Model-based reconstruction for undersampled dynamic contrast-enhanced MRI

Ben K. Felsted, Ross T. Whitaker, Matthias Schabel, Edward V R DiBell

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

3 Citations (Scopus)

Abstract

This paper describes a method for estimating, from dynamic contrast-enhanced MRI raw k-space data of the breast, parameter maps that model tissue properties associated with a compartmental model of contrast exchange. The contrast agent kinetics, as represented by these parameter maps, are important in distinguishing benign and malignant tumors. The proposed model-based reconstruction algorithm estimates tissue parameter maps directly from MRI k-space data, thereby allowing a new and improved set of spatiotemporal resolution and noise tradeoffs. Realistic noise levels and an undersampling factor of R=4 appeared to provide reasonable accuracy for the kinetic parameters of interest.

Original languageEnglish (US)
Title of host publicationProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume7262
DOIs
StatePublished - 2009
Externally publishedYes
EventMedical Imaging 2009: Biomedical Applications in Molecular, Structural, and Functional Imaging - Lake Buena Vista, FL, United States
Duration: Feb 8 2009Feb 10 2009

Other

OtherMedical Imaging 2009: Biomedical Applications in Molecular, Structural, and Functional Imaging
CountryUnited States
CityLake Buena Vista, FL
Period2/8/092/10/09

Fingerprint

Magnetic resonance imaging
Noise
R Factors
Tissue
Contrast Media
Breast
Kinetic parameters
Tumors
kinetics
tradeoffs
breast
Neoplasms
Kinetics
estimating
tumors
estimates

Keywords

  • Breast imaging
  • Dynamic contrast-enhanced magnetic resonance imaging
  • Iterative reconstruction
  • Model-based reconstruction
  • Pharmacokinetic modeling
  • Undersampled k-space

ASJC Scopus subject areas

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

Cite this

Felsted, B. K., Whitaker, R. T., Schabel, M., & DiBell, E. V. R. (2009). Model-based reconstruction for undersampled dynamic contrast-enhanced MRI. In Progress in Biomedical Optics and Imaging - Proceedings of SPIE (Vol. 7262). [72622S] https://doi.org/10.1117/12.813991

Model-based reconstruction for undersampled dynamic contrast-enhanced MRI. / Felsted, Ben K.; Whitaker, Ross T.; Schabel, Matthias; DiBell, Edward V R.

Progress in Biomedical Optics and Imaging - Proceedings of SPIE. Vol. 7262 2009. 72622S.

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

Felsted, BK, Whitaker, RT, Schabel, M & DiBell, EVR 2009, Model-based reconstruction for undersampled dynamic contrast-enhanced MRI. in Progress in Biomedical Optics and Imaging - Proceedings of SPIE. vol. 7262, 72622S, Medical Imaging 2009: Biomedical Applications in Molecular, Structural, and Functional Imaging, Lake Buena Vista, FL, United States, 2/8/09. https://doi.org/10.1117/12.813991
Felsted BK, Whitaker RT, Schabel M, DiBell EVR. Model-based reconstruction for undersampled dynamic contrast-enhanced MRI. In Progress in Biomedical Optics and Imaging - Proceedings of SPIE. Vol. 7262. 2009. 72622S https://doi.org/10.1117/12.813991
Felsted, Ben K. ; Whitaker, Ross T. ; Schabel, Matthias ; DiBell, Edward V R. / Model-based reconstruction for undersampled dynamic contrast-enhanced MRI. Progress in Biomedical Optics and Imaging - Proceedings of SPIE. Vol. 7262 2009.
@inproceedings{cea6d7888e8c44cb885a2518b82b0949,
title = "Model-based reconstruction for undersampled dynamic contrast-enhanced MRI",
abstract = "This paper describes a method for estimating, from dynamic contrast-enhanced MRI raw k-space data of the breast, parameter maps that model tissue properties associated with a compartmental model of contrast exchange. The contrast agent kinetics, as represented by these parameter maps, are important in distinguishing benign and malignant tumors. The proposed model-based reconstruction algorithm estimates tissue parameter maps directly from MRI k-space data, thereby allowing a new and improved set of spatiotemporal resolution and noise tradeoffs. Realistic noise levels and an undersampling factor of R=4 appeared to provide reasonable accuracy for the kinetic parameters of interest.",
keywords = "Breast imaging, Dynamic contrast-enhanced magnetic resonance imaging, Iterative reconstruction, Model-based reconstruction, Pharmacokinetic modeling, Undersampled k-space",
author = "Felsted, {Ben K.} and Whitaker, {Ross T.} and Matthias Schabel and DiBell, {Edward V R}",
year = "2009",
doi = "10.1117/12.813991",
language = "English (US)",
isbn = "9780819475138",
volume = "7262",
booktitle = "Progress in Biomedical Optics and Imaging - Proceedings of SPIE",

}

TY - GEN

T1 - Model-based reconstruction for undersampled dynamic contrast-enhanced MRI

AU - Felsted, Ben K.

AU - Whitaker, Ross T.

AU - Schabel, Matthias

AU - DiBell, Edward V R

PY - 2009

Y1 - 2009

N2 - This paper describes a method for estimating, from dynamic contrast-enhanced MRI raw k-space data of the breast, parameter maps that model tissue properties associated with a compartmental model of contrast exchange. The contrast agent kinetics, as represented by these parameter maps, are important in distinguishing benign and malignant tumors. The proposed model-based reconstruction algorithm estimates tissue parameter maps directly from MRI k-space data, thereby allowing a new and improved set of spatiotemporal resolution and noise tradeoffs. Realistic noise levels and an undersampling factor of R=4 appeared to provide reasonable accuracy for the kinetic parameters of interest.

AB - This paper describes a method for estimating, from dynamic contrast-enhanced MRI raw k-space data of the breast, parameter maps that model tissue properties associated with a compartmental model of contrast exchange. The contrast agent kinetics, as represented by these parameter maps, are important in distinguishing benign and malignant tumors. The proposed model-based reconstruction algorithm estimates tissue parameter maps directly from MRI k-space data, thereby allowing a new and improved set of spatiotemporal resolution and noise tradeoffs. Realistic noise levels and an undersampling factor of R=4 appeared to provide reasonable accuracy for the kinetic parameters of interest.

KW - Breast imaging

KW - Dynamic contrast-enhanced magnetic resonance imaging

KW - Iterative reconstruction

KW - Model-based reconstruction

KW - Pharmacokinetic modeling

KW - Undersampled k-space

UR - http://www.scopus.com/inward/record.url?scp=67249097652&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=67249097652&partnerID=8YFLogxK

U2 - 10.1117/12.813991

DO - 10.1117/12.813991

M3 - Conference contribution

AN - SCOPUS:67249097652

SN - 9780819475138

VL - 7262

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

ER -