A recent study conducted by scientists in Brazil saw the development of a quick, non-invasive method to diagnose endometriosis.
In a recent study conducted by researchers from Brazil’s Federal University of Rio Grande do Norte, an important women’s health issue was investigated. The study, which was led by Kassio Michell Gomes de Lima, a researcher at the Federal University of Rio Grande do Norte, explored how endometriosis detection can be improved using spectroscopy. This study presents a new, fast, cost-effective, and non-invasive diagnostic method based on blood plasma analysis (1). The insights presented in this study, which was published in Scientific Reports, show how infrared (IR) spectroscopy can improve the early detection of endometriosis in women.
Endometriosis is a medical issue that affects the lining of the uterus in women. Instead of growing normally, the lining of the uterus grows outside the uterus, and this can cause the woman to feel severe pain in the pelvis and have difficulties getting pregnant (2). Women affected with endometriosis can also experience symptoms such as severe pain when urinating, nausea, abdominal bloating and pain, and sometimes depression and anxiety (2). This disease impacts approximately 10% of reproductive-age women worldwide, and there is currently no known cure (2).
As a result, researchers are primarily focused on early diagnosis and effective treatments. The problem is that current diagnostic methods, including laparoscopy, are invasive, expensive, and not always readily accessible (1). Therefore, researchers are looking for alternative strategies that could offer quicker diagnoses.
In this study, the researchers applied a combination of attenuated total reflection Fourier-transform infrared (ATR FT-IR) and near-infrared (NIR) spectroscopy techniques to blood plasma samples from two groups: women diagnosed with endometriosis (n = 41) and healthy individuals (n = 34). NIR and ATR FT-IR are not effective techniques on their own, but when they were integrated with multivariate classification models, the researchers found that they could differentiate between affected and unaffected patients (1).
The multivariate analysis methods used in this study include principal component analysis–linear discriminant analysis (PCA-LDA), successive projections algorithm–linear discriminant analysis (SPA-LDA), and genetic algorithm–linear discriminant analysis (GA-LDA). These models demonstrated impressive discriminant power, achieving improved levels of sensitivity, specificity, and overall accuracy (1). The fusion of ATR FT-IR and NIR data allowed for a more nuanced classification, which improved the reliability of the results (1).
One of the study’s most important findings was the strong positive correlations observed between spectrochemical biomarkers in both infrared (IR) regions through two-dimensional (2D) correlation analysis. This biochemical "cell fingerprint," as the researchers described in their study, captured the unique chemical alterations in blood plasma caused by endometriosis, providing a powerful diagnostic signature (1).
There are potentially important implications for clinical analysis in this study. By enabling early-stage detection through a simple blood test, healthcare providers could significantly reduce the time to diagnosis and initiate treatment sooner (1). Furthermore, the non-destructive nature of IR spectroscopy means that sample integrity is preserved, facilitating repeated analysis if needed without additional patient discomfort.
In medical diagnostics, IR spectroscopy is being routinely used with chemometrics because this integration allows for the swift detection of complex biochemical changes in biological samples (1). Based on the success of this technique for other disease detection applications, using IR spectroscopy with chemometrics for this purpose makes it an appealing tool to detect endometriosis, which currently lacks simple screening methods (1).
Ultimately, the researchers hope that future studies validate their findings by conducting larger clinical trials across diverse populations (1). Doing so, they state in their study, would help improve their approach (1). The research team at the Federal University of Rio Grande do Norte is optimistic that, with further development, this methodology could be integrated into routine gynecological exams within the next decade.
