AUTOMATED METHOD FOR ASSESSMENT OF TUMOR RESPONSE TO THERAPY WITH MULTI-PARAMETRIC MRI

• US 20100254584A1
• Filed: 03/31/2010
• Published: 10/07/2010
• Est. Priority Date: 04/07/2009
• Status: Abandoned Application

• Current Assignee: Siemens AG
• Original Assignee: Siemens Corp. (Siemens AG)
• Inventors: Strecker, Ralph, Meredith, Glenn A., Kamel, Ihab R., Gulsun, Mehmet Akif
• Application Number:
  US12/751,086
• Publication Number:
  US 20100254584A1
• Time in Patent Office: Days
• US Class Current: 382/131
• CPC Class Codes: A61B 5/055 involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
• CPC Class Codes: G01R 33/5601 involving use of a contrast agent for contrast manipulation, e.g. a paramagnetic, super-paramagnetic, ferromagnetic or hyperpolarised contrast agent
• CPC Class Codes: G01R 33/5608 Data processing and visualization specially adapted for MR, e.g. for feature analysis and pattern recognition on the basis of measured MR data, segmentation of measured MR data, edge contour detection on the basis of measured MR data, for enhancing measured MR data in terms of signal-to-noise ratio by means of noise filtering or apodization, for enhancing measured MR data in terms of resolution by means for deblurring, windowing, zero filling, or generation of gray-scaled images, colour-coded images or images displaying vectors instead of pixels image data processing or generation, in general G06T
• CPC Class Codes: G01R 33/56341 Diffusion imaging
• CPC Class Codes: G01R 33/56366 Perfusion imaging
• CPC Class Codes: G06T 2207/10076 4D tomography; Time-sequential 3D tomography
• 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 7/0014 using an image reference approach
• CPC Class Codes: G06T 7/162 involving graph-based methods

Abstract

A method for assessing a tumor'"'"'s response to therapy, includes providing images of a first study of a patient and images of a second study of the patient, the second study occurring after the first study and after the patient undergoes therapy to treat a tumor, each study comprising first and second types of functional magnetic resonance (fMR) images, performing a first registration in which the images within each study are registered, performing a second registration in which reference images from both studies are co-registered, segmenting the tumor in an image of each of the second registered studies; and determining that first and second fMR measure differences exist between the segmented tumor'"'"'s of the first and second studies, the first fMR measure difference being obtained from the first type of fMR images, the second fMR measure difference being obtained from the second type of fMR images.

Claims

1. A method for assessing a tumor'"'"'s response to therapy, comprising:

providing images of a first study of a patient and images of a second study of the patient, the second study occurring after the first study and after the patient undergoes first therapy to treat a tumor, each study comprising first and second types of functional magnetic resonance (fMR) images;

performing a first registration in which the images within each study are registered such that all of the first and second types of fMR images are in a common frame of reference and anatomically aligned;

performing a second registration in which reference images from both studies are co-registered, wherein an operation resulting from the co-registration is applied to all images of the second study;

segmenting the tumor in an image of each of the second registered studies; and

determining that first and second fMR measure differences exist between the segmented tumor of the first study and the segmented tumor of the second study, the first fMR measure difference being obtained from the first type of fMR images, the second fMR measure difference being obtained from the second type of fMR images, the determination being enabled by the second registration.

2. The method of claim 1, wherein the first study occurs prior to the patient undergoing therapy to treat the tumor.

3. The method of claim 1, wherein the first study takes place after the patient undergoes therapy to treat the tumor but before the first therapy.

4. The method of claim 1, wherein the second registration comprises a deformable registration or an affine registration, the deformable registration producing a deformation field to be applied to all images of the second study, the affine registration producing an affine transformation to be applied to all images of the second study.

5. The method of claim 1, further comprising generating a parametric map of the tumor'"'"'s viability by using, in a voxel-by-voxel calculation, functional measures of the segmented tumor in the first type of fMR images of the first and second studies, and functional measures of the segmented tumor in the second type of fMR images of the first and second studies, and a weighting of each functional measure.

6. The method of claim 5, further comprising displaying the map with scaled colorizations, the map being overlaid on grayscale images of one of the first or second types of fMR images.

7. The method of claim 5, wherein the weighting of each functional measure is adjusted per one or more of the following image quality metrics:

signal to noise ratio, contrast to noise ratio, goodness of fit parameters, signal intensity error of prediction, consistency of the functional measure within a segmented region and consistency of the functional measure over a temporal range.

8. The method of claim 1, wherein the first type of fMR images comprise dynamic contrast enhancement (DCE) images and the second type of fMR images comprise diffusion weighted images.

9. The method of claim 8, wherein the first fMR measure difference is obtained by calculating arterial or venous enhancement values on a voxel-by-voxel basis for each of the segmented tumor of the second study and the segmented tumor of the first study in corresponding DCE images and identifying differences in the arterial or venous enhancement values.

10. The method of claim 8, wherein the second cellular difference is obtained by calculating differences in apparent diffusion coefficient (ADC) values on a voxel-by-voxel basis between the segmented tumor of the second study and the segmented tumor of the first study in corresponding diffusion weighted images.

11. The method of claim 1, further comprising displaying individual fMR measure difference maps with colorized regions of increased, decreased or unchanged levels, or displaying individual fMR measure difference data as scatter plots of increased, decreased or unchanged levels overlaid on grayscale images of one of the first or second types of fMR images.

12. A system for assessing a tumor'"'"'s response to therapy, comprising:

a memory device for storing a program;

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

receive images of a first study of a patient and images of a second study of the patient, the second study occurring after the first study and after the patient undergoes first therapy to treat a tumor, each study comprising first and second types of functional magnetic resonance (fMR) images;

perform a first registration in which the images within each study are registered such that all of the first and second types of fMR images are in a common frame of reference and anatomically aligned;

perform a second registration in which reference images from both studies are co-registered, wherein an operation resulting from the co-registration is applied to all images of the second study;

segment the tumor in an image of each of the second registered studies; and

determine that first and second fMR measure differences exist between the segmented tumor of the first study and the segmented tumor of the second study, the first fMR measure difference being obtained from the first type of fMR images, the second fMR measure difference being obtained from the second type of fMR images, the determination being enabled by the second registration.

13. The system of claim 12, wherein the first study occurs prior to the patient undergoing therapy to treat the tumor.

14. The system of claim 12, wherein the first study takes place after the patient undergoes therapy to treat the tumor but before the first therapy.

15. The system of claim 12, wherein the second registration comprises a deformable registration or an affine registration, the deformable registration producing a deformation field to be applied to all images of the second study, and the affine registration producing an affine transformation to be applied to all images of the second study.

16. The system of claim 12, wherein the processor is further operative with the program to generate a parametric map of the tumor'"'"'s viability by using, in a voxel-by-voxel calculation, functional measures of the segmented tumor in the first type of fMR images of the first and second studies, and functional measures of the segmented tumor in the second type of fMR images of the first and second studies, and a weighting of each functional measure.

17. The system of claim 16, wherein the processor is further operative with the program to display the map with scaled colorizations, displaying individual fMR measure difference maps with colorized regions of increased, decreased or unchanged levels, or displaying individual fMR measure difference data as scatter plots of increased, decreased or unchanged levels.

18. The system of claim 16, wherein the weighting of each functional measure is adjusted per one or more of the following image quality metrics:

signal to noise ratio, contrast to noise ratio, goodness of fit parameters, signal intensity error of prediction, consistency of the functional measure within a segmented region and consistency of the functional measure over a temporal range.

19. The system of claim 12, wherein the first type of fMR images comprise dynamic contrast enhancement (DCE) images and the second type of fMR images comprise diffusion weighted images.

20. The system of claim 19, wherein the first fMR measure difference is obtained by calculating arterial or venous enhancement values on a voxel-by-voxel basis for each of the segmented tumor of the second study and the segmented tumor of the first study in corresponding DCE images and identifying differences in the arterial or venous enhancement values.

21. The system of claim 19, wherein the second cellular difference is obtained by calculating differences in apparent diffusion coefficient (ADC) values on a voxel-by-voxel basis between the segmented tumor of the second study and the segmented tumor of the first study in corresponding diffusion weighted images.

22. The system of claim 12, wherein the processor is further operative with the program to display individual fMR measure difference maps with colorized regions of increased, decreased or unchanged levels, or displaying individual fMR measure difference data as scatter plots of increased, decreased or unchanged levels overlaid on grayscale images of one of the first or second types of fMR images.