The accuracy of Raman spectroscopy in the detection and diagnosis of oral cancer: A systematic review and meta‐analysis

Abstract

The aim of this study was to systematically review and assess the diagnostic accuracy of Raman spectroscopy (RS) for oral cancer tissue, oral precancerous lesions, and normal oral tissue. Methods: PubMed, Embase, Web of Science, the China National Knowledge Infrastructure, and gray literature were searched for all relevant articles published before July 2019. We used the Quality Assessment of Diagnostic Accuracy Studies tool to assess the quality of the included studies. We estimated the pooled sensitivity, specificity, positive and negative likelihood ratios (PLR and NLR), diagnostic odds ratio (DOR), and established summary receiver operating characteristic (SROC) curves to identify the diagnostic accuracy of RS for oral cancer tissue, oral precancerous lesions, and normal oral tissue. In addition, the area under the curve (AUC) was reported to estimate the overall effectiveness of RS. Results: A total of 41 articles were eligible for this meta-analysis. The coalescent sensitivity and specificity of RS in diagnosing oral cancer in vivo were 0.91 and 0.85. The positive likelihood ratio, the negative likelihood ratio, and the area under the curve were 8.01, 0.10, and 0.9284. The frozen tissue subgroup in vitro oral cancer group showed improved diagnostic accuracy with an AUC of 0.9968. The in vitro frozen tissue group also showed better diagnostic accuracy in distinguishing between oral precancerous lesions and normal oral tissues. Conclusions: RS has the advantages of being noninvasive and able to provide real-time and in situ results, so it deserves to be studied and improved further to better serve clinical work. K E Y W O R D S diagnosis, meta-analysis, oral cancer, oral precancerous lesion, Raman spectroscopy 1 | INTRODUCTION Oral cancer, a type of head and neck cancer, is a generic term for malignant tumors that occur in the mouth, most † These authors contributed equally to this work.

Diagnosing COVID‐19 in human sera with detected immunoglobulins IgM and IgG by means of Raman spectroscopy

“…[17] Recent studies showed that Raman spectroscopy could be used to quantify biomarkers of kidney disease such as urea and creatinine in serum, [18] to quantify glucose and lipid components of serum, [19] and to quantify prostate-specific antigen values in serum of prostate cancer patients [20] aiming diagnosis. Very recently, two reviews thoroughly explore the potential of Raman spectroscopy for diagnosis of breast and oral cancers, [21,22] and a research paper proposed the detection of infectious diseases such as hepatitis B in plasma. [23] Recently, two reviews thoroughly explore the potential of Raman spectroscopy and others optical technologies in detecting viruses and prospect some applications for the detection of infectious diseases like COVID-19.…”

Fused Raman spectroscopic analysis of blood and saliva delivers high accuracy for head and neck cancer diagnostics

“…Yan et al was able to increase these numbers to the high 90s through implementation of a machine learning algorithm, albeit on a small dataset of only 12 patient samples 26 . A systematic review of using Raman for oral cancer diagnostics by Zhan, et al also describes a meta-analysis of 41 articles, citing that the accuracy of RS in oral cancer diagnostics on in vitro frozen tissues as 99.68% 25 . Although these are impressive numbers, the clinical relevance for diagnostics is lacking, as these studies do not address the need to create fast, non-invasive liquid biopsy approaches for rapid diagnostics.…”

Surface‐enhanced Raman spectroscopy and multivariate analysis for the diagnosis of oral squamous cell carcinoma

“…It is suitable for studying the early diagnosis of oral cancer by distinguishing the different peaks contained in the Raman spectroscopy for qualitative studies. [9][10][11][12][13] Although Raman spectroscopy has been widely used in biomedical fields, the disadvantages of weak signal, low signal-to-noise ratio, and strong autofluorescence background have hindered its further clinical application. [14] The emergence of surface-enhanced Raman spectroscopy (SERS) has greatly overcome the shortcomings of conventional Raman spectroscopy and becomes a promising solution.…”