Optimierung und klinische Evaluation einer intelligenten Atlas-basierten semiautomatischen Zielvolumendefinition am Beispiel von Kopf-Hals-Tumoren
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Philipps-Universität Marburg
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Abstract
The aim of this work was to optimize in constant cooperation with the
department of Informatics of the "Rhein-Main-Hochschule" a method for
(semi-)automatic target volume definition using the example of head and neck
cancers, in special the CTV 3 of laryngeal carcinoma, and to evaluate the use in
clinical practice.
The developed method is based on building an atlas consisting of a target
volume and a landmark model of n-CT data sets. This approximate atlas volume
can be transferred by an affine transformation on an individual patient data set,
in which defined landmarks are marked. The landmarks describe characteristic
reproducible anatomical structures, that represent the individual anatomy of the
patient.
First, 10 CT data sets of patients with head and neck cancer were selected. In
each of these data sets one pre-defined reference target volume and the socalled
landmarks, which were defined on different levels of the target volume,
were drawn. Afterwards a target volume atlas was generated.
The Similarity Index, that quantifies the over-lapping of two volumes as a
percentage, is used to compare the different volumes.
The originally defined landmarks have been improved by a systematic reduction
method and clinical assessment. So the Similarty Index of 73% of the 16
landmarks could be increased to 77 % for 13 optimized landmarks.
To evaluate the clinical applicability of (semi-)automatic target volume definition
5 physicians, who are experienced in contouring target volumes in head and
neck region, manually drew the target volume for locally advanced laryngeal
carcinoma in two different CT data sets. They also marked the optimized
landmarks in these two CT data sets. A target volume was then automatically
generated by using the atlas. This automatically generated volume was then
evaluated and adjusted by the physician who marked the landmarks. So a semiautomatic
created target volume resulted.
In comparison to the reference volume the average similarity index of the
manual contouring was 76%, the one of the automatic target volume delineationwas 74% and the one of the semi-automatic method was 79%.
Manual contouring required an average duration of 28.7 minutes, whereas the
automatic atlas based target volume definition was finished in 2.4 minutes and
the semiautomatic method in 13.8 minutes. So a time saving of about 52 % for
the semiautomatic delineation method and about 91% for automatic contouring
in comparison with the manual delineation could be achieved.
The comparisons of the delineated target volumes within the 5 physicians
showed Similarity Indices for the manual volume definition from 64% to 80 %
and for the semi-automatic contouring from 73 to 83%. This shows that the
interobserver variability is reduced by using the semi-automatic atlas-based
method.
In summary, it was shown that atlas-based semi-automatic target volume
definition in head and neck cancer is clinically applicable and combines the
advantages of time saving and reduced interobserver variability.
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Dates
Created: 2011Issued: 2011-03-18Updated: 2011-08-08
Faculty
Medizin
Publisher
Philipps-Universität Marburg
Language
ger
Data types
DoctoralThesis
Keywords
Semi automaticTarget Volume DefinitionHead&Neck-CancerZielvolumendefinition semiautomatisch
DFG-subjects
Hals-Nasen-Ohren-TumorStrahlentherapie
DDC-Numbers
610
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Haderlein, Marlen (143796356): Optimierung und klinische Evaluation einer intelligenten Atlas-basierten semiautomatischen Zielvolumendefinition am Beispiel von Kopf-Hals-Tumoren. : Philipps-Universität Marburg 2011-03-18. DOI: https://doi.org/10.17192/z2011.0247.
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This item has been published with the following license: In Copyright