Improved MR-based characterization of engineered cartilage using multiexponential T 2 relaxation and multivariate analysis

David A. Reiter, Onyi Irrechukwu, Ping-Chang Lin, Somaieh Moghadam, Sarah Von Thaer, Nancy Pleshko, Richard G. Spencer

Research output: Contribution to journalArticle

23 Citations (Scopus)

Abstract

Noninvasive monitoring of tissue quality would be of substantial use in the development of cartilage tissue engineering strategies. Conventional MR parameters provide noninvasive measures of biophysical tissue properties and are sensitive to changes in matrix development, but do not clearly distinguish between groups with different levels of matrix development. Furthermore, MR outcomes are nonspecific, with particular changes in matrix components resulting in changes in multiple MR parameters. To address these limitations, we present two new approaches for the evaluation of tissue engineered constructs using MR, and apply them to immature and mature engineered cartilage after 1 and 5weeks of development, respectively. First, we applied multiexponential T 2 analysis for the quantification of matrix macromolecule-associated water compartments. Second, we applied multivariate support vector machine analysis using multiple MR parameters to improve detection of degree of matrix development. Monoexponential T 2 values decreased with maturation, but without further specificity. Much more specific information was provided by multiexponential analysis. The T 2 distribution in both immature and mature constructs was qualitatively comparable to that of native cartilage. The analysis showed that proteoglycan-bound water increased significantly during maturation, from a fraction of 0.05±0.01 to 0.07±0.01. Classification of samples based on individual MR parameters, T 1, T 2, k m or apparent diffusion coefficient, showed that the best classifiers were T 1 and k m, with classification accuracies of 85% and 84%, respectively. Support vector machine analysis improved the accuracy to 98% using the combination (k m, apparent diffusion coefficient). These approaches were validated using biochemical and Fourier transform infrared imaging spectroscopic analyses, which showed increased proteoglycan and collagen with maturation. In summary, multiexponential T 2 and multivariate support vector machine analyses provide improved sensitivity to changes in matrix development and specificity to matrix composition in tissue engineered cartilage. These approaches show substantial potential for the evaluation of engineered cartilage tissue and for extension to other tissue engineering constructs.

Original languageEnglish (US)
Pages (from-to)476-488
Number of pages13
JournalNMR in Biomedicine
Volume25
Issue number3
DOIs
StatePublished - Mar 1 2012

Fingerprint

Cartilage
Multivariate Analysis
Tissue
Proteoglycans
Tissue Engineering
Support vector machines
Tissue engineering
Water
Fourier Analysis
Collagen
Infrared imaging
Macromolecules
Fourier transforms
Classifiers
Support Vector Machine
Monitoring
Chemical analysis

Keywords

  • Cartilage MRI
  • Multiexponential T
  • Proteoglycan
  • Support vector machine
  • Tissue engineering

ASJC Scopus subject areas

  • Molecular Medicine
  • Radiology Nuclear Medicine and imaging
  • Spectroscopy

Cite this

Reiter, D. A., Irrechukwu, O., Lin, P-C., Moghadam, S., Thaer, S. V., Pleshko, N., & Spencer, R. G. (2012). Improved MR-based characterization of engineered cartilage using multiexponential T 2 relaxation and multivariate analysis. NMR in Biomedicine, 25(3), 476-488. https://doi.org/10.1002/nbm.1804

Improved MR-based characterization of engineered cartilage using multiexponential T 2 relaxation and multivariate analysis. / Reiter, David A.; Irrechukwu, Onyi; Lin, Ping-Chang; Moghadam, Somaieh; Thaer, Sarah Von; Pleshko, Nancy; Spencer, Richard G.

In: NMR in Biomedicine, Vol. 25, No. 3, 01.03.2012, p. 476-488.

Research output: Contribution to journalArticle

Reiter, DA, Irrechukwu, O, Lin, P-C, Moghadam, S, Thaer, SV, Pleshko, N & Spencer, RG 2012, 'Improved MR-based characterization of engineered cartilage using multiexponential T 2 relaxation and multivariate analysis', NMR in Biomedicine, vol. 25, no. 3, pp. 476-488. https://doi.org/10.1002/nbm.1804
Reiter, David A. ; Irrechukwu, Onyi ; Lin, Ping-Chang ; Moghadam, Somaieh ; Thaer, Sarah Von ; Pleshko, Nancy ; Spencer, Richard G. / Improved MR-based characterization of engineered cartilage using multiexponential T 2 relaxation and multivariate analysis. In: NMR in Biomedicine. 2012 ; Vol. 25, No. 3. pp. 476-488.
@article{7a1181e5cf62404b90783104e45d9b0f,
title = "Improved MR-based characterization of engineered cartilage using multiexponential T 2 relaxation and multivariate analysis",
abstract = "Noninvasive monitoring of tissue quality would be of substantial use in the development of cartilage tissue engineering strategies. Conventional MR parameters provide noninvasive measures of biophysical tissue properties and are sensitive to changes in matrix development, but do not clearly distinguish between groups with different levels of matrix development. Furthermore, MR outcomes are nonspecific, with particular changes in matrix components resulting in changes in multiple MR parameters. To address these limitations, we present two new approaches for the evaluation of tissue engineered constructs using MR, and apply them to immature and mature engineered cartilage after 1 and 5weeks of development, respectively. First, we applied multiexponential T 2 analysis for the quantification of matrix macromolecule-associated water compartments. Second, we applied multivariate support vector machine analysis using multiple MR parameters to improve detection of degree of matrix development. Monoexponential T 2 values decreased with maturation, but without further specificity. Much more specific information was provided by multiexponential analysis. The T 2 distribution in both immature and mature constructs was qualitatively comparable to that of native cartilage. The analysis showed that proteoglycan-bound water increased significantly during maturation, from a fraction of 0.05±0.01 to 0.07±0.01. Classification of samples based on individual MR parameters, T 1, T 2, k m or apparent diffusion coefficient, showed that the best classifiers were T 1 and k m, with classification accuracies of 85{\%} and 84{\%}, respectively. Support vector machine analysis improved the accuracy to 98{\%} using the combination (k m, apparent diffusion coefficient). These approaches were validated using biochemical and Fourier transform infrared imaging spectroscopic analyses, which showed increased proteoglycan and collagen with maturation. In summary, multiexponential T 2 and multivariate support vector machine analyses provide improved sensitivity to changes in matrix development and specificity to matrix composition in tissue engineered cartilage. These approaches show substantial potential for the evaluation of engineered cartilage tissue and for extension to other tissue engineering constructs.",
keywords = "Cartilage MRI, Multiexponential T, Proteoglycan, Support vector machine, Tissue engineering",
author = "Reiter, {David A.} and Onyi Irrechukwu and Ping-Chang Lin and Somaieh Moghadam and Thaer, {Sarah Von} and Nancy Pleshko and Spencer, {Richard G.}",
year = "2012",
month = "3",
day = "1",
doi = "10.1002/nbm.1804",
language = "English (US)",
volume = "25",
pages = "476--488",
journal = "NMR in Biomedicine",
issn = "0952-3480",
publisher = "John Wiley and Sons Ltd",
number = "3",

}

TY - JOUR

T1 - Improved MR-based characterization of engineered cartilage using multiexponential T 2 relaxation and multivariate analysis

AU - Reiter, David A.

AU - Irrechukwu, Onyi

AU - Lin, Ping-Chang

AU - Moghadam, Somaieh

AU - Thaer, Sarah Von

AU - Pleshko, Nancy

AU - Spencer, Richard G.

PY - 2012/3/1

Y1 - 2012/3/1

N2 - Noninvasive monitoring of tissue quality would be of substantial use in the development of cartilage tissue engineering strategies. Conventional MR parameters provide noninvasive measures of biophysical tissue properties and are sensitive to changes in matrix development, but do not clearly distinguish between groups with different levels of matrix development. Furthermore, MR outcomes are nonspecific, with particular changes in matrix components resulting in changes in multiple MR parameters. To address these limitations, we present two new approaches for the evaluation of tissue engineered constructs using MR, and apply them to immature and mature engineered cartilage after 1 and 5weeks of development, respectively. First, we applied multiexponential T 2 analysis for the quantification of matrix macromolecule-associated water compartments. Second, we applied multivariate support vector machine analysis using multiple MR parameters to improve detection of degree of matrix development. Monoexponential T 2 values decreased with maturation, but without further specificity. Much more specific information was provided by multiexponential analysis. The T 2 distribution in both immature and mature constructs was qualitatively comparable to that of native cartilage. The analysis showed that proteoglycan-bound water increased significantly during maturation, from a fraction of 0.05±0.01 to 0.07±0.01. Classification of samples based on individual MR parameters, T 1, T 2, k m or apparent diffusion coefficient, showed that the best classifiers were T 1 and k m, with classification accuracies of 85% and 84%, respectively. Support vector machine analysis improved the accuracy to 98% using the combination (k m, apparent diffusion coefficient). These approaches were validated using biochemical and Fourier transform infrared imaging spectroscopic analyses, which showed increased proteoglycan and collagen with maturation. In summary, multiexponential T 2 and multivariate support vector machine analyses provide improved sensitivity to changes in matrix development and specificity to matrix composition in tissue engineered cartilage. These approaches show substantial potential for the evaluation of engineered cartilage tissue and for extension to other tissue engineering constructs.

AB - Noninvasive monitoring of tissue quality would be of substantial use in the development of cartilage tissue engineering strategies. Conventional MR parameters provide noninvasive measures of biophysical tissue properties and are sensitive to changes in matrix development, but do not clearly distinguish between groups with different levels of matrix development. Furthermore, MR outcomes are nonspecific, with particular changes in matrix components resulting in changes in multiple MR parameters. To address these limitations, we present two new approaches for the evaluation of tissue engineered constructs using MR, and apply them to immature and mature engineered cartilage after 1 and 5weeks of development, respectively. First, we applied multiexponential T 2 analysis for the quantification of matrix macromolecule-associated water compartments. Second, we applied multivariate support vector machine analysis using multiple MR parameters to improve detection of degree of matrix development. Monoexponential T 2 values decreased with maturation, but without further specificity. Much more specific information was provided by multiexponential analysis. The T 2 distribution in both immature and mature constructs was qualitatively comparable to that of native cartilage. The analysis showed that proteoglycan-bound water increased significantly during maturation, from a fraction of 0.05±0.01 to 0.07±0.01. Classification of samples based on individual MR parameters, T 1, T 2, k m or apparent diffusion coefficient, showed that the best classifiers were T 1 and k m, with classification accuracies of 85% and 84%, respectively. Support vector machine analysis improved the accuracy to 98% using the combination (k m, apparent diffusion coefficient). These approaches were validated using biochemical and Fourier transform infrared imaging spectroscopic analyses, which showed increased proteoglycan and collagen with maturation. In summary, multiexponential T 2 and multivariate support vector machine analyses provide improved sensitivity to changes in matrix development and specificity to matrix composition in tissue engineered cartilage. These approaches show substantial potential for the evaluation of engineered cartilage tissue and for extension to other tissue engineering constructs.

KW - Cartilage MRI

KW - Multiexponential T

KW - Proteoglycan

KW - Support vector machine

KW - Tissue engineering

UR - http://www.scopus.com/inward/record.url?scp=84857355692&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84857355692&partnerID=8YFLogxK

U2 - 10.1002/nbm.1804

DO - 10.1002/nbm.1804

M3 - Article

VL - 25

SP - 476

EP - 488

JO - NMR in Biomedicine

JF - NMR in Biomedicine

SN - 0952-3480

IS - 3

ER -