The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Feb. 01, 2022

Filed:

May. 01, 2018
Applicants:

Rhode Island Hospital, Providence, RI (US);

Children's Medical Center Corporation, Boston, MA (US);

Inventors:

Braden C. Fleming, East Greenwich, RI (US);

Martha M. Murray, Sherborn, MA (US);

Assignees:

Rhode Island Hospital, Providence, RI (US);

Children's Medical Center Corporation, Boston, MA (US);

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/00 (2006.01); A61B 5/00 (2006.01); G06T 7/62 (2017.01); G06T 7/174 (2017.01); G16H 50/50 (2018.01); G16H 30/20 (2018.01); G16H 50/30 (2018.01); A61B 5/055 (2006.01); G01R 33/56 (2006.01); G06T 7/00 (2017.01); G06T 11/00 (2006.01);
U.S. Cl.
CPC ...
A61B 5/7275 (2013.01); A61B 5/055 (2013.01); A61B 5/4533 (2013.01); A61B 5/4585 (2013.01); A61B 5/4851 (2013.01); G01R 33/5608 (2013.01); G06T 7/0016 (2013.01); G06T 7/174 (2017.01); G06T 7/62 (2017.01); G06T 11/005 (2013.01); G06T 11/008 (2013.01); G16H 30/20 (2018.01); G16H 50/30 (2018.01); G16H 50/50 (2018.01); G06T 2207/10088 (2013.01); G06T 2207/30052 (2013.01);
Abstract

The current subject matter provides a tool for evaluating the risk of failure or the likelihood of success of surgery of healing ligaments and tendons in the body. In some embodiments, a region of a scan comprising one or more of an anterior cruciate ligament (ACL) or an ACL graft can be defined. A magnetic resonance (MR) imaging data set can be obtained. MR parameters characterizing a size and a quality of the ACL or ACL graft can be derived using the MR data. The MR parameters can be used as inputs to a predictive model. A score characterizing a likelihood of failure of the ACL or ACL graft in a human patient can be generated using the predictive model.


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