Accuracy of Raman spectroscopy in differentiating brain tumor from normal brain tissue
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Jing Zhang1,2,*, Yimeng Fan3,*, Min He2,*, Xuelei Ma1,*, Yanlin Song3, Ming Liu1 and Jianguo Xu2
1 Department of Medical Oncology, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, and Collaborative Innovation Center for Biotherapy, Chengdu, PR China
2 Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu, PR China
3 West China School of Medicine, West China Hospital, Sichuan University, Chengdu, PR China
* These authors have contributed equally to this work
Ming Liu, email:
Xuelei Ma, email:
Keywords: Raman spectroscopy, diagnosis, brain tumors, meta-analysis
Received: November 10, 2016 Accepted: February 28, 2017 Published: March 07, 2017
Raman spectroscopy could be applied to distinguish tumor from normal tissues. This meta-analysis was conducted to assess the accuracy of Raman spectroscopy in differentiating brain tumor from normal brain tissue. PubMed and Embase were searched to identify suitable studies prior to Jan 1st, 2016. We estimated the pooled sensitivity, specificity, positive and negative likelihood ratios (LR), diagnostic odds ratio (DOR), and constructed summary receiver operating characteristics (SROC) curves to identity the accuracy of Raman spectroscopy in differentiating brain tumor from normal brain tissue. A total of six studies with 1951 spectra were included. For glioma, the pooled sensitivity and specificity of Raman spectroscopy were 0.96 (95% CI 0.94-0.97) and 0.99 (95% CI 0.98-0.99), respectively. The area under the curve (AUC) was 0.9831. For meningioma, the pooled sensitivity and specificity were 0.98 (95% CI 0.94-1.00) and 1.00 (95% CI 0.98-1.00), respectively. The AUC was 0.9955. This meta-analysis suggested that Raman spectroscopy could be an effective and accurate tool for differentiating glioma and meningioma from normal brain tissue, which would help us both avoid removal of normal tissue and minimize the volume of residual tumor.
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