A Method to Track 3D Knee Kinematics by Multi-Channel 3D-Tracked A-Mode Ultrasound.

This paper introduces a method for measuring 3D tibiofemoral kinematics using a multi-channel A-mode ultrasound system under dynamic conditions. The proposed system consists of a multi-channel A-mode ultrasound system integrated with a conventional motion capture system (i.e., optical tracking system). This approach allows for the non-invasive and non-radiative quantification of the tibiofemoral joint's six degrees of freedom (DOF). We demonstrated the feasibility and accuracy of this method in the cadaveric experiment. The knee joint's motions were mimicked by manually manipulating the leg through multiple motion cycles from flexion to extension. To measure it, six custom ultrasound holders, equipped with a total of 30 A-mode ultrasound transducers and 18 optical markers, were mounted on various anatomical regions of the lower extremity of the specimen. During experiments, 3D-tracked intra-cortical bone pins were inserted into the femur and tibia to measure the ground truth of tibiofemoral kinematics. The results were compared with the tibiofemoral kinematics derived from the proposed ultrasound system. The results showed an average rotational error of 1.51 ± 1.13° and a translational error of 3.14 ± 1.72 mm for the ultrasound-derived kinematics, compared to the ground truth. In conclusion, this multi-channel A-mode ultrasound system demonstrated a great potential of effectively measuring tibiofemoral kinematics during dynamic motions. Its improved accuracy, nature of non-invasiveness, and lack of radiation exposure make this method a promising alternative to incorporate into gait analysis and prosthetic kinematic measurements later.

Knee Bone and Cartilage Segmentation Based on a 3D Deep Neural Network Using Adversarial Loss for Prior Shape Constraint.

Fast and accurate segmentation of knee bone and cartilage on MRI images is becoming increasingly important in the orthopaedic area, as the segmentation is an essential prerequisite step to a patient-specific diagnosis, optimising implant design and preoperative and intraoperative planning. However, manual segmentation is time-intensive and subjected to inter- and intra-observer variations. Hence, in this study, a three-dimensional (3D) deep neural network using adversarial loss was proposed to automatically segment the knee bone in a resampled image volume in order to enlarge the contextual information and incorporate prior shape constraints. A restoration network was proposed to further improve the bone segmentation accuracy by restoring the bone segmentation back to the original resolution. A conventional U-Net-like network was used to segment the cartilage. The ultimate results were the combination of the bone and cartilage outcomes through post-processing. The quality of the proposed method was thoroughly assessed using various measures for the dataset from the Grand Challenge Segmentation of Knee Images 2010 (SKI10), together with a comparison with a baseline network U-Net. A fine-tuned U-Net-like network can achieve state-of-the-art results without any post-processing operations. This method achieved a total score higher than 76 in terms of the SKI10 validation dataset. This method showed to be robust to extract bone and cartilage masks from the MRI dataset, even for the pathological case.

A robust and semi-automatic quantitative measurement of patellofemoral instability based on four dimensional computed tomography.

Patellofemoral instability is a motion related disease, featured as the patella dislocating from the trochlear groove. Four dimensional computed tomography (4DCT) enables full assessment of the patellofemoral movement. Nevertheless, the quantitative measurements of patellofemoral instability are still under research and currently of limited practical use. The aim of this study is to develop a robust and semi-automatic workflow to quantitatively describe the patellofemoral movement in a patient group of eight suffering from patellofemoral instability. The initial results show agreement with manual observations of the tibial tubercle - trochlear groove (TT-TG) distance in routine practice, and the possibility to evaluate both TT-TG distance and patellar centre - trochlear groove (PC-TG) distance dynamically during active flexion-extension-flexion movement of the knee.

Assessment of fasted and fed gastrointestinal contraction frequencies in healthy subjects using continuously tagged MRI.

BACKGROUND: Continuously tagged MRI during free breathing can assess bowel motility at frequencies as low as the slow wave, motility pattern range. This study aimed to evaluate noninvasive gastrointestinal-tagged MRI for small bowel motility assessment and to observe the physiological response to a 300-kcal meal challenge in healthy, overnight-fasted volunteers. METHODS: After overnight fasting, 16 healthy subjects (7 women, mean age 25.5, range 19-37 years) underwent a free breathing, tagged MRI scan to capture small bowel motility. Each subject underwent a (a) baseline motility scan, (b) food challenge, (c) postchallenge scan, and (d) second postchallenge scan (after 20 minutes). Motility was quantified using a frequency analysis technique for measuring the spectral power of the strain, referred to as motility score. Motility score was assessed in 20 frequency intervals between 1 and 20 contractions per minute (cpm), and the data were analyzed with linear mixed-effect models. KEY RESULT: The stimulation protocol demonstrated an immediate, food-induced, motility response in the low-frequency range (2-10 cpm), which is consistent with the stomach and small bowel frequency range (3-12 cpm). CONCLUSIONS AND INFERENCES: This study shows that this MRI tagging technique is able to quantify the fasted-to-fed response to a 300-kcal meal challenge within the specific small bowel motility frequency range in healthy subjects. The food provocation MRI protocol provides a tool to explore the gut's response to a stimulus in specific motility frequency ranges in patients with gastrointestinal dysmotility and functional disorders.

A noninvasive MRI based approach to estimate the mechanical properties of human knee ligaments.

Characterization of the main tibiofemoral ligaments is an essential step in developing patient-specific computational models of the knee joint for personalized surgery pre-planning. Tensile tests are commonly performed in-vitro to characterize the mechanical stiffness and rupture force of the knee ligaments which makes the technique unsuitable for in-vivo application. The time required for the limited noninvasive approaches for properties estimation based on knee laxity remained the main obstacle in clinical implementation. Magnetic resonance imaging (MRI) technique can be a platform to noninvasively assess the knee ligaments. In this study the aim was to explore the potential role of quantitative MRI and dimensional properties, in characterizing the mechanical properties of the main tibiofemoral ligaments. After MR scanning of six cadaveric legs, all 24 main tibiofemoral bone-ligaments-bone specimens were tested in vitro. During the tensile test cross sectional area of the specimens was captured using ultrasound and force-displacement curve was extracted. Digital image correlation technique was implemented to check the strain behavior of the specimen and rupture region and to assure the fixation of ligament bony block during the test. The volume of the specimen was measured using manual segmentation data, and quantitative MR parameters as T2*, T1ρ, and T2 were calculated. Linear mixed statistical models for repeated measures were used to examine the association of MRI parameters and dimensional measurements with the mechanical properties (stiffness and rupture force). The results shows that while the mechanical properties were mostly correlated to the volume, inclusion of the MR parameters increased the correlation strength for stiffness (R2 ≈ 0.48) and partial rupture force (R2 = 0.53). Inclusion of ligament type in the statistical analysis enhanced the correlation of mechanical properties with MR parameters and volume as for stiffness (R2 = 0.60) and partial rupture (R2 = 0.57). In conclusion, this study revealed the potentials in using quantitative MR parameters, T1ρ, T2 and T2*, combined with specimen volume to estimate the essential mechanical properties of all main tibiofemoral ligaments required for subject-specific computational modeling of human knee joint.

Automated segmentation of trabecular and cortical bone from proton density weighted MRI of the knee.

Patient-specific implant design and pre- and intra-operative planning is becoming increasingly important in the orthopaedic field. For clinical feasibility of these techniques, fast and accurate segmentation of bone structures from MRI is essential. However, manual segmentation is time intensive and subject to inter- and intra-observer variation. The challenge in developing automatic segmentation algorithms for MRI data mainly exists in the inhomogeneity problem and the low contrast among cortical bone and adjacent tissues. In this paper, we proposed a method for automatic segmentation of knee bone structures for MRI data with a 3D local intensity clustering-based level set and a novel approach to determine the cortical boundary utilizing the normal vector of the trabecular surface. Application to clinical imaging data shows that our method is robust to MRI inhomogeneity. In comparing our method to manual segmentation in 18 femurs and tibiae, we found a dice similarity coefficient (DSC) of 0.9611 ± 0.0052 for the femurs and 0.9591 ± 0.0173 for tibiae. The average surface distance error was 0.4649 ± 0.1430 mm for the femurs and 0.4712 ± 0.2113 mm for the tibiae. The results of the automatic technique thus strongly corresponded to the manual segmentation using less than 3% of the time and with virtually no workload. Graphical abstract ᅟ.

Computer-aided detection of fasciculations and other movements in muscle with ultrasound: Development and clinical application.

OBJECTIVE: To develop an automated algorithm for detecting fasciculations and other movements in muscle ultrasound videos. Fasciculation detection in muscle ultrasound is routinely performed online by observing the live videos. However, human observation limits the objective information gained. Automated detection of movement is expected to improved sensitivity and specificity and increase reliability. METHODS: We used 42 ultrasound videos from 11 neuromuscular patients for an iterative learning process between human observers and automated computer analysis, to identify muscle ultrasound movements. Two different datasets were selected from this, one to develop the algorithm and one to validate it. The outcome was compared to manual movement identification by clinicians. The algorithm also quantifies specific parameters of different movement types, to enable automated differentiation of events. RESULTS: The algorithm reliably detected fasciculations. With algorithm guidance, observers found more fasciculations compared to visual analysis alone, and prescreening the videos with the algorithm saved clinicians significant time compared to reviewing full video sequences. All videos also contained other movements, especially contraction pseudotremor, which confused human interpretation in some. CONCLUSIONS: Automated movement detection is a feasible and attractive method to screen for fasciculations in muscle ultrasound videos. SIGNIFICANCE: Our findings affirm the potential clinical usefulness of automated movement analysis in muscle ultrasound.

A Novel Ultrasound-Based Lower Extremity Motion Tracking System.

Tracking joint motion of the lower extremity is important for human motion analysis. In this study, we present a novel ultrasound-based motion tracking system for measuring three-dimensional (3D) position and orientation of the femur and tibia in 3D space and quantifying tibiofemoral kinematics under dynamic conditions. As ultrasound is capable of detecting underlying bone surface noninvasively through multiple layers of soft tissues, an integration of multiple A-mode ultrasound transducers with a conventional motion tracking system provides a new approach to track the motion of bone segments during dynamic conditions. To demonstrate the technical and clinical feasibilities of this concept, an in vivo experiment was conducted. For this purpose the kinematics of healthy individuals were determined in treadmill walking conditions and stair descending tasks. The results clearly demonstrated the potential of tracking skeletal motion of the lower extremity and measuring six-degrees-of-freedom (6-DOF) tibiofemoral kinematics and related kinematic alterations caused by a variety of gait parameters. It was concluded that this prototyping system has great potential to measure human kinematics in an ambulant, non-radiative, and noninvasive manner.

Feasibility of A-mode ultrasound based intraoperative registration in computer-aided orthopedic surgery: A simulation and experimental study.

PURPOSE: A fast and accurate intraoperative registration method is important for Computer-Aided Orthopedic Surgery (CAOS). A-mode ultrasound (US) is able to acquire bone surface data in a non-invasive manner. To utilize A-mode US in CAOS, a suitable registration algorithm is necessary with a small number of registration points and the presence of measurement errors. Therefore, we investigated the effects of (1) the number of registration points and (2) the Ultrasound Point Localization Error (UPLE) on the overall registration accuracy. METHODS: We proposed a new registration method (ICP-PS), including the Iterative Closest Points (ICP) algorithm and a Perturbation Search algorithm. This method enables to avoid getting stuck in the local minimum of ICP iterations and to find the adjacent global minimum. This registration method was subsequently validated in a numerical simulation and a cadaveric experiment using a 3D-tracked A-mode US system. RESULTS: The results showed that ICP-PS outperformed the standard ICP algorithm. The registration accuracy improved with the addition of ultrasound registration points. In the numerical simulation, for 25 sample points with zero UPLE, the averaged registration error of ICP-PS reached 0.25 mm, while 1.71 mm for ICP, decreasing by 85.38%. In the cadaver experiment, using 25 registration points, ICP-PS achieved an RMSE of 2.81 mm relative to 5.84 mm for the ICP, decreasing by 51.88%. CONCLUSIONS: The simulation approach provided a well-defined framework for estimating the necessary number of ultrasound registration points and acceptable level of UPLE for a given required level of accuracy for intraoperative registration in CAOS. ICP-PS method is suitable for A-mode US based intraoperative registration. This study would facilitate the application of A-mode US probe in registering the point cloud to a known shape model, which also has the potential for accurately estimating bone position and orientation for skeletal motion tracking and surgical navigation.

Measuring relative positions and orientations of the tibia with respect to the femur using one-channel 3D-tracked A-mode ultrasound tracking system: A cadaveric study.

The purpose of this study is to investigate the technical feasibility of measuring relative positions and orientations of the tibia with respect to the femur in an in-vitro experiment by using a 3D-tracked A-mode ultrasound system and to determine its accuracy of angular and translational measurements. As A-mode ultrasound is capable of detecting bone surface through soft tissue in a non-invasive manner, the combination of a single A-mode ultrasound transducer with an optical motion tracking system provides the possibility for digitizing the 3D locations of bony points at different anatomical regions on the thigh and the shank. After measuring bony points over a large area of both the femur and tibia, the bone models of the femur and tibia that were segmented from CT or MRI images were registered to the corresponding bony points. Then the relative position of the tibia with respect to the femur could be obtained and the angular and translational components could also be measured. A cadaveric experiment was conducted to assess its accuracy compared to the reference measurement obtained by optical markers fixed to intra-cortical bone pins placed in the femur and tibia. The results showed that the ultrasound system could achieve 0.49 ±â€¯0.83°, 0.85 ±â€¯1.86° and 1.85 ±â€¯2.78° (mean ±â€¯standard deviation) errors for Flexion-Extension, Adduction-Abduction and External-Internal rotations, respectively, and -2.22 ±â€¯3.62 mm, -2.80 ±â€¯2.35 mm and -1.44 ±â€¯2.90 mm errors for Anterior-Posterior, Proximal-Distal and Lateral-Medial translations, respectively. It was concluded that this technique is feasible and facilitates the integration of arrays of A-mode ultrasound transducers with an optical motion tracking system for non-invasive dynamic tibiofemoral kinematics measurement.

Strain imaging of the lateral collateral ligament using high frequency and conventional ultrasound imaging: An ex-vivo comparison.

Recent first attempts of in situ ultrasound strain imaging in collateral ligaments encountered a number of challenges and illustrated a clear need for additional studies and more thorough validation of the available strain imaging methods. Therefore, in this study we experimentally validated ultrasound strain measurements of ex vivo human lateral collateral ligaments in an axial loading condition. Moreover, the use of high frequency ultrasound (>20 MHz) for strain measurement was explored and its performance compared to conventional ultrasound. The ligaments were stretched up to 5% strain and ultrasound measurements were compared to surface strain measurements from optical digital image correlation (DIC) techniques. The results show good correlations between ultrasound based and DIC based strain measures with R2 values of 0.71 and 0.93 for high frequency and conventional ultrasound, subsequently. The performance of conventional ultrasound was significantly higher compared to high frequency ultrasound strain imaging, as the high frequency based method seemed more prone to errors. This study demonstrates that ultrasound strain imaging is feasible in ex vivo lateral collateral ligaments, which are relatively small structures. Additional studies should be designed for a more informed assessment of optimal in vivo strain measurements in collateral knee ligaments.

Accelerated 4D phase contrast MRI in skeletal muscle contraction.

PURPOSE: 3D time-resolved (4D) phase contrast MRI can be used to study muscle contraction. However, 3D coverage with sufficient spatiotemporal resolution can only be achieved by interleaved acquisitions during many repetitions of the motion task, resulting in long scan times. The aim of this study was to develop a compressed sensing accelerated 4D phase contrast MRI technique for quantification of velocities and strain rate of the muscles in the lower leg during active plantarflexion/dorsiflexion. METHODS: Nine healthy volunteers were scanned during active dorsiflexion/plantarflexion task. For each volunteer, we acquired a reference scan, as well as 4 different accelerated scans (k-space undersampling factors: 3.14X, 4.09X, 4.89X, and 6.41X) obtained using Cartesian Poisson disk undersampling schemes. The data was reconstructed using a compressed sensing pipeline. For each scan, velocity and strain rate values were quantified in the gastrocnemius lateralis, gastrocnemius medialis, tibialis anterior, and soleus. RESULTS: No significant differences in velocity values were observed as a function acceleration factor in the investigated muscles. The strain rate calculation resulted in one positive (s+ ) and one negative (s- ) eigenvalue, whereas the third eigenvalue (s3 ) was consistently 0 for all the acquisitions. No significant differences were observed for the strain rate eigenvalues as a function of acceleration factor. CONCLUSIONS: Data undersampling combined with compressed sensing reconstruction allowed obtainment of time-resolved phase contrast acquisitions with 3D coverage and quantitative information comparable to the reference scan. The 3D sensitivity of the method can help in understanding the connection between muscle architecture and muscle function in future studies.

In situ comparison of A-mode ultrasound tracking system and skin-mounted markers for measuring kinematics of the lower extremity.

Skin-mounted marker based motion capture systems are widely used in measuring the movement of human joints. Kinematic measurements associated with skin-mounted markers are subject to soft tissue artifacts (STA), since the markers follow skin movement, thus generating errors when used to represent motions of underlying bone segments. We present a novel ultrasound tracking system that is capable of directly measuring tibial and femoral bone surfaces during dynamic motions, and subsequently measuring six-degree-of-freedom (6-DOF) tibiofemoral kinematics. The aim of this study is to quantitatively compare the accuracy of tibiofemoral kinematics estimated by the ultrasound tracking system and by a conventional skin-mounted marker based motion capture system in a cadaveric experimental scenario. Two typical tibiofemoral joint models (spherical and hinge models) were used to derive relevant kinematic outcomes. Intra-cortical bone pins equipped with optical markers were inserted in the tibial and femoral bones to serve as a reference to provide ground truth kinematics. The ultrasound tracking system resulted in lower kinematic errors than the skin-mounted markers (the ultrasound tracking system: maximum root-mean-square (RMS) error 3.44° for rotations and 4.88 mm for translations, skin-mounted markers with the spherical joint model: 6.32° and 6.26 mm, the hinge model: 6.38° and 6.52 mm). Our proposed ultrasound tracking system has the potential of measuring direct bone kinematics, thereby mitigating the influence and propagation of STA. Consequently, this technique could be considered as an alternative method for measuring 6-DOF tibiofemoral kinematics, which may be adopted in gait analysis and clinical practice.

Accelerated 4D self-gated MRI of tibiofemoral kinematics.

Anatomical (static) magnetic resonance imaging (MRI) is the most useful imaging technique for the evaluation and assessment of internal derangement of the knee, but does not provide dynamic information and does not allow the study of the interaction of the different tissues during motion. As knee pain is often only experienced during dynamic tasks, the ability to obtain four-dimensional (4D) images of the knee during motion could improve the diagnosis and provide a deeper understanding of the knee joint. In this work, we present a novel approach for dynamic, high-resolution, 4D imaging of the freely moving knee without the need for external triggering. The dominant knee of five healthy volunteers was scanned during a flexion/extension task. To evaluate the effects of non-uniform motion and poor coordination skills on the quality of the reconstructed images, we performed a comparison between fully free movement and movement instructed by a visual cue. The trigger signal for self-gating was extracted using principal component analysis (PCA), and the images were reconstructed using a parallel imaging and compressed sensing reconstruction pipeline. The reconstructed 4D movies were scored for image quality and used to derive bone kinematics through image registration. Using our method, we were able to obtain 4D high-resolution movies of the knee without the need for external triggering hardware. The movies obtained with and without instruction did not differ significantly in terms of image scoring and quantitative values for tibiofemoral kinematics. Our method showed to be robust for the extraction of the self-gating signal even for uninstructed motion. This can make the technique suitable for patients who, as a result of pain, may find it difficult to comply exactly with instructions. Furthermore, bone kinematics can be derived from accelerated MRI without the need for additional hardware for triggering.

Ultrasound Imaging of Muscle Contraction of the Tibialis Anterior in Patients with Facioscapulohumeral Dystrophy.

A need exists for biomarkers to diagnose, quantify and longitudinally follow facioscapulohumeral muscular dystrophy (FSHD) and many other neuromuscular disorders. Furthermore, the pathophysiological mechanisms leading to muscle weakness in most neuromuscular disorders are not completely understood. Dynamic ultrasound imaging (B-mode image sequences) in combination with speckle tracking is an easy, applicable and patient-friendly imaging tool to visualize and quantify muscle deformation. This dynamic information provides insight in the pathophysiological mechanisms and may help to distinguish the various stages of diseased muscle in FSHD. In this proof-of-principle study, we applied a speckle tracking technique to 2-D ultrasound image sequences to quantify the deformation of the tibialis anterior muscle in patients with FSHD and in healthy controls. The resulting deformation patterns were compared with muscle ultrasound echo intensity analysis (a measure of fat infiltration and dystrophy) and clinical outcome measures. Of the four FSHD patients, two patients had severe peroneal weakness and two patients had mild peroneal weakness on clinical examination. We found a markedly varied muscle deformation pattern between these groups: patients with severe peroneal weakness showed a different motion pattern of the tibialis anterior, with overall less displacement of the central tendon region, while healthy patients showed a non-uniform displacement pattern, with the central aponeurosis showing the largest displacement. Hence, dynamic muscle ultrasound of the tibialis anterior muscle in patients with FSHD revealed a distinctively different tissue deformation pattern among persons with and without tibialis anterior weakness. These findings could clarify the understanding of the pathophysiology of muscle weakness in FSHD patients. In addition, the change in muscle deformation shows good correlation with clinical measures and quantitative muscle ultrasound measurements. In conclusion, dynamic ultrasound in combination with speckle tracking allows the study of the effects of muscle pathology in relation to strength, force transmission and movement generation. Although further research is required, this technique can develop into a biomarker to quantify muscle disease severity.

Water and fat separation in real-time MRI of joint movement with phase-sensitive bSSFP.

PURPOSE: To introduce a method for obtaining fat-suppressed images in real-time MRI of moving joints at 3 Tesla (T) using a bSSFP sequence with phase detection to enhance visualization of soft tissue structures during motion. METHODS: The wrist and knee of nine volunteers were imaged with a real-time bSSFP sequence while performing dynamic tasks. For appropriate choice of sequence timing parameters, water and fat pixels showed an out-of-phase behavior, which was exploited to reconstruct water and fat images. Additionally, a 2-point Dixon sequence was used for dynamic imaging of the joints, and resulting water and fat images were compared with our proposed method. RESULTS: The joints could be visualized with good water-fat separation and signal-to-noise ratio (SNR), while maintaining a relatively high temporal resolution (5 fps in knee imaging and 10 fps in wrist imaging). The proposed method produced images of moving joints with higher SNR and higher image quality when compared with the Dixon method. CONCLUSIONS: Water-fat separation is feasible in real-time MRI of moving knee and wrist at 3 T. PS-bSSFP offers movies with higher SNR and higher diagnostic quality when compared with Dixon scans. Magn Reson Med 78:58-68, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

A novel diffusion-tensor MRI approach for skeletal muscle fascicle length measurements.

Musculoskeletal (dys-)function relies for a large part on muscle architecture which can be obtained using Diffusion-Tensor MRI (DT-MRI) and fiber tractography. However, reconstructed tracts often continue along the tendon or aponeurosis when using conventional methods, thus overestimating fascicle lengths. In this study, we propose a new method for semiautomatic segmentation of tendinous tissue using tract density (TD). We investigated the feasibility and repeatability of this method to quantify the mean fascicle length per muscle. Additionally, we examined whether the method facilitates measuring changes in fascicle length of lower leg muscles with different foot positions. Five healthy subjects underwent two DT-MRI scans of the right lower leg, with the foot in 15° dorsiflexion, neutral, and 30° plantarflexion positions. Repeatability of fascicle length measurements was assessed using Bland-Altman analysis. Changes in fascicle lengths between the foot positions were tested using a repeated multivariate analysis of variance (MANOVA). Bland-Altman analysis showed good agreement between repeated measurements. The coefficients of variation in neutral position were 8.3, 16.7, 11.2, and 10.4% for soleus (SOL), fibularis longus (FL), extensor digitorum longus (EDL), and tibialis anterior (TA), respectively. The plantarflexors (SOL and FL) showed significant increase in fascicle length from plantarflexion to dorsiflexion, whereas the dorsiflexors (EDL and TA) exhibited a significant decrease. The use of a tract density for semiautomatic segmentation of tendinous structures provides more accurate estimates of the mean fascicle length than traditional fiber tractography methods. The method shows moderate to good repeatability and allows for quantification of changes in fascicle lengths due to passive stretch.

Assessment of passive muscle elongation using Diffusion Tensor MRI: Correlation between fiber length and diffusion coefficients.

In this study we investigated the changes in fiber length and diffusion parameters as a consequence of passive lengthening and stretching of the calf muscles. We hypothesized that changes in radial diffusivity (RD) are caused by changes in the muscle fiber cross sectional area (CSA) as a consequence of lengthening and shortening of the muscle. Diffusion Tensor MRI (DT-MRI) measurements were made twice in five healthy volunteers, with the foot in three different positions (30° plantarflexion, neutral position and 15° dorsiflexion). The muscles of the calf were manually segmented on co-registered high resolution anatomical scans, and maps of RD and axial diffusivity (AD) were reconstructed from the DT-MRI data. Fiber tractography was performed and mean fiber length was calculated for each muscle group. Significant negative correlations were found between the changes in RD and changes in fiber length in the dorsiflexed and plantarflexed positions, compared with the neutral foot position. Changes in AD did not correlate with changes in fiber length. Assuming a simple cylindrical model with constant volume for the muscle fiber, the changes in the muscle fiber CSA were calculated from the changes in fiber length. In line with our hypothesis, we observed a significant positive correlation of the CSA with the measured changes in RD. In conclusion, we showed that changes in diffusion coefficients induced by passive muscle stretching and lengthening can be explained by changes in muscle CSA, advancing the physiological interpretation of parameters derived from skeletal muscle DT-MRI.

A comparison between dynamic implicit and explicit finite element simulations of the native knee joint.

The finite element (FE) method has been widely used to investigate knee biomechanics. Time integration algorithms for dynamic problems in finite element analysis can be classified as either implicit or explicit. Although previously both static/dynamic implicit and dynamic explicit method have been used, a comparative study on the outcomes of both methods is of high interest for the knee modeling community. The aim of this study is to compare static, dynamic implicit and dynamic explicit solutions in analyses of the knee joint to assess the prediction of dynamic effects, potential convergence problems, the accuracy and stability of the calculations, the difference in computational time, and the influence of mass-scaling in the explicit formulation. The heel-strike phase of fast, normal and slow gait was simulated for two different body masses in a model of the native knee. Our results indicate that ignoring the dynamic effect can alter joint motion. Explicit analyses are suitable to simulate dynamic loading of the knee joint in high-speed simulations, as this method offers a substantial reduction of the computational time with a similar prediction of cartilage stresses and meniscus strains. Although mass-scaling can provide even more gain in computational time, it is not recommended for high-speed activities, in which inertial forces play a significant role.

Noninvasive automated motion assessment of intestinal motility by continuously tagged MR imaging.

PURPOSE: To evaluate continuously tagged 3 Tesla MRI for monitoring glucagon-induced bowel motility changes in healthy volunteers. MATERIALS AND METHODS: After standardized oral bowel preparation, 10 healthy volunteers underwent a free-breathing, continuously tagged three-dimensional (3D) dynamic fast-field-echo (FFE), at a 3.36 Hz sampling frequency. One milligram of glucagon was administered intravenously during data acquisition. Each dataset was divided into four temporal sets of 2 min (period 1 to 4). Taglines were tracked automatically using a scale spaced based algorithm. Assessment of global spectral resolution was performed for three frequency intervals: 0.008-0.300 Hz (motility), 0.300-0.400 Hz (breathing motion), and 0.400-0.533 Hz (higher order motion). Additional analyses were performed at fine spectral resolution in frequency bands of 0.033 Hz. Glucagon-induced motility changes were investigated by means of a motility index (spectral power normalized to the maximal spectral power per-volunteer), resulting in a range of 0 to 1 (no motion to maximal motion). Statistical comparison was done for period 1 and 4 (Wilcoxon-signed rank test). RESULTS: After glucagon administration, a significant decrease in the motility index was found for the low- (0.008-0.300 Hz) (P < 0.0001) and high-frequency interval (0.400-0.533 Hz) (P < 0.0001). Around breathing motion frequencies, no decrease in motility index was detected. CONCLUSION: Free-breathing, continuously tagged MR imaging is a noninvasive method for automated bowel motility assessment and allows for detection of drug-induced changes.