F-18 FDG PET/CT based Preoperative Machine Learning Prediction Models for Evaluating Regional Lymph Node Metastasis Status of Patients with Colon Cancer.

Journal: Asian Pacific journal of cancer prevention : APJCP

PMID: 39873989

Abstract

OBJECTIVE: This study aimed to develop a simple machine-learning model incorporating lymph node metastasis status with F-18 Fluorodeoxyglucose positron emission tomography/computed tomography (FDG PET/CT) and clinical information for predicting regional lymph node metastasis in patients with colon cancer.

Authors

Su Jung Choi

Department of Nuclear Medicine, Busan Paik Hospital, Inje University College of Medicine, 75 Bokji-ro, Busanjin-gu, Busan, Korea.
Ji Sun Park

Department of Nuclear Medicine, Busan Paik Hospital, University of Inje College of Medicine, Busan, Republic of Korea.
Hyung Joo Baik

Department of Surgery, Busan Paik Hospital, University of Inje College of Medicine, Busan, Republic of Korea.
Min Sung An

Department of Surgery, Busan Paik Hospital, University of Inje College of Medicine, Busan, Republic of Korea.
Ki Beom Bae

Department of Surgery, Busan Paik Hospital, University of Inje College of Medicine, Busan, Republic of Korea.
Sun Seong Lee

Department of Nuclear Medicine, Busan Paik Hospital, Inje University College of Medicine, 75 Bokji-ro, Busanjin-gu, Busan, Korea.

Keywords

Adult Aged Aged, 80 and over Colonic Neoplasms Female Fluorodeoxyglucose F18 Follow-Up Studies Humans Lymph Nodes Lymphatic Metastasis Machine Learning Male Middle Aged Positron Emission Tomography Computed Tomography Prognosis Radiopharmaceuticals Retrospective Studies ROC Curve

External Resources

View on PubMed Access via DOI PubMed (39873989)

F-18 FDG PET/CT based Preoperative Machine Learning Prediction Models for Evaluating Regional Lymph Node Metastasis Status of Patients with Colon Cancer.

Abstract

Authors

Keywords

External Resources

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