Physical and Engineering Sciences in Medicine最新文献_第10页

Inter-fractional portability of deep learning models for lung target tracking on cine imaging acquired in MRI-guided radiotherapy. 深度学习模型在核磁共振成像引导放疗中获取的 cine 成像上进行肺部目标跟踪的分段间可移植性。

IF 4.4 4区医学

Physical and Engineering Sciences in Medicine Pub Date : 2024-06-01 Epub Date: 2024-01-10 DOI: 10.1007/s13246-023-01371-z

Jiayuan Peng, Hayley B Stowe, Pamela P Samson, Clifford G Robinson, Cui Yang, Weigang Hu, Zhen Zhang, Taeho Kim, Geoffrey D Hugo, Thomas R Mazur, Bin Cai

{"title":"Inter-fractional portability of deep learning models for lung target tracking on cine imaging acquired in MRI-guided radiotherapy.","authors":"Jiayuan Peng, Hayley B Stowe, Pamela P Samson, Clifford G Robinson, Cui Yang, Weigang Hu, Zhen Zhang, Taeho Kim, Geoffrey D Hugo, Thomas R Mazur, Bin Cai","doi":"10.1007/s13246-023-01371-z","DOIUrl":"10.1007/s13246-023-01371-z","url":null,"abstract":"MRI-guided radiotherapy systems enable beam gating by tracking the target on planar, two-dimensional cine images acquired during treatment. This study aims to evaluate how deep-learning (DL) models for target tracking that are trained on data from one fraction can be translated to subsequent fractions. Cine images were acquired for six patients treated on an MRI-guided radiotherapy platform (MRIdian, Viewray Inc.) with an onboard 0.35 T MRI scanner. Three DL models (U-net, attention U-net and nested U-net) for target tracking were trained using two training strategies: (1) uniform training using data obtained only from the first fraction with testing performed on data from subsequent fractions and (2) adaptive training in which training was updated each fraction by adding 20 samples from the current fraction with testing performed on the remaining images from that fraction. Tracking performance was compared between algorithms, models and training strategies by evaluating the Dice similarity coefficient (DSC) and 95% Hausdorff Distance (HD95) between automatically generated and manually specified contours. The mean DSC for all six patients in comparing manual contours and contours generated by the onboard algorithm (OBT) were 0.68 ± 0.16. Compared to OBT, the DSC values improved 17.0 - 19.3% for the three DL models with uniform training, and 24.7 - 25.7% for the models based on adaptive training. The HD95 values improved 50.6 - 54.5% for the models based on adaptive training. DL-based techniques achieved better tracking performance than the onboard, registration-based tracking approach. DL-based tracking performance improved when implementing an adaptive strategy that augments training data fraction-by-fraction.","PeriodicalId":48490,"journal":{"name":"Physical and Engineering Sciences in Medicine","volume":" ","pages":"769-777"},"PeriodicalIF":4.4,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139404833","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}

引用次数: 0

Evaluation of the effect of sagging correction calibration errors in radiotherapy software on image matching. 评估放射治疗软件中的下垂校正校准误差对图像匹配的影响。

IF 4.4 4区医学

Physical and Engineering Sciences in Medicine Pub Date : 2024-06-01 Epub Date: 2024-02-19 DOI: 10.1007/s13246-024-01388-y

Yumi Yamazawa, Akitane Osaka, Yasushi Fujii, Takahiro Nakayama, Kunio Nishioka, Yoshinori Tanabe

{"title":"Evaluation of the effect of sagging correction calibration errors in radiotherapy software on image matching.","authors":"Yumi Yamazawa, Akitane Osaka, Yasushi Fujii, Takahiro Nakayama, Kunio Nishioka, Yoshinori Tanabe","doi":"10.1007/s13246-024-01388-y","DOIUrl":"10.1007/s13246-024-01388-y","url":null,"abstract":"To investigate the impact of sagging correction calibration errors in radiotherapy software on image matching. Three software applications were used, with and without a polymethyl methacrylate rod supporting the ball bearings (BB). The calibration error for sagging correction across nine flex maps (FMs) was determined by shifting the BB positions along the Left-Right (LR), Gun-Target (GT), and Up-Down (UD) directions from the reference point. Lucy and pelvic phantom cone-beam computed tomography (CBCT) images underwent auto-matching after modifying each FM. Image deformation was assessed in orthogonal CBCT planes, and the correlations among BB shift magnitude, deformation vector value, and differences in auto-matching were analyzed. The average difference in analysis results among the three softwares for the Winston-Lutz test was within 0.1 mm. The determination coefficients (R2) between the BB shift amount and Lucy phantom matching error in each FM were 0.99, 0.99, and 1.00 in the LR-, GT-, and UD-directions, respectively. The pelvis phantom demonstrated no cross-correlation in the GT direction during auto-matching error evaluation using each FM. The correlation coefficient (r) between the BB shift and the deformation vector value was 0.95 on average for all image planes. Slight differences were observed among software in the evaluation of the Winston-Lutz test. The sagging correction calibration error in the radiotherapy imaging system was caused by an auto-matching error of the phantom and deformation of CBCT images.","PeriodicalId":48490,"journal":{"name":"Physical and Engineering Sciences in Medicine","volume":" ","pages":"589-596"},"PeriodicalIF":4.4,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11166816/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139900659","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}

引用次数: 0

Nanodosimetric quantity-weighted dose optimization for carbon-ion treatment planning. 用于碳离子治疗规划的纳米计量加权剂量优化。

IF 4.4 4区医学

Physical and Engineering Sciences in Medicine Pub Date : 2024-06-01 Epub Date: 2024-02-28 DOI: 10.1007/s13246-024-01399-9

Jingfen Yang, Xinguo Liu, Hui Zhang, Zhongying Dai, Pengbo He, Yuanyuan Ma, Guosheng Shen, Weiqiang Chen, Qiang Li

{"title":"Nanodosimetric quantity-weighted dose optimization for carbon-ion treatment planning.","authors":"Jingfen Yang, Xinguo Liu, Hui Zhang, Zhongying Dai, Pengbo He, Yuanyuan Ma, Guosheng Shen, Weiqiang Chen, Qiang Li","doi":"10.1007/s13246-024-01399-9","DOIUrl":"10.1007/s13246-024-01399-9","url":null,"abstract":"Dose verification of treatment plans is an essential step in radiotherapy workflows. In this work, we propose a novel method of treatment planning based on nanodosimetric quantity-weighted dose (NQWD), which could realize biological representation using pure physical quantities for biological-oriented carbon ion-beam treatment plans and their direct verification. The relationship between nanodosimetric quantities and relative biological effectiveness (RBE) was studied with the linear least-squares method for carbon-ion radiation fields. Next, under the framework of the matRad treatment planning platform, NQWD was optimized using the existing RBE-weighted dose (RWD) optimization algorithm. The schemes of NQWD-based treatment planning were compared with the RWD treatment plans in term of the microdosimetric kinetic model (MKM). The results showed that the nanodosimetric quantity F3 - 10 had a good correlation with the radiobiological effect reflected by the relationship between RBE and F3 - 10. Moreover, the NQWD-based treatment plans reproduced the RWD plans generally. Therefore, F3 - 10 could be adopted as a radiation quality descriptor for carbon-ion treatment planning. The novel method proposed herein not only might be helpful for rapid physical verification of biological-oriented ion-beam treatment plans with the development of experimental nanodosimetry, but also makes the direct comparison of ion-beam treatment plans in different institutions possible. Thus, our proposed method might be potentially developed to be a new strategy for carbon-ion treatment planning and improve patient safety for carbon-ion radiotherapy.","PeriodicalId":48490,"journal":{"name":"Physical and Engineering Sciences in Medicine","volume":" ","pages":"703-715"},"PeriodicalIF":4.4,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139984172","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}

引用次数: 0

Pattern classification of interstitial lung diseases from computed tomography images using a ResNet-based network with a split-transform-merge strategy and split attention. 利用基于 ResNet 的网络，采用分裂-变换-合并策略和分裂注意力，对计算机断层扫描图像中的肺间质疾病进行模式分类。

IF 4.4 4区医学

Physical and Engineering Sciences in Medicine Pub Date : 2024-06-01 Epub Date: 2024-03-04 DOI: 10.1007/s13246-024-01404-1

Jian-Xun Chen, Yu-Cheng Shen, Shin-Lei Peng, Yi-Wen Chen, Hsin-Yuan Fang, Joung-Liang Lan, Cheng-Ting Shih

{"title":"Pattern classification of interstitial lung diseases from computed tomography images using a ResNet-based network with a split-transform-merge strategy and split attention.","authors":"Jian-Xun Chen, Yu-Cheng Shen, Shin-Lei Peng, Yi-Wen Chen, Hsin-Yuan Fang, Joung-Liang Lan, Cheng-Ting Shih","doi":"10.1007/s13246-024-01404-1","DOIUrl":"10.1007/s13246-024-01404-1","url":null,"abstract":"In patients with interstitial lung disease (ILD), accurate pattern assessment from their computed tomography (CT) images could help track lung abnormalities and evaluate treatment efficacy. Based on excellent image classification performance, convolutional neural networks (CNNs) have been massively investigated for classifying and labeling pathological patterns in the CT images of ILD patients. However, previous studies rarely considered the three-dimensional (3D) structure of the pathological patterns of ILD and used two-dimensional network input. In addition, ResNet-based networks such as SE-ResNet and ResNeXt with high classification performance have not been used for pattern classification of ILD. This study proposed a SE-ResNeXt-SA-18 for classifying pathological patterns of ILD. The SE-ResNeXt-SA-18 integrated the multipath design of the ResNeXt and the feature weighting of the squeeze-and-excitation network with split attention. The classification performance of the SE-ResNeXt-SA-18 was compared with the ResNet-18 and SE-ResNeXt-18. The influence of the input patch size on classification performance was also evaluated. Results show that the classification accuracy was increased with the increase of the patch size. With a 32 × 32 × 16 input, the SE-ResNeXt-SA-18 presented the highest performance with average accuracy, sensitivity, and specificity of 0.991, 0.979, and 0.994. High-weight regions in the class activation maps of the SE-ResNeXt-SA-18 also matched the specific pattern features. In comparison, the performance of the SE-ResNeXt-SA-18 is superior to the previously reported CNNs in classifying the ILD patterns. We concluded that the SE-ResNeXt-SA-18 could help track or monitor the progress of ILD through accuracy pattern classification.","PeriodicalId":48490,"journal":{"name":"Physical and Engineering Sciences in Medicine","volume":" ","pages":"755-767"},"PeriodicalIF":4.4,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140023058","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}

引用次数: 0

Comparison of skin dose in IMRT and VMAT with TrueBeam and Halcyon linear accelerator for whole breast irradiation. 使用 TrueBeam 和 Halcyon 直线加速器进行全乳腺照射时，IMRT 和 VMAT 皮肤剂量的比较。

IF 4.4 4区医学

Physical and Engineering Sciences in Medicine Pub Date : 2024-06-01 Epub Date: 2024-01-15 DOI: 10.1007/s13246-023-01373-x

Jae Hyun Seok, So Hyun Ahn, Woo Sang Ahn, Dong Hyeok Choi, Seong Soo Shin, Wonsik Choi, In-Hye Jung, Rena Lee, Jin Sung Kim

{"title":"Comparison of skin dose in IMRT and VMAT with TrueBeam and Halcyon linear accelerator for whole breast irradiation.","authors":"Jae Hyun Seok, So Hyun Ahn, Woo Sang Ahn, Dong Hyeok Choi, Seong Soo Shin, Wonsik Choi, In-Hye Jung, Rena Lee, Jin Sung Kim","doi":"10.1007/s13246-023-01373-x","DOIUrl":"10.1007/s13246-023-01373-x","url":null,"abstract":"With the increasing use of flattening filter free (FFF) beams, it is important to evaluate the impact on the skin dose and target coverage of breast cancer treatments. This study aimed to compare skin doses of treatments using FFF and flattening filter (FF) beams for breast cancer. The study established treatment plans for left breast of an anthropomorphic phantom using Halcyon's 6-MV FFF beam and TrueBeam's 6-MV FF beam. Volumetric modulated arc therapy (VMAT) with varying numbers of arcs and intensity modulated radiation therapy (IMRT) were employed, and skin doses were measured at five points using Gafchromic EBT3 film. Each measurement was repeated three times, and averaged to reduce uncertainty. All plans were compared in terms of plan quality to ensure homogeneous target coverage. The study found that when using VMAT with two, four, and six arcs, in-field doses were 19%, 15%, and 6% higher, respectively, when using Halcyon compared to TrueBeam. Additionally, when using two arcs for VMAT, in-field doses were 10% and 15% higher compared to four and six arcs when using Halcyon. Finally, in-field dose from Halcyon using IMRT was about 1% higher than when using TrueBeam. Our research confirmed that when treating breast cancer with FFF beams, skin dose is higher than with traditional FF beams. Moreover, number of arcs used in VMAT treatment with FFF beams affects skin dose to the patient. To maintain a skin dose similar to that of FF beams when using Halcyon, it may be worth considering increasing the number of arcs.","PeriodicalId":48490,"journal":{"name":"Physical and Engineering Sciences in Medicine","volume":" ","pages":"443-451"},"PeriodicalIF":4.4,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11166860/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139467140","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}

引用次数: 0

Brain identification of IBS patients based on GBDT and multiple imaging techniques. 基于 GBDT 和多种成像技术识别肠易激综合征患者的大脑。

IF 4.4 4区医学

Physical and Engineering Sciences in Medicine Pub Date : 2024-06-01 Epub Date: 2024-02-28 DOI: 10.1007/s13246-024-01394-0

Li Han, Qian Xu, Panting Meng, Ruyun Xu, Jiaofen Nan

{"title":"Brain identification of IBS patients based on GBDT and multiple imaging techniques.","authors":"Li Han, Qian Xu, Panting Meng, Ruyun Xu, Jiaofen Nan","doi":"10.1007/s13246-024-01394-0","DOIUrl":"10.1007/s13246-024-01394-0","url":null,"abstract":"The brain biomarker of irritable bowel syndrome (IBS) patients is still lacking. The study aims to explore a new technology studying the brain alterations of IBS patients based on multi-source brain data. In the study, a decision-level fusion method based on gradient boosting decision tree (GBDT) was proposed. Next, 100 healthy subjects were used to validate the effectiveness of the method. Finally, the identification of brain alterations and the pain evaluation in IBS patients were carried out by the fusion method based on the resting-state fMRI and DWI for 46 patients and 46 controls selected randomly from 100 healthy subjects. The results showed that the method can achieve good classification between IBS patients and controls (accuracy = 95%) and pain evaluation of IBS patients (mean absolute error = 0.1977). Moreover, both the gain-based and the permutation-based evaluation instead of statistical analysis showed that left cingulum bundle contributed most significantly to the classification, and right precuneus contributed most significantly to the evaluation of abdominal pain intensity in the IBS patients. The differences seem to suggest a probable but unexplored separation about the central regions between the identification and progression of IBS. This finding may provide one new thought and technology for brain alteration related to IBS.","PeriodicalId":48490,"journal":{"name":"Physical and Engineering Sciences in Medicine","volume":" ","pages":"651-662"},"PeriodicalIF":4.4,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139984161","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}

引用次数: 0

A Q-transform-based deep learning model for the classification of atrial fibrillation types. 基于 Q 变换的心房颤动类型分类深度学习模型。

IF 4.4 4区医学

Physical and Engineering Sciences in Medicine Pub Date : 2024-06-01 Epub Date: 2024-02-14 DOI: 10.1007/s13246-024-01391-3

B Dhananjay, R Pradeep Kumar, Bala Chakravarthy Neelapu, Kunal Pal, J Sivaraman

{"title":"A Q-transform-based deep learning model for the classification of atrial fibrillation types.","authors":"B Dhananjay, R Pradeep Kumar, Bala Chakravarthy Neelapu, Kunal Pal, J Sivaraman","doi":"10.1007/s13246-024-01391-3","DOIUrl":"10.1007/s13246-024-01391-3","url":null,"abstract":"According to the World Health Organization (WHO), Atrial Fibrillation (AF) is emerging as a global epidemic, which has resulted in a need for techniques to accurately diagnose AF and its various subtypes. While the classification of cardiac arrhythmias with AF is common, distinguishing between AF subtypes is not. Accurate classification of AF subtypes is important for making better clinical decisions and for timely management of the disease. AI techniques are increasingly being considered for image classification and detection in various ailments, as they have shown promising results in improving diagnosis and treatment outcomes. This paper reports the development of a custom 2D Convolutional Neural Network (CNN) model with six layers to automatically differentiate Non-Atrial Fibrillation (Non-AF) rhythm from Paroxysmal Atrial Fibrillation (PAF) and Persistent Atrial Fibrillation (PsAF) rhythms from ECG images. ECG signals were obtained from a publicly available database and segmented into 10-second segments. Applying Constant Q-Transform (CQT) to the segmented ECG signals created a time-frequency depiction, yielding 98,966 images for Non-AF, 16,497 images for PAF, and 52,861 images for PsAF. Due to class imbalance in the PAF and PsAF classes, data augmentation techniques were utilized to increase the number of PAF and PsAF images to match the count of Non-AF images. The training, validation, and testing ratios were 0.7, 0.15, and 0.15, respectively. The training set consisted of 207,828 images, whereas the testing and validation set consisted of 44,538 images and 44,532 images, respectively. The proposed model achieved accuracy, precision, sensitivity, specificity, and F1 score values of 0.98, 0.98, 0.98, 0.97, and 0.98, respectively. This model has the potential to assist physicians in selecting personalized AF treatment and reducing misdiagnosis.","PeriodicalId":48490,"journal":{"name":"Physical and Engineering Sciences in Medicine","volume":" ","pages":"621-631"},"PeriodicalIF":4.4,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139730785","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}

引用次数: 0

The effects of distance between the imaging isocenter and brain center on the image quality of cone-beam computed tomography for brain stereotactic irradiation. 成像等中心和脑中心之间的距离对用于脑立体定向照射的锥形束计算机断层扫描图像质量的影响。

IF 4.4 4区医学

Physical and Engineering Sciences in Medicine Pub Date : 2024-06-01 Epub Date: 2024-02-14 DOI: 10.1007/s13246-024-01389-x

Sayaka Kihara, Shingo Ohira, Naoyuki Kanayama, Toshiki Ikawa, Yoshihiro Ueda, Shoki Inui, Hikari Minami, Tomohiro Sagawa, Masayoshi Miyazaki, Masahiko Koizumi, Koji Konishi

{"title":"The effects of distance between the imaging isocenter and brain center on the image quality of cone-beam computed tomography for brain stereotactic irradiation.","authors":"Sayaka Kihara, Shingo Ohira, Naoyuki Kanayama, Toshiki Ikawa, Yoshihiro Ueda, Shoki Inui, Hikari Minami, Tomohiro Sagawa, Masayoshi Miyazaki, Masahiko Koizumi, Koji Konishi","doi":"10.1007/s13246-024-01389-x","DOIUrl":"10.1007/s13246-024-01389-x","url":null,"abstract":"In linear accelerator-based stereotactic irradiation (STI) for brain metastasis, cone-beam computed tomography (CBCT) image quality is essential for ensuring precise patient setup and tumor localization. However, CBCT images may be degraded by the deviation of the CBCT isocenter from the brain center. This study aims to investigate the effects of the distance from the brain center to the CBCT isocenter (DBI) on the image quality in STI. An anthropomorphic phantom was scanned with varying DBI in right, anterior, superior, and inferior directions. Thirty patients undergoing STI were prospectively recruited. Objective metrics, utilizing regions of interest included contrast-to-noise ratio (CNR) at the centrum semiovale, lateral ventricle, and basal ganglia levels, gray and white matter noise at the basal ganglia level, artifact index (AI), and nonuniformity (NU). Two radiation oncologists assessed subjective metrics. In this phantom study, objective measures indicated a degradation in image quality for non-zero DBI. In this patient study, there were significant correlations between the CNR at the centrum semiovale and lateral ventricle levels (rs = - 0.79 and - 0.77, respectively), gray matter noise (rs = 0.52), AI (rs = 0.72), and NU (rs = 0.91) and DBI. However, no significant correlations were observed between the CNR at the basal ganglia level, white matter noise, and subjective metrics and DBI (rs < ± 0.3). Our results demonstrate the effects of DBI on contrast, noise, artifacts in the posterior fossa, and uniformity of CBCT images in STI. Aligning the CBCT isocenter with the brain center can aid in improving image quality.","PeriodicalId":48490,"journal":{"name":"Physical and Engineering Sciences in Medicine","volume":" ","pages":"597-609"},"PeriodicalIF":4.4,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139730786","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}

引用次数: 0

Additive manufacturing of patient specific bolus for radiotherapy: large scale production and quality assurance. 用于放射治疗的患者专用栓剂的增材制造：大规模生产和质量保证。

IF 4.4 4区医学

Physical and Engineering Sciences in Medicine Pub Date : 2024-06-01 Epub Date: 2024-01-29 DOI: 10.1007/s13246-024-01385-1

Deepak Basaula, Barry Hay, Mark Wright, Lisa Hall, Alan Easdon, Peter McWiggan, Adam Yeo, Elena Ungureanu, Tomas Kron

{"title":"Additive manufacturing of patient specific bolus for radiotherapy: large scale production and quality assurance.","authors":"Deepak Basaula, Barry Hay, Mark Wright, Lisa Hall, Alan Easdon, Peter McWiggan, Adam Yeo, Elena Ungureanu, Tomas Kron","doi":"10.1007/s13246-024-01385-1","DOIUrl":"10.1007/s13246-024-01385-1","url":null,"abstract":"Bolus is commonly used to improve dose distributions in radiotherapy in particular if dose to skin must be optimised such as in breast or head and neck cancer. We are documenting four years of experience with 3D printed bolus at a large cancer centre. In addition to this we review the quality assurance (QA) program developed to support it. More than 2000 boluses were produced between Nov 2018 and Feb 2023 using fused deposition modelling (FDM) printing with polylactic acid (PLA) on up to five Raise 3D printers. Bolus is designed in the radiotherapy treatment planning system (Varian Eclipse), exported to an STL file followed by pre-processing. After checking each bolus with CT scanning initially we now produce standard quality control (QC) wedges every month and whenever a major change in printing processes occurs. A database records every bolus printed and manufacturing details. It takes about 3 days from designing the bolus in the planning system to delivering it to treatment. A 'premium' PLA material (Spidermaker) was found to be best in terms of homogeneity and CT number consistency (80 HU +/- 8HU). Most boluses were produced for photon beams (93.6%) with the rest used for electrons. We process about 120 kg of PLA per year with a typical bolus weighing less than 500 g and the majority of boluses 5 mm thick. Print times are proportional to bolus weight with about 24 h required for 500 g material deposited. 3D printing using FDM produces smooth and reproducible boluses. Quality control is essential but can be streamlined.","PeriodicalId":48490,"journal":{"name":"Physical and Engineering Sciences in Medicine","volume":" ","pages":"551-561"},"PeriodicalIF":4.4,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11166743/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139570164","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}

引用次数: 0

Fetal QRS extraction from single-channel abdominal ECG using adaptive improved permutation entropy. 利用自适应改进的置换熵从单通道腹部心电图中提取胎儿 QRS。

IF 4.4 4区医学

Physical and Engineering Sciences in Medicine Pub Date : 2024-06-01 Epub Date: 2024-02-08 DOI: 10.1007/s13246-024-01386-0

Nastaran Mansourian, Sadaf Sarafan, Farah Torkamani-Azar, Tadesse Ghirmai, Hung Cao

{"title":"Fetal QRS extraction from single-channel abdominal ECG using adaptive improved permutation entropy.","authors":"Nastaran Mansourian, Sadaf Sarafan, Farah Torkamani-Azar, Tadesse Ghirmai, Hung Cao","doi":"10.1007/s13246-024-01386-0","DOIUrl":"10.1007/s13246-024-01386-0","url":null,"abstract":"Fetal electrocardiogram (fECG) monitoring is crucial for assessing fetal condition during pregnancy. However, current fECG extraction algorithms are not suitable for wearable devices due to their high computational cost and multi-channel signal requirement. The paper introduces a novel and efficient algorithm called Adaptive Improved Permutation Entropy (AIPE), which can extract fetal QRS from a single-channel abdominal ECG (aECG). The proposed algorithm is robust and computationally efficient, making it a reliable and effective solution for wearable devices. To evaluate the performance of the proposed algorithm, we utilized our clinical data obtained from a pilot study with 10 subjects, each recording lasting 20 min. Additionally, data from the PhysioNet 2013 Challenge bank with labeled QRS complex annotations were simulated. The proposed methodology demonstrates an average positive predictive value ( <math><mrow><mo>+</mo> <mi>P</mi></mrow> </math> ) of 91.0227%, sensitivity (Se) of 90.4726%, and F1 score of 90.6525% from the PhysioNet 2013 Challenge bank, outperforming other methods. The results suggest that AIPE could enable continuous home-based monitoring of unborn babies, even when mothers are not engaging in any hard physical activities.","PeriodicalId":48490,"journal":{"name":"Physical and Engineering Sciences in Medicine","volume":" ","pages":"563-573"},"PeriodicalIF":4.4,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139703737","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}

引用次数: 0