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BACKGROUND: Multi-segment foot models (MFMs) provide a better understanding of the intricate biomechanics of the foot, yet it is unclear if they accurately differentiate foot type function during locomotion. RESEARCH QUESTION: We employed an MFM to detect subtle kinematic differences between foot types, including: pes cavus, neutrally aligned, and asymptomatic and symptomatic pes planus. The study investigates how variable the results of this MFM are and if it can detect kinematic differences between pathologic and non-pathologic foot types during the stance phase of gait. METHODS: Independently, three raters instrumented three subjects on three days to assess variability. In a separate cohort, each foot type was statically quantified for ten subjects per group. Each subject walked while instrumented with a four-segment foot model to assess static alignment and foot motion during the stance phase of gait. Statistical analysis performed with a linear mixed effects regression. RESULTS: Model variability was highest for between-day and lowest for between-rater, with all variability measures being within the true sample variance. Almost all static measures (radiographic, digital scan, and kinematic markers) differed significantly by foot type. Sagittal hindfoot to leg and forefoot to leg kinematics differed between foot types during late stance, as well as coronal hallux to forefoot range of motion. The MFM had low between-rater variability and may be suitable for multiple raters to apply to a single study sample without introducing significant error. The model, however, only detected a few dynamic differences, with the most dramatic being the hallux to forefoot coronal plane range of motion. SIGNIFICANCE: Results only somewhat aligned with previous work. It remains unclear if the MFM is sensitive enough to accurately detect different motion between foot types (pathologic and non-pathologic). A more accurate method of tracking foot bone motion (e.g., biplane fluoroscopy) may be needed to address this question.
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Postural control is one of the primary body functions for fall prevention. Unexpected perturbation-based balance training is effective for improving postural control. However, the effect of perturbation-based training using assistive devices on muscle activity and co-contraction for standing balance is still unclear. This training is also difficult to perform easily because it requires large instruments or expert guidance. The purpose of this study is to demonstrate the effect of perturbation-based balance training using a wearable balance training device (WBTD) on postural control. In this study, fourteen healthy young adult males were assigned to either a WBTD group or a sham group. In the intervention session, participants in the WBTD group were perturbed either left or right direction at random timing by the WBTD during tandem stance balance training. Participants in the Sham group did not receive external perturbation during tandem stance balance training. Before and after the intervention session, participants of both groups underwent unexpected lateral perturbation postural control testing (pre- and post-test). The normalized integral of electromyography (IEMG), co-contraction index (CCI), and center of pressure (COP) parameters were measured in the pre- and post-test. Experimental results showed that the WBTD group in the post-test significantly decreased left Gluteus Medius IEMG, CCI of both Gluteus Medius, and peak [Formula: see text] velocity, compared to those of the pre-test ( [Formula: see text], p =0.024 , p =0.031 , respectively). We conclude that balance training using WBTD could improve flexible postural control adjustment via cooperative muscle activation.
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Electromiografía , Voluntarios Sanos , Contracción Muscular , Músculo Esquelético , Equilibrio Postural , Posición de Pie , Dispositivos Electrónicos Vestibles , Humanos , Masculino , Equilibrio Postural/fisiología , Adulto Joven , Músculo Esquelético/fisiología , Contracción Muscular/fisiología , AdultoRESUMEN
PURPOSE: The focal radiation therapy (RT) boost technique was shown in a phase III randomized controlled trial (RCT) to improve prostate cancer outcomes without increasing toxicity. This technique relies on the accurate delineation of prostate tumors on MRI. A recent prospective study evaluated radiation oncologists' accuracy when asked to delineate prostate tumors on MRI and demonstrated high variability in tumor contours. We sought to evaluate the impact of contour variability and inaccuracy on predicted clinical outcomes. We hypothesized that radiation oncologists' contour inaccuracies would yield meaningfully worse clinical outcomes. METHODS AND MATERIALS: Forty-five radiation oncologists and 2 expert radiologists contoured prostate tumors on 30 patient cases. Of these cases, those with CT simulation or diagnostic CT available were selected for analysis. A knowledge-based planning model was developed to generate focal RT boost plans for each contour per the RCT protocol. The probability of biochemical failure (BF) was determined using a model from the RCT. The primary metric evaluated was delta BF (DBF = Participant BF - Expert BF). An absolute increase in BF ≥5% was considered clinically meaningful. RESULTS: Eight patient cases and 394 target volumes for focal RT boost planning were included in this analysis. In general, participant plans were associated with worse predicted clinical outcomes compared to the expert plan, with an average absolute increase in BF of 4.3%. Of participant plans, 37% were noted to have an absolute increase in BF of 5% or more. CONCLUSIONS: Radiation oncologists' attempts to contour tumor targets for focal RT boost are frequently inaccurate enough to yield meaningfully inferior clinical outcomes for patients.
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Children in rural communities consume more energy-dense foods relative to their urban peers. Identifying effective interventions for improving energy intake patterns are needed to address these geographic disparities. The primary aim of this study was to harness the benefits of physical activity on children's executive functioning to see if these improvements lead to acute changes in eating behaviors. In a randomized crossover design, 91 preadolescent (8-10y; M age = 9.48 ± 0.85; 50.5% female; 85.7% White, 9.9% Multiracial, 9.9% Hispanic) children (86% rural) completed a 20-minute physical activity condition (moderate intensity walking) and time-matched sedentary condition (reading and/or coloring) ~ 14 days apart. Immediately following each condition, participants completed a behavioral inhibition task and then eating behaviors (total energy intake, relative energy intake, snack intake) were measured during a multi-array buffet test meal. After adjusting for period and order effects, body fat (measured via DXA), and depressive symptoms, participants experienced significant small improvements in their behavioral inhibition following the physical activity versus sedentary condition (p = 0.04, Hedge's g = 0.198). Eating behaviors did not vary by condition, nor did improvements in behavioral inhibition function as a mediator (ps > 0.09). Thus, in preadolescent children, small improvements in behavioral inhibition from physical activity do not produce acute improvements in energy intake. Additional research is needed to clarify whether the duration and/or intensity of physical activity sessions would produce different results in this age group, and whether intervention approaches and corresponding mechanisms of change vary by individual factors, like age and degree of food cue responsivity.
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Ingestión de Energía , Ejercicio Físico , Conducta Alimentaria , Inhibición Psicológica , Humanos , Femenino , Masculino , Niño , Conducta Alimentaria/psicología , Ejercicio Físico/psicología , Estudios Cruzados , Conducta Infantil/psicología , Función Ejecutiva , Conducta SedentariaRESUMEN
ABSTRACT: Mongold, SJ, Ricci, AW, Hahn, ME, and Callahan, DM. Skeletal muscle compliance and echogenicity in resistance-trained and nontrained women. J Strength Cond Res 38(4): 671-680, 2024-Noninvasive assessment of muscle mechanical properties in clinical and performance settings tends to rely on manual palpation and emphasizes examination of musculotendinous stiffness. However, measurement standards are highly subjective. The purpose of the study was to compare musculotendinous stiffness in adult women with varying resistance training history while exploring the use of multiple tissue compliance measures. We identified relationships between tissue stiffness and morphology, and tested the hypothesis that combining objective measures of morphology and stiffness would better predict indices of contractile performance. Resistance-trained (RT) women (n = 11) and nontrained (NT) women (n = 10) participated in the study. Muscle echogenicity and morphology were measured using B-mode ultrasonography (US). Vastus lateralis (VL) and patellar tendon (PT) stiffness were measured using digital palpation and US across submaximal isometric contractions. Muscle function was evaluated during maximal voluntary isometric contraction (MVIC) of the knee extensors (KEs). Resistance trained had significantly greater PT stiffness and reduced echogenicity (p < 0.01). Resistance trained also had greater strength per body mass (p < 0.05). Muscle echogenicity was strongly associated with strength and rate of torque development (RTD). Patellar tendon passive stiffness was associated with RTD normalized to MVIC (RTDrel; r = 0.44, p < 0.05). Patellar tendon stiffness was greater in RT young women. No predictive models of muscle function incorporated both stiffness and echogenicity. Because RTDrel is a clinically relevant measure of rehabilitation in athletes and can be predicted by digital palpation, this might represent a practical and objective measure in settings where RTD may not be easy to measure directly.
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Articulación de la Rodilla , Músculo Esquelético , Adulto , Humanos , Femenino , Músculo Esquelético/diagnóstico por imagen , Músculo Esquelético/fisiología , Articulación de la Rodilla/fisiología , Contracción Muscular/fisiología , Músculo Cuádriceps/fisiología , Contracción Isométrica/fisiología , Ultrasonografía , Fuerza Muscular/fisiología , TorqueRESUMEN
Background: Restriction Spectrum Imaging restriction score (RSIrs) is a quantitative biomarker for detecting clinically significant prostate cancer (csPCa). However, the quantitative value of the RSIrs is affected by imaging parameters such as echo time (TE). Purpose: The purpose of the present study is to develop a calibration method to account for differences in echo times and facilitate use of RSIrs as a quantitative biomarker for the detection of csPCa. Methods: This study included 197 consecutive patients who underwent MRI and biopsy examination; 97 were diagnosed with csPCa (grade group ≥ 2). RSI data were acquired three times during the same session: twice at minimum TEâ¼75ms and once at TE=90ms (TEmin 1 , TEmin 2 , and TE90, respectively). A proposed calibration method, trained on patients without csPCa, estimated a linear scaling factor (f) for each of the four diffusion compartments (C) of the RSI signal model. A linear regression model was determined to match C-maps of TE90 to the reference C-maps of TEmin 1 within the interval ranging from 95 th to 99 th percentile of signal intensity within the prostate. RSIrs comparisons were made at 98 th percentile within each patient's prostate. We compared RSIrs from calibrated TE90 (RSIrs TE90corr ) and uncorrected TE90 (RSIrs TE90 ) to RSIrs from reference TEmin 1 (RSIrs TEmin1 ) and repeated TEmin 2 (RSIrs TEmin2 ). Calibration performance was evaluated with sensitivity, specificity, area under the ROC curve, positive predicted value, negative predicted value, and F1-score. Results: Scaling factors for C 1 , C 2 , C 3 , and C 4 were estimated as 1.70, 1.38, 1.03, and 1.19, respectively. In non-csPCa cases, the 98 th percentile of RSIrs TEmin2 and RSIrs TEmin1 differed by 0.27±0.86SI (mean±standard deviation), whereas RSIrs TE90 differed from RSIrs TEmin1 by 1.81±1.20SI. After calibration, this bias was reduced to -0.41±1.20SI, representing a 78% reduction in absolute error. For patients with csPCa, the difference was 0.54±1.98SI between RSIrs TEmin2 and RSIrs TEmin1 and 2.28±2.06SI between RSIrs TE90 and RSIrs TEmin1 . After calibration, the mean difference decreased to -0.86SI, a 38% reduction in absolute error. At the Youden index for patient-level classification of csPCa (8.94SI), RSIrs TEmin1 has a sensitivity of 66% and a specificity of 72%. Prior to calibration, RSIrs TE90 at the same threshold tended to over-diagnose benign cases (sensitivity 44%, specificity 88%). Post-calibration, RSIrs TE90corr performs more similarly to the reference (sensitivity 71%, specificity 62%). Conclusion: The proposed linear calibration method produces similar quantitative biomarker values for acquisitions with different TE, reducing TE-induced error by 78% and 38% for non-csPCa and csPCa, respectively.
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OBJECTIVE: To identify vaginal morphology and position factors associated with prolapse recurrence following vaginal surgery. DESIGN: Secondary analysis of magnetic resonance images (MRI) of the Defining Mechanisms of Anterior Vaginal Wall Descent cross-sectional study. SETTING: Eight clinical sites in the US Pelvic Floor Disorders Network. POPULATION OR SAMPLE: Women who underwent vaginal mesh hysteropexy (hysteropexy) with sacrospinous fixation or vaginal hysterectomy with uterosacral ligament suspension (hysterectomy) for uterovaginal prolapse between April 2013 and February 2015. METHODS: The MRI (rest, strain) obtained 30-42 months after surgery, or earlier for participants with recurrence who desired reoperation before 30 months, were analysed. MRI-based prolapse recurrence was defined as prolapse beyond the hymen at strain on MRI. Vaginal segmentations (at rest) were used to create three-dimensional models placed in a morphometry algorithm to quantify and compare vaginal morphology (angulation, dimensions) and position. MAIN OUTCOME MEASURES: Vaginal angulation (upper, lower and upper-lower vaginal angles in the sagittal and coronal plane), dimensions (length, maximum transverse width, surface area, volume) and position (apex, mid-vagina) at rest. RESULTS: Of the 82 women analysed, 12/41 (29%) in the hysteropexy group and 22/41 (54%) in the hysterectomy group had prolapse recurrence. After hysteropexy, women with recurrence had a more laterally deviated upper vagina (p = 0.02) at rest than women with successful surgery. After hysterectomy, women with recurrence had a more inferiorly (lower) positioned vaginal apex (p = 0.01) and mid-vagina (p = 0.01) at rest than women with successful surgery. CONCLUSIONS: Vaginal angulation and position were associated with prolapse recurrence and suggestive of vaginal support mechanisms related to surgical technique and potential unaddressed anatomical defects. Future prospective studies in women before and after prolapse surgery may distinguish these two factors.
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Prolapso de Órgano Pélvico , Prolapso Uterino , Femenino , Humanos , Estudios Prospectivos , Estudios Transversales , Resultado del Tratamiento , Procedimientos Quirúrgicos Ginecológicos/métodos , Vagina/diagnóstico por imagen , Vagina/cirugía , Histerectomía Vaginal , Prolapso Uterino/cirugía , Prolapso de Órgano Pélvico/cirugíaRESUMEN
PURPOSE: In a phase III randomized trial, adding a radiation boost to tumor(s) visible on MRI improved prostate cancer (PCa) disease-free and metastasis-free survival without additional toxicity. Radiation oncologists' ability to identify prostate tumors is critical to widely adopting intraprostatic tumor radiotherapy boost for patients. A diffusion MRI biomarker, called the Restriction Spectrum Imaging restriction score (RSIrs), has been shown to improve radiologists' identification of clinically significant PCa. We hypothesized that (1) radiation oncologists would find accurately delineating PCa tumors on conventional MRI challenging and (2) using RSIrs maps would improve radiation oncologists' accuracy for PCa tumor delineation. METHODS AND MATERIALS: In this multi-institutional, international, prospective study, 44 radiation oncologists (participants) and 2 expert radiologists (experts) contoured prostate tumors on 39 total patient cases using conventional MRI with or without RSIrs maps. Participant volumes were compared to the consensus expert volumes. Contouring accuracy metrics included percent overlap with expert volume, Dice coefficient, conformal number, and maximum distance beyond expert volume. RESULTS: 1604 participant volumes were produced. 40 of 44 participants (91%) completely missed ≥1 expert-defined target lesion without RSIrs, compared to 13 of 44 (30%) with RSIrs maps. On conventional MRI alone, 134 of 762 contour attempts (18%) completely missed the target, compared to 18 of 842 (2%) with RSIrs maps. Use of RSIrs maps improved all contour accuracy metrics by approximately 50% or more. Mixed effects modeling confirmed that RSIrs maps were the main variable driving improvement in all metrics. System Usability Scores indicated RSIrs maps significantly improved the contouring experience (72 vs. 58, pâ¯<â¯0.001). CONCLUSIONS: Radiation oncologists struggle with accurately delineating visible PCa tumors on conventional MRI. RSIrs maps improve radiation oncologists' ability to target MRI-visible tumors for prostate tumor boost.
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Neoplasias de la Próstata , Planificación de la Radioterapia Asistida por Computador , Masculino , Humanos , Estudios Prospectivos , Planificación de la Radioterapia Asistida por Computador/métodos , Oncólogos de Radiación , Imagen por Resonancia Magnética/métodos , Neoplasias de la Próstata/diagnóstico por imagen , Neoplasias de la Próstata/radioterapia , Neoplasias de la Próstata/patologíaRESUMEN
In laboratory experiments, biomechanical data collections with wearable technologies and machine learning have been promising. Despite the development of lightweight portable sensors and algorithms for the identification of gait events and estimation of kinetic waveforms, machine learning models have yet to be used to full potential. We propose the use of a Long Short Term Memory network to map inertial data to ground reaction force data gathered in a semi-uncontrolled environment. Fifteen healthy runners were recruited for this study, with varied running experience: novice to highly trained runners (<15â min 5â km race), and ages ranging from 18 to 64 years old. Force sensing insoles were used to measure normal foot-shoe forces, providing the standard for identification of gait events and measurement of kinetic waveforms. Three inertial measurement units (IMUs) were mounted to each participant, two bilaterally on the dorsal aspect of the foot and one clipped to the back of each participant's waistband, approximating their sacrum. Data input into the Long Short Term Memory network were from the three IMUs and output were estimated kinetic waveforms, compared against the standard of the force sensing insoles. The range of RMSE for each stance phase was from 0.189-0.288â BW, which is similar to multiple previous studies. Estimation of foot contact had an r 2 = 0.795. Estimation of kinetic variables varied, with peak force presenting the best output with an r 2 = 0.614. In conclusion, we have shown that at controlled paces over level ground a Long Short Term Memory network can estimate 4â s temporal windows of ground reaction force data across a range of running speeds.
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Demonstration of a very dense or hyper-attenuated liver on the pre-contrast CT images of the abdomen can be an unexpected finding. It may present as a diagnostic challenge if the underlying cause of it is not apparent from the provided clinical history. There are about 12 different pathologic conditions that are associated with deposition of radiopaque elements within the hepatic parenchyma, resulting in diffuse or multi-lobar hyperdense appearance of the liver on abdominal radiographs and CT. Most of them are drug-induced or iatrogenic in nature, while others are the sequelae of genetic disorders like thalassemia, Wilson's disease, and primary hemochromatosis. This pictorial essay will present the CT appearance and etiology of hyper-attenuated liver in various clinical entities.
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Cavidad Abdominal , Degeneración Hepatolenticular , Humanos , Hígado/diagnóstico por imagen , Hígado/patología , Degeneración Hepatolenticular/diagnóstico por imagen , Degeneración Hepatolenticular/complicaciones , Abdomen , Tomografía Computarizada por Rayos XRESUMEN
Wearable sensors and machine learning algorithms are becoming a viable alternative for biomechanical analysis outside of the laboratory. The purpose of this work was to estimate gait events from inertial measurement units (IMUs) and utilize machine learning for the estimation of ground reaction force (GRF) waveforms. Sixteen healthy runners were recruited for this study, with varied running experience. Force sensing insoles were used to measure normal foot-shoe forces, providing a proxy for vertical GRF and a standard for the identification of gait events. Three IMUs were mounted on each participant, two bilaterally on the dorsal aspect of each foot and one clipped to the back of each participant's waistband, approximating their sacrum. Participants also wore a GPS watch to record elevation and velocity. A Bidirectional Long Short Term Memory Network (BD-LSTM) was used to estimate GRF waveforms from inertial waveforms. Gait event estimation from both IMU data and machine learning algorithms led to accurate estimations of contact time. The GRF magnitudes were generally underestimated by the machine learning algorithm when presented with data from a novel participant, especially at faster running speeds. This work demonstrated that estimation of GRF waveforms is feasible across a range of running velocities and at different grades in an uncontrolled environment.
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Carrera , Dispositivos Electrónicos Vestibles , Humanos , Caminata , Fenómenos Biomecánicos , Marcha , Aprendizaje AutomáticoRESUMEN
Background: Multiparametric magnetic resonance imaging (mpMRI) improves detection of clinically significant prostate cancer (csPCa), but the subjective Prostate Imaging Reporting and Data System (PI-RADS) system and quantitative apparent diffusion coefficient (ADC) are inconsistent. Restriction spectrum imaging (RSI) is an advanced diffusion-weighted MRI technique that yields a quantitative imaging biomarker for csPCa called the RSI restriction score (RSIrs). Objective: To evaluate RSIrs for automated patient-level detection of csPCa. Design setting and participants: We retrospectively studied all patients (n = 151) who underwent 3 T mpMRI and RSI (a 2-min sequence on a clinical scanner) for suspected prostate cancer at University of California San Diego during 2017-2019 and had prostate biopsy within 180 d of MRI. Intervention: We calculated the maximum RSIrs and minimum ADC within the prostate, and obtained PI-RADS v2.1 from medical records. Outcome measurements and statistical analysis: We compared the performance of RSIrs, ADC, and PI-RADS for the detection of csPCa (grade group ≥2) on the best available histopathology (biopsy or prostatectomy) using the area under the curve (AUC) with two-tailed α = 0.05. We also explored whether the combination of PI-RADS and RSIrs might be superior to PI-RADS alone and performed subset analyses within the peripheral and transition zones. Results and limitations: AUC values for ADC, RSIrs, and PI-RADS were 0.48 (95% confidence interval: 0.39, 0.58), 0.78 (0.70, 0.85), and 0.77 (0.70, 0.84), respectively. RSIrs and PI-RADS were each superior to ADC for patient-level detection of csPCa (p < 0.0001). RSIrs alone was comparable with PI-RADS (p = 0.8). The combination of PI-RADS and RSIrs had an AUC of 0.85 (0.78, 0.91) and was superior to either PI-RADS or RSIrs alone (p < 0.05). Similar patterns were seen in the peripheral and transition zones. Conclusions: RSIrs is a promising quantitative marker for patient-level csPCa detection, warranting a prospective study. Patient summary: We evaluated a rapid, advanced prostate magnetic resonance imaging technique called restriction spectrum imaging to see whether it could give an automated score that predicted the presence of clinically significant prostate cancer. The automated score worked about as well as expert radiologists' interpretation. The combination of the radiologists' scores and automated score might be better than either alone.
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Purpose To develop a multicompartmental signal model for whole-body diffusion-weighted imaging (DWI) and apply it to study the diffusion properties of normal tissue and metastatic prostate cancer bone lesions in vivo. Materials and Methods This prospective study (ClinicalTrials.gov: NCT03440554) included 139 men with prostate cancer (mean age, 70 years ± 9 [SD]). Multicompartmental models with two to four tissue compartments were fit to DWI data from whole-body scans to determine optimal compartmental diffusion coefficients. Bayesian information criterion (BIC) and model-fitting residuals were calculated to quantify model complexity and goodness of fit. Diffusion coefficients for the optimal model (having lowest BIC) were used to compute compartmental signal-contribution maps. The signal intensity ratio (SIR) of bone lesions to normal-appearing bone was measured on these signal-contribution maps and on conventional DWI scans and compared using paired t tests (α = .05). Two-sample t tests (α = .05) were used to compare compartmental signal fractions between lesions and normal-appearing bone. Results Lowest BIC was observed from the four-compartment model, with optimal compartmental diffusion coefficients of 0, 1.1 × 10-3, 2.8 × 10-3, and >3.0 ×10-2 mm2/sec. Fitting residuals from this model were significantly lower than from conventional apparent diffusion coefficient mapping (P < .001). Bone lesion SIR was significantly higher on signal-contribution maps of model compartments 1 and 2 than on conventional DWI scans (P < .008). The fraction of signal from compartments 2, 3, and 4 was also significantly different between metastatic bone lesions and normal-appearing bone tissue (P ≤ .02). Conclusion The four-compartment model best described whole-body diffusion properties. Compartmental signal contributions from this model can be used to examine prostate cancer bone involvement. Keywords: Whole-Body MRI, Diffusion-weighted Imaging, Restriction Spectrum Imaging, Diffusion Signal Model, Bone Metastases, Prostate Cancer Clinical trial registration no. NCT03440554 Supplemental material is available for this article. © RSNA, 2023 See also commentary by Margolis in this issue.
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Neoplasias Óseas , Neoplasias de la Próstata , Masculino , Humanos , Anciano , Estudios Prospectivos , Teorema de Bayes , Imagen de Difusión por Resonancia Magnética/métodos , Imagen por Resonancia Magnética/métodos , Neoplasias de la Próstata/diagnóstico por imagen , Neoplasias de la Próstata/patología , Neoplasias Óseas/diagnóstico por imagen , Neoplasias Óseas/secundarioRESUMEN
Zero-velocity assumption has been used for estimation of foot trajectory and stride length during running from the data of foot-mounted inertial measurement units (IMUs). Although the assumption provides a reasonable initialization for foot trajectory and stride length estimation, the other source of errors related to the IMU's orientation still remains. The purpose of this study was to develop an improved foot trajectory and stride length estimation method for the level ground running based on the displacement of the foot. Seventy-nine runners performed running trials at 5 different paces and their running motions were captured using a motion capture system. The accelerations and angular velocities of left and right feet were measured with two IMUs mounted on the dorsum of each foot. In this study, foot trajectory and stride length were estimated using zero-velocity assumption with IMU data, and the orientation of IMU was estimated to calculate the mediolateral and vertical distance of the foot between two consecutive midstance events. Calculated foot trajectory and stride length were compared with motion capture data. The results show that the method used in this study can provide accurate estimation of foot trajectory and stride length for level ground running across a range of running speeds.
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Pie , Carrera , Aceleración , Fenómenos Biomecánicos , Marcha , Movimiento (Física) , Reflejo de Sobresalto , Trastornos Somatomorfos , TorsoRESUMEN
Introduction: Loading of a residual limb within a prosthetic socket can cause tissue damage such as ulceration. Computational simulations may be useful tools for estimating tissue loading within the socket, and thus provide insights into how prosthesis designs affect residual limb-socket interface dynamics. The purpose of this study was to model and simulate residual limb-socket interface dynamics and evaluate the effects of varied prosthesis stiffness on interface dynamics during gait. Methods: A spatial contact model of a residual limb-socket interface was developed and integrated into a gait model with a below-knee amputation. Gait trials were simulated for four subjects walking with low, medium, and high prosthesis stiffness settings. The effects of prosthesis stiffness on interface kinematics, normal pressure, and shear stresses were evaluated. Results: Model-predicted values were similar to those reported previously in sensor-based experiments; increased stiffness resulted in greater average normal pressure and shear stress (p < 0.05). Conclusions: These methods may be useful to aid experimental studies by providing insights into the effects of varied prosthesis design parameters or gait conditions on residual limb-socket interface dynamics. The current results suggest that these effects may be subject-specific.
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Diffusion-weighted MRI (DW-MRI) offers a potential adjunct to dynamic contrast-enhanced MRI to discriminate benign from malignant breast lesions by yielding quantitative information about tissue microstructure. Multi-component modeling of the DW-MRI signal over an extended b-value range (up to 3000 s/mm2) theoretically isolates the slowly diffusing (restricted) water component in tissues. Previously, a three-component restriction spectrum imaging (RSI) model demonstrated the ability to distinguish malignant lesions from healthy breast tissue. We further evaluated the utility of this three-component model to differentiate malignant from benign lesions and healthy tissue in 12 patients with known malignancy and synchronous pathology-proven benign lesions. The signal contributions from three distinct diffusion compartments were measured to generate parametric maps corresponding to diffusivity on a voxel-wise basis. The three-component model discriminated malignant from benign and healthy tissue, particularly using the restricted diffusion C1 compartment and product of the restricted and intermediate diffusion compartments (C1 and C2). However, benign lesions and healthy tissue did not significantly differ in diffusion characteristics. Quantitative discrimination of these three tissue types (malignant, benign, and healthy) in non-pre-defined lesions may enhance the clinical utility of DW-MRI in reducing excessive biopsies and aiding in surveillance and surgical evaluation without repeated exposure to gadolinium contrast.
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The development of lightweight portable sensors and algorithms for the identification of gait events at steady-state running speeds can be translated into the real-world environment. However, the output of these algorithms needs to be validated. The purpose of this study was to validate the identification of running gait events using data from Inertial Measurement Units (IMUs) in a semi-uncontrolled environment. Fifteen healthy runners were recruited for this study, with varied running experience and age. Force-sensing insoles measured normal foot-shoe forces and provided a standard for identification of gait events. Three IMUs were mounted to the participant, two bilaterally on the dorsal aspect of the foot and one clipped to the back of each participant's waistband, approximating their sacrum. The identification of gait events from the foot-mounted IMU was more accurate than from the sacral-mounted IMU. At running speeds <3.57 m s−1, the sacral-mounted IMU identified contact duration as well as the foot-mounted IMU. However, at speeds >3.57 m s−1, the sacral-mounted IMU overestimated foot contact duration. This study demonstrates that at controlled paces over level ground, we can identify gait events and measure contact time across a range of running skill levels.
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Carrera , Algoritmos , Fenómenos Biomecánicos , Pie , Marcha , HumanosRESUMEN
Diffusion-weighted magnetic resonance imaging (DWI) of the musculoskeletal system has various applications, including visualization of bone tumors. However, DWI acquired with echo-planar imaging is susceptible to distortions due to static magnetic field inhomogeneities. This study aimed to estimate spatial displacements of bone and to examine whether distortion corrected DWI images more accurately reflect underlying anatomy. Whole-body MRI data from 127 prostate cancer patients were analyzed. The reverse polarity gradient (RPG) technique was applied to DWI data to estimate voxel-level distortions and to produce a distortion corrected DWI dataset. First, an anatomic landmark analysis was conducted, in which corresponding vertebral landmarks on DWI and anatomic T2-weighted images were annotated. Changes in distance between DWI- and T2-defined landmarks (i.e., changes in error) after distortion correction were calculated. In secondary analyses, distortion estimates from RPG were used to assess spatial displacements of bone metastases. Lastly, changes in mutual information between DWI and T2-weighted images of bone metastases after distortion correction were calculated. Distortion correction reduced anatomic error of vertebral DWI up to 29 mm. Error reductions were consistent across subjects (Wilcoxon signed-rank p < 10-20). On average (± SD), participants' largest error reduction was 11.8 mm (± 3.6). Mean (95% CI) displacement of bone lesions was 6.0 mm (95% CI 5.0-7.2); maximum displacement was 17.1 mm. Corrected diffusion images were more similar to structural MRI, as evidenced by consistent increases in mutual information (Wilcoxon signed-rank p < 10-12). These findings support the use of distortion correction techniques to improve localization of bone on DWI.
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Neoplasias Óseas/diagnóstico por imagen , Imagen de Difusión por Resonancia Magnética , Neoplasias de la Próstata/patología , Imagen de Cuerpo Entero , Artefactos , Neoplasias Óseas/secundario , Humanos , Interpretación de Imagen Asistida por Computador , Masculino , Valor Predictivo de las Pruebas , Estudios Prospectivos , Reproducibilidad de los ResultadosRESUMEN
To report the radiological features of intestinal ascariasis and to review the clinical implications of this re-emerging disease for adult population of the USA. This retrospective observational study involved 12 adult patients, whose radiological examinations disclosed unsuspected presence of ascaris in their intestinal tract. They were evaluated by computed tomography of the abdomen with oral contrast, small bowel series with barium, and magnetic resonance enterography. This series included 7 men and 5 women, who ranged in age from 19 to 72 years (mean age 48 years). The typical configuration of ascaris within the bowel loops was demonstrated on CT of the abdomen in 5 patients, small bowel examination with barium in 3, and by MR enterography in another 4 cases. Our study highlights the radiological appearances of intestinal ascariasis and the clinical implications of this resurging disease. The practicing radiologists should be aware of these findings, particularly when examining patients who have immigrated from or traveled to the endemic regions.
Asunto(s)
Ascariasis , Adulto , Anciano , Ascariasis/diagnóstico por imagen , Femenino , Humanos , Intestino Delgado/diagnóstico por imagen , Intestinos , Imagen por Resonancia Magnética/métodos , Masculino , Persona de Mediana Edad , Estudios Observacionales como Asunto , Tomografía Computarizada por Rayos X/métodos , Adulto JovenRESUMEN
The purpose of this study was to compare a heuristic feature identification algorithm with output from the Beta Process Auto Regressive Hidden Markov Model (BP-AR-HMM) utilizing minimally sampled (≤ 100 Hz) human locomotion data for identification of gait events prior to their occurrence. Data were collected from 16 participants (21-64 years) using a single gyroscopic sensor in an inertial measurement unit on the dorsum of the foot, across multiple locomotion modes, including level ground walking and running (across speeds 0.8 m s-1 - 3.0 m s-1), ramps and stairs. Identification of gait events, initial contact (IC) and toe off (TO) with the heuristic algorithm, was 94% across locomotion modes. The features identified prior to initial contact had a lead time of 186.32 ± 86.70 ms, while TO had a lead time of 63.96 ± 46.30 ms. The BP-AR-HMM identified features that indicated an impending IC and TO with 99% accuracy, with a lead time of 59.41 ± 54.41 ms for IC and 90.79 ± 35.51 ms for TO. These approaches are consistent in their identification of gait events and have the potential to be utilized for classification and prediction of locomotion mode.