Helical liver CT with computer-assisted bolus-tracking technology: is it possible to predict which patients will not achieve a threshold of enhancement?
PURPOSE: To determine how often a prescribed threshold of hepatic contrast material enhancement is not reached at helical computed tomography (CT) of the liver in patients in a tertiary teaching hospital-based practice and which variables are predictive of failure. MATERIALS AND METHODS: Hepatic helical CT was performed in 250 consecutive patients with computer-assisted bolus-tracking technology after either mechanical injection at 3 mL/sec (n = 177) or manual injection (n = 73) of 150 mL of iopamidol. Demographic variables were recorded. After 17 seconds, low-milliamperage monitoring scans were obtained every 6 seconds until hepatic enhancement of 50 HU over baseline was achieved. Time-enhancement curves were reviewed. RESULTS: The threshold was not reached by 60 seconds in 88 patients (35%; default group). The success and default groups were similar in most variables and differed only in weight (P = .002), patient status (inpatient, outpatient, or emergency department; P < .001), and injection type (mechanical vs manual; P < .001). Ten patients (4%) did not achieve the threshold because of inappropriate placement of elliptic regions of interest. CONCLUSION: By using computer-assisted bolus-tracking technology, 35% of patients in a tertiary teaching hospital-based practice will not achieve a threshold of 50 HU above baseline by 60 seconds after injection initiation and will require the use of a set delay. Failures are more frequent in patients who are heavy and in inpatients. No historic or demographic factors are strongly predictive of failure.[1]References
- Helical liver CT with computer-assisted bolus-tracking technology: is it possible to predict which patients will not achieve a threshold of enhancement? Paulson, E.K., Fisher, A.J., DeLong, D.M., Parker, D.D., Nelson, R.C. Radiology. (1998) [Pubmed]
Annotations and hyperlinks in this abstract are from individual authors of WikiGenes or automatically generated by the WikiGenes Data Mining Engine. The abstract is from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.About WikiGenesOpen Access LicencePrivacy PolicyTerms of Useapsburg
