Prognostic importance of volumetric measurements in stage I lung adenocarcinoma.

PURPOSE To perform volumetric analysis of stage I lung adenocarcinomas by using an automated computer program and to determine value of volumetric computed tomographic (CT) measurements associated with prognostic factors and outcome. MATERIALS AND METHODS Consecutive patients (n = 145) with stage I lung adenocarcinoma who underwent surgery after preoperative chest CT were enrolled. By using volumetric automated computer-assisted analytic program, nodules were classified into three subgroups: pure ground glass, part solid, or solid. Total tumor volume, solid tumor volume, and percentage of solid volume of each cancer were calculated after eliminating vessel components. One radiologist measured the longest diameter of the solid tumor component and of total tumor with their ratio, which was defined as solid proportion. The value of these quantitative data by examining associations with pathologic prognostic factors and outcome measures (disease-free survival and overall survival) were analyzed with logistic regression and Cox proportional hazards regression models, respectively. Significant parameters identified at univariate analysis were included in the multiple analyses. RESULTS All 22 recurrences occurred in patients with nodules classified as part solid or solid. Multiple logistic regression analysis revealed that percentage of solid volume of 63% or greater was an independent indicator associated with pleural invasion (P = .01). Multiple Cox proportional hazards regression analysis revealed that percentage of solid volume of 63% or greater was a significant indicator of lower disease-free survival (hazard ratio, 18.45 [95% confidence interval: 4.34, 78.49]; P < .001). Both solid tumor volume of 1.5 cm(3) or greater and percentage of solid volume of 63% or greater were significant indicators of decreased overall survival (hazard ratio, 5.92 and 9.60, respectively [95% confidence interval: 1.17, 30.33 and 1.17, 78.91, respectively]; P = .034 and .036, respectively). CONCLUSION Two volumetric measurements (solid volume, ≥1.5 cm(3); percentage of solid volume, ≥63%) were found to be independent indicators associated with increased likelihood of recurrence and/or death in patients with stage I adenocarcinoma.

[1]  Kenji Suzuki,et al.  The size of consolidation on thin-section computed tomography is a better predictor of survival than the maximum tumour dimension in resectable lung cancer. , 2013, European journal of cardio-thoracic surgery : official journal of the European Association for Cardio-thoracic Surgery.

[2]  Anthony P. Reeves,et al.  THREE-DIMENSIONAL MULTICRITERION AUTOMATIC SEGMENTATION OF PULMONARY NODULES OF HELICAL COMPUTED TOMOGRAPHY IMAGES , 1999 .

[3]  Mathias Prokop,et al.  Pulmonary ground-glass nodules: increase in mass as an early indicator of growth. , 2010, Radiology.

[4]  J. Arenas-Jiménez.  Measurement of solid component in part-solid lesions with a mediastinal window setting? , 2013, Radiology.

[5]  M. Noguchi.  Stepwise progression of pulmonary adenocarcinoma—clinical and molecular implications , 2010, Cancer and Metastasis Reviews.

[6]  Antoni B. Chan,et al.  On measuring the change in size of pulmonary nodules , 2006, IEEE Transactions on Medical Imaging.

[7]  T. Trikalinos,et al.  Comparison of the diagnostic accuracy of lymphatic endothelium markers: Bayesian approach , 2005, Modern Pathology.

[8]  Kyung Soo Lee,et al.  Persistent pure ground-glass opacity lung nodules ≥ 10 mm in diameter at CT scan: histopathologic comparisons and prognostic implications. , 2013, Chest.

[9]  W. Willett,et al.  Misinterpretation and misuse of the kappa statistic. , 1987, American journal of epidemiology.

[10]  D. Naidich,et al.  Evaluation of individuals with pulmonary nodules: when is it lung cancer? Diagnosis and management of lung cancer, 3rd ed: American College of Chest Physicians evidence-based clinical practice guidelines. , 2013, Chest.

[11]  Wilhelm Burger,et al.  Digital Image Processing - An Algorithmic Introduction using Java , 2008, Texts in Computer Science.

[12]  Y. Kato,et al.  Prognostic significance of thin-section CT scan findings in small-sized lung adenocarcinoma. , 2008, Chest.

[13]  Y. Sakao,et al.  Lung adenocarcinoma can be subtyped according to tumor dimension by computed tomography mediastinal-window setting. Additional size criteria for clinical T1 adenocarcinoma. , 2004, European journal of cardio-thoracic surgery : official journal of the European Association for Cardio-thoracic Surgery.

[14]  Binsheng Zhao,et al.  Small pulmonary nodules: volumetrically determined growth rates based on CT evaluation. , 2000, Radiology.

[15]  Noriyuki Tomiyama,et al.  Automated assessment of malignant degree of small peripheral adenocarcinomas using volumetric CT data: correlation with pathologic prognostic factors. , 2010, Lung cancer.

[16]  Ugo Pastorino,et al.  Pulmonary nodules: volume repeatability at multidetector CT lung cancer screening. , 2009, Radiology.

[17]  Guido Gerig,et al.  Three-dimensional multi-scale line filter for segmentation and visualization of curvilinear structures in medical images , 1998, Medical Image Anal..

[18]  O. Honda,et al.  One-dimensional quantitative evaluation of peripheral lung adenocarcinoma with or without ground-glass opacity on thin-section CT images using profile curves. , 2009, The British journal of radiology.

[19]  Margrit Betke,et al.  Small pulmonary nodules: volume measurement at chest CT--phantom study. , 2003, Radiology.

[20]  G. Chatellier,et al.  Pulmonary nodules: preliminary experience with three-dimensional evaluation. , 2004, Radiology.

[21]  Yong Soo Choi,et al.  Malignant Pure Pulmonary Ground-Glass Opacity Nodules: Prognostic Implications , 2009, Korean journal of radiology.

[22]  池原 瑞樹.  Prognosis of small adenocarcinoma of the lung based on thin-section computed tomography and pathological preparations , 2007 .

[23]  L. Schwartz,et al.  Segmentation of lung lesions on CT scans using watershed, active contours, and Markov random field. , 2013, Medical physics.

[24]  H. Kato,et al.  Lung cancer patients showing pure ground-glass opacity on computed tomography are good candidates for wedge resection. , 2004, Lung cancer.

[25]  M. Okada,et al.  Prognostic significance of using solid versus whole tumor size on high-resolution computed tomography for predicting pathologic malignant grade of tumors in clinical stage IA lung adenocarcinoma: a multicenter study. , 2012, The Journal of thoracic and cardiovascular surgery.

[26]  Henry Rusinek,et al.  Pulmonary Nodules: growth rate assessment in patients by using serial CT and three-dimensional volumetry. , 2012, Radiology.

[27]  Charles E Willis,et al.  Measurement of CT radiation profile width using CR imaging plates. , 2005, Medical physics.

[28]  Y. Sakao,et al.  Prognostic significance of a histologic subtype in small adenocarcinoma of the lung: the impact of nonbronchioloalveolar carcinoma components. , 2007, The Annals of thoracic surgery.

[29]  M. L. R. D. Christenson,et al.  International Association for the Study of Lung Cancer/American Thoracic Society/European Respiratory Society International Multidisciplinary Classification of Lung Adenocarcinoma , 2012 .

[30]  Y. Sakao,et al.  Subtypes of peripheral adenocarcinoma of the lung: differentiation by thin-section CT , 2005, European Radiology.

[31]  M Thelen,et al.  Automatic detection and quantification of ground-glass opacities on high-resolution CT using multiple neural networks: comparison with a density mask. , 2000, AJR. American journal of roentgenology.

[32]  G Gamsu,et al.  CT-determined pulmonary artery diameters in predicting pulmonary hypertension. , 1984, Investigative radiology.

[33]  Jin Mo Goo,et al.  Pure and part-solid pulmonary ground-glass nodules: measurement variability of volume and mass in nodules with a solid portion less than or equal to 5 mm. , 2013, Radiology.

[34]  Athens Greece,et al.  Comparative evaluation of angiogenesis assessment with anti-factor-VIII and anti-CD31 immunostaining in non-small cell lung cancer. , 1997, Clinical cancer research : an official journal of the American Association for Cancer Research.

[35]  Marcos Salganicoff,et al.  Automated Volumetry of Solid Pulmonary Nodules in a Phantom: Accuracy Across Different CT Scanner Technologies , 2007, Investigative radiology.