Literature DB >> 10485238

New classification of small pulmonary nodules by margin characteristics on high-resolution CT.

K Furuya1, S Murayama, H Soeda, J Murakami, Y Ichinose, H Yabuuchi, Y Katsuda, M Koga, K Masuda.   

Abstract

PURPOSE: To analyze margin characteristics of pulmonary nodules on high-resolution CT (HRCT) in order to improve imaging diagnoses.
MATERIAL AND METHODS: HRCT images of 193 pulmonary nodules of less than 30 mm maximum diameter (113 primary cancers, 15 metastatic cancers, 55 inflammatory nodules, and 10 benign tumors) were reviewed and classified as to 6 types of margins: round, lobulated, densely spiculated, ragged, tentacle or polygonal and halo. The relationships of these imaging types to the diagnoses, the underlying pathological features, mainly those of tumor growth patterns in 93 neoplasms, and the pathological characteristics of 14 inflammatory nodules were investigated.
RESULTS: Eighty-two percent of the lobulated, 97% of the densely spiculated, 93% of the ragged and 100% of the halo nodules were malignant. Eighty percent of the tentacle or polygonal nodules were inflammatory and 66% of the round ones were benign. The 6 types differed statistically as to the nature of the benignity/malignancy (p<0.001). Pathologically, in case of neoplasms, most of the 6 types had a relationship to a particular tumor growth pattern.
CONCLUSION: This HRCT classification method is useful for determining the nature of small pulmonary nodules and reflects the underlying pathological characteristics.

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Mesh:

Year:  1999        PMID: 10485238     DOI: 10.3109/02841859909175574

Source DB:  PubMed          Journal:  Acta Radiol        ISSN: 0284-1851            Impact factor:   1.990


  22 in total

1.  Solitary pulmonary nodules and masses: a meta-analysis of the diagnostic utility of alternative imaging tests.

Authors:  Paul Cronin; Ben A Dwamena; Aine Marie Kelly; Steven J Bernstein; Ruth C Carlos
Journal:  Eur Radiol       Date:  2008-07-08       Impact factor: 5.315

2.  Quantitative MDCT analysis of pulmonary solid nodules using three parameters.

Authors:  Naoki Kutuya; Yutaka Ozaki; Yoshihisa Kurosaki
Journal:  Radiat Med       Date:  2008-09-04

Review 3.  [Characterization and management of incidentally detected solitary pulmonary nodules].

Authors:  C Menzel; O W Hamer
Journal:  Radiologe       Date:  2010-01       Impact factor: 0.635

4.  Computer-aided diagnosis systems for lung cancer: challenges and methodologies.

Authors:  Ayman El-Baz; Garth M Beache; Georgy Gimel'farb; Kenji Suzuki; Kazunori Okada; Ahmed Elnakib; Ahmed Soliman; Behnoush Abdollahi
Journal:  Int J Biomed Imaging       Date:  2013-01-29

5.  Toward Understanding the Size Dependence of Shape Features for Predicting Spiculation in Lung Nodules for Computer-Aided Diagnosis.

Authors:  Ron Niehaus; Daniela Stan Raicu; Jacob Furst; Samuel Armato
Journal:  J Digit Imaging       Date:  2015-12       Impact factor: 4.056

Review 6.  [Management of solid pulmonary nodules].

Authors:  F Poschenrieder; L Beyer; B Rehbock; S Diederich; D Wormanns; C Stroszczynski; O W Hamer
Journal:  Radiologe       Date:  2014-05       Impact factor: 0.635

7.  What CT characteristics of lepidic predominant pattern lung adenocarcinomas correlate with invasiveness on pathology?

Authors:  Emily A Aherne; Andrew J Plodkowski; Joseph Montecalvo; Sumar Hayan; Junting Zheng; Marinela Capanu; Prasad S Adusumilli; William D Travis; Michelle S Ginsberg
Journal:  Lung Cancer       Date:  2018-02-03       Impact factor: 5.705

8.  Prediction of pulmonary metastasis in pulmonary nodules (≤10 mm) detected in patients with primary extrapulmonary malignancy at thin-section staging CT.

Authors:  Qiuxia Yang; Yiqi Wang; Xiaohua Ban; Jing Wu; Dailin Rong; Qianqian Zhao; Chuanmiao Xie; Rong Zhang
Journal:  Radiol Med       Date:  2017-07-18       Impact factor: 3.469

9.  Hybrid models for lung nodule malignancy prediction utilizing convolutional neural network ensembles and clinical data.

Authors:  Rahul Paul; Matthew B Schabath; Robert Gillies; Lawrence O Hall; Dmitry B Goldgof
Journal:  J Med Imaging (Bellingham)       Date:  2020-04-06

10.  Limited value of ⁹⁹mTc depreotide single photon emission CT compared with CT for the evaluation of pulmonary lesions.

Authors:  S W Harders; H H Madsen; K Hjorthaug; M Rehling; T R Rasmussen; U Pedersen; H K Pilegaard; P Meldgaard; U T Baandrup; F Rasmussen
Journal:  Br J Radiol       Date:  2012-07       Impact factor: 3.039

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