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Dose response modelling of secretory cell loss in salivary glands using PSMA PET
- Source :
- Radiotherapy and Oncology, 177, 164-171. ELSEVIER IRELAND LTD
- Publication Year :
- 2022
- Publisher :
- ELSEVIER IRELAND LTD, 2022.
-
Abstract
- Background and purpose: 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. Secretory salivary gland cells express the prostate-specific membrane antigen (PSMA), and show significant uptake on PET scans using 68Ga/18F-PSMA-ligands. We aimed to objectively quantify the dose–response of salivary glands to RT using PSMA PET. Methods and materials: 28H&N cancer patients received RT with 70 Gy in 35 fractions over 7 weeks. PSMA PET/CT was acquired at baseline (BL), during treatment (DT) and at 1-&6-months post-treatment (PT1M/PT6M). Dose, BL- PT1M- and PT6M-SUV were extracted for every voxel inside each parotid (PG) and submandibular (SMG) gland. The PT1M/6M data was analysed using a generalised linear mixed effects model. Patient-reported xerostomia and DT-PSMA loss was also analysed. Results: Dose had a relative effect on BL SUV. For a population average gland (BL-SUV of 10), every 1 Gy increment, decreased the PT1M/PT6M-SUV by 1.6 %/1.6 % for PGs and by 0.9 %/1.8 % for SMGs. TD50 of the population curves was 26.5/31.3 Gy for PGs, and 22.9/27.8 Gy for SMGs at PT1M /PT6M. PSMA loss correlated well with patient-reported xerostomia at DT/PT1M (Spearman's ρ = -0.64, −0.50). Conclusion: A strong relationship was demonstrated between radiation dose and loss of secretory cells in salivary glands derived using PSMA PET/CT. The population curve could potentially be used as a dose planning objective, by maximising the predicted post-treatment SUV. BL scans could be used to further tailor this to individual patients.
Details
- Language :
- English
- ISSN :
- 18790887 and 01678140
- Volume :
- 177
- Database :
- OpenAIRE
- Journal :
- Radiotherapy and Oncology
- Accession number :
- edsair.doi.dedup.....764cd30b88cb07056a0c2a8fedfa4328
- Full Text :
- https://doi.org/10.1016/j.radonc.2022.10.038