Background: To investigate the feasibility and benefits of a modified adaptive radiotherapy (ART) by replanning in the initial CT (iCT) with new contours from a repeat CT (rCT) based on CT-CT image fusion for nasopharyngeal cancer (NPC) patients underwent volumetric modulated arc radiotherapy (VMAT).
Materials And Methods: Nine NPC patients underwent VMAT treatment with a rCT at 23rd fraction were enrolled in this study. Dosimetric differences for replanning VMAT plans in the iCT and in the rCT were compared. Volumetric and dosimetric changes of gross tumor volume (GTV) and organs at risk (OARs) of this modified ART were also investigated.
Results: No dosimetric differences between replanning in the iCT and in the rCT were observed. The average volume of GTV decreased from 78.83 ± 38.42 cm3 in the iCT to 71.44 ± 37.46 cm3 in the rCT, but with no significant difference (p = 0.42).The average volume of the left and right parotid decreased from 19.91 ± 4.89 cm3 and 21.58 ± 6.16 cm3 in the iCT to 11.80 ± 2.79 cm3 and 13.29 ± 4.17 cm3 in the rCT (both p < 0.01), respectively. The volume of other OARs did not shrink very much. No significant differences on PTVGTV and PTVCTV coverage were observed for replanning with this modified ART. Compared to the initial plans, the average mean dose of the left and right parotid after re-optimization were decreased by 62.5 cGy (p = 0.05) and 67.3 cGy (p = 0.02), respectively, and the V5 (the volume receiving 5 Gy) of the left and right parotids were decreased by 7.8% (p = 0.01) and 11.2% (p = 0.001), respectively. There was no significant difference on the dose delivered to other OARs.
Conclusion: Patients with NPC undergoing VMAT have significant anatomic and dosimetric changes to parotids. Repeat CT as an anatomic changes reference and re-optimization in the iCT based on CT-CT image fusion was accurate enough to identify the volume changes and to ensure safe dose to parotids.
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http://dx.doi.org/10.1186/1748-717X-8-277 | DOI Listing |
JCO Clin Cancer Inform
January 2025
Machine Learning Department, H. Lee Moffit Cancer Center and Research Institute, Tampa, FL.
Purpose: Adaptive radiotherapy accounts for interfractional anatomic changes. We hypothesize that changes in the gross tumor volumes identified during daily scans could be analyzed using delta-radiomics to predict disease progression events. We evaluated whether an auxiliary data set could improve prediction performance.
View Article and Find Full Text PDFRadiat 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).
Strahlenther Onkol
January 2025
Department of Radiation Oncology, University Hospital Zurich, University of Zurich, Rämistrasse 100, 8091, Zurich, Switzerland.
The integration of artificial intelligence (AI) into radiotherapy has advanced significantly during the past 5 years, especially in terms of automating key processes like organ at risk delineation and treatment planning. These innovations have enhanced consistency, accuracy, and efficiency in clinical practice. Magnetic resonance (MR)-guided linear accelerators (MR-linacs) have greatly improved treatment accuracy and real-time plan adaptation, particularly for tumors near radiosensitive organs.
View Article and Find Full Text PDFEur Urol
January 2025
Department of Urology, University Hospitals Cleveland Medical Center, Case Western Reserve University Cleveland OH USA.
Background: In proton radiotherapy, the steep dose deposition profile near the end of the proton's track, the Bragg peak, ensures a more conformed deposition of dose to the tumor region when compared with conventional radiotherapy while reducing the probability of normal tissue complications. However, uncertainties, as in the proton range, patient geometry, and positioning pose challenges to the precise and secure delivery of the treatment plan (TP). In vivo range determination and dose distribution are pivotal for mitigation of uncertainties, opening the possibility to reduce uncertainty margins and for adaptation of the TP.
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