Original Research

Breast lesion characterization using whole-lesion histogram analysis with stretched-exponential diffusion model

Corresponding Author

Chunling Liu MD

[email protected]

Department of Radiology, Guangdong General Hospital affiliated to South China University of Technology/Guangdong Academy of Medical Sciences, P.R. China

The first two authors contributed equally to this work.

Address reprint requests to: C.L., 106 Zhongshan Er Road, Guangzhou, China. E-mail: [email protected]Search for more papers by this author

Kun Wang MD,

Kun Wang MD

Department of Breast Center, Cancer Center, Guangdong General Hospital affiliated to South China University of Technology/Guangdong Academy of Medical Sciences, P.R. China

The first two authors contributed equally to this work.

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Xiaodan Li MS,

Xiaodan Li MS

Department of Radiology, Guangdong General Hospital affiliated to South China University of Technology/Guangdong Academy of Medical Sciences, P.R. China

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Jine Zhang MD,

Jine Zhang MD

Department of Radiology, Guangdong General Hospital affiliated to South China University of Technology/Guangdong Academy of Medical Sciences, P.R. China

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Jie Ding MS,

Jie Ding MS

Department of Biomedical Engineering, Stony Brook University, Stony Brook, New York, USA

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Karl Spuhler MS,

Karl Spuhler MS

Department of Biomedical Engineering, Stony Brook University, Stony Brook, New York, USA

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Timothy Duong PhD,

Timothy Duong PhD

Department of Radiology, Stony Brook Medicine, Stony Brook, New York, USA

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Changhong Liang MD,

Changhong Liang MD

Department of Radiology, Guangdong General Hospital affiliated to South China University of Technology/Guangdong Academy of Medical Sciences, P.R. China

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Chuan Huang PhD,

Chuan Huang PhD

orcid.org/0000-0001-6052-0663

Department of Radiology, Stony Brook Medicine, Stony Brook, New York, USA

Department of Psychiatry, Stony Brook Medicine, Stony Brook, New York, USA

Department of Biomedical Engineering, Stony Brook University, Stony Brook, New York, USA

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Chunling Liu MD,

Corresponding Author

Chunling Liu MD

[email protected]

Department of Radiology, Guangdong General Hospital affiliated to South China University of Technology/Guangdong Academy of Medical Sciences, P.R. China

The first two authors contributed equally to this work.

Address reprint requests to: C.L., 106 Zhongshan Er Road, Guangzhou, China. E-mail: [email protected]Search for more papers by this author

Kun Wang MD,

Kun Wang MD

Department of Breast Center, Cancer Center, Guangdong General Hospital affiliated to South China University of Technology/Guangdong Academy of Medical Sciences, P.R. China

The first two authors contributed equally to this work.

Search for more papers by this author

Xiaodan Li MS,

Xiaodan Li MS

Department of Radiology, Guangdong General Hospital affiliated to South China University of Technology/Guangdong Academy of Medical Sciences, P.R. China

Search for more papers by this author

Jine Zhang MD,

Jine Zhang MD

Department of Radiology, Guangdong General Hospital affiliated to South China University of Technology/Guangdong Academy of Medical Sciences, P.R. China

Search for more papers by this author

Jie Ding MS,

Jie Ding MS

Department of Biomedical Engineering, Stony Brook University, Stony Brook, New York, USA

Search for more papers by this author

Karl Spuhler MS,

Karl Spuhler MS

Department of Biomedical Engineering, Stony Brook University, Stony Brook, New York, USA

Search for more papers by this author

Timothy Duong PhD,

Timothy Duong PhD

Department of Radiology, Stony Brook Medicine, Stony Brook, New York, USA

Search for more papers by this author

Changhong Liang MD,

Changhong Liang MD

Department of Radiology, Guangdong General Hospital affiliated to South China University of Technology/Guangdong Academy of Medical Sciences, P.R. China

Search for more papers by this author

Chuan Huang PhD,

Chuan Huang PhD

orcid.org/0000-0001-6052-0663

Department of Radiology, Stony Brook Medicine, Stony Brook, New York, USA

Department of Psychiatry, Stony Brook Medicine, Stony Brook, New York, USA

Department of Biomedical Engineering, Stony Brook University, Stony Brook, New York, USA

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First published: 22 November 2017

https://doi.org/10.1002/jmri.25904

Citations: 26

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Abstract

Background

Diffusion-weighted imaging (DWI) has been studied in breast imaging and can provide more information about diffusion, perfusion and other physiological interests than standard pulse sequences. The stretched-exponential model has previously been shown to be more reliable than conventional DWI techniques, but different diagnostic sensitivities were found from study to study.

Purpose

This work investigated the characteristics of whole-lesion histogram parameters derived from the stretched-exponential diffusion model for benign and malignant breast lesions, compared them with conventional apparent diffusion coefficient (ADC), and further determined which histogram metrics can be best used to differentiate malignant from benign lesions.

Study Type

This was a prospective study.

Population

Seventy females were included in the study.

Field Strength/Sequence

Multi-b value DWI was performed on a 1.5T scanner.

Assessment

Histogram parameters of whole lesions for distributed diffusion coefficient (DDC), heterogeneity index (α), and ADC were calculated by two radiologists and compared among benign lesions, ductal carcinoma in situ (DCIS), and invasive carcinoma confirmed by pathology.

Statistical Tests

Nonparametric tests were performed for comparisons among invasive carcinoma, DCIS, and benign lesions. Comparisons of receiver operating characteristic (ROC) curves were performed to show the ability to discriminate malignant from benign lesions.

Results

The majority of histogram parameters (mean/min/max, skewness/kurtosis, 10–90^th percentile values) from DDC, α, and ADC were significantly different among invasive carcinoma, DCIS, and benign lesions. DDC_10% (area under curve [AUC] = 0.931), ADC_10% (AUC = 0.893), and α_mean (AUC = 0.787) were found to be the best metrics in differentiating benign from malignant tumors among all histogram parameters derived from ADC and α, respectively. The combination of DDC_10% and α_mean, using logistic regression, yielded the highest sensitivity (90.2%) and specificity (95.5%).

Data Conclusion

DDC_10% and α_mean derived from the stretched-exponential model provides more information and better diagnostic performance in differentiating malignancy from benign lesions than ADC parameters derived from a monoexponential model.

Level of Evidence: 2

Technical Efficacy: Stage 2

J. Magn. Reson. Imaging 2018;47:1701–1710.

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Citing Literature

Volume47, Issue6

June 2018

Pages 1701-1710

Breast lesion characterization using whole-lesion histogram analysis with stretched-exponential diffusion model

Abstract

Background

Purpose

Study Type

Population

Field Strength/Sequence

Assessment

Statistical Tests

Results

Data Conclusion

References

Citing Literature

References

Information

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Breast lesion characterization using whole-lesion histogram analysis with stretched-exponential diffusion model

Abstract

Background

Purpose

Study Type

Population

Field Strength/Sequence

Assessment

Statistical Tests

Results

Data Conclusion

References

Citing Literature

References

Related

Information