OBJECTIVE: The purpose of this study was to assess the diagnostic value of (18)F-FDG PET/CT and MRI in predicting the clinicopathologic subtypes of breast cancer. MATERIALS AND METHODS: The cases of 89 patients with mass-type invasive breast cancer who underwent FDG PET/CT and MRI before therapy were retrospectively analyzed. Eight imaging variables-maximum standardized uptake value (SUVmax), apparent diffusion coefficient, size, shape, margin, intratumoral enhancement, dynamic kinetics, and high intratumoral signal intensity on T2-weighted images-were compared with results for the pathologic markers Ki-67 antibody, estrogen receptor (ER), progesterone receptor (PR), and ERBB2 (formerly HER2 or HER2/neu). The diagnostic performance of the imaging variables for sub-typing was evaluated, and the predictors of the subtypes were elucidated. RESULTS: Higher SUVmax was significantly associated with a high Ki-67 index (p < 0.0001), ER-negative status (p = 0.0001), and PR-negative status (p = 0.047). Significant correlation was also found between size and ER status (p = 0.002) and between shape and PR status (p = 0.044). The AUC exceeded 0.7 only in identification of the luminal A sub-type by application of cutoff values for SUVmax (AUC, 0.751). When smaller tumors were excluded, AUC increased (AUC, 0.803 for tumors > 16 mm). Multivariate analysis showed that SUVmax was the sole independent predictor of luminal A subtype (odds ratio per SD, 0.291; p < 0.0001). SUVmax was significantly lower for luminal A (4.4 ± 2.2) than non-luminal A (8.1 ± 4.4; p < 0.0001) tumors. A cutoff value of 5.4 yielded 79% sensitivity and 68% specificity for prediction that a tumor was the luminal A subtype. CONCLUSION: FDG PET/CT findings may contribute to differentiation of the luminal A and non-luminal A subtypes of invasive breast cancer.
OBJECTIVE: The purpose of this study was to assess the diagnostic value of (18)F-FDG PET/CT and MRI in predicting the clinicopathologic subtypes of breast cancer. MATERIALS AND METHODS: The cases of 89 patients with mass-type invasive breast cancer who underwent FDG PET/CT and MRI before therapy were retrospectively analyzed. Eight imaging variables-maximum standardized uptake value (SUVmax), apparent diffusion coefficient, size, shape, margin, intratumoral enhancement, dynamic kinetics, and high intratumoral signal intensity on T2-weighted images-were compared with results for the pathologic markers Ki-67 antibody, estrogen receptor (ER), progesterone receptor (PR), and ERBB2 (formerly HER2 or HER2/neu). The diagnostic performance of the imaging variables for sub-typing was evaluated, and the predictors of the subtypes were elucidated. RESULTS: Higher SUVmax was significantly associated with a high Ki-67 index (p < 0.0001), ER-negative status (p = 0.0001), and PR-negative status (p = 0.047). Significant correlation was also found between size and ER status (p = 0.002) and between shape and PR status (p = 0.044). The AUC exceeded 0.7 only in identification of the luminal A sub-type by application of cutoff values for SUVmax (AUC, 0.751). When smaller tumors were excluded, AUC increased (AUC, 0.803 for tumors > 16 mm). Multivariate analysis showed that SUVmax was the sole independent predictor of luminal A subtype (odds ratio per SD, 0.291; p < 0.0001). SUVmax was significantly lower for luminal A (4.4 ± 2.2) than non-luminal A (8.1 ± 4.4; p < 0.0001) tumors. A cutoff value of 5.4 yielded 79% sensitivity and 68% specificity for prediction that a tumor was the luminal A subtype. CONCLUSION: FDG PET/CT findings may contribute to differentiation of the luminal A and non-luminal A subtypes of invasive breast cancer.
Entities:
Keywords:
FDG PET/CT; MRI; SUVmax; clinicopathologic subtypes; invasive breast cancer; standardized uptake value
Authors: Sun Seong Lee; Sang Kyun Bae; Yun Soo Park; Ji Sun Park; Tae Hyun Kim; Hye Kyoung Yoon; Hyo Jung Ahn; Seok Mo Lee Journal: Nucl Med Mol Imaging Date: 2016-08-15
Authors: Andrew B Rosenkrantz; Kent Friedman; Hersh Chandarana; Amy Melsaether; Linda Moy; Yu-Shin Ding; Komal Jhaveri; Luis Beltran; Rajan Jain Journal: AJR Am J Roentgenol Date: 2015-10-22 Impact factor: 3.959
Authors: Bishnu P Joshi; Juan Zhou; Asha Pant; Xiyu Duan; Quan Zhou; Rork Kuick; Scott R Owens; Henry Appelman; Thomas D Wang Journal: Bioconjug Chem Date: 2015-12-28 Impact factor: 4.774
Authors: Mariarosaria Incoronato; Anna Maria Grimaldi; Carlo Cavaliere; Marianna Inglese; Peppino Mirabelli; Serena Monti; Umberto Ferbo; Emanuele Nicolai; Andrea Soricelli; Onofrio Antonio Catalano; Marco Aiello; Marco Salvatore Journal: Eur J Nucl Med Mol Imaging Date: 2018-04-25 Impact factor: 9.236