# US 12,005,271 B2 · Super resolution magnetic resonance (MR) images in MR guided radiotherapy

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- Number: US 12,005,271 B2
- Document ID: US12005271B2
- Status: Granted
- Kind: B2
- Application number: 17/661,768
- Filed: 2022-05-03
- Published: 2022-11-17
- Granted: 2024-06-11
- Earliest claimed: 2021-05-03
- Assignees: Washington University
- Applicants: Washington University
- Inventors: Taeho Kim; Geoffrey Hugo; Zhen Ji; Matthew Schmidt; Yu Wu
- Web page: https://patentgrep.com/patent/US12005271B2

## CPC

- A61N 5/1049: {for verifying the position of the patient with respect to the radiation beam}
- A61N 5/1069: {Target adjustment, e.g. moving the patient support}
- A61B 5/055: involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
- G01R 33/4808: {Multimodal MR, e.g. MR combined with positron emission tomography [PET], MR combined with ultrasound or MR combined with computed tomography [CT]}
- 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)}
- G06T 3/4053: based on super-resolution, i.e. the output image resolution being higher than the sensor resolution
- A61N 2005/1055: {using magnetic resonance imaging [MRI]}
- A61N 2005/1056: {by projecting a visible image of the treatment field}
- G01R 33/4826: {in three dimensions}
- G01R 33/5673: {Gating or triggering based on a physiological signal other than an MR signal, e.g. ECG gating or motion monitoring using optical systems for monitoring the motion of a fiducial marker}
- A61N: ELECTROTHERAPY; MAGNETOTHERAPY; RADIATION THERAPY; ULTRASOUND THERAPY (measurement of bioelectric currents A61B; surgical instruments, devices or methods for transferring non-mechanical forms of energy to or from the body A61B18/00; anaesthetic apparatus in general A61M; incandescent lamps H01K; infrared radiators for heating H05B)
- A61B: DIAGNOSIS; SURGERY; IDENTIFICATION (usefulness limited to only animals A61D)
- G01R: MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES (indicating correct tuning of resonant circuits H03J3/12)
- G06T: IMAGE DATA PROCESSING OR GENERATION, IN GENERAL

## Abstract

A computer implemented method of treatment targeting includes receiving magnetic resonance (MR) images of a subject including a target region, generating at least one contour of at least one surrogate element apart from the target region in the MR images, and determining a location of the target region in each of the MR images based on a location of the at least one contour in the MR images.

## Claims

### Claim 1

A treatment targeting system comprising:
a computing device including a processor and a memory, the memory storing instructions that when executed by the processor cause the processor to:
receive magnetic resonance (MR) images of a subject including a target region;
generate at least one contour of at least one surrogate element apart from the target region in the MR images; and
determine a location of the target region in each of the MR images based on a location of the at least one contour in the MR images.

### Claim 2 (depends on 1)

The treatment targeting system of claim 1, further comprising an MR imaging (MRI) device coupled to the computing device to generate the MR images of the subject.

### Claim 3 (depends on 2)

The treatment targeting system of claim 2, further comprising a radiotherapy delivery device coupled to the treatment targeting system, wherein the target region includes a tumor and the instructions further cause the processor to operate the radiotherapy delivery device to direct radiotherapy at the target region based on the determined location of the target region in each of the MR images.

### Claim 4 (depends on 1)

The treatment targeting system of claim 1, wherein the instructions cause the processor to generate at least one contour of at least one surrogate element by generating a first contour of a first surrogate element and generating a second contour of a second surrogate element.

### Claim 5 (depends on 4)

The treatment targeting system of claim 4, wherein the instructions cause the processor to determine the location of the target region in each of the MR images based on a location of the first contour and the second contour in the MR images.

### Claim 6 (depends on 4)

The treatment targeting system of claim 4, wherein the first surrogate element comprises the subject's diaphragm, and the second surrogate element comprises an anterior abdominal surface of the subject.

### Claim 7 (depends on 1)

The treatment targeting system of claim 1, wherein the at least one surrogate element comprises the subject's diaphragm.

### Claim 8 (depends on 1)

The treatment targeting system of claim 1, wherein the at least one surrogate element comprises an anterior abdominal surface of the subject.

### Claim 9 (depends on 1)

The treatment targeting system of claim 1, wherein the instructions cause the processor to determine the location of the target region in each of the MR images based on the location of the at least one contour in the MR images using a ridge regression model based on a relationship between a center of the target area and the at least one surrogate element.

### Claim 10 (depends on 1)

The treatment targeting system of claim 1, wherein the instructions cause the processor to determine the location of the target region in each of the MR images based on the location of the at least one contour in the MR images using principal component analysis (PCA).

### Claim 11 (depends on 1)

The treatment targeting system of claim 1, wherein the received MR images are a plurality of first MR images having a first spatial resolution, and the instructions further cause the processor to:
generate a plurality of second MR images having a second spatial resolution based on the plurality of first MR images using a neural network model, the second spatial resolution higher than the first spatial resolution, the neural network model is trained with a plurality of downsampled images downsampled from a plurality of training images as inputs and the plurality of training images as outputs; and
generate the at least one contour of the at least one surrogate element and determine the location of the target region using the second MR images.

### Claim 12 (depends on 11)

The treatment targeting system of claim 11, wherein the plurality of first MR images are a plurality of cine MR images.

### Claim 13 (depends on 1)

The computer implemented method of claim 1, wherein the received MR images are a plurality of first MR images having a first spatial resolution, and the method further comprises:
generating a plurality of second MR images having a second spatial resolution based on the plurality of first MR images using a neural network model, the second spatial resolution higher than the first spatial resolution, the neural network model is trained with a plurality of downsampled images downsampled from a plurality of training images as inputs and the plurality of training images as outputs; and
generating the at least one contour of the at least one surrogate element and determine the location of the target region using the second MR images.

### Claim 14

A computer implemented method of treatment targeting comprising:
receiving magnetic resonance (MR) images of a subject including a target region;
generating at least one contour of at least one surrogate element apart from the target region in the MR images; and
determining a location of the target region in each of the MR images based on a location of the at least one contour in the MR images.

### Claim 15 (depends on 14)

The computer implemented method of claim 14, further comprising generating the MR images of the subject using an MR imaging (MRI) device.

### Claim 16 (depends on 15)

The computer implemented method of claim 15, wherein the target region includes a tumor and the method further comprises directing, using a radiotherapy device, radiotherapy at the target region based on the determined location of the target region in each of the MR images.

### Claim 17 (depends on 14)

The computer implemented method of claim 14, wherein generating at least one contour of at least one surrogate element apart from the target region in the MR images comprises generating a first contour of a first surrogate element and generating a second contour of a second surrogate element.

### Claim 18 (depends on 17)

The computer implemented method of claim 17, wherein determining the location of the target region in each of the MR images based on a location of the at least one contour in the MR images comprises determining the location of the target region in each of the MR images based on a location of the first contour and the second contour in the MR images.

### Claim 19 (depends on 14)

The computer implemented method of claim 14, wherein determining the location of the target region in each of the MR images based on the location of the at least one contour in the MR images comprises determining the location of the target region in each of the MR images based on the location of the at least one contour in the MR images using a ridge regression model based on a relationship between a center of the target area and the at least one surrogate element.

### Claim 20 (depends on 14)

The computer implemented method of claim 14, wherein determining the location of the target region in each of the MR images based on the location of the at least one contour in the MR images comprises determining the location of the target region in each of the MR images based on the location of the at least one contour in the MR images using principal component analysis (PCA).