{"id":5583,"date":"2023-09-04T03:10:17","date_gmt":"2023-09-04T03:10:17","guid":{"rendered":"https:\/\/cm.vastapps.dev\/tcia-collection\/acrin-6664\/"},"modified":"2023-09-13T11:58:25","modified_gmt":"2023-09-13T11:58:25","slug":"acrin-6664","status":"publish","type":"tcia_collection","link":"https:\/\/cm.vastapps.dev\/tcia-collection\/acrin-6664\/","title":{"rendered":"ACRIN-6664"},"featured_media":0,"template":"","citation-tax":[],"cancer_types":["Colon Cancer"],"citations":[4444,4445,2925],"collection_doi":"10.7937\/K9\/TCIA.2015.NWTESAY1","collection_download_info":"Click the Versions tab for more info about data releases.","collection_downloads":[4991,4992,4993,4994,4995],"full_export":"

Summary<\/h2>

The National CT Colonography Trial (ACRIN 6664) collection contains 825 cases of CT colonography imaging with accompanying spreadsheets that provide polyp descriptions and their location within the colon segments.\u00a0 Additional information about the trial is available in the Study Protocol<\/a> and Case Report Forms<\/a>.<\/p>

Main Objective:<\/strong>\u00a0<\/span>To clinically validate widespread use of computerized tomographic colonography (CTC) in a screening population for the detection of colorectal neoplasia.<\/p>

Participants:<\/strong>\u00a0Male and female outpatients, aged 50 years or older, scheduled\u00a0for screening colonoscopy, who have not had a colonoscopy in the past five years.<\/p>

Study Design Summary:<\/strong>\u00a0<\/span>The study addresses aspects of central importance to the clinical application of CTC in several interrelated but independent parts that will be conducted in parallel. In Part I, the clinical performance of the CTC examination will be prospectively compared in a blinded fashion to colonoscopy. In Part II, optimization of the CT technique will be performed in view of new technological advances in CT technology. In Part III, lesion detection will be\u00a0optimized by studying the morphologic features of critical lesion types and in\u00a0the development of a database for computer-assisted diagnosis. In Part IV,\u00a0patient preferences and cost-effectiveness implications of observed performance\u00a0outcomes will be evaluated using a predictive model.<\/p>