Tarsometatarsal Joint Status

Purpose	Detect if Lisfranc joint is normal or abnormal
Tag(s)
Panel	Musculoskeletal
Define-AI ID	18050016
Originator	Musculoskeletal Panel
Panel Chair	Jay Patti
Panel Reviewers	Musculoskeletal Panel
License	Creative Commons 4.0
Status	Published

Clinical Implementation

Value Proposition

Injury is common but easily missed by nonspecialists. Nonspecialists would benefit from an algorithm that segments the joint and detects abnormality. AI meeting this use case would help to reduce the false negative rate, patient risk, and the medical legal risk for the radiologists.

Narrative(s)

A 25-year-old patient presents with foot trauma and an x-ray is taken in the emergency room. An algorithm evaluates the image and categorizes the joint as normal, abnormal, or undetermined. The radiologist is informed of this categorization at the time of interpretation.

Workflow Description

An image is obtained from a modality and sent to PACS and the AI engine. The image is analyzed by the engine. The system categorizes the Lisfranc joint as normal, abnormal, or uncertain. A message is sent to PACS from the engine with the classification information. If the location of the joint is also identified, the location information can also be sent to PACS to highlight the region the engine identified.

Considerations for Dataset Development

Procedures(s): X-ray, Lower Extremity

 

View(s): {AP, Oblique, Lateral}

 

Sex at Birth: {Male, Female}

 

Age: [15,90]

 

Anatomy Altering Conditions: {Diabetes, Charcot Joint}

 

Position: {weight bearing, non-weight bearing}

 

Weight: varied

Technical Specifications

Inputs

DICOM Study

Procedure	XRAY, Lower Extremity
Views	AP, Oblique, Lateral
Data Type	DICOM
Modality	XRAY
Body Region	Lower Extremity
Anatomic Focus	Foot

 

Primary Outputs

Lisfranc Joint Status

RadElement ID	RDE262
Definition	Status of Lisfranc joint
Data Type	Categorical
Value Set	0–Unknown 1–Normal 2–Abnormal
Units	N/A

Related Datasets

No known related public datasets at this time,  please us alert us if you know of any.