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Integrating Raman spectroscopy and RT-qPCR for enhanced diagnosis of thyroid lesions: A comparative study of biochemical and molecular markers:

1. Introduction

Thyroid lesions encompass a range of benign and malignant disorders, with accurate early diagnosis being critical for effective clinical management. Conventional diagnostic approaches, including fine-needle aspiration cytology (FNAC), often yield indeterminate results, prompting the need for supplementary techniques. This study explores the integration of Raman spectroscopy and reverse transcription quantitative PCR (RT-qPCR) to enhance diagnostic accuracy. By combining biochemical and molecular data, this dual approach holds promise for a more comprehensive, sensitive, and specific analysis of thyroid lesions.

2. Raman Spectroscopy as a Biochemical Fingerprinting Tool

Raman spectroscopy offers a rapid, non-destructive method for biochemical analysis by detecting vibrational energy changes in molecular bonds. In the context of thyroid lesion diagnosis, Raman spectroscopy can identify changes in proteins, nucleic acids, and lipid content that correlate with malignancy. This technique provides immediate insight into the biochemical landscape of thyroid tissues, helping differentiate between benign and malignant states with high spectral resolution and minimal sample preparation.

3. RT-qPCR for Quantitative Molecular Marker Assessment

RT-qPCR remains a gold standard for assessing gene expression levels, particularly in cancer diagnostics. In this study, RT-qPCR was used to quantify the expression of known thyroid cancer-associated genes such as BRAF, RAS, and RET/PTC rearrangements. These molecular markers serve as critical indicators of malignancy and, when interpreted alongside biochemical data from Raman spectroscopy, offer a multidimensional view of the lesion's biological status.

4. Comparative Analysis of Diagnostic Performance

This research systematically compares the diagnostic performance of Raman spectroscopy and RT-qPCR, individually and in combination. While RT-qPCR provides high specificity through genetic data, Raman spectroscopy adds complementary biochemical insights. The combined approach showed improved sensitivity and accuracy in differentiating various types of thyroid lesions, including follicular neoplasms and papillary thyroid carcinomas, suggesting a synergistic diagnostic value.

5. Integration Strategy and Multivariate Data Analysis

To harmonize the outputs from both techniques, multivariate statistical analysis, such as principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA), was employed. These tools enabled the integration of spectral and gene expression datasets, revealing distinct clusters for benign versus malignant lesions. This integration strategy enhances interpretability and provides a robust diagnostic model for clinical applications.

6. Clinical Implications and Future Perspectives

The integration of Raman spectroscopy and RT-qPCR represents a promising step toward personalized and precision diagnostics in thyroid pathology. This dual-modality approach not only improves diagnostic confidence but also has potential for intraoperative assessments and real-time decision-making. Future research will focus on expanding sample sizes, automating the analysis process, and validating the model in multi-center clinical trials to facilitate adoption in routine pathology labs.

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#RamanSpectroscopy #RTqPCR #ThyroidCancer #MolecularDiagnostics #BiochemicalMarkers #PrecisionMedicine #ThyroidLesions #CancerDiagnostics #SpectroscopyInMedicine #MultiOmics #GeneExpression #OncologyResearch #BiomedicalSpectroscopy #RTqPCRAnalysis #ThyroidPathology #NonInvasiveDiagnostics #MachineLearningInHealthcare #VibrationalSpectroscopy #TranslationalMedicine #Biophotonics

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