Preliminary study of AI-assisted diagnosis using FDG-PET/CT for axillary lymph node metastasis in patients with breast cancer
Zongyao Li; Kazuhiro Kitajima; Kenji Hirata; Ren Togo; Junki Takenaka; Yasuo Miyoshi; Kohsuke Kudo; Takahiro Ogawa · 2021 · EJNMMI Research
WASTE classifies this as Negative / Null Result Report · AI classification, approximate
The study found no significant effect — useful as a negative control or null benchmark for your own design.
Abstract
Abstract Background To improve the diagnostic accuracy of axillary lymph node (LN) metastasis in breast cancer patients using 2-[ 18 F]FDG-PET/CT, we constructed an artificial intelligence (AI)-assisted diagnosis system that uses deep-learning technologies. Materials and methods Two clinicians and the new AI system retrospectively analyzed and diagnosed 414 axillae of 407 patients with biopsy-proven breast cancer who had undergone 2-[ 18 F]FDG-PET/CT before a mastectomy or breast-conserving surgery with a sentinel lymph node (LN) biopsy and/or axillary LN dissection. We designed and trained a
Abstract by Zongyao Li; Kazuhiro Kitajima; Kenji Hirata; Ren Togo; Junki Takenaka; Yasuo Miyoshi; Kohsuke Kudo; Takahiro Ogawa, EJNMMI Research (2021) — licensed CC BY 4.0.
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Metadata source: OpenAlex · DOI 10.1186/s13550-021-00751-4