Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.821704
Title: Personalised advanced 3D dosimetry in peptide receptor radionuclide therapy
Author: Berenato, Salvatore
ISNI:       0000 0005 0285 3792
Awarding Body: Cardiff University
Current Institution: Cardiff University
Date of Award: 2020
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Abstract:
Peptide Receptor Radionuclide Therapy is one of the most efficient therapies against Neuro endocrine tumours. In clinical practice, absorbed dose calculations are computed based on the Medical Internal Radiation Dose (MIRD) schema which is not planned or optimised for patient-specific characteristics. This PhD project has aimed to assess the impact that advanced personalised 3D dosimetry can have within a Molecular Radiotherapy (MRT) treatment with an image-based dosimetry component. For this purpose, the impact of image registration algorithms has been studied, comparing rigid and non-rigid schemes. Results showed that nonrigid algorithms performed better than rigid equivalents in aligning images to the same frame of reference. The non-rigid algorithm was then used to investigate a workflow which involved dose maps instead of SPECT images, because such analysis has not previously been reported in the literature. Raydose, a Monte Carlo-based software package, was used to perform 3D personalised dosimetry; the results were compared against the calculations carried out with OLINDA/EXM, a MIRD-based software system. Differences were statistically significant only for kidneys and lesions (p-value < 0.005). Finally, a new segmentation method for tumour delineation is described and its performance compared with a manual segmentation performed by expert 2 physicians. JACCARD analysis showed that the two methods do not have a good overlap (mean JACCARD coefficient = 0.29). From visual assessment, the proposed approach obtained better results than the manual segmentation according to the target tissue characteristics. Furthermore, quantitative analysis showed that the manual segmentation significantly overestimates the volume by 3.7 ± 13.3 cc (p-value < 0.05), while it significantly underestimates the dose by -2.67 ± 6.8 Gy (p-value < 0.05) compared to the proposed method. This study has demonstrated the importance of assessing accurate personalised 3D absorbed dose distribution to lesions and organs at risk. It also has the potential to be extended to other MRT treatments and other tumour sites.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.821704  DOI: Not available
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