Automated assessment of malignant degree of small peripheral adenocarcinomas using volumetric CT data: correlation with pathologic prognostic factors.

PURPOSE To evaluate a custom-developed software for analyzing malignant degrees of small peripheral adenocarcinomas on volumetric CT data compared to pathological prognostic factors. MATERIALS AND METHODS Forty-six adenocarcinomas with a diameter of 2cm or less from 46 patients were included. The custom-developed software can calculate the volumetric rates of solid parts to whole nodules even though solid parts show a punctate distribution, and automatically classify nodules into the following six types according to the volumetric rates of solid parts: type 1, pure ground-glass opacity (GGO); type 2, semiconsolidation; type 3, small solid part with a GGO halo; type 4, mixed type with an area that consisted of GGO and solid parts which have air-bronchogram or show a punctate distribution; type 5, large solid part with a GGO halo; and type 6, pure solid type. The boundary between solid portion and GGO on CT was decided using two threshold selection methods for segmenting gray-scale images. A radiologist also examined two-dimensional rates of solid parts to total opacity (2D%solid) which was already confirmed with previous reports. RESULTS There were good agreements between the classification determined by the software and radiologists (weighted kappa=0.778-0.804). Multivariate logistic regression analyses showed that both 2D%solid and computer-automated classification were significantly useful in estimating lymphatic invasion (p=0.0007, 0.0027), vascular invasion (p=0.003, 0.012), and pleural invasion (p=0.021, 0.025). CONCLUSION Using our custom-developed software, it is feasible to predict the pathological prognostic factors of small peripheral adenocarcinomas.

[1]  Kenji Suzuki,et al.  The proportion of consolidation to ground-glass opacity on high resolution CT is a good predictor for distinguishing the population of non-invasive peripheral adenocarcinoma. , 2003, Lung cancer.

[2]  H Nakata,et al.  Evolution of peripheral lung adenocarcinomas: CT findings correlated with histology and tumor doubling time. , 2000, AJR. American journal of roentgenology.

[3]  J M Bland,et al.  Statistical methods for assessing agreement between two methods of clinical measurement , 1986 .

[4]  Josef Kittler,et al.  Minimum error thresholding , 1986, Pattern Recognit..

[5]  Yoshihiro Matsuno,et al.  Surgically Curable “Early” Adenocarcinoma in the Periphery of the Lung , 1994, The American journal of surgical pathology.

[6]  K S Lee,et al.  Bronchioloalveolar carcinoma: focal area of ground-glass attenuation at thin-section CT as an early sign. , 1996, Radiology.

[7]  M. Okada,et al.  Effect of tumor size on prognosis in patients with non-small cell lung cancer: the role of segmentectomy as a type of lesser resection. , 2005, The Journal of thoracic and cardiovascular surgery.

[8]  K Kuriyama,et al.  Prognostic value of ground-glass opacity found in small lung adenocarcinoma on high-resolution CT scanning. , 2001, Lung cancer.

[9]  Hironobu Nakamura,et al.  Pulmonary adenocarcinomas with ground-glass attenuation on thin-section CT: quantification by three-dimensional image analyzing method. , 2008, European journal of radiology.

[10]  S. Sone,et al.  Prognostic significance of high-resolution CT findings in small peripheral adenocarcinoma of the lung: a retrospective study on 64 patients. , 2002, Lung cancer.

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

[12]  R. Read,et al.  Segmental pulmonary resection for cancer. , 1985, American journal of surgery.

[13]  Kenji Suzuki,et al.  Radiologic classification of small adenocarcinoma of the lung: radiologic-pathologic correlation and its prognostic impact. , 2006, The Annals of thoracic surgery.

[14]  A. Beckett,et al.  AKUFO AND IBARAPA. , 1965, Lancet.

[15]  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.

[16]  M. Revel,et al.  Are two-dimensional CT measurements of small noncalcified pulmonary nodules reliable? , 2004, Radiology.

[17]  K Kuriyama,et al.  Ground-glass opacity on thin-section CT: value in differentiating subtypes of adenocarcinoma of the lung. , 1999, AJR. American journal of roentgenology.

[18]  L. Garfinkel,et al.  The changing pattern of lung carcinoma , 1991, Cancer.

[19]  N. Otsu.  A threshold selection method from gray level histograms , 1979 .

[20]  Kenji Suzuki,et al.  "Early" peripheral lung cancer: prognostic significance of ground glass opacity on thin-section computed tomographic scan. , 2002, The Annals of thoracic surgery.

[21]  K. Nakata,et al.  Surgically curable peripheral lung carcinoma: correlation of thin-section CT findings with histologic prognostic factors and survival. , 2005, Chest.

[22]  S. Barsky,et al.  Rising incidence of bronchioloalveolar lung carcinoma and its unique clinicopathologic features , 1994, Cancer.

[23]  Y. Nishiwaki,et al.  Prognostic implications of fibrotic focus (scar) in small peripheral lung cancers , 1980, The American journal of surgical pathology.

[24]  K. Yasumoto,et al.  Peripheral lung adenocarcinoma: correlation of thin-section CT findings with histologic prognostic factors and survival. , 2001, Radiology.

[25]  C. Henschke.  Early lung cancer action project , 2000, Cancer.

[26]  J. Austin,et al.  Glossary of terms for CT of the lungs: recommendations of the Nomenclature Committee of the Fleischner Society. , 1996, Radiology.

[27]  H. Winer-Muram,et al.  Lung tumor growth: assessment with CT--comparison of diameter and cross-sectional area with volume measurements. , 2004, Radiology.

[28]  Setsuo Hirohashi,et al.  Small adenocarcinoma of the lung. Histologic characteristics and prognosis , 1995 .

[29]  Y. Nishiwaki,et al.  Prognostic significance of the size of central fibrosis in peripheral adenocarcinoma of the lung. , 2000, The Annals of thoracic surgery.

[30]  Morihito Okada,et al.  Discrepancy of computed tomographic image between lung and mediastinal windows as a prognostic implication in small lung adenocarcinoma. , 2003, The Annals of thoracic surgery.

[31]  Kiyoshi Mori,et al.  Objective definition and measurement method of ground-glass opacity for planning limited resection in patients with clinical stage IA adenocarcinoma of the lung. , 2004, European journal of cardio-thoracic surgery : official journal of the European Association for Cardio-thoracic Surgery.

[32]  K. S. Lee,et al.  Quantification of ground-glass opacity on high-resolution CT of small peripheral adenocarcinoma of the lung: pathologic and prognostic implications. , 2001, AJR. American journal of roentgenology.

[33]  D. Altman,et al.  STATISTICAL METHODS FOR ASSESSING AGREEMENT BETWEEN TWO METHODS OF CLINICAL MEASUREMENT , 1986, The Lancet.

[34]  Y. Nishiwaki,et al.  Favorable and unfavorable morphological prognostic factors in peripheral adenocarcinoma of the lung 3 cm or less in diameter. , 2000, Lung cancer.

[35]  N. Tsubota,et al.  Prospective study of extended segmentectomy for small lung tumors: the final report. , 2002, The Annals of thoracic surgery.