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Whole-lesion histogram and texture analyses of breast lesions on inline quantitative DCE mapping with CAIPIRINHA-Dixon-TWIST-VIBE

  • Breast
  • Published:
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Abstract

Purpose

To investigate the diagnostic capability of whole-lesion (WL) histogram and texture analysis of dynamic contrast-enhanced (DCE) MRI inline-generated quantitative parametric maps using CAIPIRINHA-Dixon-TWIST-VIBE (CDTV) to differentiate malignant from benign breast lesions and breast cancer subtypes.

Materials and methods

From February 2018 to November 2018, DCE MRI using CDTV was performed on 211 patients. The inline-generated parametric maps included Ktrans, kep, Ve, and IAUGC60. Histogram and texture features were extracted from the above parametric maps respectively based on a WL analysis. Student’s t tests, one-way ANOVAs, Mann-Whitney U tests, Jonckheere-Terpstra tests, and ROC curves were used for statistical analysis.

Results

Compared with benign breast lesions, malignant breast lesions showed significantly higher Ktrans_median, 5th percentile, entropy, and diff-entropy, IAUGC60_median, 5th percentile, entropy, and diff-entropy, kep_mean, median, 5th percentile, entropy, and diff-entropy, and Ve_95th percentile, diff-variance, and contrast, and significantly lower kep_skewness and Ve_SD, entropy, diff-entropy, and skewness (all p ≤ 0.011). The combination of all the extracted parameters yielded an AUC of 0.85 (sensitivity 76%, specificity 86%). kep_contrast showed a significant difference among different subtypes of breast cancer (p = 0.006). kep_skewness showed a significant difference between lymph node–positive and lymph node–negative breast cancer (p = 0.007). The IAGC60_5th percentile had an AUC of 0.71 (sensitivity 50%, specificity 91%) for differentiating between high- and low-proliferation groups of breast cancer.

Conclusions

The WL histogram and texture analyses of CDTV-DCE-derived parameters may give additional information for further evaluation of breast cancer.

Key Points

• Inline DCE mapping with CDTV is effective and time-saving.

• WL histogram and texture-extracted features could distinguish breast cancer from benign lesions accurately.

• kep_contrast, kep_skewness, and IAUGC60_5th percentile could predict breast cancer subtypes, lymph node metastasis, and proliferation abilities, respectively.

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Abbreviations

AIF:

Arterial input function

AUC:

Area under the receiver operating characteristic curve

BI-RADS:

Breast Imaging Reporting and Data System

CAIPIRINHA:

Controlled aliasing in parallel imaging results in higher acceleration

CDTV:

CAIPIRINHA-Dixon-TWIST-VIBE

DCE:

Dynamic contrast enhancement

ER:

Estrogen receptor

HER2:

Human epidermal growth factor receptor-2

IAUGC60 :

Initial area under the gadolinium curve after the first 60 s

k ep :

Outflow rate constant

K trans :

Inflow transfer constant

PR:

Progesterone receptor

ROC:

Receiver operating characteristic

TE:

Echo time

TR:

Reception time

TWIST:

Time-resolved angiography with interleaved stochastic trajectories

V e :

Extravascular extracellular space

VFA:

Variable flip angle

VIBE:

Volumetric interpolated breath-hold examination

WL:

Whole lesion

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Funding

This study was funded by the National Natural Science Foundation of China (81801651).

Author information

Authors and Affiliations

  1. Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, No. 197 Ruijin Er Road, Shanghai, 200025, China

    Kun Sun, Hong Zhu, Weimin Chai, Ying Zhan & Fuhua Yan

  2. MR Application Predevelopment, Siemens Healthcare GmbH, 91052, Erlangen, Germany

    Dominik Nickel & Robert Grimm

  3. MR Application Development, Siemens Shenzhen Magnetic Resonance Ltd., Gaoxin C. Ave, 2nd, Hi-Tech Industrial Park, Shenzhen, 518057, China

    Caixia Fu

Authors
  1. Kun Sun
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  2. Hong Zhu
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  3. Weimin Chai
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  4. Ying Zhan
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  5. Dominik Nickel
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  6. Robert Grimm
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  7. Caixia Fu
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  8. Fuhua Yan
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Corresponding author

Correspondence to Fuhua Yan.

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Guarantor

The scientific guarantor of this publication is Fuhua Yan.

Conflict of interest

The authors of this manuscript declare that they have relationships with Siemens Shenzhen Magnetic Resonance Ltd., Shenzhen, China, and Siemens Healthcare, Erlangen, Germany.

Statistics and biometry

No complex statistical methods were necessary for this paper.

Informed consent

Institutional review board approval was obtained.

Ethical approval

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

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• Prospective

• Diagnostic or prognostic study

• Performed at one institution

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Sun, K., Zhu, H., Chai, W. et al. Whole-lesion histogram and texture analyses of breast lesions on inline quantitative DCE mapping with CAIPIRINHA-Dixon-TWIST-VIBE. Eur Radiol 30, 57–65 (2020). https://doi.org/10.1007/s00330-019-06365-8

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