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Usefulness of feature analysis of breast-specific gamma imaging for predicting malignancy

  • Breast
  • Published:
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Abstract

Objectives

The purpose of this study was to investigate which feature of the breast-specific gamma imaging (BSGI) uptake in women who were recently diagnosed with breast cancer was associated with malignancy.

Methods

Data on 231 newly diagnosed breast cancer patients who underwent preoperative BSGI were retrospectively reviewed. Feature analysis was done by classifying BSGI uptake into mass, non-mass, or focus/foci. Descriptors for mass, non-mass, or focus/foci were shape, distribution, number, and intensity. BSGI features of known malignancies and lesions that were additionally found by BSGI were correlated with mammographic breast density, histology, hormonal status, and clinical follow-up data obtained over at least 2 years.

Results

Among 372 breast lesions from 231 patients, 241 malignancies had been pathologically confirmed prior to BSGI and 131 additional lesions were found on BSGI. Irregular shape was more predictive of malignancy than oval shape (p=0.004) in mass uptake. Linear/ductal distribution was more predictive of malignancy than focal, regional, and segmental distribution (p<0.05) in non-mass uptake. Mammographic breast density was not associated with BSGI features. The lesion to normal ratio (LNR) was higher in the postmenopausal patients than that in the premenopausal patients (p=0.003).

Conclusions

The feature analysis of radiotracer uptake in BSGI is useful in predicting whether breast lesions are malignant or benign.

Key Points

• The feature analysis of BSGI uptake is useful in predicting malignancy.

• Irregular shape was predictive of malignancy in mass uptake.

• Linear/ductal distribution was predictive of malignancy in non-mass uptake.

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Abbreviations

BI-RADS:

Breast imaging reporting and data system

BSGI:

Breast-specific gamma imaging

CC:

Craniocaudal

DCIS:

Ductal carcinoma in situ

IDC:

Invasive ductal carcinoma

LNR:

Lesion to normal ratio

MBI:

Molecular breast imaging

MLO:

Mediolateral oblique

PET:

Positron emission tomography

ROC:

Receiver operating characteristics

ROI:

Region of interest

Tc-99m:

MIBI Tc-99m sestamibi

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Funding

This study was supported by the Brain Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT (NRF-2015M3C7A1064832).

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Authors and Affiliations

  1. Department of Radiology, Incheon St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, 56, Dongsu-ro, Bupyeong-gu, Seoul, 403-720, South Korea

    Eun Kyoung Choi, Jooyeon Jamie Im, Chang Suk Park, Yong-An Chung, Kijun Kim & Jin Kyoung Oh

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  1. Eun Kyoung Choi
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  2. Jooyeon Jamie Im
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  4. Yong-An Chung
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Corresponding author

Correspondence to Jin Kyoung Oh.

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Guarantor

The scientific guarantor of this publication is Jin Kyoung Oh.

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 waived by the Institutional Review Board.

Ethical approval

Institutional Review Board approval was obtained.

Methodology

• retrospective

• observational

• performed at one institution

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Choi, E.K., Im, J.J., Park, C.S. et al. Usefulness of feature analysis of breast-specific gamma imaging for predicting malignancy. Eur Radiol 28, 5195–5202 (2018). https://doi.org/10.1007/s00330-018-5563-3

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  • DOI: https://doi.org/10.1007/s00330-018-5563-3

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