Abstract P5-01-02: Diagnostic Accuracy of 18F-FDG PET/CT plus Contrast-Enhanced MRI for Axillary Lymph Node Metastasis Involved in Invasive Ductal Carcinoma
Authors: Kawaguchi Shun , Tamura Nobuko , Tanaka Kiyo , Kobayashi Yoko , Sato Junichiro , Kinowaki Keiichi , Shiiba Masato , Ishihara Makiko , Kawabata Hidetaka 
Published: March 2023

Abstract
Background: Positron emission tomography/computed tomography (PET/CT) and magnetic resonance imaging (MRI) are useful imaging modalities for the preoperative nodal staging in breast cancer; however, clinical evidence demonstrating the diagnostic accuracy of the combination of PET/CT and MRI is limited. The purpose of this study is to establish a clinical prediction model based on PET/CT plus contrast-enhanced MRI for ALN metastasis, and explore the possibility of non-invasive patients’ risk stratification using the PET/CT plus MRI model preoperatively. Methods: A total of 361 women (370 axillae; mean age, 56 years ± 12 [standard deviation]) who underwent surgery for primary invasive ductal carcinoma at a single institution between April 2017 and March 2020 were evaluated. Subjects were divided into two cohorts: a derivation cohort (n = 333) and a validation cohort (n = 37). In the derivation cohort, we constructed a prediction model with logistic regression to estimate the potential explanatory variables obtained by PET/CT, MRI, and preoperative core-needle biopsy. Using a simple integer risk score, patients were divided into low-risk and high-risk groups. We assessed the predictive ability of the PET/CT plus MRI model using the area under the curve (AUC), and internal validation was achieved by risk scoring system in the validation cohort. Results: The PET/CT plus MRI model included five predictor variables: maximum standardized uptake value of primary tumor and ALN, primary tumor size, ALN cortical thickness, and histological grade. The PET/CT plus MRI model had significantly improved AUC of 0.867 (p &lt; 0.05) as compared to those of the PET/CT model (AUC = 0.821) and MRI model (AUC = 0.815). We assigned the weighted scores to each retained variables in the PET/CT plus MRI model, and determined the optimal cut-off value of 7 (range, 0−17). In the derivation and validation cohorts, 55% and 65% of the patients were classified as low-risk by the risk scoring system, with negative predictive values of 97% and 100%, respectively. Conclusions: Our findings demonstrated a better diagnostic accuracy of the clinical prediction model utilizing both PET/CT and MRI than previous models based on either PET/CT or MRI, and the negative predictive value of 97% was not inferior to that of sentinel lymph node biopsy. Thus, the preoperative risk evaluation of axillary lymph node macrometastasis using our integrated model could be useful while considering individualized therapy for patients with invasive ductal breast cancer. Further validation should be performed for clinical applications.
Citation Format: Shun Kawaguchi, Nobuko Tamura, Kiyo Tanaka, Yoko Kobayashi, Junichiro Sato, Keiichi Kinowaki, Masato Shiiba, Makiko Ishihara, Hidetaka Kawabata. Diagnostic Accuracy of 18F-FDG PET/CT plus Contrast-Enhanced MRI for Axillary Lymph Node Metastasis Involved in Invasive Ductal Carcinoma [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P5-01-02.