Method and system for determining a temporospatially-fractionated radiotherapy planning
US-2024424320-A1 · Dec 26, 2024 · US
US10029121B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-10029121-B2 |
| Application number | US-201415108188-A |
| Country | US |
| Kind code | B2 |
| Filing date | Dec 30, 2014 |
| Priority date | Dec 31, 2013 |
| Publication date | Jul 24, 2018 |
| Grant date | Jul 24, 2018 |
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Systems and methods directed to adaptive radiotherapy planning are provided. In some aspects, provided system and method include producing synthetic images from magnetic resonance data using relaxometry maps. The method includes applying corrections to the data and generating relaxometry maps therefrom. In other aspects, a method for adapting a radiotherapy plan is provided. The method includes determining an objective function based on dose gradients from an initial dose distribution, and generating an optimized plan based on updated images, using aperture morphing and gradient maintenance algorithms without need for organ-at-risk contouring. In yet other aspects, a method for obtaining 4D MR imaging using a temporal reshuffling of data acquired during normal breathing, a method for deformable image registration using a sequentially applied semi-physical model regularization method for multimodality images, and a method to generate 4D plans using an aperture morphing algorithm based on 4D CT or 4D MR imaging are provided.
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The invention claimed is: 1. A system for developing a radiotherapy treatment plan, the system comprising: a data storage device configured to hold MR image data acquired by an MRI system; at least one processor configured to: receive the MR image data from the data storage device; apply corrections to the MR image data to produce a series of corrected image data; assemble the series of corrected image data to generate a set of relaxometry maps; perform a segmentation of a plurality of regions of interest using the set of relaxometry maps; classify the plurality of regions of interest, using the set of relaxometry maps, to yield a plurality of classified structures; assign electron density values to the classified structures using an assignment process; generate, using the electron density values of the classified structures, a set of corrected synthetic electron density images; and perform a dose calculation using the corrected synthetic electron density images to develop a radiotherapy treatment plan. 2. The system of claim 1 , wherein the MR image data comprises 4D MR image data. 3. The system of claim 1 , wherein the processor is further configured to apply the corrections using a magnetic field (B0) map, a radio-frequency transmit (B1+) map, or both, to compensate for a magnetic field (B0) inhomogeneity, a RF transmit field (B1+) inhomogeneity, or both. 4. The system of claim 1 , wherein the set of relaxometry maps includes a T1 map, a T2 map, a T2* map, or a combination thereof. 5. The system of claim 1 , wherein the processor is further configured to classify the plurality of regions of interest according to image intensities in the set of relaxometry maps. 6. The system of claim 1 , wherein the processor is further configured to utilize an atlas-based classification technique in the assignment process assigning electron density values to the classified structures. 7. The system of claim 1 , wherein the processor is further configured to adapt a radiation treatment plan using the corrected synthetic electron density images according to a treatment optimization process. 8. The system of claim 1 , wherein the processor is further configured to correct the set of corrected synthetic electron density images for gradient nonlinearity, or off-resonance effects, field inhomogeneties, or a combination thereof. 9. The system of claim 1 , wherein electron density values in the set of corrected synthetic electron density images are used to determine a radiation dose distribution for the dose calculation. 10. A method for producing synthetic images for use in a radiotherapy treatment, the method comprising: receiving a plurality of magnetic resonance (MR) image data acquired using a magnetic resonance system (MRI) system; applying corrections to the MR image data to produce a series of corrected image data; assembling the series of corrected image data to generate a set of relaxometry maps; performing a segmentation of a plurality of regions of interest using the set of relaxometry maps; classifying the plurality of regions of interest to yield a plurality of classified structures; assigning electron density values to the classified structures using an assignment process; and generating, using the electron density values of the classified structures, a set of corrected synthetic electron density images. 11. The method of claim 10 , the method further comprising acquiring, using the MRI system, 3D fast low angle shot (FLASH) images at a plurality of flip angles, 3D balanced steady-state free precession (bSSFP) images at a plurality of flip angles, 3D gradient echo (GRE) images at a plurality of echo times, 3D actual flip angle (AFI) images at a plurality of repetition times, or a combination thereof. 12. The method of claim 10 , the method further comprising generating a magnetic field (B0) map, a radio-frequency transmit (B1+) map, or both, to compensate for a magnetic field (B0) inhomogeneity, a RF transmit field (B1+) inhomogeneity, or both. 13. The method of claim 10 , wherein the set of relaxometry maps includes a T1 map, a T2 map, a T2* map, or a combination thereof. 14. The method of claim 10 , the method further comprising applying a thresholding technique in performing the segmentation. 15. The method of claim 10 , the method further comprising classifying the plurality of regions of interest according to image intensities in the set of relaxometry maps to yield the plurality of classified structures. 16. The method of claim 15 , the method further comprising utilizing an atlas-based classification technique in the assignment process. 17. The method of claim 10 , the method further comprising converting the set of corrected synthetic electron density images to a set of corrected synthetic CT images using an inverted conversion process. 18. The method of claim 10 , wherein the set of corrected synthetic electron density images are corrected for at least one of the magnetic field (B0) inhomogeneity, the RF transmit field (B1+) inhomogeneity, and the gradient nonlinearity geometric distortion. 19. The method of claim 10 , the method further comprising performing a dose calculation using the corrected synthetic electron density images to develop or adapt a radiotherapy treatment plan. 20. The method of claim 19 , wherein electron density values in the set of corrected synthetic electron density images are used to determine a radiation dose distribution for the dose calculation.
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