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Assessment of Polyp and Mass Histopathology by Intravenous Contrast-Enhanced CT Colonography

  • Ronald M. Summers
  • , Adam Huang
  • , Jianhua Yao
  • , Shannon R. Campbell
  • , Jennifer E. Dempsey
  • , Andrew J. Dwyer
  • , Marek Franaszek
  • , Danny S. Brickman
  • , Ingmar Bitter
  • , Nicholas Petrick
  • , Amy K. Hara

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

Rationale and Objectives: We sought to demonstrate that intravenous contrast-enhanced CT colonography (CTC) can distinguish colonic adenomas from carcinomas. Methods: Supine intravenous contrast-enhanced CTC with colonoscopic and/or surgical correlation was performed on 25 patients with colonic adenomas or carcinomas. Standard deviation of mean polyp CT attenuation was computed and assessed using ANOVA and receiver-operating characteristic analyses. Results: Colonoscopy confirmed 32 polyps or masses 1 to 8 cm in size. The standard deviations of CT attenuation were carcinomas (n = 13; 36 ± 6 HU; range 28-48 HU) and adenomas (n = 19; 49 ± 14 HU; range 31-100 HU) (P = 0.005). At a standard deviation threshold of 42 HU, the sensitivity and specificity for classifying a polyp or mass as a carcinoma were 92% and 79%, respectively. The area under the receiver-operating characteristic curve was 0.89 ± 0.06 (95% confidence interval 0.73-0.96). Conclusions: Measurement of the standard deviation of CT attenuation on intravenous contrast-enhanced CTC permits histopathologic classification of polyps 1 cm or larger as carcinomas versus adenomas. The presence of ulceration or absence of muscular invasion in carcinomas creates overlap with adenomas, reducing the specificity of carcinoma classification.

Original languageEnglish
Pages (from-to)1490-1495
Number of pages6
JournalAcademic Radiology
Volume13
Issue number12
DOIs
StatePublished - Dec 2006

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • CT, 3D reconstruction
  • CT, colon
  • colon cancer
  • image processing
  • intravenous contrast enhancement

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