Littérature scientifique sur le sujet « Automation, Planning Optimization, Radiotherapy, Breast »

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.

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.

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.

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.

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.

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.

This work explored effective strategies to automatize radiotherapy planning for whole breast irradiation, mimicking the classical tangential fields (TF) technique. An original arc technique (named Virtual Tangential-fields Arc Therapy, ViTAT) was first optimized to mimic TF. Then, using the commercial software RapidPlan (Varian Medical System, Inc), dose distributions of past clinical plans were used to train Knowledge-Based models: after proper validation, models were translated into individually-optimized templates for automatic plan optimization: ViTAT clinically replaced manual TF, also replacing the manual choice of beam angles. This approach was extended to the TomoDirect approach, delivering TF-like treatments with the Tomotherapy machine: the clinical implementation is currently on going.

Radiation therapy makes use of ionization radiation to eliminate in a controlled way tumours cells sparing as much as possible the normal tissues. The treatment is delivered to the patient during several sessions according to a personalized plan optimized a priori by a planner in a treatment plan system. The most advanced planning techniques, such as inverse planning optimization of static beams or volumetric arcs, require the use of dose optimization algorithms, that allow the planner to find one or more solutions that satisfies as much as possible the prescription dose for the target and the tolerance dose criteria for the normal tissues. Treatment plan automation based on multicriteria optimization algorithms generates treatment planning solutions with equivalent dose distribution quality and reduced the interaction from the planner. The quality of the dose distribution can even be substantially enhanced when beam angle optimization and arc trajectory optimization algorithms are incorporated in plan optimization. The main purpose of this work is to contribute to the treatment planning automation process by developing new plan assessment tools and use them for testing new directions/trajectory optimization algorithms. To support clinical decision-making, a graphical method incorporating the clinical aims of the radiation oncologist was developed to evaluate and compare treatment plans independently from the algorithm, the treatment technique or the treatment planning system used. This plan quality assessment tool, named SPIDERplan, was clinically validated for the nasopharynx pathology by three radiation oncologists from the three Portuguese Oncology Institutes in Lisbon, Porto and Coimbra. The performance of SPIDERplan proved to be comparable with the radiation oncologists’ evaluations. Its configuration and resulting scoring were discussed enabling its generalized application. SPIDERplan was then extensively used. Firstly, for nasopharynx tumour cases, in the comparison of two-fluence based beam angle optimization algorithms for coplanar and non-coplanar geometries in a multicriterial optimization framework. The direction optimization topic was afterwards extended to intracranial tumours, namely to meningioma cases. SPIDERplan was used, this time, not just to assess plans quality but also to guide the non-coplanar beam angle optimization algorithm. Furthermore, a new arc trajectory optimization algorithm based in the anchor point concept was proposed, driven again by SPIDERplan. In both nasopharynx and meningioma pathologies, SPIDERplan was used to assess the plans quality, averaged over the used patient samples. In addition, its application to specific-patient situations enabled to evidence the advantages of the optimization of direction/trajectory in a very impressive way.
A Radioterapia é uma modalidade terapêutica multidisciplinar de elevada com-plexidade e exatidão que utiliza, de forma controlada, radiação ionizante para eliminar as células tumorais poupando o máximo possível os tecidos normais. O doente é tratado ao longo de várias sessões de acordo com um plano de trata-mento personalizado otimizado, a priori, por um planeador num sistema de pla-neamento. As novas técnicas de planeamento, como o planeamento inverso com campos estáticos ou com arcos volumétricos, requerem a utilização de al-goritmos de otimização de dose que, de forma iterativa, permitem ao planeador encontrar uma ou mais soluções que satisfaçam o melhor possível a prescrição de dose e cumpram os limites de dose de tolerância definidos para os órgãos de risco. A automatização do processo de planeamento utilizando algoritmos de otimização multicritério permite que todos os doentes tenham planos de trata-mento com qualidade equivalente e reduzir drasticamente a dependência do processo de otimização da destreza do planeador. A qualidade das distribuições de dose pode ainda ser melhorada se durante a otimização da intensidade dos feixes de radiação forem incorporados algoritmos de otimização das direções e trajetórias dos feixes de tratamento. Este trabalho tem como principais propósi-tos contribuir para o processo de automatização do planeamento em Radioterapia através do desenvolvimento de novas ferramentas para avaliação de planos e de novos algoritmos de otimização de direções e trajetórias dos feixes de tratamento. Neste sentido foi desenvolvida uma ferramenta gráfica de avaliação e comparação de planos de apoio à decisão do radioncologista designada SPIDERplan. Para além da informação dosimétrica do plano, esta ferramenta incorpora na sua metodologia as preferências clínicas dos radionco-logistas e permite avaliar e comparar de forma independente planos otimizados com diferentes algoritmos, diferentes técnicas ou provenientes de diferentes sis-temas de planeamento. A SPIDERplan foi validada clinicamente para os carcino-mas de nasofaringe por três médicos radioncologistas dos três institutos portu-gueses de oncologia de Lisboa, Porto e Coimbra. Os resultados obtidos prova-ram que a avaliação dos planos por esta realizada é comparável à avaliação clínica dos médicos pelo que a sua utilização foi alargada a outros estudos e patologias. Assim, a SPIDERplan foi utilizada na comparação de dois algoritmos de otimização angular baseados na otimização de fluências para geometrias co-planares e não-coplanares num sistema de otimização multicritério. A investiga-ção das possíveis vantagens da otimização angular foi alargada aos tumores de sistema nervoso central, mais concretamente aos meningiomas. Neste caso, para além da avaliação da qualidade dos planos, a SPIDERplan foi também uti-lizada para guiar o algoritmo de otimização angular para geometrias não-copla-nares. Ainda no estudo dos meningiomas foi proposto um novo algoritmo de otimização de trajetórias de feixes em arco baseado no conceito de pontos de ancoragem, cuja otimização foi também guiada pela SPIDERplan. Quer para o estudo da nasofaringe quer para os meningiomas, a SPIDERplan foi usada para avaliar a qualidade dos planos gerados de um ponto de vista global, avaliando a qualidade média de todos os casos. Em casos chave foi usada, mais especi-ficamente, para evidenciar as vantagens que podem advir para a otimização dos planeamentos em Radioterapia com os algoritmos de otimização de direções e trajetórias dos feixes de radiação.
Programa Doutoral em Engenharia Física

Ο σκοπός της διπλωματικής εργασίας ήταν η βελτιστοποίηση του πλάνου θεραπείας στο μαστό για τα 2 εφαπτόμενα συνεπίπεδα πεδία ενέργειας 6 MV. Η ανάγκη αυτή πρόκυψε από το γεγονός της εμφάνισης ελλείμματος στην κατανομή της δόσης καθώς όπως φαίνεται και στις παρακάτω εικόνες (στην αξονική και στην οβελιαία τομή) είχαμε ικανοποιητική κάλυψη του CTV στην περιφέρεια του μαστού αλλά στο κέντρο του CTV και σε μεγαλύτερα βάθη όχι. Για την πραγματοποίηση του παραπάνω σκοπού εφαρμόστηκαν 4 τεχνικές ακτινοβόλησης: 1. Δύο εφαπτόμενα συνεπίπεδα πεδία ενέργειας 6 MV, 2. Δύο εφαπτόμενα συνεπίπεδα πεδία ενέργειας 15 MV, 3. Δύο εφαπτόμενα συνεπίπεδα πεδία ενέργειας 6 MV + 1 Field In a Filed (FiF) πεδίο ενέργειας 15 MV και 4. . Δύο εφαπτόμενα συνεπίπεδα πεδία ενέργειας 6 MV + 2 Field In a Filed (FiF) πεδία ενέργειας 15 MV. Η παραπάνω μεθοδολογία εφαρμόστηκε σε πλήθος Ν=100 ασθενών, κατά 95% μεγέθους όγκου Τ1 (έως 2cm) και Τ2 (2-5 cm) και με αριθμό διηθημένων λεμφαδένων Ν<3. Ο υλικοτεχνικός εξοπλισμός που χρησιμοποιήθηκε για την υλοποίηση της εργασίας ήταν: 1. Αξονικός τομογράφος- Simulator Somatom Duo Siemens, 2. Σύστημα διαχείρισης (RVS) ακτινοθεραπευτικού τμήματος ARIA της VARIAN, 3. Σύστημα σχεδιασμού θεραπείας (TPS) Eclipse της VARIAN, 4. Σύστημα κλασσικού εξομοιωτή Aquity της VARIAN και 5. Γραμμικός Επιταχυντής ELEKTA SL 15. Για την στατιστική επεξεργασία των αποτελεσμάτων για πλήθος Ν=100 ασθενών χρησιμοποιήθηκε το πρόγραμμα IBM SPSS (Statistical Package for Social Sciences) έκδοση 20. Η στατιστική επεξεργασία έδειξε ότι μέσος όρος της μέσης δόσης για τις διάφορες τεχνικές ήταν 96.5%, 98.9%, 100.7%, 101.9% για τα 6MV, 15MV, 6MV + 1FIF 15MV και 6MV + 2FIF 15MV, αντίστοιχα. Τα 95% διαστήματα εμπιστοσύνης (Confidence Intervals) ήταν (96.2-96.8), (98.6-99.1), (100.4-100.9), (101.7-102.1) αντίστοιχα. Η ανάλυση έδειξε πως όλες οι ομάδες διέφεραν μεταξύ τους σε επίπεδο στατιστικής σημαντικότητας p < 0.001. Τα αποτελέσματα της εργασίας ήταν ότι η μέση δόση αυξάνεται από μέθοδο σε μέθοδο όπως έδειξε και η στατιστική ανάλυση, ο δείκτης ομοιογένειας μειώνεται αντίστοιχα από μέθοδο σε μέθοδο και αυτό αποτελεί δείγμα βελτίωσης της κατανομής της δόσης. Ακόμα ότι από ένα συγκεκριμένο όγκο του CTV και πάνω η καλύτερη μέθοδος αποδείχτηκε ότι είναι η 6MV + 2FIF 15MV, ενώ από ένα συγκεκριμένο όγκο του CTV και κάτω οι μέθοδοι έχουν περίπου την ίδια αποτελεσματικότητα. Τέλος όσον αφορά τα φυσιολογικά όργανα (organs at risk), τον αντίστοιχο πνεύμονα και την καρδιά, μετρήθηκε το V20 (ο όγκος του οργάνου που λαμβάνει από 2000 cGy και πάνω) και αποδείχτηκε ότι είναι ανεξάρτητο από την τεχνική ακτινοβόλησης.
The purpose of this thesis is to optimize the breast cancer treatment planning for the coplanar tangential fields of 6MV energy. The need for this arose as the dose distribution appears deficient both at the center and deeper in the CTV, as shown in the CT and sagittal images below, whereas the dose is satisfactory distributed at the perimeter of the breast. In order to accomplish that, there were applied 4 radiation techniques: 1. Two coplanar tangential fields of 6MV energy, 2. Two coplanar tangential fields of 15MV energy, 3. Two coplanar tangential fields of 6MV energy with Field in a Field (FiF) of 15MV energy and 4. Two coplanar tangential fields of 6MV energy with two Fields in a Field (FiF’s) of 15MV energy. The method above was applied on 100 patients. 95% of them had T1 tumor (T<2cm), T2 tumor (T=2-5cm) and a number of infiltrated lymph N<3. The equipment that has been used for the materialization of the procedure was: 1. A Computed Tomographer Somatom Duo Siemens, 2. An RVS system of VARIAN, 3. A TPS Eclipse system of VARIAN, 4. A Simulator Aquity of VARIAN and 5. A linear accelerator ELEKTA SL 15. Using the program IBM SPSS 20 (Statistical Package for Social Sciences), for a hundred patients, the statistical analysis showed that the average of the mean dose was 96.5% for the 6MV, 98.9% for the 15MV, 100.7% for the 6MV + 1 FIF of 15MV and 101.9% for the 6MV + 2 FIF of 15MV respectively (95% CI, p<0.001). There was an interaction between CTV size and mean dose, notably for large breasted patients (CTV>750cc). In this particular clinical scenario two 6MV tangential fields with 2 FIFs consistently outperformed the others. Minimum dose was also statistically different among all groups (p<0.05) except for the two FIF-less tangential fields with 6 and 15 MV. Interestingly, minimum dose (%) lacked a dependence on volume size. The result of this procedure was that the mean dose increases from method to method as it was obvious from the statistical analysis. The homogeneity index decreases respectively from method to method which indicates improvement of the dose distribution. It was also proved that, for certain large volumes of CTV the best method was the 6MV with two FIF’s of 15MV energy, whereas for smaller volumes of CTV the other three methods were of the same effectiveness. In conclusion, as far as the organs at risk concern, it has been found that the V20, of the heart and the right or left lung each time, is irrelevant of the technique that has been used each time.