RECRUITING

Project 1: Self-Triage by 2D Full-field Digital Mammography or Synthetic Images

Study Overview

This clinical trial focuses on testing the efficacy of different digital interventions to promote re-engagement in cancer-related long-term follow-up care for adolescent and young adult (AYA) survivors of childhood cancer.

Description

One method of breast cancer screening involves radiologists reading digital tomosynthesis (DBT) images. DBT consists of a 3D stack of x-ray "slices" through the breast. The exam is accompanied by a 2D image like a standard mammogram, a single x-ray of the breast. In a screening setting, most cases are normal. Sometimes it is obvious that a case is normal from a quick look at the 2D image. It would speed up the process of screening if readers could dismiss a clearly normal case on the basis of the 2D image, alone, without looking at the DBT images. Obviously, the investigators would only want to "triage" cases in this way if the investigators were almost perfectly sure that no cancers would be missed. In this study, the investigators look at radiologist's willingness to triage cases and on the accuracy of their answers. In addition, the investigators ask about the impact of an Artificial Intelligence (AI) opinion. Would it be possible to triage an image on the basis of the AI opinion, alone? Radiologists will look at each case for up to five seconds and offer an opinion (on a 1-10 scale) about how sure they are that a case is normal. Next, they will see the opinion of the AI. Finally, they will say (using a 1-10) scale, how willing they would be for the AI to triage this case without human intervention. This study is the start of an effort to understand the conditions under which radiologists might be willing to declare a case "normal" with little or no human examination.

Official Title

Project 1: Self-Triage by 2D Full-field Digital Mammography or Synthetic Images NOTE: Note, This is One Study Under Study ID 386408 Project 1: Radiologist Studies

Quick Facts

Study Start:2023-03-01
Study Completion:2028-09-01
Study Type:Not specified
Phase:Not Applicable
Enrollment:Not specified
Status:RECRUITING

Study ID

NCT05960188

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Ages Eligible for Study:18 Years
Sexes Eligible for Study:ALL
Accepts Healthy Volunteers:No
Standard Ages:ADULT, OLDER_ADULT
Inclusion CriteriaExclusion Criteria
  1. * Must be Radiologists or radiology trainees
  2. * some experience reading mammography.
  1. * acuity less than 20/25 with correction

Contacts and Locations

Study Contact

Jeremy M Wolfe, PhD
CONTACT
617-851-1166
jwolfe@bwh.harvard.edu
Ava A Mitra, BA
CONTACT
617-525-3681
amitra@bwh.harvard.edu

Study Locations (Sites)

Visual Attention Lab / Brigham and Women's Hospital
Boston, Massachusetts, 02215
United States

Collaborators and Investigators

Sponsor: Brigham and Women's Hospital

Study Record Dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Registration Dates

Study Start Date2023-03-01
Study Completion Date2028-09-01

Study Record Updates

Study Start Date2023-03-01
Study Completion Date2028-09-01

Terms related to this study

Keywords Provided by Researchers

  • Mammography
  • Digital Breast Tomosynthesis
  • Artificial Intelligence
  • Radiology
  • Medical Image Perception

Additional Relevant MeSH Terms

  • Breast Cancer Screening