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Background Although the Node Reporting and Data System (Node-RADS) offers a standardized method for assessing lymph node metastasis, its performance may vary according to the histologic type of breast cancer. Purpose To evaluate the applicability of the Node-RADS score in assessing axillary lymph node involvement in patients with invasive ductal carcinoma (IDC) or invasive lobular carcinoma (ILC). Materials and Methods In this retrospective study, data from consecutive women with pathologically confirmed IDC or ILC who underwent preoperative breast MRI between January 2017 and December 2018 were analyzed. Axillary nodal status was assessed using Node-RADS, in which nodal size and configuration criteria are combined into a final assessment score ranging from 1 (very low suspicion) to 5 (very high suspicion). The performance of the Node-RADS score for predicting axillary lymph node metastasis was compared between the two histologic types using the χ test. Results A total of 1602 women (mean age, 50.6 years ± 9.8 [SD]), including 25 with bilateral cancers, were included, yielding 1627 breast cancers. Among these cancers, 1486 were IDC and 141 were ILC. The frequency of lymph node metastasis was 25% (377 of 1486) for IDC and 28% (40 of 141) for ILC ( = .44). A Node-RADS score of 3 or greater yielded the highest Youden index for predicting axillary lymph node metastasis for both histologic types. At this cutoff, the sensitivity and specificity were 71.1% (268 of 377) and 86.5% (959 of 1109) for IDC and 52.5% (21 of 40) and 85.1% (86 of 101) for ILC, respectively. Although there was no evidence of a difference in specificity between the histologic types, sensitivity was significantly lower for ILC ( = .02). The area under the receiver operating characteristic curve (AUC) was 0.83 for IDC and 0.74 for ILC ( = .08). Multivariable logistic regression analyses confirmed Node-RADS score as an independent predictor of axillary lymph node metastasis (odds ratio, 3.1; < .001). Conclusion The Node-RADS score demonstrated comparable performance in terms of AUC in axillary nodal evaluation for IDC and ILC but lower sensitivity for ILC. © RSNA, 2025 See also the editorial by Freitas in this issue.
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http://dx.doi.org/10.1148/radiol.243823 | DOI Listing |
J Bras Pneumol
September 2025
. Universidade Federal do Rio de Janeiro, Rio de Janeiro (RJ) Brasil.
Anticancer Drugs
September 2025
Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College.
Nonsmall cell lung cancer (NSCLC) with SMARCA4 deficiency represents a rare subset of lung tumors characterized by early metastasis, poor response to chemotherapy, and unfavorable prognosis. Established therapy strategies for SMARCA4-deficient NSCLC remain elusive. While immune checkpoint inhibitors have been proposed as a potential solution, their efficacy remains uncertain.
View Article and Find Full Text PDFInt J Surg
September 2025
Guangxi Medical University, Nanning, Guangxi, China.
Ann Nucl Med
September 2025
Department of Nuclear Medicine, Marmara University School of Medicine, Istanbul, Turkey.
Objective: This study aims to systematically evaluate the inter- and intra-observer agreement regarding lesions with uncertain malignancy potential in Ga-68 PSMA PET/CT imaging of prostate cancer patients, utilizing the PSMA-RADS 2.0 classification system, and to emphasize the malignancy evidence associated with these lesions.
Methods: We retrospectively reviewed Ga-68 PSMA PET/CT images of patients diagnosed with prostate cancer via histopathology between December 2016 and November 2023.
Ann Surg Oncol
September 2025
Cancer Center, Renmin Hospital of Wuhan University, Wuhan, China.
Background: The optimal number of examined lymph nodes (ELN) for accurate staging and prognosis for esophageal cancer patients receiving neoadjuvant therapy remains controversial. This study aimed to evaluate the impact of ELN count on pathologic staging and survival outcomes and to develop a predictive model for lymph node positivity in this patient population.
Methods: Data were extracted from the Surveillance, Epidemiology, and End Results (SEER) database and a multicenter cohort.