Biomedical Physics & Engineering Express最新文献

{"title":"High performance method for COPD features extraction using complex network.","authors":"Trong-Thanh Han, Kien Le Trung, Phuong Nguyen Anh, Phat Nguyen Huu","doi":"10.1088/2057-1976/ad8093","DOIUrl":"10.1088/2057-1976/ad8093","url":null,"abstract":"<p><p><i>Objectives</i>. The paper proposes a novel methodology for the classification of Chronic Obstructive Pulmonary Disease (COPD) utilizing respiratory sound attributes.<i>Methods</i>. The approach involves segmenting respiratory sounds into individual breaths and conducting extensive studies on this dataset. Spectral Transforms, various Wavelet Transforms are applied to capture distinct signal features. Complex Network is also employed to extract characteristic elements, generating novel representations of spectrogram data based on graph factors, including entropy, density, and position. The normalized and enriched data is then used to develop COPD classifiers using six machine learning algorithms, fine-tuning with appropriate training details and hyperparameter tuning.<i>Results</i>. Our results demonstrate robust performance, with ROC curves consistently exhibiting an Area Under the Curve (AUC) > 96% across different time-frequency transformations. Notably, the Random Forest algorithm achieves an AUC of 99.67%, outperforming other algorithms. Moreover, the Wavelet Daubechies 2 (Db2) consistently approaches 98% accuracy, particularly noteworthy in conjunction with the Naive Bayes algorithm.<i>Conclusion</i>. This study diagnosis patients through spectrogram images extracted from lung sounds. The application of Inverse Transforms, Complex Network, and Optimized Classification Algorithms yielded results beyond expectations. This methodology provides a promising approach for accurate COPD diagnosis, leveraging Machine Learning techniques applied to respiratory sound analysis.</p>","PeriodicalId":8896,"journal":{"name":"Biomedical Physics & Engineering Express","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142340560","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"TRU-IMP: techniques for reliable use of images in medical physics; a graphical user interface to analyze and compare segmentations in nuclear medicine.","authors":"Philippe Laporte, Jean-François Carrier","doi":"10.1088/2057-1976/ad82ef","DOIUrl":"10.1088/2057-1976/ad82ef","url":null,"abstract":"<p><p><i>Background</i>. In the context of pharmacokinetic analyses, the segmentation method one uses has a large impact on the results obtained, thus the importance of transparency.<i>Innovation</i>. This paper introduces a graphical user interface (GUI), TRU-IMP, that analyzes time-activity curves and segmentations in dynamic nuclear medicine. This GUI fills a gap in the current technological tools available for the analysis of quantitative dynamic nuclear medicine image acquisitions. The GUI includes various techniques of segmentations, with possibilities to compute related uncertainties.<i>Results</i>. The GUI was tested on image acquisitions made on a dynamic nuclear medicine phantom. This allows the comparison of segmentations via their time-activity curves and the extracted pharmacokinetic parameters.<i>Implications</i>. The flexibility and user-friendliness allowed by the proposed interface make the analyses both easy to perform and adjustable to any specific case. This GUI permits researchers to better show and understand the reproducibility, precision, and accuracy of their work in quantitative dynamic nuclear medicine.<i>Availability and Implementation</i>. Source code freely available on GitHub:https://github.com/ArGilfea/TRU-IMPand location of the interface available from there. The GUI is fully compatible with iOS and Windows operating systems (not tested on Linux). A phantom acquisition is also available to test the GUI easily.</p>","PeriodicalId":8896,"journal":{"name":"Biomedical Physics & Engineering Express","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2024-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142370903","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluation of automatic tube current modulation in a CT scanner using a customised homogeneous phantom.","authors":"Urshella Hishaam, Jeyasingam Jeyasugiththan, Sameera Viswakula, D M Satharasinghe, T Amalaraj, M Costa, A M C Kumarihami, Aruna Pallewatte, Steve Peterson","doi":"10.1088/2057-1976/ad857a","DOIUrl":"10.1088/2057-1976/ad857a","url":null,"abstract":"<p><p><i>Objective.</i>The introduction of automatic tube current modulation (ATCM) has resulted in complex relationships between scanner parameters, patient body habitus, radiation dose, and image quality. ATCM adjusts tube current based on x-ray attenuation variations in the scan region, and overall patient dose depends on a combination of factors. This work aims to develop mathematical models that predict CT radiation dose and image noise in terms of attenuating diameter and all relevant scanner parameters.<i>Approach.</i>A homogenous phantom, equipped with the features to conduct discrete and continuous adaption tests, was developed to model ATCM in a Philips CT scanner. Scanner parameters were varied based on theoretical dose relationships, and a MATLAB script was developed to extract data from DICOM images. R statistical software was employed for data analysis, plotting, and regression modelling.<i>Main Results.</i>Phantom data provided the following insights: Median tube current decreased by 81% as tube potential varied from 80 kVp to 140 kVp. Doubling the DoseRight Index (DRI) from 12 to 24, at 24 cm diameter, produced a 294% increase in mA and a 46% decrease in noise. Mean mA increased by 53% whilst mean noise increased by 5.7% as helical pitch increased from 0.6 to 0.925. Changing rotation time from 0.33s to 0.75s gave a 56% reduction in mean mA and no change in image noise. Increasing detector collimation (<i>n × T</i>) resulted in higher tube currents and lower output image noise values, as<i>n</i>and<i>T</i>were varied independently. Interpreting these results to apply transformations relevant to each independent variable produced models for tube current and noise with adjusted R-squared values of 0.965 and 0.912, respectively.<i>Significance.</i>The models developed more accurately predict radiation dose and image quality for specific patients and scanner settings. They provide imaging professionals with a practical tool to optimize scan protocols according to patient diameters and clinical objectives.</p>","PeriodicalId":8896,"journal":{"name":"Biomedical Physics & Engineering Express","volume":"10 6","pages":""},"PeriodicalIF":1.3,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142457123","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Computed tomography employing sensing of high energy particle current.","authors":"Piotr Zygmanski, Davide Brivio, Wolfgang Hoegele","doi":"10.1088/2057-1976/ad844d","DOIUrl":"10.1088/2057-1976/ad844d","url":null,"abstract":"<p><p><i>Objective</i>. We demonstrate High Energy Current Computed Tomography (HEC-CT) employing megavoltage linac x-rays.<i>Approach</i>. Using deterministic radiation transport we simulate two-parameter HEC-CT projections and using inverse Fourier transform we reconstruct two distinct material parameters for water phantoms with ICRP tissue inserts and materials of different atomic number Z. The HEC-CT projections are obtained by beam scanning and rotating the object.<i>Main Results</i>. The first HEC-CT material parameter is alike the standard attenuation coefficient with dependence on atomic number and material density similar to the Hounsfield Units. The second material parameter has opposite trends and does not find any analogy in the standard CT framework.<i>Significance</i>. New CT method has been invented for medical imaging or non-destructive testing. The key feature of the technique is a two-value CT reconstruction based on particle current instead of transmitted dose.</p>","PeriodicalId":8896,"journal":{"name":"Biomedical Physics & Engineering Express","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2024-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142387586","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prediction of puncturing events through LSTM for multilayer tissue.","authors":"Bulbul Behera, M Felix Orlando, R S Anand","doi":"10.1088/2057-1976/ad844c","DOIUrl":"10.1088/2057-1976/ad844c","url":null,"abstract":"<p><p>Recognizing penetration events in multilayer tissue is critical for many biomedical engineering applications, including surgical procedures and medical diagnostics. This paper presents a unique method for detecting penetration events in multilayer tissue using Long Short-Term Memory (LSTM) networks. LSTM networks, a form of recurrent neural network (RNN), excel at analyzing sequential data because of their ability to hold long-term dependencies. The suggested method collects time-series insertion force data from sensors integrated from a 1-DOF prismatic robot as it penetrates tissue. This data is then processed by the LSTM network, which has been trained to recognize patterns indicating penetration events through various tissue layers. The effectiveness of this approach is validated through experimental setups, demonstrating high accuracy and reliability in detecting penetration events. This technique offers significant improvements over traditional methods, providing a non-invasive, real-time solution that enhances the precision and safety of medical procedures involving multilayer tissue interaction.</p>","PeriodicalId":8896,"journal":{"name":"Biomedical Physics & Engineering Express","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142387587","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Finite element analysis and optimization studies on tibia implant of SS 316L steel and Ti6Al4V alloy.","authors":"Ishan R Sathone, Umesh G Potdar","doi":"10.1088/2057-1976/ad8095","DOIUrl":"10.1088/2057-1976/ad8095","url":null,"abstract":"<p><p>Tibial fractures account for approximately 15% of all fractures, typically resulting from high-energy trauma. A critical surgical approach to treat these fractures involves the fixation of the tibia using a plate with minimally invasive osteosynthesis. The selection and fixation of the implant plate are vital for stabilizing the fracture. This selection is highly dependent on the plate's stability, which is influenced by factors like the stresses generated in the plate due to the load on the bone, as well as the plate's length, thickness, and number of screw holes. Minimizing these stresses is essential to reduce the risk of implant failure, ensuring optimal stress distribution and promoting faster, more effective bone healing. In the present work, the finite element and statistical approach was used to optimize the geometrical parameters of the implant plate made of SS 316L steel and Ti6Al4V alloy. A 3D finite element model was developed for analyzing the stresses and deformation, and implant plates were manufactured to validate the results with the help of an experiment conducted on the universal testing machine. A strong correlation was observed between the experimental and predicted results, with an average error of 8.6% and 8.55% for SS316L and Ti6Al4V alloy, respectively. Further, using the signal-to-noise ratio for the minimum stress condition was applied to identify the optimum parameters of the plate. Finally, regression models were developed to predict the stresses generated in SS316L and Ti6Al4V alloy plates with different input conditions. The statistical model helps us to develop the relation between different geometrical parameters of the Tibia implant plate. As determined by the present work, the parameter most influencing is implant plate length. This outcome will be used to select the implant for a specific patient, resulting in a reduction in implant failure post-surgery.</p>","PeriodicalId":8896,"journal":{"name":"Biomedical Physics & Engineering Express","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142340546","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bio-mechanical analysis of porous Ti-6Al-4V scaffold: a comprehensive review on unit cell structures in orthopaedic application.","authors":"Sachin Deshmukh, Aditya Chand, Ratnakar Ghorpade","doi":"10.1088/2057-1976/ad8202","DOIUrl":"10.1088/2057-1976/ad8202","url":null,"abstract":"<p><p>A scaffold is a three-dimensional porous structure that is used as a template to provide structural support for cell adhesion and the formation of new cells. Metallic cellular scaffolds are a good choice as a replacement for human bones in orthopaedic implants, which enhances the quality and longevity of human life. In contrast to conventional methods that produce irregular pore distributions, 3D printing, or additive manufacturing, is characterized by high precision and controlled manufacturing processes. AM processes can precisely control the scaffold's porosity, which makes it possible to produce patient specific implants and achieve regular pore distribution. This review paper explores the potential of Ti-6Al-4V scaffolds produced via the SLM method as a bone substitute. A state-of-the-art review on the effect of design parameters, material, and surface modification on biological and mechanical properties is presented. The desired features of the human tibia and femur bones are compared to bulk and porous Ti6Al4V scaffold. Furthermore, the properties of various porous scaffolds with varying unit cell structures and design parameters are compared to find out the designs that can mimic human bone properties. Porosity up to 65% and pore size of 600 μm was found to give optimum trade-off between mechanical and biological properties. Current manufacturing constraints, biocompatibility of Ti-6Al-4V material, influence of various factors on bio-mechanical properties, and complex interrelation between design parameters are discussed herein. Finally, the most appropriate combination of design parameters that offers a good trade-off between mechanical strength and cell ingrowth are summarized.</p>","PeriodicalId":8896,"journal":{"name":"Biomedical Physics & Engineering Express","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2024-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142364238","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A wearable gait-analysis device for idiopathic normal-pressure hydrocephalus (INPH) monitoring.","authors":"Erdem Atbas, Patrick Gaydecki, Michael J Callaghan","doi":"10.1088/2057-1976/ad2a1a","DOIUrl":"10.1088/2057-1976/ad2a1a","url":null,"abstract":"<p><p>Idiopathic Normal Pressure Hydrocephalus (iNPH) is a progressive neurologic disorder (fluid build-up in the brain) that affects 0.2%-5% of the UK population aged over 65. Mobility problems, dementia and urinary incontinence are symptoms of iNPH but often these are not properly evaluated, and patients receive the wrong diagnosis. Here, we describe the development and testing of firmware embedded in a wearable device in conjunction with a user-based software system that records and analyses a patient's gait. The movement patterns, expressed as quantitative data, allow clinicians to improve the non-invasive assessment of iNPH as well as monitor the management of patients undergoing treatment. The wearable sensor system comprises a miniature electronic unit that attaches to one ankle of the patient via a simple Velcro strap which was designed for this application. The unit monitors acceleration along three axes with a sample rate of 60 Hz and transmits the data via a Bluetooth communication link to a tablet or smart phone running the Android and the iOS operating systems. The software package extracts statistics based on stride length, stride height, distance walked and speed. Analysis confirmed that the system achieved an average accuracy of at least 98% for gait tests conducted over distances 9 m. This device has been developed to assist in the management and treatment of older adults diagnosed with iNPH.</p>","PeriodicalId":8896,"journal":{"name":"Biomedical Physics & Engineering Express","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2024-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139745960","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advanced artificial intelligence framework for T classification of TNM lung cancer in¹⁸FDG-PET/CT imaging.","authors":"Mariem Trabelsi, Hamida Romdhane, Lotfi Ben Salem, Dorra Ben-Sellem","doi":"10.1088/2057-1976/ad81ff","DOIUrl":"10.1088/2057-1976/ad81ff","url":null,"abstract":"<p><p>The integration of artificial intelligence (AI) into lung cancer management offers immense potential to revolutionize diagnostic and treatment strategies. The aim is to develop a resilient AI framework capable of two critical tasks: firstly, achieving accurate and automated segmentation of lung tumors and secondly, facilitating the T classification of lung cancer according to the ninth edition of TNM staging 2024 based on PET/CT imaging. This study presents a robust AI framework for the automated segmentation of lung tumors and T classification of lung cancer using PET/CT imaging. The database includes axial DICOM CT and¹⁸FDG-PET/CT images. A modified ResNet-50 model was employed for segmentation, achieving high precision and specificity. Reconstructed 3D models of segmented slices enhance tumor boundary visualization, which is essential for treatment planning. The Pulmonary Toolkit facilitated lobe segmentation, providing critical diagnostic insights. Additionally, the segmented images were used as input for the T classification using a CNN ResNet-50 model. Our classification model demonstrated excellent performance, particularly for T1a, T2a, T2b, T3 and T4 tumors, with high precision, F1 scores, and specificity. The T stage is particularly relevant in lung cancer as it determines treatment approaches (surgery, chemotherapy and radiation therapy or supportive care) and prognosis assessment. In fact, for Tis-T2, each increase of one centimeter in tumor size results in a worse prognosis. For locally advanced tumors (T3-T4) and regardless of size, the prognosis is poorer. This AI framework marks a significant advancement in the automation of lung cancer diagnosis and staging, promising improved patient outcomes.</p>","PeriodicalId":8896,"journal":{"name":"Biomedical Physics & Engineering Express","volume":"10 6","pages":""},"PeriodicalIF":1.3,"publicationDate":"2024-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142457122","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cold plasma irradiation inhibits skin cancer via ferroptosis.","authors":"Tao Sun, Changqing Liu, Ling Kong, Jingjing Zha, Guohua Ni","doi":"10.1088/2057-1976/ad8200","DOIUrl":"10.1088/2057-1976/ad8200","url":null,"abstract":"<p><p>Cold atmospheric plasma (CAP) has been extensively utilized in medical treatment, particularly in cancer therapy. However, the underlying mechanism of CAP in skin cancer treatment remains elusive. In this study, we established a skin cancer model using CAP treatment<i>in vitro</i>. Also, we established the Xenograft experiment model<i>in vivo</i>. The results demonstrated that treatment with CAP induced ferroptosis, resulting in a significant reduction in the viability, migration, and invasive capacities of A431 squamous cell carcinoma, a type of skin cancer. Mechanistically, the significant production of reactive oxygen species (ROS) by CAP induces DNA damage, which then activates Ataxia-telangiectasia mutated (ATM) and p53 through acetylation, while simultaneously suppressing the expression of Solute Carrier Family 7 Member 11 (SLC7A11). Consequently, this cascade led to the down-regulation of intracellular Glutathione peroxidase 4 (GPX4), ultimately resulting in ferroptosis. CAP exhibits a favorable impact on skin cancer treatment, suggesting its potential medical application in skin cancer therapy.</p>","PeriodicalId":8896,"journal":{"name":"Biomedical Physics & Engineering Express","volume":"10 6","pages":""},"PeriodicalIF":1.3,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142399228","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}