Journal of Mechanics in Medicine and Biology

Thermography is a non-invasive and non-contact imaging technique widely used in the medical arena. This paper investigates the analysis of thermograms with the use of biostatistical methods and Artificial Neural Networks (ANN). It is desired that through these approaches, highly accurate diagnosis using thermography techniques can be established.

The proposed advanced technique is a multipronged approach comprising of Linear Regression (LR), Radial Basis Function Network (RBFN) and Receiver Operating Characteristics (ROC). It is a novel and integrative technique that can be used to analyze complicated and large numerical data. In this study, the advanced technique will be used to analyze breast cancer thermogram for diagnosis purposes.

The use of LR shows the correlation between the variables and the actual health status (healthy or cancerous) of the subject, which is decided by using mammography. This is important when selecting the variables to be used as inputs, in particular, for building the neural network.

For ANN, RBFN is applied. Based on the various inputs fed into the network, RBFN will be trained to produce the desired outcome, which is either positive for cancerous or negative for healthy cases. When this is done, the RBFN algorithm will possess the ability to predict the outcome when there are new input variables. The advantages of using RBFN include fast training, superior classification and decision making abilities as compared to other networks such as back-propagation.

Next, ROC is used to evaluate the accuracy, sensitivity and specificity of the outcome of RBFN Test files. The best results obtained are an accuracy (score) rate of 80.95%, with 81.2% sensitivity and 88.2% specificity. For breast cancer diagnosis, clinical examination by experienced doctors has an accuracy rate of approximately 60–70%. Hence, the proposed method has a higher accuracy rate than the existing practice.

Through the use of Bio-statistical methods and ANN, improvements are made in thermography application with regard to achieving a higher level of accuracy rate in diagnosis as compared to clinical examination. It has now become possible to use thermography as a powerful adjunct tool for breast cancer detection, together with mammography for diagnosis purposes.

Malignancies of the oral cavity are conventionally diagnosed by white light endoscopy, biopsy and histopathology. However, it is often difficult to distinguish between benign lesions and premalignant or early lesions. There is a need for a more definitive, non-invasive technique for diagnosis of oral cavity lesions. A laser confocal endomicroscope offers non-invasive surface and subsurface imaging of tissue. We investigated its potential for fluorescence imaging of the oral cavity using hypericin, fluorescein and aminolevulinic acid. Fluorescence imaging was carried out both in vivo and on resected tissue samples of the oral cavity in both humans and animal models. Good structural images of the oral cavity were obtained. Morphological differences between normal and lesion tissue can be distinguished. The use of Pharmasolve® enhanced the subsurface depth from which images can be obtained. Our results show that laser confocal fluorescence endomicroscopy has great potential for the diagnosis of oral cavity malignancies.

Worldwide, oral cancer is the sixth most common cancer for both sexes. In Singapore, the 5-year survival rate of oral cancer is about 50%. The high mortality rate has been attributed to the difficulties in detecting the disease in an early treatable stage. Here, we present two application examples of gold nanoparticles in the early detection of oral cancer. In the first, gold nanoparticles were used as a reflective contrast agent for performing molecular imaging under confocal reflectance microscopy for the early diagnosis of epithelial carcinoma. While in the second, closely-packed gold nanoparticle, films were used as a bio-sensing surface for the chemical analysis of saliva via Surface Enhanced Raman Scattering. Preliminary results will be discussed.

Surgical training is one of the most promising areas in medicine where 3-D computer graphics and virtual reality techniques are emerging. Orthopedic surgery is a discipline requiring appreciation and understanding of complex 3-dimensional bony structures and their relationships to nerves, blood vessels and other vital structures. Learning these spatial skills requires a lengthy period and much practice. In this paper, we present a software simulator which was developed to aid in the understanding of the complex 3-dimensional relationships between bones and implants. The developed software cuts down the learning curve and allows for better and more precise surgery by letting the surgeon practice the surgery in a virtual environment before undertaking the actual procedure.

The 3D volume visualization is to overcome the difficulties of the 2D imaging by using computer technology. A volume visualization approach has been successfully implemented for Surgical Planning System in National Neuroscience Institute (NNI). The system allows surgeons to plan a surgical approach on a set of 2D image slices and process into volume models and visualise them in 3D rapidly and interactively on PC. In our implementation, we have applied it in neurosurgical planning. The surgeon can visualize objects of interest like tumor and surgical path, and verify that the surgical plan avoids the critical features and the planning of the surgical path can thus be optimal.

Injuries to the knee joint are common and often have an adverse impact on a patient's quality of life. It is therefore important to understand the load transfer mechanism of the knee, especially with regard to the loading of the menisci in different positions and under different conditions.

To date, only contact pressure between joint surfaces and menisci, as well as circumferential strain, have been measured by pressure sensors and strain gauges. Therefore, the aim of this study was to investigate the spread of axial load within the menisci and the effect of the knee flexion angle on the axial load within the menisci.

Intrameniscal forces were measured with Fiber Bragg Grating (FBG) sensors and conductive rubber sensors in porcine knee joint specimens. The changes in pressure were measured under different loading conditions. Measurement of the intrameniscal pressure is feasible. Although, there is some existence of variations in readings, some trends can be inferred. From the overall trend, it was observed that higher stress occurs at lateral central and lateral posterior regions. As the occurrences of injuries are mainly at the medial meniscus, this may imply that the level of stress is secondary to the mobility of the meniscus in incidents of injuries. It was found that the posterior meniscofemoral ligament plays a crucial role in the mechanics of the lateral meniscus.

A mathematical model of the A2 pulley system will enable us to have a better understanding of the mechanics of the pulley-tendon system and provide us with insights of the pulley rupture mechanism. The A2 pulley was modeled based on parallel pulley fibers attached to a phalanx with a tendon passing them. Mechanical properties of the pulleys such as stiffness, strength and friction were included in the model. A convergence test was done to ensure the accuracy of the test. The model managed to show high loads on flexed finger may lead to pulley ruptures. Further studies on the rupture mechanism showed that pulley ruptures are self-propagating when a constant force is applied and the rate of rupture increases, as fewer intact fibers are present to support the load. The initial rate of propagation is much slower and this accelerates as more fibers are ruptured. This explains the common occurrence of partial pulley ruptures.

Permanent metallic stents are frequently used in cardiovascular interventions, due to the many advantages metals possess in bulk and surface properties, design and chemistry, as well as their high modulus and ease of producing thin sections. However, the presence of foreign bodies in humans is associated with many long-term safety concerns; removal of the stent is therefore preferred through a second intervention after recovery. Based primarily on this consideration, biodegradable stents have been of significant interest in the past few years. This paper reports the manufacturing and near-physiological testing of a novel Biodegradable Metallic Coronary Stent (BMCS). To date, very limited literature is available on this aspect of research. Generally, magnesium is reactive and generally difficult to process. However, preliminary results demonstrate strong feasibility of fabricating low-profiled magnesium-based biodegradable coronary stents. Near-physiological tests based on a specially designed accelerated radial stent fatigue system were carried out. Results show that the biodegradable stents retained their arterial scaffolding functions for up to one year (simulated) before totally being resorbed into the biological fluid past its point of functionality. The results obtained so far show great promise for application.

The convergence of biomedical instruments and computing platforms has resulted in medical imaging equipment being subjected to the threats of malicious software (Malware) which have traditionally plagued the computing industry.

Vulnerabilities increase several-fold with implementations of Clinical Information Systems like the Picture Archival & Communication Systems (PACS), where computer-based biomedical equipment work hand in glove with computer servers.

With the increasing complexity of modern Malware, proactive monitoring and reviews of known vulnerabilities are no longer sufficient. An institute faced with an IT security attack on their medical networks will still experience extended downtime, performance degradation and increased service costs, even if equipped with an adequate security system and recovery plans.

Biomedical equipment vendors usually need more time than computing vendors to validate the security updates required for vulnerabilities before they can recommend changes for installation to their systems. This includes all system changes, patches, updates, and enhancements. However, the interval between the launch of a new Malware attack and the availability of a solution from the vendor can result in the medical network being compromised and rendered totally crippled.

In view of such new challenges, it is crucial to redesign your medical network and operating procedures to ensure continuous operation with minimum performance degradation even under a Malware attack until the biomedical equipment vendor can provide the software updates to resolve security vulnerabilities.

Such strategic implementation is not only necessary to ensure integrity and confidentiality of patient's data but also to protect the healthcare institute's reputation and business continuity.

This study characterizes left ventricular function in terms of passive and active elastances (E_p & E_a) and shape factor index. Both the active elastance and shape factor indices can be employed as contractility indices. The work also demonstrates how E_p and E_a can explain LV pressure dynamics in terms of LV volume dynamics.