Application of Photonics in Diagnosis of Papillary Thyroid Carcinoma Tissues through Raman Spectroscopy-Assisted with Chemometrics

Diagnosis of common intraosseous lesions of the dentomaxillofacial region by chemometry-assisted FT-IR spectroscopy in dental tissue samples

PURPOSES

This study aimed to determine the differential diagnosis of three intraosseous lesions (odontogenic keratocyst (OKC), central giant cell granuloma (CGCG), and dentigerous cyst (DC)) of the dentomaxillofacial region with very similar radiological and clinical features by using chemometrics assisted FT-IR (Fourier transform infrared) spectroscopy in tissue samples.

METHODS

Tissue samples (exposed to formaldehyde for a similar time) of 20-micron thickness belonging to 19 intraosseous lesions diagnosed histopathologically were obtained from the pathology laboratory. The samples were analyzed by FT-IR spectroscopic method using the 400-4000 cm-1 wavenumber range, and the obtained spectra of the samples were evaluated using the orthogonal partial least squares discriminant analysis (OPLS-DA) algorithm.

RESULTS

The intraosseous lesions with different histopathological diagnoses were accurately and precisely clustered with different FT-IR bands corresponding to the main molecular vibrations, especially the phosphodiester region, of the tissue components using the proposed model with 3 latent variables.

CONCLUSIONS

The model showed high sensitivity and specificity. The present study is the first to report the elucidation of clear spectral differences between similar lesions in the maxillofacial region. In the future, the FT-IR method may be used in the non-destructive classification of similar lesions in the maxillofacial region as an alternative to histopathological evaluation.

Raman Spectroscopy as a Potential Adjunct of Thyroid Nodule Evaluation: A Systematic Review

The incidence of thyroid nodules (TNs) is estimated at 36.5% and 23% in females and males, respectively. A single thyroid nodule is usually detected during ultrasound assessment in patients with symptoms of thyroid dysfunction or neck mass. TNs are classified as benign tumours (non-malignant hyperplasia), benign neoplasms (e.g., adenoma, a non-invasive follicular tumour with papillary nuclear features) or malignant carcinomas (follicular cell-derived or C-cell derived). The differential diagnosis is based on fine-needle aspiration biopsies and cytological assessment (which is burdened with the bias of subjectivity). Raman spectroscopy (RS) is a laser-based, semiquantitative technique which shows for oscillations of many chemical groups in one label-free measurement. RS, through the assessment of chemical content, gives insight into tissue state which, in turn, allows for the differentiation of disease on the basis of spectral characteristics. The purpose of this study was to report if RS could be useful in the differential diagnosis of TN. The Web of Science, PubMed, and Scopus were searched from the beginning of the databases up to the end of June 2023. Two investigators independently screened key data using the terms "Raman spectroscopy" and "thyroid". From the 4046 records found initially, we identified 19 studies addressing the differential diagnosis of TNs applying the RS technique. The lasers used included 532, 633, 785, 830, and 1064 nm lines. The thyroid RS investigations were performed at the cellular and/or tissue level, as well as in serum samples. The accuracy of papillary thyroid carcinoma detection is approx. 90%. Furthermore, medullary, and follicular thyroid carcinoma can be detected with up to 100% accuracy. These results might be biased with low numbers of cases in some research and overfitting of models as well as the reference method. The main biochemical changes one can observe in malignancies are as follows: increase of protein, amino acids (like phenylalanine, tyrosine, and tryptophan), and nucleic acid content in comparison with non-malignant TNs. Herein, we present a review of the literature on the application of RS in the differential diagnosis of TNs. This technique seems to have powerful application potential in thyroid tumour diagnosis.

Application Value of Color Doppler Ultrasonography Combined with Thyroid Autoantibody Tests in Early Diagnosis of Thyroid Cancer

OBJECTIVE

To explore the application value of color Doppler ultrasonography combined with thyroid autoantibody tests in the early diagnosis of thyroid cancer.

METHODS

The medical data of 100 patients with thyroid nodules treated in our hospital from June 2019 to June 2021 were retrospectively analyzed; all patients received color Doppler ultrasonography and thyroid autoantibody tests before surgery and were divided into the benign lesion group (n = 45) and the malignant lesion group (n = 55) according to the postoperative pathological findings (the gold standard), so as to compare and analyze the application value of color Doppler ultrasonography, thyroid autoantibody tests, and their combination in the early diagnosis of thyroid cancer.

RESULTS

Compared with the pathological findings, the accuracy rate, sensitivity, specificity, positive predictive value, and negative predictive value of the combined diagnosis were significantly higher than those in the single diagnosis of color Doppler ultrasonography, TgAb test, TPOAb test, and TRAb test (P < 0.05), and by plotting the ROC curves to analyze the effect of these modalities in diagnosing early thyroid diseases, the results showed that the areas under the curve from large to small were combined diagnosis, color Doppler ultrasonography, TgAb test, TPOAb test, and TRAb test.

CONCLUSION

Color Doppler ultrasonography has many advantages in the diagnosis of thyroid nodules, such as easy operation, painlessness, noninvasiveness, high efficiency, and repeatable detection, and the high-definition probe is able to show tiny lesions, echogenicity, blood flow signal, and other characteristics of foci. Combining color Doppler ultrasonography with testing thyroid autoantibodies such as TgAb, TPOAb, and TRAb can effectively improve the detection rate of early thyroid cancer, presenting significant reference value and meaning to clinical diagnosis and treatment of thyroid cancer.

Towards development of a novel universal medical diagnostic method: Raman spectroscopy and machine learning

This review summarizes recent progress made using Raman spectroscopy and machine learning for potential universal medical diagnostic applications.

Raman spectroscopy and chemometrics: A potential universal method for diagnosing cancer

Cancer is the second-leading cause of death worldwide. It affects an unfathomable number of people, with almost 16 million Americans currently living with it. While many cancers can be detected, current diagnostic efforts exhibit definite room for improvement. It is imperative that a person be diagnosed with cancer as early on in its progression as possible. An earlier diagnosis allows for the best treatment and intervention options available to be presented. Unfortunately, existing methods for diagnosing cancer can be expensive, invasive, inconclusive or inaccurate, and are not always made during initial stages of the disease. As such, there is a crucial unmet need to develop a singular universal method that is reliable, cost-effective, and non-invasive and can diagnose all forms of cancer early-on. Raman spectroscopy in combination with advanced statistical analysis is offered here as a potential solution for this need. This review covers recently published research in which Raman spectroscopy was used for the purpose of diagnosing cancer. The benefits and the risks of the methodology are presented; however, there is overwhelming evidence that suggests Raman spectroscopy is highly suitable for becoming the first universal method to be used for diagnosing cancer.