MULTISCALE STUDY OF INFRARED DATA FOR BREAST CANCER DETECTING
Evgeniya Gerasimova1, Yuriy Bayandin1, Oleg Naimark1, G.Freynd2
1
Institute of Continuous Media Mechanics UB RAS, 1 Acad.Korolev str., 614013 Perm, Russia
2
Department of pathological anatomy, Perm State Medical Academy, 26, Petropavlovskaya street, 614990,
Perm, Russia
egerasimova@icmm.ru
Infrared (IR) light is electromagnetic radiation with a wavelength from 0.74 to 300 µm. The intensity of
skin infrared radiation characterizes the thermal state of tissues. The IR camera captures the natural infrared
emission of the skin and converts it into a visual image or thermogram. The thermogram represents temperature
distribution over the surface of the body. Pathological processes change the normal temperature distribution on
the body surface, and in many cases, temperature changes take place earlier than other clinical symptoms,
which is very important for early diagnosis and timely treatment. Nowadays, oncology has gained experience of
using IR thermography in cancer detection, but all obtained cancer signs are only qualitative. So, definition of
objective characteristics of thermogram is important problem for cancer diagnosis.
The aim of this study is to search for quantitative thermography criteria for characterization of cancerous
and healthy tissues using mathematical methods for signal analysis. The IR imaging of 15 patients (with DS:
invasive carcinoma) was performed at the State oncologic dispensary in Perm using IR camera Sedip Jade III
with spectral range 3-5 µm. First, we recorded the IR films of a patient in 3 projections during 30 seconds, and
then performed the functional test by cooling patient’s arms and obtained the second series of IR-films. We
select the area of interest, chose the “hottest” temperature signal corresponding to a tumor and the temperature
signal corresponding to a healthy tissue.
We used four methods for time series analysis: detrended
Table 1
Comparison of scaling parameters for
fluctuation analysis, the greatest amplitude method, RMS-method
tumor and healthy tissue
and power spectrum analysis. The time series x(i), i = 1,...,N under
Tumor
Healthy
tissue
investigation was divided into boxes of equal length n. In each box
Kmax (H)
0.50±0.06 0.36±0.06
corresponding function was calculated. This computation is repeated
DFA (α)
1.55±0.06 1.36±0.11
over all time scales (box sizes) to characterize the relationship
RMS (H)
0.58±0.12 0.36±0.11
between calculated function and the box size n. Then we determined
Power spectrum 1.80±0.08 1.75±0.23
(β)
scaling exponents (the slope of the line relating log of calculated
function to log of time scale n) for temperature time series corresponding to a tumor and to a healthy tissue
(Fig. 1a). It is established that the value of the exponent for tumor is greater than the value of the exponent
obtained for healthy tissue (table 1). Furthermore phase portraits of temperature time series obtained from
tumor area and from healthy tissue were plotted (Fig. 1b). It is seen the qualitative differences in the phase
portraits of “cancerous” and “healthy” signals.
It is supposed that
determined parameters can be
Fdfa(n)
(b)
dT/dt, °C/s
(a)
used
us
significant
– Healthy tissue
informative characteristics of
– Tumor
Tumor
the heat pattern of the breast
α=1.527
2
surface that allow early
R =0.993
recognition of breast surface
Healthy tissue
thermographic abnormalities
α=1.307
R2=0.987
T,
°C
n
invisible to the human eye
and essentially improve the
Figure 1. Determination of scaling exponents α (a) and phase portraits (b) of temperature
information potential of
signals obtained from tumor area and from healthy tissue of one patient.
infrared thermography in
medicine.
The research was supported by the Russian Foundation for Basic Research (grant № 10-01-96051r_ural_а).