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1Department of Radiology, University Hospital Erlangen,Friedrich-Alexander Universität Erlangen-Nürnberg, 2Department of Medical Physics in Radiation Oncology,German Cancer Research Center, 3Department of Internal Medicine 3, University Hospital Erlangen,Friedrich-Alexander Universität Erlangen-Nürnberg
Chapters
- 00:04Introduction
- 00:46Magnetic Resonance Imaging (MRI) Analysis
- 02:11Positron Emission Tomography/Computed Tomography (PET/CT) Analysis
- 03:03Tumor-Take Rate Calculation
- 03:30Feature Selection
- 04:23Machine Learning (ML) Analysis, Model-Averaged Neural Network (avNNet) ML Algorithm Training, and ML Algorithm Data Analysis
- 05:12Results: Representative Machine Learning Algorithm Rat Bone Metastasis Detection
- 06:19Conclusion
This protocol was designed to train a machine learning algorithm to use a combination of imaging parameters derived from magnetic resonance imaging (MRI) and positron emission tomography/computed tomography (PET/CT) in a rat model of breast cancer bone metastases to detect early metastatic disease and predict subsequent progression to macrometastases.
