Linked Life Data

8246327

Source:http://linkedlifedata.com/resource/pubmed/id/8246327

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
4
pubmed:dateCreated
1994-1-6
pubmed:abstractText
To meaningfully evaluate factors determining the overall accuracy of computed tomography (CT) for identifying pulmonary nodules, computer-generated nodules were superimposed on normal CT scans and interpreted independently by three experienced chest radiologists. Variables evaluated included nodule size, shape, number, density, location, edge characteristics, and relationship to adjacent vessels, as well as technical factors, including slice thickness and electronic windowing. The overall sensitivity in identifying nodules was 62% and the specificity was 80%. On average, the observers identified 56, 67, and 63% of nodules on 1.5-, 5-, and 10-mm-thick sections, respectively (p = 0.037). Nodules were more difficult to identify on 1.5-mm-thick sections. On average, observers identified 1, 48, 82, and 91% of nodules < 1.5, < 3, < 4.5, and < 7 mm in diameter, respectively (p < 0.001). Other factors that made a significant contribution (p < 0.01) in identifying nodules, as determined by linear discriminant function analysis, included nodule location, angiocentricity, and density. We concluded that computer-generated nodules can be used to assess a large number of imaging variables. We anticipate that this approach will be of considerable utility in assessing the accuracy of interpretation of a wide range of pathologic entities as well as in optimizing three-dimensional scan protocols within the thorax.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:issn
0883-5993
pubmed:author
pubmed:issnType
Print
pubmed:volume
8
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
291-9
pubmed:dateRevised
2008-11-21
pubmed:meshHeading
pubmed:year
1993
pubmed:articleTitle
Variables affecting pulmonary nodule detection with computed tomography: evaluation with three-dimensional computer simulation.
pubmed:affiliation
Department of Radiology, New York University Medical Center, Bellevue Hospital, NY 10016.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't