BACKGROUND AND PURPOSE: Manual segmentation of infarct volume on follow-up MRI diffusion-weighted imaging (MRI-DWI) is considered the gold standard but is prone to rater variability. We assess the variability of manual segmentations of MRI-DWI infarct volume. METHODS: Consecutive patients (May 2018 to May 2019) with the anterior circulation stroke and endovascularly treated were enrolled. All patients underwent 24- to 32-hour follow-up MRI. Three users manually segmented DWI infarct volumes slice by slice twice. The reference standard of DWI infarct volume was generated by the STAPLE algorithm. Intra- and interrater reliability was evaluated using the intraclass correlation coefficient (ICC) by comparing manual segmentations with the reference standard. Spatial measurements were evaluated using metrics of the Dice similarity coefficient (DSC). Volumetric measurements were compared using the lesion volume. RESULTS: The dataset consisted of 44 patients, mean (SD) age was 70.1 years (±10.3), 43% were women, and median baseline NIHSS score was 16. Among three users, the mean DSC for MRI-DWI infarct volume segmentations ranged from 80.6% ± 11.7% to 88.6% ± 7.5%, and the mean absolute volume difference was 2.8 ± 6.8 to 13.0 ± 14.0 ml. Interrater ICC among the users for DSC and infarct volume was .86 (95% confidence interval [95% CI]: .78-.91) and .997 (95% CI: .995-.998). Intrarater ICC for the three users was .83 (95% CI: .69-.93), .84 (95% CI: .72-.91), and .80 (95% CI: .64-.89) for DSC, and .99 (95% CI: .987-.996), .991 (95% CI: .983-.995), and .996 (95% CI: .993-.998) for infarct volume. CONCLUSIONS: Manual segmentation of infarct volume on follow-up MRI-DWI shows excellent agreement and good spatial overlap with the reference standard, suggesting its usefulness for measuring infarct volume on 24- to 32-hour MRI-DWI.

• MeSH
• Algorithms MeSH
• Diffusion Magnetic Resonance Imaging methods   MeSH
• Endovascular Procedures methods   MeSH
• Middle Aged MeSH
• Humans MeSH
• Brain Infarction diagnostic imaging   pathology   therapy   MeSH
• Reproducibility of Results MeSH
• Aged MeSH
• Check Tag
• Middle Aged MeSH
• Humans MeSH
• Male MeSH
• Aged MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH

PURPOSE: Infarct lesion volume (ILV) may serve as an imaging biomarker for clinical outcomes in the early post-treatment stage in patients with acute ischemic stroke. The aim of this study was to evaluate the inter- and intra-rater reliability of manual segmentation of ILV on follow-up non-contrast CT (NCCT) scans. METHODS: Fifty patients from the Prove-IT study were randomly selected for this analysis. Three raters manually segmented ILV on 24-h NCCT scans, slice by slice, three times. The reference standard for ILV was generated by the Simultaneous Truth And Performance Level estimation (STAPLE) algorithm. Intra- and inter-rater reliability was evaluated, using metrics of intraclass correlation coefficient (ICC) regarding lesion volume and the Dice similarity coefficient (DSC). RESULTS: Median age of the 50 subjects included was 74.5 years (interquartile range [IQR] 67-80), 54% were women, median baseline National Institutes of Health Stroke Scale was 18 (IQR 11-22), median baseline ASPECTS was 9 (IQR 6-10). The mean reference standard ILV was 92.5 ml (standard deviation (SD) ± 100.9 ml). The manually segmented ILV ranged from 88.2 ± 91.5 to 135.5 ± 119.9 ml (means referring to the variation between readers, SD within readers). Inter-rater ICC was 0.83 (95%CI: 0.76-0.88); intra-rater ICC ranged from 0.85 (95%CI: 0.72-0.92) to 0.95 (95%CI: 0.91-0.97). The mean DSC among the three readers ranged from 65.5 ± 22.9 to 76.4 ± 17.1% and the mean overall DSC was 72.8 ± 23.0%. CONCLUSION: Manual ILV measurements on follow-up CT scans are reliable to measure the radiological outcome despite some variability.

• MeSH
• Algorithms MeSH
• Stroke * diagnostic imaging   MeSH
• Ischemic Stroke * MeSH
• Humans MeSH
• Tomography, X-Ray Computed methods   MeSH
• Reproducibility of Results MeSH
• Aged MeSH
• Check Tag
• Humans MeSH
• Male MeSH
• Aged MeSH
• Female MeSH
• Publication type
• Journal Article MeSH

BACKGROUND: Segmentation of the gray and white matter (GM, WM) of the human spinal cord in MRI images as well as the analysis of spinal cord diffusivity are challenging. When appropriately segmented, diffusion tensor imaging (DTI) of the spinal cord might be beneficial in the diagnosis and prognosis of several diseases. PURPOSE: To evaluate the applicability of a semiautomatic algorithm provided by ITK-SNAP in classification mode (CLASS) for segmenting cervical spinal cord GM, WM in MRI images and analyzing DTI parameters. STUDY TYPE: Prospective. SUBJECTS: Twenty healthy volunteers. SEQUENCES: 1.5T, turbo spin echo, fast field echo, single-shot echo planar imaging. ASSESSMENT: Three raters segmented the tissues by manual, CLASS, and atlas-based methods (Spinal Cord Toolbox, SCT) on T2 -weighted and DTI images. Masks were quantified by similarity and distance metrics, then analyzed for repeatability and mutual comparability. Masks created over T2 images were registered into diffusion space and fractional anisotropy (FA) values were statistically evaluated for dependency on method, rater, or tissue. STATISTICAL TESTS: t-test, analysis of variance (ANOVA), coefficient of variation, Dice coefficient, Hausdorff distance. RESULTS: CLASS segmentation reached better agreement with manual segmentation than did SCT (P < 0.001). Intra- and interobserver repeatability of SCT was better for GM and WM (both P < 0.001) but comparable with CLASS in entire spinal cord segmentation (P = 0.17 and P = 0.07, respectively). While FA values of whole spinal cord were not influenced by choice of segmentation method, both semiautomatic methods yielded lower FA values (P < 0.005) for GM than did the manual technique (mean differences 0.02 and 0.04 for SCT and CLASS, respectively). Repeatability of FA values for all methods was sufficient, with mostly less than 2% variance. DATA CONCLUSION: The presented semiautomatic method in combination with the proposed approach to data registration and analyses of spinal cord diffusivity can potentially be used as an alternative to atlas-based segmentation. LEVEL OF EVIDENCE: 1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;47:1217-1227.

• MeSH
• Algorithms MeSH
• Anisotropy MeSH
• White Matter diagnostic imaging   MeSH
• Diffusion Magnetic Resonance Imaging * MeSH
• Adult MeSH
• Echo-Planar Imaging * MeSH
• Cervical Cord diagnostic imaging   MeSH
• Humans MeSH
• Young Adult MeSH
• Observer Variation MeSH
• Image Processing, Computer-Assisted methods   MeSH
• Spinal Cord Injuries diagnostic imaging   MeSH
• Prospective Studies MeSH
• Gray Matter diagnostic imaging   MeSH
• Machine Learning MeSH
• Diffusion Tensor Imaging * MeSH
• Check Tag
• Adult MeSH
• Humans MeSH
• Young Adult MeSH
• Male MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH

Introduction: Arterial brain vessel assessment is crucial for the diagnostic process in patients with cerebrovascular disease. Non-invasive neuroimaging techniques, such as time-of-flight (TOF) magnetic resonance angiography (MRA) imaging are applied in the clinical routine to depict arteries. They are, however, only visually assessed. Fully automated vessel segmentation integrated into the clinical routine could facilitate the time-critical diagnosis of vessel abnormalities and might facilitate the identification of valuable biomarkers for cerebrovascular events. In the present work, we developed and validated a new deep learning model for vessel segmentation, coined BRAVE-NET, on a large aggregated dataset of patients with cerebrovascular diseases. Methods: BRAVE-NET is a multiscale 3-D convolutional neural network (CNN) model developed on a dataset of 264 patients from three different studies enrolling patients with cerebrovascular diseases. A context path, dually capturing high- and low-resolution volumes, and deep supervision were implemented. The BRAVE-NET model was compared to a baseline Unet model and variants with only context paths and deep supervision, respectively. The models were developed and validated using high-quality manual labels as ground truth. Next to precision and recall, the performance was assessed quantitatively by Dice coefficient (DSC); average Hausdorff distance (AVD); 95-percentile Hausdorff distance (95HD); and via visual qualitative rating. Results: The BRAVE-NET performance surpassed the other models for arterial brain vessel segmentation with a DSC = 0.931, AVD = 0.165, and 95HD = 29.153. The BRAVE-NET model was also the most resistant toward false labelings as revealed by the visual analysis. The performance improvement is primarily attributed to the integration of the multiscaling context path into the 3-D Unet and to a lesser extent to the deep supervision architectural component. Discussion: We present a new state-of-the-art of arterial brain vessel segmentation tailored to cerebrovascular pathology. We provide an extensive experimental validation of the model using a large aggregated dataset encompassing a large variability of cerebrovascular disease and an external set of healthy volunteers. The framework provides the technological foundation for improving the clinical workflow and can serve as a biomarker extraction tool in cerebrovascular diseases.

• Publication type
• Journal Article MeSH

PURPOSE: To assess the benefit of 4D-CT angiography (4D-CTA) in determination and precise measurement of middle cerebral artery (MCA) occlusion in comparison to CTA. Possible relationship of measured occlusion lengths with recanalization after intravenous thrombolysis was analysed as a second objective. METHODS: Detailed evaluation of complete MCA occlusions in 80 patients before intravenous thrombolysis using temporal maximum intensity projection (tMIP) dataset, calculated from 4D-CTA and conventional single-phase CTA was performed. Further, manual measurement technique was compared to results of semiautomatic procedure (vessel analysis) as reference. Statistical analysis of correlation between MCA occlusion length and IVT efficacy (24 h recanalization rate according modified Thrombolysis In Myocardial Infarction criteria-mTIMI) was performed. RESULTS: The distal end of occlusion was identified in all patients using tMIP, but only in 48 patients (60%) using CTA. The manual measurement method was not statistically different and well correlated with reference tMIP-vessel analysis. (15.4 vs. 16.3 mm; p = 0.434; r = 97). In measurable occlusions by CTA, no significant difference was proved in manually measured lengths using tMIP and CTA (14.5 vs. 13.3 mm; p = 0.089). Favorable recanalization (mTIMI 2-3) was achieved in 37 patients (47%). Length of occlusion in M1 segment (p = 0.002) and M2 segment involvement (p = 0.017) were proved as independent negative predictors of recanalization. Using receiver operating characteristics analysis, the cutoff length of the M1 segment occlusion for favorable recanalization was found to be 12 mm. CONCLUSION: The feasibility of MCA occlusion assessment using tMIP datasets and benefit over conventional CTA were confirmed. The manual measurement method was proved as feasible and simple with good correlation to reference semiautomatic analysis. The significant correlation of the MCA occlusion length and early recanalization was found. The length of 12 mm was recognized as cut-off length for favorable recanalization.

• MeSH
• Acute Disease MeSH
• Four-Dimensional Computed Tomography MeSH
• Adult MeSH
• Fibrinolytic Agents administration & dosage   MeSH
• Infarction, Middle Cerebral Artery drug therapy   radiography   MeSH
• Injections, Intravenous MeSH
• Middle Aged MeSH
• Humans MeSH
• Young Adult MeSH
• Drug Monitoring methods   MeSH
• Cerebral Angiography MeSH
• Observer Variation MeSH
• Prognosis MeSH
• Reproducibility of Results MeSH
• Retrospective Studies MeSH
• Aged, 80 and over MeSH
• Aged MeSH
• Sensitivity and Specificity MeSH
• Tissue Plasminogen Activator administration & dosage   MeSH
• Thrombolytic Therapy methods   MeSH
• Treatment Outcome MeSH
• Check Tag
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Young Adult MeSH
• Male MeSH
• Aged, 80 and over MeSH
• Aged MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Comparative Study MeSH

BACKGROUND: Manual segmentations of intracranial hemorrhage on non-contrast CT images are the gold-standard in measuring hematoma growth but are prone to rater variability. AIMS: We demonstrate that a convex optimization-based interactive segmentation approach can accurately and reliably measure intracranial hemorrhage growth. METHODS: Baseline and 16-h follow-up head non-contrast CT images of 46 subjects presenting with intracranial hemorrhage were selected randomly from the ANNEXA-4 trial imaging database. Three users semi-automatically segmented intracranial hemorrhage to measure hematoma volume for each timepoint using our proposed method. Segmentation accuracy was quantitatively evaluated compared to manual segmentations by using Dice similarity coefficient, Pearson correlation, and Bland-Altman analysis. Intra- and inter-rater reliability of the Dice similarity coefficient and intracranial hemorrhage volumes and volume change were assessed by the intraclass correlation coefficient and minimum detectable change. RESULTS: Among the three users, the mean Dice similarity coefficient, Pearson correlation, and mean difference ranged from 76.79% to 79.76%, 0.970 to 0.980 (p < 0.001), and -1.5 to -0.4 ml, respectively, for all intracranial hemorrhage segmentations. Inter-rater intraclass correlation coefficients between the three users for Dice similarity coefficient and intracranial hemorrhage volume were 0.846 and 0.962, respectively, and the corresponding minimum detectable change was 2.51 ml. Inter-rater intraclass correlation coefficient for intracranial hemorrhage volume change ranged from 0.915 to 0.958 for each user compared to manual measurements, resulting in an minimum detectable change range of 2.14 to 4.26 ml. CONCLUSIONS: We spatially and volumetrically validate a novel interactive segmentation method for delineating intracranial hemorrhage on head non-contrast CT images. Good spatial overlap, excellent volume correlation, and good repeatability suggest its usefulness for measuring intracranial hemorrhage volume and volume change on non-contrast CT images.

• MeSH
• Stroke * diagnostic imaging   MeSH
• Head MeSH
• Intracranial Hemorrhages diagnostic imaging   MeSH
• Humans MeSH
• Tomography, X-Ray Computed MeSH
• Reproducibility of Results MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH

Purpose To develop a deep learning-based method for fully automated quantification of left ventricular (LV) function from short-axis cine MR images and to evaluate its performance in a multivendor and multicenter setting. Materials and Methods This retrospective study included cine MRI data sets obtained from three major MRI vendors in four medical centers from 2008 to 2016. Three convolutional neural networks (CNNs) with the U-NET architecture were trained on data sets of increasing variability: (a) a single-vendor, single-center, homogeneous cohort of 100 patients (CNN1); (b) a single-vendor, multicenter, heterogeneous cohort of 200 patients (CNN2); and (c) a multivendor, multicenter, heterogeneous cohort of 400 patients (CNN3). All CNNs were tested on an independent multivendor, multicenter data set of 196 patients. CNN performance was evaluated with respect to the manual annotations from three experienced observers in terms of (a) LV detection accuracy, (b) LV segmentation accuracy, and (c) LV functional parameter accuracy. Automatic and manual results were compared with the paired Wilcoxon test, Pearson correlation, and Bland-Altman analysis. Results CNN3 achieved the highest performance on the independent testing data set. The average perpendicular distance compared with manual analysis was 1.1 mm ± 0.3 for CNN3, compared with 1.5 mm ± 1.0 for CNN1 (P < .05) and 1.3 mm ± 0.6 for CNN2 (P < .05). The LV function parameters derived from CNN3 showed a high correlation (r2 ≥ 0.98) and agreement with those obtained by experts for data sets from different vendors and centers. Conclusion A deep learning-based method trained on a data set with high variability can achieve fully automated and accurate cine MRI analysis on multivendor, multicenter cine MRI data. © RSNA, 2018 See also the editorial by Colletti in this issue.

• MeSH
• Deep Learning * MeSH
• Image Interpretation, Computer-Assisted methods   MeSH
• Humans MeSH
• Magnetic Resonance Imaging, Cine methods   MeSH
• Retrospective Studies MeSH
• Ventricular Function physiology   MeSH
• Heart Ventricles diagnostic imaging   MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH

BACKGROUND: Lumbar paraspinal muscles (LPM) are a part of the deep spinal stabilisation system and play an important role in stabilising the lumbar spine and trunk. Inadequate function of these muscles is thought to be an essential aetiological factor in low back pain, and several neuromuscular diseases are characterised by dysfunction of LPM. The main aims of our study were to develop a methodology for LPM assessment using advanced magnetic resonance imaging (MRI) methods, including a manual segmentation process, to confirm the measurement reliability, to evaluate the LPM morphological parameters [fat fraction (FF), total muscle volume (TMV) and functional muscle volume (FMV)] in a healthy population, to study the influence of physiological factors on muscle morphology, and to build equations to predict LPM morphological parameters in a healthy population. METHODS: This prospective cross-sectional observational comparative single-centre study was conducted at the University Hospital in Brno, enrolling healthy volunteers from April 2021 to March 2023. MRI of the lumbar spine and LPM (erector spinae muscle and multifidus muscle) were performed using a 6-point Dixon gradient echo sequence. The segmentation of the LPM and the control muscle (psoas muscle) was done manually to obtain FF and TMV in a range from Th12/L1 to L5/S1. Intra-rater and inter-rater reliability were evaluated. Linear regression models were constructed to assess the effect of physiological factors on muscle FF, TMV and FMV. RESULTS: We enrolled 90 healthy volunteers (median age 38 years, 45 men). The creation of segmentation masks and the assessment of FF and TMV proved reliable (Dice coefficient 84% to 99%, intraclass correlation coefficient ≥0.97). The univariable models showed that FF of LPM was influenced the most by age (39.6% to 44.8% of variability, P<0.001); TMV and FMV by subject weight (34.9% to 67.6% of variability, P<0.001) and sex (24.7% to 64.1% of variability, P<0.001). Multivariable linear regression models for FF of LPM included age, body mass index and sex, with R-squared values ranging from 45.4% to 51.1%. Models for volumes of LPM included weight, age and sex, with R-squared values ranged from 37.4% to 76.8%. Equations were developed to calculate predicted FF, TMV and FMV for each muscle. CONCLUSIONS: A reliable methodology has been developed to assess the morphological parameters (biomarkers) of the LPM. The morphological parameters of the LPM are significantly influenced by physiological factors. Equations were constructed to calculate the predicted FF, TMV and FMV of individual muscles in relation to anthropometric parameters, age, and sex. This study, which presented LPM assessment methodology and predicted values of LPM morphological parameters in a healthy population, could improve our understanding of diseases involving LPM (low back pain and some neuromuscular diseases).

• Publication type
• Journal Article MeSH

Neurorehabilitace je základní terapeutický přístup k pa­cientům po míšním poranění. Intenzivní stimulace centrálního nervového systému má za cíl maximální neurologické zlepšení. Nezávisle na neurologickém vývoji je snahou dosáhnout nejvyšší úrovně motorických schopností, vertikalizace a lokomoce za účelem zajistit maximální soběstačnost. Nejzávažnějším motorickým postižením je porucha dechového stereotypu s hraničními ventilačními parametry, která je spojena s poruchou motorických funkcí při lézi hrudní, ale především krční míchy. Aktivita trupového svalstva určuje schopnost vertikalizace do sedu, do stoje, avšak významně ovlivňuje i funkci končetin. Aktivita horních končetin je spojena hlavně s úrovní sebeobsluhy, ovšem samozřejmě i s úrovní mobility. Schopnost zapojení dolních končetin má největší vliv na lokomoci, ale zbytková hybnost může být využitelná např. při přesunech. Rehabilitace je proto zaměřena na trup i končetiny, návrat svalové síly a zapojení paretických svalů do funkčních pohybových stereotypů vč. dechového stereotypu. Ke splnění výše uvedených cílů můžeme využít různé fyzioterapeutické metody. Ty se dají podle potřeby a kreativity fyzioterapeuta různě kombinovat. Základem jsou metody terapie na neurofyziologickém podkladě, mezi které řadíme přístupy založené na principech motorické ontogeneze. Cílem je využít v terapii determinovaných pohybových vzorů a zapojit poškozené segmenty co nejblíže jejich fyziologické funkci. K tomu lze využít metod pracujících s volní kontrolou (např. Dynamická neuromuskulární stabilizace) i metod založených na aktivaci bez volní kontroly pohybu (např. Vojtova reflexní lokomoce). Specifickým terapeutickým přístupem jsou robotické systémy, které efektivně doplňují konvenční metody fyzioterapie, poskytují větší variabilitu terapie a jsou také velmi dobrým motivačním prvkem.

Neurorehabilitation constitutes to be the primary therapeutic approach to patients with spinal cord injury. Intense stimulation of the central nervous system is intended to maximize improvement in neurological function. Besides the neurological development, every attempt is made to achieve the highest possible level of motor function, verticalization and locomotion with the goal to secure maximum self-sufficiency. The most serious motor impairment is the respiratory pattern disorder with limited ventilatory parameters. This is due to impairment of motor functions caused by thoracic but primarily cervical lesions. Strength of the trunk muscles determines the ability of verticalization to the sitting or standing position and is also influenced by the upper and lower limb function. Activity of the upper extremities predominantly determines the level of self-sufficiency but also the level of mobility. Ability to recruit lower extremity function is crucial for locomotion though residual mobility may be useful e.g. during transfers. Rehabilitation is therefore focused on training the trunk as well as the limb muscles. The desired outcome is the return of muscle strength and inclusion of paretic muscles into functional movement patterns as well as respiratory pattern. To meet these goals, several different physiotherapeutic methods may be utilized. These may be combined as needed and according to a therapist’s creativity. The treatment is based on neurophysiological principles including those based on motor ontogenesis. The objective is to utilize predetermined motor targets and recruit the damaged segments into their physiologic function. To that end, it is possible to utilize methods that employ voluntary muscle control (e.g. Dynamic Neuromuscular Stabilization) as well as methods based on involuntary movement control (e.g. Vojta’s reflex locomotion). A specific therapeutic approach utilizes robotic systems that complete more conventional methods of physiotherapy and afford a greater variety of treatment. This also provides a significant motivating element.

• Keywords
• pohybový stereotyp,
• MeSH
• Breathing Exercises methods   MeSH
• Occupational Therapy MeSH
• Humans MeSH
• Locomotion MeSH
• Musculoskeletal Manipulations methods   MeSH
• Neurological Rehabilitation * methods   MeSH
• Paraplegia rehabilitation   MeSH
• Dependent Ambulation MeSH
• Motor Activity physiology   MeSH
• Patient Positioning MeSH
• Spinal Cord Injuries * rehabilitation   MeSH
• Posture MeSH
• Robotics MeSH
• Independent Living MeSH
• Physical Therapy Modalities * MeSH
• Wheelchairs MeSH
• Check Tag
• Humans MeSH
• Publication type
• Research Support, Non-U.S. Gov't MeSH

Cílem této studie bylo porovnat rozdíl v postavení pánve vzniklý vlivem svalových dysbalancí u skupiny dětí ve věku 11-13 let ze sportovních klubů se zaměřením na karate, s kontrolní skupinou dětí stejného věku. V rámci studie proběhlo měření somatometrických charakteristik a tělesného složení (% BF) dětí středního školního věku, vyšetření technikami manuální medicíny pro zjištění postavení pánve a bederní lordózy (Lewit, 2003). Hlavní použitou metodou byla 3D analýza pohybu pro zjištění rozsahu pohybu pánve z maximální retroverze do maximální anteverze. Byl hodnocen pohyb pánve v prostoru (pohyb segmentu pánve vůči souřadnicovému systému laboratoře - LSS) a pohyb bederní páteře vůči pánvi (neboli pohyb segmentu bederní páteře vůči segmentu pánve). Výsledky z 3 D analýzy pohybu ukázaly, že velikost rozsahu pohybu (ať byla porovnávána mediány či průměry) se při porovnání karatistů a ne-karatistů významně nelišila. Významné rozdíly byly zjištěny pouze v hodnotách výběrových směrodatných odchylek pohybu (p=0,03). Lze tedy konstatovat, že i přes malé počty probandů se podařilo prokázat rozdíl mezi karatisty a ne-karatisty alespoň ve variabilitě rozsahů pohybu.

The aim of this study was to compare the difference in the position of the pelvis due to muscle imbalances resulting in a group of children aged 11-13 years from sports clubs to focus on karate, with a control group of children of the same age. The study concentrated on somatometric measurement characteristics and body composition (% BF) of children in middle school age, examination manual medicine techniques to determine the position of the pelvis and lumbar lordosis (Lewit, 2003). The main method used was a 3D motion analysis to determine the range of motion of the pelvis from the maximum to the maximum retroversion anteversion. There were evaluated pelvic movement in space (motion of pelvis segment against laboratory coordinate system - LCS) and lumbar spine movement towards pelvis (or motion of lumbar spine segment to pelvis segment). Results from 3-D motion analysis showed, that the range of movement (either compared the medians or averages), if compared karate with non-karate practising pupils, was not significantly different. Significant differences were found only in the values of sample standard deviations of motion (p=0.03). It can be said that despite the small numbers of subjects the data are able to demonstrate the difference between karate practising and karate nonpractising pupils at least in the variability of ranges of movement.

• Keywords
• svalová nerovnováha, 3D analýza pohybu, manuální medicína, pohyb pánve, karate,
• MeSH
• Martial Arts * physiology   statistics & numerical data   MeSH
• Child MeSH
• Humans MeSH
• Adolescent MeSH
• Pelvis * physiology   MeSH
• Motor Activity * MeSH
• Muscles MeSH
• Imaging, Three-Dimensional MeSH
• Check Tag
• Child MeSH
• Humans MeSH
• Adolescent MeSH
• Male MeSH
• Female MeSH