Liver-ultrasound based motion modelling to estimate 4D dose distributions for lung tumours in scanned proton therapy

Abstract

Motion mitigation strategies are crucial for scanned particle therapy of mobile tumours in order to prevent geometrical target miss and interplay effects. We developed a patient-specific respiratory motion model based on simultaneously acquired time-resolved volumetric MRI and 2D abdominal ultrasound images. We present its effects on 4D pencil beam scanned treatment planning and simulated dose distributions. Given an ultrasound image of the liver and the diaphragm, principal component analysis and Gaussian process regression were applied to infer dense motion information of the lungs. 4D dose calculations for scanned proton therapy were performed using the estimated and the corresponding ground truth respiratory motion; the differences were compared by dose difference volume metrics. We performed this simulation study on 10 combined CT and 4DMRI data sets where the motion characteristics were extracted from 5 healthy volunteers and fused with the anatomical CT data of two lung cancer patients. Median geometrical estimation errors below 2 mm for all data sets and maximum dose differences of V diff>5 % = 43.2 % and V diff>10 % = 16.3 % were found. Moreover, it was shown that abdominal ultrasound imaging allows to monitor organ drift. This study demonstrated the feasibility of the proposed ultrasound-based motion modelling approach for its application in scanned proton therapy of lung tumours.

Liver-ultrasound-guided lung tumour tracking for scanned proton therapy: a feasibility study

“…The main image processing tools and data sets used here have been described in detail in our preceding study (Giger et al 2020). Although the principal concepts and methods are presented below, certain information has been omitted for conciseness.…”

“…The benefits of more advanced motion predictors on the resulting dose distribution is not clear (Knopf, Stützer, Richter, Rucinski, da Silva, Phillips, Engelsman, Shimizu, Werner, Jakobi et al 2016). In this study, we extend our previously presented motion model (Giger et al 2020) with a linear autoregressive (AR) model (Giger, Jud, Nguyen, Krieger, Zhang, Lomax, Bieri, Salomir & Cattin 2019) which allows forecasting of the motion information to account for A c c e p t e d M a n u s c r i p t system latency. We simulate various treatment scenarios for proton beam tracking and investigate the performance of the spatio-temporal motion prediction model in terms of dose restoration.…”

“…Recently, we have introduced a respiratory motion model that uses Gaussian process regression (GPR, Williams & Rasmussen (2006)) to estimate dense DVFs, i.e. defined on every voxel, of the lung using abdominal US images as input (Giger, Krieger, Jud, Duetschler, Salomir, Bieri, Bauman, Nguyen, Weber, Lomax, Zhang & Cattin 2020). This framework was used to retrospectively reconstruct the delivered 4D dose distributions by taking into account variable motion patterns.…”

Dosimetry, Efficacy, Safety, and Cost-Effectiveness of Proton Therapy for Non-Small Cell Lung Cancer

“…Four-dimensional (4D)computed tomography (CT) ventilation imaging-guided proton therapy, based on breathing patterns, may be helpful for reducing uncertainties and dosing to the normal tissues [31][32][33]. IMPT via a deep-inspiration breath-hold, deformable image registration with daily adaptive proton therapy, and liver-ultrasound-based motion modeling may also provide additional benefits [34][35][36][37]. FLASH proton therapy which optimizes tissue-receiving dose rate distribution and dose distribution may also provide substantial improvements, compared to IMPT, for normal tissue sparing [38].…”

The potential of Gantry beamline large momentum acceptance for real time tumour tracking in pencil beam scanning proton therapy

“…Its technical realisation for time resolved 4D imaging is however not reality yet and therefore alternative approaches have to be considered. Near(er) future applications therefore entails the use of more conventional in room volumetric imaging technologies such as 4D cone beam CT 49 , magnetic resonance 17 or ultrasound 50,51 , as surrogates to update the treatment plan based on the patient's breathing and synchronise the delivery.…”