Radiomics based on multiple machine learning methods for diagnosing early bone metastases not visible on CT images.

Journal: Skeletal radiology
PMID: 39028463

Abstract

OBJECTIVES: This study utilizes [Tc]-methylene diphosphate (MDP) single photon emission computed tomography (SPECT) images as a reference standard to evaluate whether the integration of radiomics features from computed tomography (CT) and machine learning algorithms can identify microscopic early bone metastases. Additionally, we also determine the optimal machine learning approach.

Authors

  • Huili Wang
    Guangxi Forestry Research Institute, Key Laboratory of Central South Fast-Growing Timber Cultivation of Forestry Ministry of China, Nanning, China.
  • Jianfeng Qiu
    School of Radiology, Shandong First Medical University & Shandong Academy of Medicine Sciences, Tai'an, Shandong, 271000, China; Science and Technology Innovation Center, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, 250000, China. Electronic address: jfqiu100@163.com.
  • Weizhao Lu
    Department of Radiology, the Second Affiliated Hospital of Shandong First Medical University, Tai'an, Shandong, 271000, China.
  • Jindong Xie
    Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.
  • Junchi Ma
    School of Radiology, Shandong First Medical University (Shandong Academy of Medical Sciences), Taian, 271016, China. mjc.928@163.com.

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