Abstract
Purpose: The aim of this prospective study was to assess the incidence of extra-axillary lymph node involvement on baseline FDG PET/CT in patients with stage II-III breast cancer scheduled for neo-adjuvant chemotherapy. Methods: Patients with invasive breast cancer of >3 cm and/or proven axillary lymph node metastasis were included for before neo-adjuvant chemotherapy. Baseline ultrasound of the infra- and supraclavicular regions was performed with fine-needle biopsy as needed. Subsequently FDG PET/CT was performed. All visually FDG-positive nodes were regarded as metastatic based on the previously reported high specificity of the technique. Results: Sixty patients were included. In 17 patients (28%) extra-axillary lymph nodes were detected by FDG PET/CT, localised in an intra-mammary node (1 lymph node in 1 patient), mediastinal (2 lymph nodes in 2 patients), internal mammary chain (9 lymph nodes in 8 patients), intra- and interpectoral (6 lymph nodes in 4 patients), infraclavicular (5 lymph nodes in 4 patients) and in the contralateral axilla (3 lymph nodes in 2 patients). Ultrasound-guided cytology had detected extra-axillary lymph node involvement in seven of these patients, but was unable to detect extra-axillary nodes in the other 10 patients with positive extra-axillary lymph nodes on FDG PET/CT. Radiotherapy treatment was altered in 7 patients with extra-axillary involvement (12% of the total group). Conclusions: FDG PET/CT detected extra-axillary lymph node involvement in almost one-third of the patients with stage II-III breast cancer, including regions not evaluable with ultrasound. FDG PET/CT may be useful as an additional imaging tool to assess extra-axillary lymph node metastasis, with an impact on the adjuvant radiotherapy management. © 2010 Elsevier Ltd. All rights reserved.
| Original language | English |
|---|---|
| Pages (from-to) | 3205-3210 |
| Journal | European Journal of Cancer |
| Volume | 46 |
| Issue number | 18 |
| DOIs | |
| Publication status | Published - Dec 2010 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
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