Magnetic Resonance Imaging of the Ear for Patient-Specific Reconstructive Surgery

Introduction

Like a fingerprint, ear shape is a unique personal feature that should be reconstructed with a high fidelity during reconstructive surgery. Ear cartilage tissue engineering (TE) advantageously offers the possibility to use novel 3D manufacturing techniques to reconstruct the ear, thus allowing for a detailed auricular shape. However it also requires detailed patient-specific images of the 3D cartilage structures of the patient’s intact contralateral ear (if available). Therefore the aim of this study was to develop and evaluate an imaging strategy for acquiring patient-specific ear cartilage shape, with sufficient precision and accuracy for use in a clinical setting.

Methods and Materials

Magnetic resonance imaging (MRI) was performed on 14 volunteer and six cadaveric auricles and manually segmented. Reproducibility of cartilage volume (Cg.V), surface (Cg.S) and thickness (Cg.Th) was assessed, to determine whether raters could repeatedly define the same volume of interest. Additionally, six cadaveric auricles were harvested, scanned and segmented using the same procedure, then dissected and scanned using high resolution micro-CT. Correlation between MR and micro-CT measurements was assessed to determine accuracy.

Results

Good inter- and intra-rater reproducibility was observed (precision errors <4% for Cg.S and <9% for Cg.V and Cg.Th). Intraclass correlations were good for Cg.V and Cg.S (>0.82), but low for Cg.Th (<0.23) due to similar average Cg.Th between patients. However Pearson’s coefficients showed that the ability to detect local cartilage shape variations is unaffected. Good correlation between clinical MRI and micro-CT (r>0.95) demonstrated high accuracy.

Discussion and Conclusion

This study demonstrated that precision and accuracy of the proposed method was high enough to detect patient-specific variation in ear cartilage geometry. The present study provides a clinical strategy to access the necessary information required for the production of 3D ear scaffolds for TE purposes, including detailed patient-specific shape. Furthermore, the protocol is applicable in daily clinical practice with existing infrastructure.     

Automated CT bone segmentation using statistical shape modelling and local template matching

Abstract

Accurate CT bone segmentation is essential to develop chair-side manufacturing of implants based on additive manufacturing. We herewith present an automated method able to accurately segment challenging bone regions, while simultaneously providing anatomical correspondences. The method was evaluated on demanding regions: normal and osteoarthritic scapulae, healthy and atrophied mandibles, and orbital bones. On average, results were accurate with surface distances of approximately 0.5?mm and average Dice coefficients >90%. Since anatomical correspondences are propagated during the segmentation process, this approach can directly yield anatomical measurements, provide design parameters for personalized surgical instruments, or determine the bone geometry to manufacture patient-specific implants.     

Investigation of the XCAT phantom as a validation tool in cardiac MRI tracking algorithms

PurposeTo describe our magnetic resonance imaging (MRI) simulated implementation of the 4D digital extended cardio torso (XCAT) phantom to validate our previously developed cardiac tracking techniques. Real-time tracking will play an important role in the non-invasive treatment of atrial fibrillation with MRI-guided radiosurgery. In addition, to show how quantifiable measures of tracking accuracy and patient-specific physiology could influence MRI tracking algorithm design.MethodsTwenty virtual patients were subjected to simulated MRI scans that closely model the proposed real-world scenario to allow verification of the tracking technique’s algorithm. The generated phantoms provide ground-truth motions which were compared to the target motions output from our tracking algorithm. The patient-specific tracking error, e_p, was the 3D difference (vector length) between the ground-truth and algorithm trajectories. The tracking errors of two combinations of new tracking algorithm functions that were anticipated to improve tracking accuracy were studied. Additionally, the correlation of key physiological parameters with tracking accuracy was investigated.ResultsOur original cardiac tracking algorithm resulted in a mean tracking error of 3.7 ± 0.6 mm over all virtual patients. The two combinations of tracking functions demonstrated comparable mean tracking errors however indicating that the optimal tracking algorithm may be patient-specific.ConclusionsCurrent and future MRI tracking strategies are likely to benefit from this virtual validation method since no time-resolved 4D ground-truth signal can currently be derived from purely image-based studies.     

Development of an x-ray-opaque-marker system for quantitative phantom positioning in patient-specific quality assurance

PurposeWe developed an x-ray-opaque-marker (XOM) system with inserted fiducial markers for patient-specific quality assurance (QA) in CyberKnife (Accuray) and a general-purpose linear accelerator (linac). The XOM system can be easily inserted or removed from the existing patient-specific QA phantom. Our study aimed to assess the utility of the XOM system by evaluating the recognition accuracy of the phantom position error and estimating the dose perturbation around a marker.MethodsThe recognition accuracy of the phantom position error was evaluated by comparing the known error values of the phantom position with the values measured by matching the images with target locating system (TLS; Accuray) and on-board imager (OBI; Varian). The dose perturbation was evaluated for 6 and 10 MV single-photon beams through experimental measurements and Monte Carlo simulations.ResultsThe root mean squares (RMSs) of the residual position errors for the recognition accuracy evaluation in translations were 0.07 mm with TLS and 0.30 mm with OBI, and those in rotations were 0.13° with TLS and 0.15° with OBI. The dose perturbation was observed within 1.5 mm for 6 MV and 2.0 mm for 10 MV from the marker.ConclusionsSufficient recognition accuracy of the phantom position error was achieved using our system. It is unnecessary to consider the dose perturbation in actual patient-specific QA. We concluded that the XOM system can be utilized to ensure quantitative and accurate phantom positioning in patient-specific QA with CyberKnife and a general-purpose linac.     

Rotationally resliced 3D prostate segmentation of MR images using Bhattacharyya similarity and active band theory

PurposeIn this article, we propose a novel, semi-automatic segmentation method to process 3D MR images of the prostate using the Bhattacharyya coefficient and active band theory with the goal of providing technical support for computer-aided diagnosis and surgery of the prostate.MethodsOur method consecutively segments a stack of rotationally resectioned 2D slices of a prostate MR image by assessing the similarity of the shape and intensity distribution in neighboring slices. 2D segmentation is first performed on an initial slice by manually selecting several points on the prostate boundary, after which the segmentation results are propagated consecutively to neighboring slices. A framework of iterative graph cuts is used to optimize the energy function, which contains a global term for the Bhattacharyya coefficient with the help of an auxiliary function. Our method does not require previously segmented data for training or for building statistical models, and manual intervention can be applied flexibly and intuitively, indicating the potential utility of this method in the clinic.ResultsWe tested our method on 3D T2-weighted MR images from the ISBI dataset and PROMISE12 dataset of 129 patients, and the Dice similarity coefficients were 90.34 ± 2.21% and 89.32 ± 3.08%, respectively. The comparison was performed with several state-of-the-art methods, and the results demonstrate that the proposed method is robust and accurate, achieving similar or higher accuracy than other methods without requiring training.ConclusionThe proposed algorithm for segmenting 3D MR images of the prostate is accurate, robust, and readily applicable to a clinical environment for computer-aided surgery or diagnosis.     

Deformation and recovery of cartilage in the intact hip under physiological loads using 7 T MRI

Accurate measurement of cartilage deformation in loaded cadaver hip joints could be a valuable tool to answer clinically relevant research questions. MRI is a promising tool, but its use requires an understanding of cartilage deformation and recovery properties in the intact hip. Our objective was to answer the following questions: (1) How long does it take for hip cartilage to reach a deformed steady-state thickness distribution under simulated physiological load, and how much does the cartilage deform? (2) How long does it take for hip cartilage to return to the original cartilage thickness distribution once the load is removed?MethodsFive human hip specimens were axially loaded to 1980 N in a 7 T MR scanner and scanned every 15 min throughout loading. One specimen was scanned every hour throughout recovery from load. One repeatability specimen was loaded and scanned every day for 4 days. Hip cartilage was segmented as a single unit and thickness was measured radially.ResultsThe hip cartilage reached a steady-state thickness distribution after 225 min of load, and 16.5 h of recovery. Mean strain after 225 min of load was 30.9%. The repeatability specimen showed an average day-to-day change in mean cartilage thickness of 0.10 mm over 4 days of data collection. The amount of deformation (0.96 mm) was far greater than the image resolution (0.11 mm) and error due to repeatability (0.10 mm).ConclusionUsing an ex vivo model, this method has potential for assessing changes in hip cartilage strain due to injury or surgical intervention.     

Validation of frame-based positioning accuracy with cone-beam computed tomography in Gamma Knife Icon radiosurgery

BackgroundFrame based positioning accuracy in Gamma Knife (GK) stereotactic radiosurgery (SRS) is extremely high but removal of a post may be necessary to enable the treatment in selected patients.ObjectiveTo verify the positioning accuracy in clinical scenarios with 4 and 3 posts in patients and phantoms using cone-beam CT (CBCT) of Gamma Knife Icon™.MethodsWe analyzed positioning accuracy for 12 patients with standard 4 post setup using pretreatment CBCT (pre-CBCT) on GK Icon™ and report 4 patients with different clinical scenarios (removal of a post). We performed phantom measurements to verify the frame accuracy via CBCT in different clinical scenarios without the influence of the human patient.ResultsMean frame accuracy for 12 patients with 4 posts was 0.35 mm/0.34 degree. Mean motion during treatment was 0.11 mm/0.04 degree. For two of the clinical scenarios where a post was removed, we found acceptable deviations within 0.66 mm/0.61 degree. For 2 patients, a deviation of 2.94 mm/−3.47 degree and 1.85 mm/−0.74 degree was found and replanning was necessary. Phantom measurements showed good agreement when planning MR/CT was performed with 4 or 3 post. Larger deviations of 0.86 mm/0.88 degree were detected when a post was removed after planning MR/CT.ConclusionThe frame accuracy with 4 posts before and during GK treatments is as high as expected. For clinical situations, where a post is removed after planning-CT/MR, pre-treatment position verification is strongly suggested using stereotactic CBCT or the P-CT/MR should be repeated to avoid possible mistreatments.     

Optimizing MRI sequences and images for MRI-based stereotactic radiosurgery treatment planning

AimDevelopment of MRI sequences and processing methods for the production of images appropriate for direct use in stereotactic radiosurgery (SRS) treatment planning.BackgroundMRI is useful in SRS treatment planning, especially for patients with brain lesions or anatomical targets that are poorly distinguished by CT, but its use requires further refinement. This methodology seeks to optimize MRI sequences to generate distortion-free and clinically relevant MR images for MRI-only SRS treatment planning.Materials and methodsWe used commercially available SRS MRI-guided radiotherapy phantoms and eight patients to optimize sequences for patient imaging. Workflow involved the choice of correct MRI sequence(s), optimization of the sequence parameters, evaluation of image quality (artifact free and clinically relevant), measurement of geometrical distortion, and evaluation of the accuracy of our offline correction algorithm.ResultsCT images showed a maximum deviation of 1.3 mm and minimum deviation of 0.4 mm from true fiducial position for SRS coordinate definition. Interestingly, uncorrected MR images showed maximum deviation of 1.2 mm and minimum of 0.4 mm, comparable to CT images used for SRS coordinate definition. After geometrical correction, we observed a maximum deviation of 1.1 mm and minimum deviation of only 0.3 mm.ConclusionOur optimized MRI pulse sequences and image correction technique show promising results; MR images produced under these conditions are appropriate for direct use in SRS treatment planning.     

Estimation of accuracy of patient-specific musculoskeletal modelling: case study on a post polio residual paralysis subject

For patients with patterns ranging out of anthropometric standard values, patient-specific musculoskeletal modelling becomes crucial for clinical diagnosis and follow-up. However, patient-specific modelling using imaging techniques and motion capture systems is mainly subject to experimental errors. The aim of this study was to quantify these experimental errors when performing a patient-specific musculoskeletal model. CT scan data were used to personalise the geometrical model and its inertial properties for a post polio residual paralysis subject. After having performed a gait-based experimental protocol, kinematics data were measured using a VICON motion capture system with six infrared cameras. The musculoskeletal model was computed using a direct/inverse algorithm (LifeMod software). A first source of errors was identified in the segmentation procedure in relation to the calculation of personalised inertial parameters. The second source of errors was subject related, as it depended on the reproducibility of performing the same type of gait. The impact of kinematics, kinetics and muscle forces resulting from the musculoskeletal modelling was quantified using relative errors and the absolute root mean square error. Concerning the segmentation procedure, we found that the kinematics results were not sensitive to the errors (relative error < 1%). However, a strong influence was noted on the kinetics results (deviation up to 71%). Furthermore, the reproducibility error showed a significant influence (relative mean error varying from 5 to 30%). The present paper demonstrates that in patient-specific musculoskeletal modelling variations due to experimental errors derived from imaging techniques and motion capture need to be both identified and quantified. Therefore, the paper can be used as a guideline.     

Accuracy and Reproducibility of Adipose Tissue Measurements in Young Infants by Whole Body Magnetic Resonance Imaging

PurposeMR might be well suited to obtain reproducible and accurate measures of fat tissues in infants. This study evaluates MR-measurements of adipose tissue in young infants in vitro and in vivo.ResultsIn vitro accuracy errors depended on the chosen segmentation procedure, ranging from 5.4% to 76%, while the sequence showed no significant influence. Artificial breathing increased the minimal accuracy error to 9.1%. In vivo reproducibility errors for total fat volume of the sleeping infants ranged from 2.6% to 3.4%. Neither segmentation nor sequence significantly influenced reproducibility.ConclusionWith both cartesian and PROPELLER sequences an accurate and reproducible measure of body fat was achieved. Adequate segmentation was mandatory for high accuracy.     

MRI-guided voxel-based automatic semi-quantification of dopamine transporter imaging

PurposeFunctional imaging with ¹²³I-FP-CIT SPECT suffers from poor spatial resolution resulting in partial-volume effect, which affects the subsequent semi-quantification. Definition of regions of interest for semi-quantification is further subject to user's experience and inter-observer variability. The aim of this work has been to develop an automatic method for definition of volumes of interest and partial-volume correction using patient-specific MRI and providing complete contrast recovery in striatal region.MethodThe method consists of spatial pre-processing (image segmentation and multi-modality registration), partial-volume correction (performed by region-based voxel-wise technique), and calculation of uptake indices in striatal structures. Anthropomorphic striatal phantom was used to optimize the method and to assess linearity, accuracy, and reproducibility. The method was tested on 58 patient datasets and compared with clinical assessment and BasGan software.ResultsThe method works automatically. The output is highly linear regarding changing striatal uptake. Complete contrast recovery is achieved using 6.5 mm FWHM. Accuracy is better than 0.15 in terms of RMSE between measured and true uptake indices. Reproducibility is better than 5% for normal uptake ratio. The method outperformed clinical assessment in all measures. With patient data, it provided results closer to BasGan (RMSE 0.9) than to clinical assessment (RMSE 1.9) and fairly correlated with both.ConclusionThe proposed method provides complete recovery of striatal contrast under given acquisition and reconstruction conditions. It reduces intra- and inter-observer variability, accurately defines volumes of interest, and effectively suppresses partial-volume effect. It can be reproduced using publicly available software.     

Patient-specific guides improve hip arthroplasty surgical accuracy

Abstract

The role of patient-specific (PS) technology in total hip arthroplasty remains relatively unexplored. We asked whether PS guides: (1) Reduced average surgical errors? (2) Reduced outlier error frequencies? (3) Could predict the size of implants used? A single surgeon implanted femurs using either standard or PS guides and was blinded to the pre-operative plans. There were significant differences in median leg length errors between standard (3.3?mm) and PS groups (1.4?mm), U?=?110, z?=?–2.3, p?=?0.02. In contrast to the PS group, the standard group had significantly more outlier errors and frequently undersized implants. PS guides improve hip arthroplasty surgical accuracy.Abbreviations: PS: patient specific; THA: total hip arthroplasty; LLD: leg length discrepancies; HRA: hip resurfacing arthroplasty     

The effect of respiration-driven flow waveforms on hemodynamic metrics used in Fontan surgical planning

ObjectivePoor total cavopulmonary connection (TCPC) hemodynamics have been hypothesized to be associated with long-term complications in Fontan patients. Image-based Fontan surgical planning has shown great potential as a clinical tool because it can pre-operatively evaluate patient-specific hemodynamics. Current surgical planning paradigms commonly utilize cardiac-gated phase contrast magnetic resonance (MR) imaging to acquire vessel flows. These acquisitions are often taken under breath-held (BH) conditions and ignore the effect of respiration on blood flow waveforms. This study investigates the effect of respiration-driven flow waveforms on patient-specific hemodynamics using real-time MR acquisitions.MethodsPatient-specific TCPCs were reconstructed from cardiovascular MR images. Real-time phase contrast MR images were acquired under both free-breathing (FB) and breath-held conditions for 9 patients. Numerical simulations were employed to assess flow structures and hemodynamics used in Fontan surgical planning including hepatic flow distribution (HFD) and indexed power loss (iPL), which were then compared between FB and BH conditions.ResultsDifferences in TCPC flow structures between FB and BH conditions were observed throughout the respiratory cycle. However, the average differences (BH – FB values for each patient, which are then averaged) in iPL and HFD between these conditions were 0.002 ± 0.011 (p = 0.40) and 1 ± 3% (p = 0.28), respectively, indicating no significant difference in clinically important hemodynamic metrics.ConclusionsRespiration affects blood flow waveforms and flow structures, but might not significantly influence the values of iPL or HFD. Therefore, breath-held MR acquisition can be adequate for Fontan surgical planning when focusing on iPL and HFD.     

Statistical shape modeling predicts patellar bone geometry to enable stereo-radiographic kinematic tracking

Complications in the patellofemoral (PF) joint of patients with total knee replacements include patellar subluxation and dislocation, and remain a cause for revision. Kinematic measurements to assess these complications and evaluate implant designs require the accuracy of dynamic stereo-radiographic systems with 3D-2D registration techniques. While tibiofemoral kinematics are typically derived by tracking metallic implants, PF kinematic measurements are difficult as the patellar implant is radiotransparent and a representation of the resected patella bone requires either pre-surgical imaging and precise implant placement or post-surgical imaging. Statistical shape models (SSMs), used to characterize anatomic variation, provide an alternative means to obtain the representation of the resected patella for use in kinematic tracking. Using a virtual platform of a stereo-radiographic system, the objectives of this study were to evaluate the ability of an SSM to predict subject-specific 3D implanted patellar geometries from simulated 2D image profiles, and to formulate an effective data collection methodology for PF kinematics by considering accuracy for a variety of patient pose scenarios. An SSM of the patella was developed for 50 subjects and a leave-one-out approach compared SSM-predicted and actual geometries; average 3D errors were 0.45 ± 0.07 mm (mean ± standard deviation), which is comparable to the accuracy of traditional segmentation. Further, initial imaging of the patella in five unique stereo radiographic perspectives yielded the most accurate representation. The ability to predict the remaining patellar geometry of the implanted PF joint with radiographic images and SSM, instead of CT, can reduce radiation exposure and streamline in vivo kinematic evaluations.     

Estimation of accuracy of patient-specific musculoskeletal modelling: case study on a post polio residual paralysis subject

For patients with patterns ranging out of anthropometric standard values, patient-specific musculoskeletal modelling becomes crucial for clinical diagnosis and follow-up. However, patient-specific modelling using imaging techniques and motion capture systems is mainly subject to experimental errors. The aim of this study was to quantify these experimental errors when performing a patient-specific musculoskeletal model. CT scan data were used to personalise the geometrical model and its inertial properties for a post polio residual paralysis subject. After having performed a gait-based experimental protocol, kinematics data were measured using a VICON motion capture system with six infrared cameras. The musculoskeletal model was computed using a direct/inverse algorithm (LifeMod software). A first source of errors was identified in the segmentation procedure in relation to the calculation of personalised inertial parameters. The second source of errors was subject related, as it depended on the reproducibility of performing the same type of gait. The impact of kinematics, kinetics and muscle forces resulting from the musculoskeletal modelling was quantified using relative errors and the absolute root mean square error. Concerning the segmentation procedure, we found that the kinematics results were not sensitive to the errors (relative error<1%). However, a strong influence was noted on the kinetics results (deviation up to 71%). Furthermore, the reproducibility error showed a significant influence (relative mean error varying from 5 to 30%). The present paper demonstrates that in patient-specific musculoskeletal modelling variations due to experimental errors derived from imaging techniques and motion capture need to be both identified and quantified. Therefore, the paper can be used as a guideline.     

Fully automatic and robust segmentation of the clinical target volume for radiotherapy of breast cancer using big data and deep learning

PurposeTo train and evaluate a very deep dilated residual network (DD-ResNet) for fast and consistent auto-segmentation of the clinical target volume (CTV) for breast cancer (BC) radiotherapy with big data.MethodsDD-ResNet was an end-to-end model enabling fast training and testing. We used big data comprising 800 patients who underwent breast-conserving therapy for evaluation. The CTV were validated by experienced radiation oncologists. We performed a fivefold cross-validation to test the performance of the model. The segmentation accuracy was quantified by the Dice similarity coefficient (DSC) and the Hausdorff distance (HD). The performance of the proposed model was evaluated against two different deep learning models: deep dilated convolutional neural network (DDCNN) and deep deconvolutional neural network (DDNN).ResultsMean DSC values of DD-ResNet (0.91 and 0.91) were higher than the other two networks (DDCNN: 0.85 and 0.85; DDNN: 0.88 and 0.87) for both right-sided and left-sided BC. It also has smaller mean HD values of 10.5 mm and 10.7 mm compared with DDCNN (15.1 mm and 15.6 mm) and DDNN (13.5 mm and 14.1 mm). Mean segmentation time was 4 s, 21 s and 15 s per patient with DDCNN, DDNN and DD-ResNet, respectively. The DD-ResNet was also superior with regard to results in the literature.ConclusionsThe proposed method could segment the CTV accurately with acceptable time consumption. It was invariant to the body size and shape of patients and could improve the consistency of target delineation and streamline radiotherapy workflows.     

Automatic extraction and measurement of individual trees from mobile laser scanning point clouds of forests

Background and AimsIn addition to terrestrial laser scanning (TLS), mobile laser scanning (MLS) is increasingly arousing interest as a technique which provides valuable 3-D data for various applications in forest research. Using mobile platforms, the 3-D recording of large forest areas is carried out within a short space of time. Vegetation structure is described by millions of 3-D points which show an accuracy in the millimetre range and offer a powerful basis for automated vegetation modelling. The successful extraction of single trees from the point cloud is essential for further evaluations and modelling at the individual-tree level, such as volume determination, quantitative structure modelling or local neighbourhood analyses. However, high-precision automated tree segmentation is challenging, and has so far mostly been performed using elaborate interactive segmentation methods.MethodsHere, we present a novel segmentation algorithm to automatically segment trees in MLS point clouds, applying distance adaptivity as a function of trajectory. In addition, tree parameters are determined simultaneously. In our validation study, we used a total of 825 trees from ten sample plots to compare the data of trees segmented from MLS data with manual inventory parameters and parameters derived from semi-automatic TLS segmentation.Key ResultsThe tree detection rate reached 96 % on average for trees with distances up to 45 m from the trajectory. Trees were almost completely segmented up to a distance of about 30 m from the MLS trajectory. The accuracy of tree parameters was similar for MLS-segmented and TLS-segmented trees.ConclusionsBesides plot characteristics, the detection rate of trees in MLS data strongly depends on the distance to the travelled track. The algorithm presented here facilitates the acquisition of important tree parameters from MLS data, as an area-wide automated derivation can be accomplished in a very short time.     

Comparison of patient-specific intensity modulated radiation therapy quality assurance for the prostate across multiple institutions

AimTo evaluate the success of a patient-specific intensity modulated radiation therapy (IMRT) quality assurance (QA) practice for prostate cancer patients across multiple institutions using a questionnaire survey.BackgroundThe IMRT QA practice involves different methods of dose distribution verification and analysis at different institutions.Materials and MethodsTwo full-arc volumetric modulated arc therapy (VMAT) plan and 7 fixed-gantry IMRT plan with DMLC were used for patient specific QA across 22 institutions. The same computed tomography image and structure set were used for all plans. Each institution recalculated the dose distribution with fixed monitor units and without any modification. Single-point dose measurement with a cylindrical ionization chamber and dose distribution verification with a multi-detector or radiochromic film were performed, according to the QA process at each institution.ResultsTwenty-two institutions performed the patient-specific IMRT QA verifications. With a single-point dose measurement at the isocenter, the average difference between the calculated and measured doses was 0.5 ± 1.9%. For the comparison of dose distributions, 18 institutions used a two or three-dimensional array detector, while the others used Gafchromic film. In the γ test with dose difference/distance-to-agreement criteria of 3%?3 mm and 2%?2 mm with a 30% dose threshold, the median gamma pass rates were 99.3% (range: 41.7%–100.0%) and 96.4% (range: 29.4%–100.0%), respectively.ConclusionThis survey was an informative trial to understand the verification status of patient-specific IMRT QA measurements for prostate cancer. In most institutions, the point dose measurement and dose distribution differences met the desired criteria.     

In vivo tibiofemoral cartilage deformation during the stance phase of gait

The knowledge of articular cartilage contact biomechanics in the knee joint is important for understanding the joint function and cartilage pathology. However, the in vivo tibiofemoral articular cartilage contact biomechanics during gait remains unknown. The objective of this study was to determine the in vivo tibiofemoral cartilage contact biomechanics during the stance phase of treadmill gait. Eight healthy knees were magnetic resonance (MR) scanned and imaged with a dual fluoroscopic system during gait on a treadmill. The tibia, femur and associated cartilage were constructed from the MR images and combined with the dual fluoroscopic images to determine in vivo cartilage contact deformation during the stance phase of gait. Throughout the stance phase of gait, the magnitude of peak compartmental contact deformation ranged between 7% and 23% of the resting cartilage thickness and occurred at regions with thicker cartilage. Its excursions in the anteroposterior direction were greater in the medial tibiofemoral compartment as compared to those in the lateral compartment. The contact areas throughout the stance phase were greater in the medial compartment than in the lateral compartment. The information on in vivo tibiofemoral cartilage contact biomechanics during gait could be used to provide physiological boundaries for in vitro testing of cartilage. Also, the data on location and magnitude of deformation among non-diseased knees during gait could identify where loading and later injury might occur in diseased knees.