Methods for generating a lung report

• US 6,901,277 B2
• Filed: 07/17/2001
• Issued: 05/31/2005
• Est. Priority Date: 07/17/2001
• Status: Expired due to Term

• Current Assignee: Merative US LP
• Original Assignee: AccuImage Diagnostics Corp. (International Business Machines Corporation)
• Inventors: Kaufman, Leon, Powers, Shelley, Goldhaber, David, Mineyev, Mikhail
• Primary Examiner(s): Casler, Brian L.
• Assistant Examiner(s): Jung, William C
• Application Number:
  US09/908,466
• Publication Number:
  US 20030018245A1
• Time in Patent Office: 1,414 Days
• Field of Search: 600/407, 600/425, 600/408, 600/410, 383/130, 383/131, 128/922, 382/130, 382/131
• US Class Current: 600/407
• CPC Class Codes: A61B 5/055 involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
• CPC Class Codes: A61B 5/411 Detecting or monitoring allergy or intolerance reactions to an allergenic agent or substance
• CPC Class Codes: A61B 5/7289 Retrospective gating, i.e. associating measured signals or images with a physiological event after the actual measurement or image acquisition, e.g. by simultaneously recording an additional physiological signal during the measurement or image acquisition
• CPC Class Codes: A61B 5/7292 Prospective gating, i.e. predicting the occurrence of a physiological event for use as a synchronisation signal
• CPC Class Codes: A61B 6/00 Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment instruments measuring radiation intensity for application in the field of nuclear medicine, e.g. in vivo counting, G01T1/161; apparatus for taking X-ray photographs G03B42/02
• CPC Class Codes: A61B 6/463 characterised by displaying multiple images or images and diagnostic data on one display
• CPC Class Codes: A61B 6/5288 involving retrospective matching to a physiological signal
• CPC Class Codes: A61B 6/541 involving acquisition triggered by a physiological signal
• CPC Class Codes: Y10S 128/922 including image analysis

Abstract

Software, methods and user interfaces for viewing and generating a lung report. In exemplary methods, a first baseline image is analyzed to localize lung nodules. The lung nodule information can be stored and used to relocate the previously localized lung nodules in a second, follow-up imaging scan. The follow-up scan can be analyzed—either manually or automatically—to generate statistics for the lung nodules localized in the follow-up scan. Information derived from the baseline scan can be used to ease the localization of the lung nodules in the follow-up scan. In some exemplary methods, both the baseline scan and follow-up scan are displayed and the nodules are selected for comparison. Typically, the graphical user interface can display a third, composite image that displays the change of size of the nodules.

Claims

1. A method of analyzing lung nodules in a body slice image and generating a patient report, the method comprising:

providing patient information;

displaying a first image along a body slice taken at t₁;

displaying a second image along the body slice taken at t₂;

localizing lung nodules in the first image and second image;

registering the first image with the second image so that lung nodules in the first image are substantially registered with corresponding lung nodules in the second image;

comparing the lung nodules in the first image with the lung nodules in the second image; and

generating the patient report using a decision tree or a set of logic steps that combines patient information, and the comparison of selected parameters of the lung nodules and the number of lung nodules in the first image and the second image.

2. The method of claim 1 wherein registering comprises automatically registering the first image and second image, wherein the comparing identifies changes in the parameters of the lung nodules and the number of lung nodules.

3. The method of claim 1 wherein registering comprises manually panning at least one of the first and second images to align the first image with the second image, wherein the comparing identifies changes in the parameters of the nodules and the number of lung nodules.

4. The method of claim 1 wherein registering comprises automatically or semi-automatically panning at least one of the first and second images to register the first image with the second image, wherein the comparing identifies changes in the parameters of the nodules and the number of lung nodules.

5. The method of claim 4 wherein registering comprises automatically correcting for differences at acquisition in spatial parameters prior to panning at least one of the first and second images to align the first image with the second image.

6. The method of claim 1 wherein comparing comprises computing a third image which is a subtraction of the first image and second image.

7. The method of claim 1 wherein comparing comprises computing a third image which is an absolute difference of the first image and second image.

8. The method of claim 1 wherein comparing comprises computing a third image which is a sum of the first image and second image.

9. The method of claim 1 wherein registering comprises matching the lung nodules in the first image and second image, wherein matching comprises demanding that at least one voxel be overlapped.

10. The method of claim 1 wherein registering comprises matching the nodule in the first image and second image, wherein matching comprises demanding that the edges of the lung nodule be no more than a fixed number of pixels apart.

11. The method of claim 10 wherein nodule in the first image and second image are matched by demanding that the edges of the lung nodule be no more than one pixel apart.

12. The method of claim 10 wherein nodules are matched by demanding that the edges of the lung nodule be no more than three pixels apart.

13. The method of claim 1 wherein localizing further comprising logging at least one of the lung nodule number, anatomic position, volume, surface area, roundness, density and standard deviation, major and minor axes of the lung nodule.

14. The method of claim 13 wherein density comprises HU in x-ray CT.

15. The method of claim 13 where density comprises signal intensity in MRI.

16. The method of claim 1 wherein comparing comprises calculating at least one of a change in size volume, surface area, roundness, density and standard deviation, major and minor axes of the nodule.

17. The method of claim 1, further comprising illustrating the lung nodule(s) in the first image in a first color and the lung nodule(s) in the second image in a second color.

18. The method of claim 1 further comprising removing surrounding tissues or organs from the first and second images.

19. The method of claim 18 wherein removing comprises filtering a range of HU values.

20. The method of claim 1 wherein the first and second images are MRI images or CT images.

21. The method of claim 1 further comprising selecting a viewing plane of at least one of the first image and second image.

22. The method of claim 21 wherein selecting a viewing plane comprises an axial plane, sagittal plane, coronal plane, or an oblique plane.

23. The method of claim 1 wherein generating the patient report comprises posting the report on a secure website.

24. The method of claim 1 wherein generating the patient report comprises electronically transmitting the report to a patient'"'"'s physician or a patient.

25. The method of claim 1 wherein generating the patient report comprises saving the report on an electronic media or printing a report with a printer.

26. The method of claim 1 wherein the patient report comprises at least one of patient data, number of lung nodules, nodule parameters, recommendations, images, and risk information.

27. The method of claim 1 further comprising marking the lung nodules in at least one of the first image and second image.

28. The method of claim 27 wherein marking comprises displaying a marker, changing the intensity of the lung nodule, or changing the color of the lung nodule.

29. A method of generating a customized lung nodule patient report, the method comprising:

storing patient information in a memory;

providing a first image along a body slice taken at t₁;

localizing lung nodules in the first image;

measuring a plurality of parameters about the lung nodules in the first image;

measuring the number of lung nodules in the first image;

inputting customization selections into a decision tree or a set of logic steps so as to combine selected patient information with selected parameters of the lung nodules and the number of nodules to generate a customized patient report.

30. The method of claim 29 further providing physician recommendations based on of the measured parameters of the lung nodule in the first image and the number of nodules in the first image, wherein the customized patient report selections includes the physician recommendations.

31. The method of claim 29 wherein the decision tree or set of logic steps generates a risk ranking for selected parameters of the lung nodules.

32. The method of claim 29 wherein measuring the plurality of parameters comprises measuring at least one of the anatomic position, volume, surface area, roundness, density and standard deviation, major and minor axes of the lung nodule.

33. The method of claim 29 further comprising:

providing a second image along the body slice taken at t₂;

localizing lung nodules in the second image and registering the first image with the second image so that lung nodules in the first image are substantially registered with corresponding lung nodules in the second image;

measuring a plurality of parameters about the localized lung nodules in the second image;

comparing parameters of lung nodules in the first image with the lung nodules in the second image to determine a progression of the lung nodules;

storing the comparison of parameters in the memory; and

using the comparison of parameters to generate a recommendation in the customized patient report.

34. The method of claim 33 wherein registering comprises automatically registering the first image and second image.

35. The method of claim 33 wherein registering comprises manually panning at least one of the first and second images to align the first image with the second image.

36. The method of claim 33 wherein registering comprises automatically or semi-automatically panning at least one of the first and second images to register the first image with the second image.

37. The method of claim 36 wherein registering comprises automatically correcting for differences at acquisition in spatial parameters prior to panning at least e first and second images to align the first image with the second image.

38. The method of claim 33 wherein comparing comprises computing a third image which is a subtraction of the first image and second image.

39. The method of claim 33 wherein comparing comprises computing a third image which is an absolute difference of the first image and second image.

40. The method of claim 33 wherein comparing comprises computing a third image which is a sum of the first image an second image.

41. The method of claim 33 wherein registering comprises matching the nodule in the first image and second image, wherein matching comprises demanding that at least one voxel be overlapped.

42. The method of claim 33 wherein registering comprises matching the nodule in the first image and second image, wherein matching comprises demanding that the edges of the nodule be no more than a fixed number of pixels apart.

43. The method of claim 42 wherein nodule in the first image and second image are matched by demanding that the edges of the lesion be no more than one pixel apart.

44. The method of claim 43 wherein nodules are matched by demanding that the edges of the lesion be no more than three pixels apart.

45. The method of claim 43 wherein nodules are matched by manual input from an operator.

46. The method of claim 33 wherein comparing comprises calculating at least one of a change in volume, surface area, roundness, density and standard deviation, major and minor axes of the nodule.

47. The method of claim 33, further comprising illustrating the nodule(s) in the first image in a first color and the nodule(s) in the second image in a second color.

48. The method of claim 33 further comprising removing surrounding tissues or organs from the first and second images.

49. The method of claim 29 further comprising marking the nodules in at least one of the first image and second image.

50. The method of claim 49 wherein marking comprises displaying a marker, changing the intensity of the nodule, or changing the color of the nodule.