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Optimisation of 90Y Selective Internal Radiation Therapy (SIRT) Procedures: towards improved personalised dosimetry
Author(s)
Date Issued
2025
Date Available
2025-10-24T13:39:02Z
Abstract
Selective internal radiation therapy (SIRT) is a well-established therapy for treating unresectable hepatocellular carcinoma (HCC). The current PhD research, identified and quantified uncertainties in the dosimetric process for 90Y SIRT treatments and developed new methods for improved accuracy in the dose estimation and delivery. Current planar nuclear medicine imaging methods often overestimate the Lung Shunt Fraction (LSF). A new scatter correction method was developed, improving LSF accuracy which is easily implementable in any standard nuclear medicine department. The improved accuracy of SPECT/CT LSF estimation was demonstrated using realistic 4D anatomical phantoms. The corrected planar method from the first study also showed comparable accuracy, offering a simpler alternative. The implications of tumour delineation among different radiologists on the dosimetric accuracy in SIRT was investigated. Post-treatment 90Y PET/CT is challenging due to the decay characteristics of 90Y which makes dose verification challenging. This study optimised imaging parameters for 90Y PET/CT following SIRT. The irregular shape of liver tumours make dose quantification challenging. Radiomic analysis of SIRT patient data was used to 3D-print tumour models and imaged to assess the uncertainties non-spherical objects have on quantitative 90Y PET/CT. The work presented in this thesis has addressed some of the challenges associated with the dosimetric accuracy in SIRT therapies and provides a means for correcting for some of these limitations.
Type of Material
Doctoral Thesis
Qualification Name
Doctor of Philosophy (Ph.D.)
Publisher
University College Dublin. School of Physics
Copyright (Published Version)
2025 the Author
Language
English
Status of Item
Peer reviewed
This item is made available under a Creative Commons License
File(s)
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Name
Full Thesis NMA.pdf
Size
5.47 MB
Format
Adobe PDF
Checksum (MD5)
efa0795845a30702323067e961565672
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