WO2002045581A1 - Relation entre cancer du sein et oestrogene par signal de surface corporelle en temps reel - Google Patents

Relation entre cancer du sein et oestrogene par signal de surface corporelle en temps reel Download PDF

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Publication number
WO2002045581A1
WO2002045581A1 PCT/JP2001/010253 JP0110253W WO0245581A1 WO 2002045581 A1 WO2002045581 A1 WO 2002045581A1 JP 0110253 W JP0110253 W JP 0110253W WO 0245581 A1 WO0245581 A1 WO 0245581A1
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WIPO (PCT)
Prior art keywords
breast cancer
frequency
normal
time
estrogen
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PCT/JP2001/010253
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English (en)
Japanese (ja)
Inventor
Michiko Yagi
Zenro Nihei
Takayuki Osanai
Yukiko Koike
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Kabushiki Kaisya Advance
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Application filed by Kabushiki Kaisya Advance filed Critical Kabushiki Kaisya Advance
Priority to JP2002547375A priority Critical patent/JPWO2002045581A1/ja
Publication of WO2002045581A1 publication Critical patent/WO2002045581A1/fr

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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7235—Details of waveform analysis
    • A61B5/7253—Details of waveform analysis characterised by using transforms
    • A61B5/7257—Details of waveform analysis characterised by using transforms using Fourier transforms
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof

Definitions

  • the present invention relates to the relationship between breast cancer and estrogen using body surface real-time signals.
  • Breast cancer is a typical hormone-dependent tumor. Therefore, endocrine diagnosis and treatment are performed for diagnosis and treatment of breast cancer. One of them is the method of measuring estrogen (ES) and its receptor (ER), which has attracted attention in recent years. In addition, there are other methods for diagnosing breast tumors such as ultrasound, NMR measurement, and bioelectrical impedance measurement.
  • ES estrogen
  • ER receptor
  • the frequency time-series analysis method of the real-time signal waveform of the present method uses the frequency response in response to the biological activity of the living body. This method analyzes the time-varying pattern. This method analyzes the relationship between the physiological activity and the complex network of frequency. In order to apply this study to diagnosis, many cases (100 or more patients) and time and Basic knowledge of frequency analysis is required as an absolute condition. Based on these conditions, the relationship between bioactivity and frequency must be clarified. For that purpose, the relationship with the physiological activity must be examined for each frequency of 1 Hz. Therefore, applying this method to diagnosis requires time and detailed basic research.
  • Figure 1 is a Draf showing the frequency (FFT) spectra of normal individuals and patients with papillary ductal carcinoma.
  • FIG. 2 is a diagram showing a relationship between upper left and left outer breast cancer and frequency.
  • FIG. 3 is a diagram showing a relationship between upper right, right inner and right outer breast cancer and frequency.
  • FIG. 4 is a graph showing a time-series pattern in a low frequency region of breast cancer and a normal person
  • Figures 4A-1 and 4A-2 show the time series patterns obtained from the upper breasts of 25-35 year old breast cancer patients and normals
  • Figures 4B-1 and 4B-2 show the time-series patterns obtained from the outer breasts of 25-35 year old breast cancer patients and normals
  • Figures 4C-1 and 4C-2 show the time series patterns obtained from the upper breasts of breast cancer patients and normals between the ages of 40 and 50,
  • FIGS.4D-1 to 4D-4 show time series patterns obtained from the outer breasts of breast cancer patients aged 40 to 50 years and normals
  • Figures 4E-1 and 4E-2 show the time series patterns obtained from the upper breasts of 50- to 60-year-old breast cancer patients and normal persons,
  • Figures 4F-1 and 4F-2 show 50 to 60 year old breast cancer patients and Shows a time series pattern obtained from the outer breast of a normal person
  • Figures 4G-1 and 4G-2 show the time series patterns obtained from the upper breasts of breast cancer patients and normals between the ages of 60 and 76.
  • Figures 4H-1 and 4H-2 show the time series patterns obtained from the outer breasts of breast cancer patients and normals between the ages of 60 and 76.
  • Figure 5A is a Draf showing the 5.7.373 Hz time series of the lower left breast of a normal person (66 years old).
  • FIG. 5B is a graph showing a 58.594 Hz time series of estrogen-treated lower left lower breast cancer patient (66 years old).
  • FIG. 6A is a graph showing a transient spike time series (E mn) of 68.359 Hz on the first day of the menstrual cycle (ES minimum value) of a normal person (28 years old).
  • FIG. 6B is a graph showing a 68.359 Hz bispike time series (Emax) of a normal person (28 years old) at 12 days after the menstrual cycle (maximum ES).
  • FIG. 7A is a Draf showing the 50.49 Hz time series of a lower right breast cancer patient (48 years old).
  • FIG. 7B shows the time-course of 50.49 Hz of Tamoxifen administration (20 mg / day) lower right breast cancer patient (48 years old: same person as 7A).
  • FIG. 7C is a graph showing the 64.679 Hz time series of a right posterior breast cancer patient (30 years old).
  • FIG. 7D shows the 6.4.697 Hz time series of Tamoxifen administration (20 mg / day) right posterior breast cancer patient (30 years old).
  • FIG. 8 is a diagram schematically showing the relationship between non-voltage-dependent calcium channels and breast cancer.
  • FIG. 9 is a diagram showing the positions of the electrodes.
  • FIG. 10 is a schematic configuration of a signal processing device according to one embodiment of the present invention.
  • a surface electrode was placed on the body surface of a breast cancer patient and a normal human at the same age and position as the patient (see Fig. 9; , B is approximately 3 to 5 cm).
  • the signals responding to the electrodes were input to an oscilloscope for biological signal analysis (Nihon Kohden Memory Oscilloscope VC-11) and A / D converted.
  • FFT analysis of the signal wave was performed, and time series analysis was performed for each frequency of the FFT peak value for normal and breast cancer up to 170 Hz. In this case, if the normal person is the same as breast cancer, analyze the same FFT peak value or the peak value near it and compare the normal and cancer did.
  • Group A 70-80% A 'group, 50-70% B group, 20-40% B 'Group, only one case was classified into Group C.
  • each group is extracted as a group with one feature in the frequency range of 10 to 17 Hz, and this is connected to a line to form a group. .. '688 ⁇ 016 899 ⁇ 606 06-900 ⁇ 906
  • Table 3 shows the relationship between each tissue image and the common frequency for each tissue image of ductal carcinoma.
  • Ductal carcinoma is invasive cancer in which cancer cells have invaded the stroma.
  • ductal carcinoma Histological features of ductal carcinoma were classified into papillary ductal carcinoma, solid ductal carcinoma and hard carcinoma
  • Papillary duct carcinoma (Papi 1 lotubular carcinoma)
  • Solid cancerous nests are those that show exclusion or swelling growth to surrounding tissues.
  • Cancer foci consist of solid growth of medullary or obscure small ducts in the glandular cavities. Demonstrates relatively clear boundaries to surrounding tissues almost all around the cancerous lesion
  • Hard cancer includes two from its origin. One is a narrowly defined hard carcinoma with extremely few intraductal carcinoma foci and advanced interstitial invasion, and the other is derived from papillary duct carcinoma or solid ductal carcinoma and has diffuse interstitial invasion. Predominate II
  • the common frequency in each histological image in the table is the frequency (A group) that appears in common with a probability of 80% or more in cases.
  • the number shown at the right end of the table is the common frequency probability (%) with respect to the number of cases.
  • Hard cancer has a high probability of commonality due to few cases, and has many common frequencies. However, the probability of commonality decreases as the number of cases increases.
  • time series analysis and autocorrelation analysis of signal waveforms were performed for each extracted common frequency to further prove the reliability of the common frequency of each breast cancer site and each tissue image shown in the table and figure. In comparison, we searched for differences from normal.
  • Fig.4 Area of burst signals in the 9.766Hz time series of left (L) and ri ht () up and out breasts in B-cancer and women
  • the signal processing device of the present invention includes a pair of electrodes 1 for detecting an electric signal from a living body, an amplifier 2 for amplifying the electric signal obtained at the electrode 1, a Fourier transform of the amplifier output to a specific frequency, A specific frequency component detection circuit 3 for detecting a signal of a component (mainly a frequency of '10 Hz or less), and integrates the output of the detection circuit up to a predetermined time (for example, FIG.
  • the value of POWER on the vertical axis is integrated with respect to the time from 0.000 msec on the left end of the horizontal axis to 466 7 2.000 msec on the right end.)
  • the combination configuration of the comparison circuit 7 for comparing and outputting the data of the comparison result is an example. Wear. Needless to say, these circuits may be configured in the form of software that can realize the functions by a computer.
  • the above configuration is only an example, and a specific frequency
  • the time-series change of the turn is displayed on the monitor, and it can be used as an auxiliary means for the doctor's diagnosis.
  • the starting frequency of this retraction is between 10 and 32 Hz for both normal and breast cancer as shown in Fig. 4, but it is often between 10 and 26 Hz for normal and for breast cancer.
  • Frequency attraction is a self-regulatory mechanism required for cell stabilization.
  • Spike (twin-spike) vibration appears between 30 and 7 OHz.
  • Fig. 4 Spike vibration includes transient spike (Transient) and twin-spike (Bisp.). Except for transient spikes at 60 to 70 years of age, bilateral spikes appear in both left (L) and right (R) cancers in most age groups.
  • Estrogen (ES) -ES receptor (ER) binds to R0CC and D0CC in these Ca "ch. And mobilizes Ca2 + from the endoplasmic reticulum, and the (Ca2 + ) i Are reported to activate MAPK to form a cascade of —transcriptional activity—nuclear gene activation.From these literature reports and the results of this study, burst oscillations in the 9.766 Hz time series described above (item III) are reported. Explaining the difference between the normal (B0S) area and breast cancer, ES-binding protein decreases and blood free estrogen (f-ES) increases after menopause (after age 45) in breast cancer and normal subjects.
  • f-ES blood free estrogen
  • f-ES Since f-ES has a small molecular weight, it can freely pass through cells, enter the cytoplasm, and bind to the tpsi.
  • B0S time-series burst oscillation

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  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Surgery (AREA)
  • Public Health (AREA)
  • Biomedical Technology (AREA)
  • Heart & Thoracic Surgery (AREA)
  • Medical Informatics (AREA)
  • Molecular Biology (AREA)
  • Biophysics (AREA)
  • Animal Behavior & Ethology (AREA)
  • General Health & Medical Sciences (AREA)
  • Pathology (AREA)
  • Veterinary Medicine (AREA)
  • Mathematical Physics (AREA)
  • Artificial Intelligence (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Physiology (AREA)
  • Psychiatry (AREA)
  • Signal Processing (AREA)
  • Investigating Or Analysing Biological Materials (AREA)
  • Measurement And Recording Of Electrical Phenomena And Electrical Characteristics Of The Living Body (AREA)

Abstract

Selon l'invention, on obtient une information sur la présence d'un cancer par production de signaux en série chronologique, durant une période prédéterminée des signaux, d'une zone de fréquence spécifique d'un signal en temps réel d'une surface corporelle, et par détermination de l'aire des signaux en série chronologique.
PCT/JP2001/010253 2000-11-22 2001-11-22 Relation entre cancer du sein et oestrogene par signal de surface corporelle en temps reel WO2002045581A1 (fr)

Priority Applications (1)

Application Number Priority Date Filing Date Title
JP2002547375A JPWO2002045581A1 (ja) 2000-11-22 2001-11-22 体表面リアルタイム信号による乳癌とエストロゲンの関係

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JP2000-356496 2000-11-22
JP2000356496 2000-11-22

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Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPS573623A (en) * 1980-06-10 1982-01-09 Tokyo Shibaura Electric Co Apparatus for detecting abnormal cell
JPS5772627A (en) * 1980-10-21 1982-05-07 Tokyo Shibaura Electric Co Apparatus for detecting abnormal cell
JPS61122851A (ja) * 1984-09-26 1986-06-10 サウスウエスト・リサ−チ・インステイチユ−ト 乳房の非侵入テストを行なうための方法と装置
JPS63158462A (ja) * 1986-09-29 1988-07-01 ベイラー　カレッジ　オブ　メディシン エストロゲン受容蛋白定量のための尿素誘導体ｄｎａ結合検査法

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPS573623A (en) * 1980-06-10 1982-01-09 Tokyo Shibaura Electric Co Apparatus for detecting abnormal cell
JPS5772627A (en) * 1980-10-21 1982-05-07 Tokyo Shibaura Electric Co Apparatus for detecting abnormal cell
JPS61122851A (ja) * 1984-09-26 1986-06-10 サウスウエスト・リサ−チ・インステイチユ−ト 乳房の非侵入テストを行なうための方法と装置
JPS63158462A (ja) * 1986-09-29 1988-07-01 ベイラー　カレッジ　オブ　メディシン エストロゲン受容蛋白定量のための尿素誘導体ｄｎａ結合検査法

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