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@PHDTHESIS{Hild:184427,
author = {Hild, Sebastian},
othercontributors = {Bert, Christoph and Fietkau, Rainer and Hensel, Bernhard
and Durante, Marco},
title = {{A}daptive {T}reatment of prostate carcinoma in scanned ion
beam therapy [cumulative {P}h{D}]},
school = {Friedrich-Alexander-Universität Erlangen-Nürnberg},
type = {Dr.},
reportid = {GSI-2016-00157},
pages = {-},
year = {2015},
note = {The Thesis is presented as a cumulative work of two
publications (see linked works).
https://repository.gsi.de/record/96010 and
https://repository.gsi.de/record/184394 .;
Friedrich-Alexander-Universität Erlangen-Nürnberg, Diss.,
2015},
abstract = {Radiation therapy for prostate carcinoma (PCa) is
challenged in part by large target dislocations between
single fractions (interfraction motion). To prevent
geometrical target misses, in clinical practice the volume
to be irradiated is enlarged by so called safety margins of
typically 5 to 12 mm, in some cases even up to 15 mm, in any
direction. The extension causes an unnecessary dose
delivered to healthy tissue and radiation sensitive organs
like the bladder and the rectum. Toxicity in these organs
restricts the maximum target dose which has been found to
improve tumor control if increased. In this work, adaptive
radiation therapy (ART) strategies have been analyzed for
their possible application in prostate cancer therapy. For
this purpose, scanned ion beam therapy, which is known to
feature a highly conformal dose delivery, was combined with
two ART strategies: image guided target definition and daily
plan re-optimization. As a proof of concept, the treatment
planning software for particles TRiP, developed at GSI
Helmholtz Center for Heavy Ion Research (GSI) in Darmstadt,
Germany, has been optimized for calculation speed. A
reduction of computation time from 4 hours to 6 min for a
two-field prostate plan demonstrated the plausibility of
daily plan re-optimization. In addition a treatment
simulation study on a dataset containing 60 computed
tomography scans (CTs) of ten prostate cancer patients has
been designed comparing the performance of image guided
target definition and daily plan re-optimization with
conventional one plan radiotherapy. In the presented dataset
$20\%$ of the patients showed considerable motion (mean 3D
vector length > 4 mm). The fraction of the target volume
receiving at least $95\%$ of the prescribed target dose in
$5\%$ of all fractions $(V955\%)$ for these patients was
lower than 0.64 (mean 0.87) and lower than 0.66 (mean 0.91)
for conventional one-plan particle therapy and image guided
target definition, respectively. In patients showing only
small motion(mean 3D vector length < 4 mm), image guided
target definition reduced the mean rectal volume receiving
more than $60\%$ target dose (V60mean) by $13\%$ at slightly
but significantly improved target coverage. Daily
re-optimization, the most versatile correction method, kept
target coverage in all patients above $95\%$ of the
prescribed dose and reduced the rectal V60mean by $37\%$ and
$47\%$ for patients with large and small motion,
respectively, due to the possible margin reduction. It has
been shown in this work that treatment replanning can become
possible in the future. Patients exhibiting large prostate
motion will greatly benefit of such on line adaptation
strategies, while adaptation could be completely omitted in
patients showing small prostate displacements only. For
motion classification, pre treatment motion assessment,
using repeated imaging sessions, would be the preferable
approach. The best suited treatment modality/protocol that
way can be determined before a therapy course is started and
reduce the additional workload coming from adaptation
protocols to a minimum. Treatment replanning still waits for
advances in hard- and software development, to ease the
entire TRP process and thereby permit integration in a
clinical environment. Based on the findings of this work,
dedicated motion management is indicated for one fifth of
the patients in PT of the prostate.},
cin = {BIO},
ddc = {610},
cid = {I:(DE-Ds200)BIO-20160831OR354},
pnm = {315 - Imaging and radiooncology (POF3-315)},
pid = {G:(DE-HGF)POF3-315},
typ = {PUB:(DE-HGF)11},
url = {https://repository.gsi.de/record/184427},
}