Diagnostic accuracy of computed tomography imaging for the detection of differences between peripheral small cell lung cancer and peripheral non-small cell lung cancerReport as inadecuate




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International Journal of Clinical Oncology

pp 1–7

First Online: 09 May 2017Received: 04 January 2017Accepted: 02 May 2017DOI: 10.1007-s10147-017-1131-0

Cite this article as: Ren, Y., Cao, Y., Hu, W. et al. Int J Clin Oncol 2017. doi:10.1007-s10147-017-1131-0

Abstract

BackgroundTo evaluate the computed tomography features of peripheral small cell lung cancer and non-small cell lung cancer and to establish a predictive model to conveniently distinguish between them.

Materials and methodsWe retrospectively reviewed the computed tomography features of 51 patients with peripheral small cell lung cancer and 207 patients with peripheral non-small cell lung cancer after pathological diagnosis. Thirteen computed tomography morphologic findings were included and analyzed statistically. Meaningful features were analyzed by logistic regression for multivariate analysis. We then used β-coefficients as the basis to establish an image scoring prediction model.

ResultThe meaningful morphologic features for distinguishing between peripheral small cell lung cancer and other tumor types are multinodular shape and lymphadenectasis, with scores of 12 and 11, respectively. The scores ranged from −51 to 23, and the most reasonable cut-off was −24. The available area under the curve was 0.834 95% confidence interval CI 0.783–0.877. Sensitivity and specificity were 86.3% 95% CI 0.737–0.943 and 69.6% 95% CI 0.628–0.758, respectively.

ConclusionThe image scoring predictive model that we constructed provides a simple and economical noninvasive method for distinguishing between peripheral small cell lung cancer and peripheral non-small cell lung cancer.

KeywordsCT features Peripheral small cell lung cancer Peripheral non-small cell lung cancer Sensitivity Specificity AbbreviationsSCLCSmall cell lung cancer

NSCLCNon-small cell lung cancer

PSCLCPeripheral small cell lung cancer

PNSCLCPeripheral non-small cell lung cancer

95% CI95% Confidence interval

CTComputed tomography

MRIMagnetic resonance imaging

PETPositron emission tomography

NCFSNomenclature Committee of the Fleischner Society

ROCReceiver operating characteristics curves

AUCAvailable area under the curve

NCCNNational Comprehensive Cancer Network

Yanchen Ren and Yiyuan Cao contributed equally to this article.





Author: Yanchen Ren - Yiyuan Cao - Weidong Hu - Xiaoxuan Wei - Xiaoyan Shen

Source: https://link.springer.com/



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