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ISSN 0928-7329 (P)
Impact Factor 2023: 1.6
Technology and Health Care is intended to serve as a forum for the presentation of original articles and technical notes, observing rigorous scientific standards. Furthermore, upon invitation, reviews, tutorials, discussion papers and minisymposia are featured.
The following types of contributions and areas are considered:
1. Original articles:
Technology development in medicine: New concepts, procedures and devices associated with the use of technology in medical research and clinical practice are presented to a readership with a widespread background in engineering and/or medicine.
Significance of medical technology and informatics for healthcare: The appropriateness, efficacy and usefulness deriving from the application of engineering methods, devices and informatics in medicine and with respect to public health are discussed.
2. Technical notes:
Short communications on novel technical developments with relevance for clinical medicine.
3. Reviews and tutorials (upon invitation only):
Tutorial and educational articles for persons with a primarily medical background on principles of engineering with particular significance for biomedical applications and vice versa are presented.
4. Minisymposia (upon invitation only):
Under the leadership of a Special Editor, controversial issues relating to healthcare are highlighted and discussed by various authors.
Abstract: BACKGROUND: Coronary artery disease (CAD) manifests with a blockage the coronary arteries, usually due to plaque buildup, and has a serious impact on the human life. Atherosclerotic plaques, including fibrous plaques, lipid plaques, and calcified plaques can lead to occurrence of CAD. Optical coherence tomography (OCT) is employed in the clinical practice as it clearly provides a detailed display of the lesion plaques, thereby assessing the patient’s condition. Analyzing the OCT images manually is a very tedious and time-consuming task for the clinicians. Therefore, automatic segmentation of the coronary OCT images is necessary. OBJECTIVE: In view…of the good utility of Unet network in the segmentation of medical images, the present study proposed the development of a Unet network based on Sk-Conv and spatial pyramid pooling modules to segment the coronary OCT images. METHODS: In order to extract multi-scale features, these two modules were added at the bottom of UNet. Meanwhile, ablation experiments are designed to verify each module is effective. RESULTS: After testing, our model achieves 0.8935 on f1 score and 0.7497 on mIOU. Compared to the current advanced models, our model performs better. CONCLUSION: Our model achieves good results on OCT sequences.
Abstract: BACKGROUND: 125 I BT is an effective radiotherapy for prostate cancer. However, comparison data of GI and GU toxicities between BT, BT + EBRT, and EBRT-alone patient groups is limited. OBJECTIVE: To define the GI and GU toxicities in prostate cancer to prevent adverse events after treatment. METHODS: We searched published studies in PubMed, Cochrane, and Embase databases up to December 31, 2022. The endpoints were the RRs of GI and GU toxicities. Pooled data were assessed using a random-effects model. RESULTS: Fifteen eligible…studies were included into this analysis. LDR-BT had significantly lower RRs than LDR-BT + EBRT for acute GI (2.13; 95% CI, 1.22–3.69; P = 0.007) and late GI toxicities (3.96; 95% CI, 1.23–12.70; P = 0.02). Moreover, EBRT had significantly higher RRs than LDR-BT for acute GU (2.32; 95% CI, 1.29–4.15; P = 0.005) and late GU toxicities (2.38; 95% CI, 1.27–4.44; P = 0.007). HDR-BT had significantly higher RRs for acute GU toxicities than LDR-BT alone (0.30; 95% CI, 0.23–0.40; P < 0.00001). CONCLUSION: The results implied that BT with and without EBRT can result in both GI and GU toxicities in patients with prostate cancer, with LDR-BT leading to a poorer urinary function than EBRT.
Abstract: BACKGROUND: Individuals with gait disturbances, such as that post-stroke, are discharged home to undergo outpatient rehabilitation. Rehabilitation in the community is not as effective as that in hospital, due to long travel times and short program duration. OBJECTIVE: This study analyzed rail unit structure, with the aim of assisting home indoor assistive mobility system (HIAMS) development, allowing patients to undergo gait-related rehabilitation training at home. METHODS: The HIAMS consists of a mobile rail running around the whole room, a turn-table for movement between rails, and a weight-supporting component. Structural analysis was performed using…the Abaqus/CAE solution (Version 6.14, Dassault systems, Inc.) to verify device safety, according to the load applied to the rail and turn-table units. The load was applied vertically at 150 kg to reflect the weight of potential users. RESULTS: Structural analysis was performed on the weight-supporting components, which was consist of turn-table case, bearing components (center, left), connective bracket and rail rollers. The safety factors of each components were estimated as 1.31, 5.39 (bearing, center), 8.45 (bearing, left), 1.43 and 3.61 in sequence. CONCLUSION: We demonstrated a safety factor of ⩾ 1.3 for the key system units, suggesting this technology is safe for use in the home rehabilitation training of individuals with gait impairment post-ICU stay.
Keywords: Assistive mobility system, rail unit development, indoor assistive mobility
Abstract: BACKGROUND: High-resolution (HR) magnetic resonance imaging (MRI) provides rich pathological information which is of great significance in diagnosis and treatment of brain lesions. However, obtaining HR brain MRI images comes at the cost of extending scan time and using sophisticated expensive instruments. OBJECTIVE: This study aims to reconstruct HR MRI images from low-resolution (LR) images by developing a deep learning based super-resolution (SR) method. METHODS: We propose a feedback network with self-attention mechanism (FNSAM) for SR reconstruction of brain MRI images. Specifically, a feedback network is built to correct shallow features by using…a recurrent neural network (RNN) and the self-attention mechanism (SAM) is integrated into the feedback network for extraction of important information as the feedback signal, which promotes image hierarchy. RESULTS: Experimental results show that the proposed FNSAM obtains more reasonable SR reconstruction of brain MRI images both in peak signal to noise ratio (PSNR) and structural similarity index measure (SSIM) than some state-of-the-arts. CONCLUSION: Our proposed method is suitable for SR reconstruction of MRI images.
Abstract: BACKGROUND: With the advent of 5G and the era of Big Data, the rapid development of medical information technology around the world, the massive application of electronic medical records and cases, and the digitization of medical equipment and instruments, a large amount of data has accumulated in the database system of hospitals, which includes clinical diagnosis data and hospital management data. OBJECTIVE: This study aimed to examine the classification effects of different machine learning algorithms on medical datasets so as to better explore the value of machine learning methods in aiding medical diagnosis. METHODS:…The classification datasets of four different medical fields in the University of California Irvine machine learning database were used as the research object. Also, six categories of classification models based on the Bayesian theorem idea, integrated learning idea, and rule-based and tree-based idea were constructed using the Weka platform. RESULTS: The between-group experiments showed that the Random Forest algorithm achieved the best results on the Indian liver disease patient dataset (ILPD), delivery cardiotocography (CADG), and lymphatic tractography (LYMP) datasets, followed by Bagging and partition and regression tree. In the within-group algorithm comparison experiments, the Bagging algorithm achieved better results than other algorithms based on the integration idea for 11 metrics on all datasets, mainly focusing on 2 binary datasets. Logit Boost had only 7 metrics with significant performance, and the best algorithm was Rotation Forest, with 28 metrics achieving optimal values. Among the algorithms based on tree ideas, the logistic model tree algorithm achieved optimal results on all metrics on the mammographic dataset (MAGR). The classification performance of BFTree, J48, and Random Tree was poor on each dataset. The best algorithm was Random Forest on the ILPD, CADG, and LYMP datasets with 27 metrics reaching the optimum. CONCLUSION: Machine learning algorithms have good application value in disease prediction and can provide a reference basis for disease diagnosis.
Keywords: Algorithms, comparison, machine learning, medical data, prediction, Weka
Abstract: BACKGROUND: Microglia express phosphatidylinositol 3-kinase (PI3K) has been implicated in the induction and maintenance of long-term potentiation (LTP) and in hippocampal synaptic plasticity. However, there are few studies on the interference of PI3K signal pathway in microglia. OBJECTIVE: The study goal is to gain a better understanding of the mechanism by which EA affects synapses provides insights into how electroacupuncture (EA) modulates synaptic plasticity in learning and memory. METHODS: Rat models of posttraumatic stress disorder (PTSD) were used to explore the effects of EA on microglial PI3K pathway, brain-derived neurotrophic factor (BDNF) and…LTP, and the target and mechanism underlying the effects of EA on PI3K from the perspective of protein ubiquitination. RESULTS: EA induced microglial BDNF expression by activating the PI3K-AKT pathway, thereby facilitating LTP and synaptic plasticity. EA inhibited lincRNA 02023 to rescue the binding of WWP2 to PTEN, thereby promoting PTEN ubiquitination and degradation. CONCLUSION: The mechanism of EA improving the learning and memory ability of PTSD rats may be that it can promote the competitive combination of WWP2 and PTEN by inhibiting Linc RNA02023, and then lead to microglial PI3K and its pathway activation, BDNF up-regulation, and finally induce LTP and repair damaged synaptic plasticity.
Keywords: PTSD, electroacupuncture, long-term potentiation, microglia, protein ubiquitination, long intergenic noncoding RNAs
Abstract: BACKGROUND: Eye exam diagnosis is one of the early detection methods for eye diseases. However, such a method is dependent on expensive and unpredictable optical equipment. OBJECTIVE: The eye exam can be re-emerged through an optometric lens attached to a smartphone and come to read the diseases automatically. Therefore, this study aims to provide a stable and predictable model with a given dataset representing the target group domain and develop a new method to identify eye disease with accurate and stable performance. METHODS: The ResNet-18 models pre-trained on ImageNet data composed of 1,000…everyday objects were employed to learn the dataset’s features and validate the test dataset separated from the training dataset. RESULTS: A proposed model showed high training and validation accuracy values of 99.1% and 96.9%, respectively. CONCLUSION: The designed model could produce a robust and stable eye disease discrimination performance.
Keywords: Deep learning model, image data, eye exam
Abstract: BACKGROUND: As a unique traditional Chinese medicine therapy, the central effect of acupuncture has received increasing attention. Functional brain networks can provide connectivity information among brain regions. OBJECTIVE: The study goal is to explore the regulatory effect of acupuncture on the brain functional network. METHODS: This paper analyzes the electroencephalography (EEG)-based power spectrum and brain functional network elicited by acupuncture at Quchi (LI 11). RESULTS: The power spectrum results showed that acupuncture at LI 11 decreased the energy in the alpha frequency, mainly in the central region, left parietal lobe,…left temporal lobe and left frontal lobe. Moreover, functional brain networks converted from the magnitude-squared coherence matrix in the alpha band are reconstructed. The results show that acupuncture did not alter the basic properties of the brain functional connection network. During acupuncture, the average node degree, average clustering coefficient, and small-world property of the brain functional connection network decreased after acupuncture compared with that before it. However, the average characteristic path length increased after acupuncture compared with before. CONCLUSION: Acupuncture at LI 11 altered the brain’s electrical activity. In the meantime, this acupuncture reduced the network’s internal connectivity and information transfer efficiency.
Keywords: Acupuncture, functional brain networks, electroencephalography, Quchi (LI 11)
Abstract: BACKGROUND: Haemorrhage of pancreas is a rare cause of upper gastrointestinal bleeding, and currently there is no clinical satisfactory treatment for this disorder. OBIECTIVE: The present study envisaged to treat the haemorrhage of pancreas caused by pseudoaneurysm rupture using interventional super-selective coil impregnation therapy, so as to achieve a better treatment efficacy. METHODS: Six cases presenting haemorrhage of pancreas were employed for the study, including 5 cases caused by splenic artery pseudoaneurysm and 1 case caused by superior pancreatic artery pseudoaneurysm. In all 6 patients the femoral artery was punctured using Seldinger femoral…artery puncture and intubation technique. Subsequently, a catheter was inserted into the abdominal trunk and the contrast medium was injected, and the pseudoaneurysm was developed. A coil was then inserted into the distal end and proximal end of the pseudoaneurysm, respectively, leading to the elimination of the pseudoaneurysm. RESULTS: All 6 patients with pancreatic haemorrhage were implanted with coil at the distal and proximal end of the aneurysm, until the aneurysm disappeared during intraoperative angiography. Further, clinical symptoms such as abdominal pain, melena and hematemesis disappeared after the operation. No recurrence of the symptoms was observed in the studied population. CONCLUSION: A 100% treatment outcome can be achieved in patients with pseudoaneurysm-induced haemorrhage of pancreas using interventional super-selective coil embolization.
Keywords: Hemorrage of pancreatic duct, pseudoaneurysm, embolization, super-selective
Abstract: BACKGROUND: Chaihu Shugan powder (CSP) is a prevalent prescription product used in the treatment functional dyspepsia (FD) in China. However, the underlying pharmacological mechanisms involved in the treatment of FD remain unclear. OBJECTIVE: To explore the key components of CSP and their molecular targets and mechanisms in the treatment of FD. METHODS: Active compounds for CSP were identified from the TCMSP and SymMap databases, and the relevant targets were predicted. FD-related targets were obtained from the GeneCards and CTD database. In addition, using the protein-protein interactions (PPI) analysis, the common targets were obtained.…Furthermore, the compound-target networks were created with Cytoscape. Finally, molecular docking was performed to identify the core targets and validate them experimentally. RESULTS: In total, 78 active compounds and 671 related targets of CSP were obtained. PPI network analysis identified 15 key FD-related compound targets. Molecular docking revealed that sitosterol and hyndarin exhibited good binding activities with AKT1 and IL6, respectively. Animal experiments have shown that CSP effectively increased the protein levels of AKT1 and reduced the serum levels of IL-6 in FD rats. CONCLUSION: This study provides a theoretical evidence for the analysis of the molecular targets and mechanisms of the action of CSP in FD.