Utility of 18F-Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography Fusion Imaging for Prediction of Metastasis to Sentinel and Nonsentinel Nodes in Patients with Clinically Node-Negative Breast Cancer

• Published in: Annals of surgical oncology Vol. 27; no. 8; pp. 2698 - 2710
• Main Authors: Yamagishi, Yoji, Yamasaki, Tamio, Ishida, Jiro, Moriya, Tomoyuki, Einama, Takahiro, Koiwai, Tomomi, Fukumura-Koga, Makiko, Kono, Takako, Hayashi, Katsumi, Ueno, Hideki, Yamamoto, Junji, Tsuda, Hitoshi
• Format: Journal Article
• Language: English
• Published: Cham Springer International Publishing 01-08-2020; Springer Nature B.V
• Subjects: Breast cancer; Breast Oncology; Computed tomography; Medicine; Medicine & Public Health; Metastases; Metastasis; Multivariate analysis; Oncology; Positron emission tomography; Risk factors; Surgery; Surgical Oncology; Tomography; Tumors
• ISSN: 1068-9265; 1534-4681
• DOI: 10.1245/s10434-020-08269-0

Purpose
18
F-Fluorodeoxyglucose positron emission tomography/computed tomography fusion imaging (
18
F-FDG PET/CT) is an important diagnostic tool in breast cancer. The utility of maximum standardized uptake values (SUVmax) of primary tumors has been evaluated to predict sentinel node (SN) and non-SN metastasis in clinically node-negative (cN0) patients.
Patients and Methods
18
F-FDG PET/CT was performed on 414 cN0 patients. The following parameters were evaluated: SUVmax at 60 min (SUVmax1), SUVmax at 120 min (SUVmax2), percent change between SUVmax1 and SUVmax2 (ΔSUVmax%), SN metastasis foci maximum size (SN meta size), and ratio of metastatic SNs to total SNs or SN ratio (SNR). It was assessed whether these were risk factors for SN metastasis. The relationship between these parameters and the status of SN and/or non-SN metastasis was retrospectively explored to predict non-SN metastasis.
Results
All SUV parameters significantly correlated with pathological
T
factor (pT), nuclear grade, lymphatic invasion (Ly), and Ki-67 labeling index. On multivariate analysis, pT and Ly were independent predictive factors for SN metastasis. In SN meta-positive cases, SN meta size, SNR, and ΔSUVmax% were predictors for non-SN metastasis on univariate analyses, and the former two were independent predictors on multivariate analysis. The combination of SUVmax2 and ΔSUVmax% was an independent predictor of non-SN metastasis (
P
 = 0.0312) and was associated with prediction of non-SN metastasis negative status with high probability (92.3%).
Conclusions
In patients with cN0 breast cancer, SUV parameters of the primary tumor were correlated with pathological features. The combination of SUVmax2 and ΔSUVmax% may be useful for predicting non-SN metastasis.