Journal articles on the topic 'Automation, Planning Optimization, Radiotherapy, Breast'
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Purdie, Thomas G., Robert E. Dinniwell, Daniel Letourneau, Christine Hill, and Michael B. Sharpe. "Automated Planning of Tangential Breast Intensity-Modulated Radiotherapy Using Heuristic Optimization." International Journal of Radiation Oncology*Biology*Physics 81, no. 2 (October 2011): 575–83. http://dx.doi.org/10.1016/j.ijrobp.2010.11.016.
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Fan, J., J. Wang, Z. Zhang, and W. Hu. "EP-1537: Iterative dataset optimization in automated planning: implementation for breast radiotherapy." Radiotherapy and Oncology 123 (May 2017): S826. http://dx.doi.org/10.1016/s0167-8140(17)31972-2.
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Rossi, Maija, Eeva Boman, and Mika Kapanen. "Optimal selection of optimization bolus thickness in planning of VMAT breast radiotherapy treatments." Medical Dosimetry 44, no. 3 (2019): 266–73. http://dx.doi.org/10.1016/j.meddos.2018.10.001.
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Fan, Jiawei, Jiazhou Wang, Zhen Zhang, and Weigang Hu. "Iterative dataset optimization in automated planning: Implementation for breast and rectal cancer radiotherapy." Medical Physics 44, no. 6 (April 20, 2017): 2515–31. http://dx.doi.org/10.1002/mp.12232.
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Yin, Chuou, Peng Yang, Shengyuan Zhang, Shaoxian Gu, Ningyu Wang, Fengjie Cui, Jinyou Hu, Xia Li, Zhangwen Wu, and Chengjun Gou. "A self-adaptive prescription dose optimization algorithm for radiotherapy." Open Physics 19, no. 1 (January 1, 2021): 146–51. http://dx.doi.org/10.1515/phys-2021-0012.
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Abstract Purpose The aim of this study is to investigate an implementation method and the results of a voxel-based self-adaptive prescription dose optimization algorithm for intensity-modulated radiotherapy. Materials and methods The self-adaptive prescription dose optimization algorithm used a quadratic objective function, and the optimization engine was implemented using the molecular dynamics. In the iterative optimization process, the optimization prescription dose changed with the relationship between the initial prescription dose and the calculated dose. If the calculated dose satisfied the initial prescription dose, the optimization prescription dose was equal to the calculated dose; otherwise, the optimization prescription dose was equal to the initial prescription dose. We assessed the performance of the self-adaptive prescription dose optimization algorithm with two cases: a mock head and neck case and a breast case. Isodose lines, dose–volume histogram, and dosimetric parameters were compared between the conventional molecular dynamics optimization algorithm and the self-adaptive prescription dose optimization algorithm. Results The self-adaptive prescription dose optimization algorithm produces the different optimization results compared with the conventional molecular dynamics optimization algorithm. For the mock head and neck case, the planning target volume (PTV) dose uniformity improves, and the dose to organs at risk is reduced, ranging from 1 to 4%. For the breast case, the use of self-adaptive prescription dose optimization algorithm also leads to improvements in the dose distribution, with the dose to organs at risk almost unchanged. Conclusion The self-adaptive prescription dose optimization algorithm can generate an ideal clinical plan more effectively, and it could be integrated into a treatment planning system after more cases are studied.
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Haidar, Ali, Matthew Field, Vikneswary Batumalai, Kirrily Cloak, Daniel Al Mouiee, Phillip Chlap, Xiaoshui Huang, et al. "Standardising Breast Radiotherapy Structure Naming Conventions: A Machine Learning Approach." Cancers 15, no. 3 (January 17, 2023): 564. http://dx.doi.org/10.3390/cancers15030564.
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In progressing the use of big data in health systems, standardised nomenclature is required to enable data pooling and analyses. In many radiotherapy planning systems and their data archives, target volumes (TV) and organ-at-risk (OAR) structure nomenclature has not been standardised. Machine learning (ML) has been utilised to standardise volumes nomenclature in retrospective datasets. However, only subsets of the structures have been targeted. Within this paper, we proposed a new approach for standardising all the structures nomenclature by using multi-modal artificial neural networks. A cohort consisting of 1613 breast cancer patients treated with radiotherapy was identified from Liverpool & Macarthur Cancer Therapy Centres, NSW, Australia. Four types of volume characteristics were generated to represent each target and OAR volume: textual features, geometric features, dosimetry features, and imaging data. Five datasets were created from the original cohort, the first four represented different subsets of volumes and the last one represented the whole list of volumes. For each dataset, 15 sets of combinations of features were generated to investigate the effect of using different characteristics on the standardisation performance. The best model reported 99.416% classification accuracy over the hold-out sample when used to standardise all the nomenclatures in a breast cancer radiotherapy plan into 21 classes. Our results showed that ML based automation methods can be used for standardising naming conventions in a radiotherapy plan taking into consideration the inclusion of multiple modalities to better represent each volume.
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Sayed Omer, Hiba Baha Eldin. "Intensity modulated radiotherapy using Monte Carlo for routine postmastectomy radiotherapy." Polish Journal of Medical Physics And Engineering 18, no. 2 (June 1, 2012): 49–58. http://dx.doi.org/10.2478/v10013-012-0007-x.
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Radiotherapy given after mastectomy (PMRT) will reduce the risk of local recurrence by about two-thirds. Clinical and dosimetric trials were carried out using various techniques to optimize the treatments by maximizing the dose to the tumour and minimizing it to the healthy tissues at proximity. Different conventional techniques which have been studied suffer from important dose inhomogeneities due to the complex anatomy of the chest, which reduces the benefits from such treatments. Moreover, due to the heterogeneity of breast cancer, the response to therapy and a systematic approach to treatment cannot be derived and treatment regimens must be determined on a patient-by-patient basis. This is only possible if accurate and fast treatment planning systems are available. Intensity Modulated Radiotherapy (IMRT) allows delivering higher doses to the target volume and limits the doses to the surrounding tissues. The objective of this study is to test the feasibility of applying a Monte Carlo-based treatment planning system, Hyperion accurately in routine Intensity Modulated Radiotherapy (IMRT) postmastectomy. In order to use a treatment planning system for routine work it should prove to provide optimized dose delivery in a suitable time. Treatment planning for IMRT application to PMRT was performed using Hyperion. Constraints were set to deliver the prescribed dose to the target and minimize the dose to the organs at risk. Dose Volume Histograms (DVH) were used to evaluate the set up plans. Time taken to optimize the plan was measured. The target coverage was within the accepted values. Approximately 90% of the breast and 80% of the PTV received 45 Gy or above. The volume of the lung that received 40Gy was less than 10% and the volume that received 20Gy (V20) was less than 25%. The volume of the heart receiving 30 Gy (V30) or above was negligible. This indicates low NTCP of these organs. The time taken for optimization, showed it possible to apply Monte Carlo-based treatment-planning systems for patient-to-patient PMRT.
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Kraus, Kim Melanie, Johanna Winter, Yating Zhang, Mabroor Ahmed, Stephanie Elisabeth Combs, Jan Jakob Wilkens, and Stefan Bartzsch. "Treatment Planning Study for Microbeam Radiotherapy Using Clinical Patient Data." Cancers 14, no. 3 (January 28, 2022): 685. http://dx.doi.org/10.3390/cancers14030685.
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Microbeam radiotherapy (MRT) is a novel, still preclinical dose delivery technique. MRT has shown reduced normal tissue effects at equal tumor control rates compared to conventional radiotherapy. Treatment planning studies are required to permit clinical application. The aim of this study was to establish a dose comparison between MRT and conventional radiotherapy and to identify suitable clinical scenarios for future applications of MRT. We simulated MRT treatment scenarios for clinical patient data using an inhouse developed planning algorithm based on a hybrid Monte Carlo dose calculation and implemented the concept of equivalent uniform dose (EUD) for MRT dose evaluation. The investigated clinical scenarios comprised fractionated radiotherapy of a glioblastoma resection cavity, a lung stereotactic body radiotherapy (SBRT), palliative bone metastasis irradiation, brain metastasis radiosurgery and hypofractionated breast cancer radiotherapy. Clinically acceptable treatment plans were achieved for most analyzed parameters. Lung SBRT seemed the most challenging treatment scenario. Major limitations comprised treatment plan optimization and dose calculation considering the tissue microstructure. This study presents an important step of the development towards clinical MRT. For clinical treatment scenarios using a sophisticated dose comparison concept based on EUD and EQD2, we demonstrated the capability of MRT to achieve clinically acceptable dose distributions.
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Srivastava, Anoop Kumar, Avinav Bharati, Madhup Rastogi, Surendra Prasad Mishra, Rohini Khurana, Rahat Hadi, Ajeet Kumar Gandhi, and Lalatendu Mishra. "Evaluation of dosimetric implications of Pareto and constrained mode of optimization for Monaco TPS generated VMAT plans in post operated carcinoma of the left breast." Polish Journal of Medical Physics and Engineering 27, no. 1 (March 1, 2021): 11–18. http://dx.doi.org/10.2478/pjmpe-2021-0002.
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Abstract Intensity-modulated radiotherapy (IMRT) is being practiced for the last several years with a special approach for radiation therapy in post-mastectomy breast cancer patients. Meeting the cardiac dose constraints has always been a challenge during radiotherapy planning by both IMRT and VMAT (volumetric modulated arc therapy) of post-mastectomy left breast patients. With the advancement in IMRT planning techniques, it has been modified to VMAT with more degrees of freedom for modulation and is being utilised more frequently. This helps in obtaining a suitable plan for achieving both the dose homogeneity in target volume and dose constraints to Organ at Risk (OAR). 10 Patients with carcinoma of the left breast (post-mastectomy) were selected for this study. VMAT treatment plans for these patients were generated for 6 MV photons on the Monaco treatment planning system (TPS) using two types of optimization modes i.e. Pareto and Constrained mode available in Monaco TPS. For comparative dosimetric evaluation of the efficacy of these two types of optimization modes similar calculation algorithms, calculation grids, arcs, and beam sequencing parameters were used for generating treatment plans. The dosimetric quantities such as volume receiving more than 95% of the prescribed dose (V95), volume receiving more than 107% of the prescribed dose (V107) and Maximum dose (Dmax) for target volume, mean dose (Dmean) for heart, volume receiving more than 30 Gy (V30) volume receiving more than 20 Gy (V20) volume receiving more than 5 Gy (V5) for ipsilateral lung and total monitor units delivered were analysed for both optimization modes. A judicious mix of multiple planning parameters and variables using these two modes of optimization was applied and recorded. Both optimization modes yielded similar outcomes. However, Pareto mode has shown better coverage for planning target volume (PTV) with comparable doses to OARs.
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Casesnoves, Francisco. "RADIOTHERAPY GENETIC ALGORITHM PARETO-MULTIOBJECTIVE OPTIMIZATION OF BIOLOGICAL EFFECTIVE DOSE AND CLONOGENS MODELS FOR BREAST TUMOR IMPROVED TREATMENT." INTERNATIONAL JOURNAL OF MATHEMATICS AND COMPUTER RESEARCH 11, no. 01 (January 12, 2023): 3102–14. http://dx.doi.org/10.47191/ijmcr/v11i1.02.
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BED model (Biological Effective Dose) for Hyperfractionation TPO was optimized with Pareto-Multiobjective Genetic Algorithms (GA) software. Secondly, the NEffective (Effective Tumor Population Clonogens Number) model optimization for breast cancer clonogens parameters determination in TPO (Treatment Planning Optimization) is carried out with 3D Graphical and Interior Optimization methods. BED model (Biological Effective Dose) for Hyperfractionation TPO was optimized with Pareto-Multiobjective GA software. Results comprise imaging process series and numerical values of NEffective model for breast cancer parameters. Additional results demonstrate Pareto-Multiobjective GA BED model both with Pareto-Optimal Front graphics, charts and numerical dose fractionation datasets. For all these findings, supplementary new recent applications with 3D Isodoses TPO with AAA (Anisotropic Analytic Algorithm) model wedge filters dose delivery is shown. Modern RT treatment breast cancer, and tumors in general for Fractionation-dose protocols are explained.
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Casesnoves, Francisco. "RADIOTHERAPY GENETIC ALGORITHM PARETO-MULTIOBJECTIVE OPTIMIZATION OF BIOLOGICAL EFECTIVE DOSE AND CLONOGENS MODELS FOR HEAD AND NECK TUMOR ADVANCED TREATMENT." INTERNATIONAL JOURNAL OF MATHEMATICS AND COMPUTER RESEARCH 11, no. 01 (January 30, 2023): 3156–77. http://dx.doi.org/10.47191/ijmcr/v11i1.08.
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BED model (Biological Effective Dose) for Head and Neck tumors Hyperfractionation TPO was optimizedwith Pareto-Multiobjective (PMO) Genetic Algorithms (GA) software. Artificial Intelligence (AI) with GA is applied on Radiotherapy Treatment Planning Optimization (TPO). Secondly, the review of NEffective (Effective Tumor Population Clonogens Number) model optimization for breast cancer clonogens parameters determination in TPO (Treatment Planning Optimization) is got with 3D Graphical and Interior Optimization methods. Results series comprise PMO imaging process sequences and numerical values of PMO and NEffective model for Head and Neck cancer parameters. Further results demonstrate PMO-GA BED model both with Pareto-Optimal Front detailed graphics, charts and numerical dose fractionation datasets. Supplemental review of new recent applications with 3D Isodoses TPO with AAA (Anisotropic Analytic Algorithm) model wedge filters dose delivery is shown. Advanced RT Head and Neck cancer TPO, and tumors in general for Fractionation-dose protocols are explained.
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Vargas-Bedoya, Eliseo, Juan Carlos Rivera, Maria Eugenia Puerta, Aurelio Angulo, Niklas Wahl, and Gonzalo Cabal. "Contour Propagation for Radiotherapy Treatment Planning Using Nonrigid Registration and Parameter Optimization: Case Studies in Liver and Breast Cancer." Applied Sciences 12, no. 17 (August 26, 2022): 8523. http://dx.doi.org/10.3390/app12178523.
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Radiotherapy treatments are carried out using computerized axial tomography. In radiation therapy planning, the radiation oncologist must do a manual segmentation of volumes of interest to delineate the organs that should be irradiated. This way of carrying out the process generates long execution times and introduces a subjective component. In this study, a contour-propagation algorithm is formulated to automate the segmentation, based on elastic registration or nonrigid demon registration. A heuristic algorithm to find the parameters that optimize the registration is also proposed. The parameters found along with the contour-propagation algorithm are able to estimate contours of scans with Dice similarity coefficients (DSC) greater than 0.92 and maintain stability with B-spline registration, which takes in the parameters found as input. The study allows for validating the results using the correlation coefficient (CC) to compare the similarity between the voxels’ gray-scale intensity of the estimated tomography and the original tomography, obtaining values greater than 0.96. These values were validated under medical criteria and applied to liver and breast CT scans, indicating good performance for radiation therapy planning.
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Castriconi, R., P. Esposito, P. Mangili, M. Pasetti, A. Fodor, N. Di Muzio, A. del Vecchio, and C. Fiorino. "Knowledge-based (KB) automatic plan optimization can replace manual planning in tangential field irradiation for right breast cancer radiotherapy." Physica Medica 92 (December 2021): S60. http://dx.doi.org/10.1016/s1120-1797(22)00128-4.
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Çelen, Yonca Yahşi, and Atilla Evcin. "Comparison of Different Algorithms in the Radiotherapy Plans of Breast Cancer." ITM Web of Conferences 22 (2018): 01048. http://dx.doi.org/10.1051/itmconf/20182201048.
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It is aimed to evaluate portal dosimetry results of planned breast cancer patients with intensity-modulated radiotherapy (YART) of Anisotropic Analytical Algorithm (AAA) and Pencil Beam Convolution (PBC) dose calculation algorithms. The plans of 10 treated patients will receive 6 MV photon energy and a total of 25 fractions of 50 Gray dose using the inverse YART technique, which is reverse planned in the Eclipse (ver.13.6) treatment planning system with Varian Trilogy Linear Accelerator prescribing. For each plan, dose was calculated after optimization using PBC and then AAA algorithms. The quality controls of the plans were made using the Electronic Portal Imaging Device (EPID) by creating individual verification plans for each algorithm. In addition, the maximum and average dose values in the target volume were compared in inverse YART plans calculated using PBC and AAA. When treatment plans generated by AAA and PBC dose calculation algorithms are analyzed using EPID, for the PBC algorithm, the mean values of VArea and VAvg are 98.15 ± 1.07, 0.40 ± 0.048 and 98.72 ± 1.13, 0.37 ± 0.051, respectively, for the AAA algorithm. The PTV Dmax value for the PBC algorithm is 109.3 ± 1.09 and the DAvg value is 101.7 ± 0.51. For the AAA algorithm, the PTV Dmax value is 110.6 ± 1.12 and the DAvg value is 102.9 ± 0.62. When the mean values of portal dosimetry VArea and VAvg evaluated using PBC and AAA algorithms were compared, the differences between the algorithms were not statistically significant (p> 0.05). Differences between the algorithms for PTV Dmax and DAvg values are not statistically significant (p> 0.05).
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Qiu, Jianjian, Shujun Zhang, Bo Lv, and Xiangpeng Zheng. "Cardiac Dose Control and Optimization Strategy for Left Breast Cancer Radiotherapy With Non-Uniform VMAT Technology." Technology in Cancer Research & Treatment 20 (January 2021): 153303382110537. http://dx.doi.org/10.1177/15330338211053752.
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Purpose: A novel in-house technology “Non-Uniform VMAT (NU-VMAT)” was developed for automated cardiac dose reduction and treatment planning optimization in the left breast radiotherapy. Methods: The NU-VMAT model based on IGM (gantry MLC Movement coefficient index) was established to optimize the volumetric modulated arc therapy (VMAT) MLC movement and modulation intensity in certain gantry angles. The ESAPI embedded in Eclipse® was employed to connect TPS and the optimization program via I/O relevant DICOM RT files. The adjuvant whole-breast radiotherapy of 14 patients with left breast cancer was replanned using our NU-VMAT technology in comparison with VMAT and IMRT technology. Dosimetric parameters including D1%, D99%, and Dmean of PTV, V5, V10, and V20 of ipisilateral lung, V5, D20, D30, and Dmean of heart, monitor units (MUs), and delivery time derived from IMRT, VMAT, and NU-VMAT plans were evaluated for plan quality and delivery efficiency. The quality assurance (QA) was conducted using both point-dose and planar-dose measurements for all treatment plans. Results: The IGM−NU−VMAT curves with plan optimization (range from 50% to 147%) were converged more significantly than IGM-VMAT curves (range from 0% to 297%). The dose distribution requirements of the target and normal tissues could be met using IMRT, VMAT, or NU-VMAT; the lowest Dmean was achieved in NU-VMAT plans (5.38 ± 0.46 Gy vs 5.63 ± 0.61 Gy in IMRT and 7.95 ± 0.52 Gy in VMAT plans). Statistically significant differences were found in terms of delivery time and MU when comparing IMRT with VMAT and NU-VMAT plans ( P < .05). In comparison with IMRT plans, the MU and delivery time in NU-VMAT plans dramatically decreased by 69.8% and 28.4%, respectively. Moreover, NU-VMAT plans showed a high gamma passing rate (96.5% ± 1.11) in plane dose verification and minimal dose difference (2.4% ± 0.19) in point absolute dose verification. Conclusion: Our non-uniform VMAT facilitated the treatment strategy optimization for left breast cancer radiotherapy with dosimetric advantage in cardiac dose reduction and delivery efficiency in comparison with the conventional VMAT and IMRT.
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Diklic, Ana, Doris Segota, Ingrid Belac-Lovasic, and Slaven Jurkovic. "An assessment of dose indicators for computed tomography localization procedures in radiation therapy at the University Hospital Rijeka." Nuclear Technology and Radiation Protection 33, no. 3 (2018): 301–6. http://dx.doi.org/10.2298/ntrp1803301d.
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The computed tomography has become a standard tool in radiation therapy treatment planning. Additionally, there is a growing awareness of the dose delivered to the part of the body outside the target volume. The ionizing radiation carries a stochastic risk of malignancy, therefore, the doses should be kept as low as reasonably achievable in order to provide an adequate information needed for the radiotherapy planning. The objective of this work was to set up the initial diagnostic reference levels and correlate to the image quality that would be used in the future optimization of localization scans. To quantify the doses from computed tomography localization scans at the University Hospital Rijeka, local diagnostic reference levels were established for five most common procedures of different anatomical regions; head, head and neck, pelvis, breast and thorax. The Computed Tomography Dose Index volumetric and the Dose-Length Product were used as dose indicators and scanning parameters were also recorded. The image quality assessment was performed for each set of images. The results were compared to the seldom published data in order to compare the clinical practice. The image quality for almost all of the body regions are scored as acceptable in average but require improvement. It is shown that the optimization of radiotherapy protocols is required. Therefore, these results will be used as a guideline for that process. The establishment of the national diagnostic reference levels for computed tomography localization procedures in radiation therapy is the next step and is currently an ongoing process.
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Chomal, Manish, Minaal Iyer, Ananth Kalimurthy, Joshua Sahay, and Sushanta Banik. "Abstract P1-10-15: Concious sparing of contralateral thyroid lobe in Ca Breast patients receiving post mastectomy radiotherapy by IMRT technique – A single institution dosimetric study." Cancer Research 83, no. 5_Supplement (March 1, 2023): P1–10–15—P1–10–15. http://dx.doi.org/10.1158/1538-7445.sabcs22-p1-10-15.
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Abstract Purpose/Objective(s): The purpose of this paper is to report the dosimetric effects of conscious sparing of contralateral lobe of thyroid gland in carcinoma breast patient receiving locoregional radiation by tangential beam Intensity Modulated radiotherapy technique. Materials/Methods: Treatment plans of 20 Ca Breast patients, who received post mastectomy adjuvant locoregional radiotherapy, were evaluated. Since October 2021 we adopted a department protocol of conscious sparing of contralateral thyroid in breast radiotherapy. 10 of these had conscious sparing of contralateral thyroid (group A) whereas 10 of old plans were evaluated when C/L thyroid were not given constraints & are being passively spared due to location on contralateral/non treatment side of neck (group B). Treatment planning was done using tangential beam (6 MV) IMRT in Eclipse 13.7 TPS in all of these patients. All of these patients received treatment to chest wall & SCF. RTOG contouring guidelines were followed in all the patients. Prescription Dose was 40Gy in 15# for both groups. The best treatment plans were selected ensuring 95% PTV dose coverage and acceptable dose to OARs. Uniform contouring, plan optimization & evaluation protocols were followed for all of these patients. Results: The mean thyroid volume in group A is 4.30cc & in group B is 3.99cc which is not statistically different (P value -0.639) The mean dose of thyroid in group A is 7.98Gy whereas in group B it is 17.00Gy which is spastically significant (P value – 0.000003). Comparison of mean dose to contralateral lobe (in Gy) between the two groups Groups No. Mean ± SD ‘t’ value P value Thyroid dose with constraint 10 7.98±1.46 -6.702, df=18 0.000003* Thyroid dose without constraint 10 17.00±3.99 Unpaired ‘t’ test applied. P value = 0.000003, Significant Conclusion: OARs present on contralateral side are passively spared due to the location. This often results in a tendency of not actively prescribing constraints to these. This study emphasizes that conscious sparing of contralateral Thyroid lobe can further reduce the dose to significant levels. This reduction can preserve thyroid function further. Further clinical trials are required to corroborate this dosimetric gain with clinical thyroid function preservation. Citation Format: Manish Chomal, Minaal Iyer, Ananth Kalimurthy, Joshua Sahay, Sushanta Banik. Concious sparing of contralateral thyroid lobe in Ca Breast patients receiving post mastectomy radiotherapy by IMRT technique – A single institution dosimetric study [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P1-10-15.
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Vologdina, I. V., E. G. Poroshina, R. M. Zhabina, and A. A. Stanzhevsky. "Prevalence of risk factors of cardiovascular complications in elderly women with left breast cancer." HERALD of North-Western State Medical University named after I.I. Mechnikov 11, no. 3 (November 18, 2019): 85–92. http://dx.doi.org/10.17816/mechnikov201911385-92.
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The purpose to study the risk factors for elderly women with left breast cancer at the stage of chemotherapy and radiotherapy in the context of daily clinical practice for early detection of possible cardiovascular complications and optimization of therapy.
Material and methods. 69 women with HER2 neu negative left breast cancer without severe cardiovascular disease were examined. The first group included 39 elderly patients (67.7 3.8 years). The second group consisted of 34 middle-aged patients (49.8 5.7 years). In addition to the risk assessment according to the Score scale, additional factors including psychosocial factors were studied. The examination was carried out before the start of treatment, after the end of the course of doxorubicin in a cumulative dose of up to 360 mg/m2 and after the completion of radiation therapy 3D conformal radiation therapy SOD 39 Gr.
Results. In elderly patients, risk factors such as obesity, increased cholesterol, and hypertension were significantly more common. In both study groups, low physical activity was revealed associated with both cancer itself and the treatment. All examined patients had moderate reactive anxiety on the Spielberger-Hanin scale. Elderly patients showed high level of personal anxiety; the number of points scored 49.3 3.6. According to the Score scale, a moderate risk was detected in 18 (58.1%) and a high risk in 13(41.9%) elderly patients. After doxorubicin treatment asymptomatic systolic dysfunction was detected in 8 (20.5%) patients (decrease in EF50%), 21 (75%) diastolic dysfunction with relaxation slowdown (E/A1). In 9 (23.1%) of the women without reducing the EF fibrotic changes in the myocardium of the left ventricle was revealed. In 8 (20.5%) women a thickening of the pericardial layer was revealed.
Conclusion. The findings suggest the need for a personalized approach and assessment of risk factors in patients of different age groups with left breast cancer at the stage of preparation and conduct of chemoradiotherapy. This highlights the need for enhanced history collection and consideration of not only key but also additional risk factors. The results of the study can be used in the work of practical health care institutions for the planning, development, implementation and control of chemoradiography safety in terms of preventing cardiovascular complications.
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Krishnamurthy, Revathy, Naveen Mummudi, Jayant Sastri Goda, Supriya Chopra, Ben Heijmen, and Jamema Swamidas. "Using Artificial Intelligence for Optimization of the Processes and Resource Utilization in Radiotherapy." JCO Global Oncology, no. 8 (November 2022). http://dx.doi.org/10.1200/go.21.00393.
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The radiotherapy (RT) process from planning to treatment delivery is a multistep, complex operation involving numerous levels of human-machine interaction and requiring high precision. These steps are labor-intensive and time-consuming and require meticulous coordination between professionals with diverse expertise. We reviewed and summarized the current status and prospects of artificial intelligence and machine learning relevant to the various steps in RT treatment planning and delivery workflow specifically in low- and middle-income countries (LMICs). We also searched the PubMed database using the search terms (Artificial Intelligence OR Machine Learning OR Deep Learning OR Automation OR knowledge-based planning AND Radiotherapy) AND (list of Low- and Middle-Income Countries as defined by the World Bank at the time of writing this review). The search yielded a total of 90 results, of which results with first authors from the LMICs were chosen. The reference lists of retrieved articles were also reviewed to search for more studies. No language restrictions were imposed. A total of 20 research items with unique study objectives conducted with the aim of enhancing RT processes were examined in detail. Artificial intelligence and machine learning can improve the overall efficiency of RT processes by reducing human intervention, aiding decision making, and efficiently executing lengthy, repetitive tasks. This improvement could permit the radiation oncologist to redistribute resources and focus on responsibilities such as patient counseling, education, and research, especially in resource-constrained LMICs.
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Shan, Zhirui. "Dosimetric Comparison of the Lung Dose on the Affected Side in Radiotherapy after Breast Cancer Breast-Conserving Therapy Based on Two Subfield Optimization Methods in Monaco Planning System." Journal of Clinical Medicine Research 2, no. 2 (June 25, 2021). http://dx.doi.org/10.32629/jcmr.v2i2.362.
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Objective — To conduct comparison of the quantity difference of different segmentation optimization methods in Monaco planning system on the affected lung in radiotherapy after breast cancer breast-conserving therapy. Methods — 10 cases with breast cancer after breast-conserving surgery were selected with the prescription dose of 50GY/25F. In each case, volume modulated arc therapy (VMAT) based double arc distribution mode was adopted, and the same optimization parameters and functions were set accordingly. After completion of flux optimization, automatic weight optimization method and manual weight optimization method were adopted for optimization respectively. When the similar dose distribution of the target volume was obtained and the dose of the organ at risk (OAR) was satisfied, the dose of the affected lung obtained by the two optimization methods was compared. Results — When similar target coverage and other organs at risk met the prescribed conditions, the affected lung received by the manual weight optimization method was significantly lower than that by the automatic weight optimization method, and the results were statistically significant. Conclusion — The manual weight optimization method used in VMAT program after breast conserving surgery can effectively reduce the lung volume on the affected side and the probability of radiation pneumonia can be reduced.
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Oonsiri, Puntiwa, Chonnipa Nantavithya, Chawalit Lertbutsayanukul, Thanaporn Sarsitthithum, Mananchaya Vimolnoch, Tanawat Tawonwong, and Kitwadee Saksornchai. "Dosimetric evaluation of photons versus protons in postmastectomy planning for ultrahypofractionated breast radiotherapy." Radiation Oncology 17, no. 1 (January 29, 2022). http://dx.doi.org/10.1186/s13014-022-01992-w.
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Abstract Background Ultrahypofractionation can shorten the irradiation period. This study is the first dosimetric investigation comparing ultrahypofractionation using volumetric arc radiation therapy (VMAT) and intensity-modulated proton radiation therapy (IMPT) techniques in postmastectomy treatment planning. Materials and methods Twenty postmastectomy patients (10-left and 10-right sided) were replanned with both VMAT and IMPT techniques. There were four scenarios: left chest wall, left chest wall including regional nodes, right chest wall, and right chest wall including regional nodes. The prescribed dose was 26 Gy(RBE) in 5 fractions. For VMAT, a 1-cm bolus was added for 2 in 5 fractions. For IMPT, robust optimization was performed on the CTV structure with a 3-mm setup uncertainty and a 3.5% range uncertainty. This study aimed to compare the dosimetric parameters of the PTV, ipsilateral lung, contralateral lung, heart, skin, esophageal, and thyroid doses. Results The PTV-D95 was kept above 24.7 Gy(RBE) in both VMAT and IMPT plans. The ipsilateral lung mean dose of the IMPT plans was comparable to that of the VMAT plans. In three of four scenarios, the V5 of the ipsilateral lung in IMPT plans was lower than in VMAT plans. The Dmean and V5 of heart dose were reduced by a factor of 4 in the IMPT plans of the left side. For the right side, the Dmean of the heart was less than 1 Gy(RBE) for IMPT, while the VMAT delivered approximately 3 Gy(RBE). The IMPT plans showed a significantly higher skin dose owing to the lack of a skin-sparing effect in the proton beam. The IMPT plans provided lower esophageal and thyroid mean dose. Conclusion Despite the higher skin dose with the proton plan, IMPT significantly reduced the dose to adjacent organs at risk, which might translate into the reduction of late toxicities when compared with the photon plan.
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Chau, Oi-Wai, Hatim Fakir, Michael Lock, Robert Dinniwell, Francisco Perera, Abigail Erickson, and Stewart Gaede. "Dosimetric Planning Comparison for Left-Sided Breast Cancer Radiotherapy: The Clinical Feasibility of Four-Dimensional-Computed Tomography-Based Treatment Planning Optimization." Cureus, May 6, 2022. http://dx.doi.org/10.7759/cureus.24777.
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Chen, Wei, Yixin Lu, Liangfei Qiu, and Subodha Kumar. "Designing Personalized Treatment Plans for Breast Cancer." Information Systems Research, August 9, 2021. http://dx.doi.org/10.1287/isre.2021.1002.
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Breast cancer remains the leading cause of cancer deaths among women around the world. Contemporary treatment for breast cancer is complex and involves highly specialized medical professionals collaborating in a series of information-intensive processes. This poses significant challenges to optimization of treatment plans for individual patients. We propose a novel framework that enables personalization and customization of treatment plans for early stage breast cancer patients undergoing radiotherapy. Using a series of simulation experiments benchmarked with real-world clinical data, we demonstrate that the treatment plans generated from our proposed framework consistently outperform those from the existing practices in balancing the risk of local tumor recurrence and radiation-induced adverse effects. Our research sheds new light on how to combine domain knowledge and patient data in developing effective decision-support tools for clinical use. Although our research is specifically geared toward radiotherapy planning for breast cancer, the design principles of our framework can be applied to the personalization of treatment plans for patients with other chronic diseases that typically involve complications and comorbidities.
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Redapi, L., L. Rossi, L. Marrazzo, J. J. Penninkhof, S. Pallotta, and B. Heijmen. "Comparison of volumetric modulated arc therapy and intensity-modulated radiotherapy for left-sided whole-breast irradiation using automated planning." Strahlentherapie und Onkologie, August 5, 2021. http://dx.doi.org/10.1007/s00066-021-01817-x.
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Abstract Background Published treatment technique comparisons for postoperative left-sided whole breast irradiation (WBI) with deep-inspiration breath-hold (DIBH) are scarce, small, and inconclusive. In this study, fully automated multi-criterial plan optimization, generating a single high-quality, Pareto-optimal plan per patient and treatment technique, was used to compare for a large patient cohort 1) intensity modulated radiotherapy (IMRT) with two tangential fields and 2) volumetric modulated arc therapy (VMAT) with two small tangential subarcs. Materials and methods Forty-eight randomly selected patients recently treated with DIBH and 16 × 2.66 Gy were included. The optimizer was configured for the clinical planning protocol. Comparisons between IMRT and VMAT included dosimetric plan parameters, estimated excess relative risks (ERR) for toxicities, delivery times, MUs, and deliverability accuracy at a linac. Results The automatically generated IMRT and VMAT plans applied in this study were similar or higher in quality than the manually generated clinical plans. For equal PTVin V95% (98.4 ± 0.9%), VMAT had significant advantages compared to IMRT regarding breast dose homogeneity and doses in heart and ipsilateral lung, at the cost of some minor deteriorations for contralateral breast (few cases with larger deteriorations) and lung. Conformality improved from 1.38 to 1.18 (p < 0.001). With VMAT, ERR for major coronary events and ipsilateral lung tumors were reduced by 3% (range: −1–12%) and 16% (range: −3–38%), respectively. MUs and delivery times were higher for VMAT. There were no statistical differences in γ passing rates. Conclusion For WBI in conservative therapy of left-sided breast patients treated with DIBH, VMAT with two tangential subarcs was generally dosimetrically superior to IMRT with two tangential static fields. Results need confirmation by robustness analyses.
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Chang, Sheng, Gang Liu, Lewei Zhao, Joshua T. Dilworth, Weili Zheng, Saada Jawad, Di Yan, et al. "Feasibility study: spot-scanning proton arc therapy (SPArc) for left-sided whole breast radiotherapy." Radiation Oncology 15, no. 1 (October 7, 2020). http://dx.doi.org/10.1186/s13014-020-01676-3.
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Abstract Background This study investigated the feasibility and potential clinical benefit of utilizing a new proton treatment technique: Spot-scanning proton arc (SPArc) therapy for left-sided whole breast radiotherapy (WBRT) to further reduce radiation dose to healthy tissue and mitigate the probability of normal tissue complications compared to conventional intensity modulated proton therapy (IMPT). Methods Eight patients diagnosed with left-sided breast cancer and treated with breast-preserving surgery followed by whole breast irradiation without regional nodal irradiation were included in this retrospective planning. Two proton treatment plans were generated for each patient: vertical intensity-modulated proton therapy used for clinical treatment (vIMPT, gantry angle 10°–30°) and SPArc for comparison purpose. Both SPArc and vIMPT plans were optimized using the robust optimization of ± 3.5% range and 5 mm setup uncertainties. Root-mean-square deviation dose (RMSD) volume histograms were used for plan robustness evaluation. All dosimetric results were evaluated based on dose-volume histograms (DVH), and the interplay effect was evaluated based on the accumulation of single-fraction 4D dynamic dose on CT50. The treatment beam delivery time was simulated based on a gantry rotation with energy-layer-switching-time (ELST) from 0.2 to 5 s. Results The average D1 to the heart and LAD were reduced to 53.63 cGy and 82.25 cGy compared with vIMPT 110.38 cGy (p = 0.001) and 170.38 cGy (p = 0.001), respectively. The average V5Gy and V20Gy of ipsilateral lung was reduced to 16.77% and 3.07% compared to vIMPT 25.56% (p = 0.001) and 4.68% (p = 0.003). Skin3mm mean and maximum dose were reduced to 3999.38 cGy and 4395.63 cGy compared to vIMPT 4104.25 cGy (p = 0.039) and 4411.63 cGy (p = 0.043), respectively. A significant relative risk reduction (RNTCP = NTCPSPArc/NTCPvIMPT) for organs at risk (OARs) was obtained with SPArc ranging from 0.61 to 0.86 depending on the clinical endpoint. The RMSD volume histogram (RVH) analysis shows SPArc provided better plan robustness in OARs sparing, including the heart, LAD, ipsilateral lung, and skin. The average estimated treatment beam delivery times were comparable to vIMPT plans when the ELST is about 0.5 s. Conclusion SPArc technique can further reduce dose delivered to OARs and the probability of normal tissue complications in patients treated for left-sided WBRT.
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Guyer, Gian, Silvan Mueller, Carole Koechli, Daniel Frei, Werner Volken, Jenny Bertholet, Paul-Henry Mackeprang, et al. "Enabling non-isocentric dynamic trajectory radiotherapy by integration of dynamic table translations." Physics in Medicine & Biology, July 25, 2022. http://dx.doi.org/10.1088/1361-6560/ac840d.
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Abstract Objective: The purpose of this study is to develop a treatment planning process (TPP) for non-isocentric dynamic trajectory radiotherapy (DTRT) using dynamic gantry rotation, collimator rotation, table rotation, longitudinal, vertical and lateral table translations and intensity modulation and to validate the dosimetric accuracy. Approach: The TPP consists of two steps. First, a path describing the dynamic gantry rotation, collimator rotation and dynamic table rotation and translations is determined. Second, an optimization of the intensity modulation along the path is performed. We demonstrate the TPP for three use cases. First, a non-isocentric DTRT plan for a brain case is compared to an isocentric DTRT plan in terms of dosimetric plan quality and delivery time. Second, a non-isocentric DTRT plan for a craniospinal irradiation (CSI) case is compared to a multi-isocentric intensity modulated radiotherapy (IMRT) plan. Third, a non-isocentric DTRT plan for a bilateral breast case is compared to a multi-isocentric volumetric modulated arc therapy (VMAT) plan. The non-isocentric DTRT plans are delivered on a TrueBeam in developer mode and their dosimetric accuracy is validated using radiochromic films. Main results: The non-isocentric DTRT plan for the brain case is similar in dosimetric plan quality and delivery time to the isocentric DTRT plan but is expected to reduce the risk of collisions. The DTRT plan for the CSI case shows similar dosimetric plan quality while reducing the delivery time by 45% in comparison with the IMRT plan. The DTRT plan for the breast case showed better treatment plan quality in comparison with the VMAT plan. The gamma passing rates between the measured and calculated dose distributions are higher than 95% for all three plans. Significance: The versatile benefits of non-isocentric DTRT are demonstrated with three use cases, namely reduction of collision risk, reduced setup and delivery time and improved dosimetric plan quality.