Calcium feature-based brain tumor diagnosis platform using random forest model

• Autorzy: Qiu Ziyi , Hu Xiaoping , Xu Ting , Sheng Kai , Lu Guanlin , Cao Xiaona , Lu Weicheng , Xie Jingdun , Xu Bingzhe

Identyfikatory

DOI

10.1016/j.bbe.2024.07.002

• Języki publikacji: EN

Abstrakty

EN

Calcium flux has been successfully verified to play an important role in the malignant proliferation and progression of brain tumors, which can serve as an important diagnosis guide. However, clinical diagnosis based on calcium information remains challenging because of the highly complex and heterogeneous features in calcium signals. Here we propose a calcium feature-based tumor diagnosis and treatment guidance platform (CA-TDT-GP) using random forest analysis framework for the efficient prediction of complex tumor behaviors for clinical therapy guidance. Multiple important features associated with brain tumor biological malignancy were screened out through comprehensive feature importance analysis. It provided useful guidance for understanding the biological process and the selection of drugs of brain tumors. Further clinical validation confirmed the accurate prediction of tumor biological characteristics by the model, with a coefficient of determination of over 0.86 in the same cohort of patients and over 0.77 for the new cohort of patients. We further verified the clinical malignant assessment by this model, which performed a 100% prediction match with diagnosed WHO grades, indicating great potential of the platform for clinical guidance. This promising model provides a new diagnostic and therapeutic tool for brain tumor research and preclinical treatment.

Słowa kluczowe

EN

brain tumor; calcium flux; random forest; clinical guidance

PL

guz mózgu; las losowy; wskazówki kliniczne

• Wydawca: Nałęcz Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences ; Elsevier
• Czasopismo: Biocybernetics and Biomedical Engineering
• Rocznik: 2024
• Tom: Vol. 44, no. 2
• Strony: 286--294
• Opis fizyczny: Bibliogr. 43 poz., rys., wykr.

Twórcy

autor

Qiu Ziyi

• School of Biomedical Engineering, Sun Yat-sen University, No. 135, Xingang Xi Road, Guangzhou 510275, PR China
• School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, No.66, Gongchang Road, Guangming District, Shenzhen 518107, PR China

autor

Hu Xiaoping

• School of Biomedical Engineering, Sun Yat-sen University, No. 135, Xingang Xi Road, Guangzhou 510275, PR China
• School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, No.66, Gongchang Road, Guangming District, Shenzhen 518107, PR China

autor

Xu Ting

• School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, No.66, Gongchang Road, Guangming District, Shenzhen 518107, PR China

autor

Sheng Kai

• School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, No.66, Gongchang Road, Guangming District, Shenzhen 518107, PR China

autor

Lu Guanlin

• School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, No.66, Gongchang Road, Guangming District, Shenzhen 518107, PR China

autor

Cao Xiaona

• School of Biomedical Engineering, Sun Yat-sen University, No. 135, Xingang Xi Road, Guangzhou 510275, PR China
• School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, No.66, Gongchang Road, Guangming District, Shenzhen 518107, PR China

autor

Lu Weicheng

• Department of Anesthesiology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in Southern China, Collaborative Innovation for Cancer Medicine, Guangzhou, Guangdong 510060, PR China

autor

Xie Jingdun

• Department of Anesthesiology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in Southern China, Collaborative Innovation for Cancer Medicine, Guangzhou, Guangdong 510060, PR China

autor

Xu Bingzhe

• School of Biomedical Engineering, Sun Yat-sen University, No. 135, Xingang Xi Road, Guangzhou 510275, PR China
• School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, No.66, Gongchang Road, Guangming District, Shenzhen 518107, PR China

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