Download theory of oncobackground and phase transitions in the system

EXPERT SYSTEM TECHNOLOGIES FOR DIAGNOSIS
AND PROGNOSIS OF MALIGNANCIES
Oleg Kshivets, MD, PhD
Omsk Cancer Center, Thoracic Surgery Department,
Russia
National Cancer Institute of The USA
Washington, DC, The USA, 1997
Main Problem of Analysis of Living
Supersystems: Phenomenon of
«Combinatorial Explosion»
• Average Number of Routine Blood
Parameters:………………………………… 28
• Number of Possible Combination for
Random Search:……….. n!=28!=3.049e+29
• Computer Operation Time of The 7G
Teracomputer (1000TFLOPS) (The 21st
Century)…………………… 9.7 Million Years
Basis
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•
•
•
•
NP

RP

P



n! n*n*2(e+n) or n log n  n



AI

CSA+S+B  SM
Model «Cancer Cells(Cr)-Human Killer Cells(Kl)»
• Ćr=Cr(1-Kl·μCr/λKl);
• Ќl=(Kl·μCr/λKl)·[25·Cr/(4.189+
• +2.5·Cr)-Cr-1];
Phase Transitions in System
«Homeostasis-Malignancy»
Regularities of Cell Population
Dynamics in Human Host
Samplings
• Early and Differential Oncodiagnosis
and Immunooncodiagnosis……12162
• Corrected Oncodiagnosis and
Immunooncodiagnosis……….….6013
• Immunooncodiagnosis and
Immunostaging of Malignancy…1743
• Oncoprognosis..……..……………1429
Sampling Structure
• Cancer Patients with the I-IV Stage
(T1-4N0-2M0-1)…………………….6721
• Patients with Non-Malignant
Pathology…………………………..3977
• Practically Healthy Old People…1464
• In All…….…………………………12162
Samplings
• Control Samplings…………..3509
• Learning Samplings………...8653
• Control Histologic Early Cancer
Patients (T1N0M0)…………….373
• Learning Histologic Early Cancer
Patients (T1N0M0)…………….428
Phase Transition Early Malignancy into
Invasive Cancer
Cluster-Analysis of Data of Early and
Invasive Lung Cancer Patients
The Three Phase Transitions in the
System «Malignancy-Human’s
Organism»
Early and Differential
Diagnosis of Malignancies
The Results of Multiple Correspondence and
Claster Analysis of Blood Indexes in
Oncoscreening
Interdependencies between Blood
Parameters, Indexes and Cancer Cell
Population
Interdependencies between Blood
Indexes and Immune System of Cancer
Patients
Prognostic Role of
Cancer Diameter
Prognosis of Cancer
Patients Survival Rate
Trajectories of Interdependencies between Tumor’s
Characteristics and 5-year Cancer Patients Survival
Rate after Radically Operation
Estimation of Average Malignant Tumor
Diameters in Terms of SOD-Technology
High-Precision Quantitative Prognosis
of Cancer Patients Survival
Superoncoscreeng-1.0
SUPERONCOSCREEN
SCREENING
ANTHROPOMETRY
ANAMNESIS
LOCALIZA
SCR-1
SCR-2
ANT-1
ANT-2
LOC1
LO
LOC2
LO
SCR-3 ANT-3
LOC22
LOC3
LO
LOC4
LO
LOC5
LO
LOC6
LO
LOC7
LO
STATISTICS
MALIGNANT
NEOPLASM
LOV8
LO
LOC9
LO
LOC10
LO
PRECANCER
FEMALE
MALE
LOC11
NORM
Superoncodiagnos-1.0
SUPERONCODIAGNOSIS-1.0
DIAGNOSIS-1
DIAGNOSIS-2
PRECANCER
NORM
MALIGNANT NEOPLASM
POPULATION
EARLY CANCER
LOCALIZATION
PHASE TRANSITION
INVASIVE CANCER
STATISTICS
Superoncodiagnosis of
Metastasazing-1.0
SUPERONCODIAGNOSIS O
MTS-N MTS-MLOCALIZATION
LIVER
L
MET-1
MET-2
DEP-1
DEP-2
CANCEROMATO
BONES
B
STATISTICS
MTS
STAGING
KIDNEY
ADREN
OVARY
C1C2 MC
POPULATION
GENERALIZA
PHASE TRANSITION
EARLY MALIGNANCY
ST3
ST1
ST2
PT1
PT2
PT3
INVASIVE MALIGNANC
MALIGNANCY
MALIGNANCY
OF THE II-III STAG
OF T
Superoncoimmunology-1.0
SUPERONCOIMMUNOLOGY-1.0
IMMUNODIAGNOSIS-1
MALIGNANT NEOPLASM
POPULATION
IMMUNODIAGNOSIS-2
IMMUNODEFICIENCY
IMMUNOSTAGING
PHASE TRANSITION
N
EARLY CANCER
INVASIVE CANCER
NORM
M
G
Superoncoprognosis-1.0
SUPERONCOPROGNOSIS-1.0
SURVIVAL-2
PROGNOSIS
PROG-2
PROG-1
SURVIVAL LESS 5 YEARS
SURVIVAL-1
A
B
C
PROG-3
E
SURVIVAL MORE 5 YEARS
Total Monitoring System
POPULATION OF THE COUNTRY
HEALTHY PEOPLE
SOS-1.0
PRECANCER
PERSONS FOR SUSPICION OF
MALIGNANCY
SOD-1.0
SOI-1.0
NONMALIGNANT
PATHOLOGY
MALIGNANCY
SODM-1.0
INVASIVE CANCER
II-III STAGES
EARLY CANCER
SOP-1.0
IV STAGE
CONCLUSION
• 1. The present research which studied 12162
patients with malignant neoplasm, pre-cancer
and
non-malignant
pathology
of
any
localization and practically healthy people
demonstrated
that
the
parameters
of
hematological, biochemical and immunological
homeostasis and their interconnections of
patients with any early oncopathology are
changing typically, while these changes are
certainly different from the norm, pre-cancer
and non-malignant pathology and strictly
correlate to the total quantity of malignant cell’s
population in the patient’s
organism and
neoplasm’s prognosis.
• 2. The system analysis of data of 6013
oncopatients made it possible to establish that
there is a complex net of stable relationship
and
interconnections
between
the
hematological, biochemical, immunological
homeostasis of a patient and a malignant tumor
where factors of the ratio of total quantity of
blood cell’s subpopulations, immunocompetent
cells and healthy cell’s population to the total
quantity of malignant cell’s population in the
whole patient’s organism play the main and
universal role. The dynamic behavior of the
cancer and, in the end, the decease prognosis
for the concrete patient are depended on
numerical values of this ratio.
• 3. Using complex system analysis and
simulation modeling it is found that the system
“cancer-patient’s homeostasis” passes through
three phase transitions (norm-oncobackground,
oncobackground-early oncopathology, early
oncopathology-invasive cancer) in the process
of which the qualitative characteristics,
behavior
and
aggressiveness
of
the
malignancy, anti-tumor abilities of the patient’s
homeostasis and decease prognosis are
changing spasmodically.
• 4. Phase transition of an early oncopathology
into invasive cancer happens when the quantity
of malignant cell’s population reaches 4.189+9
per human organism and the qualitative
oncopathology prognosis gets worth.
• 5. The process of regional and distant
metastasizing and the generalization of
malignancy are typical, their dynamics is
influenced by the same hematological,
biochemical and immunological factors of
human organism’s homeostasis, while these
process are stringently interdepended, are of a
phase character and are strictly determined by
the ratio of total quantity of malignant cell’s
population to the total quantity of healthy cells,
blood cells and immunocompetent cells in the
whole patient’s organism independing on the
tumor localization.
• 6. Complex system analysis of the postponed
survival rate of 1429 operated oncopatients
revealed that prognosis of any malignancy for
patient depends on phase transition of early
oncopathology into invasive cancer and strictly
determined both by the homeostasis data and
tumor’s characteristics, while the life duration of
radically
and
non-radically
operated
oncopatients with the unfavorable decease
prognosis practically does not depend on the
process localization and is regulated by the
same
factors
of
homeostasis
and
oncopathology.
• 7. The 5-year survival rate of radically operated
oncopatients certainly and strictly depends on a
whole number of hematological, biochemical
and immunological parameters of homeostasis;
on cell factors of the ratio of tumor cells to
normal cells for a single patient; on malignancy
characteristics. This dependence is of a
universal and stereotypical character at any
oncopathology localization.
• 8. Complex system account of hematological,
biochemical, immunological, anthropometrical,
clinical, statistical and epidemiological data in
terms of expert systems technology allows the
detection of malignancies of any localization up
to 30% under screening and up to 80% under
differential diagnosis and immunodiagnosis and
also to improve the accuracy of the process
spreading detection up to 96%.
• 9. Complex and system registration of
homeostasis
parameters,
oncopathology
characteristics, interdependencies in the
system
“cancer-human
organism”,
anthropometric data based on the technology
of expert systems allow to make reliable
qualitative-quantitative prognosis of postponed
survival for every radically operated patient with
malignancies of any localization and to
estimate the life duration for non-radically
operated concrete patient with the accuracy of
up to 85%.
• 10. The developed methodologies of early,
differential and corrected diagnosis, prognosis,
immunodiagnosis and immunostaging of
malignant neoplasm oriented for expert
systems technology and computers make it
possible to detect early and invasive
oncopathology of any localization with high
accuracy, to identify regional and distant
metastasizing, to estimate probable time of
relapse and generalization of the process, to
select patients for surgical, combined or
complex treatment. It creates principally new
opportunities for the optimization of the whole
diagnosis-treatment process in terms of
oncology and allows to reduce financial
expenses and volume of instrumental checkups by 2-3 orders in comparison with existing
traditional programs.
Address:
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Oleg Kshivets, M.D., Ph.D.
Thoracic Surgeon
Dep. of Thoracic Surgery
Omsk Cancer Center, Russia
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Tilzes:42-16, Siauliai, LT78206, Lithuania
Tel. (37041)416614
[email protected]
[email protected]
http//:myprofile.cos.com/Kshivets