Adaptive Proton Therapy

The high conformality of intensity-modulated proton therapy (IMPT) dose distributions causes treatment plans to be sensitive to geometrical changes during the course of a fractionated treatment. This can be addressed using adaptive proton therapy (APT). One important question in APT is the frequency of adaptations performed during a fractionated treatment, which is related to the question whether adaptation has to be done online or offline. The purpose of this work is to investigate the impact of weekly and daily online IMPT plan adaptation on the treatment quality for head and neck patients. A cohort of ten head and neck patients with daily acquired cone-beam CT (CBCT) images was evaluated retrospectively. Dose tracking of the IMPT treatment was performed for three scenarios: base plan with no adaptation (BP), weekly online adaptation (OAW), and daily online adaptation (OAD). Both adaptation schemes used an in-house developed online APT workflow, performing Monte Carlo (MC) for dose calculations on scatter-corrected CBCTs. IMPT plan adaptation was achieved by only tuning the weights of a subset of beamlets, based on deformable image registration from the planning CT to each CBCT. Although OAD mitigated random delivery errors more effectively than OAW on a fraction per fraction basis, both OAW and OAD achieved the clinical goals for all ten patients, while BP failed for six cases. In the high-risk CTV, accumulated values of D98% ranged between 97.15% and 99.73% of the prescription dose for OAD, with a median of 98.07%. For OAW, values between 95.02% and 99.26% were obtained, with a median of 97.61% of the prescription dose. Otherwise, the dose to most organs at risk was similar for all three scenarios. Globally, our results suggest that OAW could be used as an alternative approach to OAD for most patients in order to reduce the clinical workload.


Setup variations and anatomical changes can severely affect the quality of head and neck intensity-modulated proton therapy treatments. The impact of these changes can be alleviated by increasing the plan’s robustness a priori, or by adapting the plan online. The figure shown below compares these approaches. For each patient in the study, three IMPT plans were created: 1- a classical robust optimization (cRO) plan optimized on the planning CT, 2- an anatomical robust optimization (aRO) plan additionally including the two first daily CBCTs and 3- a plan optimized without robustness constraints, but online-adapted (OA) daily, using a constrained spot intensity re-optimization technique only. The cumulative dose following OA fulfilled the clinical objective of both the high-risk and low- risk clinical target volumes (CTV) coverage in all 10 patients, compared to 8 for aRO and 4 for cRO. aRO did not significantly increase the dose to most organs at risk compared to cRO, although the integral dose was higher. OA significantly reduced the integral dose to healthy tissues compared to both robust meth- ods, while providing equivalent or superior target coverage. Using a simple spot intensity re-optimization, daily OA can achieve superior target coverage and lower dose to organs at risk than robust optimization methods.

Metal Artifact Reduction

Metal implants induce image artifacts in treatment planning CT images, with an estimated 15% of all radiation therapy patients being seriously affected in their radiation therapy. Despite extensive CT metal artifact reduction (MAR) research, it remains one of the long-standing challenges in the CT field, without a clinically satisfactory solution. The overall goal of this project is to develop cutting-edge deep learning methods and an AI-based software package for clinical CT scanners for elimination of CT metal artifacts in general and improvement of radiation therapy (RT) in particular.

Risk for developing second cancers in pediatric patients

The purpose of this project is to provide investigators at the NCI radiation epidemiology & genetics branch with computational support for conducting in-field and out-of-field dose calculations for pediatric proton therapy patients.