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Deformable registration for quantifying longitudinal tumor changes during neoadjuvant chemotherapy
Author(s) -
Ou Yangming,
Weinstein Susan P.,
Conant Emily F.,
Englander Sarah,
Da Xiao,
Gaonkar Bilwaj,
Hsieh MengKang,
Rosen Mark,
DeMichele Angela,
Davatzikos Christos,
Kontos Despina
Publication year - 2015
Publication title -
magnetic resonance in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.696
H-Index - 225
eISSN - 1522-2594
pISSN - 0740-3194
DOI - 10.1002/mrm.25368
Subject(s) - image registration , magnetic resonance imaging , landmark , matching (statistics) , computer science , intensity (physics) , artificial intelligence , breast tumor , breast cancer , anatomical landmark , nuclear medicine , medicine , computer vision , radiology , image (mathematics) , cancer , surgery , pathology , physics , quantum mechanics
Purpose To evaluate DRAMMS, an attribute‐based deformable registration algorithm, compared to other intensity‐based algorithms, for longitudinal breast MRI registration, and to show its applicability in quantifying tumor changes over the course of neoadjuvant chemotherapy. Methods Breast magnetic resonance images from 14 women undergoing neoadjuvant chemotherapy were analyzed. The accuracy of DRAMMS versus five intensity‐based deformable registration methods was evaluated based on 2,380 landmarks independently annotated by two experts, for the entire image volume, different image subregions, and patient subgroups. The registration method with the smallest landmark error was used to quantify tumor changes, by calculating the Jacobian determinant maps of the registration deformation. Results DRAMMS had the smallest landmark errors (6.05 ± 4.86 mm), followed by the intensity‐based methods CC‐FFD (8.07 ± 3.86 mm), NMI‐FFD (8.21 ± 3.81 mm), SSD‐FFD (9.46 ± 4.55 mm), Demons (10.76 ± 6.01 mm), and Diffeomorphic Demons (10.82 ± 6.11 mm). Results show that registration accuracy also depends on tumor versus normal tissue regions and different patient subgroups. Conclusions The DRAMMS deformable registration method, driven by attribute‐matching and mutual‐saliency, can register longitudinal breast magnetic resonance images with a higher accuracy than several intensity‐matching methods included in this article. As such, it could be valuable for more accurately quantifying heterogeneous tumor changes as a marker of response to treatment. Magn Reson Med 73:2343–2356, 2015. © 2014 Wiley Periodicals, Inc.