Eun Kyoung Choi1, Jooyeon Jamie Im1, Chang Suk Park1, Yong-An Chung1, Kijun Kim1, Jin Kyoung Oh2. 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. 2. 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. mirriam@catholic.ac.kr.
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.
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 cancerpatients 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.
Authors: Amy Lynn Conners; Carrie B Hruska; Cindy L Tortorelli; Robert W Maxwell; Deborah J Rhodes; Judy C Boughey; Wendie A Berg Journal: Eur J Nucl Med Mol Imaging Date: 2012-06 Impact factor: 9.236
Authors: Carrie B Hruska; Amy Lynn Conners; Katie N Jones; Michael K O'Connor; James P Moriarty; Judy C Boughey; Deborah J Rhodes Journal: AJR Am J Roentgenol Date: 2015-06 Impact factor: 3.959
Authors: Hui Tan; Lei Jiang; Yusen Gu; Yan Xiu; Lei Han; Pengyue Wu; Hongwei Zhang; Hongcheng Shi Journal: Ann Nucl Med Date: 2013-10-19 Impact factor: 2.668