Terahertz imaging of metastatic lymph nodes using spectroscopic integration technique

Abstract

Terahertz (THz) imaging was used to differentiate the metastatic states of frozen lymph nodes (LNs) by using spectroscopic integration technique (SIT). The metastatic states were classified into three groups: healthy LNs, completely metastatic LNs, and partially metastatic LNs, which were obtained from three mice without infection and six mice infected with murine melanoma cells for 30 days and 15 days, respectively. Under histological examination, the healthy LNs and completely metastatic LNs were found to have a homogeneous cellular structure but the partially metastatic LNs had interfaces of the melanoma and healthy tissue. THz signals between the experimental groups were not distinguished at room temperature due to high attenuation by water in the tissues. However, a signal gap between the healthy and completely metastatic LNs was detected at freezing temperature. The signal gap could be enhanced by using SIT that is a signal processing method dichotomizing the signal difference between the healthy cells and melanoma cells with their normalized spectral integration. This technique clearly imaged the interfaces in the partially metastatic LNs, which could not be achieved by existing methods using a peak point or spectral value. The image resolution was high enough to recognize a metastatic area of about 0.7 mm size in the partially metastatic LNs. Therefore, this pilot study demonstrated that THz imaging of the frozen specimen using SIT can be used to diagnose the metastatic state of LNs for clinical application.

Terahertz radiation and the skin: a review

“…The characteristic sample features are observed in the maximum or minimum values of the time-domain TPS waveform or in the frequency-domain data, such as the sample refractive index and absorption coefficient in a broad frequency range. The contrast-enhancement approaches, such as the integration technique, 80 principal component analysis, linear discriminant analysis, 81 or signal complexity analysis, 82 are often applied to improve the capabilities of THz spectroscopy and imaging.…”

AVNP2 protects against cognitive impairments induced by C6 glioma by suppressing tumour associated inflammation in rats

“…In particular, terahertz (THz) imaging as one of the candidate technologies for medical imaging has attracted great attention in recent years due to its properties of fingerprint spectrum, safety, and water sensitivity. The research on THz biological imaging has been used in various medical fields, such as dermatology and oncology (Sim et al, 2013;Woodward et al, 2003;Reid et al, 2011;Park et al, 2017). In the field of neurosurgery, investigations of gliomas using THz spectrum and THz reflection imaging have also been reported for post-processed, fresh ex vivo and in vivo brain tissues (Park et al, 2017;Oh et al, 2014;Meng et al, 2014;Wu et al, 2019).…”

Machine Learning Techniques for THz Imaging and Time-Domain Spectroscopy

“…In recent years, numerous THz applications have been developed in biomedical and engineering fields [ 1 , 2 , 3 , 4 , 5 , 6 , 7 ]. In particular, they can be used for disease diagnosis in biological samples [ 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 ], characteristic analysis of biological samples [ 21 , 22 , 23 , 24 , 25 , 26 ] and biomolecules [ 27 , 28 , 29 , 30 , 31 , 32 , 33 ], non-destructive detection of artifacts and objects in samples [ 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 ], identification of hidden materials and their properties [ 42 , 43 , 44 , 45 ], estimation of the components in a mixture [ 46 , 47 , 48 , 49 , 50 , 51 ], and so on. Due to the rapid evolution of THz technologies and their increased availability, it is expected that the appli...…”

“…In recent years, numerous THz applications have been developed in biomedical and engineering fields [1][2][3][4][5][6][7]. In particular, they can be used for disease diagnosis in biological samples [8][9][10][11][12][13][14][15][16][17][18][19][20], characteristic analysis of biological samples [21][22][23][24][25][26] and biomolecules [27][28][29][30][31][32][33], non-destructive detection of artifacts and objects in samples [34][35][36][37][38][39][40][41], identification of hidden materials and their properties [42][43][44][45], estimation of the components in a mixture [46][47][48]…”