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.
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.
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).
The feature analysis of radiotracer uptake in BSGI is useful in predicting whether breast lesions are malignant or benign.
• 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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Breast imaging reporting and data system
Breast-specific gamma imaging
Ductal carcinoma in situ
Invasive ductal carcinoma
Lesion to normal ratio
Molecular breast imaging
Positron emission tomography
Receiver operating characteristics
Region of interest
MIBI Tc-99m sestamibi
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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).
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.
Written informed consent was waived by the Institutional Review Board.
Institutional Review Board approval was obtained.
• 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
- Breast Neoplasms
- Radionuclide Imaging
- Molecular Imaging
- Diagnostic Imaging
- Technetium Tc 99m Sestamibi