Prediction of lung adenocarcinoma without vessel invasion: a CT scan volumetric analysis.
OBJECTIVE
Patients with lung adenocarcinoma without vessel invasion have a favorable prognosis after resection and are among the candidates for limited surgery. The purpose of the present study was to predict lung adenocarcinoma without vessel invasion based on a volumetric analysis of the lesion with a CT scan prior to the operation.


METHODS
CT scan images were obtained in 288 consecutive patients with adenocarcinoma of the lung before surgical resection. Total tumor volume, the volume of the nonsolid component, and the proportion occupied by the nonsolid component were calculated by the perimeter method. The performance of the derived logistic regression model and the volumetric results were evaluated by receiver operating characteristic analysis. The model derived for the prediction of tumors without vessel invasion was assessed by means of the leave-one-out cross-validation technique.


RESULTS
The pathologic diagnosis was adenocarcinoma with vessel invasion in 160 cases, and without vessel invasion in 128 cases. The median total tumor volume, the median volume of the nonsolid component, and median proportion occupied by the nonsolid component were 1,123.7 mm(3), 253.4 mm(3), and 58.0%, respectively. With the derivation of the predictive rule, stepwise regression yielded the following five features: the proportion occupied by the nonsolid component; spiculation; pleural indentation; gender; and tumor size. The Az value, a measure of diagnostic power represented as the area under the curve, was 0.957 for prediction of lung adenocarcinoma without vessel invasion. The cross-validation accuracy achieved by applying the rule was 90.3%.


CONCLUSIONS
The proportion occupied by the nonsolid component based on a CT scan volumetric analysis was a reliable predictor of tumors without vessel invasion in patients with adenocarcinoma of the lung.
Tateishi
Ukihide
U
Division of Diagnostic Radiology, National Cancer Center Hospital, Tokyo, Japan. utateish@ncc.go.jp
Uno
Hajime
H
Yonemori
Kan
K
Satake
Mistuo
M
Takeuchi
Masahiro
M
Arai
Yasuaki
Y
D000230:Adenocarcinoma / Q000000981:diagnostic imaging* / Q000473:pathology; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D005260:Female; D006801:Humans; D016015:Logistic Models; D008175:Lung Neoplasms / Q000000981:diagnostic imaging* / Q000473:pathology; D008875:Middle Aged; D011379:Prognosis; D012372:ROC Curve; D014057:Tomography, X-Ray Computed