title: CT screening and follow-up of lung nodules: effects of tube current-time setting and nodule size and density on detectability and of tube current-time setting on apparent size.
abstract: OBJECTIVE
  The purpose of the study was to quantify and compare the effect of CT dose and of size and density of nodules on the detectability of lung nodules and to quantify the influence of CT dose on the size of the nodules.
  
  
  METHODS
  From 50 patients a total of 125 cuboidal regions of interest (3 × 3 × 1.5 cm volumes) showing a single nodule (≤ 8 mm) and 27 normal cuboids were selected. Image sets were reconstructed with the software from raw data simulating different dose levels: 300 (original dose), 220, 180, 140, 100, 80, 60, 50, 40, 30, 20, 10, and 5 reference mAs. A logistic regression model was used to analyze detectability for three blinded readers. Odds ratios were calculated for nodule size smaller than 3 mm versus 3 mm and larger and for nodule attenuation of -300 HU and greater versus less than -300 HU.
  
  
  RESULTS
  Tube current-time settings of 10 mAs and greater were not associated with a significant difference in individual reader sensitivity compared with the standard setting of 300 mAs. At 5 mAs only one reader had a significant decrease in sensitivity, from 82% to 77% (p = 0.0035). According to the odds ratios and logistic regression results, the strongest negative effect on sensitivity can be assumed for low nodule density followed by small nodule size and dose level. The mean nodule volume measurement error between 5 and 300 mAs was 2.2% ± 18% (SD) and much lower than the interobserver volume measurement error rate of 38% ± 45%.
  
  
  CONCLUSIONS
  The results show the feasibility of a low-dose CT protocol at 10 mAs for follow-up of lung nodules. Computer-aided volume measurement in follow-up of lung nodules decreases interobserver variability.
authors.affiliation: Department of Radiology, Stanford University School of Medicine, Stanford, CA, USA. andreas.christe@insel.ch
authors.forename: Andreas
authors.initials: A
authors.lastname: Christe
authors.forename: Jaled Charimo
authors.initials: JC
authors.lastname: Torrente
authors.forename: Margaret
authors.initials: M
authors.lastname: Lin
authors.forename: Andrew
authors.initials: A
authors.lastname: Yen
authors.forename: Rich
authors.initials: R
authors.lastname: Hallett
authors.forename: Kingshuk
authors.initials: K
authors.lastname: Roychoudhury
authors.forename: Florian
authors.initials: F
authors.lastname: Schmitzberger
authors.forename: Peter
authors.initials: P
authors.lastname: Vock
authors.forename: Justus
authors.initials: J
authors.lastname: Roos
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D005240:Feasibility Studies; D005260:Female; D005500:Follow-Up Studies; D006801:Humans; D016015:Logistic Models; D008175:Lung Neoplasms / Q000000981:diagnostic imaging* / Q000473:pathology; D008297:Male; D008875:Middle Aged; D011446:Prospective Studies; D011829:Radiation Dosage; D011857:Radiographic Image Interpretation, Computer-Assisted; D012680:Sensitivity and Specificity; D012984:Software; D003074:Solitary Pulmonary Nodule / Q000000981:diagnostic imaging* / Q000473:pathology; D013997:Time Factors; D014057:Tomography, X-Ray Computed / Q000379:methods*