Bone drilling is a well-known process in operative fracture treatment and reconstructive surgery. The cutting ability of the drill is lost when used for multiple times. In this study, the effect of different levels of drill wear on bone temperature, drilling force, torque, delamination around the drilling region and surface roughness of the hole was investigated using a series of experiments. Experimental results demonstrated that the wear of the drill is strongly related to the drilling force, torque, temperature and surface roughness of the drilled hole. Statistical analysis was performed to find the effect of various factors on multiple response variables in the bone drilling process. The favorable conditions for bone drilling are obtained when feed rate, drill speed and the roughness of the cutting edge of the drill were fixed at 30 mm, 2000 rpm and up to 2 mm, respectively. Further, analysis of variance (ANOVA) was performed to determine the factor with a significant impact on the response variables. F-test and p-value indicated that the feed rate had the highest effect on grey relational grade followed by the roughness of the drill. This study suggests that the sharp drill along with controlled drilling speed and feed rate may be used for safe and efficient surgical drilling in bone.
Osteocytes are of high importance in bone metabolism as they orchestrate bone remodeling, react to mechanosensory stimuli and have endocrine functions. In vitro investigations with osteocytes are therefore of high relevance for biomaterial and drug testing. The application of primary human cells instead of rodent osteocyte cell lines like MLOY4 and IDG SW3 is desirable but provides the challenge of isolating these cells, which are deeply embedded into the mineralized bone matrix. The present study describes an improved protocol for the isolation of human primary osteocytes. In contrast to an already established protocol, resting steps between the demineralization /digestion steps of the bone particles considerably improved the yield of osteocytes. Real-time polymerase chain reaction (PCR) analysis revealed the expression of typical osteocyte markers like osteocalcin, E11/podoplanin and dentin matrix protein 1 (DMP-1).
B-mode ultrasonography and sonoelastography are used in the clinical diagnosis of prostate cancer (PCa). A combination of the two ultrasound (US) modalities using computer aid may be helpful for improving the diagnostic performance. A technique for computer-aided diagnosis (CAD) of PCa is presented based on multimodal US. Firstly, quantitative features are extracted from both B-mode US images and sonoelastograms, including intensity statistics, regional percentile features, gray-level co-occurrence matrix (GLCM) texture features and binary texture features. Secondly, a deep network named PGBM-RBM2 is proposed to learn and fuse multimodal features, which is composed of the point-wise gated Boltzmann machine (PGBM) and two layers of the restricted Boltzmann machines (RBMs). Finally, the support vector machine (SVM) is used for prostatic disease classification. Experimental evaluation was conducted on 313 multimodal US images of the prostate from 103 patients with prostatic diseases (47 malignant and 56 benign). Under five-fold cross-validation, the classification sensitivity, specificity, accuracy, Youden’s index and area under the receiver operating characteristic (ROC) curve with the PGBM-RBM2 were 87.0%, 88.8%, 87.9%, 75.8% and 0.851, respectively. The results demonstrate that multimodal feature learning and fusion using the PGBM-RBM2 can assist in the diagnosis of PCa. This deep network is expected to be useful in the clinical diagnosis of PCa.
Conventional electrophysiological (EP) tests may yield ambiguous or false-negative results in some patients with signs and symptoms of carpal tunnel syndrome (CTS). Therefore, researchers tend to investigate new parameters to improve the sensitivity and specificity of EP tests. We aimed to investigate the mean and maximum power of the compound muscle action potential (CMAP) as a novel diagnostic parameter, by evaluating diagnosis and classification performance using the supervised Kohonen self-organizing map (SOM) network models. The CMAPs were analyzed using the fast Fourier transform (FFT). The mean and maximum power parameters were calculated from the power spectrum. A counter-propagation artificial neural network (CPANN), supervised Kohonen network (SKN) and XY-fused network (XYF) were compared to evaluate the classification and diagnostic performance of the parameters using the confusion matrix. The mean and maximum power of the CMAP were significantly lower in patients with CTS than in the normal group (p < 0.05), and the XYF network had the best total performance of classification with 91.4%. This study suggests that the mean and maximum power of the CMAP can be considered as less time-consuming parameters for the diagnosis of CTS without using additional EP tests which can be uncomfortable for the patient due to poor tolerance to electrical stimulation.
The first part of this study investigated pattern recognition of head movements based on mechanomyography (MMG) signals. Four channel MMG signals were collected from the sternocleidomastoid (SCM) muscles and the splenius capitis (SPL) muscles in the subjects’ neck when they bowed the head, raised the head, side-bent to left, side-bent to right, turned to left and turned to right. The MMG signals were then filtered, normalized and divided using an unequal length segmentation algorithm into a single action frame. After extracting the energy features of the wavelet packet coefficients and the feature of the principal diagonal slices of the bispectrum, the dimension of the energy features were reduced by the Fisher linear discriminant analysis (FLDA). Finally, all the features were classified through the support vector machine (SVM) classifier. The recognition rate was up to 95.92%. On this basis, the second part of this study used the head movements to control a car model for simulating the control of a wheelchair, and the success rate was 85.74%.
Radioguided surgery (RGS) is the use of radiation detection probes and handheld gamma cameras in surgery rooms to identify radioactively labeled lesions inside the body with an aim to improve surgical outcome. In today’s surgery, application of these devices is a well-established practice, which provides surgeons with real-time information to guide them to the site of a lesion. In recent years, there have been several major improvements in the technology and design of gamma probes and handheld gamma cameras, enhancing their applications in surgical practices. Handheld gamma cameras, for example, are now moving from single-modality to dual-modality scanners that add anatomical data to the physiologic data, and with that provide more clinical information of the tissue under study. Also, in the last decade, a radioguided surgical technique based on the Cerenkov radiation was introduced, with more improved sensitivity in identifying radioactively labeled lesions. Additionally, recent advances in hybrid tracers have led to more efficient detection of lesions labeled with these tracers. Besides, it seems that combining medical robotics and augmented reality technology with current radioguided surgical practices potentially will change the delivery and performance of RGS in the near future. The current paper aims to give an overview of the physics of RGS and summarizes recent advances in this field that have a potential to improve the application of radioguided surgical procedures in the management of cancer.
In this paper, a method for evaluating the chronological age of adolescents on the basis of their voice signal is presented. For every examined child, the vowels a, e, i, o and u were recorded in extended phonation. Sixty voice parameters were extracted from each recording. Voice recordings were supplemented with height measurement in order to check if it could improve the accuracy of the proposed solution. Predictor selection was performed using the LASSO (least absolute shrinkage and selection operator) algorithm. For age estimation, the random forest (RF) for regression method was employed and it was tested using a 10-fold cross-validation. The lowest absolute error (0.37 year ± 0.28) was obtained for boys only when all selected features were included into prediction. In all cases, the achieved accuracy was higher for boys than for girls, which results from the fact that the change of voice with age is larger for men than for women. The achieved results suggest that the presented approach can be employed for accurate age estimation during rapid development in children.
Pay-load deliveries across the skin barrier to the systemic circulation have been one of the most challenging delivery options. Necessitated requirements of the skin and facilitated skin layer cross-over delivery attempts have resulted in development of different non-invasive, non-oral methods, devices and systems which have been standardized, concurrently used and are in continuous upgrade and improvements. Iontophoresis, electroporation, sonophoresis, magnetophoresis, dermal patches, nanocarriers, needled and needle-less shots, and injectors are among some of the methods of transdermal delivery. The current review covers the current state of the art, merits and shortcomings of the systems, devices and transdermal delivery patches, including drugs’ and other payloads’ passage facilitation techniques, permeation and absorption feasibility studies, as well as physicochemical properties affecting the delivery through different transdermal modes along with examples of drugs, vaccines, genes and other payloads.