# A New Method for Screening Thalassemia Patients Using Mid-Infrared Spectroscopy

## TL;DR

This study introduces a new, rapid, and non-invasive method using mid-infrared spectroscopy to screen for thalassemia with high accuracy.

## Contribution

A novel application of IR Microspectroscopy combined with statistical methods for thalassemia screening is proposed.

## Key findings

- Spectral differences between thalassemia patients, carriers, and normals were clearly observed.
- Classification models achieved 80–90% sensitivity and specificity for disease detection.
- The method is non-destructive, reagent-free, and offers biochemical profiling of hemoglobin.

## Abstract

Background/Objectives: Thalassemia is an inherited blood disorder caused by defects in hemoglobin production, where an imbalance or reduction in globin-chain synthesis impairs normal red cell development and results in anemia of varying severity. The disease is classified into α-thalassemia and β-thalassemia according to the affected globin genes. In recent years, infrared (IR) Microspectroscopy has gained increasing attention for blood analysis because it is rapid, label-free, and capable of detecting subtle biochemical alterations. Method: In this study, we analyzed hemoglobin lysate collected from clinically characterized normal, carriers, and thalassemia patients (n = 333) using IR Microspectroscopy combined with multivariate statistical methods, including Principal Component Analysis (PCA) and Partial Least Squares Discriminant Analysis (PLS-DA). This approach enabled us to investigate how spectral features correspond to disease status across a range of genotypes commonly encountered in clinical practice. Results: Clear intergroup spectral differences were observed, and the classification models demonstrated diagnostic performance with sensitivity and specificity of approximately 80–90%. Because the technique is non-destructive, requires no chemical reagents, and allows direct biochemical profiling of hemoglobin, it offers practical advantages over conventional hematologic or molecular assays. Conclusions: These findings support the potential of IR-based spectral analysis as a complementary tool for thalassemia screening. Looking ahead, incorporating advanced machine learning algorithms with IR Microspectroscopy may further enhance early detection, improve risk stratification, and strengthen prevention and management strategies in routine clinical workflows.