Copenhagen, Denmark
Onsite/Online

ESTRO 2022

Session Item

Sunday
May 08
11:40 - 12:40
Room D3
Highlights of Proffered Papers - Best Papers
Esther Troost, Germany;
Umberto Ricardi, Italy
2320
Proffered Papers
Interdisciplinary
12:10 - 12:20
Physics Best Paper: Salivary gland dose response modelling using PSMA PET/CT
Vineet Mohan, The Netherlands
OC-0506

Abstract

Salivary gland dose response modelling using PSMA PET/CT
Authors:

Vineet Mohan1, Natascha Bruin2, Jeroen van de Kamer1, Jan-Jakob Sonke1, Wouter Vogel2

1Netherlands Cancer Institute, Radiation Oncology, Amsterdam, The Netherlands; 2Netherlands Cancer Institute, Radiation Oncology and Nuclear Medicine, Amsterdam, The Netherlands

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Purpose or Objective

Xerostomia remains a common side effect of radiotherapy (RT) for patients with head and neck (H&N) cancer despite advancements in treatment planning and delivery. Molecular PET imaging of the prostate specific membrane antigen (using 68Ga/18F-PSMA) is highly specific to prostate cancer, but uptake in salivary glands reflects the presence of generally abundantly PSMA-positive secretory cells. We aimed to objectively quantify the dose-response of salivary glands using PSMA PET.

Material and Methods

30 H&N cancer patients were included in a prospective study. They received RT with 70 Gy in 35 fractions over 7 weeks. PSMA PET/CT was acquired in treatment position at baseline and at 6-months post-RT. The PET scans were deformably registered to the planning CT and the associated dose distribution. Dose, pre-RT SUV and post-RT SUV were extracted for every voxel inside each delineated parotid salivary gland. The data was analysed using a generalised linear mixed effects model using a log link. 

Results

Fig. 1 shows the dose distribution, and baseline and post-RT PSMA PET images of one patient. The baseline SUV was observed to moderate the effect of dose on the post-RT SUV. The population and patient-specific dose-response curves for the parotid glands, can be seen in Fig. 2. The model fit the data well with an R2 of 0.79. The D50 of the population-curve is 34 Gy. The population curve indicates that for a 1 Gy increase in dose, the post-treatment SUV decreases by 1.8%, for a baseline SUV of 10. 

Conclusion

The PSMA PET response in salivary glands after RT demonstrates a strong relationship between dose and loss of secretory cells. Differences in patient sensitivity can also be observed, which the model can account for. The population curve could potentially be used in dose planning, using a planning objective to maximize the predicted post-treatment SUV. This could be improved upon further by using a pre-treatment PSMA scan to get patient-specific curves.