Morphology-Based Deep Learning Approach for Predicting Osteogenic Differentiation

Yiqing Lan; Nannan Huang; Yiru Fu; Kehao Liu; He Zhang; Yuzhou Li; Sheng Yang

doi:10.3389/fbioe.2021.802794

Morphology-Based Deep Learning Approach for Predicting Osteogenic Differentiation

Front Bioeng Biotechnol. 2022 Jan 27:9:802794. doi: 10.3389/fbioe.2021.802794. eCollection 2021.

Authors

Yiqing Lan^{1

2

3}, Nannan Huang^{1

2

3}, Yiru Fu^{1

2

3}, Kehao Liu^{1

2

3}, He Zhang^{1

2

3}, Yuzhou Li^{1

2

3}, Sheng Yang^{1

2

3}

Affiliations

¹ Stomatological Hospital of Chongqing Medical University, Chongqing, China.
² Chongqing Key Laboratory of Oral Diseases and Biomedical Sciences, Chongqing, China.
³ Chongqing Municipal Key Laboratory of Oral Biomedical Engineering of Higher Education, Chongqing, China.

Abstract

Early, high-throughput, and accurate recognition of osteogenic differentiation of stem cells is urgently required in stem cell therapy, tissue engineering, and regenerative medicine. In this study, we established an automatic deep learning algorithm, i.e., osteogenic convolutional neural network (OCNN), to quantitatively measure the osteogenic differentiation of rat bone marrow mesenchymal stem cells (rBMSCs). rBMSCs stained with F-actin and DAPI during early differentiation (day 0, 1, 4, and 7) were captured using laser confocal scanning microscopy to train OCNN. As a result, OCNN successfully distinguished differentiated cells at a very early stage (24 h) with a high area under the curve (AUC) (0.94 ± 0.04) and correlated with conventional biochemical markers. Meanwhile, OCNN exhibited better prediction performance compared with the single morphological parameters and support vector machine. Furthermore, OCNN successfully predicted the dose-dependent effects of small-molecule osteogenic drugs and a cytokine. OCNN-based online learning models can further recognize the osteogenic differentiation of rBMSCs cultured on several material surfaces. Hence, this study initially demonstrated the foreground of OCNN in osteogenic drug and biomaterial screening for next-generation tissue engineering and stem cell research.

Keywords: convolutional neural network; deep learning; drug screening; online learning; osteogenic differentiation.