The clinical value of texture analysis of dual-time-point 18F-FDG-PET/CT imaging to differentiate between 18F-FDG-avid benign and malignant pulmonary lesions

  • Masatoyo NakajoEmail author
  • Megumi Jinguji
  • Masaya Aoki
  • Atsushi Tani
  • Masami Sato
  • Takashi Yoshiura
Nuclear Medicine



To examine whether the texture analysis of dual-time-point (DTP) F-18-fluorodeoxyglucose (18F-FDG)-PET/CT imaging can differentiate between 18F-FDG-avid benign and malignant pulmonary lesions.


We compared standardized uptake value (SUV)-related (SUVmax [g/ml] and SUVmean [g/ml]), volumetric (metabolic tumor volume [MTV] [cm3] and total lesion glycolysis [TLG] [g]), and texture (entropy, homogeneity, dissimilarity, intensity variability [IV], size-zone variability [SZV], and zone percentage [ZP]) (MTV ≥ 5.0 cm3 and SUV ≥ 2.5 g/ml) parameters between 13 benign and 46 malignant lesions using the Mann–Whitney U test. Diagnostic performance was evaluated by receiver operating characteristic (ROC) analysis. Stepwise logistic regression analysis was performed to identify and use the independent variables that correctly differentiate between benign and malignant lesions.


Malignant pulmonary lesions showed significantly higher SUVmax, SUVmean, MTV, TLG, entropy, dissimilarity, IV, and SZV and significantly lower homogeneity and ZP than benign pulmonary lesions (all p < 0.05) in both early and delayed images. Their areas under the ROC curves (AUCs) ranged between 0.69 and 0.94, and diagnostic accuracies between 64.4% and 93.2%. Entropy-early (p = 0.014), SUVmean-delay (p = 0.039), and dissimilarity-delay (p = 0.027) were independent parameters, and combined use of them yielded the highest AUC (0.98) with 100% sensitivity (46/46), 84.6% specificity (11/13), and 96.7% (57/59) accuracy for distinguishing between benign and malignant lesions.


The individual early and delayed SUV-related, volumetric, and texture parameters showed a wide range of accuracy. Combined use of independent parameters extracted from DTP imaging might yield a high diagnostic accuracy with balanced sensitivity and specificity to differentiate between benign and malignant 18F-FDG-avid pulmonary lesions.

Key Points

• Malignant pulmonary lesions showed significantly higher SUV-related (SUVmax and SUVmean) and volumetric (MTV and TLG) parameters than benign pulmonary lesions in both early and delayed images.

• Malignant pulmonary lesions showed significantly more heterogeneous 18 F-FDG uptake than benign pulmonary lesions in both early and delayed images.

• Combined use of independent parameters extracted from DTP imaging might yield a high diagnostic accuracy to differentiate between benign and malignant 18 F-FDG-avid pulmonary lesions.


Lung neoplasm 18F-FDG Positron emission tomography computed tomography Differential diagnosis 



Body surface area


Confidence interval




Full-width half-maximum


Intensity variability


Lean body mass


Metabolic tumor volume




Standardized uptake value


Size-zone variability


Total lesion glycolysis


Volume of interest


Zone percentage



We thank Tetsuya Shinaji (Department of Nuclear Medicine, University of Würzburg) for the technical support for performing texture analysis. We also thank Prof. Chihaya Koriyama, of the Department of Epidemiology and Preventive Medicine, Kagoshima University, for the validation of the statistical analysis.

Funding information

The authors state that this work has not received any funding.

Compliance with ethical standards


The scientific guarantor of this publication is T. Yoshiura.

Conflict of interest

The authors declare that they have no competing interests.

Statistics and biometry

No complex statistical methods were necessary for this paper.

Informed consent

Written informed consent was waived by the Institutional Review Board.

Ethical approval

Institutional Review Board approval was obtained.


• retrospective

• diagnostic or prognostic study

• performed at one institution

Supplementary material

330_2019_6463_MOESM1_ESM.docx (32 kb)
ESM 1 (DOCX 32 kb)


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Copyright information

© European Society of Radiology 2019

Authors and Affiliations

  • Masatoyo Nakajo
    • 1
    Email author
  • Megumi Jinguji
    • 1
  • Masaya Aoki
    • 2
  • Atsushi Tani
    • 1
  • Masami Sato
    • 2
  • Takashi Yoshiura
    • 1
  1. 1.Department of Radiology, Graduate School of Medical and Dental SciencesKagoshima UniversityKagoshimaJapan
  2. 2.Department of Thoracic Surgery, Graduate School of Medical and Dental SciencesKagoshima UniversityKagoshimaJapan

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