Development of Terahertz Imaging Markers for Pancreatic Ductal Adenocarcinoma using Maximum A Posteriori Probability (MAP) Estimation.

Abstract

Pancreatic ductal adenocarcinoma (PDAC) is one of the significant reasons for cancer-related death in the United States due to a lack of timely prognosis and the poor efficacy of the standard treatment protocol. Immunotherapy-based neoadjuvant therapy, such as stereotactic body radiotherapy (SBRT), has shown promising results compared to conventional radiotherapy in strengthening the antitumor response in PDAC. To probe and quantify the antitumor response with SBRT, we propose to study the tumor microenvironment using terahertz time-domain spectroscopy (THz-TDS). Since the tumor's complex microenvironment plays a key role in disease progression and treatment supervision, THz-TDS can be a revolutionary tool to help in treatment planning by probing the changes in the tissue microenvironment. This paper presents THz-TDS of paraffin-embedded PDAC samples utilizing a clinically relevant genetically engineered mouse model. This Article aims to develop and validate a novel time-domain approximation method based on maximum a posteriori probability (MAP) estimation to extract terahertz parameters, namely, the refractive index and the absorption coefficient, from THz-TDS. Unlike the standard frequency-domain (FD) analysis, the parameters extracted from MAP construct better-conserved tissue parameters estimates, since the FD optimization often incorporates errors due to numerical instabilities during phase unwrapping, especially when propagating in lossy media. The THz-range index of refraction extracted from MAP and absorption coefficient parameters report a statistically significant distinction between PDAC tissue regions and their healthy equivalents. The coefficient of variation of the refractive index extracted by MAP is one order of magnitude lower compared to the one extracted from FD analysis. The index of refraction and absorption coefficient extracted from the MAP are suggested as the best imaging markers to reconstruct THz images of biological tissues to reflect their physical properties accurately and reproducibly. The obtained THz scans were validated using standard histopathology.