Colon Polyp Detection

Purpose

Detect polyps greater than six millimeters 

Tag(s)

#C-RADS

Panel

Abdominal

TOUCH-AI ID

TAI-02180002

Originator

Beth McFarland

Panel Chair

Arun Krishnaraj

Panel Reviewers

Abdominal Panel

License

Creative Commons 4.0

Status Public Commenting
                               

Clinical Implementation


Value Proposition

Colorectal polyps are precursors to cancer that can be detected with imaging and then removed by optical colonoscopy to prevent cancer development. CT colonography (CTC) provides a minimally invasive structural exam of the colon and rectum to detect clinically significant polyps; however, less experienced radiologists can miss polyps and take excessive time to complete the exam. AI could help improve accuracy and efficiency of polyp detection at CTC, reduce false positives, and reduce medical legal risk for radiologists.

Narrative(s)

A 50-year-old patient presents for first-time colorectal screening by CTC. An algorithm evaluates the colon for detection of polyps larger than 6 mm in maximal diameter. The radiologist is informed of this categorization at the time of the interpretation.

Workflow Description

Images are obtained by CT and sent to the 3D workstation/PACS and AI engine. Images are analyzed by the engine. The size, number, and location of polyps larger than 6 mm are identified. A message is sent to PACS from the engine with the classification information.

Considerations for Dataset Development


Procedures(s): {CT colonography, pelvis/abdomen, low dose screening, without contrast}

View(s): {Supine, prone, right lateral decubitus, left lateral decubitus}

Indication: Colorectal screening

 

Colon Anatomy: {Nonredundant, redundant, very redundant}

Colon Surgery: Colon segments excised

 

Inflammatory Bowel Disease: {Crohn disease, ulcerative colitis}

 

Tagging: Stool tagging

Technical Specifications


Inputs

DICOM Study

Procedure

CT colonography, pelvis/abdomen, low-dose screening, without contrast

Views

Supine, prone, right lateral decubitus, left lateral decubitus

Data Type

DICOM

Modality

CT

Body Region

Abdomen

Anatomic Focus

Colon

 

Primary Outputs

Polyp Detection (>6 mm)

RadElement ID

RDE206

Definition

Detection of polyps ≥ 6 mm

Data Type

Categorical

Value Set

0–Unknown 

1–Zero polyps > 6 mm

2–One polyp > 6 mm

3–Two or more polyps > 6 mm

Units

N/A

Public Commenting


Use cases are meant to be a primary vehicle for distributing clinical information to the developer community. They pinpoint precise scenarios within radiology workflows where potential automation could add noticeable value and establish standards for interpreting and passing corresponding common data elements. Implementing effective standards requires the perspective from all stakeholders. So to that end, we encourage your feedback on use cases.

To submit comments, please email DSIUseCases@acr.org with the use case title(s) and relevant comments by January 1, 2019. If more convenient, you may also download this use case and comment directly on the PDF. Just attach the PDF copy on the email.