We report a novel photoacoustic (PA) scoring method for the risk stratification of thyroid nodules, which is combination of the American Thyroid Association (ATA) and PA malignancy probability. We performed multi-spectral PA imaging and multi-parametric PA analysis for thyroid cancer patients (23 malignancy and 29 benign cases). Initial multi-parametric PA analysis showed that malignancy of the thyroid nodules can be diagnosed with a 78% sensitivity and 93% specificity. Moreover, our novel score called ATAP improved the sensitivity to 83% while maintaining the specificity. The results suggest that the ATAP may help physicians examine thyroid nodules, thus reducing unnecessary biopsies.
Thyroid cancer is one of the most prevalent cancers. About 3-8% of the people in the United States have thyroid nodules, and 5-15% of these nodules are malignant. Fine-needle aspiration biopsy (FNAB) is a standard procedure to diagnose malignity of nodules. However, about 10-20% of FNABs produce indeterminable results, which leads to repeat biopsies and unnecessary surgical operations. We have explored photoacoustic (PA) imaging as a new method to identify cancerous nodules. In a pilot study to test its feasibility, we recruited patients with thyroid nodules (currently 36 cases with 21 malignant and 15 benign nodules), acquired in vivo PA and ultrasound (US) images of the nodules in real time using a recently-developed clinical PA/US imaging system, and analyzed the acquired data offline. The preliminary results show that malignant and benign nodules could be differentiated by utilizing their PA amplitudes at different excitation wavelengths. This is the first in vivo PA analysis of thyroid nodules. Although a larger-scale study is needed for statistical significance, the preliminary results show the good potential of PA imaging as a non-invasive tool for triaging thyroid cancer.
Atherosclerosis, the most common cause of death, kills suddenly by arterial occlusion by thrombosis, which is caused by plaque rupture. Because a growing necrotic core is highly related to plaque rupture in atherosclerosis, distinguishing between fibrous plaque and lipid-rich plaque in real time is important, but has been challenging. Real-time photoacoustic imaging requires a pulse laser with high repetition rate, which tends to sacrifice pulse energy. Furthermore, a high repetition rate is hard to achieve at lipid-sensitive wavelengths, such as 1210 nm and 1720 nm. To address the unmet need, we have developed the algorithm for PA imaging. We successfully acquired ex vivo PA images from the lipid cores of arterial plaques in rabbit arteries, using a low-power 1064-nm laser. PA images were acquired with a custom-made catheter employing a single-element 40-MHz ultrasound transducer and a compact 1064-nm laser with the pulse energy of 5 μJ and the repetition rate of 24 kHz. Acquired raw data were processed in the time and frequency domains. In the time domain, a delay-and-sum algorithm was used for image enhancement. In the frequency domain, signals exceeding the MTF were removed. As a result, SNR was increased by about 10 dB without degrading spatial resolution. We were able to achieve high-speed and high-SNR lipid target imaging in animals in spite of the low lipid sensitivity of a 1064nm laser. These results show good promise for detecting lipid-rich plaques with a compact high-speed laser, which can be easily adapted for target clinical applications.
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