Medical physics最新文献

{"title":"A microscopic oxygen transport model for ultra-high dose rate radiotherapy in vivo: The impact of physiological conditions on FLASH effect","authors":"Lixiang Guo, Paul M. Medin, Ken Kang-Hsin Wang","doi":"10.1002/mp.17398","DOIUrl":"10.1002/mp.17398","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Ultra-high dose rate irradiation (≥40 Gy/s, FLASH) has been shown to reduce normal tissue toxicity, while maintaining tumor control compared to conventional dose-rate radiotherapy. The radiolytic oxygen (O<sub>2</sub>) depletion (ROD) resulting from FLASH has been proposed to explain the normal tissue protection effect; however, in vivo experiments have not confirmed that FLASH induced global tissue hypoxia. Nonetheless, the experiments reported are based on volume-averaged measurement, which have inherent limitations in detecting microscopic phenomena, including the potential preservation of stem cells niches due to local FLASH-induced O<sub>2</sub> depletion. Computational modeling offers a complementary approach to understand the ROD caused by FLASH at the microscopic level.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>We developed a comprehensive model to describe the spatial and temporal dynamics of O<sub>2</sub> consumption and transport in response to irradiation in vivo. The change of oxygen enhancement ratio (OER) was used to quantify and investigate the FLASH effect as a function of physiological and radiation parameters at microscopic scale.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We considered time-dependent O<sub>2</sub> supply and consumption in a 3D cylindrical geometry, incorporating blood flow linking the O<sub>2</sub> concentration ([O<sub>2</sub>]) in the capillary to that within the tissue through the Hill equation, radial and axial diffusion of O<sub>2</sub>, metabolic and zero-order radiolytic O<sub>2</sub> consumption, and a pulsed radiation structure. Time-evolved distributions of [O<sub>2</sub>] were obtained by numerically solving perfusion-diffusion equations. The model enables the computation of dynamic O<sub>2</sub> distribution and the relative change of OER (<i>δ<sub>ROD</sub></i>) under various physiological and radiation conditions in vivo.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Initial [O<sub>2</sub>] level and the subsequent changes during irradiation determined <i>δ<sub>ROD</sub></i> distribution, which strongly depends on physiological parameters, i.e., intercapillary spacing, ultimately determining the tissue area with enhanced radioresistance. We observed that the <i>δ<sub>ROD</sub></i>/FLASH effect is affected by and sensitive to the interplay effect among physiological and radiation parameters. It renders that the FLASH effect can be tissue environment dependent. The saturation of FLASH normal tissue protection upon dose and dose rate was shown. Beyond ∼6","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"51 11","pages":"8623-8637"},"PeriodicalIF":3.2,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/mp.17398","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142250887","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AAPM 2024 66th Annual Meeting & Exhibition July 21–25 Los Angeles,CA","authors":"","doi":"10.1002/mp.17396","DOIUrl":"https://doi.org/10.1002/mp.17396","url":null,"abstract":"","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"51 9","pages":"6536-6548"},"PeriodicalIF":3.2,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142234872","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"List of Advertisers","authors":"","doi":"10.1002/mp.15754","DOIUrl":"https://doi.org/10.1002/mp.15754","url":null,"abstract":"","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"51 9","pages":"7008"},"PeriodicalIF":3.2,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/mp.15754","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142234908","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A hybrid, nonlinear programming approach for optimizing passive shimming in MRI","authors":"Jie Zhao,&nbsp;Minhua Zhu,&nbsp;Ling Xia,&nbsp;Yifeng Fan,&nbsp;Feng Liu","doi":"10.1002/mp.17403","DOIUrl":"10.1002/mp.17403","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>In magnetic resonance imaging (MRI), maintaining a highly uniform main magnetic field (<i>B</i>₀) is essential for producing detailed images of human anatomy. Passive shimming (PS) is a technique used to enhance <i>B</i>₀ uniformity by strategically arranging shimming iron pieces inside the magnet bore. Traditionally, PS optimization has been implemented using linear programming (LP), posing challenges in balancing field quality with the quantity of iron used for shimming.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>In this work, we aimed to improve the efficacy of passive shimming that has the advantages of balancing field quality, iron usage, and harmonics in an optimal manner and leads to a smoother field profile.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>This study introduces a hybrid algorithm that combines particle swarm optimization with sequential quadratic programming (PSO-SQP) to enhance shimming performance. Additionally, a regularization method is employed to reduce the iron pieces' weight effectively.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The simulation study demonstrated that the magnetic field was improved from 462  to 3.6 ppm, utilizing merely 1.2 kg of iron in a 40 cm diameter spherical volume (DSV) of a 7T MRI magnet. Compared to traditional optimization techniques, this method notably enhanced magnetic field uniformity by 96.7% and reduced the iron weight requirement by 81.8%.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>The results indicated that the proposed method is expected to be effective for passive shimming.</p>\u0000 </section>\u0000 </div>","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"51 11","pages":"8613-8622"},"PeriodicalIF":3.2,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142250889","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Eigenbin compression for reducing photon‐counting CT data size","authors":"Taly Gilat Schmidt, Zhye Yin, Jingwu Yao, Jiahua Fan","doi":"10.1002/mp.17409","DOIUrl":"https://doi.org/10.1002/mp.17409","url":null,"abstract":"BackgroundPhoton‐counting CT (PCCT) systems acquire multiple spectral measurements at high spatial resolution, providing numerous image quality benefits while also increasing the amount of data that must be transferred through the gantry slip ring.PurposeThis study proposes a lossy method to compress photon‐counting CT data using eigenvector analysis, with the goal of providing image quality sufficient for applications that require a rapid initial reconstruction, such as to confirm anatomical coverage, scan quality, and to support automated advanced applications. The eigenbin compression method was experimentally evaluated on a clinical silicon PCCT prototype system.MethodsThe proposed eigenbin method performs principal component analysis (PCA) on a set of PCCT calibration measurements. PCA finds the orthogonal axes or eigenvectors, which capture the maximum variance in the &lt;jats:italic&gt;N&lt;/jats:italic&gt; dimensional photon‐count data space, where &lt;jats:italic&gt;N&lt;/jats:italic&gt; is the number of acquired energy bins. To reduce the dimensionality of the PCCT data, the data are linearly transformed into a lower dimensional space spanned by the M &lt; N eigenvectors with highest eigenvalues (i.e., the vectors that account for most of the information in the data). Only M coefficients are then transferred per measurement, which we term eigenbin values. After transmission, the original N energy‐bin measurements are estimated as a linear combination of the M eigenvectors. Two versions of the eigenbin method were investigated: pixel‐specific and pixel‐general. The pixel‐specific eigenbin method determines eigenvectors for each individual detector pixel, while the more practically realizable pixel‐general eigenbin method finds one set of eigenvectors for the entire detector array. The eigenbin method was experimentally evaluated by scanning a 20 cm diameter Gammex Multienergy phantom with different material inserts on a clinical silicon‐based PCCT prototype. The method was evaluated with the number of eigenbins varied between two and four. In each case, the eigenbins were used to estimate the original 8‐bin data, after which material decomposition was performed. The mean, standard deviation, and contrast‐to‐noise ratio (CNR) of values in the reconstructed basis and virtual monoenergetic images (VMI) were compared for the original 8‐bin data and for the eigenbin data.ResultsThe pixel‐specific eigenbin method reduced photon‐counting CT data size by a factor of four with &lt;5% change in mean values and a small noise penalty (mean change in noise of &lt;12%, maximum change in noise of 20% for basis images). The pixel‐general eigenbin compression method reduced data size by a factor of 2.67 with &lt;5% change in mean values and a less than 10% noise penalty in the basis images (average noise penalty ≤5%). The noise penalty and errors were less for the VMIs than for the basis images, resulting in &lt;5% change in CNR in the VMIs.ConclusionThe eigenbin compression me","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"198 1","pages":""},"PeriodicalIF":3.8,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142250890","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development and external validation of a novel modality for rapid recognition of aortic dissection based on peripheral pulse oximetry waveforms","authors":"Jing-chao Luo,&nbsp;Yi-jie Zhang,&nbsp;Ying Niu,&nbsp;Ming-hao Luo,&nbsp;Feng Sun,&nbsp;Guo-wei Tu,&nbsp;Zhao Chen,&nbsp;Si-ying Zhou,&nbsp;Guo-rong Gu,&nbsp;Xu-feng Cheng,&nbsp;Yu-wei Zhao,&nbsp;Wan-ting Zhou,&nbsp;Zhe Luo","doi":"10.1002/mp.17405","DOIUrl":"10.1002/mp.17405","url":null,"abstract":"&lt;div&gt;\u0000 \u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Background&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Aortic dissection (AD) is a life-threatening cardiovascular emergency that is often misdiagnosed as other chest pain conditions. Physiologically, AD may cause abnormalities in peripheral blood flow, which can be detected using pulse oximetry waveforms.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Purpose&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;This study aimed to assess the feasibility of identifying AD based on pulse oximetry waveforms and to highlight the key waveform features that play a crucial role in this diagnostic method.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Methods&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;This prospective study employed high-risk chest pain cohorts from two emergency departments. The initial cohort was enriched with AD patients (&lt;i&gt;n&lt;/i&gt; = 258, 47% AD) for model development, while the second cohort consisted of chest pain patients awaiting angiography (&lt;i&gt;n&lt;/i&gt; = 71, 25% AD) and was used for external validation. Pulse oximetry waveforms from the four extremities were collected for each patient. After data preprocessing, a recognition model based on the random forest algorithm was trained using patients' gender, age, and waveform difference features extracted from the pulse oximetry waveforms. The performance of the model was evaluated using receiver operating characteristic (ROC) curve analysis and decision curve analysis (DCA). The importance of features was also assessed using Shapley Value and Gini importance.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Results&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;The model demonstrated strong performance in identifying AD in both the training and external validation sets. In the training set, the model achieved an area under the ROC curve of 0.979 (95% CI: 0.961–0.990), sensitivity of 0.918 (95% CI: 0.873–0.955), specificity of 0.949 (95% CI: 0.912–0.985), and accuracy of 0.933 (95% CI: 0.904–0.959). In the external validation set, the model attained an area under the ROC curve of 0.855 (95% CI: 0.720–0.965), sensitivity of 0.889 (95% CI: 0.722–1.000), specificity of 0.698 (95% CI: 0.566–0.812), and accuracy of 0.794 (95% CI: 0.672–0.878). Decision curve analysis (DCA) further showed that the model provided a substantial net benefit for identifying AD. The median mean and median variance of the four limbs' signals were the most influential features in the recognition model.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Conclusions&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;This study demonstrated the feasibility and strong performance of identifying AD based on peripheral pulse oximetry waveforms in high-risk chest pain populations in the emergency setting. The findings also provided valuable insights for future human fluid dy","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"51 11","pages":"8434-8441"},"PeriodicalIF":3.2,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/mp.17405","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142250888","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Performance evaluation of a 4D similarity filter for dynamic CT angiography imaging of the liver","authors":"Sjoerd A. M. Tunissen, Ewoud J. Smit, Mikhail Mikerov, Mathias Prokop, Ioannis Sechopoulos","doi":"10.1002/mp.17394","DOIUrl":"https://doi.org/10.1002/mp.17394","url":null,"abstract":"BackgroundDynamic computed tomography (CT) angiography of the abdomen provides perfusion information and characteristics of the tissues present in the abdomen. This information could potentially help characterize liver metastases. However, radiation dose has to be relatively low for the patient, causing the images to have very high noise content. Denoising methods are needed to increase image quality.PurposeThe purpose of this study was to investigate the performance, limitations, and behavior of a new 4D filtering method, called the 4D Similarity Filter (4DSF), to reduce image noise in temporal CT data.MethodsThe 4DSF averages voxels with similar time‐intensity curves (TICs). Each phase is filtered individually using the information of all phases except for the one being filtered. This approach minimizes the bias toward the noise initially present in this phase. Since the 4DSF does not base similarity on spatial proximity, loss of spatial resolution is avoided. The 4DSF was evaluated on a 12‐phase liver dynamic CT angiography acquisition of 52 digital anthropomorphic phantoms, each containing one hypervascular 1 cm lesion with a small necrotic core. The metrics used for evaluation were noise reduction, lesion contrast‐to‐noise ratio (CNR), CT number accuracy using peak‐time and peak‐intensity of the TICs, and resolution loss. The results were compared to those obtained by the time‐intensity profile similarity (TIPS) filter, which uses the whole TIC for determining similarity, and the combination 4DSF followed by TIPS filter (4DSF + TIPS).ResultsThe 4DSF alone resulted in a median noise reduction by a factor of 6.8, which is lower than that obtained by the TIPS filter at 8.1, and 4DSF + TIPS at 12.2. The 4DSF increased the median CNR from 0. 44 to 1.85, which is less than the TIPS filter at 2.59 and 4DSF + TIPS at 3.12. However, the peak‐intensity accuracy in the TICs was superior for the 4DSF, with a median intensity decrease of −34 HU compared to −88 and −50 HU for the hepatic artery when using the TIPS filter and 4DSF + TIPS, respectively. The median peak‐time accuracy was inferior for the 4DSF filter and 4DSF + TIPS, with a time shift of −1 phases for the portal vein TIC compared to no shift in time when using the TIPS. The analysis of the full‐width‐at‐half‐maximum (FWHM) of a small artery showed significantly less spatial resolution loss for the 4DSF at 3.2 pixels, compared to the TIPS filter at 4.3 pixels, and 3.4 pixels for the 4DSF + TIPS.ConclusionThe 4DSF can reduce noise with almost no resolution loss, making the filter very suitable for denoising 4D CT data for detection tasks, even in very low dose, i.e., very high noise level, situations. In combination with the TIPS filter, the noise reduction can be increased even further.","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"12 1","pages":""},"PeriodicalIF":3.8,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142176368","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dual‐stage semantic segmentation of endoscopic surgical instruments","authors":"Wenxin Chen, Kaifeng Wang, Xinya Song, Dongsheng Xie, Xue Li, Mobarakol Islam, Changsheng Li, Xingguang Duan","doi":"10.1002/mp.17397","DOIUrl":"https://doi.org/10.1002/mp.17397","url":null,"abstract":"BackgroundEndoscopic instrument segmentation is essential for ensuring the safety of robotic‐assisted spinal endoscopic surgeries. However, due to the narrow operative region, intricate surrounding tissues, and limited visibility, achieving instrument segmentation within the endoscopic view remains challenging.PurposeThis work aims to devise a method to segment surgical instruments in endoscopic video. By designing an endoscopic image classification model, features of frames before and after the video are extracted to achieve continuous and precise segmentation of instruments in endoscopic videos.MethodsDeep learning techniques serve as the algorithmic core for constructing the convolutional neural network proposed in this study. The method comprises dual stages: image classification and instrument segmentation. MobileViT is employed for image classification, enabling the extraction of key features of different instruments and generating classification results. DeepLabv3+ is utilized for instrument segmentation. By training on distinct instruments separately, corresponding model parameters are obtained. Lastly, a flag caching mechanism along with a blur detection module is designed to effectively utilize the image features in consecutive frames. By incorporating specific parameters into the segmentation model, better segmentation of surgical instruments can be achieved in endoscopic videos.ResultsThe classification and segmentation models are evaluated on an endoscopic image dataset. In the dataset used for instrument segmentation, the training set consists of 7456 images, the validation set consists of 829 images, and the test set consists of 921 images. In the dataset used for image classification, the training set consists of 2400 images and the validation set consists of 600 images. The image classification model achieves an accuracy of 70% on the validation set. For the segmentation model, experiments are conducted on two common surgical instruments, and the mean Intersection over Union (mIoU) exceeds 98%. Furthermore, the proposed video segmentation method is tested using videos collected during surgeries, validating the effectiveness of the flag caching mechanism and blur detection module.ConclusionsExperimental results on the dataset demonstrate that the dual‐stage video processing method excels in performing instrument segmentation tasks under endoscopic conditions. This advancement is significant for enhancing the intelligence level of robotic‐assisted spinal endoscopic surgeries.","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"9 1","pages":""},"PeriodicalIF":3.8,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142176402","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development of a three‐dimensional scintillation detector for pencil beam verification in proton therapy patient‐specific quality assurance","authors":"Anne‐Marie Frelin, Gautier Daviau, My Hoang Hoa Bui, Cathy Fontbonne, Jean‐Marc Fontbonne, Dorothée Lebhertz, Erwan Mainguy, Cyril Moignier, Juliette Thariat, Anthony Vela","doi":"10.1002/mp.17388","DOIUrl":"https://doi.org/10.1002/mp.17388","url":null,"abstract":"BackgroundPencil Beam Scanning proton therapy has many advantages from a therapeutic point of view, but raises technical constraints in terms of treatment verification. The treatment relies on a large number of planned pencil beams (PB) (up to thousands), whose delivery is divided in several low‐intensity pulses delivered a high frequency (1 kHz in this study).PurposeThe purpose of this study was to develop a three‐dimensional quality assurance system allowing to verify all the PBs’ characteristics (position, energy, intensity in terms of delivered monitor unit—MU) of patient treatment plans on a pulse‐by‐pulse or a PB‐by‐PB basis.MethodsA system named SCICOPRO has been developed. It is based on a 10 × 10 × 10 cm&lt;jats:sup&gt;3&lt;/jats:sup&gt; scintillator cube and a fast camera, synchronized with beam delivery, recording two views (direct and using a mirror) of the scintillation distribution generated by the pulses. A specific calibration and analysis process allowed to extract the characteristics of all the pulses delivered during the treatment, and consequently of all the PBs. The system uncertainties, defined here as average value + standard deviation, were characterized with a customized irradiation plan at different PB intensities (0.02, 0.1, and 1 MU) and with two patient's treatment plans of three beams each. The system's ability to detect potential treatment delivery problems, such as positioning errors of the treatment table in this work (1° rotations and a 2 mm translation), was assessed by calculating the confidence intervals (CI) for the different characteristics and evaluating the proportion of PBs within these intervals.ResultsThe performances of SCICOPRO were evaluated on a pulse‐by‐pulse basis. They showed a very good signal‐to‐noise ratio for all the pulse intensities (between 2 × 10&lt;jats:sup&gt;−3&lt;/jats:sup&gt; MU and 150 × 10&lt;jats:sup&gt;−3&lt;/jats:sup&gt; MU) allowing uncertainties smaller than 580 µm for the position, 180 keV for the energy and 3% for the intensity on patients treatment plans. The position and energy uncertainties were found to be little dependent from the pulse intensities whereas the intensity uncertainty depends on the pulses number and intensity distribution. Finally, treatment plans evaluations showed that 98% of the PBs were within the CIs with a nominal positioning against 83% or less with the table positioning errors, thus proving the ability of SCICOPRO to detect this kind of errors.ConclusionThe high acquisition rate and the very high sensitivity of the system developed in this work allowed to record pulses of intensities as low as 2 × 10&lt;jats:sup&gt;−3&lt;/jats:sup&gt; MU. SCICOPRO was thus able to measure all the characteristics of the spots of a treatment (position, energy, intensity) in a single measurement, making it possible to verify their compliance with the treatment plan. SCICOPRO thus proved to be a fast and accurate tool that would be useful for patient‐specific quality assurance (PSQA) on a pulse‐by‐pulse or PB‐by‐PB","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"8 1","pages":""},"PeriodicalIF":3.8,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142176403","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Elucidating the hemodynamic impact of residual stenosis post‐carotid artery stenting: A numerical study","authors":"Xianghao Zhang, Zhenmin Fan, Pengfei Zhao, Xia Ye, Xiaoyan Deng, Robert Guidoin, Mingyuan Liu","doi":"10.1002/mp.17386","DOIUrl":"https://doi.org/10.1002/mp.17386","url":null,"abstract":"BackgroundResidual stenosis (RS) and hemodynamics demonstrate a significant correlation with postoperative in‐stent restenosis/thrombosis following carotid artery stenting (CAS).PurposeThis study endeavors to elucidate the potential associations between RS and adverse postoperative hemodynamic factors.MethodsThis study utilized 46 patient‐specific carotid artery models post‐stenting, which were categorized into two groups based on the presence of RS: the normal group (N, <jats:italic>n</jats:italic> = 23) and the RS group (RS, <jats:italic>n</jats:italic> = 23). A comparative analysis was conducted to evaluate the discrepancies in geometry and adverse hemodynamic parameters, alongside investigating the potential correlation between hemodynamic and geometric parameters.ResultsThe results reveal that a higher reflux flow volume is discernible in the RS group during low‐velocity phases of the cardiac cycle, concomitant with an augmented extent of areas exposed to oscillatory shear stress and extended particle residence time. Moreover, the adverse hemodynamic parameters exhibit a positive correlation with the degree of stent expansion, stent length in the common carotid artery (CCA), and the distal slope of the RS.ConclusionThe distal slope and tortuosity of RS significantly influence the development of adverse hemodynamic conditions post‐stenting, exacerbating the hemodynamic environment near the stenosis. Interestingly, while an extended stent length in the internal carotid artery (ICA) region improves hemodynamics by reducing flow disturbance, a longer stent in the CCA significantly worsens these conditions. Hence, it is prudent to analyze the characteristics of the local lesion regions to optimize the strategy for stent implantation.","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"15 1","pages":""},"PeriodicalIF":3.8,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142176404","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}