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1.
Med Phys ; 51(1): 476-484, 2024 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-37921262

RESUMO

BACKGROUND: Although re-irradiation is increasingly used in clinical practice, almost no dedicated planning software exists. PURPOSE: Standard dose-based optimization functions were adjusted for re-irradiation planning using accumulated equivalent dose in 2-Gy fractions (EQD2) with rigid or deformable dose mapping, tissue-specific α/ß, treatment-specific recovery coefficients, and voxelwise adjusted EQD2 penalization levels based on the estimated previously delivered EQD2 (EQD2deliv ). METHODS: To demonstrate proof-of-concept, 35 Gy in 5 fractions was planned to a fictitious spherical relapse planning target volume (PTV) in three separate locations following previous prostate treatment on a virtual human phantom. The PTV locations represented one repeated irradiation scenario and two re-irradiation scenarios. For each scenario, three re-planning strategies with identical PTV dose-functions but various organ at risk (OAR) EQD2-functions was used: 1) reRTregular : Regular functions with fixed EQD2 penalization levels larger than EQD2deliv for all OAR voxels. 2) reRTreduce : As reRTregular , but with lower fixed EQD2 penalization levels aiming to reduce OAR EQD2. 3) reRTvoxelwise : As reRTregular and reRTreduce , but with voxelwise adjusted EQD2 penalization levels based on EQD2deliv . PTV near-minimum and near-maximum dose (D98% /D2% ), homogeneity index (HI), conformity index (CI) and accumulated OAR EQD2 (α/ß = 3 Gy) were evaluated. RESULTS: For the repeated irradiation scenario, all strategies resulted in similar dose distributions. For the re-irradiation scenarios, reRTreduce and reRTvoxelwise reduced accumulated average and near-maximum EQD2 by ˜1-10 Gy for all relevant OARs compared to reRTregular . The reduced OAR doses for reRTreduce came at the cost of distorted dose distributions with D98% = 92.3%, HI = 12.0%, CI = 73.7% and normal tissue hot spots ≥150% for the most complex scenario, while reRTregular (D98% = 98.1%, HI = 3.2%, CI = 94.2%) and reRTvoxelwise (D98%  = 96.9%, HI = 6.1%, CI = 93.7%) fulfilled PTV coverage without hot spots. CONCLUSIONS: The proposed re-irradiation-specific EQD2-based optimization functions introduce novel planning possibilities with flexible options to guide the trade-off between target coverage and OAR sparing with voxelwise adapted penalization levels based on EQD2deliv .


Assuntos
Radioterapia de Intensidade Modulada , Reirradiação , Masculino , Humanos , Dosagem Radioterapêutica , Planejamento da Radioterapia Assistida por Computador/métodos , Radioterapia de Intensidade Modulada/métodos , Órgãos em Risco/efeitos da radiação
2.
Cancers (Basel) ; 15(15)2023 Jul 28.
Artigo em Inglês | MEDLINE | ID: mdl-37568647

RESUMO

(1) Background: The STRIDeR (Support Tool for Re-Irradiation Decisions guided by Radiobiology) planning pathway aims to facilitate anatomically appropriate and radiobiologically meaningful re-irradiation (reRT). This work evaluated the STRIDeR pathway for robustness compared to a more conservative manual pathway. (2) Methods: For ten high-grade glioma reRT patient cases, uncertainties were applied and cumulative doses re-summed. Geometric uncertainties of 3, 6 and 9 mm were applied to the background dose, and LQ model robustness was tested using α/ß variations (values 1, 2 and 5 Gy) and the linear quadratic linear (LQL) model δ variations (values 0.1 and 0.2). STRIDeR robust optimised plans, incorporating the geometric and α/ß uncertainties during optimisation, were also generated. (3) Results: The STRIDeR and manual pathways both achieved clinically acceptable plans in 8/10 cases but with statistically significant improvements in the PTV D98% (p < 0.01) for STRIDeR. Geometric and LQ robustness tests showed comparable robustness within both pathways. STRIDeR plans generated to incorporate uncertainties during optimisation resulted in a superior plan robustness with a minimal impact on PTV dose benefits. (4) Conclusions: Our results indicate that STRIDeR pathway plans achieved a similar robustness to manual pathways with improved PTV doses. Geometric and LQ model uncertainties can be incorporated into the STRIDeR pathway to facilitate robust optimisation.

3.
Radiother Oncol ; 182: 109545, 2023 05.
Artigo em Inglês | MEDLINE | ID: mdl-36813170

RESUMO

BACKGROUND: The STRIDeR (Support Tool for Re-Irradiation Decisions guided by Radiobiology) project aims to create a clinically viable re-irradiation planning pathway within a commercial treatment planning system (TPS). Such a pathway should account for previously delivered dose, voxel-by-voxel, taking fractionation effects, tissue recovery and anatomical changes into account. This work presents the workflow and technical solutions in the STRIDeR pathway. METHODS: The pathway was implemented in RayStation (version 9B DTK) to allow an original dose distribution to be used as background dose to guide optimisation of re-irradiation plans. Organ at risk (OAR) planning objectives in equivalent dose in 2 Gy fractions (EQD2) were applied cumulatively across the original and re-irradiation treatments, with optimisation of the re-irradiation plan performed voxel-by-voxel in EQD2. Different approaches to image registration were employed to account for anatomical change. Data from 21 patients who received pelvic Stereotactic Ablative Radiotherapy (SABR) re-irradiation were used to illustrate the use of the STRIDeR workflow. STRIDeR plans were compared to those produced using a standard manual method. RESULTS: The STRIDeR pathway resulted in clinically acceptable plans in 20/21 cases. Compared to plans produced using the laborious manual method, less constraint relaxation was required or higher re-irradiation doses could be prescribed in 3/21. CONCLUSION: The STRIDeR pathway used background dose to guide radiobiologically meaningful, anatomically-appropriate re-irradiation treatment planning within a commercial TPS. This provides a standardised and transparent approach, offering more informed re-irradiation and improved cumulative OAR dose evaluation.


Assuntos
Radioterapia de Intensidade Modulada , Reirradiação , Humanos , Dosagem Radioterapêutica , Reirradiação/métodos , Planejamento da Radioterapia Assistida por Computador/métodos , Fracionamento da Dose de Radiação , Radioterapia de Intensidade Modulada/métodos , Órgãos em Risco/efeitos da radiação
4.
Phys Imaging Radiat Oncol ; 21: 84-89, 2022 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-35243037

RESUMO

BACKGROUND AND PURPOSE: Re-irradiation may be used for recurrent glioblastoma (GBM) patients. In some cases Planning Target Volume (PTV) under-coverage is necessary to meet organ at risk (OAR) constraints. This study aimed to develop a Volumetric Modulated Arc Therapy planning solution for GBM re-irradiation including a means of assessing if target coverage would be achievable and how much PTV 'cropping' would be required to meet OAR constraints, based on PTV volume and OAR proximity. MATERIALS AND METHODS: For 10 PTVs, 360°, 180°, two coplanar 180° and 180° + non-coplanar 45° arc arrangements were compared using 35 Gy in 10 fractions. Using the preferred arrangement, dose fall-off was modelled to determine the separation required between PTV and OAR to ensure OAR dose constraints were met, with data presented graphically. To evaluate the graph as an aid to planning, seven cases with overlap were replanned in two treatment planning systems (TPSs). RESULTS: There were no significant dosimetric differences between arc arrangements. 180° was preferred due to shorter treatment times. The graph, which indicated if 95% PTV coverage would be achievable based on PTV volume and OAR proximity, was employed in seven cases to guide planning in two TPSs. Plans were deliverable. CONCLUSIONS: Re-irradiation treatment planning can be challenging, especially when PTV under-coverage is necessary. 180° was considered optimal. To assist in the planning process, graphical guidance was produced to inform planners whether PTV under-coverage would be necessary and how much PTV 'cropping' would be required to meet constraints during optimisation.

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