Identification of ibd using an electronic e nose
This presentation is the property of its rightful owner.
Sponsored Links
1 / 21

Identification of IBD using an electronic e-nose PowerPoint PPT Presentation


  • 77 Views
  • Uploaded on
  • Presentation posted in: General

Identification of IBD using an electronic e-nose. Covington JA 3, , Westinbrink E 3 , Nwokolo C 1 , Bardhan KD 4 , Arasaradnam RP 1,2 1University Hospital Coventry & Warwickshire & 2Clinical Sciences Research Institute, Medical School, University of Warwick

Download Presentation

Identification of IBD using an electronic e-nose

An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -

Presentation Transcript


Identification of ibd using an electronic e nose

Identification of IBD using an electronic e-nose

Covington JA3,, Westinbrink E3, Nwokolo C1, Bardhan KD4, Arasaradnam RP1,2

1University Hospital Coventry & Warwickshire &

2Clinical Sciences Research Institute, Medical School,

University of Warwick

3School of Engineering, University of Warwick, 4Rotherham NHS Trust

11th BROAD Meeting, Los Angeles – March 2013

1


Identification of ibd using an electronic e nose

Distal UC; proximal constipation

PL, age 64

11 weeks after PEG: 4 / 20 markers

Before PEG: 13 / 20 markers

Cow 100%

Horse 100%

Cow 50%

Saw dust 50%

--horse-oid!

2


Composite animal volatile organic compounds vocs chromatogram profile gc

Composite animal Volatile Organic Compounds (VOCs) - chromatogram profile (GC)

Pilot – Animal Studies

Chicken = Black

Horse = Pink

Cow = Blue

Time

Quantity: Measured as ppm or calculated as area under curve (AUC)

3


Identification of ibd using an electronic e nose

Sniffing diseases..…

Can we smell these chemcical?

(>5 senses)


Smell @ warwick

‘Smell’ @ Warwick

Life in ‘Smell’

Persaud & Dodd Nature 1982

First research group dedicated to the sense of smell

First company making artificial olfaction instruments

First commercial products manufactured here…

Long history of smell research…


What can we analyse

What can we analyse?

Urine/Faecal/Breath samples from animals & patients

Chemical analysis of odours emanating from the sample – essentially sniffing!

6


Volatile organic compounds vocs

Volatile organic compounds (VOCs)

  • Disease alters gut flora - altered fermentation patterns which alters the composition of gases emitted from urine

  • Organic compounds that have high vapour pressure at normal room temperature.

  • Mainly from colonic fermentation by gut bacteria and partly from physiological metabolic processes

  • Released in breath, urine, faeces, blood

  • A potential diagnostic biomarker in IBD


Technologies used

Technologies used

Ion Mobility Spectrometry

Electronic nose

GCMS


Study design

Study design

62 subjects – 3 groups

Urine collected and analysed using E-nose and FAIMS

Data analysed using Principal Component analysis


Identification of ibd using an electronic e nose

E-nose sensor response


Differentiating ibd using e nose

Differentiating IBD using E-nose

The maximum response minus the minimum response

is used as a feature for data analysis


Results e nose

Results – E nose

Discriminant Function (DF) Analysis of Fox 4000 data


Faims field asymetric ion mobility spectrometry

FAIMS – Field Asymetric Ion Mobility Spectrometry

  • Simple fast analysis of vapours and gases

  • Detects chemicals in complex mixtures

  • Identifies by mobility (ion movement through an electric field)

  • Mobility determined by molecule size and mass


Faims data

FAIMS Data

  • 4,000 variables from Wavelet transform

  • Cluster Analysis to identify key variables

  • Use 20 for identification

1st 500 variables

Control – Disease state


Study design1

Study design

105 subjects – 2 groups

Urine collected and analysed using FAIMS

Data analysed using Principal Component analysis


Results faims n 105

Results – FAIMS (n = 105)

  • 40 Crohns

  • 40 Ulcerative Colitis

  • 25 Controls

Each sample re-classified based on remaining samples


Identification of ibd using an electronic e nose

Results – FAIMS flare vs remission


Identification of ibd using an electronic e nose

Separation of IBD and controls with Gas Chromatography


Summary of chemical peaks in volunteers and crohn s uc patients

Summary of chemical peaks in volunteers and Crohn’s , UC patients

What are we detecting?

Possible Key chemicals

  • In excess of 20 chemicals modulated;

  • Likely key chemicals:

    • ethyl esters propanoic or butanoic acids, butanoic acid

    • methyl ester, 3-methyl butanoic acid, 1-butanol, 1-propanol and indole

HA=hydrogen azide (HN3); APossible Key chemicalsA=acetic acid (CH3COOH); PG=propylene glycol (C3H6(OH)2); A=aldehydes; K=ketones; OA=organic acids.


Conclusions

Conclusions

Clear disease separation between controls, ulcerative colitis and Crohn’s disease

Able to detect between disease flares and remission

VOC correlation with GC

Potential first line diagnostic modality in patients with suspected IBD

Inexpensive novel tool, non invasive and potentially provides point of care diagnosis


Thank you questions

Acknowledgements:

Nathalie Ouaret (PhD)

Nabil Quraishi (MSc)

Eic Westinbrink (PhD)

Nicki O’Connel, RGN

Catherine Bailey, RGN

BROAD Foundation

BRET

BDRF

Thank you - Questions


  • Login