System and method for quantitative muscle ultrasound for diagnosis of neuromuscular disease

1. An ultrasound diagnostic system comprising an ultrasound imaging system, an ultrasound imaging phantom, and a diagnostic image processor,

the ultrasound imaging system configured to acquire an ultrasound image of a muscular region of interest of a patient and transmit the ultrasound image to the diagnostic image processor, the ultrasound image comprising a mean signal intensity;

the diagnostic image processor configured to:

receive a patient data set comprising:

the ultrasound image of the muscular region of interest of the patient;

a muscle region identifier of the muscular region of interest of the patient;

a subcutaneous tissue thickness and a muscle thickness of the muscular region of interest of the patient; and

at least one patient variable selected from the group consisting of an age of the patient, a weight of the patient, a height of the patient, and a sex of the patient;

determine a signal variance between the mean signal intensity and a normalized mean signal intensity and a thickness variance between the subcutaneous tissue thickness and a normalized subcutaneous tissue thickness, between the muscle thickness and a normalized muscle thickness, or between a sum of the muscle thickness and the subcutaneous tissue thickness and a sum of the normalized muscle thickness and the normalized subcutaneous tissue thickness;

categorize the muscular region of interest based on the signal variance, the thickness variance, or a combination thereof, wherein the normalized mean signal intensity, the normalized subcutaneous tissue thickness, and the normalized muscle thickness are selected based on the muscle region identifier and the one or more patient variables;

the ultrasound phantom comprising:

a gel having a calibration surface; and

a plurality of grey scale targets within the gel,

wherein a first grey scale target has a first mean echo intensity and is located at a first depth from the calibration surface, and

wherein a second grey scale target has a second mean echo intensity equal to the first mean echo intensity and is located at a second depth from the calibration surface, wherein the second depth is different than the first depth.

2. The system of claim 1 , wherein the muscle region identifier is a word or a number representing the muscular region of interest.

3. The system of claim 1 , wherein the subcutaneous tissue thickness or the muscle thickness of the muscular region of interest of the patient is measured by the ultrasound imaging system.

4. The system of claim 1 , wherein the at least one patient variable is at least two patient variables.

5. The system of claim 4 , wherein the at least two patient variables include the age of the patient and the weight of the patient, the height of the patient, or the sex of the patient.

6. The system of claim 1 , wherein the at least one patient variable is at least four patient variables, the at least four patient variables including the age of the patient, the weight of the patient, the height of the patient, and the sex of the patient.

7. The system of claim 1 , wherein the normalized mean signal intensity, the normalized subcutaneous thickness, or the normalized muscle thickness is calculated based on the muscle region identifier and the at least one patient variable.

8. The system of claim 1 , wherein the normalized mean signal intensity, the normalized subcutaneous thickness, or the normalized muscle thickness is calculated using a multiple linear regression model generated from data collected from a normalized control group of individuals that do not have a disease state of healthy individuals.

9. The system of claim 1 , wherein the diagnostic image processor is configured to categorize the muscular region of interest into at least a normal category and an abnormal category.

10. The system of claim 1 , wherein the gel has a sound velocity ranging from about 1400 m/s to about 1700 m/s.

11. The system of claim 1 , wherein the gel has a sound absorption ranging from about 0.3 dB/cm/MHz to about 1.0 dB/cm/MHz.

12. The system of claim 1 , wherein the first mean echo intensity is at least about +18 dB.

13. The system of claim 1 , wherein the first and second grey scale targets each have at least one physical dimension ranging from about 0.1 mm to about 5.0 mm.

14. The system of claim 1 , wherein the first and second depth are from about 0.1 cm to about 10.0 cm.

15. A method of diagnosing neuromuscular disease in a patient suspected of having a neuromuscular disease using a diagnostic image processor, the method comprising:

receiving, at the diagnostic image processor, a patient data set comprising:

an ultrasound image of a muscular region of interest of the patient, the ultrasound image comprising a mean signal intensity;

a muscle region identifier of the muscular region of interest of the patient;

a subcutaneous tissue thickness and a muscle thickness of the muscular region of interest of the patient; and

at least one patient variable selected from the group consisting of an age of the patient, a weight of the patient, a height of the patient, and a sex of the patient;

determining, using the diagnostic image processor, a signal variance between the mean signal intensity and a normalized mean signal intensity and a thickness variance between the subcutaneous tissue thickness and a normalized subcutaneous tissue thickness, between the muscle thickness and a normalized muscle thickness, or between a sum of the muscle thickness and the subcutaneous tissue thickness and a sum of the normalized muscle thickness and the normalized subcutaneous tissue thickness; and

categorizing, using the diagnostic image processor, the muscular region of interest based on the signal variance, the thickness variance, or a combination thereof,

wherein the normalized mean signal intensity, the normalized subcutaneous tissue thickness, and the normalized muscle thickness are selected based on the muscle region identifier and the at least one patient variable.

16. The method of claim 15 , wherein the muscle region identifier is a word or a number representing the muscular region of interest.

17. The method of claim 15 , wherein the at least one patient variable is at least two patient variables.

18. The method of claim 17 , wherein the at least two patient variable include the age of the patient and the weight of the patient, the height of the patient, or the sex of the patient.

19. The method of claim 15 , wherein the at least one patient variable is at least four patient variables, the at least four patient variables including the age of the patient, the weight of the patient, the height of the patient, and the sex of the patient.

20. The method of claim 15 , wherein a first and second grey scale targets each have at least one physical dimension ranging from about 0.1 mm to about 5.0 mm.

21. The method of claim 15 , wherein the normalized mean signal intensity, the normalized subcutaneous thickness, or the normalized muscle thickness is calculated using a multiple linear regression model generated from data collected from a normalized control group of individuals that do not have a disease state of healthy individuals.

22. The method of claim 15 , wherein categorizing the muscular region of interest includes categorizing the muscular region of interest into at least a normal category and an abnormal category.

23. An ultrasound imaging phantom comprising:

a gel having a calibration surface, the gel comprising a sound velocity ranging from about 1400 m/s to about 1700 m/s and a sound absorption ranging from about 0.3 dB/cm/MHz to about 1.0 dB/cm/MHz; and

a plurality of grey scale targets within the gel,

wherein a first grey scale target has a mean echo intensity of at least about +18 dB and is located at a first depth from the calibration surface,

wherein a second grey scale target has a mean echo intensity equal to the first grey scale target and is located at a second depth from the calibration surface, wherein the second depth is different than the first depth,

wherein the first and second grey scale targets each have at least one physical dimension ranging from about 0.1 mm to about 5.0 mm, and

wherein the first and second depths are from about 0.1 cm to about 10.0 cm.