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Three-dimensional computerized quantification for lung invasive adenocarcinoma with different histopathological subtypes in clinical stage Ⅰ

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Author:
No author available
Journal Title:
Chinese Journal of Radiology
Issue:
4
DOI:
10.3760/cma.j.issn.1005-1201.2015.04.008
Key Word:
肺肿瘤;腺癌;体层摄影术,X线计算机;病理学;Lung neoplasms;Adenocarcinoma;Tomography,X-ray computed;Pathology

Abstract: Objective To study three-dimensional computerized quantification for clinical stage Ⅰ lung invasive adenocarcinoma with different histopathological subtypes.Methods Pathological and HRCT data of 273 patients within clinical stage Ⅰ lung invasive adenocarcinoma underwent surgery from January 2005 to December 2012 were retrospectively collected.The proportion of ground glass opacity component and solid component in tumor were calculated by three-dimensional computerized quantification.All specimens were classified into 3 grades (grade 1 as the lepidic pattern of invasive adenocarcinoma,grade 2 acinar or papillary patterns,grade 3 micropapillary or solid patterns).The proportion of different components among different histopathological grades was evaluated by Kruskal-Wallis test.The correlation between components in tumor and histopathologic subtypes grade were evaluated by Spearman correlation.Results In 273 patients,49(17.9%) were assessed as grade 1,208(76.2%) grade 2,and 16(5.9%) grade 3.The proportion of ground glass opacity component and solid component in grade 1,grade 2,and grade 3 were 18.40% (10.00%-33.45%),6.55% (2.00%-18.00%),1.70% (0.20%-3.85%) and 29.80% (11.75%-47.35%),66.60% (35.40%-83.85%),88.50% (75.28%-93.60%),respectively.Significant differences among different histopathological grades were observed(x2=37.74,47.73,P<0.01).The proportion of ground glass opacity component was negative correlation with histopathologic grade(r=-0.37,P<0.01),while the proportion of solid component was positive correlation with histopathologie grade(r=0.42,P<0.01).Conclusion Three-dimensional computerized quantification for lung invasive adenocarcinoma may predict histopathological grade.

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