A mechanically coupled reaction diffusion model of breast tumor response during neoadjuvant chemotherapy

Jared A. Weis, Michael I. Miga, Xia Li, Lori R. Arlinghaus, A. Bapsi Chakravarthy, Vandana Abramson, Richard G. Abramson, Jaime Farley, Thomas Yankeelov

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

Abstract

There is currently a paucity of reliable techniques for predicting the response of breast tumors to neoadjuvant chemotherapy. The standard approach is to monitor gross changes in tumor size as measured by physical exam and/or conventional imaging, but these methods generally do not show whether a tumor is responding until the patient has completed therapy. One promising approach to address this clinical need is to integrate quantitative in vivo imaging data into biomathematical models of tumor growth in order to predict eventual response based on early measurements during therapy. Contrast enhanced and diffusion weighted magnetic resonance imaging data acquired before and after the first cycle of therapy to calibrate a patient-specific response model can be used to predict patient outcome at the conclusion of therapy. We have developed a mathematical modeling approach to optimize key model parameters for the calibration of a patient-specific mechanically coupled reaction-diffusion model of response. We apply the approach to patient data in which tumors were either responsive or non-responsive to neoajuvant chemotherapy and demonstrate changes to the patient-specific model which result in altered growth patterns. Additionally, we show that reconstructed parameter maps exhibit drastic differences between patients with different tumor burden outcomes at the conclusion of therapy, in this case, a 10-fold increase in proliferative capacity is found for a non-responding tumor versus its responsive counterpart. Finally, we show that the mechanically coupled reaction-diffusion growth model, when projected forward, more accurately predicts residual tumor burden than the uncoupled model.

Original languageEnglish (US)
Title of host publicationMedical Imaging 2013
Subtitle of host publicationBiomedical Applications in Molecular, Structural, and Functional Imaging
DOIs
StatePublished - Jun 3 2013
EventMedical Imaging 2013: Biomedical Applications in Molecular, Structural, and Functional Imaging - Lake Buena Vista, FL, United States
Duration: Feb 10 2013Feb 13 2013

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume8672
ISSN (Print)1605-7422

Other

OtherMedical Imaging 2013: Biomedical Applications in Molecular, Structural, and Functional Imaging
CountryUnited States
CityLake Buena Vista, FL
Period2/10/132/13/13

Fingerprint

Chemotherapy
chemotherapy
breast
Tumors
tumors
Breast Neoplasms
Drug Therapy
therapy
Neoplasms
Tumor Burden
Imaging techniques
Growth
Therapeutics
Diffusion Magnetic Resonance Imaging
Residual Neoplasm
Magnetic resonance
Calibration
magnetic resonance
cycles

Keywords

  • Breast cancer
  • Mathematical model
  • Mechanical model
  • Neoadjuvant chemotherapy
  • Parameter reconstruction
  • Reaction-diffusion model
  • Tumor growth

ASJC Scopus subject areas

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

Cite this

Weis, J. A., Miga, M. I., Li, X., Arlinghaus, L. R., Chakravarthy, A. B., Abramson, V., ... Yankeelov, T. (2013). A mechanically coupled reaction diffusion model of breast tumor response during neoadjuvant chemotherapy. In Medical Imaging 2013: Biomedical Applications in Molecular, Structural, and Functional Imaging [86721G] (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 8672). https://doi.org/10.1117/12.2007961

A mechanically coupled reaction diffusion model of breast tumor response during neoadjuvant chemotherapy. / Weis, Jared A.; Miga, Michael I.; Li, Xia; Arlinghaus, Lori R.; Chakravarthy, A. Bapsi; Abramson, Vandana; Abramson, Richard G.; Farley, Jaime; Yankeelov, Thomas.

Medical Imaging 2013: Biomedical Applications in Molecular, Structural, and Functional Imaging. 2013. 86721G (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 8672).

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

Weis, JA, Miga, MI, Li, X, Arlinghaus, LR, Chakravarthy, AB, Abramson, V, Abramson, RG, Farley, J & Yankeelov, T 2013, A mechanically coupled reaction diffusion model of breast tumor response during neoadjuvant chemotherapy. in Medical Imaging 2013: Biomedical Applications in Molecular, Structural, and Functional Imaging., 86721G, Progress in Biomedical Optics and Imaging - Proceedings of SPIE, vol. 8672, Medical Imaging 2013: Biomedical Applications in Molecular, Structural, and Functional Imaging, Lake Buena Vista, FL, United States, 2/10/13. https://doi.org/10.1117/12.2007961
Weis JA, Miga MI, Li X, Arlinghaus LR, Chakravarthy AB, Abramson V et al. A mechanically coupled reaction diffusion model of breast tumor response during neoadjuvant chemotherapy. In Medical Imaging 2013: Biomedical Applications in Molecular, Structural, and Functional Imaging. 2013. 86721G. (Progress in Biomedical Optics and Imaging - Proceedings of SPIE). https://doi.org/10.1117/12.2007961
Weis, Jared A. ; Miga, Michael I. ; Li, Xia ; Arlinghaus, Lori R. ; Chakravarthy, A. Bapsi ; Abramson, Vandana ; Abramson, Richard G. ; Farley, Jaime ; Yankeelov, Thomas. / A mechanically coupled reaction diffusion model of breast tumor response during neoadjuvant chemotherapy. Medical Imaging 2013: Biomedical Applications in Molecular, Structural, and Functional Imaging. 2013. (Progress in Biomedical Optics and Imaging - Proceedings of SPIE).
@inproceedings{6223b0f4e8e84956867b25b8e8d6f923,
title = "A mechanically coupled reaction diffusion model of breast tumor response during neoadjuvant chemotherapy",
abstract = "There is currently a paucity of reliable techniques for predicting the response of breast tumors to neoadjuvant chemotherapy. The standard approach is to monitor gross changes in tumor size as measured by physical exam and/or conventional imaging, but these methods generally do not show whether a tumor is responding until the patient has completed therapy. One promising approach to address this clinical need is to integrate quantitative in vivo imaging data into biomathematical models of tumor growth in order to predict eventual response based on early measurements during therapy. Contrast enhanced and diffusion weighted magnetic resonance imaging data acquired before and after the first cycle of therapy to calibrate a patient-specific response model can be used to predict patient outcome at the conclusion of therapy. We have developed a mathematical modeling approach to optimize key model parameters for the calibration of a patient-specific mechanically coupled reaction-diffusion model of response. We apply the approach to patient data in which tumors were either responsive or non-responsive to neoajuvant chemotherapy and demonstrate changes to the patient-specific model which result in altered growth patterns. Additionally, we show that reconstructed parameter maps exhibit drastic differences between patients with different tumor burden outcomes at the conclusion of therapy, in this case, a 10-fold increase in proliferative capacity is found for a non-responding tumor versus its responsive counterpart. Finally, we show that the mechanically coupled reaction-diffusion growth model, when projected forward, more accurately predicts residual tumor burden than the uncoupled model.",
keywords = "Breast cancer, Mathematical model, Mechanical model, Neoadjuvant chemotherapy, Parameter reconstruction, Reaction-diffusion model, Tumor growth",
author = "Weis, {Jared A.} and Miga, {Michael I.} and Xia Li and Arlinghaus, {Lori R.} and Chakravarthy, {A. Bapsi} and Vandana Abramson and Abramson, {Richard G.} and Jaime Farley and Thomas Yankeelov",
year = "2013",
month = "6",
day = "3",
doi = "10.1117/12.2007961",
language = "English (US)",
isbn = "9780819494467",
series = "Progress in Biomedical Optics and Imaging - Proceedings of SPIE",
booktitle = "Medical Imaging 2013",

}

TY - GEN

T1 - A mechanically coupled reaction diffusion model of breast tumor response during neoadjuvant chemotherapy

AU - Weis, Jared A.

AU - Miga, Michael I.

AU - Li, Xia

AU - Arlinghaus, Lori R.

AU - Chakravarthy, A. Bapsi

AU - Abramson, Vandana

AU - Abramson, Richard G.

AU - Farley, Jaime

AU - Yankeelov, Thomas

PY - 2013/6/3

Y1 - 2013/6/3

N2 - There is currently a paucity of reliable techniques for predicting the response of breast tumors to neoadjuvant chemotherapy. The standard approach is to monitor gross changes in tumor size as measured by physical exam and/or conventional imaging, but these methods generally do not show whether a tumor is responding until the patient has completed therapy. One promising approach to address this clinical need is to integrate quantitative in vivo imaging data into biomathematical models of tumor growth in order to predict eventual response based on early measurements during therapy. Contrast enhanced and diffusion weighted magnetic resonance imaging data acquired before and after the first cycle of therapy to calibrate a patient-specific response model can be used to predict patient outcome at the conclusion of therapy. We have developed a mathematical modeling approach to optimize key model parameters for the calibration of a patient-specific mechanically coupled reaction-diffusion model of response. We apply the approach to patient data in which tumors were either responsive or non-responsive to neoajuvant chemotherapy and demonstrate changes to the patient-specific model which result in altered growth patterns. Additionally, we show that reconstructed parameter maps exhibit drastic differences between patients with different tumor burden outcomes at the conclusion of therapy, in this case, a 10-fold increase in proliferative capacity is found for a non-responding tumor versus its responsive counterpart. Finally, we show that the mechanically coupled reaction-diffusion growth model, when projected forward, more accurately predicts residual tumor burden than the uncoupled model.

AB - There is currently a paucity of reliable techniques for predicting the response of breast tumors to neoadjuvant chemotherapy. The standard approach is to monitor gross changes in tumor size as measured by physical exam and/or conventional imaging, but these methods generally do not show whether a tumor is responding until the patient has completed therapy. One promising approach to address this clinical need is to integrate quantitative in vivo imaging data into biomathematical models of tumor growth in order to predict eventual response based on early measurements during therapy. Contrast enhanced and diffusion weighted magnetic resonance imaging data acquired before and after the first cycle of therapy to calibrate a patient-specific response model can be used to predict patient outcome at the conclusion of therapy. We have developed a mathematical modeling approach to optimize key model parameters for the calibration of a patient-specific mechanically coupled reaction-diffusion model of response. We apply the approach to patient data in which tumors were either responsive or non-responsive to neoajuvant chemotherapy and demonstrate changes to the patient-specific model which result in altered growth patterns. Additionally, we show that reconstructed parameter maps exhibit drastic differences between patients with different tumor burden outcomes at the conclusion of therapy, in this case, a 10-fold increase in proliferative capacity is found for a non-responding tumor versus its responsive counterpart. Finally, we show that the mechanically coupled reaction-diffusion growth model, when projected forward, more accurately predicts residual tumor burden than the uncoupled model.

KW - Breast cancer

KW - Mathematical model

KW - Mechanical model

KW - Neoadjuvant chemotherapy

KW - Parameter reconstruction

KW - Reaction-diffusion model

KW - Tumor growth

UR - http://www.scopus.com/inward/record.url?scp=84878292900&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84878292900&partnerID=8YFLogxK

U2 - 10.1117/12.2007961

DO - 10.1117/12.2007961

M3 - Conference contribution

AN - SCOPUS:84878292900

SN - 9780819494467

T3 - Progress in Biomedical Optics and Imaging - Proceedings of SPIE

BT - Medical Imaging 2013

ER -