Background And Purpose: We aim to retrospectively investigate whether reducing GTV to high-risk CTV margin will significantly reduce acute and late toxicity without jeopardizing outcome in head-and-neck squamous cell carcinoma (HNSCC) treated with definitive (chemo)radiation.
Materials And Methods: Between April 2015 and April 2019, 155 consecutive patients were treated with GTV to high-risk CTV margin of 10 mm and subsequently another 155 patients with 6 mm margin. The CTV-PTV margin was 3 mm for both groups. All patients were treated with volumetric-modulated arc therapy with daily image-guidance using cone-beam CT. End points of the study were acute and late toxicity and oncologic outcomes.
Results: Overall acute grade 3 toxicity was significantly lower in 6 mm, compared to 10 mm group (48% vs. 67%, respectively, p < 0.01). The same was true for acute grade 3 mucositis (18% vs. 34%, p < 0.01) and grade ≥ 2 dysphagia (67% vs. 85%, p < 0.01). Also feeding tube-dependency at the end of treatment (25% vs. 37%, p = 0.02), at 3 months (12% and 25%, p < 0.01), and at 6 months (6% and 15%, p = 0.01) was significantly less in 6 mm group. The incidence of late grade 2 xerostomia was also significantly lower in the 6 mm group (32% vs. 50%, p < 0.01). The 2-year rates of loco-regional control, disease-free and overall survival were 78.7% vs. 73.1%, 70.6% vs. 61.4%, and 83.2% vs. 74.4% (p > 0.05, all).
Conclusion: The first study reporting on reduction of GTV to high-risk CTV margin from 10 to 6 mm showed significant reduction of the incidence and severity of radiation-related toxicity without reducing local-regional control and survival.
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http://dx.doi.org/10.1016/j.radonc.2021.07.016 | DOI Listing |
Radiat Oncol
January 2025
Department of Radiotherapy, Changzhou Cancer Hospital, Honghe Road, Xinbei Area, Changzhou, 213032, China.
Purpose: Conventional radiotherapy (CRT) has limited local control and poses a high risk of severe toxicity in large lung tumors. This study aimed to develop an integrated treatment plan that combines CRT with lattice boost radiotherapy (LRT) and monitors its dosimetric characteristics.
Methods: This study employed cone-beam computed tomography from 115 lung cancer patients to develop a U-Net + + deep learning model for generating synthetic CT (sCT).
Pract Radiat Oncol
December 2024
Radiation Oncology, Centre Hospitalier de l'Université de Montréal (CHUM), Quebec, Canada.
Purpose: Local recurrence of prostate cancer (PCa) after radiation therapy (RT) typically occurs at the site of dominant tumor burden, and recent evidence confirms that magnetic resonance imaging (MRI) guided tumor dose escalation improves outcomes. With the emergence of prostate-specific membrane antigen (PSMA) positron emission tomography (PET), we hypothesize that PSMA-PET and MRI may not equally depict the region most at risk of recurrence after RT.
Methods And Materials: Patients with intermediate- to high-risk PCa and MRI plus PSMA-PET performed before RT were identified.
Cancers (Basel)
January 2025
Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China.
: We constructed a prediction model to predict a 2-year locoregional recurrence based on the clinical features and radiomic features extracted from the machine learning method using computed tomography (CT) before definite chemoradiotherapy (dCRT) in locally advanced esophageal cancer. : A total of 264 patients (156 in Beijing, 87 in Tianjin, and 21 in Jiangsu) were included in this study. All those locally advanced esophageal cancer patients received definite radiotherapy and were randomly divided into five subgroups with a similar number and divided into training groups and validation groups by five cross-validations.
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December 2024
Section for Biomedical Physics, Department of Radiation Oncology, University of Tübingen, Tübingen, Germany; German Cancer Consortium (DKTK), partner site Tübingen, and German Cancer Research Center (DKFZ), Heidelberg, Germany; Cluster of Excellence "Machine Learning", University of Tübingen, Tübingen, Germany. Electronic address:
Purpose: To retrain a model based on a previously identified prognostic imaging biomarker using apparent diffusion coefficient (ADC) values from diffusion-weighted magnetic resonance imaging (DW-MRI) in a preclinical setting and validate the model using clinical DW-MRI data of patients with locally advanced head-and-neck cancer (HNC) acquired before radiochemotherapy.
Material And Methods: A total of 31 HNC patients underwent T2-weighted and DW-MRI using 3 T MRI before radiochemotherapy (35 x 2 Gy). Gross tumor volumes (GTV) were delineated based on T2-weighted and b500 images.
J Contemp Brachytherapy
June 2024
Division of Radiation Oncology, Department of Radiology, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand.
Purpose: The aim of this study was to investigate the predictive value of radiomic features of pre-treatment T2-weighted magnetic resonance images (MRI) for clinical outcomes of radiotherapy in cervical cancer patients.
Material And Methods: Ninety cervical cancer patients with stage IB-IVA were retrospectively analyzed. All patients received definitive radiotherapy with or without concurrent chemotherapy.
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