Surface enhanced Raman spectroscopy for urinary tract infection diagnosis and antibiogram

2010 ◽  
Author(s):  
Evdokia Kastanos ◽  
Katerina Hadjigeorgiou ◽  
Alexandros Kyriakides ◽  
Constantinos Pitris
Keyword(s):  
Raman Spectroscopy ◽  
Urinary Tract Infection ◽  
Urinary Tract ◽  
Tract Infection ◽  
Surface Enhanced Raman Spectroscopy ◽  
Infection Diagnosis ◽  
Surface Enhanced ◽  
Surface Enhanced Raman

scholarly journals Diagnosis of Bacterial Pathogens in the Urine of Urinary-Tract-Infection Patients Using Surface-Enhanced Raman Spectroscopy

Molecules ◽  
2018 ◽  
Vol 23 (12) ◽  
pp. 3374 ◽  
Author(s):  
Ni Tien ◽  
Tzu-Hsien Lin ◽  
Zen-Chao Hung ◽  
Hsiu-Shen Lin ◽  
I-Kuan Wang ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Urinary Tract Infection ◽  
Raman Spectrum ◽  
Urinary Tract ◽  
Tract Infection ◽  
Surface Enhanced Raman Spectroscopy ◽  
Bacteria Identification ◽  
Surface Enhanced ◽  
Surface Enhanced Raman ◽  
Recognition Software

(1) Background: surface-enhanced Raman spectroscopy (SERS) is a novel method for bacteria identification. However, reported applications of SERS in clinical diagnosis are limited. In this study, we used cylindrical SERS chips to detect urine pathogens in urinary tract infection (UTI) patients. (2) Methods: Urine samples were retrieved from 108 UTI patients. A 10 mL urine sample was sent to conventional bacterial culture as a reference. Another 10 mL urine sample was loaded on a SERS chip for bacteria identification and antibiotic susceptibility. We concentrated the urine specimen if the intensity of the Raman spectrum required enhancement. The resulting Raman spectrum was analyzed by a recognition software to compare with spectrum-form reference bacteria and was further confirmed by principal component analysis (PCA). (3) Results: There were 97 samples with single bacteria species identified by conventional urine culture and, among them, 93 can be successfully identified by using SERS without sample concentration. There were four samples that needed concentration for bacteria identification. Antibiotic susceptibility can also be found by SERS. There were seven mixed flora infections found by conventional culture, which can only be identified by the PCA method. (4) Conclusions: SERS can be used in the diagnosis of urinary tract infection with the aid of the recognition software and PCA.

Urinary tract infection diagnosis and response to antibiotics using Raman spectroscopy

2009 ◽  
Author(s):  
Evdokia Kastanos ◽  
Alexandros Kyriakides ◽  
Katerina Hadjigeorgiou ◽  
Constantinos Pitris
Keyword(s):  
Raman Spectroscopy ◽  
Urinary Tract Infection ◽  
Urinary Tract ◽  
Tract Infection ◽  
Infection Diagnosis

A novel method for urinary tract infection diagnosis and antibiogram using Raman spectroscopy

2009 ◽  
Vol 41 (9) ◽  
pp. 958-963 ◽  
Author(s):  
Evdokia K. Kastanos ◽  
Alexandros Kyriakides ◽  
Katerina Hadjigeorgiou ◽  
Costas Pitris
Keyword(s):  
Raman Spectroscopy ◽  
Urinary Tract Infection ◽  
Urinary Tract ◽  
Tract Infection ◽  
Infection Diagnosis ◽  
Novel Method
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