A recent study examined using Raman spectroscopy to screen leukemia in patients.
Raman spectroscopy has been explored as a potential solution for improving cancer detection. Numerous studies have explored using Raman spectroscopy to detect specific types of cancer. Researchers from Xinjiang University combined Raman spectroscopy with chaos theory to improve detection of lung cancer (1). Raman spectroscopy was also combined with specialized data treatment to diagnose lung cancer (2). A study published in Applied Spectroscopy Reviews also looked at how Raman spectroscopy has been used to detect and diagnose breast cancer (3).
A recent study published in the journal Photodiagnosis and Photodynamic Therapy explored using Raman to serve as a diagnostic tool leukemia (4). In this study, researchers at Jilin University and The First Hospital of Jilin University examined the potential of Raman spectroscopy as a diagnostic tool for leukemia. The research team was led by Sujun Gao.
The study involved a meta-analysis of data sourced from major databases, including PubMed, Embase, Web of Science, Cochrane Library, and CNKI (4). The researchers reviewed relevant articles published up until November 1, 2023, with the goal of evaluating the diagnostic accuracy of Raman spectroscopy in detecting leukemia (4). In total, 15 groups of original studies from 13 articles were included in the analysis (4).
The pooled sensitivity and specificity of Raman spectroscopy was found to be 0.93 (95% CI, [0.92–0.93]) and 0.91 (95% CI, [0.90–0.92]), respectively (4). These statistics demonstrate that Raman spectroscopy can correctly identify individuals with leukemia and distinguish them from healthy individuals. Moreover, the diagnostic odds ratio was calculated to be 613.01 (95% CI, [270.79–1387.75]), and the area under the curve for the summary receiver operating characteristic curve was 0.99 (4).
One of the most notable aspects of the study was the analyzing live cells using surface-enhanced Raman spectroscopy (SERS). The findings revealed that SERS, a variation of Raman spectroscopy that amplifies the Raman scattering signal, demonstrated even higher diagnostic efficacy compared to standard Raman techniques (4). This suggests that SERS could potentially become a more powerful tool in the early detection and screening of leukemia, offering an advantage over traditional diagnostic methods (4).
The study also delved into the heterogeneity among the included studies, identifying variations in sample categories and Raman spectroscopy techniques as key contributing factors. The researchers conducted a meta-regression analysis to assess this heterogeneity and found that it could be attributed to differences in the types of samples analyzed and the specific Raman spectroscopy methods employed (4).
The research team also examined whether the literature collected had any publication bias. Using the Deeks’ funnel plot asymmetry test, the research team determined that there was no significant bias among the studies included in the analysis (bias coefficient, 40.80; P = 0.13 < 0.10) (4). This suggests that the results of the meta-analysis are robust and not significantly influenced by selective reporting of positive outcomes (4).
The latter part of the study examined the limitations of using Raman spectroscopy to diagnose leukemia. One of the primary concerns is the relatively small number of original studies available on the use of Raman spectroscopy for leukemia detection, which constrained the scope of the meta-analysis (4). Additionally, the lack of clear information on patient selection in some studies may have introduced selection bias, potentially leading to an overestimation of the diagnostic accuracy (4).
Another limitation highlighted by the researchers is the inability to assess the accuracy of Raman spectroscopy in distinguishing between different subtypes of leukemia. Because of the limited data available, a meta-analysis specific to leukemia subtypes could not be conducted (4).
(1) Wetzel, W. Chaos Theory and Raman Spectroscopy Used to Detect Cancer. Spectroscopy. Available at:
(2) Workman, Jr., J. Light and AI Unite: Raman Breakthrough in Noninvasive Lung Cancer Detection. Spectroscopy. Available at:
(3) Wetzel, W. Advancing Breast Cancer Diagnosis and Treatment Using Raman Spectroscopy. Spectroscopy. Available at:
(4) Li, S.; Gao, S.; Su, L.; Zhang, M. Evaluating the Accuracy of Raman Spectroscopy in Differentiating Leukemia Patients from Healthy Individuals: A Systematic Review and Meta-Analysis. Photodiagnosis Photodyn. Ther. 2024, 48, 104260. DOI:
