Intensity modulated proton therapy (IMPT) in head and neck squamous cell carcinoma (HNSCC) offers superior advantages over conventional photon therapy, by generating high conformal doses to the target volume and improved sparing of the organ at risks (OARs). Besides, robust treatment planning approaches, which account for uncertainties directly into the plan optimization process, are able to generate high quality plans robust against uncertainties compared to a PTV margin expansion approach. During radiation treatment, patients are prone to present anatomical variations during the treatment course, which can be random deviations in patient positioning, as well as treatment-induced tumor shrinkage and patient weight variations. For IMPT plans using a PTV margin expansion, these anatomical variations might disturb the calculated nominal plan, with a decrease to the dose delivered to the target volume and/or increased dose to the OARs above its tolerance, and a plan adaptation might be needed. However, the influence of these anatomical variations in robustly optimized plans for HNSCC entities has not been determined. The first part of this thesis compared two proton therapy methods, single-field optimization (SFO) and multi-field optimization (MFO), applied to the treatment of unilateral HNSCC target volumes, consisting of a cohort of 8 patients. For each method, a PTV-based and a robustly optimized plan were generated, resulting in four plans per patient. The four plans showed adequate target coverage on the nominal plan, with larger doses to the ipsilateral parotid gland for both SFO approaches. No plan showed a clear advantage when variations in the anatomy during the treatment course were considered, and the same was observe considering additional setup and range uncertainties. Hence, no plan showed a decisive superiority regarding plan robustness and potential need of replanning. In the second part of this thesis, an anatomical robustly optimized plan approach was proposed (aRO), which considers additional CT datasets in the plan optimization, representing random non-rigid patient positioning variations. The aRO approach was compared to a classical robustly optimized plan (cRO) and a PTV-based approach for a cohort of 20 bilateral HNSCC patients. PTV-based and cRO approaches were not sufficient to account for weekly anatomical variations, showing a degradation in the target coverage in 10 and 5 of 20 cases, respectively. Conversely, the proposed aRO approach was able to preserve the target coverage in 19 of 20 cases, with only one patient requiring plan adaptation. An extended robustness analysis conducted on both cRO and aRO plan approaches considering
weekly anatomical variations, setup and range errors, showed that the variations in anatomy were the most critical variable for loss in target coverage, while setup and range uncertainties played a minor role. The price of the increased plan robustness for the aRO approach was a significant larger integral dose to the healthy tissue, compared to the cRO plan. However, the increase in integral dose was not reflected on the planned dose to the OARs, which were comparable between both plans. Therefore, the price for a superior plan robustness can be considered as low. In the current clinical practice, the implementation of the aRO approach would be able to reduce the need of plan adaptation. For its application, the acquisition of additional planning CT datasets, considering a complete patient repositioning between scans is required, in order to simulate random non-rigid position variations as simulated in this study by the use of the first two weekly cCTs in the plan optimization. Further studies using multiple planning CT acquisition, including strategies to reduce the patient CT dose such as dual-energy CT and iterative reconstruction algorithms, are needed to confirm the presented findings. Additionally, the aRO approach applied to other body sites and entities might also be investigated. In near future, further in-room imaging methods such as cone-beam CT and magnetic resonance imaging, optimized for proton therapy, might be used to acquire additional datasets. Moreover, alternative approaches capable of modeling variations in patient positioning as biomechanical models and deep learning methods might be able to generate in silico additional image datasets for use in proton treatment planning. In summary, this thesis proposes an additional contribution for robust treatment planning in IMPT, with the generation of treatment plans robust against anatomy variations, together with setup and range uncertainties, which can benefit the clinical workflow by reducing the need of plan adaptation.:Contents
List of Figures
List of Tables
List of Abbreviations
1 Introduction
2 Proton Therapy
2.1 Rationale for Proton Therapy
2.2 Beam Delivery Techniques
2.2.1 Passive Scattering
2.2.2 Pencil Beam Scanning
2.3 Uncertainties in Proton Therapy
2.3.1 Target Volume Definition
2.3.2 Range Uncertainty
2.3.3 Setup Uncertainty
2.3.4 Biological Uncertainty
2.3.5 Anatomical Variations
3 Robust Treatment Planning and Robustness Evaluation
3.1 Robust Treatment Planning
3.1.1 Including Uncertainties in the Optimization
3.1.2 Differences Between Approaches
3.2 Robustness Evaluation
3.2.1 Error Scenarios
3.2.2 Visual Evaluation of Plan Robustness
3.2.3 Summary
4 Illustration of Robust Treatment Planning in a Simple Geometry
4.1 Plan Design
4.2 Plan Results
4.2.1 Doses on Nominal Plan
4.2.2 Influence of Uncertainties in Plan Robustness
4.3 Discussion and Conclusion
5 Evaluation of Robust Treatment Plans in Unilateral Head and Neck Squamous
Cell Carcinoma
5.1 Study Design
5.1.1 Calculation Parameters
5.1.2 Plan Robustness Evaluation
5.2 Results
5.2.1 Evaluation of Nominal Plan Doses
5.2.2 Evaluation of Plan Robustness Against Uncertainties
5.3 Discussion
5.4 Conclusions
6 Assessment of Anatomical Robustly Optimized Plans in Bilateral Head and
Neck Squamous Cell Carcinoma
6.1 Anatomical Robust Optimization
6.2 Study Design
6.2.1 Calculation Parameters
6.2.2 Assessment of Plan Robustness
6.3 Results
6.3.1 Evaluation of Nominal Plan Doses
6.3.2 Evaluation of Plan Robustness Against Uncertainties
6.4 Discussion
6.4.1 Robustness Against Anatomical Variations
6.4.2 Robustness Against Additional Setup and Range Uncertainties
6.4.3 Study Limitations
6.5 Conclusions
7 Summary
8 Zusammenfassung
Bibliography
Appendix
| Identifer | oai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:73383 |
| Date | 19 January 2021 |
| Creators | Cubillos MesÃas, Macarena Yasmara |
| Contributors | Troost, Esther, Hoogeman, Mischa |
| Publisher | Technische Universität Dresden |
| Source Sets | Hochschulschriftenserver (HSSS) der SLUB Dresden |
| Language | English |
| Detected Language | English |
| Type | info:eu-repo/semantics/publishedVersion, doc-type:doctoralThesis, info:eu-repo/semantics/doctoralThesis, doc-type:Text |
| Rights | info:eu-repo/semantics/openAccess |
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