title: Differentiation of lung neoplasms with lepidic growth and good prognosis from those with poor prognosis using computer-aided 3D volumetric CT analysis and FDG-PET.
abstract: BACKGROUND
  Many studies have reported that transverse computed tomography (CT) imaging findings correlate with prognosis of patients with small peripheral lung neoplasm with lepidic growth. However, no studies have examined this correlation with the aid of three-dimensional (3D) CT data.
  
  
  OBJECTIVE
  To determine the most efficacious imaging factor for differentiation of lepidic growth type lung neoplasms with good prognosis from those with poor prognosis.
  
  
  METHODS
  We evaluated CT findings, nodule patterns, SUVmax on FDG-PET/CT, as well as nodule volume and ratios of solid parts to nodule volume that were semi-automatically measured on CT images of 64 pulmonary nodules of ≤ 2 cm in 60 consecutive patients (24 men and 36 women; mean age, 65 years). For logistic modeling, we used all of the significant factors observed between the neoplasms with good and with poor prognosis as independent variables to estimate the statistically significant factors for discriminating invasive adenocarcinomas with lepidic growth (lesions with poor prognosis, n=42) from the other neoplasms, including preinvasive lesions (lesions with good prognosis, n=22), resulting in a recommendation for the optimal criterion for predicting lesions with poor prognosis.
  
  
  RESULTS
  The logistic regression model identified the ratio of the solid part to the whole volume of a pulmonary nodule as the only significant factor (P=0.04) for differentiating lepidic growth type lung neoplasms with good prognosis from those with poor prognosis. A ratio of 0.238 or more showed the highest discriminatory accuracy of 84% with 91% sensitivity and 76% specificity.
  
  
  CONCLUSIONS
  Computer-aided analyses of pulmonary nodules proved most useful for establishing the optimal criterion for differentiation of lepidic growth type lung neoplasms with good prognosis from those with poor prognosis.
authors.affiliation: Osaka University Graduate School of Medicine, Division of Allied Health Sciences, Department of Diagnostic Radiological Imaging, Osaka, Japan m.daisuke@cure.ocn.ne.jp.
authors.forename: Daisuke
authors.initials: D
authors.lastname: Morimoto
authors.affiliation: Osaka University Graduate School of Medicine, Division of Allied Health Sciences, Department of Diagnostic Radiological Imaging, Osaka, Japan.
authors.forename: Shodayu
authors.initials: S
authors.lastname: Takashima
authors.affiliation: Osaka Medical Center for Cancer and Cardiovascular Diseases, Osaka, Japan.
authors.forename: Naohiro
authors.initials: N
authors.lastname: Sakashita
authors.affiliation: Osaka University Graduate School of Medicine, Department of Radiology, Osaka, Japan.
authors.forename: Yoshinobu
authors.initials: Y
authors.lastname: Sato
authors.affiliation: Osaka University Graduate School of Medicine, Division of Allied Health Sciences, Department of Diagnostic Radiological Imaging, Osaka, Japan.
authors.forename: Binghu
authors.initials: B
authors.lastname: Jiang
authors.affiliation: Osaka University Graduate School of Medicine, Division of Allied Health Sciences, Department of Diagnostic Radiological Imaging, Osaka, Japan.
authors.forename: Tomoaki
authors.initials: T
authors.lastname: Hakucho
authors.affiliation: Osaka University Graduate School of Medicine, Division of Allied Health Sciences, Department of Diagnostic Radiological Imaging, Osaka, Japan.
authors.forename: Chie
authors.initials: C
authors.lastname: Miyake
authors.affiliation: Osaka University Graduate School of Medicine, Division of Allied Health Sciences, Department of Diagnostic Radiological Imaging, Osaka, Japan.
authors.forename: Yoshiyuki
authors.initials: Y
authors.lastname: Takahashi
authors.affiliation: Osaka Medical Center for Cancer and Cardiovascular Diseases, Osaka, Japan.
authors.forename: Yasuhiko
authors.initials: Y
authors.lastname: Tomita
authors.affiliation: Osaka Medical Center for Cancer and Cardiovascular Diseases, Osaka, Japan.
authors.forename: Katsuyuki
authors.initials: K
authors.lastname: Nakanishi
authors.affiliation: Morinomiya Clinic, Osaka, Japan.
authors.forename: Takuya
authors.initials: T
authors.lastname: Hosoki
authors.affiliation: Osaka Medical Center for Cancer and Cardiovascular Diseases, Osaka, Japan.
authors.forename: Masahiko
authors.initials: M
authors.lastname: Higashiyama
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D054893:Cone-Beam Computed Tomography / Q000379:methods; D003937:Diagnosis, Differential; D005260:Female; D019788:Fluorodeoxyglucose F18; D006801:Humans; D021621:Imaging, Three-Dimensional; D008175:Lung Neoplasms / Q000000981:diagnostic imaging* / Q000473:pathology; D008297:Male; D008875:Middle Aged; D049268:Positron-Emission Tomography / Q000379:methods*; D011379:Prognosis; D019275:Radiopharmaceuticals; D012189:Retrospective Studies; D003074:Solitary Pulmonary Nodule / Q000000981:diagnostic imaging* / Q000473:pathology; D014057:Tomography, X-Ray Computed / Q000379:methods*
chemical_list: D019275:Radiopharmaceuticals; D019788:Fluorodeoxyglucose F18
keywords: Lung cancer; PET/CT; SUVmax; adenocarcinoma; computer-aided diagnosis