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Harnessing dual-energy CT for glycogen quantification: a phantom analysis.
Li, Meiqin; Li, Zhoulei; Wei, Luyong; Li, Lujie; Wang, Meng; He, Shaofu; Peng, Zhenpeng; Feng, Shi-Ting.
Afiliación
  • Li M; Department of Radiology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
  • Li Z; Department of Radiology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
  • Wei L; Department of Radiology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
  • Li L; Department of Radiology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
  • Wang M; Department of Radiology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
  • He S; Department of Radiology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
  • Peng Z; Department of Radiology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
  • Feng ST; Department of Radiology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Quant Imaging Med Surg ; 13(8): 4933-4942, 2023 Aug 01.
Article en En | MEDLINE | ID: mdl-37581088
ABSTRACT

Background:

Non-invasive glycogen quantification in vivo could provide crucial information on biological processes for glycogen storage disorder. Using dual-energy computed tomography (DECT), this study aimed to assess the viability of quantifying glycogen content in vitro.

Methods:

A fast kilovolt-peak switching DECT was used to scan a phantom containing 33 cylinders with different proportions of glycogen and iodine mixture at varying doses. The virtual glycogen concentration (VGC) was then measured using material composition images. Additionally, the correlations between VGC and nominal glycogen concentration (NGC) were evaluated using least-square linear regression, then the calibration curve was constructed. Quantitative estimation was performed by calculating the linearity, conversion factor (inverse of curve slope), stability, sensitivity (limit of detection/limit of quantification), repeatability (inter-class correlation coefficient), and variability (coefficient of variation).

Results:

In all conditions, excellent linear relationship between VGC and NGC were observed (P<0.001, coefficient of determination 0.989-0.997; residual root-mean-square error of glycogen 1.862-3.267 mg/mL). The estimated conversion factor from VGC to NGC was 3.068-3.222. In addition, no significant differences in curve slope were observed among different dose levels and iodine densities. The limit of detection and limit of quantification had respective ranges of 6.421-15.315 and 10.95-16.46 mg/mL. The data demonstrated excellent scan-repeat scan agreement (inter-class correlation coefficient, 0.977-0.991) and small variation (coefficient of variation, 0.1-0.2%).

Conclusions:

The pilot phantom analysis demonstrated the feasibility and efficacy of detecting and quantifying glycogen using DECT and provided good quantitative performance with significant stability and reproducibility/variability. Thus, in the future, DECT could be used as a convenient method for glycogen quantification to provide more reliable information for clinical decision-making.
Palabras clave

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Quant Imaging Med Surg Año: 2023 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Quant Imaging Med Surg Año: 2023 Tipo del documento: Article País de afiliación: China