scholarly journals Detection of DSS-induced gastrointestinal mucositis in mice by non-invasive optical near-infrared (NIR) imaging of cathepsin activity

2013 ◽  
Vol 14 (8) ◽  
pp. 736-741 ◽  
Author(s):  
Niklas K Finnberg ◽  
Yvette Liu ◽  
Wafik S El-Deiry
Keyword(s):  
Near Infrared ◽  
Non Invasive ◽  
Nir Imaging ◽  
Cathepsin Activity ◽  
Gastrointestinal Mucositis

scholarly journals Imaging of β-amyloid plaques by near infrared fluorescent tracers: a new frontier for chemical neuroscience

2015 ◽  
Vol 44 (7) ◽  
pp. 1807-1819 ◽  
Author(s):  
Matteo Staderini ◽  
María Antonia Martín ◽  
Maria Laura Bolognesi ◽  
J. Carlos Menéndez
Keyword(s):  
Near Infrared ◽  
Amyloid Plaques ◽  
Fluorescent Tracers ◽  
Non Invasive ◽  
Nir Imaging ◽  
New Frontier ◽  
Invasive Method ◽  
Β Amyloid

Near infrared (NIR) imaging is a promising and non-invasive method to visualize amyloid plaquesin vivo.

scholarly journals Remote near infrared identification of pathogens with multiplexed nanosensors

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Robert Nißler ◽  
Oliver Bader ◽  
Maria Dohmen ◽  
Sebastian G. Walter ◽  
Christine Noll ◽  
...  
Keyword(s):  
Near Infrared ◽  
Remote Detection ◽  
Specific Detection ◽  
Tissue Penetration ◽  
Non Invasive ◽  
Nir Imaging ◽  
Smart Surfaces ◽  
Walled Carbon Nanotubes ◽  
Major Pathogens ◽  
Specific Virulence

AbstractInfectious diseases are worldwide a major cause of morbidity and mortality. Fast and specific detection of pathogens such as bacteria is needed to combat these diseases. Optimal methods would be non-invasive and without extensive sample-taking/processing. Here, we developed a set of near infrared (NIR) fluorescent nanosensors and used them for remote fingerprinting of clinically important bacteria. The nanosensors are based on single-walled carbon nanotubes (SWCNTs) that fluoresce in the NIR optical tissue transparency window, which offers ultra-low background and high tissue penetration. They are chemically tailored to detect released metabolites as well as specific virulence factors (lipopolysaccharides, siderophores, DNases, proteases) and integrated into functional hydrogel arrays with 9 different sensors. These hydrogels are exposed to clinical isolates of 6 important bacteria (Staphylococcus aureus, Escherichia coli,…) and remote (≥25 cm) NIR imaging allows to identify and distinguish bacteria. Sensors are also spectrally encoded (900 nm, 1000 nm, 1250 nm) to differentiate the two major pathogens P. aeruginosa as well as S. aureus and penetrate tissue (>5 mm). This type of multiplexing with NIR fluorescent nanosensors enables remote detection and differentiation of important pathogens and the potential for smart surfaces.

scholarly journals An effective method for detecting dorsal hand veins utilising near-infrared imaging technology

2021 ◽  
Vol 63 (2) ◽  
pp. 32-38
Author(s):  
Hai Thanh Le ◽  
◽  
Hien Thi Thu Pham ◽  
Keyword(s):  
Near Infrared ◽  
Infrared Imaging ◽  
Blood Collection ◽  
Imaging Device ◽  
Non Invasive ◽  
Nir Imaging ◽  
Dorsal Hand ◽  
Dorsal Hand Vein ◽  
High Level ◽  
Level Process

Intravenous access for blood collection and other related therapies is one of the most frequently practiced procedures in the modern medical system. The procedure requires complex training and experience, as it might cause dangerous nerve damage and subcutaneous bleeding. This paper proposes a dorsal hand vein detection method utilising the near-infrared (NIR) imaging device to segment and visualise the subcutaneous vein patterns on the skin directly. Applying NIR light has received substantial attention because of its non-invasive and revealing substantially more information than the visible one. The proposed method is divided into the low- and high-level processes. The captured image is smoothed and enhanced to make the vein patterns clearer in the low-level process. The pre-processed image is then segmented step by step to extract the vein features and eliminate the pseudo-vein regions precisely. Lastly, the detected veins are thinned to reduce the thickness and projected back onto the acquired image in the high-level process. The proposed method performs effectively in detecting the clear dorsal hand veins through the experiment with a processing time of 0.61s for the high-resolution image.

The Role of NIR Fluorescence in MDR Cancer Treatment: From Targeted Imaging to Phototherapy

2020 ◽  
Vol 27 (33) ◽  
pp. 5510-5529
Author(s):  
Zengtao Wang ◽  
Qingqing Meng ◽  
Shaoshun Li
Keyword(s):  
Cancer Treatment ◽  
Near Infrared ◽  
Combined Therapy ◽  
Efflux Pumps ◽  
Cross Resistance ◽  
Great Promise ◽  
Drug Efflux ◽  
Nir Dyes ◽  
Nir Imaging ◽  
Drug Efflux Pumps

Background: Multidrug Resistance (MDR) is defined as a cross-resistance of cancer cells to various chemotherapeutics and has been demonstrated to correlate with drug efflux pumps. Visualization of drug efflux pumps is useful to pre-select patients who may be insensitive to chemotherapy, thus preventing patients from unnecessary treatment. Near-Infrared (NIR) imaging is an attractive approach to monitoring MDR due to its low tissue autofluorescence and deep tissue penetration. Molecular NIR imaging of MDR cancers requires stable probes targeting biomarkers with high specificity and affinity. Objective: This article aims to provide a concise review of novel NIR probes and their applications in MDR cancer treatment. Results: Recently, extensive research has been performed to develop novel NIR probes and several strategies display great promise. These strategies include chemical conjugation between NIR dyes and ligands targeting MDR-associated biomarkers, native NIR dyes with inherent targeting ability, activatable NIR probes as well as NIR dyes loaded nanoparticles. Moreover, NIR probes have been widely employed for photothermal and photodynamic therapy in cancer treatment, which combine with other modalities to overcome MDR. With the rapid advancing of nanotechnology, various nanoparticles are incorporated with NIR dyes to provide multifunctional platforms for controlled drug delivery and combined therapy to combat MDR. The construction of these probes for MDR cancers targeted NIR imaging and phototherapy will be discussed. Multimodal nanoscale platform which integrates MDR monitoring and combined therapy will also be encompassed. Conclusion: We believe these NIR probes project a promising approach for diagnosis and therapy of MDR cancers, thus holding great potential to reach clinical settings in cancer treatment.

Near-infrared Inorganic Nanomaterials-based Nanosystem for Photothermal Therapy

Nanoscale ◽  
2021 ◽  
Author(s):  
Yufei Wang ◽  
Hongmin Meng ◽  
Zhaohui Li
Keyword(s):  
Photothermal Therapy ◽  
Near Infrared ◽  
Strong Absorption ◽  
Non Invasive ◽  
Inorganic Nanomaterials

The development of robust materials for treating diseases through non-invasive photothermal therapy (PTT) has attracted increasing attention in recent years. Among many types of nanomaterials, inorganic nanomaterials with strong absorption...

scholarly journals Performance Evaluation of Dorsal Vein Network of Hand Imaging Using Relative Total Variation-Based Regularization for Smoothing Technique in a Miniaturized Vein Imaging System: A Pilot Study

2021 ◽  
Vol 18 (4) ◽  
pp. 1548 ◽  
Author(s):  
Kyuseok Kim ◽  
Hyun-Woo Jeong ◽  
Youngjin Lee
Keyword(s):  
Image Quality ◽  
Total Variation ◽  
Near Infrared ◽  
Imaging System ◽  
Histogram Equalization ◽  
Evaluation Performance ◽  
Visual Evaluation ◽  
Évaluation Performance ◽  
Nir Imaging ◽  
Relative Total Variation

Vein puncture is commonly used for blood sampling, and accurately locating the blood vessel is an important challenge in the field of diagnostic tests. Imaging systems based on near-infrared (NIR) light are widely used for accurate human vein puncture. In particular, segmentation of a region of interest using the obtained NIR image is an important field, and research for improving the image quality by removing noise and enhancing the image contrast is being widely conducted. In this paper, we propose an effective model in which the relative total variation (RTV) regularization algorithm and contrast-limited adaptive histogram equalization (CLAHE) are combined, whereby some major edge information can be better preserved. In our previous study, we developed a miniaturized NIR imaging system using light with a wavelength of 720–1100 nm. We evaluated the usefulness of the proposed algorithm by applying it to images acquired by the developed NIR imaging system. Compared with the conventional algorithm, when the proposed method was applied to the NIR image, the visual evaluation performance and quantitative evaluation performance were enhanced. In particular, when the proposed algorithm was applied, the coefficient of variation was improved by a factor of 15.77 compared with the basic image. The main advantages of our algorithm are the high noise reduction efficiency, which is beneficial for reducing the amount of undesirable information, and better contrast. In conclusion, the applicability and usefulness of the algorithm combining the RTV approach and CLAHE for NIR images were demonstrated, and the proposed model can achieve a high image quality.

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