Image quality compliance tool

Patent metadata

Field	Value
Publication number	US-12011310-B2
Application number	US-202217850529-A
Country	US
Kind code	B2
Filing date	Jun 27, 2022
Priority date	Aug 16, 2017
Publication date	Jun 18, 2024
Grant date	Jun 18, 2024

Abstract

The technology relates to a methods and systems for improving medical imaging procedures. An example method includes receiving a first set of quality metrics for a plurality of medical images acquired at a first imaging facility; receiving a second set of quality metrics for a second plurality of medical images acquired at a second imaging facility; comparing the first set of quality metrics to the second set of quality metrics; based on the comparison of the first set of quality metrics to the second set of quality metrics, generating a benchmark for at least one metric in the first set of quality metrics and the second set of quality metrics; generating facility data based on the generated benchmark and the first set of quality metrics; and sending the facility data to the first imaging facility.

First claim

What is claimed is:

1. A method for improving medical imaging procedures, the method comprising:
receiving, by a central computer system from a first imaging facility, a first one or more patient positioning metrics for a plurality of medical images acquired at the first imaging facility;
receiving, by the central computer system from a second imaging facility, a second one or more patient positioning metrics for a second plurality of medical images acquired at the second imaging facility;
comparing, by the central computer system, the first one or more patient positioning metrics to the second one or more patient positioning metrics;
based on the comparison of the first one or more patient positioning metrics to the second one or more patient positioning metrics, generating, by the central computer system, a benchmark for at least one metric in the first one or more patient positioning metrics and the second one or more patient positioning metrics;
generating, by the central computer system, facility data based on the generated benchmark and the first one or more patient positioning metrics; and
sending, by the central computer system, the facility data to the first imaging facility.

2. The method of claim 1 , further comprising:
generating a training recommendation based on the generated benchmark and the first one or more patient positioning metrics;
receiving, from the first imaging facility, a subsequent one or more patient positioning metrics for a plurality of medical images acquired at the first facility after the sending of the generated training recommendation;
comparing the subsequent one or more patient positioning metrics to the first one or more patient positioning metrics; and
based on the comparison of the subsequent one or more patient positioning metrics to the first one or more patient positioning metrics, generating an effectiveness rating for the generated training.

3. The method of claim 2 , further comprising:
receiving, from the first imaging facility, a subsequent one or more patient positioning metrics for a plurality of medical images acquired at the first facility after the sending of the generated training recommendation;
comparing the subsequent one or more patient positioning metrics to the first one or more patient positioning metrics to determine a trend for at least one patient positioning metric; and
based on determined trend for the at least one patient positioning metric, generating a trend warning.

4. The method of claim 1 , wherein the one or more patient positioning metrics are based on patient positioning scores generated from the plurality of medical images.

5. The method of claim 1 , further comprising providing the first one or more patient positioning metrics and the second one or more patient positioning metrics as inputs to an unsupervised machine learning algorithm to identify additional patterns within the one or more patient positioning metrics.

6. The method of claim 2 , wherein the first one or more patient positioning metrics are received via a web application managed by the central computer system and the training is sent via the web application.

7. The method of claim 1 , wherein the first and second one or more patient positioning metrics are based on patient movement.

8. The method of claim 7 , wherein at least one patient positioning metric is based on a movement signal that is generated by the following operations:
generating, by a force sensor, a force signal indicating a measure of force applied superior to human tissue being compressed between a compression paddle and an imaging detector to capture an image of the human tissue; and
filtering, by a movement detection circuit, a movement signal from the force signal indicating a measure of movement of the compressed human tissue.

9. A central computer system, comprising:
at least one processing unit; and
memory operatively in communication with the at least processing unit, the memory storing instructions that, when executed by the at least one processing unit, are configured to cause the system to perform the following set of operations:
receiving, from a first imaging facility, a first one or more patient positioning metrics for a plurality of medical images acquired at the first imaging facility;
receiving, from a second imaging facility, a second one or more patient positioning metrics for a second plurality of medical images acquired at the second imaging facility;
comparing, by the central computer system, the first one or more patient positioning metrics to the second one or more patient positioning metrics;
based on the comparison of the first one or more patient positioning metrics to the second one or more patient positioning metrics, generating a benchmark for at least one metric in the first one or more patient positioning metrics and the second one or more patient positioning metrics;
generating a training recommendation based on the generated benchmark and the first one or more patient positioning metrics; and
sending the generated training recommendation to the first facility.

10. The system of claim 9 , wherein the set of operations further comprises:
receiving, from the first imaging facility, a subsequent one or more patient positioning metrics for a plurality of medical images acquired at the first facility after the sending of the generated training recommendation;
comparing the subsequent one or more patient positioning metrics to the first one or more patient positioning metrics; and
based on the comparison of the subsequent one or more patient positioning metrics to the first one or more patient positioning metrics, generating an effectiveness rating for the generated training.

11. The system of claim 9 , wherein the set of operations further comprises:
receiving, from the first imaging facility, a subsequent one or more patient positioning metrics for a plurality of medical images acquired at the first facility after the sending of the generated training recommendation;
comparing the subsequent one or more patient positioning metrics to the first one or more patient positioning metrics to determine a trend for at least one patient positioning metric; and
based on determined trend for the at least one patient positioning metric, generating a trend warning.

12. The system of claim 11 , wherein the trend warning is based on a rate of the determined trend.

13. The system of claim 9 , wherein the set of operations further comprises providing the first one or more patient positioning metrics and the second one or more patient positioning metrics as inputs to an unsupervised machine learning algorithm to identify additional patterns within the one or more patient positioning metrics.

14. The system of claim 9 , wherein the first one or more patient positioning metrics are received via a web application managed by the central computer system and the training is sent via the web application.

15. The system of claim 9 , wherein the set of operations further comprise providing a dashboard via a web application to the first facility and the second facility.

16. The system of claim 15 , wherein the dashboard displays the first and second one or more patient positioning metrics received from the first facility compared to the benchmark.

17. The system of claim 9 , wherein receiving the first one or more patient positioning metrics for a plurality of medical images includes receiving identification information for the plurality of medical images.

18. A computer-implemented method comprising for improving

Assignees

• Hologic Inc

Inventors

• Wong Calvin J
• Vaddineni Venkateswara
• Mani Akshay
• Gkanatsios Nikolaos
• Laviola John

Classifications

• A61B6/465

  adapted to display user selection data, e.g. graphical user interface, icons or menus · CPC title

• A61B6/035

  Mechanical aspects of CT · CPC title

• A61B6/5258

  involving detection or reduction of artifacts or noise · CPC title

• A61B6/463

  characterised by displaying multiple images or images and diagnostic data on one display · CPC title

• A61B6/566

  involving communication between diagnostic systems · CPC title