Background: The axillary lymph node status is critical for breast cancer staging and individualized treatment planning.
Purpose: To assess the effect of determining axillary lymph node (ALN) metastasis by breast MRI-derived radiomic signatures, and compare the discriminating abilities of different MR sequences.
Study Type: Retrospective.
Population: In all, 120 breast cancer patients, 59 with ALN metastasis and 61 without metastasis, all confirmed by pathology.
Field Strength/sequence: 3 .0T scanner with T -weighted imaging, T -weighted imaging, diffusion-weighted imaging, and dynamic contrast-enhanced (DCE) sequences.
Assessment: Typical morphological and texture features of the segmented tumor were extracted from four sequences, ie, T WI, T WI, DWI, and the second postcontrast phase (CE2) of the dynamic contrast-enhanced sequences. Additional contrast enhancement kinetic features were extracted from all DCE sequences (one pre- and seven postcontrast phases). Linear discriminant analysis classifiers were built and compared when using features from an individual sequence or the combination of the sequences in differentiating the ALN metastasis status.
Statistical Tests: Mann-Whitney U-test, Fisher's exact test, least absolute shrinkage selection operator (LASSO) regression, and receiver operating characteristic analysis were performed.
Results: The accuracy/AUC of the four sequences was 79%/0.87, 77%/0.85, 74%/0.79, and 79%/0.85 for the T WI, CE2, T WI, and DWI, respectively. When CE2 was augmented by adding kinetic features, the model achieved the highest performance (accuracy = 0.86 and AUC = 0.91). When all features from the four sequences and the kinetics were combined, it did not lead to a further increase in the performance (P = 0.48).
Data Conclusion: Breast tumor's radiomic signatures from preoperative breast MRI sequences are associated with the ALN metastasis status, where CE2 phase and the contrast enhancement kinetic features lead to the highest classification effect. Level of Evidence 3 Technical Efficacy Stage 2 J. Magn. Reson. Imaging 2019;50:1125-1132.
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http://dx.doi.org/10.1002/jmri.26701 | DOI Listing |
Am J Cancer Res
December 2024
Department of General Surgery, Liaoning University of Traditional Chinese Medicine Affiliated Hospital Shenyang 110032, Liaoning, China.
The involvement of axillary lymph nodes (ALNs) is a critical prognostic factor affecting patient management and outcomes in breast cancer (BC). This study aims to comprehensively analyze the clinical data of BC patients, evaluate ultrasonic signs of ALNs, and explore the implications of a prediction model for ALN metastasis (ALNM) in early-stage BC patients based on ultrasonic features and clinical data. This study retrospectively analyzed ultrasonic features and clinical data from 216 patients diagnosed with unilateral invasive BC.
View Article and Find Full Text PDFBreast J
January 2025
Gynecology Department, Coimbra University Hospital Center, Coimbra, Portugal.
Establishing an accurate prognosis for women diagnosed with breast cancer (BC) is extremely challenging. Axillary lymph node (ALN) evaluation is considered of major prognostic value. The one-step nucleic acid amplification (OSNA) assay is currently used for assessing axillary sentinel lymph node (SLN) status in BC.
View Article and Find Full Text PDFInt J Gen Med
December 2024
Department of Breast Surgery, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Hubei Provincial Clinical Research Center for Breast Cancer, Wuhan Clinical Research, Wuhan, 430070, People's Republic of China.
Background: Axillary lymph node (ALN) is the most common metastasis path for breast cancer, and ALN dissection directly affects the postoperative staging and prognosis of breast cancer patients. Therefore, additional research is needed to accurately predict ALN metastasis before surgery and construct predictive models to assist in surgical decision-making and optimize patient care.
Methods: We retrospectively analyzed the clinical data, radiomics, and pathomics of the patients diagnosed with breast cancer in the Breast Cancer Center of Hubei Cancer Hospital from January 2017 to December 2022.
BMC Med Imaging
December 2024
Department of Radiology, The Quzhou Affiliated Hospital of Wenzhou Medical University, Quzhou People's Hospital, 100 Minjiang Avenue, Kecheng District, Quzhou, 324000, P.R. China.
Front Oncol
November 2024
Ultrasound Department, Second Affiliated Hospital of Fujian University of Traditional Chinese Medicine, Fuzhou, Fujian, China.
Purpose: This study aimed to develop a model to predict the risk of axillary lymph node (ALN) metastasis in breast cancer patients, using gray-scale ultrasound and clinical pathological features.
Methods: A retrospective analysis of 212 breast cancer patients who met the inclusion criteria from January 2011 to December 2021 was carried out. Clinical and pathological characteristics, including age, tumor size, pathological type, molecular subtype, estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2), and proliferation cell nuclear antigen (Ki-67), were examined.
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