Single cell imaging with near-field terahertz scanning microscopy.

OBJECTIVES: Terahertz (THz)-based imaging techniques hold great potential for biological and biomedical applications, which nevertheless are hampered by the low spatial resolution of conventional THz imaging systems. In this work, we report a high-performance photoconductive antenna microprobe-based near-field THz time-domain spectroscopy scanning microscope. MATERIALS AND METHODS: A single watermelon pulp cell was prepared on a clean quartz slide and covered by a thin polyethylene film. The high performance near-field THz microscope was developed based on a coherent THz time-domain spectroscopy system coupled with a photoconductive antenna microprobe. The sample was imaged in transmission mode. RESULTS: We demonstrate the direct imaging of the morphology of single watermelon pulp cells in the natural dehydration process with our near-field THz microscope. CONCLUSIONS: Given the label-free and non-destructive nature of THz detection techniques, our near-field microscopy-based single-cell imaging approach sheds new light on studying biological samples with THz.

Imaging brain tissue slices with terahertz near-field microscopy.

Photoconductive antenna microprobe (PCAM)-based terahertz (THz) near-field imaging technique is promising for biomedical detection due to its excellent biocompatibility and high resolution; yet it is limited by its imaging speed and the difficulty in the control of the PCAM tip-sample separation. In this work, we successfully realized imaging of mouse brain tissue slices using an improved home-built PCAM-based THz near-field microscope. In this system, the imaging speed was enhanced by designing and applying a voice coil motor-based delay-line. The tip-sample separation control was implemented by developing an image analysis-based technique. Compared with conventional PCAM-based THz near-field systems, our improved system is 100 times faster in imaging speed and the tip-sample separation can be controlled to a few micrometers (e.g., 3 µm), satisfying the requirements of THz near-field imaging of biological samples. It took about ~30 min (not the tens of hours it took to acquire the same kind of image previously) to collect a THz near-field image of brain tissue slices of BALb/c mice (500 µm × 500 µm) with pixel size of 20 µm × 20 µm. The results show that the mouse brain slices can be properly imaged and different regions in the slices (i.e., the corpus callosum region and the cerebrum region) can be identified unambiguously. Evidently, the work demonstrated here provides not only a convincing example but a useful technique for imaging biological samples with THz near-field microscopy. © 2018 American Institute of Chemical Engineers Biotechnol. Prog., 35: e2741, 2019.

A High Precision Terahertz Wave Image Reconstruction Algorithm.

With the development of terahertz (THz) technology, the applications of this spectrum have become increasingly wide-ranging, in areas such as non-destructive testing, security applications and medical scanning, in which one of the most important methods is imaging. Unlike remote sensing applications, THz imaging features sources of array elements that are almost always supposed to be spherical wave radiators, including single antennae. As such, well-developed methodologies such as Range-Doppler Algorithm (RDA) are not directly applicable in such near-range situations. The Back Projection Algorithm (BPA) can provide products of high precision at the the cost of a high computational burden, while the Range Migration Algorithm (RMA) sacrifices the quality of images for efficiency. The Phase-shift Migration Algorithm (PMA) is a good alternative, the features of which combine both of the classical algorithms mentioned above. In this research, it is used for mechanical scanning, and is extended to array imaging for the first time. In addition, the performances of PMA are studied in detail in contrast to BPA and RMA. It is demonstrated in our simulations and experiments described herein that the algorithm can reconstruct images with high precision.