Biomedical Physics & Engineering Express最新文献

{"title":"Should breast/thoracic wall and lymph node volumes have the same margin in hypofractionated radiotherapy?","authors":"Marianne Falk, Mattias Hedman, Mimmi-Caroline Bolin, Jens Falk, Kristin Karlsson, Eva Onjukka, Bruno Sorcini, Giovanna Gagliardi","doi":"10.1088/2057-1976/ae9ffb","DOIUrl":"10.1088/2057-1976/ae9ffb","url":null,"abstract":"<p><p><i>Purpose.</i>The aim of this study was to investigate if the same planning target volume margins should be used for the breast/thoracic wall and lymph nodes when treated simultaneously with hypofractionated radiotherapy in deep inspiration breath-hold (DIBH) and free breathing (FB).<i>Methods.</i>For 80 patients (40 treated in FB and 40 in DIBH), nine anatomy sites were evaluated. Three were located in relation to the lymph node region and six in relation to the breast/thoracic wall. For three treatment fractions, a cone beam CT was acquired before and after the treatment and compared to the planning CT. Margins were calculated based on the inter- and intra-fractional uncertainties, ensuring 90% of the patients receiving 95% of the prescribed dose to the clinical target volume. Margin calculation was done for the full patient data set as well as for a subgroup of patients with set-up errors below the clinical action level, excluding patients with set-up errors larger than 7 mm.<i>Results.</i>For the full patient data set, margins of up to 14 mm were calculated. However, for patients with set-up errors below the clinical action level, the largest margins calculated for the lymph node region for treatments in DIBH were 8.5 mm, 8.7 mm and 6.6 mm in the vertical, longitudinal, and lateral directions respectively compared to 8.4 mm, 7.9 mm and 5.9 mm for treatments in FB. For the breast/thoracic wall, the largest margins were 5.9 mm, 6.4 mm and 5.5 mm for treatments in DIBH and 5.8 mm, 7.2 mm and 5.8 mm for treatments in FB in the vertical, longitudinal and lateral directions respectively.<i>Conclusion.</i>Treatments in DIBH and FB can use the same margins. However, the lymph node region requires a larger margin than the breast/thoracic wall region, due to greater anatomical mobility.</p>","PeriodicalId":8896,"journal":{"name":"Biomedical Physics & Engineering Express","volume":" ","pages":""},"PeriodicalIF":2.0,"publicationDate":"2026-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148849715","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":"Discrepancy between collapsed cone and Monte Carlo algorithms in lung inhomogeneity correction.","authors":"Amir Hossein Karimi, Indra J Das, Saeedeh Moharramkhani, Hossein Mirzaei, Marco Esposito, Ghazale Geraily","doi":"10.1088/2057-1976/aea1f9","DOIUrl":"10.1088/2057-1976/aea1f9","url":null,"abstract":"<p><p>Stereotactic body radiation therapy (SBRT) is a well-established standard of treatment for non-small cell lung cancer patients. However, SBRT is a double-edged sword and a high degree of accuracy is required for dose calculations. In the presence of inhomogeneity, it should be below 3% and depends strongly on the accuracy of the algorithm used for dose calculation in treatment planning system (TPS). The aim of this study is to evaluate the accuracy of collapsed cone (CC) algorithm for dose calculation in the presence of lung inhomogeneity compared to the Monte Carlo (MC) algorithm as the reference. The study conducted on a wide range of photon fields from 0.5 × 0.5 cm²to 10 × 10 cm². Monaco® TPS equipped with CC and MC algorithms in 6 MV, 10 MV, and 18 MV photons was employed and the inhomogeneity correction factor and PPDs were calculated inside an in-house inhomogeneous phantom. Finally, the results were compared between two algorithms. For 6 MV photons, gamma index pass rate (GIPR) with (2 mm, 3%) criteria in a 0.5 × 0.5 cm²field is only 71.3%. The CC algorithm will not be able to confidently reproduce the PDDs in this field. For 1 × 1 cm², 2 × 2 cm², and 3 × 3 cm²fields, the accuracy of the CC algorithm can increase to above 98%. For SBRT of small lung lesions, the results recommend increasing the minimum segment width to >0.5 cm in IMRT plans if CC algorithm is used. Independent of field size, the accuracy of CC algorithm decreases with increasing energy. For 10 and 18 MV photons, average GIPR under (2 mm, 3%) criteria was 97.9% and 92.0%, respectively, which are not of clinical interest.</p>","PeriodicalId":8896,"journal":{"name":"Biomedical Physics & Engineering Express","volume":" ","pages":""},"PeriodicalIF":2.0,"publicationDate":"2026-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148886182","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":"CORRIGENDUM: Retrieving of the melanosome fraction of human epidermis<i>in vivo</i>from skin chromatic coordinates (2026<i>Biomed. Phys. Eng. Express</i> 12 025078).","authors":"Freddy Narea-Jiménez, Alexis Vázquez-Villa, Cesar Arriaga-Arriaga, Alina Santillan-Guzmán, Anthony D Cho","doi":"10.1088/2057-1976/aea29c","DOIUrl":"10.1088/2057-1976/aea29c","url":null,"abstract":"","PeriodicalId":8896,"journal":{"name":"Biomedical Physics & Engineering Express","volume":"12 5","pages":""},"PeriodicalIF":2.0,"publicationDate":"2026-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148944212","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":"Path-length-aware sinogram completion via direct moment enforcement for metal artifact reduction in X-ray CT.","authors":"Jong Hyun Seo, Sungwhan Kim","doi":"10.1088/2057-1976/aea1f8","DOIUrl":"10.1088/2057-1976/aea1f8","url":null,"abstract":"<p><p>High-density metallic objects often produce missing or severely corrupted projection data, resulting in strong streak artifacts in x-ray computed tomography (CT) images. In this paper, we propose a path-length-aware sinogram completion framework that combines interpolation in the mean attenuation domain with direct enforcement of low-order Helgason-Ludwig consistency conditions. The missing projections are first estimated using a Hermite-type interpolation that explicitly accounts for x-ray path length. Moment consistency is then restored through a probabilistic perturbation scheme based on compactly supported probability density functions, avoiding the need for solving a large-scale constrained optimization problem. Numerical experiments using both a simulated phantom and a dental CT model demonstrate that the proposed method generally achieves improved sinogram consistency and better image quality than linear interpolation-based metal artifact reduction (LI-MAR), normalized MAR (NMAR), and the TV-based iterative MAR method (TV-MAR), while preserving important anatomical structures. The proposed framework provides an efficient and physically motivated approach for MAR in x-ray CT.</p>","PeriodicalId":8896,"journal":{"name":"Biomedical Physics & Engineering Express","volume":" ","pages":""},"PeriodicalIF":2.0,"publicationDate":"2026-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148886270","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 the physical and radiological properties of different Fricke gel formulations as water-equivalent materials and biological tissues.","authors":"Ângela M M Santos, Lucas F Araújo, Luíza R Costa, Natália R S Araújo, Rita C O Sebastião, Lucas Paixão, Ester M R Andrade, Bruno M Mendes, Amir Z Mesquita, Telma C F Fonseca","doi":"10.1088/2057-1976/ae9e3b","DOIUrl":"10.1088/2057-1976/ae9e3b","url":null,"abstract":"<p><p>Fricke gel dosimeters, also known as hydrogels, have emerged as attractive tools in clinical dosimetry due to the stringent requirements of quality assurance protocols and radiation protection programs. The performance of these materials strongly depends on the characteristics of the polymeric matrices that constitute them. Their ability to mimic reference materials, such as water and biological tissue, has been widely investigated for applications as simulators in radiotherapy procedures. This study aims to evaluate the physical and radiological properties of Fricke gel formulations prepared with different polymeric matrices: porcine skin gelatin (GEL), sodium carboxymethylcellulose (CMC), guar gum (GGU), and poly(vinyl alcohol) (PVA). Key-parameters, including the linear and mass attenuation coefficients (and), the mass energy-absorption (), the electronic stopping power (Stp_e), and the effective atomic number (), were determined using both experimental and computational methods. The physical investigations included the evaluation of thermal decomposition, determined by thermogravimetric analysis and kinetic analysis, incorporating isoconversional models based on multilayer perceptron (MLP) neural networks. The results obtained experimentally and through computational tools such as Phy-X, XCOM, TOPAS, EGSnrc, and ESTAR, for the different Fricke gel formulations, revealed that all gel formulations exhibit radiological parameters comparable to those of reference materials (water and biological tissue), in accordance with ICRU Report 44. Thermal analysis revealed distinct stability characteristics among the Fricke gel compositions. The GGU and PVA formulations exhibited greater thermal resistance compared with the GEL and CMC compositions. Kinetic analysis indicated that the average activation energy values for all formulations were below 40 kJ mol, suggesting that the thermal degradation processes initiate at relatively low temperatures. The application of MLP mathematical method proved valuable for accurately modeling the observed thermal kinetics. This study demonstrates that Fricke gel formulations (GEL, CMC, GGU, and PVA) effectively mimic the radiological response of biological tissue and water. Their performance in the field of radiotherapy is relevant for applications in three-dimensional dosimetry and radiological simulations due to their tissue-equivalent properties.</p>","PeriodicalId":8896,"journal":{"name":"Biomedical Physics & Engineering Express","volume":" ","pages":""},"PeriodicalIF":2.0,"publicationDate":"2026-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148816966","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":"Bayesian neural networks for uncertainty-aware tissue identification using bioimpedance-based frequency response similarity metrics.","authors":"Jacob Search, Sabino Zani, Brian P Mann","doi":"10.1088/2057-1976/aea167","DOIUrl":"10.1088/2057-1976/aea167","url":null,"abstract":"<p><p>This work sought to improve bioimpedance-based tissue identification model performance on an eight-tissue dataset by employing frequency response function similarity metrics (FRFSMs) as feature generators and Bayesian neural networks (BNNs) for accurate uncertainty estimations. Inspired by structural dynamics, FRFSMs were applied in a new context to generate features from mean baseline measurements, thereby extracting information of how unclassified measurements compare to previous ones. Additionally, BNNs were constructed to directly estimate model parameter uncertainty effects on classification uncertainty. Finally, a stacking ensemble technique combined base model outputs to train a meta-learner for improving performance. Models trained with similarity metric features achieved higher mean accuracies and better tissue specific1-scores than those trained with measurements. BNNs with temperature scaling reduced the expected calibration error of the standard feedforward networks by 19%-83%, indicating significant enhancement of uncertainty quantification. Ensembles achieved higher mean accuracies than base models, with maximum accuracies over 75%, and maintained the enhanced uncertainty quantification. The implementation of similarity metric inputs and BNNs for bioimpedance-based tissue identification offered a clear improvement in mean accuracy and uncertainty quantification over traditional models using measurements only. This marks an essential step towards enabling bioimpedance as a feasible sensing option for real-time tissue identification. Attaining dependable bioimpedance-based tissue identification will provide a foundation for new technologies due to economical and implementation advantages over competing methods while the added uncertainty-awareness makes it an excellent candidate for medical applications because it can provide additional context for outputs to users.</p>","PeriodicalId":8896,"journal":{"name":"Biomedical Physics & Engineering Express","volume":" ","pages":""},"PeriodicalIF":2.0,"publicationDate":"2026-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148879079","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":"Cross-layer semantic alignment and context enhancement network for medical image segmentation.","authors":"Bing Liu, Xinxin Sun, Geyi Zhan","doi":"10.1088/2057-1976/aea1f7","DOIUrl":"10.1088/2057-1976/aea1f7","url":null,"abstract":"<p><p>Medical image segmentation aims to accurately delineate organs, tissues, or lesion regions from complex medical images. However, existing hybrid models based on Transformers and convolutional neural networks still suffer from limitations in local detail modeling and cross-layer feature fusion, which often leads to blurred boundary information and loss of structural details. To address these issues, this paper proposes a Cross-layer Semantic Alignment and Context Enhancement Network for medical image segmentation. Specifically, a semantic enhancement module is introduced into the skip connections to achieve effective fusion of high-level semantic information and shallow spatial details through spatial-channel collaborative modeling and multi-scale context extraction (MCE). In addition, a lightweight boundary refinement mechanism is employed in the decoder stage to improve the recovery capability for complex boundary regions. Experiments conducted on the Synapse, ACDC, and GlaS datasets demonstrate that the proposed method outperforms mainstream approaches in terms of Dice, HD95, and Intersection over Union metrics, validating the effectiveness of the cross-layer semantic alignment mechanism for complex medical image segmentation tasks.</p>","PeriodicalId":8896,"journal":{"name":"Biomedical Physics & Engineering Express","volume":" ","pages":""},"PeriodicalIF":2.0,"publicationDate":"2026-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148879109","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":"Dual-energy cone-beam CT improves iodine contrast and Hounsfield unit value stability in the maxillofacial region: a phantom study.","authors":"Dinidu Jayakody, Veli-Pekka Riekki, Michaela K Bode, Mikael A K Brix","doi":"10.1088/2057-1976/ae9cc2","DOIUrl":"10.1088/2057-1976/ae9cc2","url":null,"abstract":"<p><p>This study was designed to assess the feasibility of dual-energy cone-beam computed tomography (DE-CBCT) and the associated image processing algorithms to improve delayed phase iodine enhancement. An anthropomorphic adult head phantom with iodine inserts in maxillofacial regions was imaged using a clinical CBCT and a helical CT scanner. DE-CBCT was acquired sequentially at 80 and 120 kV, and helical CT at 100 kV (routine clinical protocol), with radiation doses matched within 5%. Virtual monochromatic images (VMIs) at 50 and 200 keV were generated with (VMI+) and without (VMI) noise-optimized frequency splitting algorithm. Evaluation included Hounsfield Unit (HU) agreement with helical CT, iodine contrast, contrast-to-noise ratio (CNR), artifact reduction, and subjective radiologist assessment of target visibility. VMI50 and VMI50+ demonstrated the strongest HU agreement with CT. VMI50+ produced significantly better contrast than CBCT in the maxillary sinus region (mean percentage change 40.7% (15.3%-66.1%);<i>p</i>< 0.05), while improvements were minor in the mandibular region (9.7% (3.0%-16.5%);<i>p</i>< 0.05). VMI50+ significantly increased CNR in the maxillary sinus compared with CBCT (3.3 vs 2.8;<i>p</i>< 0.05), with no significant difference in the mandibular region. Although DE-CBCT increased contrast and reduced artifacts, it did not reveal any additional targets compared with routine CBCT. DE-CBCT with VMI and frequency splitting improves HU agreement with CT, slightly improves soft tissue visualization, and reduces artifacts in head and neck phantom imaging.</p>","PeriodicalId":8896,"journal":{"name":"Biomedical Physics & Engineering Express","volume":" ","pages":""},"PeriodicalIF":2.0,"publicationDate":"2026-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148787921","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 geometric nonlinear return mapping framework for automated term-preterm delivery classification: a comparative analysis of TOCO and EHG signals.","authors":"Sahar Ghorbanzadeh, Mohammad Karimi Moridani","doi":"10.1088/2057-1976/ae9ecb","DOIUrl":"10.1088/2057-1976/ae9ecb","url":null,"abstract":"<p><p><i>Objective.</i>Preterm delivery remains the leading cause of neonatal mortality worldwide. Early detection and accurate prediction of women at risk are critical for improving maternal and neonatal outcomes. This study aimed to diagnose preterm delivery using uterine contraction signals, providing a non-invasive approach to assist in clinical decision-making.<i>Method.</i>Electrohysterography (EHG) and tocodynamometry (TOCO) signals were recorded from a dataset of 300 samples, including both term and preterm deliveries. Linear and nonlinear signal processing techniques were employed to extract a wide range of features across time, frequency, and nonlinear domains. Features derived from return mapping and other methods were utilized as inputs to a multi-layer perceptron (MLP) classifier for distinguishing between term and preterm deliveries.<i>Result.</i>The proposed method achieved exceptional classification performance, with an accuracy of 95.18 ± 1.21%, sensitivity of 93.84 ± 1.76%, and specificity of 95.61 ± 1.09%. These results demonstrate the method's robustness and reliability. Comparative analysis with recent research highlighted the superior performance of the proposed approach.<i>Conclusion.</i>The findings underscore the potential of a computer-aided diagnostic system for preterm delivery detection using EHG and TOCO signals. This method provides a non-invasive, efficient, and accurate tool that could significantly reduce unnecessary hospitalizations and mitigate risks for high-risk pregnancies. By enabling timely intervention, the proposed approach holds promise for improving maternal and neonatal healthcare outcomes.</p>","PeriodicalId":8896,"journal":{"name":"Biomedical Physics & Engineering Express","volume":" ","pages":""},"PeriodicalIF":2.0,"publicationDate":"2026-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148824629","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":"Investigation of drilling and necrosis zone performance of split point drills in surgical cortical bone drilling.","authors":"Pınar Kızılışık, Levent Uğur, Kutay Aydın, Emre Çalışal","doi":"10.1088/2057-1976/ae9eca","DOIUrl":"10.1088/2057-1976/ae9eca","url":null,"abstract":"<p><p>The surgical bone drilling process is unavoidable in orthopedic, traumatological and dental applications for screw, plate and implant placement procedures. The mechanical and thermal effects generated during this process have a direct impact on both surgical success and post-operative recovery. The high axial forces, torque, and local temperature increases that occur during drilling can lead to serious clinical complications such as microcrack formation, thermal necrosis, implant loosening, and delayed bone healing. Therefore, optimizing the cutting tool geometry in bone drilling processes is one of the important focal points of current research. In this study, cortical bone drilling processes performed using split point drills with different geometric parameters and standard drills were investigated. The drilling force, torque, and thermal necrosis formation during drilling were simulated using the finite element method (FEM), and the obtained data were modeled using artificial neural networks (ANNs). A high level of compatibility was achieved between the ANN model and the FEM results, with training and test correlation coefficients and mean error rates calculated as 0.99998, 0.995 02 and 1.84%, respectively. The results showed that split point drills provided significantly lower drilling forces compared to standard drills. The combination of optimum design parameters, namely a 115-degree splitting angle, 0.25 mm split point web thickness, and 7-degree gashing rake angle, resulted in a 46.8% lower drilling force, 4.6% lower torque, and 5.2% lower thermal necrosis compared to the standard drill. These findings demonstrate that split point drill geometry offers significant advantages in surgical bone drilling applications.</p>","PeriodicalId":8896,"journal":{"name":"Biomedical Physics & Engineering Express","volume":" ","pages":""},"PeriodicalIF":2.0,"publicationDate":"2026-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148824631","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}