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Diffusion kurtosis imaging to assess correlations with clinicopathologic factors for bladder cancer: a comparison between the multi-b value method and the tensor method

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Abstract

Objectives

To assess the efficacy of diffusion kurtosis imaging (DKI) in differentiating low-grade from high-grade tumors and evaluating the aggressiveness of bladder cancer.

Methods

From January 2017 to July 2017, 35 patients (28 males, 7 females; mean age 63 ± 9 years) diagnosed with bladder cancer underwent diffusion-weighted imaging (DWI) with two types of DKI protocols: (1) multi-b value ranging from 0 to 2000 s/mm2 to obtain mean diffusivity/kurtosis (MDb/MKb) and (2) the tensor method with 32 directions with 3 b values (0, 1000, and 2000s/mm2) to obtain mean/axial/radial diffusivity (MDt/Da/Dr), mean/axial/radial kurtosis (MKt/Ka/Kr), and fractional anisotropy (FA) before radical cystectomy. Comparisons between the low- and high-grade groups, non-muscle-invasive bladder cancer (NMIBC), and muscle-invasive bladder cancer (MIBC) were performed with the areas under the receiver operating characteristic curves (AUCs).

Results

The MKt and Kr values were significantly (p = 0.017 and p = 0.048) higher in patients with high-grade bladder tumors than in those with low-grade tumors. The MKt, Kr, and MKb values were significantly (p = 0.022, p = 0.000, and p = 0.044, respectively) higher in patients with MIBC than in those with NMIBC, while no significant differences (p > 0.05) were found in other values. The AUC of Kr (0.883) was the largest and was significantly higher than those of other metrics (all p < 0.05) for differentiating MIBC from NMIBC, with a sensitivity and specificity of 81.8% and 91.7%, respectively.

Conclusions

Kurtosis metrics performed better than diffusion metrics in differentiating MIBC from NMIBC, and directional kurtosis and Kr metrics may also have great potential in providing additional information regarding bladder cancer invasiveness.

Key Points

Kurtosis metrics performed better than diffusion metrics in differentiating muscle-invasive bladder cancer (MIBC) from non-muscle-invasive bladder cancer (NMIBC).

Directional kurtosis can provide additional directional microstructural information regarding bladder cancer invasiveness.

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Abbreviations

ADC:

Apparent diffusion coefficient

AUC:

Area under the receiver operating characteristic curve

CLLS:

Constrained linear least-square

Da:

Axial diffusivity

DKT:

Diffusion kurtosis tensor

Dr.:

Radial diffusivity

DTI:

Diffusion tensor imaging

DWI:

Diffusion-weighted imaging

FA:

Fractional anisotropy

ICC:

Intraclass correlation coefficient

Ka:

Axial kurtosis

Kr:

Radial kurtosis

MIBC:

Muscle-invasive bladder cancer

MK:

Mean kurtosis

MRI:

Magnetic resonance imaging

NMIBC:

Non-muscle-invasive bladder cancer

ROC:

Receiver operator characteristic

TUR:

Transurethral resection

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Funding

This study has received funding from the National Natural Science Foundation of China (Youth Program Nos. 81601487, 81672514).

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Correspondence to Guang-Yu Wu or Jian-Rong Xu.

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Guarantor

The scientific guarantor of this publication is Jian-Rong Xu.

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.

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Institutional Review Board approval was obtained.

Study subjects or cohorts overlap

Study subjects or cohorts overlap have not been published previously and not under consideration for publication elsewhere, in whole or in part.

Methodology

• retrospective

• diagnostic study

• performed at one institution

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Cite this article

Wang, F., Chen, HG., Zhang, RY. et al. Diffusion kurtosis imaging to assess correlations with clinicopathologic factors for bladder cancer: a comparison between the multi-b value method and the tensor method. Eur Radiol 29, 4447–4455 (2019). https://doi.org/10.1007/s00330-018-5977-y

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  • DOI: https://doi.org/10.1007/s00330-018-5977-y

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