Methods and kits for assessing neurological and ophthalmic function and localizing neurological lesions

• US 10,610,165 B2
• Filed: 06/17/2014
• Issued: 04/07/2020
• Est. Priority Date: 06/17/2013
• Status: Active Grant

• Current Assignee: US Department of Veterans Affairs (Government of the United States of America), New York University
• Original Assignee: New York University
• Inventors: Samadani, Uzma
• Primary Examiner(s): Hindenburg, Max F
• Application Number:
  US14/392,310
• Publication Number:
  US 20160278716A1
• Time in Patent Office: 2,121 Days
• CPC Class Codes: A61B 3/0025 characterised by electronic signal processing, e.g. eye models
• CPC Class Codes: A61B 3/0041 characterised by display arrangements
• CPC Class Codes: A61B 3/085 for testing strabismus
• CPC Class Codes: A61B 3/113 for determining or recording eye movement
• CPC Class Codes: A61B 5/031 Intracranial pressure
• CPC Class Codes: A61B 5/4064 Evaluating the brain A61B5/031, A61B5/369, A61B5/14553 take precedence
• CPC Class Codes: A61B 5/7278 Artificial waveform generation or derivation, e.g. synthesising signals from measured signals A61B5/327 takes precedence

Abstract

The invention provides methods and kits for detecting, screening, quantifying or localizing the etiology for reduced or impaired cranial nerve function or conduction; localizing a central nervous system lesion; detecting, diagnosing or screening for increased intracranial pressure, pressure or disruption of central nervous system physiology as seen with concussion; or detecting, diagnosing, monitoring progression of or screening for a disease or condition featuring increased intracranial pressure or concussion by tracking eye movement of the subject.

Claims

1. A method for assessing or quantitating structural and non-structural traumatic brain injury in a subject comprising:

a) Tracking eye movement of at least one eye of the subject using a device suitable for tracking eye movement;

b) Analyzing eye movement of at least one eye of the subject using a computer in communication with the device suitable for tracking eye movement;

c) Comparing eye movement of a first eye of the subject to eye movement of a second eye of the subject; and

d) Calculating a standard deviation or p value for eye movement of at least one eye of the subject as compared to the normal or mean eye movement to thereby assess or quantitate structural and non-structural traumatic brain injury.

2. A method according to claim 1 wherein eye movement of both eyes of the subject are tracked and analyzed.

3. A method according to claim 1 wherein both x and y coordinates of eye position for one or both eyes of a subject are collected.

4. A method according to claim 1 wherein the eye movement is tracked for at least 100 or more seconds.

5. A method according to claim 1 wherein the tracking, analyzing and comparing comprises collecting raw x and y cartesian coordinates of pupil position, and normalizing the raw x and y cartesian coordinates.

6. A method according to claim 1 wherein the analyzing and comparing comprises calculating one or more individual metric selected from the group consisting of

L. var Ytop=Var(y_{1,average k=1:}

5,1) 

 

(13)

R. var Ytop=Var(y<sub>2,average k=1;

5,1</sub>) 

 

(14)

L. var Xrit=Var(x<sub>1,average k=1;

5,2</sub>) 

 

(15)

R. var Xrit=Var(x<sub>2,average k=1;

5,2</sub>) 

 

(16)

L. var Ybot=Var(y<sub>1,average k=1;

5,3</sub>) 

 

(17)

R. var Ybot=Var(y<sub>2,average k=1;

5,3</sub>) 

 

(18)

L. var Xlef=Var(x<sub>1,average k=1;

5,4</sub>) 

 

(19)

R. var Xlef=Var(x<sub>2,average k=1;

5,4</sub>) 

 

(20)

L. var Total=Average(Var(x<sub>1,average k=1;

5</sub>)=Var(y<sub>1,average k=1;

5</sub>)) 

 

(21)

R. var Total=Average(Var(x<sub>2,average k=1;

5</sub>)=Var(y<sub>2,average k=1;

5</sub>)) 

 

(22)

L.SkewTop=Skew(y<sub>1,average k=1;

5,1</sub>) 

 

(27)

R.SkewTop=Skew(y<sub>2,average k=1;

5,1</sub>) 

 

(28)

L.SkewRit=Skew(x<sub>1,average k=1;

5,2</sub>) 

 

(29)

R.SkewRit=Skew(x<sub>2,average k=1;

5,2</sub>) 

 

(30)

L.SkewBot=Skew(y<sub>1,average k=1;

5,3</sub>) 

 

(31)

R.SkewBot=Skew(y<sub>2,average k=1;

5,3</sub>) 

 

(32)

L.SkewLef=Skew(x<sub>1,average k=1;

5,4</sub>) 

 

(33)

R.SkewLef=Skew(x<sub>2,average k=1;

5,4</sub>) 

 

(34)

BoxHeight_j,k=y_j,k,1−

y_j,k,3 

 

(45)

BoxWidth_j,k=x_j,k,2−

x_j,k,4 

 

(46)

$\begin{array}{cc}{\mathrm{AspectRatio}}_{j,k}=\frac{{\mathrm{BoxHeight}}_{j,k}}{{\mathrm{BoxWidth}}_{j,k}}& \left(47\right)\end{array}$
BoxArea_j,k=BoxHeight_j,k×

BoxWidth_j,k 

 

(48)

7. A method according to claim 1 wherein wherein the analyzing and comparing comprises calculating one or more individual metric selected from the group consisting of L height, L width, L area, L var Xrit, L var Xlef, L var Total, R height, R width, R area, R var Ytop, R var Xrit, R var Xlef, R var Total, Conj var X, Conj var Xrit, Conj var Xbot, Conj var Xlef and Conj var Ylef.

8. A method according to claim 1 wherein the structural or non-structural traumatic brain injury is concussion or subconcussion.

9. A method for diagnosing a disease characterized by or featuring structural and non-structural traumatic brain injury in a subject comprising:

a) Tracking eye movement of at least one eye of the subject using a device suitable for tracking eye movement;

b) Analyzing eye movement of at least one eye of the subject using a computer in communication with the device suitable for tracking eye movement;

c) Comparing eye movement of a first eye of the subject to eye movement of a second eye of the subject; and

d) Calculating a standard deviation or p value for eye movement of at least one eye of the subject as compared to the normal or mean eye movement to thereby diagnose a disease characterized by or featuring structural and non-structural traumatic brain injury.

10. A method according to claim 9 wherein eye movement of both eyes of the subject are tracked and analyzed.

11. A method according to claim 9 wherein both x and y coordinates of eye position for one or both eyes of a subject are collected.

12. A method according to claim 9 wherein the eye movement is tracked for at least 100 or more seconds.

13. A method according to claim 9 wherein the tracking, analyzing and comparing comprises collecting raw x and y cartesian coordinates of pupil position, and normalizing the raw x and y cartesian coordinates.

14. A method according to claim 9 wherein the analyzing and comparing comprises calculating one or more individual metric selected from the group consisting of

L. var Ytop=Var(y_{1,average k=1:}

5,1) 

 

(13)

R. var Ytop=Var(y<sub>2,average k=1;

5,1</sub>) 

 

(14)

L. var Xrit=Var(x<sub>1,average k=1;

5,2</sub>) 

 

(15)

R. var Xrit=Var(x<sub>2,average k=1;

5,2</sub>) 

 

(16)

L. var Ybot=Var(y<sub>1,average k=1;

5,3</sub>) 

 

(17)

R. var Ybot=Var(y<sub>2,average k=1;

5,3</sub>) 

 

(18)

L. var Xlef=Var(x<sub>1,average k=1;

5,4</sub>) 

 

(19)

R. var Xlef=Var(x<sub>2,average k=1;

5,4</sub>) 

 

(20)

L. var Total=Average(Var(x<sub>1,average k=1;

5</sub>)=Var(y<sub>1,average k=1;

5</sub>)) 

 

(21)

R. var Total=Average(Var(x<sub>2,average k=1;

5</sub>)=Var(y<sub>2,average k=1;

5</sub>)) 

 

(22)

L.SkewTop=Skew(y<sub>1,average k=1;

5,1</sub>) 

 

(27)

R.SkewTop=Skew(y<sub>2,average k=1;

5,1</sub>) 

 

(28)

L.SkewRit=Skew(x<sub>1,average k=1;

5,2</sub>) 

 

(29)

R.SkewRit=Skew(x<sub>2,average k=1;

5,2</sub>) 

 

(30)

L.SkewBot=Skew(y<sub>1,average k=1;

5,3</sub>) 

 

(31)

R.SkewBot=Skew(y<sub>2,average k=1;

5,3</sub>) 

 

(32)

L.SkewLef=Skew(x<sub>1,average k=1;

5,4</sub>) 

 

(33)

R.SkewLef=Skew(x<sub>2,average k=1;

5,4</sub>) 

 

(34)

BoxHeight_j,k=y_j,k,1−

y_j,k,3 

 

(45)

BoxWidth_j,k=x_j,k,2−

x_j,k,4 

 

(46)

$\begin{array}{cc}{\mathrm{AspectRatio}}_{j,k}=\frac{{\mathrm{BoxHeight}}_{j,k}}{{\mathrm{BoxWidth}}_{j,k}}& \left(47\right)\end{array}$
BoxArea_j,k=BoxHeight_j,k×

BoxWidth_j,k 

 

(48)

15. A method according to claim 9 wherein wherein the analyzing and comparing comprises calculating one or more individual metric selected from the group consisting of L height, L width, L area, L var Xrit, L var Xlef, L var Total, R height, R width, R area, R var Ytop, R var Xrit, R var Xlef, R var Total, Conj var X, Conj var Xrit, Conj var Xbot, Conj var Xlef and Conj var Ylef.

16. A method according to claim 9 wherein the structural or non-structural traumatic brain injury is concussion or subconcussion.

17. A method for assessing or quantitating structural and non-structural traumatic brain injury or diagnosing a disease characterized by or featuring structural and non-structural traumatic brain injury in a subject comprising:

a) Tracking eye movement of at least one eye of the subject using a device suitable for tracking eye movement;

b) Collecting raw x and y cartesian coordinates of pupil position using a computer in communication with the device suitable for tracking eye movement;

c) Normalizing the raw x and y cartesian coordinates; and

d) Calculating one or more individual metric selected from the group consisting of L height, L width, L area, L var Xrit, L var Xlef, L var Total, R height, R width, R area, R var Ytop, R var Xrit, R var Xlef, R var Total, Conj var X, Conj var Xrit, Conj var Xbot, Conj var Xlef and Conj var Ylef,

L. var Ytop=Var(y<sub>1,average k=1;

5,1</sub>) 

 

(13)

R. var Ytop=Var(y<sub>2,average k=1;

5,1</sub>) 

 

(14)

L. var Xrit=Var(x<sub>1,average k=1;

5,2</sub>) 

 

(15)

R. var Xrit=Var(x<sub>2,average k=1;

5,2</sub>) 

 

(16)

L. var Ybot=Var(y<sub>1,average k=1;

5,3</sub>) 

 

(17)

R. var Ybot=Var(y<sub>2,average k=1;

5,3</sub>) 

 

(18)

L. var Xlef=Var(x<sub>1,average k=1;

5,4</sub>) 

 

(19)

R. var Xlef=Var(x<sub>2,average k=1;

5,4</sub>) 

 

(20)

L. var Total=Average(Var(x<sub>1,average k=1;

5</sub>)=Var(y<sub>1,average k=1;

5</sub>)) 

 

(21)

R. var Total=Average(Var(x<sub>2,average k=1;

5</sub>)=Var(y<sub>2,average k=1;

5</sub>)) 

 

(22)

L.SkewTop=Skew(y<sub>1,average k=1;

5,1</sub>) 

 

(27)

R.SkewTop=Skew(y<sub>2,average k=1;

5,1</sub>) 

 

(28)

L.SkewRit=Skew(x<sub>1,average k=1;

5,2</sub>) 

 

(29)

R.SkewRit=Skew(x<sub>2,average k=1;

5,2</sub>) 

 

(30)

L.SkewBot=Skew(y<sub>1,average k=1;

5,3</sub>) 

 

(31)

R.SkewBot=Skew(y<sub>2,average k=1;

5,3</sub>) 

 

(32)

L.SkewLef=Skew(x<sub>1,average k=1;

5,4</sub>) 

 

(33)

R.SkewLef=Skew(x<sub>2,average k=1;

5,4</sub>) 

 

(34)

BoxHeight_j,k=y_j,k,1−

y_j,k,3 

 

(45)

BoxWidth_j,k=x_j,k,2−

x_j,k,4 

 

(46)

$\begin{array}{cc}{\mathrm{AspectRatio}}_{j,k}=\frac{{\mathrm{BoxHeight}}_{j,k}}{{\mathrm{BoxWidth}}_{j,k}}& \left(47\right)\end{array}$
BoxArea_j,k=BoxHeight_j,k×

BoxWidth_j,k 

 

(48)

18. A method according to claim 17 wherein eye movement of both eyes of the subject are tracked and analyzed.

19. A method according to claim 17 wherein both x and y coordinates of pupil position for both eyes of the subject are collected.

20. A method according to claim 17 wherein the eye movement is tracked for at least 100 or more seconds.

21. A method according to claim 17 wherein the structural or non-structural traumatic brain injury is concussion or subconcussion.