Applications of smartphone-based near-infrared (NIR) imaging, measurement, and spectroscopy technologies to point-of-care (POC) diagnostics

Abstract

The role of point-of-care (POC) diagnostics is important in public health. With the support of smartphones, POC diagnostic technologies can be greatly improved. This opportunity has arisen from not only the large number and fast spread of cell-phones across the world but also their improved imaging/diagnostic functions. As a tool, the smartphone is regarded as part of a compact, portable, and low-cost system for real-time POC, even in areas with few resources. By combining near-infrared (NIR) imaging, measurement, and spectroscopy techniques, pathogens can be detected with high sensitivity. The whole process is rapid, accurate, and low-cost, and will set the future trend for POC diagnostics. In this review, the development of smartphone-based NIR fluorescent imaging technology was described, and the quality and potential of POC applications were discussed.

Keywords: Aggregation-induced emission (AIE); Fluorescent probe; Near-infrared (NIR) fluorescent imaging; Point-of-care (POC) diagnostics; Smartphone-based imaging.

Fig. 1. Near-infrared (NIR) biological windows. (a) Absorption coefficient (on a log scale) of oxygenated blood, deoxygenated blood, fatty tissue, and water in NIR-I and NIR-II wavelengths. (b) Image of the viscera of an athymic nude mouse taken immediately after sacrifice. The arrows indicate the location of the gall bladder (GB), small intestine (SI), and bladder (Bl). Tissue autofluorescence was imaged using different excitation/emission filter sets: (c) blue/green (460‒500 nm/505‒560 nm) and (d) NIR (725‒775 nm/790‒830 nm). The results show extremely low absorption and autofluorescence of biological samples in the NIR range (Frangioni, 2003). Reprinted with permission from Frangioni (2003), copyright 2003 Elsevier. (e) Some representative organic NIR fluorophores used in clinical or preclinical applications (Luo et al., 2011). Modified and reprinted with permission from Luo et al. (2011), copyright 2011 Elsevier.

Fig. 1. Near-infrared (NIR) biological windows. (a) Absorption coefficient (on a log scale) of oxygenated blood, deoxygenated blood, fatty tissue, and water in NIR-I and NIR-II wavelengths. (b) Image of the viscera of an athymic nude mouse taken immediately after sacrifice. The arrows indicate the location of the gall bladder (GB), small intestine (SI), and bladder (Bl). Tissue autofluorescence was imaged using different excitation/emission filter sets: (c) blue/green (460‒500 nm/505‒560 nm) and (d) NIR (725‒775 nm/790‒830 nm). The results show extremely low absorption and autofluorescence of biological samples in the NIR range (Frangioni, 2003). Reprinted with permission from Frangioni (2003), copyright 2003 Elsevier. (e) Some representative organic NIR fluorophores used in clinical or preclinical applications (Luo et al., 2011). Modified and reprinted with permission from Luo et al. (2011), copyright 2011 Elsevier.

Fig. 2. Development flow and building blocks of smartphone-based near-infrared (NIR) fluorescent imaging.

Fig. 3. Smartphone-based near-infrared (NIR) fluorescent imaging devices without NIR fluorophores. (a) Rendered image of a cell-phone-based NIR spectrometer and a sectional view of the same system with the optical path (red, orange, green, and blue) highlighted (Pügner et al., 2016); (b) A compact design of an NIR spectrometer on a cell-phone (Hussain et al., 2018); (c) Smartphone-based NIR spectrometer for food detection (SCiO, Consumer Physics, Israel); (d) A smartphone developed for detecting microbial spoilage on ground beef under an 880 nm NIR LED (Liang et al., 2014); (e) An NIR smartphone-based imaging system developed to measure hemoglobin-related oxygenation changes beneath the surface of the skin (in vivo) (Kaile and Godavarty, 2019) (Note: for interpretation of the references to color in this figure legend, the reader is referred to the web version of this article).

Fig. 4. Smartphone-based near-infrared (NIR) fluorescent imaging devices with NIR fluorophores. A smart cell-phone (a) installed with an NIR camera was used to image molded and 3D-printed tissue phantoms (b), and an ex vivo animal model (c). Indocyanine green (ICG) was used as an NIR probe (Ghassemi et al., 2017); white light (d, e) and in vivo fluorescence (f) imaging of a tumor by NIR-enabled mobile phones. An NIR fluorophore monoclonal antibody (mAb)-700 was synthesized by conjugating an mAb with an NIR phthalocyanine dye (IR-700), and intravenously injected into a rodent (Suresh et al., 2018).