Objectives: This study investigated the capability of spectral parameters, extracted by frequency domain analysis of photoacoustic signals, to differentiate among malignant, benign, and normal thyroid tissue.
Methods: We acquired multiwavelength photoacoustic images of freshly excised thyroid specimens collected from 50 patients who underwent thyroidectomy after having a diagnosis of suspected thyroid lesions. A thyroid cytopathologist marked histologic slides of each tissue specimen. These marked slides were used as ground truth to identify the regions of interest (ROIs) corresponding to malignant, benign, and normal thyroid tissue. Three spectral parameters: namely, slope, midband fit, and intercept, were extracted from photoacoustic signals corresponding to different ROIs.
Results: Spectral parameters were extracted from a total of total of 65 ROIs. According to the ground truth, 12 of 65 ROIs belonged to malignant thyroids; 28 of 65 ROIs belonged to benign thyroids; and 25 of 65 ROIs belonged to normal thyroids. Besides slope, the other 2 spectral parameters and grayscale photoacoustic image pixel values were found to be significantly different (P < .05) between malignant and normal thyroids. Between benign and normal thyroids, all 3 spectral parameters and photoacoustic pixel values were significantly different (P < .05).
Conclusions: Preliminary results of our ex vivo human thyroid study show that the spectral parameters extracted from radiofrequency photoacoustic signals as well as the pixel values of 2-dimensional photoacoustic images can be used for differentiating among malignant, benign, and normal thyroid tissue.
Keywords: frequency domain analysis; head and neck ultrasound; photoacoustic imaging; thyroid cancer; tissue characterization.
© 2017 by the American Institute of Ultrasound in Medicine.