CTC-ask: a new algorithm for conversion of CT numbers to tissue parameters for Monte Carlo dose calculations applying DICOM RS knowledge

One of the building blocks in Monte Carlo (MC) treatment planning is to convert patient CT data to MC compatible phantoms, consisting of density and media matrices. The resulting dose distribution is highly influenced by the accuracy of the conversion. Two major contributing factors are precise conversion of CT number to density and proper differentiation between air and lung. Existing tools do not address this issue specifically. Moreover, their density conversion may depend on the number of media used. Differentiation between air and lung is an important task in MC treatment planning and misassignment may lead to local dose errors on the order of 10%. A novel algorithm, CTC-ask, is presented in this study. It enables locally confined constraints for the media assignment and is independent of the number of media used for the conversion of CT number to density. MC compatible phantoms were generated for two clinical cases using a CT-conversion scheme implemented in both CTC-ask and the DICOM-RT toolbox. Full MC dose calculation was subsequently conducted and the resulting dose distributions were compared. The DICOM-RT toolbox inaccurately assigned lung in 9.9% and 12.2% of the voxels located outside of the lungs for the two cases studied, respectively. This was completely avoided by CTC-ask. CTC-ask is able to reduce anatomically irrational media assignment. The CTC-ask source code can be made available upon request to the authors

Adaptation requirements due to anatomical changes in free-breathing and deep-inspiration breath-hold for standard and dose-escalated radiotherapy of lung cancer patients

<div><p>ABSTRACT</p><p><b>Background.</b> Radiotherapy of lung cancer patients is subject to uncertainties related to heterogeneities, anatomical changes and breathing motion. Use of deep-inspiration breath-hold (DIBH) can reduce the treated volume, potentially enabling dose-escalated (DE) treatments. This study was designed to investigate the need for adaptation due to anatomical changes, for both standard (ST) and DE plans in free-breathing (FB) and DIBH.</p><p><b>Material and methods.</b> The effect of tumor shrinkage (TS), pleural effusion (PE) and atelectasis was investigated for patients and for a CIRS thorax phantom. Sixteen patients were computed tomography (CT) imaged both in FB and DIBH. Anatomical changes were simulated by CT information editing and re-calculations, of both ST and DE plans, in the treatment planning system. PE was systematically simulated by adding fluid in the dorsal region of the lung and TS by reduction of the tumor volume.</p><p><b>Results.</b> Phantom simulations resulted in maximum deviations in mean dose to the GTV-T (_GTV-T) of −1% for 3 cm PE and centrally located tumor, and + 3% for TS from 5 cm to 1 cm diameter for an anterior tumor location. For the majority of the patients, simulated PE resulted in a decreasing _GTV-T with increasing amount of fluid and increasing _GTV-T for decreasing tumor volume. Maximum change in _GTV-T of -3% (3 cm PE in FB for both ST and DE plans) and + 10% (2 cm TS in FB for DE plan) was observed. Large atelectasis reduction increased the _GTV-T with 2% for FB and had no effect for DIBH.</p><p><b>Conclusion.</b> Phantom simulations provided potential adaptation action levels for PE and TS. For the more complex patient geometry, individual assessment of the dosimetric impact is recommended for both ST and DE plans in DIBH as well as in FB. However, DIBH was found to be superior over FB for DE plans, regarding robustness of _GTV-T to TS.</p></div