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      Multiple direction needle-path planning and inverse dose optimization for robotic low-dose rate brachytherapy

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          Abstract

          Purpose

          Robotic systems to assist needle placements for low-dose rate brachytherapy enable conformal dose planning only restricted to path planning around risk structures. We report a treatment planning system (TPS) combining multiple direction needle-path planning with inverse dose optimization algorithms.

          Methods

          We investigated in a path planning algorithm to efficiently locate needle injection points reaching the target volume without puncturing risk structures. A candidate needle domain with all combinations of trajectories is used for the optimization process. We report a modular algorithm for inverse radiation plan optimization. The initial plan with V100 > 99% is generated by the “greedy optimizer”. The “remove-seed algorithm” reduces the number of seeds in the high dose regions. The “depth-optimizer” varies the insertion depth of the needles. The “coverage-optimizer” locates under-dosed areas in the target volume and supports them with an additional amount of seeds. The dose calculation algorithm is benchmarked on an image set of a phantom with a liver metastasis (prescription dose D p r = 100 Gy ) and is re-planned in a commercial CE-marked TPS to compare the calculated dose grids using a global gamma analysis. The inverse optimizer is benchmarked by calculating 10 plans on the same phantom to investigate the stability and statistical variability of the dose parameters.

          Results

          The path planning algorithm efficiently removes 72.5% of all considered injection points. The candidate needle domain consists of combinations of 1971 tip points and 827 injection points. The global gamma analysis with gamma 1 % = 2.9 Gy , 1 mm showed a pass rate of 98.5 % . The dose parameters were V 100 = 99.1 ± 0.3 % , V 150 = 76.4 ± 2.5 % , V 200 = 44.5 ± 5.5 % and D 90 = 125.9 ± 3.6 Gy and 10.7 ± 1.3 needles with 34.0 ± 0.8 seeds were used. The median of the TPS total running time was 4.4 minutes.

          Conclusions

          The TPS generates treatment plans with acceptable dose coverage in a reasonable amount of time. The gamma analysis shows good accordance to the commercial TPS. The TPS allows taking full advantage of robotic navigation tools to enable a new precise and safe method of minimally invasive low-dose-rate brachytherapy.

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          Most cited references26

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          EAU-ESTRO-SIOG Guidelines on Prostate Cancer. Part 1: Screening, Diagnosis, and Local Treatment with Curative Intent.

          To present a summary of the 2016 version of the European Association of Urology (EAU) - European Society for Radiotherapy & Oncology (ESTRO) - International Society of Geriatric Oncology (SIOG) Guidelines on screening, diagnosis, and local treatment with curative intent of clinically localised prostate cancer (PCa).
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            Stereotactic Ablative Radiotherapy for the Comprehensive Treatment of Oligometastatic Cancers: Long-Term Results of the SABR-COMET Phase II Randomized Trial

            PURPOSE The oligometastatic paradigm hypothesizes that patients with a limited number of metastases may achieve long-term disease control, or even cure, if all sites of disease can be ablated. However, long-term randomized data that test this paradigm are lacking. METHODS We enrolled patients with a controlled primary malignancy and 1-5 metastatic lesions, with all metastases amenable to stereotactic ablative radiotherapy (SABR). We stratified by the number of metastases (1-3 v 4-5) and randomized in a 1:2 ratio between palliative standard-of-care (SOC) treatments (arm 1) and SOC plus SABR (arm 2). We used a randomized phase II screening design with a primary end point of overall survival (OS), using an α of .20 (wherein P < .20 indicates a positive trial). Secondary end points included progression-free survival (PFS), toxicity, and quality of life (QOL). Herein, we present long-term outcomes from the trial. RESULTS Between 2012 and 2016, 99 patients were randomly assigned at 10 centers internationally. The most common primary tumor types were breast (n = 18), lung (n = 18), colorectal (n = 18), and prostate (n = 16). Median follow-up was 51 months. The 5-year OS rate was 17.7% in arm 1 (95% CI, 6% to 34%) versus 42.3% in arm 2 (95% CI, 28% to 56%; stratified log-rank P = .006). The 5-year PFS rate was not reached in arm 1 (3.2%; 95% CI, 0% to 14% at 4 years with last patient censored) and 17.3% in arm 2 (95% CI, 8% to 30%; P = .001). There were no new grade 2-5 adverse events and no differences in QOL between arms. CONCLUSION With extended follow-up, the impact of SABR on OS was larger in magnitude than in the initial analysis and durable over time. There were no new safety signals, and SABR had no detrimental impact on QOL.
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              Characterisation and classification of oligometastatic disease: a European Society for Radiotherapy and Oncology and European Organisation for Research and Treatment of Cancer consensus recommendation

              Oligometastatic disease has been proposed as an intermediate state between localised and systemically metastasised disease. In the absence of randomised phase 3 trials, early clinical studies show improved survival when radical local therapy is added to standard systemic therapy for oligometastatic disease. However, since no biomarker for the identification of patients with true oligometastatic disease is clinically available, the diagnosis of oligometastatic disease is based solely on imaging findings. A small number of metastases on imaging could represent different clinical scenarios, which are associated with different prognoses and might require different treatment strategies. 20 international experts including 19 members of the European Society for Radiotherapy and Oncology and European Organisation for Research and Treatment of Cancer OligoCare project developed a comprehensive system for characterisation and classification of oligometastatic disease. We first did a systematic review of the literature to identify inclusion and exclusion criteria of prospective interventional oligometastatic disease clinical trials. Next, we used a Delphi consensus process to select a total of 17 oligometastatic disease characterisation factors that should be assessed in all patients treated with radical local therapy for oligometastatic disease, both within and outside of clinical trials. Using a second round of the Delphi method, we established a decision tree for oligometastatic disease classification together with a nomenclature. We agreed oligometastatic disease as the overall umbrella term. A history of polymetastatic disease before diagnosis of oligometastatic disease was used as the criterion to differentiate between induced oligometastatic disease (previous history of polymetastatic disease) and genuine oligometastatic disease (no history of polymetastatic disease). We further subclassified genuine oligometastatic disease into repeat oligometastatic disease (previous history of oligometastatic disease) and de-novo oligometastatic disease (first time diagnosis of oligometastatic disease). In de-novo oligometastatic disease, we differentiated between synchronous and metachronous oligometastatic disease. We did a final subclassification into oligorecurrence, oligoprogression, and oligopersistence, considering whether oligometastatic disease is diagnosed during a treatment-free interval or during active systemic therapy and whether or not an oligometastatic lesion is progressing on current imaging. This oligometastatic disease classification and nomenclature needs to be prospectively evaluated by the OligoCare study.
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                Author and article information

                Contributors
                Journal
                Z Med Phys
                Z Med Phys
                Zeitschrift für medizinische Physik
                Elsevier
                0939-3889
                1876-4436
                07 August 2021
                May 2022
                07 August 2021
                : 32
                : 2
                : 173-187
                Affiliations
                [1 ]Department of Radiation Oncology, University Medical Centre Mannheim, University Heidelberg, Germany
                [2 ]Fraunhofer IPA, Mannheim, Germany
                [3 ]Department of Radiation Oncology, University Hospital Bonn, University of Bonn, Germany
                Author notes
                [* ]Corresponding author: Philipp Aumüller, Department of Radiation Oncology, University Medical Centre Mannheim, University Heidelberg, Germany. philipp.aumueller@ 123456medma.uni-heidelberg.de
                Article
                S0939-3889(21)00061-1
                10.1016/j.zemedi.2021.06.003
                9948865
                34373188
                f7bff64e-f663-4aab-9282-3f9ee661d789
                © 2021 The Author(s). Published by Elsevier GmbH on behalf of DGMP, ÖGMP and SSRMP.

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 11 February 2021
                : 7 June 2021
                Categories
                Original Article

                brachytherapy,ldr,seeds,robotic,path planning,inverse optimization

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