Thyroid cancer is one of the most common cancers, with a global increase in incidence rate for both genders. Ultrasound-guided fine-needle aspiration is the current gold standard to diagnose thyroid cancers, but the results are inaccurate, leading to repeated biopsies and unnecessary surgeries. To reduce the number of unnecessary biopsies, we explored the use of multiparametric photoacoustic (PA) analysis in combination with the American Thyroid Association (ATA) Guideline (ATAP). In this study, we performed in vivo multispectral PA imaging on thyroid nodules from 52 patients, comprising 23 papillary thyroid cancer (PTC) and 29 benign cases. From the multispectral PA data, we calculated hemoglobin oxygen saturation level in the nodule area, then classified the PTC and benign nodules with multiparametric analysis. Statistical analyses showed that this multiparametric analysis of multispectral PA responses could classify PTC nodules. Combining the photoacoustically indicated probability of PTC and the ATAP led to a new scoring method that achieved a sensitivity of 83% and a specificity of 93%. This study is the first multiparametric analysis of multispectral PA data of thyroid nodules with statistical significance. As a proof of concept, the results show that the proposed new ATAP scoring can help physicians examine thyroid nodules for fine-needle aspiration biopsy, thus reducing unnecessary biopsies.
This report highlights a novel photoacoustic scoring method for risk stratification of thyroid nodules, where malignancy of the nodules can be diagnosed with 83% sensitivity and 93% specificity.