Abstract

Background and objective To investigate the feasibility of histogram analysis of the T2*-based permeability parameter volume transfer constant (Ktrans) for glioma grading and to explore the diagnostic performance of the histogram analysis of Ktrans and blood plasma volume (vp). Methods We recruited 31 and 11 patients with high- and low-grade gliomas, respectively. The histogram parameters of Ktrans and vp, derived from the first-pass pharmacokinetic modeling based on the T2* dynamic susceptibility-weighted contrast-enhanced perfusion-weighted magnetic resonance imaging (T2* DSC-PW-MRI) from the entire tumor volume, were evaluated for differentiating glioma grades. Results Histogram parameters of Ktrans and vp showed significant differences between high- and low-grade gliomas and exhibited significant correlations with tumor grades. The mean Ktrans derived from the T2* DSC-PW-MRI had the highest sensitivity and specificity for differentiating high-grade gliomas from low-grade gliomas compared with other histogram parameters of Ktrans and vp. Conclusions Histogram analysis of T2*-based pharmacokinetic imaging is useful for cerebral glioma grading. The histogram parameters of the entire tumor Ktrans measurement can provide increased accuracy with additional information regarding microvascular permeability changes for identifying high-grade brain tumors.

Original languageEnglish
Pages (from-to)19-27
Number of pages9
JournalComputer Methods and Programs in Biomedicine
Volume155
DOIs
Publication statusPublished - Mar 1 2018

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Pharmacokinetics
Glioma
Tumors
Imaging techniques
Magnetic resonance imaging
Magnetic resonance
Brain
Blood
Plasma Volume
Plasmas
Magnetic Resonance Angiography
Capillary Permeability
Tumor Burden
Brain Neoplasms
Permeability
Neoplasms
Sensitivity and Specificity

Keywords

  • Cerebral glioma
  • Histogram analysis
  • Permeability imaging
  • Tumor grading

ASJC Scopus subject areas

  • Software
  • Computer Science Applications
  • Health Informatics

Cite this

Histogram analysis of T2*-based pharmacokinetic imaging in cerebral glioma grading. / Liu, Hua Shan; Chiang, Shih Wei; Chung, Hsiao Wen; Tsai, Ping Huei; Hsu, Fei Ting; Cho, Nai Yu; Wang, Chao Ying; Chou, Ming Chung; Chen, Cheng Yu.

In: Computer Methods and Programs in Biomedicine, Vol. 155, 01.03.2018, p. 19-27.

Research output: Contribution to journalArticle

Liu, Hua Shan ; Chiang, Shih Wei ; Chung, Hsiao Wen ; Tsai, Ping Huei ; Hsu, Fei Ting ; Cho, Nai Yu ; Wang, Chao Ying ; Chou, Ming Chung ; Chen, Cheng Yu. / Histogram analysis of T2*-based pharmacokinetic imaging in cerebral glioma grading. In: Computer Methods and Programs in Biomedicine. 2018 ; Vol. 155. pp. 19-27.
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abstract = "Background and objective To investigate the feasibility of histogram analysis of the T2*-based permeability parameter volume transfer constant (Ktrans) for glioma grading and to explore the diagnostic performance of the histogram analysis of Ktrans and blood plasma volume (vp). Methods We recruited 31 and 11 patients with high- and low-grade gliomas, respectively. The histogram parameters of Ktrans and vp, derived from the first-pass pharmacokinetic modeling based on the T2* dynamic susceptibility-weighted contrast-enhanced perfusion-weighted magnetic resonance imaging (T2* DSC-PW-MRI) from the entire tumor volume, were evaluated for differentiating glioma grades. Results Histogram parameters of Ktrans and vp showed significant differences between high- and low-grade gliomas and exhibited significant correlations with tumor grades. The mean Ktrans derived from the T2* DSC-PW-MRI had the highest sensitivity and specificity for differentiating high-grade gliomas from low-grade gliomas compared with other histogram parameters of Ktrans and vp. Conclusions Histogram analysis of T2*-based pharmacokinetic imaging is useful for cerebral glioma grading. The histogram parameters of the entire tumor Ktrans measurement can provide increased accuracy with additional information regarding microvascular permeability changes for identifying high-grade brain tumors.",
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AU - Chung, Hsiao Wen

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AU - Hsu, Fei Ting

AU - Cho, Nai Yu

AU - Wang, Chao Ying

AU - Chou, Ming Chung

AU - Chen, Cheng Yu

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N2 - Background and objective To investigate the feasibility of histogram analysis of the T2*-based permeability parameter volume transfer constant (Ktrans) for glioma grading and to explore the diagnostic performance of the histogram analysis of Ktrans and blood plasma volume (vp). Methods We recruited 31 and 11 patients with high- and low-grade gliomas, respectively. The histogram parameters of Ktrans and vp, derived from the first-pass pharmacokinetic modeling based on the T2* dynamic susceptibility-weighted contrast-enhanced perfusion-weighted magnetic resonance imaging (T2* DSC-PW-MRI) from the entire tumor volume, were evaluated for differentiating glioma grades. Results Histogram parameters of Ktrans and vp showed significant differences between high- and low-grade gliomas and exhibited significant correlations with tumor grades. The mean Ktrans derived from the T2* DSC-PW-MRI had the highest sensitivity and specificity for differentiating high-grade gliomas from low-grade gliomas compared with other histogram parameters of Ktrans and vp. Conclusions Histogram analysis of T2*-based pharmacokinetic imaging is useful for cerebral glioma grading. The histogram parameters of the entire tumor Ktrans measurement can provide increased accuracy with additional information regarding microvascular permeability changes for identifying high-grade brain tumors.

AB - Background and objective To investigate the feasibility of histogram analysis of the T2*-based permeability parameter volume transfer constant (Ktrans) for glioma grading and to explore the diagnostic performance of the histogram analysis of Ktrans and blood plasma volume (vp). Methods We recruited 31 and 11 patients with high- and low-grade gliomas, respectively. The histogram parameters of Ktrans and vp, derived from the first-pass pharmacokinetic modeling based on the T2* dynamic susceptibility-weighted contrast-enhanced perfusion-weighted magnetic resonance imaging (T2* DSC-PW-MRI) from the entire tumor volume, were evaluated for differentiating glioma grades. Results Histogram parameters of Ktrans and vp showed significant differences between high- and low-grade gliomas and exhibited significant correlations with tumor grades. The mean Ktrans derived from the T2* DSC-PW-MRI had the highest sensitivity and specificity for differentiating high-grade gliomas from low-grade gliomas compared with other histogram parameters of Ktrans and vp. Conclusions Histogram analysis of T2*-based pharmacokinetic imaging is useful for cerebral glioma grading. The histogram parameters of the entire tumor Ktrans measurement can provide increased accuracy with additional information regarding microvascular permeability changes for identifying high-grade brain tumors.

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