1.
EXPERT SYSTEM TECHNOLOGIES FOR DIAGNOSIS AND PROGNOSIS OF MALIGNANCIES <ul><ul><li>Oleg Kshivets, MD, PhD </li></ul></ul><ul><ul><li>Omsk Cancer Center, Thoracic Surgery Department, Russia </li></ul></ul><ul><ul><li>National Cancer Institute of The USA </li></ul></ul><ul><ul><li>Washington, DC, The USA, 1997 </li></ul></ul>

2.
Main Problem of Analysis of Living Supersystems: Phenomenon of «Combinatorial Explosion» <ul><li>Average Number of Routine Blood Parameters:………………………………… 28 </li></ul><ul><li>Number of Possible Combination for Random Search:……….. n!=28!=3.049e+29 </li></ul><ul><li>Computer Operation Time of The 7G Teracomputer (1000TFLOPS) (The 21st Century)…………………… 9.7 Million Years </li></ul>

3.
Basis <ul><li>NP  RP  P </li></ul><ul><li>   </li></ul><ul><li>n!  n*n*2(e+n) or n log n  n </li></ul><ul><li>   </li></ul><ul><li>AI  CSA+S+B  SM </li></ul>

4.
Model «Cancer Cells(Cr)- -Human Killer Cells(Kl)» <ul><li>Ćr=Cr(1-Kl·μ Cr /λ Kl ); </li></ul><ul><li>Ќl=(Kl·μ Cr /λ Kl )·[25·Cr/(4.189+ </li></ul><ul><li>+2.5·Cr)-Cr-1]; </li></ul>

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Phase Transitions in System «Homeostasis-Malignancy»

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Regularities of Cell Population Dynamics in Human Host

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Samplings <ul><li>Early and Differential Oncodiagnosis and Immunooncodiagnosis…… 12162 </li></ul><ul><li>Corrected Oncodiagnosis and Immunooncodiagnosis……….…. 6013 </li></ul><ul><li>Immunooncodiagnosis and Immunostaging of Malignancy… 1743 </li></ul><ul><li>Oncoprognosis..……..…………… 1429 </li></ul>

8.
Sampling Structure <ul><li>Cancer Patients with the I-IV Stage (T1-4N0-2M0-1)……………………. 6721 </li></ul><ul><li>Patients with Non-Malignant Pathology………………………….. 3977 </li></ul><ul><li>Practically Healthy Old People… 1464 </li></ul><ul><li>In All…….………………………… 12162 </li></ul>

9.
Samplings <ul><li>Control Samplings………….. 3509 </li></ul><ul><li>Learning Samplings………... 8653 </li></ul><ul><li>Control Histologic Early Cancer Patients (T1N0M0)……………. 373 </li></ul><ul><li>Learning Histologic Early Cancer Patients (T1N0M0)……………. 428 </li></ul>

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Phase Transition Early Malignancy into Invasive Cancer

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Cluster-Analysis of Data of Early and Invasive Lung Cancer Patients

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The Three Phase Transitions in the System «Malignancy-Human’s Organism»

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Early and Differential Diagnosis of Malignancies

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The Results of Multiple Correspondence and Claster Analysis of Blood Indexes in Oncoscreening

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Interdependencies between Blood Parameters, Indexes and Cancer Cell Population

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Interdependencies between Blood Indexes and Immune System of Cancer Patients

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Prognostic Role of Cancer Diameter

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Prognosis of Cancer Patients Survival Rate

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Trajectories of Interdependencies between Tumor’s Characteristics and 5-year Cancer Patients Survival Rate after Radically Operation

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Estimation of Average Malignant Tumor Diameters in Terms of SOD-Technology

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High-Precision Quantitative Prognosis of Cancer Patients Survival

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Superoncoscreeng-1.0

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Superoncodiagnos-1.0

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Superoncodiagnosis of Metastasazing-1.0

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Superoncoimmunology-1.0

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Superoncoprognosis-1.0

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Total Monitoring System

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CONCLUSION <ul><ul><ul><li>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. </li></ul></ul></ul>

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<ul><ul><ul><li>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. </li></ul></ul></ul>

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<ul><ul><ul><li>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. </li></ul></ul></ul>

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<ul><ul><ul><li>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. </li></ul></ul></ul>

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<ul><ul><ul><li>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. </li></ul></ul></ul>

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<ul><ul><ul><li>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. </li></ul></ul></ul>

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<ul><ul><ul><li>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. </li></ul></ul></ul>

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<ul><ul><ul><li>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%. </li></ul></ul></ul>

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<ul><ul><ul><li>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%. </li></ul></ul></ul>

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<ul><ul><ul><li>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 check-ups by 2-3 orders in comparison with existing traditional programs. </li></ul></ul></ul>

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Address: <ul><li>Oleg Kshivets, M.D., Ph.D. </li></ul><ul><li>Thoracic Surgeon </li></ul><ul><li>Dep. of Thoracic Surgery </li></ul><ul><li>Omsk Cancer Center, Russia </li></ul><ul><li>Tilzes:42-16, Siauliai, LT78206, Lithuania </li></ul><ul><li>Tel. (37041)416614 </li></ul><ul><li>[email_address] [email_address] </li></ul><ul><li>http//:myprofile.cos.com/Kshivets </li></ul>