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1.
Clin Transl Oncol ; 25(2): 503-509, 2023 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-36194382

RESUMO

PURPOSE: Design and evaluate a knowledge-based model using commercially available artificial intelligence tools for automated treatment planning to efficiently generate clinically acceptable hippocampal avoidance prophylactic cranial irradiation (HA-PCI) plans in patients with small-cell lung cancer. MATERIALS AND METHODS: Data from 44 patients with different grades of head flexion (range 45°) were used as the training datasets. A Rapid Plan knowledge-based planning (KB) routine was applied for a prescription of 25 Gy in 10 fractions using two volumetric modulated arc therapy (VMAT) arcs. The 9 plans used to validate the initial model were added to generate a second version of the RP model (Hippo-MARv2). Automated plans (AP) were compared with manual plans (MP) according to the dose-volume objectives of the PREMER trial. Optimization time and model quality were assessed using 10 patients who were not included in the first 44 datasets. RESULTS: A 55% reduction in average optimization time was observed for AP compared to MP. (15 vs 33 min; p = 0.001).Statistically significant differences in favor of AP were found for D98% (22.6 vs 20.9 Gy), Homogeneity Index (17.6 vs 23.0) and Hippocampus D mean (11.0 vs 11.7 Gy). The AP met the proposed objectives without significant deviations, while in the case of the MP, significant deviations from the proposed target values were found in 2 cases. CONCLUSION: The KB model allows automated planning for HA-PCI. Automation of radiotherapy planning improves efficiency, safety, and quality and could facilitate access to new techniques.


Assuntos
Intervenção Coronária Percutânea , Radioterapia de Intensidade Modulada , Humanos , Dosagem Radioterapêutica , Inteligência Artificial , Planejamento da Radioterapia Assistida por Computador/métodos , Irradiação Craniana/métodos , Radioterapia de Intensidade Modulada/métodos , Hipocampo , Aprendizado de Máquina , Órgãos em Risco/efeitos da radiação
2.
Clin Transl Oncol ; 25(4): 1017-1023, 2023 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-36436177

RESUMO

BACKGROUND: To reach a consensus on recommendations for the management of high-risk and post-operative non-metastatic prostate cancer by a group of Radiation Oncologists in Catalonia dedicated to prostate cancer. METHODS: A modified Delphi approach was employed to reach consensus on controversial topics in Radiation Oncology on high-risk non-metastatic (eight questions) and post-operative (eight questions) prostate cancer. An agreement of at least 75% was considered as consensus. The survey was electronically sent 6 weeks before an expert meeting where topics were reviewed and discussed. A second-round survey for the controversial questions only was sent and answered by participants after the meeting. RESULTS: After the first round of the survey, 19 experienced Radiation Oncologists attended the meeting and 74% fulfilled the second-round online questionnaire. An agreement of 9 of the 16 questions was accounted for the first round. After the meeting, an additional agreement was reached in 3 questions leading to a final consensus on 12 of the 16 questions. There are still controversial topics like the use of PET for staging of high-risk and post-operative non-metastatic prostate cancer and the optimal dose to the prostate bed in the salvage setting. CONCLUSION: This consensus contributes to establish recommendations and a framework to help in prostate cancer radiation therapy and pharmacological management in daily clinical practice of high-risk and post-operative non-metastatic prostate cancer.


Assuntos
Neoplasias da Próstata , Masculino , Humanos , Consenso , Técnica Delphi , Espanha , Neoplasias da Próstata/terapia , Inquéritos e Questionários
3.
Clin Transl Oncol ; 13(7): 504-8, 2011 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-21775278

RESUMO

AIMS AND BACKGROUND: To evaluate the predictive factors of recurrence in cervical cancer treated with radical radiochemotherapy. METHODS: A retrospective analysis of 56 women was performed. Response was assessed using the RECIST response. Overall survival and disease-free survival curves were estimated by the Kaplan-Meier method and the Cox proportional hazards model was used to analyse predictors of recurrence. RESULTS: Local recurrence was documented in 16 patients and distant metastases in 15. The Kaplan-Meier survival probabilities were 95.1 ± 6.4% at 3 years and 80.4 ± 13.1% at 5 years and the Kaplan-Meier curve values for disease-free survival were 60.3 ± 14.3% at 3 years and 53.0 ± 15.7% at 5 years. Thirty-five patients were alive and 21 patients died, 19 from metastatic disease and 2 from other causes. Complete response after chemoradiation therapy, squamous cell carcinoma and tumour size ≤ 4 cm were significantly associated with outcome. In the Cox regression model, tumour size > 4 cm (hazard ratio 7.48; 95% CI 2.71-20.6; p < 0.001) and partial response (hazard ratio 7.09; 95% CI 2.82-17.8; p < 0.001) were predictive factors for disease-free survival and partial response (hazard ratio 3.7; 95% CI 1.3-10.1; p < 0.001) and non-squamous cell carcinoma (hazard ratio 3.5; 95% CI 1.2-9.7; p < 0.001) were predictive factors for overall survival. CONCLUSIONS: Non-squamous histology and partial response were independent prognostic factors for overall survival and tumour size and partial response were independent prognostic variables for 5-year disease survival.


Assuntos
Adenocarcinoma/terapia , Protocolos de Quimioterapia Combinada Antineoplásica/uso terapêutico , Carcinoma de Células Escamosas/terapia , Neoplasias do Colo do Útero/terapia , Adenocarcinoma/secundário , Adulto , Idoso , Idoso de 80 Anos ou mais , Braquiterapia , Carcinoma de Células Escamosas/secundário , Terapia Combinada , Feminino , Seguimentos , Humanos , Metástase Linfática , Masculino , Pessoa de Meia-Idade , Recidiva Local de Neoplasia/patologia , Recidiva Local de Neoplasia/terapia , Prognóstico , Estudos Retrospectivos , Taxa de Sobrevida , Fatores de Tempo , Neoplasias do Colo do Útero/patologia
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