Optical Differentiation of Brain Tumors Based on Raman Spectroscopy and Cluster Analysis Methods

Accuracy of Raman spectroscopy in discriminating normal brain tissue from brain tumor: A systematic review and meta-analysis

IMPORTANCE

There are several methods of intraoperative tumor border identification, but none of them is perfect. There is a need of a new tool.

OBJECTIVE

Raman spectroscopy, being a noninvasive, requiring no tissue preparation, quick technique of substance structure identification, is a potential tool for intraoperative identification of brain tumor. This meta-analysis aimed to assess the accuracy of Raman spectroscopy in differentiation of normal brain tissue from brain tumor.

DATA SOURCES

PubMed, Google Scholar, Scopus and Web of Science databases were searched until October 1, 2024.

STUDY SELECTION

All English-language articles reporting efficacy and accuracy of Raman spectroscopy for brain tumor differentiation were analyzed, sufficient data to construct 2x2 table was extracted.

EXCLUSION CRITERIA

studies using data from national databases; reviews, conference abstracts, case studies, letters to the editor; studies with irrelevant or not sufficient data; not human tissue used in the experiment. 6112 records were found; after exclusion, the suitability of 64 full-text articles was evaluated. 18 studies were reviewed and included into the meta-analysis.

DATA EXTRACTION AND SYNTHESIS

The meta-analysis was performed in accordance with PRISMA guidelines and recommendations. Methodological quality was assessed according to the QUADAS-2 guidelines. Data were extracted by multiple observers and any discrepancies were resolved by discussion and consensus. Data were pooled using a random-effects model.

MAIN OUTCOME(S) AND MEASURE(S)

The primary outcome was pooled sensitivity, specificity and diagnostic odds ratio (DOR) for Raman spectroscopy.

RESULTS

The manuscript presents 18 studies which were used to calculate pooled values. The pooled sensitivity, specificity and pooled diagnostic odds ratio (DOR) of RS for discriminating glioma and normal brain tissues were 0,965, 0,738 and 61,305 respectively. For GBM the results were 0,948, 0,506 and 78,420 respectively. For meningioma pooled values were 0,896, 0,913, and 149,59. For metastases pooled values were 0,946, 0,862 and 133,90 respectively.

CONCLUSIONS AND RELEVANCE

Raman spectroscopy has a potential to serve as a tool for differentiation of brain tumor from normal brain tissue. Not only could it be helpful in distinguishing malignant lesion from benign with high sensitivity and specificity, but also indicate type of tumor. There is a need for more studies examining the accuracy of spectroscopy in differentiating brain tumors from healthy tissues, especially in vivo and in differentiation of brain tumor subtypes.

Current research status of Raman spectroscopy in glioma detection

Glioma is the most common primary tumor of the nervous system. Conventional diagnostic methods for glioma often involve time-consuming or reliance on externally introduced materials. Consequently, there is an urgent need for rapid and reliable diagnostic techniques. Raman spectroscopy has emerged as a promising tool, offering rapid, accurate, and label-free analysis with high sensitivity and specificity in biomedical applications. In this review, the fundamental principles of Raman spectroscopy have been introduced, and then the progress of applying Raman spectroscopy in biomedical studies has been summarized, including the identification and typing of glioma. The challenges encountered in the clinical application of Raman spectroscopy for glioma have been discussed, and the prospects have also been envisioned.