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Clinical breast cancer · 2023

Axilla View of Mammography in Preoperative Axillary Lymph Node Evaluation of Breast Cancer Patients: A Pilot Study.

СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод пока не подготовлен
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Wang Ji, Di Wenyang, Shi Ke, Wang Siqi, Jiang Yunshan, Xu Weiwei, Zhong Zhaoyun, Pan Hong, Xie Hui, Zhou Wenbin, Zhao Meng, Wang Shui

Аннотация

PURPOSE: This study aimed to explore a novel position of mammography named axilla view in axillary lymph node (ALN) evaluation in breast cancer.

PATIENTS AND METHODS: Patients were prospectively enrolled and scheduled for mammography before surgery. Investigated imaging patterns included mediolateral oblique (2D-MLO) and axilla view (2D-axilla) of mammography, and axilla view of digital breast tomosynthesis (3D-axilla). The correlation of ALN numbers between imaging and pathology was analyzed. Diagnostic performance was analyzed via AUC.

RESULTS: 75 patients were included. A larger and clearer axillary region was displayed in axilla view. The total number of ALNs detected under 2D/3D-axilla view was significantly higher than that under 2D-MLO view (4.6 vs. 2.5, P < .001; 5.6 vs. 4.6, P = .034). Correlations between number of positive ALNs detected under 2D/3D-axilla view and pathologically confirmed metastatic ALNs were stronger than 2D-MLO view (Pearson correlation coefficients: 0.7084,0.7044 and 0.4744). The proportion of cases with ≥5 positive ALNs detected under 3D-axilla view was significantly higher than that under 2D-MLO (38.2% vs. 14.7%, P = .028). The overweight and obese group showed a higher AUC value than the underweight and lean group in ALN evaluation, although not significantly (2D-MLO: 0.7643 vs. 0.6458, P = .2656; 2D-axilla: 0.8083 vs. 0.6586, P = .1522; 3D-axilla: 0.8045 vs. 0.6615, P = .1874). This difference was more pronounced in axilla view.

CONCLUSION: Axilla view exhibited advantages over conventional MLO view in the extent of axilla displayed by mammography in breast cancer. Further studies with larger sample sizes are needed.

Предметные рубрики MeSH

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

Реквизиты и контакты