Improving oncoplastic breast tumor bed localization for radiotherapy planning using image registration algorithms
PBN-AR
Instytucja
Wydział Elektrotechniki, Automatyki, Informatyki i Inżynierii Biomedycznej (Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie)
Informacje podstawowe
Główny język publikacji
EN
Czasopismo
Physics in Medicine and Biology (35pkt w roku publikacji)
ISSN
0031-9155
EISSN
1361-6560
Wydawca
IOP Publishing Ltd.
DOI
Rok publikacji
2018
Numer zeszytu
3 art. no. 035024
Strony od-do
1--19
Numer tomu
63
Link do pełnego tekstu
Identyfikator DOI
Liczba arkuszy
1.35
Autorzy
Pozostali autorzy
+ 3
Autorzy przekładu
(liczba autorów przekładu: 0)
Słowa kluczowe
EN
radiotherapy
image registration
discontinuous deformation
breast cancer
oncoplastic surgery
breast-conserving therapy
tumor bed
Streszczenia
Język
EN
Treść
Knowledge about tumor bed localization and its shape analysis is a crucial factor for preventing irradiation of healthy tissues during supportive radiotherapy and as a result, cancer recurrence. The localization process is especially hard for tumors placed nearby soft tissues, which undergo complex, nonrigid deformations. Among them, breast cancer can be considered as the most representative example. A natural approach to improving tumor bed localization is the use of image registration algorithms. However, this involves two unusual aspects which are not common in typical medical image registration: the real deformation field is discontinuous, and there is no direct correspondence between the cancer and its bed in the source and the target 3D images respectively. The tumor no longer exists during radiotherapy planning. Therefore, a traditional evaluation approach based on known, smooth deformations and target registration error are not directly applicable. In this work, we propose alternative artificial deformations which model the tumor bed creation process. We perform a comprehensive evaluation of the most commonly used deformable registration algorithms: B-Splines free form deformations (B-Splines FFD), different variants of the Demons and TV-L1 optical flow. The evaluation procedure includes quantitative assessment of the dedicated artificial deformations, target registration error calculation, 3D contour propagation and medical experts visual judgment. The results demonstrate that the currently, practically applied image registration (rigid registration and B-Splines FFD) are not able to correctly reconstruct discontinuous deformation fields. We show that the symmetric Demons provide the most accurate soft tissues alignment in terms of the ability to reconstruct the deformation field, target registration error and relative tumor volume change, while B-Splines FFD and TV-L1 optical flow are not an appropriate choice for the breast tumor bed localization problem, even though the visual alignment seems to be better than for the Demons algorithm. However, no algorithm could recover the deformation field with sufficient accuracy in terms of vector length and rotation angle differences.
Cechy publikacji
original article
peer-reviewed
Inne
System-identifier
idp:112245
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