Search

EP-4734851-A1 - METHODS AND SYSTEMS TO MINIMIZE RADIATION EXPOSURE WHILE MAINTAINING OPTIMAL IMAGE QUALITY

EP4734851A1EP 4734851 A1EP4734851 A1EP 4734851A1EP-4734851-A1

Abstract

A patient procedure imaging system (200), comprising: a radiation source (270) configured to acquire images of a patient during a patient procedure; and a processor (220) configured to: obtain one or more images acquired at an initial predetermined frame rate, analyze the one or more images to determine a minimum required frame rate for a subsequent window of the patient procedure, adjust the initial predetermined frame rate to the determined minimum required frame rate, obtain new images at the adjusted frame rate, predict images when the determined minimum required frame rate is below a predetermined rate, and combine the new images at the adjusted frame rate and the predicted images to generate a complete image sequence.

Inventors

  • FEIZPOUR, Amin
  • SALEHI, Leili
  • FOTOUHI, JAVAD
  • Sinha, Ayushi
  • LEE, Brian Curtis

Assignees

  • Koninklijke Philips N.V.

Dates

Publication Date
20260506
Application Date
20240619

Claims (20)

  1. 1. An imaging system (200) for performing a patient procedure, the system comprising: a processor (220) configured to: obtain one or more images acquired at an initial predetermined frame rate, analyze the one or more images to determine a minimum required frame rate for a subsequent window of the patient procedure, adjust the initial predetermined frame rate to the determined minimum required frame rate, resulting in an adjusted frame rate, obtain one or more new images acquired at the adjusted frame rate, predict one or more images when the determined minimum required frame rate is below a predetermined rate, and combine the one or more new images at the adjusted frame rate and the predicted one or more images to generate a complete image sequence.
  2. 2. The system of claim 1, further comprising a radiation source (270) configured to acquire images of a patient during the patient procedure.
  3. 3. The system of claim 1, wherein the processor is further configured to apply a trained machine learning model (262) configured to determine the minimum required frame rate for the subsequent window of the patient procedure.
  4. 4. The system of claim 3, wherein the machine learning model is trained to predict the one or more predicted images when the determined minimum required frame rate is below a predetermined rate.
  5. 5. The system of claim 1, further comprising a user interface (240) configured to provide the complete image sequence.
  6. 6. The system of claim 1, wherein the processor is further configured to obtain additional navigation data from a navigation data source, and wherein analyzing the one or more images to determine the minimum required frame rate for a subsequent window of the patient procedure further comprises analyzing the additional navigation data.
  7. 7. The system of claim 6, wherein the navigation data source is a second imaging modality (280).
  8. 8. The system of claim 6, wherein the additional navigation data is generated by the navigation source before the patient procedure.
  9. 9. The system of claim 6, wherein the additional navigation data is generated by the navigation source during at least a portion of the patient procedure.
  10. 10. The system of claim 1, further comprising: a catheter utilized inside the patient during the patient procedure; wherein the complete image sequence is utilized for navigation of the catheter.
  11. 11. The system of claim 3, wherein another processor is configured to train a machine learning model to generate the trained machine learning model (262), the another processor configured to: obtain (310) training data comprising imaging data from a plurality of patient procedures; train (320) the machine learning model to determine a minimum required frame rate for a subsequent window of a patient procedure, wherein the minimum required frame rate minimizes the frame rate while maintaining an image quality necessary to successfully perform the patient procedure; and store (330) the trained machine learning model in memory.
  12. 12. The system of claim 11, wherein the imaging data is obtained at a frame rate at or above the initial predetermined frame rate.
  13. 13. The system of claim 10, wherein, to train the machine learning model, the another processor is configured to identify, by the machine learning model, one or more factors within the training data influencing the minimum required frame rate.
  14. 14. The system of claim 13, wherein the one or more factors comprises one or more of the patient procedure being performed, an anatomy of the patient, and a behavior of a device being navigated inside the patient including translational velocity or rotational velocity of the device.
  15. 15. A method for performing a patient procedure, the method comprising: obtaining one or more images of a patient acquired at an initial predetermined frame rate; analyzing the one or more images to determine a minimum required frame rate for a subsequent window of the patient procedure; adjusting the initial predetermined frame rate to the determined minimum required frame rate, resulting in an adjusted frame rate; obtaining one or more new images acquired at the adjusted frame rate; predicting one or more images when the determined minimum required frame rate is below a predetermined rate; and combining the one or more new images at the adjusted frame rate and the predicted one or more images to generate a complete image sequence.
  16. 16. The method of claim 15, further comprising applying a trained machine learning model (262) configured to determine the minimum required frame rate for the subsequent window of the patient procedure and to predict the one or more predicted images when the determined minimum required frame rate is below a predetermined rate.
  17. 17. The method of claim 16, further comprising generating the trained machine learning model (262) by: obtaining (310) training data comprising imaging data from a plurality of patient procedures; training (320) the machine learning model to determine a minimum required frame rate for a subsequent window of a patient procedure, wherein the minimum required frame rate minimizes the frame rate while maintaining an image quality necessary to successfully perform the patient procedure; and storing (330) the trained machine learning model in memory.
  18. 18. The method of claim 17, wherein the training of the machine learning model comprises identifying, by the machine learning model, one or more factors within the training data influencing the minimum required frame rate.
  19. 19. A non-transitory computer-readable storage medium having stored a computer program comprising instructions, which, when executed by a processor, cause the processor to: obtain one or more images acquired at an initial predetermined frame rate; analyze the one or more images to determine a minimum required frame rate for a subsequent window of a patient procedure; adjust the initial predetermined frame rate to the determined minimum required frame rate, resulting in an adjusted frame rate; obtain one or more new images acquired at the adjusted frame rate; predict one or more images when the determined minimum required frame rate is below a predetermined rate; and combine the one or more new images at the adjusted frame rate and the predicted one or more images to generate a complete image sequence.
  20. 20. The non-transitory computer-readable storage medium, wherein the instructions, when executed by the processor, further cause the processor to to apply a trained machine learning model (262) configured to determine the minimum required frame rate for the subsequent window of the patient procedure.

Description

METHODS AND SYSTEMS TO MINIMIZE RADIATION EXPOSURE WHILE MAINTAINING OPTIMAL IMAGE QUALITY Field of the Disclosure [0001] The present disclosure is directed generally to methods and systems for minimizing hazardous radiation exposure during a patient procedure. Background [0002] Patient exposure to harmful radiation is an unwanted side effect of many medical procedures. For example, exposure to X-ray for extended periods of time is a routine clinical practice during an endovascular procedure in which a catheter is inserted into patient’s blood vessels to deliver a treatment to a target site. This continuous acquisition of sequences of X-ray images is known as a fluoroscopy run. The amount of exposure is typically controlled by the operating room (OR) staff wearing protective garments, using X-ray absorbing shields between the source and the personnel, and/or staff turning the source on and off manually at various time points during the procedure. However, these protective measures often do not adequately protect the patient, and parts of the clinician’s bodies (such as their head or arms having to get close to the X-ray source) are not covered while handling the equipment around the table. [0003] X-ray imaging is utilized during endovascular navigation in order to visualize the device that is being advanced inside the patient’s body, as well as to visualize the vessels in which the device is moving. This visualization allows the interventionalist to determine how to handle the catheter and guidewire to achieve a smooth and rapid navigation toward the target. These X-ray sources are, additionally, equipped with the capability to change the delivered radiation intensity or dose, and the X-ray frame rate (FR). The X-ray frame rate is a feature that determines with what frequency a field of view is imaged by X-ray to allow a full image reconstruction. For example, an FR equal to 1 frame per second (fps) would allow visualization of the guidewire tip once every second. Such features are utilized to adjust the amount of exposure depending on the situation. While the FR, dose, and other variables can be modified on the X-ray imaging system, this is currently a manual process and users typically do not adjust these values during a fluoroscopy run. [0004] Recent technological advancements in endovascular device design and robotics have created new potentials for navigation without always requiring X-ray imaging. Some of these technologies include robotic systems that can provide information about how far and with what velocity a device has advanced into patient’s body, shape sensing devices (e.g., fiber-optic-based devices or technology) with the capability for 3D localization of hundreds of points along a catheter or guidewire, electromagnetic (EM) navigation, magnetically steerable devices, and so on. Despite the presence of such capabilities, there has not been sufficient progress in utilizing them for an intelligent image-based minimization of X-ray usage while maintaining sufficiently high image quality and resolution. Summary of the Disclosure [0005] There is thus a continued unmet need for methods and systems that minimize harmful radiation exposure to patients and clinicians during a patient procedure, without negatively impacting the outcome of the procedure. Various embodiments and implementations are directed to a method and system for determining a minimal frame rate during a patient procedure using a radiation-based patient procedure imaging system. The system receives images during the procedure at an initial frame rate. The system determines a lower, minimum required frame rate for a subsequent window of the patient procedure. For example, a trained machine learning model such as a neural network may analyze the received images and determine the frame rate. The system adjusts the frame rate to the lower rate and receives one or more new images at that lower frame rate. The system provides the one or more images received at the adjusted frame rate to a clinician via a user interface. [0006] According to an aspect, imaging system for performing a patient procedure is provided. The system includes: a processor configured to: obtain one or more images acquired at an initial predetermined frame rate; analyze the one or more images to determine a minimum required frame rate for a subsequent window of the patient procedure; adjust the initial predetermined frame rate to the determined minimum required frame rate, resulting in an adjusted frame rate; obtain one or more new images at the adjusted frame rate; predict one or more images when the determined minimum required frame rate is below a predetermined rate; and combine the one or more new images at the adjusted frame rate and the predicted one or more images to generate a complete image sequence. [0007] According to an embodiment, the system further includes a radiation source configured to acquire images of a patient during a patient procedure. [0008