Particle emission tomography
The present invention provides autoradiography methods and systems for imaging via the detection of alpha particles, beta particles, or other charged particles. Embodiments of the methods and systems provide high-resolution 3D imaging of the distribution of a radioactive probe, such as a radiopharmaceutical, on a tissue sample. Embodiments of the present methods and systems provide imaging of tissue samples by reconstruction of a 3D distribution of a source of particles, such as a radiopharmaceutical. Embodiments of the methods and systems provide tomographic methods including microtomography, macrotomography, cryomicrotomography and cryomacrotomography.
1. A method for reconstructing a three dimensional (3D) distribution of a source of particles in a tissue sample, the method comprising the steps of:
placing a particle-processing detector adjacent to a single side of the tissue sample;
repeating, for each of a plurality of particles received from the single side of the tissue sample, the steps of:
detecting the particle with the particle-processing detector, wherein the particle is a beta particle, alpha particle, positron, or electron;
determining attributes of the particle; wherein the attributes comprise at least two of:
(i) a two dimensional position corresponding to an interaction point where the particle interacts with the particle-processing detector;
(ii) an energy that is deposited in the particle-processing detector by the particle; and
(iii) a direction of travel of the particle at the interaction point where the particle interacts with the particle-processing detector; and
storing the attributes of the particle;
thereby generating attributes for each of the plurality of particles; and
reconstructing the 3D distribution of the source of particles using at least a portion of the attributes for each of the plurality of particles received from the single side of the tissue sample, wherein the detector provides a spatial resolution of 750 nm to 1 μm.
2. The method of claim 1 , wherein the particle is emitted upon radioactive decay occurring in the tissue to be imaged, and has an initial energy that is known.
3. The method of claim 1 , further comprising determining the energy and angle of the particle.
4. The method of claim 1 , further comprising calculating a distance traveled for each of the plurality of particles within the tissue sample from the energy lost by each of the particles.
5. The method of claim 1 , wherein the interaction point corresponds to a two-dimensional position that the particle interacts with an active area of the particle-processing detector.
6. The method of claim 1 , wherein the interaction point corresponds to a two-dimensional position where the particle interacts with an entrance face of the particle-processing detector.
7. The method of claim 1 , wherein the attributes further comprises a particle interaction time, or the energy of the particle upon interacting with the detector.
8. The method of claim 1 , wherein the source of particles comprises a distribution of a radiopharmaceutical within the tissue sample.
9. The method of claim 8 , wherein the 3D distribution of the source of particles comprises a distribution of the radiopharmaceutical in the tissue.
10. The method of claim 8 , wherein the source is in vivo tissue or ex vivo tissue.
11. The method of claim 8 , wherein the source of particles is provided in a tissue sample having a thickness selected from the range of 1 μm to 100 μm.
12. The method of claim 8 , wherein the source of particles is located at a depth within a tissue selected from the range of 0 to 100 μm.
13. The method of claim 8 , wherein the source of particles comprises radioactive compositions within living tissue.
14. The method of claim 1 , further comprising a step of administering the source of particles to a patient, subject or tissue, wherein the source of particles comprises one or more of a radiopharmaceutical, a radioisotope or a radiotracer.
15. A method for reconstructing a three dimensional (3D) distribution of a source of particles in a tissue sample, the method comprising the steps of:
placing a particle-processing detector adjacent to a single side of the tissue sample;
repeating, for each of a plurality of particles received from the single side of the tissue sample, the steps of:
detecting the particle with the particle-processing detector, wherein the particle is a beta particle, alpha particle, positron, or electron;
determining attributes of the particle; wherein the attributes comprise at least two of:
(i) a two dimensional position corresponding to an interaction point where the particle interacts with the particle-processing detector;
(ii) an energy that is deposited in the particle-processing detector by the particle; and
(iii) a direction of travel of the particle at the interaction point where the particle interacts with the particle-processing detector; and
storing the attributes of the particle;
thereby generating attributes for each of the plurality of particles; and
reconstructing the 3D distribution of the source of particles using at least a portion of the attributes for each of the plurality of particles received from the single side of the tissue sample,
wherein the at least a portion of the particle attributes are determined using a maximum-likelihood estimate algorithm.
16. A method for reconstructing a three dimensional (3D) distribution of a source of particles in a tissue sample, the method comprising the steps of:
placing a particle-processing detector adjacent to a single side of the tissue sample;
repeating, for each of a plurality of particles received from the single side of the tissue sample, the steps of:
detecting the particle with the particle-processing detector, wherein the particle is a beta particle, alpha particle, positron, or electron;
determining attributes of the particle; wherein the attributes comprise at least two of:
(i) a two dimensional position corresponding to an interaction point where the particle interacts with the particle-processing detector;
(ii) an energy that is deposited in the particle-processing detector by the particle; and
(iii) a direction of travel of the particle at the interaction point where the particle interacts with the particle-processing detector; and
storing the attributes of the particle;
thereby generating attributes for each of the plurality of particles; and
reconstructing the 3D distribution of the source of particles using at least a portion of the attributes for each of the plurality of particles received from the single side of the tissue sample,
wherein the step of reconstructing the 3D distribution is performed using a list-mode maximum-likelihood expectation-maximization algorithm.
17. A device for reconstructing a three dimensional (3D) distribution of a source of particles within a tissue sample, wherein the particles comprise beta particles, alpha particles, positrons, or conversion electrons, the device comprising:
a particle-processing detector for detecting particles, wherein the detector provides a spatial resolution of 750 nm to 1 μm;
a processor positioned in data communication with the particle-processing detector, wherein the processor is configured for:
determining attributes of a plurality of particles received from at least a single side of the tissue sample; wherein the attributes comprise at least two of:
(i) a two dimensional position corresponding to an interaction point where the particle interacts with the particle-processing detector;
(ii) an energy that is deposited in the particle-processing detector by the particle; and
(iii) a direction of travel of the particle at the interaction point where the particle interacts with the particle-processing detector; and
storing the attributes of the plurality of particles received from at least a single side of the tissue sample;
thereby generating attributes for each of the plurality of particles; and
reconstructing the 3D distribution of the source of particles using at least a portion of the attributes for each of the plurality of particles received from at least a single side of the tissue sample.
18. The device of claim 17 , wherein the processor is able to determine the attributes of the plurality of particles using a maximum-likelihood estimate algorithm.
19. The device of claim 17 , wherein the particle-processing detector comprises a silicon sensor or a scintillation camera.
20. The device of claim 17 comprising a tomographic imaging system.
21. The device of claim 17 , wherein the particle-processing detector further comprises a GPU, FPG or an application-specific integrated circuit (ASIC).
22. The device of claim 17 , wherein the particle-processing detector comprises a track detector.
23. The device of claim 17 , wherein the processor is able to reconstruct the 3D distribution using a list-mode maximum-likelihood expectation-maximization algorithm.