Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine最新文献

This paper presents the outcome of a data review of patients treated with the IOS external fixation system at the Royal Stoke University Hospital: a fixation designed to meet four requirements for external fixation proposed in this paper. Demographic data and outcome were collected and assessed. From 69 initial patients, 64 patients (55 males and 9 females) had an average age of 35.9 years. The mean time to union was 127 days. There were no incidences of malunion, or refracture post fixation removal attributable to the treatment method. In addition, in this cohort, there was no incidence of pin tract infection resulting in osteomyelitis. Of all the factors assessed the only factor to have any significant effect on healing was smoking: an average delay of 31 days. An examination of RUST (radiographic union score tibia) and modified RUST scores illustrated a potential false negative of up to 80%. Hence, this study cannot support the use of either scoring system to diagnose fracture healing. IOS external fixation was shown to be an effective method for the treatment of unstable tibial fractures. The reduction at fixation removal was shown to be very good. There was no incidence of osteomyelitis. It is, therefore, suggested that appropriately used external fixation is a viable alternative to intramedullary nailing if designed and surgically applied using four design principles outlined in this paper. Furthermore, it is proposed that external fixation be designed and applied to meet these four principles.

Machine Learning (ML) techniques provide the ability to effectively evaluate and analyze human skin and hair assessments. The aim of this study is to systematically review the effectiveness of applying Machine Learning (ML) methods and Artificial Intelligence (AI) techniques in order to evaluate hair and skin assessments. PubMed, Web of Science, IEEE Xplore, and Science Direct were searched in order to retrieve research publications between 1 January 2010 and 31 March 2020 using appropriate keywords such as "hair and skin analysis." Following accurate screening, 20 peer-reviewed publications were selected for inclusion in this systematic review. The analysis demonstrated that prevalent Machine Learning (ML) methods comprised of Support Vector Machine (SVM), k-nearest Neighbor, and Artificial Neural Networks (ANN). ANN's were observed to yield the highest accuracy of 95% followed by SVM generating 90%. These techniques were most commonly applied for drafting framework assessments such as that of Melanoma. Values of parameters such as Sensitivity, Specificity, and Area under the Curve (AUC) were extracted from the studies and with the help of comparisons, relevant inferences were also made. ANN's were observed to yield the highest sensitivity of 82.30% as well as a 96.90% specificity. Hence, with this systematic review, a summarization of the studies was drafted that encapsulated how Machine Learning (ML) techniques have been employed for the analysis and evaluation of hair and skin assessments.

This study aimed to compare the 3D skull models reconstructed from computed tomography (CT) images using three different open-source software with a commercial software as a reference. The commercial Mimics v17.0 software was used to reconstruct the 3D skull models from 58 subjects. Next, two open-source software, MITK Workbench 2016.11, 3D Slicer 4.8.1 and InVesalius 3.1 were used to reconstruct the 3D skull models from the same subjects. All four software went through similar steps in 3D reconstruction process. The 3D skull models from the commercial and open-source software were exported in standard tessellation language (STL) format into CloudCompare v2.8 software and superimposed for geometric analyses. Hausdorff distance (HD) analysis demonstrated the average points distance of Mimics versus MITK was 0.25 mm. Meanwhile, for Mimics versus 3D Slicer and Mimics versus InVesalius, there was almost no differences between the two superimposed 3D skull models with average points distance of 0.01 mm. Based on Dice similarity coefficient (DSC) analysis, the similarity between Mimics versus MITK, Mimics versus 3D Slicer and Mimics versus InVesalius were 94.1, 98.8 and 98.3%, respectively. In conclusion, this study confirmed that the alternative open-source software, MITK, 3D Slicer and InVesalius gave comparable results in 3D reconstruction of skull models compared to the commercial gold standard Mimics software. This open-source software could possibly be used for pre-operative planning in cranio-maxillofacial cases and for patient management in the hospitals or institutions with limited budget.

Owing to environmental and disease issues, the use of high-frequency chest wall oscillation (HFCWO) devices in hospitals is consistently increasing. This study proposes a cost-effective actuator-less HFCWO device that utilizes an external wall port utility in hospitals to generate the positive and negative pneumatic pressures required for HFCWO treatment instead of an embedded mechanical actuator. The manufactured prototype with the no-amplification (NO-AMP) setting contained an electric pressure regulator to enable intensity level adjustment and two solenoid valves to enable vibration frequency adjustment, whereas the prototype with the pre-amplification (PRE-AMP) setting contained an additional air reservoir and an air-pressure booster. The prototype device was tuned to output average local maximum values in the pressure waveform similar to a commercial VEST-205 device at an 8-12 Hz frequency and 2-4 pressure intensity levels. In vitro comparative experiments demonstrated that the prototype device showed similar local maximum pressures to those of the VEST-205 (mean absolute pressure difference, <3 mmH₂O); in contrast, the proposed device showed significantly higher local minimum pressures than those of the VEST-205 (mean absolute pressure difference, >8 mmH₂O). Additionally, the driving sound of the proposed device was 17.0-17.8 dB higher than that of VEST-205. We conclude that the proposed device has the potential to substitute for conventional HFCWO devices under the limited but most frequently used operating conditions, although more detailed modifications are necessary in future studies to improve its performance and clinical usability.

In recent years, artificial cervical discs have been used in intervertebral disc replacement surgery and hybrid surgery (HS). The advantages and disadvantages of different artificial cervical discs in artificial cervical disc replacement surgery have been compared. However, few scholars have studied the biomechanical effects of various artificial disc prostheses on the human cervical spine in HS which include the Anterior Cervical Discectomy and Fusion (ACDF) and Cervical Disc Arthroplasty (CDA). This study compared the biomechanical behavior of Mobi-C and Prestige LP in the operative and adjacent segments during two-level hybrid surgery. A three-dimensional finite element model of C2-C7 was first established and validated. Subsequently, clinical surgery was then simulated to establish a surgical model of anterior cervical fusion at the C4-C5 level. Mobi-C and Prestige-LP artificial disc prostheses were implanted at the C5-C6 level to create two hybrid models. All finite element models were fixed on the lower endplate of the C7 vertebra and subjected to a load of 73.6 N and different directions of 1 Nm torque on the odontoid process of the C2 vertebra to simulate human flexion, extension, lateral bending, and axial rotation. This paper compares the ROM, intervertebral pressure, and facet joint force after hybrid surgery with the intact model. The results show that compared with Prestige LP, Mobi-C can improve ROM of the replacement segment and compensate for the intervertebral pressure of the adjacent segment more effectively, but the facet joint pressure of the replacement segment may be higher.

The running-in process is considered an essential aspect of the comprehensive wear process. The phenomenon of running-in occurs during the initial stages of wear in the prosthetic hip joint. Within the field of tribology, the running-in phenomenon of the hip joint pertains to the mechanism by which the contact surfaces of the artificial hip joint components are adjusted and a suitable lubricating film is formed. During the process of hip joint running-in, there is an interaction between the metal surface of the ball and the joint cup, which results in adjustments being made until a steady state is achieved. The achievement of desirable wear existence and reliable performance of artificial hip joint components are reliant upon the tribological running-in of the hip joint. Despite the establishment of current modeling approaches, there remains a significant lack of understanding concerning running-in wear, particularly the metal-on-polyethylene (MoP) articulations in dual-mobility cups (DMC). An essential aspect to consider is the running-in phase of the dual mobility component. The present study employed finite element analysis to investigate the running-in behavior of dual mobility cups, wherein femoral head components were matched with polyethylene liners of varying thicknesses. The analysis of the running-in phase was conducted during the normal gait cycle. The results of this investigation may be utilized to design a dual-mobility prosthetic hip joint that exhibits minimal running-in wear.

The diagnosis of osteoporosis using Dual-energy X-ray Absorptiometry (DXA) relies on accurate hip scans, whereby variability in measurements may be introduced by altered patient positioning, as could occur with repeated scans over time. The goal herein was to test how altered postures affect diagnostic metrics (i.e., standard clinical metrics and a newer image processing tool) for femur positioning. A device was built to support cadaveric femurs and adjust their orientation in 3° increments in flexion and internal/external rotation. Seven isolated femurs were scanned in six flexion postures (0° (neutral) to 15° of flexion) and eleven rotational postures (15° external to 15° internal rotation) while collecting standard clinical DXA-based measures for each scan. The fracture risk tool was applied to each scan to calculate fracture risk. Two separate one-way repeated measures ANOVAs (α = 0.05) were performed on the DXA-based measures and fracture risk prediction output. Flexion had a significant effect on T-score, Bone Mineral Density (BMD), and Bone Mineral Content (BMC), but not area, at angles greater than 12°. Internal and external rotation did not have a significant effect on any clinical metric. Fracture risk (as assessed by the image processing tool) was not affected by either rotation mode. Overall, this suggests clinicians can adjust patient posture to accommodate discomfort if deviations are less than 12 degrees, and the greatest care should be taken in flexion. Furthermore, the tool is relatively insensitive to postural adjustments, and as such may be a good option for tracking risk over repeated patient scans.

Electrogastrography (EGG) is a novel diagnostic modality for assessing the gastrointestinal tract (GI) that generates spontaneous electrical activity and monitors gastric motility. The aim of this study was to compare patients with functional dyspepsia (FD) and diabetic gastroparesis (D-GP) with healthy controls (CT) to use established findings on abnormalities of gastric motility based on EGG characteristics. In this study, 50 patients with FD, 50 D-GP patients, and 50 CT subjects were studied to compare EGG with discrete wavelet transform models (DWT) to extract signal characteristics using a variety of different qualitative and quantitative metrics from pre-prandial and postprandial states. As a result, higher statistically significant (p < 0.05*) were found in the DWT models based on power spectral density (PSD) analysis in both states. We also present that the correlations between EGG metrics and the presence of FD, D-GP, and CT symptoms were inconsistent. This paper represents that EGG assessments of FD and D-GP patients differ from healthy controls in terms of abnormalities of gastric motility. Additionally, we demonstrate that diverse datasets showed adequate gastric motility responses to a meal. We anticipate that our method will provide a comprehensive understanding of gastric motility disorders for better treatment and monitoring in both clinical and research settings. In conclusion, we present potential future opportunities for precise gastrointestinal electrophysiological disorders.

Gastrointestinal surgery using a stapler is usually associated with tissue damage, anastomosis leakage, bleeding, and other complications, which is one of the effective methods for treating digestive tract cancer. The cutting properties of staples and the tissue damage occurring in the process of stapling porcine esophageal and gastric tissues have been evaluated and a new type of stapler has been designed. Since different structural and mechanical properties esophageal and gastric tissues layers, the puncturing force exhibits a fluctuating trend. Compressive stress caused by the bending of the staple legs can lead to the destruction of the vascular network inside the tissue, tissue deforms and tears. Finally, a staple with an internal incision arc (IIA) tip is designed, which meeting the performance requirements.

Diabetic retinopathy (DR) is a rapidly emerging retinal abnormality worldwide, which can cause significant vision loss by disrupting the vascular structure in the retina. Recently, optical coherence tomography angiography (OCTA) has emerged as an effective imaging tool for diagnosing and monitoring DR. OCTA produces high-quality 3-dimensional images and provides deeper visualization of retinal vessel capillaries and plexuses. The clinical relevance of OCTA in detecting, classifying, and planning therapeutic procedures for DR patients has been highlighted in various studies. Quantitative indicators obtained from OCTA, such as blood vessel segmentation of the retina, foveal avascular zone (FAZ) extraction, retinal blood vessel density, blood velocity, flow rate, capillary vessel pressure, and retinal oxygen extraction, have been identified as crucial hemodynamic features for screening DR using computer-aided systems in artificial intelligence (AI). AI has the potential to assist physicians and ophthalmologists in developing new treatment options. In this review, we explore how OCTA has impacted the future of DR screening and early diagnosis. It also focuses on how analysis methods have evolved over time in clinical trials. The future of OCTA imaging and its continued use in AI-assisted analysis is promising and will undoubtedly enhance the clinical management of DR.