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 publicationProgress in Biomedical Optics and Imaging - Proceedings of SPIE
PublisherSPIE
Volume9414
ISBN (Print)9781628415049, 9781628415049
DOIs
StatePublished - 2015
Externally publishedYes
EventSPIE Medical Imaging Symposium 2015: Computer-Aided Diagnosis - Orlando, United States
Duration: Feb 22 2015Feb 25 2015

Other

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

Fingerprint

Chemotherapy
chemotherapy
breast
Magnetic resonance imaging
Tumors
Breast
tumors
Drug Therapy
landmarks
Neoplasms
Imaging techniques
Breast Neoplasms
Tissue
Tumor Biomarkers
biomarkers
Biomarkers
grade
evaluation

Keywords

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

ASJC Scopus subject areas

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

Cite this

Wu, J., Ou, Y., Weinstein, S. P., Conant, E. F., Yu, N., Hoshmand, V., ... Kontos, D. (2015). Quantification of tumor changes during neoadjuvant chemotherapy with longitudinal breast DCE-MRI registration. In Progress in Biomedical Optics and Imaging - Proceedings of SPIE (Vol. 9414). [94141Z] SPIE. https://doi.org/10.1117/12.2081938

Quantification of tumor changes during neoadjuvant chemotherapy with longitudinal breast DCE-MRI registration. / Wu, Jia; Ou, Yangming; Weinstein, Susan P.; Conant, Emily F.; Yu, Ning; Hoshmand, Vahid; Keller, Brad; Ashraf, Ahmed B.; Rosen, Mark; Demichele, Angela; Davatzikos, Christos; Kontos, Despina.

Progress in Biomedical Optics and Imaging - Proceedings of SPIE. Vol. 9414 SPIE, 2015. 94141Z.

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

Wu, J, Ou, Y, Weinstein, SP, Conant, EF, Yu, N, Hoshmand, V, Keller, B, Ashraf, AB, Rosen, M, Demichele, A, Davatzikos, C & Kontos, D 2015, Quantification of tumor changes during neoadjuvant chemotherapy with longitudinal breast DCE-MRI registration. in Progress in Biomedical Optics and Imaging - Proceedings of SPIE. vol. 9414, 94141Z, SPIE, SPIE Medical Imaging Symposium 2015: Computer-Aided Diagnosis, Orlando, United States, 2/22/15. https://doi.org/10.1117/12.2081938
Wu J, Ou Y, Weinstein SP, Conant EF, Yu N, Hoshmand V et al. Quantification of tumor changes during neoadjuvant chemotherapy with longitudinal breast DCE-MRI registration. In Progress in Biomedical Optics and Imaging - Proceedings of SPIE. Vol. 9414. SPIE. 2015. 94141Z https://doi.org/10.1117/12.2081938
Wu, Jia ; Ou, Yangming ; Weinstein, Susan P. ; Conant, Emily F. ; Yu, Ning ; Hoshmand, Vahid ; Keller, Brad ; Ashraf, Ahmed B. ; Rosen, Mark ; Demichele, Angela ; Davatzikos, Christos ; Kontos, Despina. / Quantification of tumor changes during neoadjuvant chemotherapy with longitudinal breast DCE-MRI registration. Progress in Biomedical Optics and Imaging - Proceedings of SPIE. Vol. 9414 SPIE, 2015.
@inproceedings{a5f9d8e980d34f71b29b166b4514f00e,
title = "Quantification of tumor changes during neoadjuvant chemotherapy with longitudinal breast DCE-MRI registration",
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.",
keywords = "Breast Tumor, DCE-MRI, Deformable Registration, Neoadjuvant Chemotherapy, Tumor Response",
author = "Jia Wu and Yangming Ou and Weinstein, {Susan P.} and Conant, {Emily F.} and Ning Yu and Vahid Hoshmand and Brad Keller and Ashraf, {Ahmed B.} and Mark Rosen and Angela Demichele and Christos Davatzikos and Despina Kontos",
year = "2015",
doi = "10.1117/12.2081938",
language = "English (US)",
isbn = "9781628415049",
volume = "9414",
booktitle = "Progress in Biomedical Optics and Imaging - Proceedings of SPIE",
publisher = "SPIE",

}

TY - GEN

T1 - Quantification of tumor changes during neoadjuvant chemotherapy with longitudinal breast DCE-MRI registration

AU - Wu, Jia

AU - Ou, Yangming

AU - Weinstein, Susan P.

AU - Conant, Emily F.

AU - Yu, Ning

AU - Hoshmand, Vahid

AU - Keller, Brad

AU - Ashraf, Ahmed B.

AU - Rosen, Mark

AU - Demichele, Angela

AU - Davatzikos, Christos

AU - Kontos, Despina

PY - 2015

Y1 - 2015

N2 - 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.

AB - 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.

KW - Breast Tumor

KW - DCE-MRI

KW - Deformable Registration

KW - Neoadjuvant Chemotherapy

KW - Tumor Response

UR - http://www.scopus.com/inward/record.url?scp=84948808676&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84948808676&partnerID=8YFLogxK

U2 - 10.1117/12.2081938

DO - 10.1117/12.2081938

M3 - Conference contribution

SN - 9781628415049

SN - 9781628415049

VL - 9414

BT - Progress in Biomedical Optics and Imaging - Proceedings of SPIE

PB - SPIE

ER -