Three dimensional measurement of minimum joint space width in the knee from stereo radiographs using statistical shape models

Recent advancements in digital health management using multi-modal signal monitoring

Healthcare is the method of keeping or enhancing physical and mental well-being with its aid of illness and injury prevention, diagnosis, and treatment. The majority of conventional healthcare practices involve manual management and upkeep of client demographic information, case histories, diagnoses, medications, invoicing, and drug stock upkeep, which can result in human errors that have an impact on clients. By linking all the essential parameter monitoring equipment through a network with a decision-support system, digital health management based on Internet of Things (IoT) eliminates human errors and aids the doctor in making more accurate and timely diagnoses. The term "Internet of Medical Things" (IoMT) refers to medical devices that have the ability to communicate data over a network without requiring human-to-human or human-to-computer interaction. Meanwhile, more effective monitoring gadgets have been made due to the technology advancements, and these devices can typically record a few physiological signals simultaneously, including the electrocardiogram (ECG) signal, the electroglottography (EGG) signal, the electroencephalogram (EEG) signal, and the electrooculogram (EOG) signal. Yet, there has not been much research on the connection between digital health management and multi-modal signal monitoring. To bridge the gap, this article reviews the latest advancements in digital health management using multi-modal signal monitoring. Specifically, three digital health processes, namely, lower-limb data collection, statistical analysis of lower-limb data, and lower-limb rehabilitation via digital health management, are covered in this article, with the aim to fully review the current application of digital health technology in lower-limb symptom recovery.

Three-Dimensional Subject-Specific Knee Shape Reconstruction with Asynchronous Fluoroscopy Images Using Statistical Shape Modeling

Background and objectives: Statistical shape modeling (SSM) based on computerized tomography (CT) datasets has enabled reasonably accurate reconstructions of subject-specific 3D bone morphology from one or two synchronous radiographs for clinical applications. Increasing the number of radiographic images may increase the reconstruction accuracy, but errors related to the temporal and spatial asynchronization of clinical alternating bi-plane fluoroscopy may also increase. The current study aimed to develop a new approach for subject-specific 3D knee shape reconstruction from multiple asynchronous fluoroscopy images from 2, 4, and 6 X-ray detector views using a CT-based SSM model; and to determine the optimum number of planar images for best accuracy via computer simulations and in vivo experiments.

Methods: A CT-based SSM model of the knee was established from 60 training models in a healthy young Chinese male population. A new two-phase optimization approach for 3D subject-specific model reconstruction from multiple asynchronous clinical fluoroscopy images using the SSM was developed, and its performance was evaluated via computer simulation and in vivo experiments using one, two and three image pairs from an alternating bi-plane fluoroscope.

Results: The computer simulation showed that subject-specific 3D shape reconstruction using three image pairs had the best accuracy with RMSE of 0.52 ± 0.09 and 0.63 ± 0.085 mm for the femur and tibia, respectively. The corresponding values for the in vivo study were 0.64 ± 0.084 and 0.69 ± 0.069 mm, respectively, which was significantly better than those using one image pair (0.81 ± 0.126 and 0.83 ± 0.108 mm). No significant differences existed between using two and three image pairs.

Conclusion: A new two-phase optimization approach was developed for SSM-based 3D subject-specific knee model reconstructions using more than one asynchronous fluoroscopy image pair from widely available alternating bi-plane fluoroscopy systems in clinical settings. A CT-based SSM model of the knee was also developed for a healthy young Chinese male population. The new approach was found to have high mode reconstruction accuracy, and those for both two and three image pairs were much better than for a single image pair. Thus, two image pairs may be used when considering computational costs and radiation dosage. The new approach will be useful for generating patient-specific knee models for clinical applications using multiple asynchronous images from alternating bi-plane fluoroscopy widely available in clinical settings. The current SSM model will serve as a basis for further inclusion of training models with a wider range of sizes and morphological features for broader applications.

Characterization of the mid-coronal plane method for measurement of radiographic change in knee joint space width across different levels of image parallax

OBJECTIVE

Radiographic measurement of the change in knee joint space width (ΔJSW) is often affected by image parallax, which causes an apparent exaggeration of JSW due to projectional differences. This issue with parallax (quantified by intermargin distance) can in part be addressed with a novel mid-coronal plane (MCP) measurement method. The objectives of the study were to determine 1) accuracy and 2) reproducibility of the MCP method, and 3) compare the MCP method to that used in the Osteoarthritis Initiative (OAI) for different categories of parallax.

METHODS

Posteroanterior radiographs (n = 70) with known JSW were digitally reconstructed from CT images of cadaver knees and used to determine the accuracy of ΔJSW using the MCP method for parallax categories of None, Mild/Moderate, and Severe. Reproducibility was determined from pairs of clinical radiographs selected from the OAI (n = 170). The MCP method was also compared to the OAI methodology. Both reproducibility and agreement were characterized by Bland-Altman analysis and intraclass correlation coefficients (ICC).

RESULTS

The MCP method was accurate to 0.11 mm in cases with no parallax, and 0.18 mm across all categories of parallax for medial and lateral compartments. Reproducibility of the MCP method was graded "excellent" (ICC 0.98, 95% CI [0.98, 0.99]). The MCP results agreed very well with the OAI (ICC 0.92, 95% CI [0.89, 0.94]), with mean absolute differences between methods increasing with increasing parallax.

CONCLUSION

The MCP method is an accurate, reproducible alternative to the OAI method for multi-center clinical trials where subject and X-ray beam positioning may be variable.

Morphological analysis of Gissane's angle utilising a statistical shape model of the calcaneus

INTRODUCTION

Gissane's crucial angle (GA) facilitates to diagnose calcaneal fractures, and serves as an indicator of the quality of anatomical reduction after fixation. The study aimed to utilise statistical shape models (SSM) for analysing the complex 3D surface anatomy of the calcaneus represented by the simplified GA measurement on lateral radiographs.

MATERIALS AND METHODS

SSMs were generated from CT scans of paired adult calcanei from 10 Japanese and 31 Thai specimens. GA measurements in 3D and 2D were obtained for the lateral, central and medial anatomy of the posterior facet and sinus tarsi. The correlation between calcaneal length and GA was analysed. Regression and principal component (PC) analyses were conducted for analysing morphological variability in calcaneal shape relating to GA. The bilateral symmetry of the obtained measurements was analysed.

RESULTS

The mean GA (lateral) for the Japanese specimens was 105.1° ± 7.5 and 105.4° ± 8.5 for the Thai. The projected 2D angles of the central and medial measurements were larger (P < 0.00) than the 3D values. The medial projected 2D angles were larger (P ≤ 0.02) compared to the lateral. Despite the bilateral symmetry of GA and calcaneal length, their correlation displayed clear signs of asymmetry, which was confirmed by regression and PC analyses.

CONCLUSIONS

Japanese and Thai specimens revealed lower GAs (both range and mean) compared to reported reference values of other ethnicities. As a reduced GA is generally indicative of a calcaneal fracture, our results are important to surgeons for their diagnostic assessment of Japanese and Thai patients. The results indicate that the GA measurement on a plain radiograph is a simplified representation of the lateral-to-central 3D calcaneal anatomy but significantly underestimates the angle measurement on the medial aspects of the respective surface areas.

Combining statistical shape modeling, CFD, and meta-modeling to approximate the patient-specific pressure-drop across the aortic valve in real-time

BACKGROUND

Advances in medical imaging, segmentation techniques, and high performance computing have stimulated the use of complex, patient-specific, three-dimensional Computational Fluid Dynamics (CFD) simulations. Patient-specific, CFD-compatible geometries of the aortic valve are readily obtained. CFD can then be used to obtain the patient-specific pressure-flow relationship of the aortic valve. However, such CFD simulations are computationally expensive, and real-time alternatives are desired.

AIM

The aim of this work is to evaluate the performance of a meta-model with respect to high-fidelity, three-dimensional CFD simulations of the aortic valve.

METHODS

Principal component analysis was used to build a statistical shape model (SSM) from a population of 74 iso-topological meshes of the aortic valve. Synthetic meshes were created with the SSM, and steady-state CFD simulations at flow-rates between 50 and 650 mL/s were performed to build a meta-model. The meta-model related the statistical shape variance, and flow-rate to the pressure-drop.

RESULTS

Even though the first three shape modes account for only 46% of shape variance, the features relevant for the pressure-drop seem to be captured. The three-mode shape-model approximates the pressure-drop with an average error of 8.8% to 10.6% for aortic valves with a geometric orifice area below 150 mm² . The proposed methodology was least accurate for aortic valve areas above 150 mm² . Further reduction to a meta-model introduces an additional 3% error.

CONCLUSIONS

Statistical shape modeling can be used to capture shape variation of the aortic valve. Meta-models trained by SSM-based CFD simulations can provide an estimate of the pressure-flow relationship in real-time.

Design, modeling and 3D printing of a personalized cervix tissue implant with protein release function

Cervical cancer induced by human papillomavirus (HPV) causes severe morbidity worldwide. Although cervical conization has been widely accepted as the most conventional surgery against cervical cancer, tissue defects and high recurrence rates have a significant negative impact on women's mental and physical health. Herein we developed an implantable, personalized cervical implant with drug release function using 3D printing technology. The cervical implant was designed in cone-shape with hieratical porous structures according to the clinical data, 3D-printed using polyurethane by low-temperature deposition manufacturing (LDM), and finished by lyophilization. Anti-HPV protein was loaded into the porous structure under negative pressure afterwards. Elastic biomedical polyurethane and the porous structure ensured that these cervical implants were equipped with tailored mechanical properties comparable to physiological cervix tissue. Cytotoxicity and cytocompatibility tests indicated that these 3D-printed cervical implants supported cell adhesion and growth. More importantly, the cervical implants with regulated pores could help to quantitatively control the loading and release of anti-HPV protein to inhibit dissociative viruses near the cervix validly. As a result, the 3D-printed cervical implants in the present study showed considerable potential for use as functional tissue implants against HPV infection after cervical conization.

Artificial intelligence supported patient self-care in chronic heart failure: a paradigm shift from reactive to predictive, preventive and personalised care

Heart failure (HF) is one of the most complex chronic disorders with high prevalence, mainly due to the ageing population and better treatment of underlying diseases. Prevalence will continue to rise and is estimated to reach 3% of the population in Western countries by 2025. It is the most important cause of hospitalisation in subjects aged 65 years or more, resulting in high costs and major social impact. The current "one-size-fits-all" approach in the treatment of HF does not result in best outcome for all patients. These facts are an imminent threat to good quality management of patients with HF. An unorthodox approach from a new vision on care is required. We propose a novel predictive, preventive and personalised medicine approach where patients are truly leading their management, supported by an easily accessible online application that takes advantage of artificial intelligence. This strategy paper describes the needs in HF care, the needed paradigm shift and the elements that are required to achieve this shift. Through the inspiring collaboration of clinical and high-tech partners from North-West Europe combining state of the art HF care, artificial intelligence, serious gaming and patient coaching, a virtual doctor is being created. The results are expected to advance and personalise self-care, where standard care tasks are performed by the patients themselves, in principle without involvement of healthcare professionals, the latter being able to focus on complex conditions. This new vision on care will significantly reduce costs per patient while improving outcomes to enable long-term sustainability of top-level HF care.

Anatomical fitting of a plate shape directly derived from a 3D statistical bone model of the tibia

INTRODUCTION

Intra- and inter-population variations of bone morphology have made the process of designing an anatomically well-fitting fracture fixation plate challenging. Although statistical bone models have recently been used for analysing morphological variabilities, it is not known to what extent they would also provide the basis for the design of a new plate shape. This would be particularly valuable in the case where no existing plate shape is available to start the process of fit optimisation. Therefore, this study investigated the anatomical fitting of a plate shape (statistical plate) derived from the mean shape of a statistical 3D tibia bone model in comparison to results available from two other plate shapes.

METHODS

Forty-five 3D bone models of tibiae from Japanese cadaver specimens, as well as 3D models of the plate undersurface of both a commercial and shape optimised Medial Distal Tibia Plate, were utilised from earlier studies. The mean shape of the 3D statistical bone model was generated from the tibia models utilising the Statismo framework. With reverse engineering software, the plate undersurface of the statistical plate shape was derived directly from the mean surface of the statistical 3D bone model. Through an iterative process, the statistical plate model was placed at the correct surgical position on each bone model for fit assessment.

RESULTS

The statistical plate was fitting for 20% of the tibiae compared to 13% for the commercial and 67% for the optimised plate, respectively.

CONCLUSIONS

The plate shape derived directly from a statistical bone model was fitting better than the commercial plate, but considerably inferior to that of an optimised plate. However, the results do clearly indicate that this approach provides an appropriate and solid basis for commencing shape optimisation of the statistical plate. Studies of other anatomical regions are required to confirm whether these findings can be generalised.

Radiostereometric analysis using clinical radiographic views: Validation with model-based radiostereometric analysis for the knee

Radiostereometric analysis is a sophisticated radiographic technique with high measurement accuracy. In order to improve the accessibility of radiostereometric analysis for clinical use, a modified radiostereometric analysis procedure has been previously proposed that enables clinical radiographic views to be used for radiostereometric analysis. It has been successfully validated for its application to the hip wear study with the conventional bead-based radiostereometric analysis environment using computed radiography. In this study, we describe the implementation and validation of this technique for the knee study with the model-based radiostereometric analysis environment using digital radiography. A knee-joint phantom with 6 degrees of freedom was examined, and the bias and repeatability/reproducibility of the modified radiostereometric analysis approach were investigated following the newly updated ASTM recommendations. The bias parameters (mean ± 95% confidence interval) ranged from 0.008 ± 0.003 mm to 0.027 ± 0.006 mm for translation and from 0.014° ± 0.007° to 0.040° ± 0.020° for rotation. The repeatability standard deviation ranged from 0.004 to 0.020 mm for translation and from 0.005° to 0.015° for rotation. The 95% repeatability limit ranged from 0.011 to 0.055 mm for translation and from 0.014° to 0.041° for rotation. The reproducibility standard deviation ranged from 0.004 to 0.023 mm for translation and from 0.006° to 0.040° for rotation. The 95% reproducibility limit ranged from 0.012 to 0.063 mm for translation and from 0.016° to 0.112° for rotation. The modified procedure allows routine clinical radiographs to be used for radiostereometric analysis, which provides the possibility of adding quantitative measurements to current patient registries.

Radiostereometric analysis using clinical radiographic views: Development of a universal calibration object

Radiostereometric analysis (RSA) is a highly accurate technique used to provide three-dimensional (3D) measurements of orthopaedic implant migration for clinical research applications, yet its implementation in routine clinical examinations has been limited. Previous studies have introduced a modified RSA procedure that separates the calibration examinations from the patient examinations, allowing routine clinical radiographs to be analyzed using RSA. However, in order to calibrate the wide range of clinical views, a new calibration object is required. In this study, a universal, isotropic calibration object was designed to calibrate any pair of radiographic views used in the clinic for RSA. A numerical simulation technique was used to design the calibration object, followed by a phantom validation test of a prototype to verify the performance of the novel object, and to compare the measurement reliability to the conventional calibration cage. The 3D bias for the modified calibration method using the new calibration object was 0.032 ± 0.006 mm, the 3D repeatability standard deviation was 0.015 mm, and the 3D repeatability limit was 0.042 mm. Although statistical differences were present between the universal calibration object and the conventional cage, the differences were considered to be not clinically meaningful. The 3D bias and repeatability values obtained using the universal calibration object were well under the threshold acceptable for RSA, therefore it was successfully validated. The universal calibration object will help further the adoption of RSA into a more routine practice, providing the opportunity to generate quantitative databases on joint replacement performance.