In this section
We use light to develop advanced diagnostic tools, wearable sensors, and microscale robots for studying diseases and enabling minimally invasive treatments.
We use photonics to develop new technologies for medicine and to study the pathophysiology of disease. This includes new and improved diagnostic tools as well as microscale robotic devices for therapeutic applications. We use a variety of optical techniques for this purpose such as fluorescence, Raman and diffuse reflectance spectroscopy, as well as microscopy and interferometry. We develop devices ranging from wearable sensors and fibre-optic probes for minimally invasive diagnostics through to microscale robots for cellular-scale manipulation and therapy.
Our research has a number of potential clinical applications including improved monitoring of clinical therapies and interventions (e.g. in inflammatory bowel disease and malnutrition), early diagnosis of infection, and even margin mapping in tumour resection surgery.
The devices we are developing can potentially provide less invasive and lower cost diagnostics. In turn, this may facilitate patient benefits including earlier diagnosis, earlier identification of relapse (e.g. in therapy response monitoring applications), more widespread deployment and more comfortable patient experiences (e.g. through use of less invasive probes and sensors).
Dr Belal Ahmad
Imperial College Research Fellow
Dr Qian Chen
Clinical Research Fellow
Dr Ahmed Ezzat
Research Postgraduate
Dr Nilanjan Mandal
Research Associate in Optical Sensing for LMICs
Dr Alexander J Thompson
Senior Lecturer in Biomedical Sensing
Mr Zeyu Wang
Research Postgraduate
@inproceedings{Dryden:2020:10.1117/12.2545515,
author = {Dryden, S and Anastasova, S and Satta, G and Thompson, AJ and Leff, DR and Darzi, AW},
doi = {10.1117/12.2545515},
pages = {1124705--1--1124705--7},
publisher = {SPIE},
title = {Toward point-of-care uropathogen detection using SERS active filters},
url = {http://dx.doi.org/10.1117/12.2545515},
year = {2020}
}
TY - CPAPER
AB - 150 million people worldwide suffer one or more urinary tract infections (UTIs) annually. UTIs are a significant health burden: societal costs of UTI exceed $3.5 billion in the U.S. alone; 5% of sepsis cases arise from a urinary source; and UTIs are a prominent contributor toward antimicrobial resistance (AMR). Current diagnostic frameworks exacerbate this burden by providing inaccurate and delayed diagnosis. Rapid point-of-care bacterial identification will allow for early precision treatment, fundamentally altering the UTI paradigm. Raman spectroscopy has a proven ability to provide rapid bacterial identification but is limited by weak bacterial signal and a susceptibility to background fluorescence. These limitations may be overcome using surface enhanced Raman spectroscopy (SERS), provided close and consistent application of bacteria to the SERS-active surface can be achieved. Physical filtration provides a means of capturing uropathogens, separating them from the background solution and acting as SERS-active surface. This work demonstrates that filters can provide a means of aggregating bacteria, thereby allowing subsequent enhancement of the acquired Raman signal using metallic nanoparticles. 60 bacterial suspensions of common uropathogens were vacuum filtered onto commercial polyvinylidene fluoride membrane filters and Raman signals were enhanced by the addition of silver nanoparticles directly onto the filter surface. SERS spectra were acquired using a commercial Raman spectrometer (Ocean Optics, Inc.). Principal Component – Linear Discriminant Analysis provided discrimination of infected from control samples (accuracy: 88.75%, 95% CI: 79.22-94.59%, p-value <0.05). Amongst infected samples uropathogens were classified with 80% accuracy. This study has demonstrated that combining Raman spectroscopy with membrane filtration and SERS can provide identification of infected samples and rapid bacterial classification.
AU - Dryden,S
AU - Anastasova,S
AU - Satta,G
AU - Thompson,AJ
AU - Leff,DR
AU - Darzi,AW
DO - 10.1117/12.2545515
EP - 1
PB - SPIE
PY - 2020///
SP - 1124705
TI - Toward point-of-care uropathogen detection using SERS active filters
UR - http://dx.doi.org/10.1117/12.2545515
UR - https://www.spiedigitallibrary.org/conference-proceedings-of-spie/11247/2545515/Toward-point-of-care-uropathogen-detection-using-SERS-active-filters/10.1117/12.2545515.full?SSO=1
UR - http://hdl.handle.net/10044/1/77604
ER -
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