title: Dynamic contrast-enhanced CT in suspected lung cancer: quantitative results.
abstract: OBJECTIVE
  To examine whether dynamic contrast-enhanced CT (DCE-CT) could be used to characterise and safely distinguish between malignant and benign lung tumours in patients with suspected lung cancer.
  
  
  METHODS
  Using a quantitative approach to DCE-CT, two separate sets of regions of interest (ROIs) in tissues were placed in each tumour: large ROIs over the entire tumour and small ROIs over the maximally perfused parts of the tumour. Using mathematical modelling techniques and dedicated perfusion software, this yielded a plethora of results.
  
  
  RESULTS
  First, because of their non-normal distribution, DCE-CT measurements must be analysed using log scale data transformation. Second, there were highly significant differences between large ROI and small ROI measurements (p<0.001). Thus, the ROI method used in a given study should always be specified in advance. Third, neither quantitative parameters (blood flow and blood volume) nor semi-quantitative parameters (peak enhancement) could be used to distinguish between malignant and benign tumours. This was irrespective of the method of quantification used for large ROIs (0.13<p<0.76) and small ROIs (0.084<p<0.31). Fourth, although there were no indications of systematic reproducibility bias, the 95% limits of agreement were so broad that the risk of disagreement between the measurements could affect the clinical use of the measurements. This lack of reproducibility should be addressed. CONCLUSION AND ADVANCES IN KNOWLEDGE: A quantitative approach to DCE-CT is not a clinically usable method for characterising lung tumours.
authors.affiliation: Department of Radiology, Aarhus University Hospital, Aarhus, Denmark.
authors.forename: S W
authors.initials: SW
authors.lastname: Harders
authors.forename: H H
authors.initials: HH
authors.lastname: Madsen
authors.forename: H M
authors.initials: HM
authors.lastname: Nellemann
authors.forename: T R
authors.initials: TR
authors.lastname: Rasmussen
authors.forename: J
authors.initials: J
authors.lastname: Thygesen
authors.forename: H
authors.initials: H
authors.lastname: Hager
authors.forename: N T
authors.initials: NT
authors.lastname: Andersen
authors.forename: F
authors.initials: F
authors.lastname: Rasmussen
mesh_terms: D003937:Diagnosis, Differential; D006801:Humans; D008171:Lung Diseases / Q000000981:diagnostic imaging; D008175:Lung Neoplasms / Q000098:blood supply / Q000000981:diagnostic imaging*; D008954:Models, Biological; D011856:Radiographic Image Enhancement / Q000379:methods*; D015203:Reproducibility of Results; D014057:Tomography, X-Ray Computed / Q000379:methods*
references.citation: Lancet. 1986 Feb 8;1(8476):307-10
references.pmid: 2868172
references.citation: AJR Am J Roentgenol. 2006 Oct;187(4):1079-84
references.pmid: 16985160
references.citation: AJR Am J Roentgenol. 2011 Jul;197(1):113-21
references.pmid: 21701018
references.citation: Acad Radiol. 2000 Oct;7(10):840-50
references.pmid: 11048881
references.citation: Eur J Radiol. 1999 Jun;30(3):198-205
references.pmid: 10452718
references.citation: BMJ. 1996 Jul 6;313(7048):41-2
references.pmid: 8664775
references.citation: Br J Radiol. 2010 Sep;83(993):785-90
references.pmid: 20647512
references.citation: Lancet. 1991 Mar 16;337(8742):643-5
references.pmid: 1671994
references.citation: Radiology. 1993 Aug;188(2):405-11
references.pmid: 8327686
references.citation: Radiology. 1997 Nov;205(2):471-8
references.pmid: 9356631
references.citation: Lung Cancer. 2008 Jul;61(1):44-53
references.pmid: 18055062
references.citation: Radiology. 2006 May;239(2):547-53
references.pmid: 16543594
references.citation: Radiology. 2004 Oct;233(1):191-9
references.pmid: 15304661
references.citation: Clin Radiol. 2008 Jun;63(6):629-35
references.pmid: 18455553