Automatic correlation modeling of an internal target

• US 10,046,178 B2
• Filed: 01/08/2016
• Issued: 08/14/2018
• Est. Priority Date: 10/26/2007
• Status: Active Grant

• Current Assignee: Accuray Incorporated
• Original Assignee: Accuray Incorporated
• Inventors: Li, Shutian, Sheng, Ye, Sayed, Sohail
• Primary Examiner(s): Bali, Vikkram
• Application Number:
  US14/991,428
• Publication Number:
  US 20160121140A1
• Time in Patent Office: 949 Days
• Field of Search: None
• CPC Class Codes: A61B 2034/105 Modelling of the patient, e.g. for ligaments or bones
• CPC Class Codes: A61B 2034/107 Visualisation of planned trajectories or target regions
• CPC Class Codes: A61B 2090/3945 Active visible markers, e.g. light emitting diodes
• CPC Class Codes: A61B 2090/3966 Radiopaque markers visible in an X-ray image
• CPC Class Codes: A61B 2560/0475 Special features of memory means, e.g. removable memory cards
• CPC Class Codes: A61B 5/1127 using markers
• CPC Class Codes: A61B 5/113 occurring during breathing
• CPC Class Codes: A61B 5/1135 by monitoring thoracic expansion
• CPC Class Codes: A61B 5/7246 using correlation, e.g. template matching or determination of similarity
• CPC Class Codes: A61B 5/7285 for synchronising or triggering a physiological measurement or image acquisition with a physiological event or waveform, e.g. an ECG signal A61B6/5205, A61B6/541, A61B8/5207, A61B8/543 take precedence
• CPC Class Codes: A61B 5/7292 Prospective gating, i.e. predicting the occurrence of a physiological event for use as a synchronisation signal
• CPC Class Codes: A61B 6/541 involving acquisition triggered by a physiological signal
• CPC Class Codes: A61N 2005/1051 using an active marker
• CPC Class Codes: A61N 2005/1061 using an x-ray imaging system having a separate imaging source
• CPC Class Codes: A61N 2005/1074 Details of the control system, e.g. user interfaces
• CPC Class Codes: A61N 5/103 Treatment planning systems
• CPC Class Codes: A61N 5/1037 taking into account the movement of the target, e.g. 4D-image based planning
• CPC Class Codes: A61N 5/1049 for verifying the position of the patient with respect to the radiation beam
• CPC Class Codes: A61N 5/107 in real time, i.e. during treatment
• CPC Class Codes: A61N 5/1077 Beam delivery systems

Abstract

A method and apparatus to automatically control the timing of an image acquisition by an imaging system in developing a correlation model of movement of a target within a patient.

Claims

1. A method, comprising:

automatically triggering, by a processing device, image acquisition of a plurality of pretreatment images of a target, wherein the plurality of pretreatment images are internal to a patient, wherein acquisition of each of the plurality of pretreatment images is triggered at a different time; and

generating, by the processing device, a correlation model distinguishing between inspiration and expiration movements that maps the movements of an external marker to a target location of the target using the plurality of pretreatment images, wherein said automatically triggering comprises automatically triggering image acquisition at substantially evenly-distributed points of a periodic cycle, and wherein said automatically triggering each of the plurality of pretreatment images comprises;

obtaining historical data of movement of the target in one or more previous periodic cycles;

dividing the historical data into a plurality of regions based on magnitude of movement of the target;

distinguishing between the inspiration and expiration movements of the historical data;

establishing a plurality of model metric regions using the plurality of regions and the distinguished inspiration and expiration movement, wherein the plurality of model metric regions correspond to a plurality of phases of the periodic cycle;

determining whether a current sample of the target movement is in a desired phase of the periodic cycle by categorizing the current sample into one of the plurality of model metric regions; and

sending an imaging command to an imaging system to acquire the pretreatment image when the current sample is in the desired phase of the periodic cycle.

2. The method of claim 1, wherein said obtaining comprises acquiring a plurality of data points representative of a corresponding plurality of positions over time of an external marker associated with a patient, wherein the plurality of positions of the external marker define an external path of movement of the external marker, and the external path of movement defines the periodic cycle of the patient.

3. The method of claim 2, wherein said generating the correlation model comprises:

identifying a path of movement of the target based on the plurality of data points and the plurality of pretreatment images at the substantially evenly-distributed points of the periodic cycle; and

developing the correlation model using the path of movement of the target.

4. The method of claim 2, further comprising updating the correlation model in response to an acquisition of a new data point.

5. The method of claim 1, further comprising:

deriving a target position of the target based on the correlation model,

sending a position signal associated with the target position to a beam generator controller; and

controlling the beam generator controller to direct a beam at the target.

6. The method of claim 1, further comprising:

periodically generating positional data about the target by automatically acquiring additional images of the target during treatment; and

continuously generating positional data about external motion of the external marker during treatment.

10. The apparatus of claim 1, wherein the processing device is further to:

derive a target position of the target based on the correlation model,

send a position signal associated with the target position to a beam generator controller; and

control the beam generator controller to direct a beam at the target.

7. An apparatus, comprising:

a data storage device to store a plurality of pretreatment images of a target, wherein the plurality of pretreatment images are internal to a patient; and

a processing device coupled to the data storage device, the processing device to automatically trigger image acquisition of the plurality of pretreatment images, wherein acquisition of each of the plurality of pretreatment images is triggered at a different time, wherein the processing device is further to generate a correlation model distinguishing between inspiration and expiration movements that maps the movements of an external marker to a target location of the target using the plurality of pretreatment images, wherein in automatically triggering, the processing device is to automatically trigger image acquisition at substantially evenly-distributed points of a periodic cycle, and wherein in automatically triggering each of the plurality of pretreatment images, the processing device is further to;

obtain historical data of the movements of the target in one or more previous periodic cycles;

divide the historical data into a plurality of regions based on magnitude of movement of the target;

distinguish between the inspiration and expiration movements using the historical data;

establish a plurality of model metric regions using the plurality of regions and the distinguished inspiration and expiration movements, wherein the plurality of model metric regions correspond to a plurality of phases of the periodic cycle;

determine whether a current sample of the movements of the target is in a desired phase of the periodic cycle by categorizing the current sample into one of the plurality of model metric regions; and

send an imaging command to an imaging system to acquire the pretreatment image when the current sample is in the desired phase of the periodic cycle.

8. The apparatus of claim 7 wherein the processing device is to acquire a plurality of data points representative of a corresponding plurality of positions over time of the external marker associated with the patient, wherein the plurality of positions of the external marker define an external path of movement of the external marker, and the external path of movement defines the periodic cycle of the patient.

9. The apparatus of claim 8, wherein in generating the correlation model, the processing device is to:

identify a path of movement of the target based on the plurality of data points and the plurality of pretreatment images at the substantially evenly-distributed points of the periodic cycle; and

develop the correlation model using the path of movement of the target.

11. The apparatus of claim 7, wherein the processing device is further to:

periodically generate positional data about the target by automatically acquiring additional images of the target during treatment; and

continuously generate positional data about external motion of the external marker during treatment of the patient.