Air variability in maxillary sinus during radiotherapy for sinonasal carcinoma

Synthetic CT imaging for PET monitoring in proton therapy: a simulation study

Objective.This study addresses a fundamental limitation of in-beam positron emission tomography (IB-PET) in proton therapy: the lack of direct anatomical representation in the images it produces. We aim to overcome this shortcoming by pioneering the application of deep learning techniques to create synthetic control CT images (sCT) from combining IB-PET and planning CT scan data.Approach.We conducted simulations involving six patients who underwent irradiation with proton beams. Leveraging the architecture of a visual transformer (ViT) neural network, we developed a model to generate sCT images of these patients using the planning CT scans and the inter-fractional simulated PET activity maps during irradiation. To evaluate the model's performance, a comparison was conducted between the sCT images produced by the ViT model and the authentic control CT images-serving as the benchmark.Main results.The structural similarity index was computed at a mean value across all patients of 0.91, while the mean absolute error measured 22 Hounsfield Units (HU). Root mean squared error and peak signal-to-noise ratio values were 56 HU and 30 dB, respectively. The Dice similarity coefficient exhibited a value of 0.98. These values are comparable to or exceed those found in the literature. More than 70% of the synthetic morphological changes were found to be geometrically compatible with the ones reported in the real control CT scan.Significance.Our study presents an innovative approach to surface the hidden anatomical information of IB-PET in proton therapy. Our ViT-based model successfully generates sCT images from inter-fractional PET data and planning CT scans. Our model's performance stands on par with existing models relying on input from cone beam CT or magnetic resonance imaging, which contain more anatomical information than activity maps.

Dose and robustness comparison of nominal, daily and accumulated doses for photon and proton treatment of sinonasal cancer

INTRODUCTION

The aim was to evaluate and compare the dosimetric effect and robustness towards day-to-day anatomical and setup variations in the delivered dose for photon and proton treatments of sinonasal cancer (SNC) patients.

MATERIALS AND METHODS

Photon (VMAT) and proton (IMPT) plans were optimized retrospectively for 24 SNC patients. Synthetic CTs (synCT) were obtained by deforming the planning CT (pCT) to the anatomy of every daily cone-beam CT. Both VMAT and IMPT plans were recalculated on the synCTs. The recalculated daily dose was accumulated over the whole treatment on the pCT. Target coverage and dose to organs and risk (OARs) were evaluated for all patients for the nominal, daily and accumulated dose distribution.

RESULTS

In general, dose to OARs farther away from the target, including brain, chiasm and contralateral optic nerve, was lower for proton plans than photon plans. Whereas, OARs in proximity of the target received a lower dose for photon plans. For proton plans, the target coverage (volume of CTV receiving 95% of prescribed dose), V95%, fell below 99% for 9/24 patients in one or more fractions. For photon plans, 4/24 patients had one or more fractions where V95% fell below 99%. For accumulated doses, V95% was below 99% only in two cases, but above 98% for all patients.

CONCLUSION

Photon and proton treatment have different strengths regarding OAR sparing. The robustness was high for both treatment modalities. Patient selection for either proton or photon radiation therapy of SNC patients should be based on a case-by-case comparison.

Robust Angle Selection in Particle Therapy

The popularity of particle radiotherapy has grown exponentially over recent years owing to the marked advantage of the depth–dose curve and its unique biological property. However, particle therapy is sensitive to changes in anatomical structure, and the dose distribution may deteriorate. In particle therapy, robust beam angle selection plays a crucial role in mitigating inter- and intrafractional variation, including daily patient setup uncertainties and tumor motion. With the development of a rotating gantry, angle optimization has gained increasing attention. Currently, several studies use the variation in the water equivalent thickness to quantify anatomical changes during treatment. This method seems helpful in determining better beam angles and improving the robustness of planning. Therefore, this review will discuss and summarize the robust beam angles at different tumor sites in particle radiotherapy.