Ultrasonic doppler diagnostic system using pattern recognition

• US 4,770,184 A
• Filed: 12/17/1985
• Issued: 09/13/1988
• Est. Priority Date: 12/17/1985
• Status: Expired due to Fees

• Current Assignee: Washington Research Foundation (University of Washington)
• Original Assignee: Washington Research Foundation (University of Washington)
• Inventors: Greene, Francis M. Jr., Strandness, Donald E. Jr.
• Primary Examiner(s): Jaworski, Francis J.
• Application Number:
  US06/810,872
• Time in Patent Office: 1,001 Days
• Field of Search: 128/663, 73/861.25, 364/417
• US Class Current: 600/454
• CPC Class Codes: A61B 5/02007 Evaluating blood vessel condition, e.g. elasticity, compliance
• CPC Class Codes: A61B 5/7232 involving compression of the physiological signal, e.g. to extend the signal recording period
• CPC Class Codes: A61B 5/7257 using Fourier transforms
• CPC Class Codes: A61B 5/7264 Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems neural networks per se G06N3/00; expert systems per se G06N5/00
• CPC Class Codes: A61B 8/06 Measuring blood flow measuring volume flow in general G01F, e.g. G01F1/66, G01F1/72; measuring speed of fluids in general G01P5/00
• CPC Class Codes: A61B 8/488 involving Doppler signals
• CPC Class Codes: G16H 15/00 ICT specially adapted for medical reports, e.g. generation or transmission thereof
• CPC Class Codes: Y02A 90/10 Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation

Abstract

A frequency-analyzed signal from a pulsed Doppler ultrasound examination is processed in a dedicated computer using statistical pattern recognition to assess the presence and extent of arterial disease. The Doppler blood flow signal is derived from a suitable utlrasound scanner, is frequency analyzed with a real-time, fast Fourier Transformer spectrum analyzer, and is processed by the computer to achieve a diagnosis of the degree of stenosis of the carotid artery through pattern recognition between the Doppler signal and a database of known preclassified spectra. The diagnosis ordinarily follows a hierarchical decision making format to objectively classify the condition of the patient.

Claims

1. A noninvasive method for diagnosing the degree of vessel stenosis in a patient comprising the steps of:

(a) comparing patient blood flow data, based upon time domain and frequency domain ultrasound Doppler shift information obtained at a Doppler angle θ

defined with respect to the patient'"'"'s common and internal carotid arteries, with corresponding reference blood flow data, characteristic of a test group of people whose common and internal carotid arteries have been independently evaluated for stenosis, the blood flow having characteristic regions designated systole, diastole, early diastole, late distole, and dicrotic notch, the patient blood flow data and corresponding reference blood flow data being compared defining a first set that includes information indicative of;

(1) the logarithm of the product of the reciprocal of cos θ and

the mean blood flow in the common carotid artery during early diastole;

(2) the reciprocal of cos θ

multiplied by the change in the blood flow frequency in the common carotid artery after systole, the product of which is raised to the fourth power;

(3) the logarithm of the mode blood flow frequency in the internal carotid artery;

(4) the minimum point on a signal contour, which is separated by approximately 9 dB from a contour representing the mode blood flow frequency in the internal carotid artery, raised to the fourth power; and

(5) the logarithm of the product of the reciprocal of cos θ and

the mean blood flow in the common carotid artery during later diastole; and

(b) producing a diagnosis output, the diagnosis output indicating a diseased condition when the patient blood flow data and corresponding reference blood flow data have a first relationship and indicating a normal condition when the patient blood flow data and corresponding reference blood flow data have a second relationship.

2. The method of claim 1, wherein the patient blood flow data and corresponding reference blood flow data being compared further define a second set including information indicative of:

(a) the peak point on a signal contour, which is separated by approximately 9 dB from a contour representing the mode blood flow frequency in the internal carotid artery, raised to the second power;

(b) the maximum frequency, between approximately ±

50 msec of the systolic peak, on a signal contour that is approximately 9 dB below a contour representing the mode blood flow frequency in the internal carotid artery, raised to the fourth power;

(c) the reciprocal of cos θ

multiplied by the change in blood flow frequency in the internal carotid artery after systole;

(d) the logarithm of the first minimum of the blood flow frequency in the internal carotid artery; and

(e) the width of a signal contour that is approximately 9 dB above a contour representing the mode blood flow frequency in the internal carotid artery approximately 50 msec after systole, raised to the fourth power; and

wherein the diagnostic output further indicates a greater than 50 percent stenosis condition when the second set of patient blood flow data has a third relationship to the second set of reference blood flow data and indicates a less than 50 percent stenosis condition when the second set of patient blood flow data has a fourth relationship to the second set of reference blood flow data.

3. The method of claim 2, wherein the patient blood flow data and corresponding reference blood flow data being compared further define a third set including information indicative of:

(a) the peak point on a signal contour that is separated by approximately 9 dB from a contour representing the mode blood flow frequency in the internal carotid artery;

(b) the logarithm of the blood flow frequency in the common carotid artery approximately 125 msec before the dichnotic notch;

(c) the logarithm of the product of the reciprocal of cos θ and

the change in the blood flow frequency in the internal carotid artery at systole; and

(d) the logarithm of a signal contour that is approximately 9 dB below a contour representing the mode blood flow frequency in the internal carotid artery; and

wherein the diagnostic output further indicates a greater than 35 percent stenosis condition when the third set of patient blood flow data has a fifth relationship to the third set of reference blood flow data and less than 35 percent stenosis condition when the third set of patient blood flow data has a sixth relationship to the third set of reference blood flow data.

4. The method of claim 3, wherein the patient blood flow data and corresponding reference blood flow data being compared each further define a fourth set including:

(a) the logarithm of the area under a blood flow frequency curve for an interval of approximately ±

37.5 msec around systole in the common carotid artery;

(b) the logarithm of the peak point on a signal contour that is separated by approximately 9 dB from a contour representing the mode blood flow frequency in the internal carotid artery;

(c) the peak point on a signal contour that is separated by approximately 9 dB from a contour representing the mode blood flow frequency in the internal carotid artery;

(d) the width of a signal contour that is approximately 9 dB above a contour representing the mode blood flow frequency in the common carotid artery approximately 125 msec after distole; and

(e) the logarithm of the width of a signal contour that is approximately 3 dB below a contour representing the mode blood flow frequency in the internal carotid artery approximately 125 msec after diastole; and

wherein, the diagnostic output further indicates a greater than 15 percent stenosis condition when the fourth set of patient blood flow data has a seventh relationship to the fourth set of reference blood flow data and has a less than 15 percent stenosis condition when the fourth set of patient blood flow data has an eighth relationship to the fourth set of reference blood flow data.