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European Radiology

, Volume 29, Issue 3, pp 1607–1615 | Cite as

Differentiating between malignant and benign solid solitary pulmonary lesions: are intravoxel incoherent motion and diffusion kurtosis imaging superior to conventional diffusion-weighted imaging?

  • Qi Wan
  • Ying-shi Deng
  • Qiang Lei
  • Ying-ying Bao
  • Yu-ze Wang
  • Jia-xuan Zhou
  • Qiao Zou
  • Xin-chun LiEmail author
Chest
  • 161 Downloads

Abstract

Objective

To quantitatively compare the diagnostic values of various diffusion parameters obtained from mono- and biexponential diffusion-weighted imaging (DWI) models and diffusion kurtosis imaging (DKI) in differentiating between benign and malignant solitary pulmonary lesions (SPLs).

Methods

Multiple b-value DWIs and DKIs were performed in 89 patients with SPL by using a 3-T magnetic resonance (MR) imaging unit. The apparent diffusion coefficient (ADC) of various b-value sets, true diffusivity (D), pseudo-diffusion coefficient (D*), perfusion fraction (f), apparent diffusional kurtosis (Kapp), and kurtosis-corrected diffusion coefficient (Dapp) were calculated and compared between the malignant and benign groups using a Mann-Whitney U test. Receiver-operating characteristic analysis was performed for all parameters.

Result

The ADC(0, 150) values of malignant tumors were lower than those of the benign group (p = 0.01). The ADC(0, 300), ADC(0, 500), ADC(0, 600), ADC(0, 800), ADC(0, 1000), ADCtotal, D, and Dapp of malignant tumors were significantly lower than those of benign lesions (all p < 0.001). D*, f, and Kapp showed no statistically significant differences between the two groups. ADCtotal showed the highest area under the curve (AUC = 0.862), followed by ADC(0, 800)(AUC = 0.844), ADC(0, 600)(AUC = 0.843), D(AUC = 0.834), ADC(0, 1000)(AUC = 0.834) and ADC(0, 500)(AUC = 0.824), Dapp(AUC = 0.796), and ADC(0, 300) (AUC = 0.773). However, the difference in diagnostic efficacy among these parameters was not statistically significant (p > 0.05).

Conclusion

Intravoxel incoherent motion (IVIM) and DKI-derived parameters have similar performance compared with conventional ADC in differentiating SPLs.

Key Points

• Mono- and biexponential DWI and DKI are feasible for differentiating SPLs.

• ADC (0, ≥500) has better performance than ADC (0, <500) in assessing SPLs.

• IVIM and DKI have similar performance compared with conventional DWI in differentiating SPLs.

Keywords

Lung neoplasms Solitary pulmonary nodule Diffusion magnetic resonance imaging Area under curve Sensitivity and specificity 

Abbreviations

ADC

Apparent diffusion coefficient

AUC

Area under curve

D

True diffusivity

D*

Pseudo-diffusion coefficient

Dapp

Kurtosis corrected diffusion coefficient

DKI

Diffusion kurtosis imaging

DWI

Diffusion-weighted imaging

f

Perfusion fraction

IVIM

Intravoxel incoherent motion

Kapp

Apparent diffusional kurtosis

ROC

Receiver operating characteristic

ROI

Region of interest

SPL

Solitary pulmonary lesions

Notes

Funding

This study has received funding from National Natural Science Foundation of China (81601457).

Compliance with ethical standards

Guarantor

The scientific guarantor of this publication is Xinchun Li.

Conflict of interest

The authors of this manuscript declare no relationships with any companies, whose products or services may be related to the subject matter of the article.

Statistics and biometry

No complex statistical methods were necessary for this paper.

Informed consent

Written informed consent was obtained from all subjects (patients) in this study.

Ethical approval

Institutional Review Board approval was obtained.

Methodology

• prospective

• diagnostic study

• performed at one institution

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Copyright information

© European Society of Radiology 2018

Authors and Affiliations

  • Qi Wan
    • 1
  • Ying-shi Deng
    • 1
  • Qiang Lei
    • 1
  • Ying-ying Bao
    • 1
  • Yu-ze Wang
    • 1
  • Jia-xuan Zhou
    • 1
  • Qiao Zou
    • 1
  • Xin-chun Li
    • 1
    Email author
  1. 1.Department of RadiologyThe First Affiliated Hospital of Guangzhou Medical UniversityGuangzhouChina

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