Quantification of tumor changes during neoadjuvant chemotherapy with longitudinal breast DCE-MRI registration

Jia Wu, Yangming Ou, Susan P. Weinstein, Emily F. Conant, Ning Yu, Vahid Hoshmand, Brad Keller, Ahmed B. Ashraf, Mark Rosen, Angela Demichele, Christos Davatzikos, Despina Kontos

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Imaging plays a central role in the evaluation of breast tumor response to neoadjuvant chemotherapy. Image-based assessment of tumor change via deformable registration is a powerful, quantitative method potentially to explore novel information of tumor heterogeneity, structure, function, and treatment response. In this study, we continued a previous pilot study to further validate the feasibility of an open source deformable registration algorithm DRAMMS developed within our group as a means to analyze spatiooral tumor changes for a set of 14 patients with DCE-MR imaging. Two experienced breast imaging radiologists marked landmarks according to their anatomical meaning on image sets acquired before and during chemotherapy. Yet, chemotherapy remarkably changed the anatomical structure of both tumor and normal breast tissue, leading to significant discrepancies between both raters for landmarks in certain areas. Therefore, we proposed a novel method to grade the manually denoted landmarks into different challenge levels based on the inter-rater agreement, where a high level indicates significant discrepancies and considerable amounts of anatomical structure changes, which would indeed impose giant problem for the following registration algorithm. It is interesting to observe that DRAMMS performed in a similar manner as the human raters: landmark errors increased as inter-rater differences rose. Among all selected six deformable registration algorithms, DRAMMS achieves the highest overall accuracy, which is around 5.5 mm, while the average difference between human raters is 3 mm. Moreover, DRAMMS performed consistently well within both tumor and normal tissue regions. Lastly, we comprehensively tuned the fundamental parameters of DRAMMS to better understand DRAMMS to guide similar works in the future. Overall, we further validated that DRAMMS is a powerful registration tool to accurately quantify tumor changes and potentially predict early tumor response to chemotherapy. Therefore, future studies that aim at examining if DRAMMS can generate valuable biomarkers for tumor response prediction during chemotherapy become feasible.

Original languageEnglish (US)
Title of host publicationMedical Imaging 2015
Subtitle of host publicationComputer-Aided Diagnosis
EditorsLubomir M. Hadjiiski, Lubomir M. Hadjiiski, Georgia D. Tourassi, Georgia D. Tourassi
PublisherSPIE
ISBN (Electronic)9781628415049, 9781628415049
DOIs
StatePublished - Jan 1 2015
EventSPIE Medical Imaging Symposium 2015: Computer-Aided Diagnosis - Orlando, United States
Duration: Feb 22 2015Feb 25 2015

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume9414
ISSN (Print)1605-7422

Other

OtherSPIE Medical Imaging Symposium 2015: Computer-Aided Diagnosis
CountryUnited States
CityOrlando
Period2/22/152/25/15

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Keywords

  • Breast Tumor
  • DCE-MRI
  • Deformable Registration
  • Neoadjuvant Chemotherapy
  • Tumor Response

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Biomaterials
  • Atomic and Molecular Physics, and Optics
  • Radiology Nuclear Medicine and imaging

Cite this

Wu, J., Ou, Y., Weinstein, S. P., Conant, E. F., Yu, N., Hoshmand, V., Keller, B., Ashraf, A. B., Rosen, M., Demichele, A., Davatzikos, C., & Kontos, D. (2015). Quantification of tumor changes during neoadjuvant chemotherapy with longitudinal breast DCE-MRI registration. In L. M. Hadjiiski, L. M. Hadjiiski, G. D. Tourassi, & G. D. Tourassi (Eds.), Medical Imaging 2015: Computer-Aided Diagnosis [94141Z] (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 9414). SPIE. https://doi.org/10.1117/12.2081938