Literature DB >> 36267266

Clinical and Computed Tomography Characteristics of Solitary Pulmonary Nodules Caused by Fungi: A Comparative Study.

Jin Jiang1, Zhuo-Ma Lv1,2, Fa-Jin Lv1, Bin-Jie Fu1, Zhang-Rui Liang1, Zhi-Gang Chu1.   

Abstract

Purpose: To clarify the clinical and computed tomography (CT) indicators in distinguishing pulmonary nodules caused by fungal infection from lung cancers.
Methods: From January 2013 to April 2022, 68 patients with solitary fungal nodules (64 were solid and 4 were mixed ground-glass nodules) and 140 cases with solid cancerous nodules with similar size were enrolled. Their clinical characteristics and CT manifestations of the solid nodules were summarized and compared, respectively.
Results: Compared with patients with lung cancers, cases were younger (51.2 ± 11.5 vs 61.3 ± 10.2 years) and non-smokers (72.1% vs 57.9%) and immunocompromised (44.1% vs 17.9%) individuals were more common in patients with fungal nodules (each P < 0.05). The air crescent sign (ACS) (34.4% vs 0%), halo sign (HS) (23.4% vs 4.3%), and satellite lesions (45.3% vs 2.9%) were more frequently detected in fungal nodules than in cancerous ones (each P < 0.05). Air bronchogram similarly occurred in fungal and cancerous nodules, whereas the natural ones were more common in the former (100% vs 16.7%, P = 0.000). However, the fungal nodules had a lower enhancement degree (29.0 ± 19.2 HU vs 40.3 ± 28.3 HU, P = 0.038) and frequency of hilar and/or mediastinal lymph node enlargement (2.9% vs 14.3%, P = 0.013) compared with the cancerous nodules.
Conclusion: In the younger, non-smoking and immunocompromised patients, a solitary pulmonary solid nodule with ACS, HS, satellite lesions and/or natural air bronchogram but without significant enhancement, fungal infection is a probable diagnosis.
© 2022 Jiang et al.

Entities:  

Keywords:  X-ray computed; fungal infection; pulmonary nodules; tomography

Year:  2022        PMID: 36267266      PMCID: PMC9576936          DOI: 10.2147/IDR.S382289

Source DB:  PubMed          Journal:  Infect Drug Resist        ISSN: 1178-6973            Impact factor:   4.177


  35 in total

1.  Solitary solid pulmonary nodules: a CT-based deep learning nomogram helps differentiate tuberculosis granulomas from lung adenocarcinomas.

Authors:  Bao Feng; XiangMeng Chen; YeHang Chen; SenLiang Lu; KunFeng Liu; KunWei Li; ZhuangSheng Liu; YiXiu Hao; Zhi Li; ZhiBin Zhu; Nan Yao; GuangYuan Liang; JiaYu Zhang; WanSheng Long; XueGuo Liu
Journal:  Eur Radiol       Date:  2020-06-27       Impact factor: 5.315

Review 2.  Infectious and Non-Infectious Diseases Causing the Air Crescent Sign: A State-of-the-Art Review.

Authors:  Joyce Betta Sevilha; Rosana Souza Rodrigues; Miriam Menna Barreto; Gláucia Zanetti; Bruno Hochhegger; Edson Marchiori
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Journal:  Quant Imaging Med Surg       Date:  2022-01

Review 4.  Evaluating the Patient With a Pulmonary Nodule: A Review.

Authors:  Peter J Mazzone; Louis Lam
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Review 5.  Global Epidemiology of Lung Cancer.

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Journal:  Ann Glob Health       Date:  2019-01-22       Impact factor: 2.462

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Journal:  J Cardiothorac Surg       Date:  2019-03-12       Impact factor: 1.637

7.  Comparison of CT findings and histopathological characteristics of pulmonary cryptococcosis in immunocompetent and immunocompromised patients.

Authors:  Dong-Xu Wang; Qing Zhang; Qiu-Ting Wen; Guo-Xu Ding; Yu-Guang Wang; Feng-Xia Du; Tian-Yu Zhang; Xiao-Yang Zheng; Hou-Yi Cong; You-Li Du; Jun-Zhi Sang; Ming-da Wang; Shan-Xin Zhang
Journal:  Sci Rep       Date:  2022-04-05       Impact factor: 4.379

8.  Using a risk model for probability of cancer in pulmonary nodules.

Authors:  Si-Qi Liu; Xiao-Bin Ma; Wan-Mei Song; Yi-Fan Li; Ning Li; Li-Na Wang; Jin-Yue Liu; Ning-Ning Tao; Shi-Jin Li; Ting-Ting Xu; Qian-Yun Zhang; Qi-Qi An; Bin Liang; Huai-Chen Li
Journal:  Thorac Cancer       Date:  2021-05-11       Impact factor: 3.500

9.  Differential Diagnosis of Solitary Pulmonary Inflammatory Lesions and Peripheral Lung Cancers with Contrast-enhanced Computed Tomography.

Authors:  Zhi-Gang Chu; Bo Sheng; Meng-Qi Liu; Fa-Jin Lv; Qi Li; Yu Ouyang
Journal:  Clinics (Sao Paulo)       Date:  2016-10-01       Impact factor: 2.365

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