Nuclear Medicine, AMS - Ageing & Vitality, AMS - Sports, AMS - Musculoskeletal Health, ACS - Diabetes & metabolism, ACS - Atherosclerosis & ischemic syndromes, and ACS - Heart failure & arrhythmias
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Physical Therapy, Sports Therapy and Rehabilitation ,Orthopedics and Sports Medicine ,hamstring injury ,fascicle length ,diffusion tensor imaging ,pennation angle - Abstract
Objectives: To evaluate the effect of a Nordic hamstring exercise or Diver hamstring exercise intervention on biceps femoris long head, semitendinosus and semimembranosus muscle's fascicle length and orientation through diffusion tensor imaging (DTI) with magnetic resonance imaging. Methods: In this three-arm, single-center, randomized controlled trial, injury-free male basketball players were randomly assigned to a Nordic, Diver hamstring exercise intervention or control group. The primary outcome was the DTI-derived fascicle length and orientation of muscles over 12 weeks. Results: Fifty-three participants were included for analysis (mean age 22 ± 7 years). Fascicle length in the semitendinosus over 12 weeks significantly increased in the Nordic-group (mean [M]: 20.8 mm, 95% confidence interval [95% CI]: 7.8 to 33.8) compared with the Control-group (M: 0.9 mm, 95% CI: −7.1 to 8.9), mean between-groups difference: 19.9 mm, 95% CI: 1.9 to 37.9, p = 0.026. Fascicle orientation in the biceps femoris long head over 12 weeks significantly decreased in the Diver-group (mean: -2.6°, 95% CI: −4.1 to −1.0) compared with the Control-group (mean: −0.2°, 95% CI: −1.4 to 1.0), mean between-groups difference: -2.4°, 95% CI: −4.7 to −0.1, p = 0.039. Conclusion: The Nordic hamstring exercise intervention did significantly increase the fascicle length of the semitendinosus and the Diver hamstring exercise intervention did significantly change the orientation of fascicles of the biceps femoris long head. As both exercises are complementary to each other, the combination is relevant for preventing hamstring injuries.
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- 2022
4. Supervised segmentation framework for evaluation of diffusion tensor imaging indices in skeletal muscle
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Melissa T. Hooijmans, Vincent L. Aengevaeren, Aart J. Nederveen, Jithsa R. Monte, Augustin C. Ogier, David Bendahan, Laura Secondulfo, Gustav J. Strijkers, Graduate School, ACS - Diabetes & metabolism, Amsterdam Neuroscience - Brain Imaging, Amsterdam Gastroenterology Endocrinology Metabolism, Amsterdam Movement Sciences, Radiology and Nuclear Medicine, Amsterdam Neuroscience, Biomedical Engineering and Physics, ACS - Atherosclerosis & ischemic syndromes, ACS - Heart failure & arrhythmias, AMS - Sports, Department of Biomedical Engineering and Physics, Academic Medical Center, University of Amsterdam [Amsterdam] (UvA), Images et Modèles (I&M), Laboratoire d'Informatique et Systèmes (LIS), Aix Marseille Université (AMU)-Université de Toulon (UTLN)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Université de Toulon (UTLN)-Centre National de la Recherche Scientifique (CNRS), Centre de résonance magnétique biologique et médicale (CRMBM), Aix Marseille Université (AMU)-Assistance Publique - Hôpitaux de Marseille (APHM)-Centre National de la Recherche Scientifique (CNRS), Department of Radiology and Nuclear Medicine [Amsterdam], VU University Medical Center [Amsterdam], Radboud University Medical Centre [Nijmegen, The Netherlands], Academic Medical Center - Academisch Medisch Centrum [Amsterdam] (AMC), and Radboud University Medical Center [Nijmegen]
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Male ,Time Factors ,applications ,muscle ,Vascular damage Radboud Institute for Health Sciences [Radboudumc 16] ,diffusion tensor imaging (DTI) ,030218 nuclear medicine & medical imaging ,Correlation ,Automation ,03 medical and health sciences ,0302 clinical medicine ,post‐acquisition processing ,Fractional anisotropy ,Image Processing, Computer-Assisted ,medicine ,Humans ,Radiology, Nuclear Medicine and imaging ,Segmentation ,Muscle, Skeletal ,Spectroscopy ,Mathematics ,musculoskeletal ,quantitation ,business.industry ,Skeletal muscle ,Pattern recognition ,Regression analysis ,Middle Aged ,Editor's Pick ,Regression ,Diffusion Tensor Imaging ,Muscle disease ,medicine.anatomical_structure ,methods and engineering ,Linear Models ,Molecular Medicine ,[SDV.IB]Life Sciences [q-bio]/Bioengineering ,Artificial intelligence ,business ,Algorithms ,030217 neurology & neurosurgery ,post-acquisition processing ,Diffusion MRI - Abstract
Diffusion tensor imaging (DTI) is becoming a relevant diagnostic tool to understand muscle disease and map muscle recovery processes following physical activity or after injury. Segmenting all the individual leg muscles, necessary for quantification, is still a time‐consuming manual process. The purpose of this study was to evaluate the impact of a supervised semi‐automatic segmentation pipeline on the quantification of DTI indices in individual upper leg muscles. Longitudinally acquired MRI datasets (baseline, post‐marathon and follow‐up) of the upper legs of 11 subjects were used in this study. MR datasets consisted of a DTI and Dixon acquisition. Semi‐automatic segmentations for the upper leg muscles were performed using a transversal propagation approach developed by Ogier et al on the out‐of‐phase Dixon images at baseline. These segmentations were longitudinally propagated for the post‐marathon and follow‐up time points. Manual segmentations were performed on the water image of the Dixon for each of the time points. Dice similarity coefficients (DSCs) were calculated to compare the manual and semi‐automatic segmentations. Bland‐Altman and regression analyses were performed, to evaluate the impact of the two segmentation methods on mean diffusivity (MD), fractional anisotropy (FA) and the third eigenvalue (λ 3). The average DSC for all analyzed muscles over all time points was 0.92 ± 0.01, ranging between 0.48 and 0.99. Bland‐Altman analysis showed that the 95% limits of agreement for MD, FA and λ 3 ranged between 0.5% and 3.0% for the transversal propagation and between 0.7% and 3.0% for the longitudinal propagations. Similarly, regression analysis showed good correlation for MD, FA and λ 3 (r = 0.99, p < 60; 0.0001). In conclusion, the supervised semi‐automatic segmentation framework successfully quantified DTI indices in the upper‐leg muscles compared with manual segmentation while only requiring manual input of 30% of the slices, resulting in a threefold reduction in segmentation time., The performance of a semi‐automatic segmentation framework was compared to manual segmentation for quantification of DTI indices in individual upper leg muscles in a longitudinal study set‐up. The main advantage is a 3‐fold reduction in segmentation time at baseline and 10‐fold reduction for 3 time points. The average DSC value for all analyzed muscles over all time points was 0.92 ± 0.01. Regression analysis and Bland‐Altman analysis showed that the agreement and correlation was good for MD,FA and higher for λ 3.
- Published
- 2021
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