Assessing Tumor Response to Therapy

• US 20090296998A1
• Filed: 05/30/2008
• Published: 12/03/2009
• Est. Priority Date: 05/30/2008
• Status: Active Grant

• Current Assignee: Emory University
• Original Assignee: Emory University
• Inventors: Pantalone, Paul, Crocker, Ian, Fox, Tim, Schreibmann, Eduard
• Granted Patent: US 8,965,071 B2
• Time in Patent Office: Days
• US Class Current: 382/128
• CPC Class Codes: A61B 6/037 Emission tomography
• CPC Class Codes: A61B 6/5217 extracting a diagnostic or physiological parameter from medical diagnostic data
• CPC Class Codes: G06T 2207/10081 Computed x-ray tomography [CT]
• CPC Class Codes: G06T 2207/10104 Positron emission tomography [PET]
• CPC Class Codes: G06T 2207/20104 Interactive definition of region of interest [ROI]
• CPC Class Codes: G06T 2207/30096 Tumor; Lesion
• CPC Class Codes: G06T 7/0016 involving temporal comparison
• CPC Class Codes: G06V 10/50 by performing operations within image blocks; by using histograms, e.g. histogram of oriented gradients [HoG]; by summing image-intensity values; Projection analysis
• CPC Class Codes: G16H 50/30 for calculating health indices; for individual health risk assessment

Abstract

Systems, methods and computer program products identify first biologic data in a region of interest in a first image and calculate a first biologic volume histogram from the first biologic data. Second biologic data in the same region of interest is identified in a second image and a second biologic volume histogram is calculated from the second biologic data. A difference in intensity for the region of interest is determined using the first biologic volume histogram and the second biologic volume histogram.

Claims

1. A method, comprising:

identifying first biologic data in a region of interest in a first image;

calculating a first biologic volume histogram from the first biologic data;

identifying second biologic data in the region of interest in a second image;

calculating a second biologic volume histogram from the second biologic data; and

determining a difference in intensity for the region of interest using the first biologic volume histogram and the second biologic volume histogram.

2. The method of claim 1, wherein the first biologic data comprises first metabolic distribution data, and wherein the second biologic data comprises second metabolic distribution data.

3. The method of claim 2, further comprising registering the first image and the second image.

4. The method of claim 3, wherein registering the first image and the second image comprises registering the first image and the second image using rigid registration.

5. The method of claim 3, wherein registering the first image and the second image comprises registering the first image and the second image using elastic or deformable registration.

6. The method of claim 1, wherein calculating a first biologic volume histogram comprises calculating a cumulative metabolic volume histogram.

7. The method of claim 1, wherein calculating a first biologic volume histogram comprises calculating a differential metabolic volume histogram.

8. The method of claim 1, further comprising identifying a plurality of volume elements within the region of interest.

9. The method of claim 8, wherein the plurality of volume elements comprise voxels.

10. The method of claim 8, further comprising calculating a metabolic intensity value from the first image at each of the plurality of volume elements.

11. The method of claim 8, further comprising calculating a metabolic intensity value from the first image at one of the voxels.

12. The method of claim 8, wherein calculating the first biologic volume histogram is based at least in part on the calculated intensity values for each of the plurality of volume elements.

13. The method of claim 1, wherein the first image comprises a PET image.

14. The method of claim 1, further comprising identifying a plurality of sub-regions of interest within the region of interest.

15. The method of claim 14, wherein identifying a plurality of sub-regions of interest further comprises identifying the plurality of sub-regions of interest based on a center of mass of the region of interest.

16. The method of claim 15, wherein identifying a plurality of sub-regions of interest further comprises identifying the plurality of sub-regions of interest by parsing the region of interest into sections separated by radial spokes sharing the center of mass as a termination point.

17. The method of claim 15, wherein identifying a plurality of sub-regions of interest further comprises identifying the plurality of sub-regions of interest by parsing the region of interest into one or more voxels.

18. The method of claim 14, wherein identifying first biologic data in the region of interest in a first image comprises identifying metabolic activity data from the first image in at least one of the plurality of sub-regions of interest.

19. The method of claim 18, wherein identifying second biologic data in the region of interest in a second image comprises identifying metabolic activity data from the second image in the at least one of the plurality of sub-regions.

20. The method of claim 19, further comprising comparing the first metabolic activity data and the second metabolic activity data.

21. The method of claim 20, wherein the first metabolic activity data and the second metabolic activity data comprise a metabolic volume histogram, a maximum SUV, or a minimum SUV.

22. The method of claim 20, further comprising identifying at least one location in the region of interest where the first metabolic activity data differs from the second metabolic activity data.

23. A computer program product, encoded on a computer-readable medium, operable to cause data processing apparatus to perform operations comprising:

identifying first biologic data in a region of interest in a first image;

calculating a first biologic volume histogram from the first biologic data;

identifying second biologic data in the region of interest in a second image;

calculating a second biologic volume histogram from the second biologic data; and

determining a difference in intensity for the region of interest using the first biologic volume histogram and the second biologic volume histogram.

24. The computer program product of claim 23, wherein the first biologic data comprises first metabolic distribution data, and wherein the second metabolic data comprises second metabolic distribution data.

25. The computer program product of claim 24, further operable to cause data processing apparatus to perform operations comprising registering the first image and the second image.

26. The computer program product of claim 25, wherein registering the first image and the second image comprises registering the first image and the second image using rigid registration.

27. The computer program product of claim 25, wherein registering the first image and the second image comprises registering the first image and the second image using elastic or deformable registration.

28. The computer program product of claim 23, wherein calculating a first biologic volume histogram comprises calculating a cumulative metabolic volume histogram.

29. The computer program product of claim 23, wherein calculating a first biologic volume histogram comprises calculating a differential metabolic volume histogram.

30. The computer program product of claim 23, further operable to cause data processing apparatus to perform operations comprising identifying a plurality of volume elements within the region of interest.

31. The computer program product of claim 30, wherein the plurality of volume elements comprise voxels.

32. The computer program product of claim 30, further operable to cause data processing apparatus to perform operations comprising calculating a metabolic intensity value from the first image at each of the plurality of volume elements.

33. The computer program product of claim 30, further operable to cause data processing apparatus to perform operations comprising calculating a metabolic intensity value from the first image at one of the voxels.

34. The computer program product of claim 30, wherein calculating the first biologic volume histogram is based at least in part on the calculated intensity values for each of the plurality of volume elements.

35. The computer program product of claim 23, wherein the first image comprises a PET image.

36. The computer program product of claim 23, further operable to cause data processing apparatus to perform operations comprising identifying a plurality of sub-regions of interest within the region of interest.