Multi-Dimensional Image Reconstruction and Analysis for Expert-System Diagnosis

• US 20080033291A1
• Filed: 01/15/2006
• Published: 02/07/2008
• Est. Priority Date: 01/13/2005
• Status: Active Grant

• Current Assignee: Spectrum Dynamics Medical Ltd
• Original Assignee: Spectrum Dynamics LLC
• Inventors: Rousso, Benny, Vallabhajosula, Shankar, Dickman, Dalia, Nagler, Michael
• Granted Patent: US 7,872,235 B2
• Time in Patent Office: Days
• US Class Current: 600/436
• CPC Class Codes: A61B 5/02755 Radioactive tracers
• CPC Class Codes: A61B 5/415 the glands, e.g. tonsils, adenoids or thymus
• CPC Class Codes: A61B 5/416 the spleen
• CPC Class Codes: A61B 5/418 lymph vessels, ducts or nodes
• CPC Class Codes: A61B 5/4519 Muscles A61B5/389, A61B5/224 take precedence
• CPC Class Codes: A61B 5/7203 for noise prevention, reduction or removal
• CPC Class Codes: A61B 5/7264 Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems neural networks per se G06N3/00; expert systems per se G06N5/00
• CPC Class Codes: A61B 6/037 Emission tomography
• CPC Class Codes: A61B 6/486 involving generating temporal series of image data
• CPC Class Codes: A61B 6/507 for determination of haemodynamic parameters, e.g. perfusion CT
• CPC Class Codes: G01T 1/1647 Processing of scintigraphic data not related to a particular imaging system G01T1/2992
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

The present invention relates to the capabilities of a highly sensitive radioactive-emission camera, a result of a meticulous search for the many different effects that combine synergistically to increase sensitivity and spatial, spectral, and time resolutions. The new camera opens a new realm in SPECT-type imaging, making it viable for dynamic studies, the use of radiopharmaceutical cocktails, molecular imaging, dosimetry and other studies requiring the high sensitivity and resolutions. In particular, the new camera opens the door to SPECT expert system, examples for which are provided. The expert system relates to defining disease signatures for automatic diagnosis, preferably, based on a multi-parameter vector, preferably, based on kinetic radiopharmaceutical values. Additionally or alternatively, based on simultaneous administration of multiple isotopes.

Claims

1. A method of image reconstruction of a multi-isotope source, comprising:

modeling photon scatter for each isotope j, based on the Compton scatter equation, relating initial and final photon energies to a Compton scatter angle;

employing an iterative process for generating a solution for the image reconstruction, by describing a probability that an emitted photon of an isotope j, from a voxel u, be detected by a detector t, at an energy bin b.

2. A method for determining a future administration dose, comprising:

i. administering a radiopharmaceutical at no more than one fifth of an expected effective dose;

ii. measuring by SPECT the distribution of the radiopharmaceutical in the body; and

iii. determining the preferred administration dose of the radiopharmaceutical agent for at least one future administration.

3. The method of claim 2, wherein the future administration is of a radiopharmaceutical.

4. The method of claim 2, wherein the future administration is of a therapeutic agent.

5. A method of diagnosing a patient condition, comprising:

defining pathological signatures, each characterized by a unique combination of at least two parameters, which relate to behavior of a radiopharmaceutical in vivo;

measuring the at least two parameters, for a patient, by SPECT imaging; and

automatically diagnosing a pathology of the patient, by automatically matching the at least two parameters and the pathological signatures.

7. The methods of claims 5, wherein automatically diagnosing a pathology comprises automatically diagnosing based on a database of values for normal and diseased populations.

8. The methods of claims 5, wherein measuring includes measuring at least one radiopharmaceutical kinetic parameter of a flow rate across a tissue membrane.

9. The method of any one of claims 5, and further including automatically determining the degree of the pathology.

6. A method of diagnosing a patient condition, comprising:

defining pathological signatures, each characterized by a unique combination of at least two patient parameters, at least one of which relating to behavior of a radiopharmaceutical in vivo;

measuring the at least two patient parameters, wherein the at least one patient parameter relating to the behavior of the radiopharmaceutical in vivo is measured by SPECT imaging; and

automatically diagnosing a pathology by automatically matching the at least two patient parameters and the pathological signatures.

10. An electronic storage medium comprising

at least one radiopharmaceutical identity;

SPECT measured values of at least one radiopharmaceutical kinetic parameter of a flow rate across a tissue membrane, for the radiopharmaceutical, and

a set of instructions for associating the at least one radiopharmaceutical kinetic parameter with a disease signature.

11. Apparatus for performing automatic diagnosis, based on SPECT data, comprising a set of instructions for:

defining pathological signatures, each characterized by a unique combination of at least two patient parameters, at least one of which relating to behavior of a radiopharmaceutical in vivo, as measured by SPECT;

measuring the at least two patient parameters, wherein the at least one patient parameter relating to the behavior of the radiopharmaceutical in vivo is measured by SPECT imaging; and

automatically diagnosing a pathology by automatically matching the at least two patient parameters and the pathological signatures.

12. The apparatus of claim 11, wherein automatically diagnosing a pathology comprises automatically diagnosing based on a database of values for normal and diseased populations.

13. The apparatus of claim 11, wherein measuring includes measuring at least one radiopharmaceutical kinetic parameter of a flow rate across a tissue membrane.

14. The apparatus of claim 12, wherein automatically diagnosing includes determining a degree of a pathology.

15. An electronic storage medium comprising a set of instructions for:

defining pathological signatures, each characterized by a unique combination of at least two patient parameters, at least one of which relating to behavior of a radiopharmaceutical in vivo, as measured by SPECT;

measuring the at least two patient parameters, wherein the at least one patient parameter relating to the behavior of the radiopharmaceutical in vivo is measured by SPECT imaging; and

automatically diagnosing a pathology by automatically matching the at least two patient parameters and the pathological signatures.

16. The electronic storage medium of claim 15, wherein automatically diagnosing a pathology comprises automatically diagnosing based on a database of values for normal and diseased populations.

17. The electronic storage medium of claim 15, wherein measuring includes measuring at least one radiopharmaceutical kinetic parameter of a flow rate across a tissue membrane.