Biomedical Physics & Engineering Express最新文献

{"title":"ADC-MambaNet: A Lightweight U-Shaped Architecture with Mamba and Multi-Dimensional Priority Attention for Medical Image Segmentation.","authors":"Thi-Nhu-Quynh Nguyen, Quang-Huy Ho, Van Quang Nguyen, Van-Truong Pham, Thi-Thao Tran","doi":"10.1088/2057-1976/adde66","DOIUrl":"https://doi.org/10.1088/2057-1976/adde66","url":null,"abstract":"<p><strong>Objective: </strong>Medical image segmentation is becoming a growing crucial step in assisting with disease detection and diagnosis. However, medical images often exhibit complex structures and textures, resulting in the need for highly complex methods. Particularly, when Deep Learning methods are utilized, they often require large-scale pretraining, leading to significant memory demands and increased computational costs. The well-known Convolutional Neural Networks (CNNs) have become the backbone of medical image segmentation tasks thanks to their effective feature extraction abilities. However, they often struggle to capture global context due to the limited sizes of their kernels. To address this, various Transformer-based models have been introduced to learn long-range dependencies through self-attention mechanisms. However, these architectures typically incur relatively high computational complexity.&#xD;Methods: To address the aforementioned challenges, we propose a lightweight and computationally efficient model named ADC-MambaNet, which combines the conventional Depthwise Convolutional layers with the Mamba algorithm that can address the computational complexity of Transformers. In the proposed model, a new feature extractor named Harmonious Mamba-Convolution (HMC) block, and the Multi-Dimensional Priority Attention (MDPA) block have been designed. These blocks enhance the feature extraction process, thereby improving the overall performance of the model. In particular, the mechanisms enable the model to effectively capture local and global patterns from the feature maps while keeping the computational costs low. A novel loss function called the Balanced Normalized Cross Entropy is also introduced, bringing promising performance compared to other losses.</p><p><strong>Results: </strong>Evaluations on five public medical image datasets: ISIC 2018 Lesion Segmentation, PH2, Data Science Bowl 2018, GlaS, and Lung X-ray demonstrate that ADC-MambaNet achieves higher evaluation scores while maintaining compact parameters and low computational complexity.&#xD;Conclusion: ADC-MambaNet offers a promising solution for accurate and efficient medical image segmentation, especially in resource-limited or edge-computing environments. Implementation code will be publicly accessible at: https://github.com/nqnguyen812/mambaseg-model.</p>","PeriodicalId":8896,"journal":{"name":"Biomedical Physics & Engineering Express","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2025-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144180684","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":"Quality Assurance of Beam Base Data in Modern Radiotherapy: A Monte Carlo Simulation Approach.","authors":"Matthias Kowatsch, Eva Partoll, Thomas Kunzler, Christian Attenberger, Philipp Szeverinski, Patrick Clemens, Peter Tschann","doi":"10.1088/2057-1976/adde64","DOIUrl":"https://doi.org/10.1088/2057-1976/adde64","url":null,"abstract":"<p><p>Accurate dose computation in radiotherapy is critical due to the complexity of modern treatment modalities. Beam base data (BBD) underpin the precision of dose calculations in techniques such as Volumetric Modulated Arc Therapy (VMAT), Intensity-Modulated Radiation Therapy (IMRT), Stereotactic Radiosurgery (SRS), and Stereotactic Body Radiation Therapy (SBRT). Even minor discrepancies in BBD can compromise the accuracy of dose computations, necessitating quality assurance (QA). This study investigates the application of Monte Carlo (MC) simulations, considered the \"gold standard\" in dose calculations, for BBD QA using SciMoCa. SciMoCa is a Monte Carlo dose engine which shares its concepts with the VMC family of codes. &#xD;A total of 87 BBD sets, from 39 datasets, representing diverse linacs, were analyzed, provided by the vendor of the MC-system. Systematic errors (e.g., dose, point dose, spectrum, output errors) were categorized into error classes: severe (Type 1), moderate (Type 2), minor (Type 3). Measurements were conducted using ionization chambers and diodes, and results were compared to MC simulations.&#xD;The virtual source model was tested against measurements as a proof of concept, showing an overall deviation of less than 1%, with output factors differing by less than 0.3%.&#xD;The analysis of the 87 BBD sets presented that 86% of BBD sets passed the criterions of Type 1 errors, 60% for Type 2 and 28% for Type 3 criteria. In absolute terms, 24 of the 87 BBD sets met the minimum criteria and would not compromise dose calculation in TPS.&#xD;The study highlights the potential of MC simulations in establishing a standardized approach to BBD QA. This approach allows for robust validation of BBD quality and self-consistency, achieving typical precision within ±0.5%. In more challenging cases, the precision may expand to ±1.0%.</p>","PeriodicalId":8896,"journal":{"name":"Biomedical Physics & Engineering Express","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2025-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144179798","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":"κ-Carrageenan and Hyaluronic acid Composite Injectable Hydrogel-Containing Isosorbide mononitrate-loaded Liposomes for Treatment of Myocardial Infarction.","authors":"Yinjian Hua, Jun Zeng, Sai He, Yuzhe Zhang, Longtai Wang, Linrong Xiao, Guohua Jiang","doi":"10.1088/2057-1976/adde67","DOIUrl":"https://doi.org/10.1088/2057-1976/adde67","url":null,"abstract":"<p><p>In this study, isosorbide mononitrate (ISMN)-loaded liposomes (ISMN-LNPs) were encapsulated within an injectable composite hydrogel that consisted of κ-Carrageenan (κ-Car), hyaluronic acid (HA), and tannic acid (TA). The fabricated composite hydrogel exhibited exceptional reactive oxygen species (ROS) scavenging capabilities to enhance cell migration. Upon injection of the ISMN-LNP-loaded composite hydrogel into the injured hearts of rats, significant improvements in cardiac function could be observed after treatment. Furthermore, Masson's staining results revealed that the injectable hydrogel system reduced myocardial infarct size and increased left ventricular wall thickness post-myocardial infarction. Immunofluorescence staining results indicated the upregulating expression of vascular hemophilic factor (VWF) and α-actinin, suggesting that the injectable hydrogel system to promote vascular proliferation and enhance cardiac systolic and diastolic function following myocardial infarction.</p>","PeriodicalId":8896,"journal":{"name":"Biomedical Physics & Engineering Express","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2025-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144179508","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":"Cone beam computed tomography in 6- and 60-second acquisitions: implications for adaptive radiotherapy when respiratory motion is present.","authors":"Patricia A K Oliver, Logan Montgomery, Dal Alexander Granville","doi":"10.1088/2057-1976/adde65","DOIUrl":"https://doi.org/10.1088/2057-1976/adde65","url":null,"abstract":"<p><strong>Purpose: </strong>To investigate the effects of respiratory motion during fast (~6 s) and slow (~60 s) cone beam computed tomography (CBCT) acquisition modes, with a focus on implications for adaptive radiotherapy (ART).&#xD;&#xD;Methods: CBCT images are compared with 4D fan beam CT acquisitions, considering average (\"AVE\") and maximum (\"MIP\") intensity projections. Data are acquired using a respiratory motion phantom representing a human thorax with a lung tumour. A range of sup-inf motion amplitudes (3 to 11 mm) and periods (3 to 5 s) are considered. HU perturbations, target contouring implications, and dosimetric effects are considered.&#xD;&#xD;Results: Fast mode CBCT motion artefacts are more severe for larger amplitudes and longer periods. Motion artefacts are minimal in slow mode. The standard deviation of HU differences (CBCT minus AVE) in regions-of-interest encompassing the tumour are within 44 HU for slow mode, increasing up to 75 HU for fast mode. Target volumes contoured using HU thresholding on slow mode CBCTs are smaller than those on the AVE/MIP by up to 7%/29%. HU thresholding was not applied to fast mode CBCTs because motion artefacts were judged to be too severe. Gamma pass rates for dose distributions calculated on fast or slow mode CBCTs compared to the AVE are ≥ 99% (criteria: 1%, 1 mm, 10% dose threshold). Dose differences (fast mode CBCT minus AVE) are larger for larger amplitudes and longer periods, and tend toward negative values. Dose differences (slow mode CBCT minus AVE) are generally smaller and more consistent across all amplitudes and periods considered.&#xD;&#xD;Conclusions: Dosimetric perturbations resulting from motion artefacts are not severe for the amplitudes and periods considered. However, motion artefacts (especially in fast mode) have implications for image registration, target contouring, and treatment plan optimization for ART. &#xD.</p>","PeriodicalId":8896,"journal":{"name":"Biomedical Physics & Engineering Express","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2025-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144180164","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":"DCA-U-Net: a deep learning network for segmentation of laser-induced thermal damage regions in mouse skin OCT images.","authors":"Chenliang Xu, Qiong Ma, Jingyuan Wu, Yu Wei, Qi Liu, Qingyu Cai, Haiyang Sun, Xiaoan Tang, Hongxiang Kang","doi":"10.1088/2057-1976/adcd7c","DOIUrl":"10.1088/2057-1976/adcd7c","url":null,"abstract":"<p><p>Laser-induced thermal injury is a common form of skin damage in clinical treatment, and accurately assessing the extent of injury and treatment efficacy is crucial for patient recovery. In recent years, deep learning models have been increasingly applied to the automatic segmentation of skin injury regions. However, existing methods often suffer from a large number of parameters, leading to a significant decline in segmentation accuracy when reducing the number of model parameters, thus limiting their clinical applicability. To address this issue, we propose an efficient and lightweight segmentation model, Dilated ConvNeXT Attention U-Net (DCA-U-Net), based on U-Net. By incorporating the more efficient Dilated ConvNeXT Block (DCB) and Dual Module Attention Block (DMAB), DCA-U-Net significantly reduces the number of parameters while simultaneously improving feature extraction capability and segmentation accuracy. Compared to the standard U-Net, our model reduces the number of parameters by 33%. Experimental results on two different sections of mouse skin laser thermal damage Optical Coherence Tomography (OCT) datasets show that our model has better segmentation performance with insufficient or sufficient amount of data. These improvements not only enhance the model's ability to accurately identify skin thermal injury regions, but also substantially reduce computational costs while maintaining high segmentation accuracy, offering promising technical support for the precise diagnosis and treatment of skin laser thermal injuries.</p>","PeriodicalId":8896,"journal":{"name":"Biomedical Physics & Engineering Express","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2025-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143976890","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":"Comparative evaluation of intraoral stent materials: dosimetric response analysis.","authors":"Gabriela Corati Touguinha, Alberto E Gonzales-Ccoscco, Leonardo Pessoa da Silva, Henrique Trombini, Heitor Ribeiro Birnfeld, Luzia Fernandes Millão, Romulo Rocha Santos, José Fernando Marquez Pachas, Oliver Paucar, Carmen Calcina, Mirko Salomón Alva-Sánchez","doi":"10.1088/2057-1976/add6ac","DOIUrl":"10.1088/2057-1976/add6ac","url":null,"abstract":"<p><p><i>Purpose</i>. To evaluate and compare the dosimetric properties of various materials used in intraoral stents, with a particular focus on their interaction with a 6 MV photon beam in head and neck cancer radiotherapy.<i>Materials and Methods</i>. Experimental irradiation and computational simulation methods were employed to analyze the interaction of various materials with a 6 MV photon beam used in an intraoral procedure. A head phantom, cylindrical in shape and divided into 1 cm plates, was used along with circular PMMA plates and polystyrene to simulate an intraoral procedure. Radiochromic film (EBT3) was used to evaluate the dose-response of PMMA and PET-G materials with thicknesses of 1, 2, and 3 mm, irradiated under a 10 × 10 cm²field size at a 100 cm source-to-skin distance (SSD). The PENELOPE code was used to simulate the dosimetric properties of PMMA, PET-G, EVA, PDMS, and PVDF based on their chemical compositions.<i>Results</i>. A maximum divergence of 4.2% was observed between PET-G and PMMA at a thickness of 3 mm during the experimental procedure. Additionally, a maximum difference of 1.2% was noted when comparing the simulated percentage depth dose curves. Discrepancies of up to 10% were found between experimental irradiation and simulations in polystyrene regions, likely due to the sensitivity of the film to incident fluence. When comparing the simulated materials (PMMA, PET-G, EVA, PDMS, and PVDF), the largest divergence observed was 20% at the surface of the phantom and did not exceed 15% at depths under 10 cm, specifically between PVDF and PMMA. For all other materials, the divergence remained below 10% across all regions.<i>Conclusions</i>. The results suggest that all the materials evaluated for intraoral stent fabrication can be effectively analyzed using the simulation code. PET-G, EVA, and PDMS showed dose-response variations of less than 10%, which should be considered when calculating doses in the treatment system planning, as stents made from these materials may increase the dose to nearby organs.</p>","PeriodicalId":8896,"journal":{"name":"Biomedical Physics & Engineering Express","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2025-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144061321","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":"Recovering the central axis from the crossline dose profiles in Elekta Unity MR-Linac.","authors":"Vivien W S Chu, Louis K Y Lee","doi":"10.1088/2057-1976/adddc4","DOIUrl":"https://doi.org/10.1088/2057-1976/adddc4","url":null,"abstract":"<p><p>This study quantifies the lateral shifts of the crossline dose profiles from the central axis (CAX) under the influence of the 1.5 T magnetic field of an Elekta Unity MR-linac using two parameters: the midpoint between the 50% value of the dose profile (Mid-D50%) and the midpoint between the inflection points (Mid-IP). The dependence of the shifts of Mid-D50% and Mid-IP on depth, source-to-surface distance, and field size was studied through simulations in Elekta's Monaco treatment planning system. Coefficients for the linear fit of the shifts are presented to enable the determination of the position of the CAX from either Mid-D50% or Mid-IP. Our results show that not only is the deviation of Mid-IP from the CAX smaller than that of Mid-D50%, but it is also less dependent on depth and field size. The ability to recover the CAX from the asymmetric dose profiles enables the measurement of the radiation isocenter size of the MR-linac using a star-shot test. The radii of the isocenters determined using the CAX recovered from either Mid-D50% or Mid-IP are both consistent with the expected result of the machine, demonstrating the accuracy of the recovered CAX and offering an alternative approach for conducting the star-shot test on the Unity MR-linac.</p>","PeriodicalId":8896,"journal":{"name":"Biomedical Physics & Engineering Express","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2025-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144172503","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":"An enhanced microstate clustering algorithm based on canopy, K-means, and genetic simulated annealing.","authors":"Jingting Liang, Xiangguo Yin, Mingxing Lin","doi":"10.1088/2057-1976/adda50","DOIUrl":"10.1088/2057-1976/adda50","url":null,"abstract":"<p><p><i>Background</i>. Electroencephalogram (EEG) microstate analysis can capture transient patterns of brain activity and provide valuable insights into brain motor and cognitive functions. However, the performance of traditional microstate analysis algorithms limits a deeper understanding of the neural mechanisms behind complex conditions.<i>Methods</i>. This study proposed a Canopy-KM-GSA algorithm, which combines Canopy clustering algorithm, K-means algorithm and genetic simulated annealing framework to automatically determine the optimal number of microstates and refine the clustering sequence. Utilizing the proposed algorithm, the study performed microstate analysis of pedaling motor datasets, Passive Auditory Oddball Paradigm task datasets, and epileptic patients datasets. The performance of the proposed algorithm is compared with seven baseline algorithms (including traditional K-means algorithm, K-medoids algorithm, ICA algorithm, PCA algorithm, GMD driven density canopy K-means algorithm, modified K-means algorithm and Agglomerative Hierarchical Clustering(AAHC) algorithm).<i>Results</i>. The results demonstrated the superior performance of Canopy-KM-GSA, achieving a significantly higher total evaluation compared to baseline microstate analysis algorithms. With an average Global Explained Variance (GEV) of 94.43%, an average Calinski-Harabasz Index (CHI) of 537.99, and an average Davies-Bouldin Index (DBI) of 1.57 in pedaling motor datasets; an average GEV of 94.46%, an average CHI of 389.29, and an average DBI of 1.44 in Passive Auditory Oddball Paradigm task datasets; an average GEV of 58.40%, an average CHI of 254.11, and an average DBI of 1.53 in epileptic patients datasets.<i>Conclusions</i>. The novel microstate analysis algorithms offers a more accurate tool for EEG microstate analysis.</p>","PeriodicalId":8896,"journal":{"name":"Biomedical Physics & Engineering Express","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2025-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144101245","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":"Rational design of alternative natural-based coupling media for diagnostic ultrasound imaging: a review.","authors":"Dennis Nimoh, Isaac Acquah, Elizabeth Wordui","doi":"10.1088/2057-1976/add7e2","DOIUrl":"10.1088/2057-1976/add7e2","url":null,"abstract":"<p><p>Ultrasound imaging is an indispensable diagnostic and screening tool in healthcare, renowned for its non-invasive nature, real-time visualization, and use of non-ionizing radiation. It plays a vital role in obstetrics and gynaecology by significantly reducing maternal mortality and enhancing patient care. In addition to its use in obstetrics, ultrasound is used to guide biopsies and to evaluate various diseases such as liver cirrhosis, thyroid disorders, and kidney stones. Point-of-care ultrasonography has proven to be increasingly beneficial in low-resource settings. However, the availability and cost of commercial ultrasound gels pose significant challenges. Alternative natural-based gels formulated from locally sourced materials have emerged as viable substitutes. This review critically examines alternative natural-based ultrasound gels, focusing on their physicochemical properties, formulation procedures, and the limitations associated with their use in diagnostic imaging. Furthermore, it presents a rational design approach that methodically selects the ingredients based on their properties and interactions to formulate these gels for imaging applications. This offers a promising pathway for indigenous manufacturers to develop gels that meet ideal performance criteria, ensuring better imaging outcomes and wider acceptability in clinical practice.</p>","PeriodicalId":8896,"journal":{"name":"Biomedical Physics & Engineering Express","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144061923","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":"Fast dual-energy micro-CT with reliable detection of iodine in thin vessels.","authors":"Ian Buchanan, Michela Esposito, Alberto Astolfo, Thomas Partridge, Grammatiki Lioliou, Marco Endrizzi, David Bate, Charlotte Klara Hagen, Alessandro Olivo","doi":"10.1088/2057-1976/addd26","DOIUrl":"https://doi.org/10.1088/2057-1976/addd26","url":null,"abstract":"<p><p>X-ray micro-computed tomography (µCT) is a widely used imaging modality in preclinical research, with a range of specific applications. Minimising the dose both from X-rays and of administered contrast agents such as iodine is desirable for the improvement of research and subject outcomes. Here, we introduce a new data processing scheme that enables accurate localisation and quantification of iodine concentrations resulting from fast, low dose µCT scans. The technique makes use of characteristic shape detection to selectively decompose dual-energy X-ray µCT data in iodine-containing regions only, thus removing any background iodine signal in the decomposed basis. We demonstrate the technique's effectiveness using scan data acquired over 3.6 seconds and a dose to water of 8.7 mGy where the weakest concentration of iodine successfully isolated was 21 mgI/ml in a 500 µm diameter vessel, and note that this scan speed could be further improved with a detector with a faster framerate. The technique is extended to complex vessel shapes in three dimensions and remains robust. It is expected to be useful in the context of small animal imaging as the low dose requirements increase the repeatability of scans per subject.</p>","PeriodicalId":8896,"journal":{"name":"Biomedical Physics & Engineering Express","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144156162","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}