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. 2016 Jul;46(7):681-6.
doi: 10.1093/jjco/hyw053. Epub 2016 May 12.

Clinicopathological characteristics of lung cancer mimicking organizing pneumonia on computed tomography-a novel radiological entity of pulmonary malignancy

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Clinicopathological characteristics of lung cancer mimicking organizing pneumonia on computed tomography-a novel radiological entity of pulmonary malignancy

Tomohiro Ichikawa et al. Jpn J Clin Oncol. 2016 Jul.

Abstract

Objective: Lung cancer could be misdiagnosed as benign due to its atypical radiological findings or difficulty in the histological diagnosis. We intended to elucidate the clinicopathological features of such lung cancers.

Methods: Between 2008 and 2011, we performed surgical resection for 564 consecutive patients with lung adenocarcinoma. Findings on thin-section computed tomography were reviewed for all patients, 13 of whom were found to have lung cancer mimicking organizing pneumonia. The radiological and clinicopathological features of lung cancer mimicking organizing pneumonia and other adenocarcinomas were evaluated.

Results: Among 13 patients with lung cancer mimicking organizing pneumonia, 4 were men. The median age was 70 years (range 62-81 years). Six patients were followed up for more than 1 year (range 1-108 months) as their lesions were misdiagnosed as organizing pneumonia. Preoperative carcinoembryonic antigen was significantly high (P = 0.025), and maximum tumor dimension was significantly large for lung cancer mimicking organizing pneumonia (30 vs. 23.6 mm, P = 0.001). Pathologically, there was no vascular invasion (P = 0.012) and only one lymphatic invasion (P = 0.064). One case of lymph node metastasis to the N2 node was found due to misdiagnosis as organizing pneumonia for 9 years.

Conclusions: Basically, lung cancer mimicking organizing pneumonia was less invasive and showed slow growth. However, nodal metastasis could be found. Thus, radiological diagnosis based on the findings of thin-section computed tomography is valuable to avoid delay in diagnosis.

Keywords: computed tomography; diagnosis; lung cancer.

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