NEW APPLICATION OF INFRARED SPECTROSCOPY

IN MEDICAL DIAGNOSIS

Prof. János Mink

Department of Molecular SpectroscopyInstitute of Structural Chemistry

Chemical Research Center of theHungarian Academy of Sciences

H-1025-BudapestPusztaszeri str. 59-67.

Chemical Research Center of HAS Department of Molecular Spectroscopy

Laboratories: Infrared and Raman Spectroscopic Lab. ESR Spectroscopic Lab. NMR Spectroscopic Lab. Laser Spectroscopic Lab.

Professors: László Biczók Gábor Keresztury János Mink Lászó Nemes Antal Rockenbauer Tamás Vidóczy

28 – 16 young scientists / PhD students

University of Pannonia (Veszprém)

Research group: 5 (4) PhD / young scientists

PhD School: Material Science and Technology

Infrared and Raman Laboratory

Budapest: 2 FT-Raman systems FTIR Microscope with FPA detector (micro ATR) FTIR Microscope 2 FTIR spectrometer (ATR) FTIR emission system FTIR-GC system

Veszprém: FTIR research grade 2 FTIR routine Far-IR system Open-path FTIR

13 spectrometer

Extended Collaborations

Surface study: ATR; IRRAS; DRIFTS; EMISSION; LB-films; coatings; polymer surfaces; dispersed

catalysts; archeological samples Analytical studies: HPLC-FTIR; GC-FTIR;TLC-Raman Environmental studies: atmospheric pollutants;

aerosol-microscopy Theoretical studies: DFT; ab initio; Chemometrsics;

etc. Medical applications: human hair and skin

One fingerprint

Four fingerprints

Discovery of the spectral effects

Hair: Narcotics in hair Effects of bleaching Effects of UV-radiation

Skin: Moisture content Lipid content Effects of cosmetics

(Literature)

Unexpected spectral differences

Spectral parameters

• Band position

• Band intensities

• Band widths

• Spectral subtraction

• First derivative

• Second derivative

• Band deconvolution

Statistical data processing

• artificial neural network (ANN),• principal component analysis (PCA) and factor analysis (FA),• principal component regression (PCR),• partial minimum squares (PMS),• Cluster analysis (CA),• generic algorithms (GA).

SKIN

Difference IR spectrum of two healthy patients is very small

0

.2

.4

.6

.8

1

1.2

1.4

Abs

orba

nce

1750 1700 1650 1600 1550 1500 1450 Wavenumber (cm-1)

difference

Spectral deviations between “healthy” and “ill” patients, exhibiting different RIAR values

- .15

- .1

- .05

0

.05

.1

.15

.2

Arb

itrar

y

1700 1600 1500 1400 1300 1200 1100 1000 900

Wavenumber(cm-1)

1550 RIAR 720 RIAR 20 RIAR

- .15

- .1

- .05

0

.05

.1

.15

.2

1600 1500 1400 1300 1200 1100 1000 900

RIAR - Relative Infrared Analytical Risk

RIAR values

ClassificationsCategory of healthy

condition

0-400 Healthy 1

400-600 Weakly endangered 2

600-800 Endangered 3

800-1800 Highly endangered 4

Deviation of a healthy patient’s spectra from the averaged spectra of healthy patients (minimum 20-40 persons) RIAR – Relative Infrared Analytical Risk

Ara nk a

0

20 0

40 0

60 0

80 0

100 0

120 0

140 0

160 0

180 0

1 3 4 7 9 1 0 1 1 1 2 1 4da y

RIA

R

Process of recovery monitored by infrared spectra of the skin belonging to a patient suffering in pancreas cancer. Green line is the limit value of healthy patients

1704

1220

164

0

200

400

600

800

1000

1200

1400

1600

1800

1 64 147day

RIA

R

Distribution between different types of diseases of 820 “ill” patients measured by FTIR spectra of their skin

820 personsTotal

(5%)40 personsAllergy

(8%)67 personsDiabetes

(9%)74 personsLesions of nervous system

(10%)82 personsDiseases of gastrointestinal segments

(33%)270 personsCancerous diseases

(35%)287 personsDiseases of cardiovascular system

820 personsTotal

(5%)40 personsAllergy

(8%)67 personsDiabetes

(9%)74 personsLesions of nervous system

(10%)82 personsDiseases of gastrointestinal segments

(33%)270 personsCancerous diseases

(35%)287 personsDiseases of cardiovascular system

Results of measurements for 380 patients declaring themselves as healthy in accordance of their genial state of health

Qualification Numbers Percent

Healthy or weakly endangered

152 40%

Endangered 137 36%

Highly endangered

91 24%

Results of 39 diabetic patients and 59 healthy persons analyzed by Principal Component Analysis (PCA)

8 8.2 8.4 8.6 8.8 9 9.2-1.4

-1.2

-1

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

diabetic

healthy

HAIR

Infrared spectra of untreated (lower trace) and bleached (upper trace) female hair sample. The difference spectrum is given below (dashed line, with 5x ordinate expansion)

Comparison of human hair infrared spectra of a healthy (lower trace, full line) and a breast cancer patient (upper trace, dashed line)

1800 1700 1600 1500 1400 1300 1200 1100 1000 900

Wavenumber(cm-1)

Abs

orba

nce

0.5 A.U.

Difference spectrum of healthy and breast cancer patient’s hair samples

1800 1700 1600 1500 1400 1300 1200 1100 1000 900

Wavenumber(cm-1)

Abs

orba

nce

0.02 A.U.

Plot of PCA scores for infrared spectra of hair samples

◊-Healthy female scores (negative), □-healthy male scores (positive), ○-breast cancer patients’ scores

Partners

• Stockholm University (Electron Microscopy)

• Institute für Innovative Diagnostik (Ulm)

• Municipal Clinic (XVI District, Budapest)

• LaborTrading Ltd./Varian (Instrumentation)

PRE-DIAGNOSIS BY OPTICAL METHODS

EXPERIMENTAL METHODS IN LABORATORIES

Full diagnosisand therapy

Patient

RIAR software

Skin

Hair

12

Categories of health conditions

1234

Category 2-4

Pre

limin

ary

eval

uat

ion

Ch

emo

met

ric

(Sta

tist

ical

dat

a p

roce

ssin

g)

Mea

sure

men

t MEDICAL CONTROL IN HOSPITAL

Repeating themeasurementchecking the

diagnosis

Classification

Preliminary comparisonwith medical control of

health conditions(4 categories)

Disagreement

34

Agreement

Category 1 = „healthy” library (averaging)

IR measurementsSkin (in situ)Hair (laboratory)

IR spectra IR images(Selected samples)

EM structures(Selected samples)

Illness diagnosis from hospitals

ChemometricCategories 2-4

Classesof similarities

Chemometric Structures

Classesof similarities

Classesof similarities

Type of illnesses

A

B

C

D-

-

-

B

C

D-

-

A

C

D-

-

B

Illness specific libraries

A

B

C

D

EF

Skin Hair-

-

DE

-

B

Hair Hair

Scheme I

(Involves WP 1.1 - WP 1.9 work packages)

WP 1.1

WP 1.3

WP 1.2

WP 1.4

WP 1.5

WP 1.6

WP 1.7

WP 1.8

SUMMARY OF THE TWO YEARS RESULTSWP 1.9 SUMMARY OF THE RESULTS

Transmission FT-IR imaging of human hair

Cuticle

Cortex

Medulla

A B

Images based on the absorption of the CH stretching band (collagen) (A), the Amide I band (protein) (B), of hair

ADVANTAGES

Detection (health condition) Prevention (early diagnosis) Monitoring Diagnosis (under investigation)

CHALLANGING

Simple methods Quick measurement (hair: ~1 min, skin: ~ ½ min)

Not invasive and painless Relative cheap Screening test in mass measures Patients showed very positive attitudes

PhD students and young co-workers

László Kocsis Éva Pfeifer Viktória Komlósi

Bernadett Illés László HajbaVeronika Gombás

Csaba Németh Dr. Károly Héberger

Katalin Módly

Zsuzsanna Kovács

Dr. Gábor Keresztury

Dr. Judith Mihály Dr. Zoltán Bacsik

Co-workers

It was my great pleasure to be with you:

Thanks for Jenny, Carolyn, Jennifer, Kevin, Imre, Glenn, Chris, Mark, George, Baijn and Sam

Special thanks for April H. Foley, Ambassador of

United States

Thanks for your kind attention!!!