Medical Engineering & Physics最新文献

{"title":"Surrogate-based positioning optimization of hip prostheses for minimal stress shielding","authors":"Mahmoud Mohammadizand,&nbsp;Massoud Shariat-Panahi,&nbsp;Morad Karimpour","doi":"10.1016/j.medengphy.2024.104273","DOIUrl":"10.1016/j.medengphy.2024.104273","url":null,"abstract":"<div><div>The stress shielding phenomenon causes undesirable changes in stress distribution in the bones in which implants are implanted. This phenomenon leads to a gradual decrease in bone density in the vicinity of the implant and ultimately loosening. To improve the endurance of the prosthesis and postpone the revision surgery the prosthesis should be designed and positioned in such a way that the post-implant stress distribution within the bones is as close to the natural distribution as possible.</div><div>We formulate the problem of achieving a near-normal stress distribution as a constrained optimization problem in which the difference between pre- and post-implant stress distributions constitutes the loss function and five positional and dimensional parameters, including Femoral Anteversion, Neck Shaft Angle, Femoral Head Offset, Cup Version, and Cup Inclination comprise the set of design variables. Finite Elements (FE) analysis is used to obtain the stress distribution in bones before and after the implantation. To create a FE model, first a three-dimensional model of the patient's hip is created using CT images. The model is then subjected to the loads obtained from the patient's gait analysis, and the Stress Shielding Index (SSI) is calculated at critical points of the bones before and after the implantation. The difference between pre- and post-implant SSI values defines the cost function. To reduce the computational cost of numerous cost function evaluations a surrogate model (a 5 × 1 MLP neural network) is employed to predict the value of the cost function. Design Of Experiments (DOE) is used to sample the hyperspace of the design variables and generate training, test and validation data. The optimization problem is solved using Genetic Algorithms and the results are compared with the results of the best set of initial samples.</div><div>Results from the proposed approach show a significant reduction in the difference between pre- and post-implant stress distributions and a 12 % reduction in the Stress Shielding Index.</div></div>","PeriodicalId":49836,"journal":{"name":"Medical Engineering & Physics","volume":"135 ","pages":"Article 104273"},"PeriodicalIF":1.7,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143095990","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Classification of acute myeloid leukemia by pre-trained deep neural networks: A comparison with different activation functions","authors":"Aswathy Elma Aby ,&nbsp;S. Salaji ,&nbsp;K.K. Anilkumar ,&nbsp;Tintu Rajan","doi":"10.1016/j.medengphy.2024.104277","DOIUrl":"10.1016/j.medengphy.2024.104277","url":null,"abstract":"<div><div>Acute Myeloid Leukemia(AML) is a rapidly progressing cancer affecting blood and bone marrow, marked by the swift proliferation of abnormal myeloid cells. Effective treatment requires precise classification of AML subtypes. Conventional classification methods rely on manual microscopic analysis, which is time-consuming and variable, while traditional machine learning approaches often struggle with feature extraction and generalization. This underscores the need for automated detection methods which enhance this process by minimizing manual effort. Activation functions are critical in neural networks, introducing non-linearity that influences training convergence, computational efficiency, and model performance. This study evaluates the effectiveness of CNN architectures, Sequential (VGG16), Directed Acyclic Graph (InceptionV3), and Residual (ResNet50v2) in distinguishing between AML subtypes: AML without maturation, Acute Monoblastic Leukemia, and Pure Erythroid Leukemia, using peripheral blood smear images, while also investigating the impact of different activation functions on model accuracy and training time. The results show that ResNet50v2 achieves the shortest training time, while InceptionV3 takes the longest due to its complex architecture. GELU delivers the highest accuracy, reaching 94.02 % in InceptionV3 and 92.53 % in ResNet50v2, while SELU achieves the highest accuracy for VGG16 at 92.83 %. Mish provides competitive accuracy with lower training time than GELU, while Softplus and Softsign consistently perform poorly. This research demonstrates the potential of CNNs for automating AML subtype classification and identifies GELU as the most effective activation function. Future work could explore data augmentation, optimized activation functions, and attention mechanisms to improve classification performance.</div></div>","PeriodicalId":49836,"journal":{"name":"Medical Engineering & Physics","volume":"135 ","pages":"Article 104277"},"PeriodicalIF":1.7,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143135688","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Biomechanical evaluation for bone arthrosis morphology based on reconstructed dynamic kinesiology","authors":"Zhengxin Tu ,&nbsp;Jinghua Xu ,&nbsp;Zhenyu Dong ,&nbsp;Shuyou Zhang ,&nbsp;Jianrong Tan","doi":"10.1016/j.medengphy.2024.104278","DOIUrl":"10.1016/j.medengphy.2024.104278","url":null,"abstract":"<div><div>A biomechanical evaluation method for bone arthrosis morphology based on reconstructed dynamic kinesiology (RDK) is proposed. The hip joint is a ball-and-socket joint, morphologically characterized by an acetabulum with a nearly spherical concavity and uniform curvatures, where Gaussian curvature exhibits negative characteristic. Subsequently, RDK of bone joint morphology is developed, offering detailed anatomical and kinematic insights. The hip joint is taken as a verification instance, where a precise biomechanical evaluation of bone arthrosis morphology is simulated through finite element analysis (FEA). Latin Hypercube sampling (LHS) with the criterion of maximizing the minimum distance enhances uniformity and representation. The response surface is subsequently constructed by Kriging interpolation, significantly enhancing computational efficiency and FEA accuracy. Innovatively, a stress contour statistical histogram of load transfer is presented to quantitatively analyze the stress lines, supplying support for biomechanical evaluation, which is essential for accurate hip replacement planning. The instance indicates that the proposed RDK facilitates accurate biomechanical evaluations for bone arthrosis morphology, providing a critical theoretical foundation for conceptual design of ergonomic wearable devices, as well as optimization of replacement surgeries.</div></div>","PeriodicalId":49836,"journal":{"name":"Medical Engineering & Physics","volume":"135 ","pages":"Article 104278"},"PeriodicalIF":1.7,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143135689","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A finite element model to simulate intraoperative fractures in cementless hip stem designs","authors":"Maila Petrucci ,&nbsp;Antonino A. La Mattina ,&nbsp;Cristina Curreli ,&nbsp;Enrico Tassinari ,&nbsp;Marco Viceconti","doi":"10.1016/j.medengphy.2024.104274","DOIUrl":"10.1016/j.medengphy.2024.104274","url":null,"abstract":"<div><div>Intraoperative femur fractures are a complication of hip arthroplasty, strongly related to the cementless stem design; this kind of fracture is not always recognised during surgery, and revision surgery may be necessary. The present study aimed to simulate intraoperative crack propagation during stem implantation using subject-specific quasi-static finite element models. Eleven subject-specific finite element femur models were built starting from CT data, and the implant pose and size of a non-commercial cementless stem were identified. The model boundary conditions were set with a compressive load from 1000 N to 10 000 N, to simulate the surgeon's hammering, and element deactivation was used to model the crack propagation. Two damage quantifiers were analysed to identify a threshold value that would allow us to assess if a fracture occurred. A methodology to assess the primary stability of the stem during insertion was also proposed, based on a push-out test. Crack propagation up to the surface was obtained in six patients; in two cases there was no crack generation, while in three patients the crack did not reach the external surface. This study demonstrates the possibility to simulate the propagation of the fracture intraoperatively during hip replacement surgery and generate quantitative information about the bone damage using a virtual cohort of simulated patients with anatomical and physiological variability.</div></div>","PeriodicalId":49836,"journal":{"name":"Medical Engineering & Physics","volume":"135 ","pages":"Article 104274"},"PeriodicalIF":1.7,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143135692","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Trends and developments in 3D photoacoustic imaging systems: A review of recent progress","authors":"Fikhri Astina Tasmara ,&nbsp;Mitrayana Mitrayana ,&nbsp;Andreas Setiawan ,&nbsp;Takuro Ishii ,&nbsp;Yoshifumi Saijo ,&nbsp;Rini Widyaningrum","doi":"10.1016/j.medengphy.2024.104268","DOIUrl":"10.1016/j.medengphy.2024.104268","url":null,"abstract":"<div><div>Photoacoustic imaging (PAI) is a non-invasive diagnostic imaging technique that utilizes the photoacoustic effect by combining optical and ultrasound imaging systems. The development of PAI is mostly centered on the generation of a high-quality 3D reconstruction system for more optimal and accurate identification of tissue abnormalities. This literature study was conducted to analyze the 3D image reconstruction in PAI over 2017–2024. In this review, the collected articles in 3D photoacoustic imaging were categorized based on the approach, design, and purpose of each study. Firstly, the approaches of the studies were classified into three groups: experimental studies, numerical simulation, and numerical simulation with experimental validation. Secondly, the design of the study was assessed based on the photoacoustic modality, laser type, and sensing mechanism. Thirdly, the purpose of the collected studies was summarized into seven subsections, including image quality improvement, frame rate improvement, image segmentation, system integration, inter-systems comparisons, improving computational efficiency, and portable system development. The results of this review revealed that the 3D PAI systems have been developed by various research groups, suggesting the investigation of numerous biological objects. Therefore, 3D PAI has the potential to contribute a wide range of novel biological imaging systems that support real-time biomedical imaging in the future.</div></div>","PeriodicalId":49836,"journal":{"name":"Medical Engineering & Physics","volume":"135 ","pages":"Article 104268"},"PeriodicalIF":1.7,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143096507","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Acknowledgement to Reviewers 2024","authors":"","doi":"10.1016/S1350-4533(25)00009-8","DOIUrl":"10.1016/S1350-4533(25)00009-8","url":null,"abstract":"","PeriodicalId":49836,"journal":{"name":"Medical Engineering & Physics","volume":"135 ","pages":"Article 104290"},"PeriodicalIF":1.7,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143303225","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"2D human pose tracking in the cardiac catheterisation laboratory with BYTE","authors":"Rick M. Butler ,&nbsp;Teddy S. Vijfvinkel ,&nbsp;Emanuele Frassini ,&nbsp;Sjors van Riel ,&nbsp;Chavdar Bachvarov ,&nbsp;Jan Constandse ,&nbsp;Maarten van der Elst ,&nbsp;John J. van den Dobbelsteen ,&nbsp;Benno H.W. Hendriks","doi":"10.1016/j.medengphy.2024.104270","DOIUrl":"10.1016/j.medengphy.2024.104270","url":null,"abstract":"<div><div>Workflow insights can enable safety- and efficiency improvements in the Cardiac Catheterisation Laboratory (Cath Lab). Human pose tracklets from video footage can provide a source of workflow information. However, occlusions and visual similarity between personnel make the Cath Lab a challenging environment for the re-identification of individuals. We propose a human pose tracker that addresses these problems specifically, and test it on recordings of real coronary angiograms. This tracker uses no visual information for re-identification, and instead employs object keypoint similarity between detections and predictions from a third-order motion model. Algorithm performance is measured on Cath Lab footage using Higher-Order Tracking Accuracy (HOTA). To evaluate its stability during procedures, this is done separately for five different surgical steps of the procedure. We achieve up to 0.71 HOTA where tested state-of-the-art pose trackers score up to 0.65 on the used dataset. We observe that the pose tracker HOTA performance varies with up to 10 percentage point (pp) between workflow phases, where tested state-of-the-art trackers show differences of up to 23 pp. In addition, the tracker achieves up to 22.5 frames per second, which is 9 frames per second faster than the current state-of-the-art on our setup in the Cath Lab. The fast and consistent short-term performance of the provided algorithm makes it suitable for use in workflow analysis in the Cath Lab and opens the door to real-time use-cases. Our code is publicly available at <span><span>https://github.com/RM-8vt13r/PoseBYTE</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":49836,"journal":{"name":"Medical Engineering & Physics","volume":"135 ","pages":"Article 104270"},"PeriodicalIF":1.7,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143096508","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advances and future trends in the detection of beta-amyloid: A comprehensive review","authors":"Atri Ganguly ,&nbsp;Srivalliputtur Sarath Babu ,&nbsp;Sumanta Ghosh ,&nbsp;Ravichandiran Velyutham ,&nbsp;Govinda Kapusetti","doi":"10.1016/j.medengphy.2024.104269","DOIUrl":"10.1016/j.medengphy.2024.104269","url":null,"abstract":"<div><div>The neurodegenerative condition known as Alzheimer's disease is typified by the build-up of beta-amyloid plaques within the brain. The timely and precise identification of beta-amyloid is essential for understanding disease progression and developing effective therapeutic interventions. This comprehensive review explores the diverse landscape of beta-amyloid detection methods, ranging from traditional immunoassays to cutting-edge technologies. The review critically examines the strengths and limitations of established techniques such as ELISA, PET, and MRI, providing insights into their roles in research and clinical settings. Emerging technologies, including electrochemical methods, nanotechnology, fluorescence techniques, point-of-care devices, and machine learning integration, are thoroughly discussed, emphasizing recent breakthroughs and their potential for revolutionizing beta-amyloid detection. Furthermore, the review delves into the challenges associated with current detection methods, such as sensitivity, specificity, and accessibility. By amalgamating knowledge from multidisciplinary approaches, this review aims to guide researchers, clinicians, and policymakers in navigating the complex landscape of beta-amyloid detection, ultimately contributing to advancements in Alzheimer's disease diagnostics and therapeutics.</div></div>","PeriodicalId":49836,"journal":{"name":"Medical Engineering & Physics","volume":"135 ","pages":"Article 104269"},"PeriodicalIF":1.7,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143135685","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Denture reinforcement via topology optimization","authors":"Rabia Altunay ,&nbsp;Kalevi Vesterinen ,&nbsp;Pasi Alander ,&nbsp;Eero Immonen ,&nbsp;Andreas Rupp ,&nbsp;Lassi Roininen","doi":"10.1016/j.medengphy.2024.104272","DOIUrl":"10.1016/j.medengphy.2024.104272","url":null,"abstract":"<div><div>We present a computational design method that optimizes the reinforcement of dentures and increases the stiffness of dentures. Our approach optimally places reinforcement in the denture, which modern multi-material three-dimensional printers could implement. The study focuses on reducing denture displacement by identifying regions that require reinforcement (E-glass material) with the help of topology optimization. Our method is applied to a three-dimensional complete lower jaw denture. We compare the displacement results of a non-reinforced denture and a reinforced denture that has two materials. The comparison results indicate that there is a decrease in the displacement in the reinforced denture. Considering node-based displacement distribution, the reinforcement reduces the displacement magnitudes in the reinforced denture compared to the non-reinforced denture. The study guides dental technicians on where to automatically place reinforcement in the fabrication process, helping them save time and reduce material usage.</div></div>","PeriodicalId":49836,"journal":{"name":"Medical Engineering & Physics","volume":"135 ","pages":"Article 104272"},"PeriodicalIF":1.7,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143095986","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Thermal imaging for characterization of skin adaptation in prosthesis users","authors":"Joan E Sanders,&nbsp;Conor L Lanahan,&nbsp;Joseph C Mertens","doi":"10.1016/j.medengphy.2024.104279","DOIUrl":"10.1016/j.medengphy.2024.104279","url":null,"abstract":"<div><div>The purpose of this research was to investigate the use of time to peak temperature (TTP) as a metric for characterizing skin adaptation in prothesis users. Two experiments were conducted. A static pressure was applied to a participant's transtibial residual limb for 10 min, then a thermal imaging camera was used to capture the time-varying temperature response. The TTP, time to reach 70 % of the maximum temperature, was shorter at locations adapted to mechanical stress, the patellar tendon and anterior lateral distal region (mean 41.5 s and 47.2 s, respectively), than at mid-limb locations (127.1 s). In the second experiment, an able-bodied participant rubbed a towel across the anterior proximal aspect of his lower limb each day for 5 min per day for 11 days. His mean TTP in the region decreased from 68.5 s at Day 1 to 47.2 s at Day 11. The results suggest that a short TTP reflects skin well adapted to mechanical stress and a long TTP reflects skin not well adapted to mechanical stress. Investigations characterizing relationships between TTP and health outcomes should be pursued.</div></div>","PeriodicalId":49836,"journal":{"name":"Medical Engineering & Physics","volume":"135 ","pages":"Article 104279"},"PeriodicalIF":1.7,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143135686","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}