Predicting personalised and progressive adaptive dose escalation to gross tumour volume using knowledge-based planning models for inoperable advanced-stage non-small cell lung cancer patients treated with volumetric modulated arc therapy. (1st May 2022)

• Record Type: Journal Article
• Authors: Tambe, Nilesh S; Pires, Isabel M; Moore, Craig; Wieczorek, Andrew; Upadhyay, Sunil; Beavis, Andrew W
• Is Part Of: Biomedical physics & engineering express. Volume 8:Number 3(2022)
• Publication Date: 2022-05-01
• Subjects: volumetric modulated arc therapy -- dose escalation -- non-small cell lung cancer -- personalized radiotherapy -- treatment planning optimization -- knowledge-based planning model; Medical physics -- Periodicals; Biophysics -- Periodicals; Biomedical engineering -- Periodicals; Medical sciences -- Periodicals; 610.153
• DOI: 10.1088/2057-1976/ac56eb
• Languages: English
• ISSNs: 2057-1976

Abstract

Abstract: Objectives . Increased radiation doses could improve local control and overall survival of lung cancer patients, however, this could be challenging without exceeding organs at risk (OAR) dose constraints, especially for patients with advanced-stage disease. Increasing OAR doses could reduce the therapeutic ratio and quality of life. It is therefore important to investigate methods to increase the dose to target volume without exceeding OAR dose constraints. Methods . Gross tumour volume (GTV) was contoured on synthetic computerised tomography (sCT) datasets produced using the Velocity adaptive radiotherapy software for eleven patients. The fractions where GTV volume decreased compared to that prior to radiotherapy (reference plan) were considered for personalised progressive dose escalation. The dose to the adapted GTV (GTVAdaptive ) was increased until OAR doses were affected (as compared to the original clinical plan). Planning target volume (PTV) coverage was maintained for all plans. Doses were also escalated to the reference plan (GTVClinical ) using the same method. Adapted, dose-escalated, plans were combined to estimate accumulated dose, D99 (dose to 99%) of GTVAdapted, PTV D99 and OAR doses and compared with those in the original clinical plans. Knowledge-based planning (KBP) model was developed to predict D99 of the adapted GTV with OAR doses and PTV coverage kept similar to the original clinical plans; prediction accuracy and model verification were performed using further data sets. Results . Compared to the original clinical plan, the dose to GTV was significantly increased without exceeding OAR doses. Adaptive dose-escalation increased the average D99 to GTVAdaptive by 15.1Gy and 8.7Gy compared to the clinical plans. The KBP models were verified and demonstrated prediction accuracy of 0.4% and 0.7% respectively. Conclusion . Progressive adaptive dose escalation can significantly increase the dose to GTV without increasing OAR doses or compromising the dose to microscopic disease. This may increase overall survival without increasing toxicities.