journal article·2016-06-10Open access

Rapid and quantitative discrimination of tumour cells on tissue slices

Kai-Wen Huang, Jen-Jie Chieh, Shu-Hsien Liao, Wen-Chun Wei, Pei-Yi Hsiao, Hong-Chang Yang, Herng-Er Horng

Nanotechnology· Volume 27· Issue 23

Abstract

After a needle biopsy, immunohistochemistry is generally used to stain tissue slices for clinically confirming tumours. Currently, tissue slices are immersed in a bioprobe-linked fluorescent reagent for several minutes, washed to remove the unbound reagent, and then observed using a fluorescence microscope. However, the observation must be performed by experienced pathologists, and producing a qualitative analysis is time consuming. Therefore, this study proposes a novel scanning superconducting quantum interference device biosusceptometry (SSB) method for avoiding these drawbacks. First, stain reagents were synthesised for the dual modalities of fluorescent and magnetic imaging by combining iron-oxide magnetic nanoparticles and the currently used fluorescent reagent. The reagent for the proposed approach was stained using the same procedure as that for the current fluorescent reagent, and tissue slices were rapidly imaged using the developed SSB for obtaining coregistered optical and magnetic images. Analysing the total intensity of magnetic spots in SSB images enables quantitatively determining the tumour cells of tissue slices. To confirm the magnetic imaging results, a traditional observation methodology entailing the use of a fluorescence microscope was also performed as the gold standard. This study determined high consistency between the fluorescent and magnetic spots in different regions of the tissue slices, demonstrating the feasibility of the proposed approach, which will benefit future clinical pathology.
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Research context

OpenAlex topics: Advanced Electron Microscopy Techniques and Applications · Electron and X-Ray Spectroscopy Techniques · Advanced X-ray Imaging Techniques

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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