Journal of Applied Clinical Medical Physics最新文献

{"title":"Advancements in synthetic CT generation from MRI: A review of techniques, and trends in radiation therapy planning.","authors":"Mohamed A Bahloul, Saima Jabeen, Sara Benoumhani, Habib Abdulmohsen Alsaleh, Zehor Belkhatir, Areej Al-Wabil","doi":"10.1002/acm2.14499","DOIUrl":"https://doi.org/10.1002/acm2.14499","url":null,"abstract":"<p><strong>Background: </strong>Magnetic resonance imaging (MRI) and Computed tomography (CT) are crucial imaging techniques in both diagnostic imaging and radiation therapy. MRI provides excellent soft tissue contrast but lacks the direct electron density data needed to calculate dosage. CT, on the other hand, remains the gold standard due to its accurate electron density information in radiation therapy planning (RTP) but it exposes patients to ionizing radiation. Synthetic CT (sCT) generation from MRI has been a focused study field in the last few years due to cost effectiveness as well as for the objective of minimizing side-effects of using more than one imaging modality for treatment simulation. It offers significant time and cost efficiencies, bypassing the complexities of co-registration, and potentially improving treatment accuracy by minimizing registration-related errors. In an effort to navigate the quickly developing field of precision medicine, this paper investigates recent advancements in sCT generation techniques, particularly those using machine learning (ML) and deep learning (DL). The review highlights the potential of these techniques to improve the efficiency and accuracy of sCT generation for use in RTP by improving patient care and reducing healthcare costs. The intricate web of sCT generation techniques is scrutinized critically, with clinical implications and technical underpinnings for enhanced patient care revealed.</p><p><strong>Purpose: </strong>This review aims to provide an overview of the most recent advancements in sCT generation from MRI with a particular focus of its use within RTP, emphasizing on techniques, performance evaluation, clinical applications, future research trends and open challenges in the field.</p><p><strong>Methods: </strong>A thorough search strategy was employed to conduct a systematic literature review across major scientific databases. Focusing on the past decade's advancements, this review critically examines emerging approaches introduced from 2013 to 2023 for generating sCT from MRI, providing a comprehensive analysis of their methodologies, ultimately fostering further advancement in the field. This study highlighted significant contributions, identified challenges, and provided an overview of successes within RTP. Classifying the identified approaches, contrasting their advantages and disadvantages, and identifying broad trends were all part of the review's synthesis process.</p><p><strong>Results: </strong>The review identifies various sCT generation approaches, consisting atlas-based, segmentation-based, multi-modal fusion, hybrid approaches, ML and DL-based techniques. These approaches are evaluated for image quality, dosimetric accuracy, and clinical acceptability. They are used for MRI-only radiation treatment, adaptive radiotherapy, and MR/PET attenuation correction. The review also highlights the diversity of methodologies for sCT generation, each with its own advantages and li","PeriodicalId":14989,"journal":{"name":"Journal of Applied Clinical Medical Physics","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2024-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142347140","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":"Evaluation of a non-metallic dual-port expander for intensity modulated proton therapy.","authors":"Kristen McConnell, Zachary Fellows, James Kraus, Mauricio Acosta, Joseph Panoff, Eduardo Pons, Alonso Gutierrez, Andrew Wroe","doi":"10.1002/acm2.14512","DOIUrl":"https://doi.org/10.1002/acm2.14512","url":null,"abstract":"<p><strong>Purpose: </strong>To provide a methodology for characterization of the technical properties of a newly developed non-metallic tissue expander for intensity modulated proton therapy.</p><p><strong>Methods: </strong>Three tissue expanders (AlloX2-Pro: plastic-dual port, AlloX2: metal-dual port, and Dermaspan: metal-single port) were deconstructed, CT-scanned, and modeled in RayStation12A. A 165 MeV single spot was used to create RayStation dose planes, and the integrated depth dose profiles were calculated and the DR90 extracted to predict water equivalent thickness (WET). These predictions were compared to measurements taken with an IBA Giraffe MLIC. Native, water, and fully modelled overrides were compared for the AlloX2 Pro to quantify differences in override choices. Geometric considerations between expanders were compared using a ray-tracing technique to contour the \"no-fly\" zone around metallic components using a clinical, three beam arrangement. Lastly, a planning and evaluation framework was provided using a single plan as an illustration.</p><p><strong>Results: </strong>The measured AlloX2-Pro WET values were within 0.22 cm of RayStation predictions while metallic values ranged from 0.08 to 0.46 cm. Using natively scanned density values for the AlloX2 Pro improved the discrepancy in WET between predicted and measured from -0.22 to -0.09 cm (drain) and from -0.17 to -0.12 cm (injection). The \"no-fly\" zone volume of all three beams reduced 95% between the AlloX2-Pro and Dermaspan, which geometrically allowed more uniform coverage behind the port and reduced need for beam modulation.</p><p><strong>Conclusion: </strong>The beam perturbation of the AlloX2-Pro is well modeled, but improved agreement with measured WET values was observed when utilizing native densities in calculations. The AlloX2 Pro can support beam arrangements that traverse the ports, which can enable simpler beam geometry and a reduction in dose modulation around the port to promote improved robustness and treatment delivery quality.</p>","PeriodicalId":14989,"journal":{"name":"Journal of Applied Clinical Medical Physics","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2024-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142307810","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":"Brain tumor segmentation by combining MultiEncoder UNet with wavelet fusion","authors":"Yuheng Pan, Haohan Yong, Weijia Lu, Guoyan Li, Jia Cong","doi":"10.1002/acm2.14527","DOIUrl":"https://doi.org/10.1002/acm2.14527","url":null,"abstract":"Background and objectiveAccurate segmentation of brain tumors from multimodal magnetic resonance imaging (MRI) holds significant importance in clinical diagnosis and surgical intervention, while current deep learning methods cope with situations of multimodal MRI by an early fusion strategy that implicitly assumes that the modal relationships are linear, which tends to ignore the complementary information between modalities, negatively impacting the model's performance. Meanwhile, long‐range relationships between voxels cannot be captured due to the localized character of the convolution procedure.MethodAiming at this problem, we propose a multimodal segmentation network based on a late fusion strategy that employs multiple encoders and a decoder for the segmentation of brain tumors. Each encoder is specialized for processing distinct modalities. Notably, our framework includes a feature fusion module based on a 3D discrete wavelet transform aimed at extracting complementary features among the encoders. Additionally, a 3D global context‐aware module was introduced to capture the long‐range dependencies of tumor voxels at a high level of features. The decoder combines fused and global features to enhance the network's segmentation performance.ResultOur proposed model is experimented on the publicly available BraTS2018 and BraTS2021 datasets. The experimental results show competitiveness with state‐of‐the‐art methods.ConclusionThe results demonstrate that our approach applies a novel concept for multimodal fusion within deep neural networks and delivers more accurate and promising brain tumor segmentation, with the potential to assist physicians in diagnosis.","PeriodicalId":14989,"journal":{"name":"Journal of Applied Clinical Medical Physics","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142267021","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":"Long‐term stability of a PTW 34070 large‐area parallel ionization chamber in clinical proton scanning beams","authors":"Masashi Yamanaka, Yutaro Mori, Kazuki Matsumoto, Shunsuke Moriya, Akihiro Yamano, Takahiro Shimo, Ryosuke Shirata, Kazunori Nitta, Hironori Nagata, Koichi Tokuuye","doi":"10.1002/acm2.14525","DOIUrl":"https://doi.org/10.1002/acm2.14525","url":null,"abstract":"PurposeIn the modeling of beam data for proton therapy planning systems, absolute dose measurements are performed utilizing a Bragg peak chamber (BPC), which is a parallel‐plate ionization chamber. The long‐term stability of the BPC is crucial for ensuring accurate absolute dose measurement. The study aims to assess the long‐term stability of the BPC in clinical proton pencil beam scanning delivery.MethodsThe long‐term stability evaluation focused on the BPC‐Type 34070 (PTW Freiburg, Germany), utilizing clinical proton scanning beams from December 2022 to November 2023. Monthly investigations were conducted to evaluate the response and cross‐calibration factor of the BPC and a reference chamber, employing the spread‐out Bragg peak (SOBP) field. Additionally, assessments were made regarding the BPC's response to monoenergetic beams, along with an examination of the impact of polarity and ion recombination on the BPC.ResultsThe response and cross‐calibration factor of the BPC varied up to 1.9% and 1.8%, respectively, while the response of the reference chamber remained within a 0.5% range. The BPC's response to the mono‐energetic beams varied up to 2.0% across all energies, demonstrating similar variation trends in both the SOBP field and mono‐energetic beams. Furthermore, the variations in polarity and ion recombination effect remained stable within a 0.4% range throughout the year. Notably, the reproducibility of the BPC remained high for each measurement conducted, whether for the SOBP field or mono‐energetic beams, with a maximum deviation observed at 0.1%.ConclusionsThe response and cross‐calibration factor of the BPC demonstrated significant variations, with maximum changes of 1.9% and 1.8%, respectively. However, the reproducibility of the BPC remained consistently high for each measurement. It is recommended that when conducting absolute dose measurements using a BPC, its response should be compared and corrected against the reference chamber for each measurement.","PeriodicalId":14989,"journal":{"name":"Journal of Applied Clinical Medical Physics","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142266811","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":"New findings on clinical experience on surface‐guided radiotherapy for frameless non‐coplanar stereotactic radiosurgery treatments","authors":"Patricia Sánchez‐Rubio, Ruth Rodríguez‐Romero, María Pinto‐Monedero, Luis Alejo‐Luque, Jaime Martínez‐Ortega","doi":"10.1002/acm2.14510","DOIUrl":"https://doi.org/10.1002/acm2.14510","url":null,"abstract":"PurposeThe aim of this study was to assess the accuracy of a surface‐guided radiotherapy (SGRT) system for setup and intra‐fraction motion control in frameless non‐coplanar stereotactic radiosurgery (fSRS) using actual patient data immobilized with two different types of open‐faced masks and employing a novel SGRT systems settings.Methods and materialsForty‐four SRS patients were immobilized with two types of open‐faced masks. Sixty lesions were treated, involving the analysis of 68 cone‐beam scans (CBCT), 157 megavoltage (MV) images, and 521 SGRT monitoring sessions. The average SGRT translations/rotations and 3D vectors (MAG‐Trasl and MAG‐Rot) were compared with CBCT or antero‐posterior MV images for 0° table or non‐coplanar beams, respectively. The intrafraction control was evaluated based on the average shifts obtained from each monitoring session. To assess the association between the SGRT system and the CBCT, the two types of masks and the 3D vectors, a generalized estimating equations (GEE) regression analysis was performed. The Wilcoxon singed‐rank test for paired samples was performed to detect differences in couch rotation with longitudinal (LNG) and lateral (LAT) translations and/or yaw.ResultsThe average SGRT corrections were smaller than those detected by CBCT (≤0.5 mm and 0.1°), with largest differences in LNG and yaw. The GEE analysis indicated that the average MAG‐Trasl, obtained by the SGRT system, was not statistically different (<jats:italic>p</jats:italic> = 0.09) for both mask types, while, the MAG‐Rot was different (<jats:italic>p</jats:italic> = 0.01). For non‐coplanar beams, the Wilcoxon singed‐rank test demonstrated no significantly differences for the corrections (LNG, LAT, and yaw) for any table rotation except for LNG corrections at 65° (<jats:italic>p</jats:italic> = 0.04) and 75° (<jats:italic>p</jats:italic> = 0.03) table angle position; LAT shifts at 65° (<jats:italic>p</jats:italic> = 0.03) and 270° (<jats:italic>p</jats:italic> &lt; 0.001) table angle position, and yaw rotation at 30° (<jats:italic>p</jats:italic> = 0.02) table angle position. The average intrafraction motion was &lt; 0.1 mm and 0.1° for any table angle.ConclusionThe SGRT system used, along with the novel workflow performed, can achieve the setup and intra‐fraction motion control accuracy required to perform non‐coplanar fSRS treatments. Both masks ensure the accuracy required for fSRS while providing a suitable surface for monitoring.","PeriodicalId":14989,"journal":{"name":"Journal of Applied Clinical Medical Physics","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142267020","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":"Automated confidence estimation in deep learning auto‐segmentation for brain organs at risk on MRI for radiotherapy","authors":"Nouf M. Alzahrani, Ann M. Henry, Bashar M. Al‐Qaisieh, Louise J. Murray, Michael G. Nix","doi":"10.1002/acm2.14513","DOIUrl":"https://doi.org/10.1002/acm2.14513","url":null,"abstract":"PurposeWe have built a novel AI‐driven QA method called AutoConfidence (ACo), to estimate segmentation confidence on a per‐voxel basis without gold standard segmentations, enabling robust, efficient review of automated segmentation (AS). We have demonstrated this method in brain OAR AS on MRI, using internal and external (third‐party) AS models.MethodsThirty‐two retrospectives, MRI planned, glioma cases were randomly selected from a local clinical cohort for ACo training. A generator was trained adversarialy to produce internal autosegmentations (IAS) with a discriminator to estimate voxel‐wise IAS uncertainty, given the input MRI. Confidence maps for each proposed segmentation were produced for operator use in AS editing and were compared with “difference to gold‐standard” error maps. Nine cases were used for testing ACo performance on IAS and validation with two external deep learning segmentation model predictions [external model with low‐quality AS (EM‐LQ) and external model with high‐quality AS (EM‐HQ)]. Matthew's correlation coefficient (MCC), false‐positive rate (FPR), false‐negative rate (FNR), and visual assessment were used for evaluation. Edge removal and geometric distance corrections were applied to achieve more useful and clinically relevant confidence maps and performance metrics.ResultsACo showed generally excellent performance on both internal and external segmentations, across all OARs (except lenses). MCC was higher on IAS and low‐quality external segmentations (EM‐LQ) than high‐quality ones (EM‐HQ). On IAS and EM‐LQ, average MCC (excluding lenses) varied from 0.6 to 0.9, while average FPR and FNR were ≤0.13 and ≤0.21, respectively. For EM‐HQ, average MCC varied from 0.4 to 0.8, while average FPR and FNR were ≤0.37 and ≤0.22, respectively.ConclusionACo was a reliable predictor of uncertainty and errors on AS generated both internally and externally, demonstrating its potential as an independent, reference‐free QA tool, which could help operators deliver robust, efficient autosegmentation in the radiotherapy clinic.","PeriodicalId":14989,"journal":{"name":"Journal of Applied Clinical Medical Physics","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142266813","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":"Identifying dose constraints for the parotid ducts to minimize patient‐reported xerostomia: Is conventional mean dose sparing of the parotid glands sufficient?","authors":"Manal Ahmidouch, Shiva K. Das, Tong Zhu, Colette Shen, Lawrence B. Marks, Bhishamjit S. Chera, David V. Fried","doi":"10.1002/acm2.14515","DOIUrl":"https://doi.org/10.1002/acm2.14515","url":null,"abstract":"Background and purposeThe aim of this study was to identify dose constraints for the parotid ducts that limit patient‐reported xerostomia and estimate whether these constraints are achieved during conventional parotid gland sparing radiation therapy (PGS‐RT).Methods and materialsThirty‐eight oropharyngeal squamous cell carcinoma patients were treated prospectively on trial with MRI sialography‐guided parotid duct sparing radiation therapy (PDS‐RT). PDS‐RT explicitly minimizes dose to the parotid ducts in addition to PGS‐RT. Parotid duct dose constraints were identified that distinguished patients reporting high and low rates of xerostomia. Atlas‐based parotid duct contours were generated on a retrospective cohort of similar patients where the parotid ducts were not contoured nor explicitly spared to estimate the dose received by the parotid ducts during PGS‐RT.ResultsPatients whose intraglandular parotid ducts or total parotid ducts were planned for a mean dose &lt; 14 Gy and &lt; 12 Gy, respectively, reported significantly (<jats:italic>p</jats:italic> &lt; 0.01) lower rates of xerostomia at 6 and 12 months post‐RT. Patients receiving PDS‐RT had average total and intraglandular duct doses of 11.6 and 13.6 Gy, respectively, compared to an estimated 23.8 and 22.1 Gy, for those receiving PGS‐RT (<jats:italic>p</jats:italic> &lt; 0.01). Only 6% (6/108) and 20% (22/108) of patients receiving PGS‐RT were estimated to meet the dose constraints for the total ducts and intraglandular ducts, respectively.ConclusionParotid duct dose thresholds exist that appear to distinguish patients with and without xerostomia. The identified dose thresholds are frequently not met in PGS‐RT plans. In addition to reducing the dose to the parotid gland(s), parotid duct sparing may also further reduce xerostomia.","PeriodicalId":14989,"journal":{"name":"Journal of Applied Clinical Medical Physics","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142266809","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":"Improving access in medical physics residency programs for physicists with disabilities","authors":"Jessica M. Fagerstrom, Grace Eliason, Hania Al‐Hallaq, Brian A. Taylor, Muhammad Ramish Ashraf, Natalie Viscariello","doi":"10.1002/acm2.14518","DOIUrl":"https://doi.org/10.1002/acm2.14518","url":null,"abstract":"Within the landscape of medical physics education, residency programs are instrumental in imparting hands‐on training and experiential knowledge to early‐career physicists. Ensuring access to educational opportunities for physicists with disabilities is a legal, ethical, and pragmatic requirement for programs, considering that a significant proportion of the United States population has a disability. Grounded in conceptual frameworks of competency‐based medical education and the social model of disability, this work provides an introduction to some practical recommendations for medical physics residency programs. Strategies include embracing universal design principles, fostering partnerships with disability service offices, using inclusive language, developing and publicizing clear procedures for disclosing disabilities and requesting accommodations, and maintaining an overall commitment to equitable access to education. This work urges medical physics residency leadership to proactively move towards training environments that support the needs of residents across the spectrum of disability, highlighting why disability inclusion fundamentally enriches diversity.","PeriodicalId":14989,"journal":{"name":"Journal of Applied Clinical Medical Physics","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142269758","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":"Evaluation of deep learning based dose prediction in head and neck cancer patients using two different types of input contours","authors":"Masahide Saito, Noriyuki Kadoya, Yuto Kimura, Hikaru Nemoto, Ryota Tozuka, Keiichi Jingu, Hiroshi Onishi","doi":"10.1002/acm2.14519","DOIUrl":"https://doi.org/10.1002/acm2.14519","url":null,"abstract":"PurposeThis study evaluates deep learning (DL) based dose prediction methods in head and neck cancer (HNC) patients using two types of input contours.Materials and methodsSeventy‐five HNC patients undergoing two‐step volumetric‐modulated arc therapy were included. Dose prediction was performed using the AIVOT prototype (AiRato.Inc, Sendai, Japan), a commercial software with an HD U‐net‐based dose distribution prediction system. Models were developed for the initial plan (46 Gy/23Fr) and boost plan (24 Gy/12Fr), trained with 65 cases and tested with 10 cases. The 8‐channel model used one target (PTV) and seven organs at risk (OARs), while the 10‐channel model added two dummy contours (PTV ring and spinal cord PRV). Predicted and deliverable doses, obtained through dose mimicking on another radiation treatment planning system, were evaluated using dose‐volume indices for PTV and OARs.ResultsFor the initial plan, both models achieved approximately 2% prediction accuracy for the target dose and maintained accuracy within 3.2 Gy for OARs. The 10‐channel model outperformed the 8‐channel model for certain dose indices. For the boost plan, both models exhibited prediction accuracies of approximately 2% for the target dose and 1 Gy for OARs. The 10‐channel model showed significantly closer predictions to the ground truth for D50% and Dmean. Deliverable plans based on prediction doses showed little significant difference compared to the ground truth, especially for the boost plan.ConclusionDL‐based dose prediction using the AIVOT prototype software in HNC patients yielded promising results. While additional contours may enhance prediction accuracy, their impact on dose mimicking is relatively small.","PeriodicalId":14989,"journal":{"name":"Journal of Applied Clinical Medical Physics","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142269765","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":"Comparative assessment and QA measurement array validation of Monte Carlo and Collapsed Cone dose algorithms for small fields and clinical treatment plans","authors":"Guus B. Spenkelink, Sophie C. Huijskens, Jaap D. Zindler, Marc de Goede, Wilhelmus J. van der Star, Jaap van Egmond, Anna L. Petoukhova","doi":"10.1002/acm2.14522","DOIUrl":"https://doi.org/10.1002/acm2.14522","url":null,"abstract":"PurposeMany studies have demonstrated superior performance of Monte Carlo (MC) over type B algorithms in heterogeneous structures. However, even in homogeneous media, MC dose simulations should outperform type B algorithms in situations of electronic disequilibrium, such as small and highly modulated fields.Our study compares MC and Collapsed Cone (CC) dose algorithms in RayStation 12A. Under consideration are 6 MV and 6 MV flattening filter‐free (FFF) photon beams, relevant for VMAT plans such as head‐and‐neck and stereotactic lung treatments with heterogeneities, as well as plans for multiple brain metastases in one isocenter, involving highly modulated small fields. We aim to investigate collimator angle dependence of small fields and performance differences between different combinations of ArcCHECK configuration and dose algorithm.MethodsSeveral verification tests were performed, ranging from simple rectangular fields to highly modulated clinical plans. To evaluate and compare the performance of the models, the agreements between calculation and measurement are compared between MC and CC. Measurements include water tank measurements for test fields, ArcCHECK measurements for test fields and VMAT plans, and film dosimetry for small fields.Results and conclusionsIn very small or narrow fields, our measurements reveal a strong dependency of dose output to collimator angle for VersaHD with Agility MLC, reproduced by both dose algorithms.ArcCHECK results highlight a suboptimal agreement between measurements and MC calculations for simple rectangular fields when using inhomogeneous ArcCHECK images. Therefore, we advocate for the use of homogeneous phantom images, particularly for static fields, in ArcCHECK verification with MC.MC might offer performance benefits for more modulated treatment fields. In ArcCHECK results for clinical plans, MC performed comparable to CC for 6 MV. For 6 MV FFF and the preferred homogeneous phantom image, MC resulted in consistently better results (13%–64% lower mean gamma index) compared to CC.","PeriodicalId":14989,"journal":{"name":"Journal of Applied Clinical Medical Physics","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142266812","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}