System and method for monitoring disease progression or response to therapy using multi-modal visualization

1. A method for multi-modal visualization, comprising:

selecting a first image dataset of a first timepoint, wherein the first image dataset represents an anatomical structure;

loading the first image dataset of the first timepoint;

selecting a second image dataset of a second timepoint, wherein the second image dataset represents the anatomical structure;

loading the second image dataset of the second timepoint,

wherein the first and second image datasets were acquired from different modalities;

registering the first image dataset of the first timepoint with the second image dataset of the second timepoint; and

displaying an image from the first image dataset of the first timepoint and an image from the second image dataset of the second timepoint at the same time and in separate views,

wherein the first image dataset of the first timepoint and the second image dataset of the second timepoint each comprise data acquired from a computed tomography (CT), positron emission tomography (PET), single photon emission computed tomography (SPECT), magnetic resonance (MR) or ultrasound modality, and

wherein the first image dataset of the first timepoint and the second image dataset of the second timepoint each comprise a CT image series and MR image series, a PET image series and SPECT image series, a combination of a CT and PET image series, a combination of an MR and PET image series, a combination of a CT and SPECT image series, a combination of an MR and SPECT image series or an ultrasound image series.

2. The method of claim 1 , wherein the image series in each of the first image dataset of the first timepoint and the second image dataset of the second timepoint comprise data from a pre-therapy, ongoing therapy or post-therapy study.

3. The method of claim 1 , wherein the first image dataset of the first timepoint and the second image dataset of the second timepoint are registered using automatic registration, landmark registration or visual registration.

4. The method of claim 3 , wherein automatic registration used during the step of registering the first image dataset of the first timepoint and the second image dataset of the second timepoint, comprises:

registering a first image series with a second image series of the first image dataset of the first timepoint;

registering the first image series of the first image dataset of the first timepoint with a first image series of the second image dataset of the second timepoint; and

registering the first image series of the second image dataset of the second timepoint with a second image series of the second image dataset of the second timepoint.

5. The method of claim 1 , wherein the step of displaying the first image dataset of the first timepoint and the second image dataset of the second timepoint, comprises:

displaying a first image series and a second image series of the first image dataset of the first timepoint and a first image series and a second image series of the second image dataset of the second timepoint.

6. The method of claim 5 , further comprising:

drawing a volume of interest (VOI) on one of the first image series or second image series of the first image dataset of the first timepoint and the first image series or second image series of the second image dataset of the second timepoint;

copying the VOI onto remaining image series of the first image dataset of the first timepoint and second image dataset of the second timepoint; and

linking the VOIs of the first image series and second image series of the first image dataset of the first timepoint and the first image series and second image series of the second image dataset of the second timepoint.

7. The method of claim 6 , wherein the VOI is a lesion, tumor or cancerous region.

8. The method of claim 6 , further comprising:

quantifying the VOIs on the first image series and second image series of the first image dataset of the first timepoint and the first image series and second image series of the second image dataset of the second timepoint.

9. The method of claim 8 , wherein the quantification is a minimum deviation, maximum deviation, standard deviation, average, volume, mean, diameter area number of pixels or centroid.

10. The method of claim 8 , further comprising:

detecting a change in the VOIs.

11. The method of claim 8 , further comprising:

generating a report associated with the quantified VOIs.

12. The method of claim 1 , further comprising:

calculating a maximum intensity projection (MIP) of the first image dataset of the first timepoint or the second image dataset of the second timepoint; and

displaying the MIP.

13. The method of claim 12 , further comprising:

coordinating the MIP with the first image dataset of the first timepoint and the second image dataset of the second timepoint.

14. A user interface for multi-modal visualization, comprising:

a first display area for displaying a first image dataset of a first timepoint and a second image dataset of a second timepoint to compare the first image dataset of the first timepoint and the second image dataset of the second timepoint to each other;

a second display area for displaying a control area, wherein the control area comprises a patient folder, a workflow pane and controls;

wherein the first image dataset of the first timepoint and the second image dataset of the second timepoint each comprise data acquired from a computed tomography (CT), positron emission tomography (PET), single photon emission computed tomography (SPECT), magnetic resonance (MR) or ultrasound modality, and

wherein the workflow pane comprises a registration pane, a visualization pane, a maximum intensity projection (MIP) pane, a contour pane and a report pane, which are arranged in a stepwise fashion so that a user can utilize the functionality of each pane in sequence.

15. The user interface of claim 14 , wherein the first image dataset of the first timepoint and the second image dataset of the second timepoint each comprise a CT image series and MR image series a PET image series and SPECT image series, a combination of a CT and PET image series a combination of an MR and PET image series a combination of a CT and SPECT image series, a combination of an MR and SPECT image series or an ultrasound image series.

16. The user interface of claim 15 , wherein the image series in each of the first image dataset of the first timepoint and the second image dataset of the second timepoint comprise data from a pre-therapy, ongoing therapy or post-therapy study.

17. The user interface of claim 14 , wherein when the first image dataset of the first timepoint and the second image dataset of the second timepoint are each displayed in a sagittal view, coronal view or axial view, the first image dataset and the second image dataset are displayed in a fused view.

18. A system for multi-modal visualization, comprising:

a memory device for storing a program;

a processor in communication with the memory device, the processor operative with the program to:

select a first image dataset of a first timepoint and a second image dataset of a second timepoint;

load the first image dataset of the first timepoint and the second image dataset of the second time point,

wherein the first and second image datasets were acquired from different modalities;

register the first image dataset of the first timepoint with the second image dataset of the second timepoint; and

display an image from the first image dataset of the first timepoint and an image from the second image dataset of the second timepoint at the same time and in separate views,

wherein the first image dataset of the first timepoint and the second image dataset of the second timepoint each comprise data acquired from a computed tomography (CT), positron emission tomography (PET), single photon emission computed tomography (SPECT), magnetic resonance (MR) or ultrasound modality, and

wherein the first image dataset of the first timepoint and the second image dataset of the second timepoint each comprise a CT image series and MR image series, a PET image series and SPECT image series, a combination of a CT and PET image series, a combination of an MR and PET image series, a combination of a CT and SPECT image series, a combination of an MR and SPECT image series or an ultrasound image series.

19. The system of claim 18 , wherein the image series in each of the first image dataset of the first timepoint and the second image dataset of the second timepoint comprise data from a pre-therapy, ongoing therapy or post-therapy study.