eprintid: 34107
rev_number: 15
eprint_status: archive
userid: 5172
dir: disk0/00/03/41/07
datestamp: 2023-12-06 14:44:12
lastmod: 2023-12-12 13:25:14
status_changed: 2023-12-06 14:44:12
type: doctoralThesis
metadata_visibility: show
creators_name: Longarino, Friderike Katharina
title: Dual-energy computed tomography for predicting range in particle therapy
subjects: ddc-500
subjects: ddc-530
subjects: ddc-600
divisions: i-130001
divisions: i-850300
adv_faculty: af-13
abstract: Radiotherapy with protons or light ions is a highly precise form of cancer treatment. In treatment planning for particle therapy, ion stopping power ratio (SPR) maps of patient tissues are used to predict particle ranges and calculate dose distributions. To more accurately calculate dose distributions and minimize irradiating healthy tissue, it is crucial to improve SPR prediction. To this end, this thesis investigated dual-layer spectral computed tomography, a dual-energy CT (DECT) technique, as an alternative to conventional single-energy CT (SECT). The SECT-based method relies on converting CT numbers to SPR, yet CT numbers acquired from photon attenuation cannot be used to accurately predict energy loss by ions, which makes the approach indirect and heuristic. The DECT-based method, however, uses measurements of relative electron density and effective atomic number to directly and patient-specifically predict SPR. SPR prediction using DECT was evaluated in tissue-equivalent materials, anthropomorphic phantoms, and non-tissue materials; clinically analyzed in a retrospective patient study; and experimentally investigated for patients with dental materials. DECT-based SPR prediction improved dose calculation accuracy in particle therapy compared to SECT with a remaining range uncertainty of about 1% in controlled experimental scenarios. DECT may thus substantially improve range prediction for highly accurate particle therapy.
date: 2023
id_scheme: DOI
id_number: 10.11588/heidok.00034107
ppn_swb: 187318638X
own_urn: urn:nbn:de:bsz:16-heidok-341070
date_accepted: 2023-11-14
advisor: HASH(0x55fc36c87e40)
language: eng
bibsort: LONGARINOFDUALENERGY2023
full_text_status: public
place_of_pub: Heidelberg
citation:   Longarino, Friderike Katharina  (2023) Dual-energy computed tomography for predicting range in particle therapy.  [Dissertation]     
document_url: https://archiv.ub.uni-heidelberg.de/volltextserver/34107/1/Dissertation_FriderikeLongarino.pdf