System and method for automatic trigger-ROI detection and monitoring during bolus tracking

• US 9,414,798 B2
• Filed: 03/23/2010
• Issued: 08/16/2016
• Est. Priority Date: 03/25/2009
• Status: Active Grant

• Current Assignee: Siemens Healthineers AG (Siemens AG)
• Original Assignee: Siemens AG, Siemens Medical Solutions USA Incorporated (Siemens AG)
• Inventors: Feuerlein, Ute, Krishnan, Arun, Zhou, Xiang Sean
• Primary Examiner(s): TURCHEN, ROCHELLE DEANNA
• Application Number:
  US12/729,274
• Publication Number:
  US 20100249582A1
• Time in Patent Office: 2,338 Days
• Field of Search: 600/407, 600/420
• US Class Current: 1/1
• CPC Class Codes: A61B 5/7285 for synchronising or triggering a physiological measurement or image acquisition with a physiological event or waveform, e.g. an ECG signal A61B6/5205, A61B6/541, A61B8/5207, A61B8/543 take precedence
• CPC Class Codes: A61B 6/032 Transmission computed tomography [CT]
• CPC Class Codes: A61B 6/469 for selecting a region of interest [ROI]
• CPC Class Codes: A61B 6/481 involving the use of contrast agents
• CPC Class Codes: A61B 6/488 involving pre-scan acquisition
• CPC Class Codes: A61B 6/504 for diagnosis of blood vessels, e.g. by angiography
• CPC Class Codes: A61B 6/541 involving acquisition triggered by a physiological signal

Abstract

A method for bolus tracking includes acquiring one or more baseline images. One or more trigger regions are automatically established within the baseline images. A bolus is administered. The automatically established trigger regions are monitored for bolus arrival at the one or more trigger regions. Bolus arrival at a volume of interest is forecasted based on the bolus arrival at the one or more trigger regions. A diagnostic scan of the volume of interest is acquired at the forecasted time.

Claims

1. A method for bolus tracking, comprising:

acquiring one or more baseline images;

automatically establishing trigger regions within each of the one or more baseline images by determining an anatomical context of a volume of interest and automatically cross-referencing the anatomical context to the trigger regions;

administering a bolus;

monitoring the automatically established trigger regions for bolus arrival at the trigger regions;

forecasting first and second bolus arrival times at the volume of interest based on the bolus arrival at first and second of the trigger regions;

automatically calculating first and second confidence scores corresponding to the first and second of the trigger regions, wherein each of the first and second confidence scores represents a level of certainty associated with an ability of a corresponding trigger region to accurately predict the bolus arrival within the volume of interest based on identification of the bolus within the corresponding trigger region;

forecasting a third bolus arrival time at the volume of interest based on an average of the first and second bolus arrival times weighted in proportion to the confidence scores; and

acquiring a diagnostic scan of the volume of interest at the forecasted third bolus arrival time.

2. The method of claim 1, wherein acquisition of the baseline images comprises:

acquiring a scout image;

automatically detecting a monitoring line within the scout image; and

acquiring the one or more baseline images at an image slice determined by the location of the automatically detected monitoring line within the scout image.

3. The method of claim 1, wherein automatic establishment of the trigger regions within the one or more baseline images includes automatically determining a shape, size, and location of the trigger regions.

4. The method of claim 1, wherein automatic establishment of the trigger regions within the one or more baseline images includes automatically determining the anatomical context by detecting one or more landmarks within the one or more baseline images.

5. The method of claim 4, wherein automatic establishment of the trigger regions within the one or more baseline images includes locating each of the trigger regions inside blood vessels and labeling each of the trigger regions to be indicative of a corresponding anatomical location.

6. The method of claim 5 wherein locating each of the trigger regions inside the blood vessels includes locating each of the trigger regions inside an ascending aorta, aortic arch, descending aorta, abdominal aorta, internal carotid artery, or external carotid artery.

7. The method of claim 1, wherein monitoring the automatically established trigger regions for bolus arrival at the trigger regions includes performing motion compensation to correct for patient motion, respiratory motion, or cardiac motion within the one or more baseline images.

8. The method of claim 7, wherein motion compensation includes repositioning one or more of the trigger regions.

9. The method of claim 1, wherein acquiring the one or more baseline images includes acquiring one or more low-dose CT images, wherein administering the bolus includes administering a radio-opaque contrast medium, and wherein acquiring the diagnostic scan includes acquiring a high-resolution CT scan.

10. The method of claim 1, further comprising automatically selecting an injection site for administering the bolus.

11. The method of claim 1, further comprising automatically identifying one or more anatomical landmarks within the baseline image, and wherein monitoring the automatically established trigger regions for bolus arrival at the trigger regions includes tracking the trigger regions and the anatomical landmarks and registering the trigger regions to an anatomical coordinate system referencing the tracked anatomical landmarks, wherein two of the one or more baseline images are registered to the anatomical coordinate system.

12. The method of claim 11, wherein tracking of the trigger regions relative to the anatomical coordinate system includes changing one or more of the trigger regions in shape, location or size, over time.

13. The method of claim 1, wherein monitoring the automatically established trigger regions for bolus arrival at the trigger regions includes recording image intensity statistics at each of the trigger regions over time, and jointly using the trigger regions and the image intensity statistics to forecast the bolus arrival at the volume of interest.

14. The method of claim 13, wherein recording image intensity statistics at each of the trigger regions over time includes recording a maximal, median, average intensity, or k-th bolus arrival where arrival is defined as an increase of image intensity above a set threshold and k is a predetermined or selected positive integer.

15. The method of claim 1, wherein automatically calculating the first and second confidence scores comprises performing machine learning that keeps track of how often the corresponding trigger region is able to accurately forecast the bolus arrival.

16. The method of claim 15, further comprising automatically and continuously updating the confidence scores of the trigger regions.

17. The method of claim 1, wherein the first trigger region is the trigger region where the bolus first arrives and the second trigger region is the trigger region where the bolus last arrives.

18. The method of claim 1, wherein automatically calculating the first and second confidence scores comprises calculating a pre-determined formula.

19. The method of claim 1, wherein automatically cross-referencing the anatomical context of the volume of interest to the trigger regions includes using a lookup table to cross-reference an anatomical description of the volume of interest to the trigger regions.

20. A method for bolus tracking, comprising:

acquiring a scout image;

automatically detecting a monitoring line within the scout image;

acquiring a baseline image at a location determined by the location of the automatically detected monitoring line within the scout image;

automatically establishing a plurality of trigger regions within the baseline image by determining an anatomical context of a volume of interest and automatically cross-referencing the anatomical context to the trigger regions;

administering a bolus;

monitoring the automatically established trigger regions for bolus arrival at the trigger regions;

forecasting first and second bolus arrival times at the volume of interest based on the bolus arrival at first and second of the trigger regions, and forecasting a third bolus arrival time at the volume of interest based on an average of the first and second bolus arrival times weighted in proportion to confidence scores corresponding to the first and second trigger regions, wherein each of the confidence scores represents a level of certainty associated with an ability of a corresponding trigger region to accurately predict the bolus arrival within the volume of interest based on identification of the bolus within the corresponding trigger region; and

acquiring a diagnostic scan of the volume of interest at the forecasted third bolus arrival time.

21. The method of claim 20, further comprising automatically assigning each of the trigger regions a confidence score.

22. The method of claim 20, wherein monitoring the automatically established trigger regions for bolus arrival at the trigger regions includes performing motion compensation to correct for patient motion within the baseline image, the motion compensation including repositioning one or more of the trigger regions.

23. A computer system comprising:

a processor; and

a non-transitory storage medium, readable by the computer system, embodying a program of instructions executable by the processor to perform method steps for bolus tracking, the method comprising;

acquiring a scout image;

automatically detecting a monitoring line within the scout image;

acquiring a baseline image at a location determined by the location of the automatically detected monitoring line within the scout image;

automatically establishing trigger regions within the baseline image by determining an anatomical context of a volume of interest and automatically cross-referencing the anatomical context to the trigger regions;

administering a bolus;

monitoring the automatically established trigger regions for bolus arrival at the trigger regions;

forecasting first and second bolus arrival times at the volume of interest based on the bolus arrival at first and second of the trigger regions, and forecasting a third bolus arrival time at the volume of interest based on an average of the first and second bolus arrival times weighted in proportion to confidence scores corresponding to the first and second trigger regions, wherein each of the confidence scores represents a level of certainty associated with an ability of a corresponding trigger region to accurately predict the bolus arrival within the volume of interest based on identification of the bolus within the corresponding trigger region; and

acquiring a diagnostic scan of the volume of interest at the forecasted third bolus arrival time.

24. The computer system of claim 23, wherein monitoring the automatically established trigger regions for bolus arrival at the trigger regions includes performing motion compensation to correct for patient motion within the baseline image.

25. The computer system of claim 23, further comprising automatically identifying one or more anatomical landmarks within the baseline image and monitoring the automatically established trigger regions for bolus arrival at the trigger regions includes tracking the trigger regions and the anatomical landmarks and registering the trigger regions to an anatomical coordinate system referencing the tracked anatomical landmarks.

26. The computer system of claim 23, further comprising automatically assigning each of the trigger regions a confidence score.