title: Comparison of STIR turbo SE imaging and diffusion-weighted imaging of the lung: capability for detection and subtype classification of pulmonary adenocarcinomas.
abstract: OBJECTIVE
  The aim of the study was to evaluate the diagnostic performance of diffusion-weighted imaging (DWI) for detection and subtype classification in pulmonary adenocarcinomas through comparison with short TI inversion recovery turbo spin-echo imaging sequence (STIR).
  
  
  METHODS
  Thirty-two patients (mean age, 65.2 years) with 33 adenocarcinomas (mean diameter, 27.6 mm) were enrolled in this study. The detection rates of both sequences were compared. The ADC values on DWI and the contrast ratio (CR) between cancer and muscle on STIR were measured and those were compared across subtype classifications. Finally, ROC-based positive tests were performed to differentiate subtype classifications, and differentiation capabilities were compared.
  
  
  RESULTS
  The DWI detection rate [85% (28/33)] was significantly lower than that of STIR [100% (33/33), P < 0.05]. The ADC values showed no significant difference regarding subtype classification; however, the CRs of bronchio-alveolar carcinomas (BACs) were significantly lower than those of other types (P < 0.05). When threshold values for differentiating BACs from others were adapted, the sensitivity and accuracy of DWI were significantly lower than those of STIR (P < 0.05). For differentiating adenocarcinomas with mixed subtypes from those with no BA component, there were no significant differences between the two sequences.
  
  
  CONCLUSIONS
  STIR is more sensitive for detection and subtype classification than DWI.
authors.affiliation: Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Hyogo, Japan. hkoyama@med.kobe-u.ac.jp
authors.forename: Hisanobu
authors.initials: H
authors.lastname: Koyama
authors.forename: Yoshiharu
authors.initials: Y
authors.lastname: Ohno
authors.forename: Nobukazu
authors.initials: N
authors.lastname: Aoyama
authors.forename: Yumiko
authors.initials: Y
authors.lastname: Onishi
authors.forename: Keiko
authors.initials: K
authors.lastname: Matsumoto
authors.forename: Munenobu
authors.initials: M
authors.lastname: Nogami
authors.forename: Daisuke
authors.initials: D
authors.lastname: Takenaka
authors.forename: Wataru
authors.initials: W
authors.lastname: Nishio
authors.forename: Chiho
authors.initials: C
authors.lastname: Ohbayashi
authors.forename: Kazuro
authors.initials: K
authors.lastname: Sugimura
mesh_terms: D000230:Adenocarcinoma / Q000175:diagnosis*; D000368:Aged; D000465:Algorithms; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods*; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008168:Lung / Q000473:pathology*; D008175:Lung Neoplasms / Q000175:diagnosis*; D008297:Male; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity