Journal of Applied Clinical Medical Physics最新文献

{"title":"Engaging grade school learners with an interactive medical imaging activity.","authors":"Jessica M Fagerstrom, Alyssa C Alvarez, Ethan O Cohen, Afua A Yorke","doi":"10.1002/acm2.14606","DOIUrl":"https://doi.org/10.1002/acm2.14606","url":null,"abstract":"<p><p>This case report describes a 45-min active learning lesson plan that engages 4th-5th and 6th-8th grade school students in spatial reasoning through a review of medical imaging. The lesson plan reviews different planar orientations and cross-sections of computed tomography (CT) images of familiar objects. The lesson is designed to introduce students to the idea that scientists are key contributors to healthcare, including in medical imaging technologies that facilitate the visualization of internal structures of patients without invasive procedures. The lesson demonstrates the three standard anatomical planes, axial, sagittal and coronal, by guiding students through CT image datasets of various objects. Students then are led in an interactive \"dissection\" of fruit to compare internal structures with medical images. The lesson plan aligns with key aspects of Next Generation Science Standards and aims to spark interest in the field of medical physics among a young student population through an introduction to imaging technologies. Worksheets and imaging datasets are included as supplementary materials to facilitate interested physicists adapting this work for educational purposes in their own communities, with minimal repeated effort.</p>","PeriodicalId":14989,"journal":{"name":"Journal of Applied Clinical Medical Physics","volume":" ","pages":"e14606"},"PeriodicalIF":2.0,"publicationDate":"2024-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142835764","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Radiomics based on dual-layer spectral detector CT for predicting EGFR mutation status in non-small cell lung cancer.","authors":"Dan Jin, Xiaoqiong Ni, Yanhuan Tan, Hongkun Yin, Guohua Fan","doi":"10.1002/acm2.14616","DOIUrl":"https://doi.org/10.1002/acm2.14616","url":null,"abstract":"<p><strong>Objective: </strong>To explore the value of dual-layer spectral computed tomography (DLCT)-based radiomics for predicting epidermal growth factor receptor (EGFR) mutation status in patients with non-small cell lung cancer (NSCLC).</p><p><strong>Methods: </strong>DLCT images and clinical information from 115 patients with NSCLC were collected retrospectively and randomly assigned to a training group (n = 81) and a validation group (n = 34). A radiomics model was constructed based on the DLCT radiomic features by least absolute shrinkage and selection operator (LASSO) dimensionality reduction. A clinical model based on clinical and CT features was established. A nomogram was built combining the radiomic scores (Radscores) and clinical factors. Receiver operating characteristic (ROC) analysis and decision curve analysis (DCA) were used for the efficacy and clinical value of the models assessment.</p><p><strong>Results: </strong>A total of six radiomic features and two clinical features were screened for modeling. The AUCs of the radiomic model, clinical model, and nomogram were 0.909, 0.797, and 0.922, respectively, in the training group and 0.874, 0.691, and 0.881, respectively, in the validation group. The AUCs of the nomogram and the radiomics model were significantly higher than that of the clinical model, but no significant difference was found between them. DCA revealed that nomogram had the greatest clinical benefit at most threshold intervals.</p><p><strong>Conclusion: </strong>Nomogram integrating clinical factors and pretreatment DLCT radiomic features can help evaluate the EGFR mutation status of patients with NSCLC in a noninvasive way.</p>","PeriodicalId":14989,"journal":{"name":"Journal of Applied Clinical Medical Physics","volume":" ","pages":"e14616"},"PeriodicalIF":2.0,"publicationDate":"2024-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142824217","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Magnetic field quality conversion factors experimentally measured in clinical MR-linac beams for seven MR-compatible ionization chamber models.","authors":"Nathan Orlando, Jennie Crosby, Carri Glide-Hurst, Wesley Culberson, Arman Sarfehnia","doi":"10.1002/acm2.14613","DOIUrl":"https://doi.org/10.1002/acm2.14613","url":null,"abstract":"<p><strong>Purpose: </strong>The purpose of this work was to experimentally quantify MR-compatible ionization chamber response for 1.5T Elekta Unity and 0.35T ViewRay MRIdian MR-linac systems through the determination of the magnetic field quality conversion factor, k_B,Q.</p><p><strong>Methods: </strong>Seven MR-compatible ionization chamber models from Standard Imaging and PTW were evaluated. Both the quality conversion factor k_Q and the magnetic field quality conversion factor k_B,Q were experimentally determined through a cross-calibration method. Specifically, the ratio of absorbed dose measured with a reference A1SL chamber under reference conditions to corrected output measured with each test chamber at the same point of measurement allowed for the determination of k_B,Q. The angular dependence of the magnetic field quality conversion factor for MR-compatible chamber models was assessed for the 1.5T Elekta Unity system by measuring k_B,Q with the chamber axis and magnetic field direction aligned at cardinal angles (0°, 90°, 180°, 270°).</p><p><strong>Results: </strong>Beam quality conversion (k_Q) factors for MR-compatible ionization chambers measured in a standard linac beam showed an average percent difference of -0.09 ± 0.18% compared to computed k_Q values for their conventional chamber versions. Similarly, magnetic field quality conversion (k_B,Q) factors for corresponding MR and non-MR ionization chamber models measured using the same cross-calibration technique demonstrated average percent differences of -0.1 ± 0.3% and 0.0 ± 0.2% for the Elekta Unity and ViewRay MRIdian, respectively. Investigation of the angular dependence of this correction factor demonstrated identical chamber response for equivalent MR-compatible and conventional chamber models.</p><p><strong>Conclusions: </strong>This work provides critical experimental validation of MR-compatible ionization chamber performance, with a direct comparison of measured k_B,Q values to corresponding conventional chamber models demonstrating nearly equivalent chamber response. k_B,Q values determined using our experimental method will serve as an important reference for upcoming MR-linac reference dosimetry protocols and ultimately represent an important step towards accurate output calibration of MR-linac systems.</p>","PeriodicalId":14989,"journal":{"name":"Journal of Applied Clinical Medical Physics","volume":" ","pages":"e14613"},"PeriodicalIF":2.0,"publicationDate":"2024-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142824216","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Routine machine quality assurance tests for a self-shielded gyroscopic radiosurgery system.","authors":"Yongsook C Lee, Ranjini Tolakanahalli, D Jay Wieczorek, Minesh P Mehta, Michael W McDermott, Rupesh Kotecha, Alonso N Gutierrez","doi":"10.1002/acm2.14589","DOIUrl":"https://doi.org/10.1002/acm2.14589","url":null,"abstract":"<p><strong>Purpose: </strong>This report describes routine machine quality assurance (QA) (daily, monthly, and annual QA) tests for the Zap-X^® Gyroscopic Radiosurgery^® platform.</p><p><strong>Methods: </strong>Following the recommendations of the American Association of Physicists in Medicine Task Group (AAPM TG)-142 and Medical Physics Practice guideline (MPPG) 8.b, routine machine QA tests for the Zap-X system were implemented. The implementation included (1) daily, monthly, and annual QA tests encompassing dosimetry, mechanical, safety and imaging tests, (2) QA methods of each test specific to the Zap-X, (3) a tolerance value for each test, and (4) necessary QA equipment.</p><p><strong>Results: </strong>Baseline values and key results of daily, monthly, and annual QA tests are presented in this report. This report also discusses QA tests not adopted from TG 142 or MPPG 8.b (e.g., distance indicator) due to unique features of the Zap-X system as well as additional QA tests added from the vendor's recommendations (e.g., self-check) and from TG-135 recommendations (e.g., monthly end-to-end testing) because of similarities between Zap-X and CyberKnife systems.</p><p><strong>Conclusions: </strong>The comprehensive information on routine machine QA tests presented in this report will assist Zap-X teams in other Neurosurgery centers or Radiation Oncology clinics in establishing and maintaining their QA programs until AAPM endorsed guidelines become available.</p>","PeriodicalId":14989,"journal":{"name":"Journal of Applied Clinical Medical Physics","volume":" ","pages":"e14589"},"PeriodicalIF":2.0,"publicationDate":"2024-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142824218","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Clinical validation of MR-generated synthetic CT by MRCAT for brain tumor radiotherapy.","authors":"Tyrone Tsz Yeung Yip, Zhichun Li, Tian Li","doi":"10.1002/acm2.14494","DOIUrl":"https://doi.org/10.1002/acm2.14494","url":null,"abstract":"<p><strong>Objective: </strong>MRI is an emerging modality in radiotherapy (RT). Accuracy synthetic CT is the prerequisite for implementing MR-only RT planning. This study validated the commercial algorithm of MR for calculating attenuation (MRCAT) in terms of image quality and dosimetric agreement.</p><p><strong>Methods: </strong>Brain tumor cases with 18 treated using intensity-modulated radiotherapy (IMRT) or volumetric modulated arc therapy (VMAT), and 15 treated using stereotactic radiosurgery (SRS) were analyzed. Synthetic CTs were resampled referencing planning CT. Treatment plan calculated on planning CT was recalculated on resampled MRCAT. Image quality of selected metrics and dosimetric agreements were assessed by dose-volume-histogram and 3D gamma analysis.</p><p><strong>Results: </strong>For IMRT/VMAT and SRS cases, mean error were 23.42 ± 1.05 and 28.39 ± 3.17 HU; mean absolute error were 38.03 ± 1.42 and 52.36 ± 2.63 HU; root mean squared error were 89.09 ± 6.65 and 108.38 ± 12.23 HU; peak signal-to-noise ratio were 29.11 ± 0.60  and 27.65 ± 0.59 dB; and structural similarity index measures were 0.88 ± 0.00 and 0.70 ± 0.01 respectively. No significant differences were identified for DVH metrics accounting the target coverage. Most OARs did not have significant dose deviation, except left lens with 0.70% higher in D-mean after recalculation (p < 0.001). For criteria of 3 mm/3%, 2 mm/2%, and 1 mm/1%, gamma passing rates for IMRT/VMAT were 99.92%, 99.42%, and 96.47%, while SRS were 99.86%, 99.52%, and 97.57% respectively. Correlation between passing rate and image quality metrics was established in IMRT/VMAT cases, with higher similarity yield better dosimetric agreement between planning and synthetic CT.</p><p><strong>Conclusion: </strong>This study has validated the MRCAT for clinical use in terms of comparable image quality and dosimetric agreement with planning CT. Further case selection and MR-compatible immobilization device would be required.</p>","PeriodicalId":14989,"journal":{"name":"Journal of Applied Clinical Medical Physics","volume":" ","pages":"e14494"},"PeriodicalIF":2.0,"publicationDate":"2024-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142824215","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The LET enhancement of energy-specific collimation in pencil beam scanning proton therapy.","authors":"Blake R Smith, Daniel E Hyer","doi":"10.1002/acm2.14477","DOIUrl":"https://doi.org/10.1002/acm2.14477","url":null,"abstract":"<p><strong>Purpose: </strong>To computationally characterize the LET distribution during dynamic collimation in PBS and quantify its impact on the resultant dose distribution.</p><p><strong>Methods: </strong>Monte Carlo simulations using Geant4 were used to model the production of low-energy proton scatter produced in the collimating components of a novel PBS collimator. Custom spectral tallies were created to quantify the energy, track- and dose-averaged LET resulting from individual beamlet and composite fields simulated from a model of the IBA dedicated nozzle system. The composite dose distributions were optimized to achieve a uniform physical dose coverage of a cubical and pyramidal target, and the resulting dose-average LET distributions were calculated for uncollimated and collimated PBS deliveries and used to generate RBE-weighted dose distributions.</p><p><strong>Results: </strong>For collimated beamlets, the scattered proton energy fluence is strongly dependent on collimator position relative to the central axis of the beamlet. When delivering a uniform profile, the distribution of dose-average LET was nearly identical within the target and increased between 1 and <math> <semantics><mrow><mn>2</mn> <mspace></mspace> <mi>keV</mi> <mo>/</mo> <mi>μ</mi> <mi>m</mi></mrow> <annotation>$2 ,{rm keV}/mathrm{umu }mathrm{m}$</annotation></semantics> </math> within 10 mm surrounding the target. Dynamic collimation resulted in larger dose-average LET changes: increasing the dose-average LET between 1 and <math> <semantics><mrow><mn>3</mn> <mspace></mspace> <mi>keV</mi> <mo>/</mo> <mi>μ</mi> <mi>m</mi></mrow> <annotation>$3 ,{rm keV}/mathrm{umu }mathrm{m}$</annotation></semantics> </math> within 10 mm of a pyramidal target while reducing the dose-average LET outside this margin by as much as <math> <semantics><mrow><mn>10</mn> <mspace></mspace> <mi>keV</mi> <mo>/</mo> <mi>μ</mi> <mi>m</mi></mrow> <annotation>$10 ,{rm keV}/mathrm{umu }mathrm{m}$</annotation></semantics> </math> . Biological dose distributions are improved with energy-specific collimation in reducing the lateral penumbra.</p><p><strong>Conclusion: </strong>The presence of energy-specific collimation in PBS can lead to dose-average LET changes relative to an uncollimated delivery. In some clinical situations, the placement and application of energy-specific collimation may require additional planning considerations based on its reduction to the lateral penumbra and increase in high-dose conformity. Future applications may embody these unique dosimetric characteristics to redirect high-LET portions of a collimated proton beamlet from healthy tissues while enhancing the dose-average LET distribution within target.</p>","PeriodicalId":14989,"journal":{"name":"Journal of Applied Clinical Medical Physics","volume":" ","pages":"e14477"},"PeriodicalIF":2.0,"publicationDate":"2024-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142791730","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Estimation of heart dose in left breast cancer radiotherapy: Assessment of vDIBH feasibility using the supervised machine learning algorithm.","authors":"Shriram Ashok Rajurkar, Teerthraj Verma, Rajeev Gupta","doi":"10.1002/acm2.14595","DOIUrl":"https://doi.org/10.1002/acm2.14595","url":null,"abstract":"<p><strong>Background and objective: </strong>The volunteer deep inspiration breath hold (vDIBH) technique is used to reduce the heart dose in left breast cancer radiotherapy. Many times, it is faced that despite rigorous exercise and training, not all patients get benefited as expected. The primary objective of this study was to develop a machine learning program for prediction of mean heart dose before left breast radiotherapy under vDIBH.</p><p><strong>Methods: </strong>The present work is based on the dosimetric parameters of eighty-two left breast cancer patients, who have undergone modified radical mastectomy, enrolled for their radiation treatment. The trained machine learning algorithm employed linear regression to establish a correlation between Haller Index and heart mean dose (HMD) received during the ca left breast cancer radiotherapy. Subsequently, HMD values were used to model the regression relationship with maximum heart distance (MHD).</p><p><strong>Results: </strong>The method adopted is beneficial in patient selection and assessment for suitability of patients' radiotherapy planning under vDIBH treatment technique. For data from 21 test patients, the mean of HMD obtained from the treatment planning system (TPS) and the mean of predicted HMD by developed program were found to be 468.76 cGy and 464.66 cGy, respectively.</p><p><strong>Conclusion: </strong>The present work facilitates precise HMD prediction in left breast cancer radiation therapy even before starting the treatment planning process. Additionally, this program offers suggestions in terms of modifications in treatment settings for even better results of vDIBH techniques if not matches with the anticipated results.</p>","PeriodicalId":14989,"journal":{"name":"Journal of Applied Clinical Medical Physics","volume":" ","pages":"e14595"},"PeriodicalIF":2.0,"publicationDate":"2024-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142785279","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Personalized federated learning for abdominal multi-organ segmentation based on frequency domain aggregation.","authors":"Hao Fu, Jian Zhang, Lanlan Chen, Junzhong Zou","doi":"10.1002/acm2.14602","DOIUrl":"https://doi.org/10.1002/acm2.14602","url":null,"abstract":"<p><strong>Purpose: </strong>The training of deep learning (DL) models in medical images requires large amounts of sensitive patient data. However, acquiring adequately labeled datasets is challenging because of the heavy workload of manual annotations and the stringent privacy protocols.</p><p><strong>Methods: </strong>Federated learning (FL) provides an alternative approach in which a coalition of clients collaboratively trains models without exchanging the underlying datasets. In this study, a novel Personalized Federated Learning Framework (PAF-Fed) is presented for abdominal multi-organ segmentation. Different from traditional FL algorithms, PAF-Fed selectively gathers partial model parameters for inter-client collaboration, retaining the remaining parameters to learn local data distributions at individual sites. Additionally, the Fourier Transform with the Self-attention mechanism is employed to aggregate the low-frequency components of parameters, promoting the extraction of shared knowledge and tackling statistical heterogeneity from diverse client datasets.</p><p><strong>Results: </strong>The proposed method was evaluated on the Combined Healthy Abdominal Organ Segmentation magnetic resonance imaging (MRI) dataset (CHAOS 2019) and a private computed tomography (CT) dataset, achieving an average Dice Similarity Coefficient (DSC) of 72.65% for CHAOS and 85.50% for the private CT dataset, respectively.</p><p><strong>Conclusion: </strong>The experimental results demonstrate the superiority of our PAF-Fed by outperforming state-of-the-art FL methods.</p>","PeriodicalId":14989,"journal":{"name":"Journal of Applied Clinical Medical Physics","volume":" ","pages":"e14602"},"PeriodicalIF":2.0,"publicationDate":"2024-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142785333","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Feasibility study of structural similarity index for patient-specific quality assurance.","authors":"Jae Choon Lee, Hyeong Wook Park, Young Nam Kang","doi":"10.1002/acm2.14591","DOIUrl":"https://doi.org/10.1002/acm2.14591","url":null,"abstract":"<p><strong>Background: </strong>The traditional gamma evaluation method combines dose difference (DD) and distance-to-agreement (DTA) to assess the agreement between two dose distributions. However, while gamma evaluation can identify the location of errors, it does not provide information about the type of errors.</p><p><strong>Purpose: </strong>The purpose of this study is to optimize and apply the structural similarity (SSIM) index algorithm as a supplementary metric for the quality evaluation of radiation therapy plans alongside gamma evaluation. By addressing the limitations of gamma evaluation, this study aims to establish clinically meaningful SSIM criteria to enhance the accuracy of patient-specific quality assurance (PSQA).</p><p><strong>Methods: </strong>We analyzed the relationship between the gamma passing rate (GPR) and the SSIM index with respect to distance and dose errors. For SSIM analysis corresponding to gamma evaluation criteria of 3%/2 mm, we introduce the concept of SSIM passing rate (SPR). We determined a valid SSIM index that met the gamma evaluation criteria and applied it. Evaluations performed for 40 fields measured with an electronic portal imaging device (EPID) were analyzed using the GPR and the applied SPR.</p><p><strong>Results: </strong>The study results showed that distance errors significantly affected both the GPR and the SSIM index, whereas dose errors had some influence on the GPR but little impact on the SSIM index. The SPR was 100% for distance error of 2 mm but began to decrease for distance errors of 3 mm or more. An optimal SSIM index threshold of 0.65 was established, indicating that SPR fell below 100% when distance errors exceeded 2 mm.</p><p><strong>Conclusions: </strong>This study demonstrates that the SSIM algorithm can be effectively applied for the quality evaluation of radiation therapy plans. The SPR can serve as a supplementary metric to gamma evaluation, offering a more precise identification of distance errors. Future research should further validate the efficacy of SSIM algorithm across a broader range of clinical cases.</p>","PeriodicalId":14989,"journal":{"name":"Journal of Applied Clinical Medical Physics","volume":" ","pages":"e14591"},"PeriodicalIF":2.0,"publicationDate":"2024-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142768896","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Commissioning and implementation of a pencil-beam algorithm with a Lorentz correction as a secondary dose calculation algorithm for an Elekta Unity 1.5T MR linear accelerator.","authors":"Sameer Taneja, Hesheng Wang, David L Barbee, Paulina Galavis, Mario Serrano Sosa, David Byun, Michael Zelefsky, Ting Chen","doi":"10.1002/acm2.14590","DOIUrl":"https://doi.org/10.1002/acm2.14590","url":null,"abstract":"<p><strong>Purpose: </strong>To commission a beam model in ClearCalc (Radformation Inc.) for use as a secondary dose calculation algorithm and to implement its use into an adaptive workflow for an MR-linear accelerator.</p><p><strong>Methods: </strong>A beam model was developed using commissioning data for an Elekta Unity MR-linear accelerator and entered into ClearCalc. The beam model consisted of absolute dose calculation settings, output factors, percent depth-dose (PDD) curves, mutli-leaf collimator (MLC) transmission and dose leaf gap error, and cryostat corrections. Beam profiles were hard-coded by the manufacturer into the beam model and were compared with Monaco-derived profiles. The beam model was tested by comparing point doses in a homogenous phantom obtained through measurements using an ionization chamber in water, Monaco, and ClearCalc for various field sizes, source-surface distances (SSDs), and point locations. Additional testing including point dose verification for test plans using a heterogeneous phantom and patient plans. Post clinical implementation, performance of ClearCalc was evaluated for the first 41 patients treated, which included 215 adaptive plans.</p><p><strong>Results: </strong>PDDs generated using ClearCalc fell within 1.2% of measurements. Field profile comparison between ClearCalc and Monaco showed an average pass rate of 98% using a 3%/3 mm gamma criteria. Measured cryostat corrections used in the beam model showed a maximum deviation from unity of 1.4%. Point dose and field monitor units (MUs) comparisons in a homogenous phantom (N = 22), heterogeneous phantoms (N = 22), and patient plans (N = 57) all passed with a threshold of 5%/5MU. Clinically, ClearCalc was implemented as a physics check post adaptive planning completed prior to beam delivery. Point dose and field MUs showed good agreement at a 5%/5MU threshold for prostate stereotactic body radiation therapy (SBRT), pelvic lymph nodes, rectum, and prostate and lymph node plans.</p><p><strong>Discussion: </strong>This work demonstrated commissioning and clinical implementation of ClearCalc into an adaptive planning workflow. No primary or adaptive plan failures were reported with proper beam model testing.</p>","PeriodicalId":14989,"journal":{"name":"Journal of Applied Clinical Medical Physics","volume":" ","pages":"e14590"},"PeriodicalIF":2.0,"publicationDate":"2024-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142769256","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}