Deep Learning Histology for Prediction of Lymph Node Metastases and Tumor Regression after Neoadjuvant FLOT Therapy of Gastroesophageal Adenocarcinoma.
Jin-On JungJuan I PisulaXenia BeyerleinLeandra LukomskiKarl KnipperAram P Abu HejlehHans F FuchsYuri TolkachSeung-Hun ChonHenrik NienhüserMarkus W BüchlerChristiane Josephine BrunsAlexander QuaasKatarzyna BozekFelix PoppThomas SchmidtPublished in: Cancers (2024)
This study demonstrates that visual features extracted by deep learning from therapy-naïve biopsies of gastroesophageal adenocarcinomas correlate with positive lymph nodes and tumor regression. The results will be confirmed in prospective studies to achieve early allocation of patients to the most promising treatment.
Keyphrases
- lymph node
- deep learning
- end stage renal disease
- neoadjuvant chemotherapy
- sentinel lymph node
- ejection fraction
- chronic kidney disease
- newly diagnosed
- squamous cell carcinoma
- locally advanced
- convolutional neural network
- peritoneal dialysis
- rectal cancer
- prognostic factors
- stem cells
- patient reported outcomes
- replacement therapy
- bone marrow