Physical and Engineering Sciences in Medicine最新文献

{"title":"Integrated wearable PPG: a multi-vital sign monitoring based on group sparse mode decomposition framework in remote health care using PPG signal.","authors":"Pankaj, Pratibha Maan, Manjeet Kumar, Ashish Kumar, Rama Komaragiri","doi":"10.1007/s13246-025-01534-0","DOIUrl":"https://doi.org/10.1007/s13246-025-01534-0","url":null,"abstract":"<p><p>Monitoring vital signs using a photoplethysmogram (PPG) signal has gained considerable attention, allowing users to monitor anyone, anywhere, and anytime with an objective. In recent years, advances in wearable technology and signal processing techniques have paved the way for accurate and reliable vital sign monitoring using PPG signals. Early detection of cardiovascular diseases can help the physician treat the disease promptly; thus, realtime monitoring of vital signs has emerged. Any deviation in the threshold value of vital signs can indicate potential threats to the cardiovascular system. The need to monitor vital signs in realtime using wearable devices has attracted the interest of the healthcare industry in developing simple and efficient vital sign estimation algorithms. This research introduces a framework to estimate the following important vital signs: heart rate (HR), respiratory rate (RR), blood pressure (BP), and blood oxygen saturation (SpO2), concurrently by overcoming the limitations posed by state-of-the-art techniques that primarily focus on individual or two vital sign estimations. Our proposed approach leverages signal processing techniques to determine the above-mentioned vital signs seamlessly and accurately. This innovation enhances the efficiency of vital sign monitoring and presents a unified solution for comprehensive health assessment. The widespread use of wearable devices for monitoring realtime health status in everyday life manifests in using PPG sensor-enabled wearable devices to perform more complex computational tasks. To date, the algorithms proposed to process an input PPG signal often use multiple processing steps to estimate any vital signs. This can increase the computational complexity of these algorithms, making it challenging to deploy devices with limited computational resources. The proposed work introduces a computationally efficient framework to estimate all four vital signs using the signal framework. The experimental results obtained with the proposed framework demonstrate that the proposed work outperforms the state-of-the-art estimation accuracy and computational complexity.</p>","PeriodicalId":48490,"journal":{"name":"Physical and Engineering Sciences in Medicine","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143796689","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":"The next chapter.","authors":"Clive Baldock","doi":"10.1007/s13246-025-01536-y","DOIUrl":"https://doi.org/10.1007/s13246-025-01536-y","url":null,"abstract":"","PeriodicalId":48490,"journal":{"name":"Physical and Engineering Sciences in Medicine","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143755172","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":"Artificial intelligence and its potential integration with the clinical practice of diagnostic imaging medical physicists: a review.","authors":"Ngo Fung Daniel Lam, Jing Cai, Kwan Hoong Ng","doi":"10.1007/s13246-025-01535-z","DOIUrl":"https://doi.org/10.1007/s13246-025-01535-z","url":null,"abstract":"<p><p>Current clinical practice in imaging medical physics is concerned with quality assurance, image processing and analysis, radiation dosimetry, risk assessment and radiation protection, and in-house training and research. Physicist workloads are projected to increase as medical imaging technologies become more sophisticated. Artificial intelligence (AI) is a rising technology with potential to assist medical physicists in their work. Exploration of AI integration into imaging medical physicist workloads is limited. In this review paper, we provide an overview of AI techniques, outline their potential usage in imaging medical physics, and discuss the limitations and challenges to clinical adoption of AI technologies.</p>","PeriodicalId":48490,"journal":{"name":"Physical and Engineering Sciences in Medicine","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143701862","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":"AOCMP-SEACOMP 2024 : 10-13 October 2024, Penang, Malaysia.","authors":"","doi":"10.1007/s13246-024-01502-0","DOIUrl":"https://doi.org/10.1007/s13246-024-01502-0","url":null,"abstract":"","PeriodicalId":48490,"journal":{"name":"Physical and Engineering Sciences in Medicine","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143701861","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":"Analysis of material composition and attenuation characteristics of anthropomorphic torso phantoms for dosimetry using dual energy CT technology.","authors":"Koji Ono, Yasuki Asada","doi":"10.1007/s13246-025-01533-1","DOIUrl":"https://doi.org/10.1007/s13246-025-01533-1","url":null,"abstract":"<p><p>Anthropomorphic phantoms are often used to estimate organ absorbed doses. However, the material composition of these phantoms is not identical to that of the human body, which may cause errors in the measurement results. The purpose of this study was to analyze the material composition of several anthropomorphic torso phantoms using dual energy computed tomography (DECT), and to clarify the differences in attenuation characteristics among the phantoms. Anthropomorphic torso phantoms (ATOM, RANDO, and PBU-60) from different manufacturers were scanned with DECT. The target organs were lung, soft tissue, liver, bone, and bone surface, and a spectral Hounsfield unit curve (HU curve) was created from the relationship between energy and CT values. Ideal CT values were estimated from the mass attenuation coefficient and density proposed by the International Commission on Radiation Units and Measurements report 44 (ideal value) and compared with the values of each phantom. There were large differences in attenuation characteristics among the phantoms for soft tissue, liver, and bone. The respective ideal, ATOM, RANDO, and PBU-60 CT values of soft tissue were 59.82, 14.17, 34.22, and - 70.11 at 45 keV; and 53.13, 24.41, 3.97, and - 5.75 at 70 keV. The phantom closest to the ideal value may differ depending on the energy. Differences in HU curve and CT values indicate that some organs in the phantom have different material composition and attenuation characteristics to human tissues. When the phantoms available for dosimetry are limited, it is important to understand the attenuation characteristics of each phantom used.</p>","PeriodicalId":48490,"journal":{"name":"Physical and Engineering Sciences in Medicine","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143659198","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":"Characteristics of the electron beam outside the applicator in an Elekta Versa HD Linac.","authors":"Kapil Dev Maharaj, Simon Goodall, Mahsheed Sabet, Joshua Dass, Mounir Ibrahim, Talat Mahmood, Pejman Rowshanfarzad","doi":"10.1007/s13246-025-01530-4","DOIUrl":"https://doi.org/10.1007/s13246-025-01530-4","url":null,"abstract":"<p><p>Radiotherapy is an essential component of cancer treatment, but healthy tissues can be exposed to out-of-field doses, potentially causing adverse effects and secondary cancers. This study investigates peripheral doses outside the electron beam applicator in an Elekta Versa HD linear accelerator. Peripheral doses outside an electron applicator were measured using 6, 9, and 12 MeV beams at their respective maximum dose depths while maintaining a 100 cm source-to-surface distance. Measurements employed EBT3 films within Plastic Water DT phantoms. The influence of field size on penumbra width and peripheral doses were examined using various cutouts (6 × 6 cm², 10 × 10 cm², and a 5 cm diameter circle) within a 10 × 10 cm² applicator, with gantry and collimator angles set to 0 degrees. Additionally, the impact of collimator angles on penumbra width and peripheral doses was explored, enhancing the understanding of dose distribution. Measured profiles were also compared with those calculated using Monaco treatment planning system. Findings showed that both penumbra width and peripheral dose values increased with energy across different field sizes and collimator angles. Root Mean Square Deviation (RMSD) analysis indicated deviations of 1.8 mm for penumbra and 1.1% for peripheral doses between measured profiles and Treatment Planning System (TPS) predictions for all field sizes. Peripheral doses remained below 5% of the maximum dose at distances ranging from 10 to 15 mm away from the field edges, indicating acceptable tolerance levels (ICRU report 24). However, further dose reduction may be possible with additional shielding to keep doses as low as reasonably achievable. This study highlights the critical importance of considering peripheral doses in radiotherapy, emphasizing the need to evaluate the impact on healthy tissues outside the primary treatment area to ensure patient safety and mitigate long-term treatment-related side effects. The findings underscore the necessity of implementing appropriate measures to minimize peripheral doses.</p>","PeriodicalId":48490,"journal":{"name":"Physical and Engineering Sciences in Medicine","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143659202","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":"Investigation of the tissue equivalence of typical 3D-printing materials for application in internal dosimetry using monte carlo simulations.","authors":"Ayse Karadeniz-Yildirim, Handan Tanyildizi-Kokkulunk","doi":"10.1007/s13246-025-01532-2","DOIUrl":"https://doi.org/10.1007/s13246-025-01532-2","url":null,"abstract":"<p><p>This study evaluates the dosimetric accuracy of PLA and ABS 3D-printed phantoms compared to real tissues using Monte Carlo simulations in radionuclide therapy.</p><p><strong>Materials and methods: </strong>A phantom representing average liver and lung volumes, with a 10 mm tumor mimic in the liver, was simulated for radioembolization using 1 mCi Tc-99 m and 1 mCi Y-90. The dose distribution (DD) was compared across PLA, ABS, and real organ densities.</p><p><strong>Results: </strong>For Tc-99 m, PLA showed a + 5.6% DD difference in the liver, and ABS showed - 35.3% and - 40.9% differences in the lungs. For Y-90, PLA had a + 1.7% DD difference in the liver, while ABS showed - 34.2% and - 34.9% differences in the lungs.</p><p><strong>Conclusion: </strong>In MC simulation, PLA is suitable for representing high-density tissues, while ABS is appropriate for simulating moderately low-density tissues.</p>","PeriodicalId":48490,"journal":{"name":"Physical and Engineering Sciences in Medicine","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143626064","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":"Fully automated template matching method for ECG-free heartbeat detection in cardiomechanical signals of healthy and pathological subjects.","authors":"Salvatore Parlato, Jessica Centracchio, Daniele Esposito, Paolo Bifulco, Emilio Andreozzi","doi":"10.1007/s13246-025-01531-3","DOIUrl":"https://doi.org/10.1007/s13246-025-01531-3","url":null,"abstract":"<p><p>Cardiomechanical monitoring techniques record cardiac vibrations on the chest via lightweight electrodeless sensors that allow long-term patient monitoring. Heartbeat detection in cardiomechanical signals is generally achieved by leveraging a simultaneous electrocardiography (ECG) signal to provide a reliable heartbeats localization, which however strongly limits long-term monitoring. A heartbeats localization method based on template matching has demonstrated very high performance in several cardiomechanical signals, with no need for a concurrent ECG recording. However, the reproducibility of that method was limited by the need for manual selection of a heartbeat template from the cardiomechanical signal by a skilled operator. To overcome that limitation, this study presents a fully automated version of the template matching method for ECG-free heartbeat detection, powered by a novel automatic template selection algorithm. The novel method was validated on 256 Seismocardiography (SCG), Gyrocardiography (GCG), and Forcecardiography (FCG) signals, from 150 healthy and pathological subjects. Comparison with all existing methods for ECG-free heartbeat detection was carried out. The method scored sensitivity and positive predictive value (PPV) of 97.8% and 98.6% for SCG, 96.3% and 94.5% for GCG, 99.2% and 99.3% for FCG, on healthy subjects, and of 85% and 95% for both SCG and GCG on pathological subjects. Statistical analyses on inter-beat intervals reported almost unit slopes (R² > 0.998) and limits of agreement within ± 6 ms for healthy subjects and ± 13 ms for pathological subjects. The proposed automated method surpasses all previous ECG-free approaches in heartbeat localization accuracy and was validated on the largest cohort of pathological subjects and the highest number of heartbeats. The method proposed in this study represents the current state of the art for ECG-free monitoring of cardiac activity via cardiomechanical signals, ensuring accurate, reproducible, operator-independent heartbeats localization. MATLAB^® code is released as an off-the-shelf tool to support a more widespread and practical use of cardiomechanical monitoring in both clinical and non-clinical settings.</p>","PeriodicalId":48490,"journal":{"name":"Physical and Engineering Sciences in Medicine","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143626043","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":"EPSM 2024, Engineering and Physical Sciences in Medicine : 17-20 November 2024, Melbourne, Australia.","authors":"","doi":"10.1007/s13246-024-01511-z","DOIUrl":"https://doi.org/10.1007/s13246-024-01511-z","url":null,"abstract":"","PeriodicalId":48490,"journal":{"name":"Physical and Engineering Sciences in Medicine","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143617659","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":"How much data do you need? An analysis of pelvic multi-organ segmentation in a limited data context.","authors":"Febrio Lunardo, Laura Baker, Alex Tan, John Baines, Timothy Squire, Jason A Dowling, Mostafa Rahimi Azghadi, Ashley G Gillman","doi":"10.1007/s13246-024-01514-w","DOIUrl":"https://doi.org/10.1007/s13246-024-01514-w","url":null,"abstract":"<p><p>Training deep learning models generally requires large, costly datasets which can limit their application towards in-house segmentation tasks. This study investigates the trade-off in dataset size within the context of pelvic multi-organ MR segmentation where we evaluate the performance of nnU-Net, a well-known segmentation model, under conditions of limited domain and data availability. 12 participants undergoing treatment on an Elekta Unity were recruited, acquiring 58 MR images, with 4 participants (12 images) withheld for testing. Prostate, seminal vesicles (SV), bladder and rectum were contoured in each image by a radiation oncologist. Seven models were trained on progressively smaller subsets of the training dataset, simulating a limited dataset setting. To investigate the efficacy of data augmentation, another set of identical models were trained without augmentation. The performance of the networks was evaluated via the Dice Similarity Coefficient, mean surface distance, and 95% Hausdorff distance metrics. When trained with entire training dataset (46 images), the model achieved a mean Dice coefficient of 0.903 (Prostate), 0.851 (SV), 0.884 (Rectum) and 0.967 (Bladder). Segmentation performance remained stable when the number of training sets was > 12 images from 4 participants, but rapidly dropped in smaller data subsets. Data augmentation was found to be influential across all dataset sizes, but especially in very small datasets. This study demonstrated nnU-Net's proficiency in performing male pelvic multi-organ segmentation under a limited domain, a single scanner, and under limited data constraints. We found that the performance degradation was often modest until a threshold is reached (12 images), below which it dropped significantly. Data augmentation improved performance across all data sizes, but especially for very small datasets. We conclude that nnU-Net's low data requirement can be advantageous for in-house cases with consistent protocol and scarce data availability.</p>","PeriodicalId":48490,"journal":{"name":"Physical and Engineering Sciences in Medicine","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143606662","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}