title: Chest CT at a dose below 0.3 mSv: impact of iterative reconstruction on image quality and lung analysis.
abstract: BACKGROUND
  In chest computed tomography (CT), iterative reconstruction (IR) algorithms maintain diagnostic image quality (IQ) while significantly reducing the dose.
  
  
  OBJECTIVE
  To evaluate the impact of IR on IQ of chest CT at effective doses below 0.3 mSv.
  
  
  METHODS
  Twenty chest CT scans performed at effective dose below 0.3 mSv (CT1) were reconstructed varying three parameters: filtered back-projection and IR iDose(4) algorithms; 512 × 512 and 768 × 768 matrices; and sharp and soft kernels, thus generating eight series per patient. The qualitative evaluation of the IQ was performed by ranking series from 1 to 8 (8 corresponding to the highest rank) which was subsequently compared to quantitative assessment of IQ by using an appropriated merit formula. Intra- and inter-reader IQ ranking reliability was also evaluated using Cohen's kappa. Analysis of lung findings was finally compared between the best CT1 series and the reference CT (CT0).
  
  
  RESULTS
  The best series in terms of qualitative and quantitative IQ was obtained using IR, 512(2) matrix and soft kernel. The best CT1 series detected nodules greater than 4 mm with an almost perfect match with CT0.
  
  
  CONCLUSIONS
  Chest CT performed at effective doses below 0.3 mSv may be used to confidently diagnose lesions greater than 4 mm using iDose(4), soft kernel and 512 × 512 matrix.
authors.affiliation: Department of Radiology, Lausanne University Hospital, Lausanne, Switzerland Chiaki.Nakajo@chuv.ch.
authors.forename: Chiaki
authors.initials: C
authors.lastname: Nakajo
authors.affiliation: Philips Healthcare, Zürich, Switzerland.
authors.forename: Susanne
authors.initials: S
authors.lastname: Heinzer
authors.affiliation: Philips Healthcare, Gland, Switzerland.
authors.forename: Stéphane
authors.initials: S
authors.lastname: Montandon
authors.affiliation: Department of Radiology, Lausanne University Hospital, Lausanne, Switzerland.
authors.forename: Vincent
authors.initials: V
authors.lastname: Dunet
authors.affiliation: Department of Radiology, Lausanne University Hospital, Lausanne, Switzerland.
authors.forename: Pierre
authors.initials: P
authors.lastname: Bize
authors.affiliation: Philips Healthcare, Haifa, Israel.
authors.forename: Andrei
authors.initials: A
authors.lastname: Feldman
authors.affiliation: Department of Radiology, Lausanne University Hospital, Lausanne, Switzerland.
authors.forename: Catherine
authors.initials: C
authors.lastname: Beigelman-Aubry
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008168:Lung / Q000000981:diagnostic imaging; D008175:Lung Neoplasms / Q000000981:diagnostic imaging*; D008297:Male; D008875:Middle Aged; D011829:Radiation Dosage; D011856:Radiographic Image Enhancement; D011857:Radiographic Image Interpretation, Computer-Assisted; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014057:Tomography, X-Ray Computed
keywords: Reduced dose chest computed tomography; image quality; iterative reconstruction; pulmonary nodules