Metastatic pulmonary dissemination as differential diagnosis of COVID-19 disease

Martinelli, Cristel Perdigón; Morell, Carlos; González, Carolina; Nova-Lozano, Cristina

doi:10.1136/bcr-2020-237453

Cited by 3 publications

(3 citation statements)

References 9 publications

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“…Differentiating primary lung cancer from LM is of great clinical interest because of the profound differences in their prognostic and therapeutic implications [ 79 , 80 ]. Furthermore, a solitary pulmonary nodule may be more difficult to interpret in patients with a history of cancer, as it may be a primary lung tumor, a metastasis, or a benign lesion [ 81 , 82 , 83 ]. From an imaging viewpoint, the ability to recognize various diseases based on qualitative criteria relies on observer expertise and experience, whereas quantitative parameters, such as pulmonary nodule diameter and/or growth rate, are surrogate biomarkers of malignancy [ 84 , 85 , 86 , 87 ].…”

Section: Discussionmentioning

confidence: 99%

Radiomics in Lung Metastases: A Systematic Review

Gabelloni

Faggioni

Fusco

et al. 2023

JPM

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Due to the rich vascularization and lymphatic drainage of the pulmonary tissue, lung metastases (LM) are not uncommon in patients with cancer. Radiomics is an active research field aimed at the extraction of quantitative data from diagnostic images, which can serve as useful imaging biomarkers for a more effective, personalized patient care. Our purpose is to illustrate the current applications, strengths and weaknesses of radiomics for lesion characterization, treatment planning and prognostic assessment in patients with LM, based on a systematic review of the literature.

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Section: Discussionmentioning

confidence: 99%

Radiomics in Lung Metastases: A Systematic Review

Gabelloni

Faggioni

Fusco

et al. 2023

JPM

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“…A case from Spain was recently published where bilateral COVID-19 pneumonia was diagnosed based on chest X-ray results. A thoracic CT scan demonstrated metastatic pulmonary nodules and lytic bone lesions [ 11 ]⁠. This case report should make clinicians aware of differential diagnoses other than COVID-19, as its clinical features may resemble those of other entities.…”

Section: Discussionmentioning

confidence: 99%

Delayed Diagnosis of an Atypical Pneumonia Resembling a Solitary Pulmonary Nodule

García-Carretero¹,

Vázquez-Gómez²,

Rodriguez-Maya³

et al. 2021

Cureus

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Atypical pneumonia shows clinical features that are different from those of typical pneumonia, and it can mimic other entities. We report the case of a 42-year-old male with a solitary pulmonary nodule found in an X-ray for a preoperative evaluation. Our patient was asymptomatic, and a pulmonary neoplasm was the first diagnostic suspicion. The round-shaped nodule seen in the X-ray turned out to be a linear ground glass opacity in a thoracic CT scan. Viral pneumonia due to SARS-CoV-2 was diagnosed. We emphasize here the educational value of this case report. We do not report a new radiological finding because lung nodules resembling neoplasms have already been reported in the medical literature. However, some clinical features of COVID-19 are relatively new and can mimic other entities, and the results of some investigations and clinicians’ interpretations of them can be misleading. Atypical radiological findings make it necessary to widen the spectrum of alternative diagnoses.

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“…3. Сохраняется риск, что очаги по типу консолидации и "матового стекла" могут иметь злокачественный характер [20,21].…”

Section: ограничения исследованияunclassified

Evaluation of the prospects for using artificial intelligence technologies to analyze CT scans of the chest organs in order to identify signs of malignant neoplasms in the lungs

Pilus

Drokin

Bazhenova

et al. 2023

Medicinskaâ vizualizaciâ

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The purpose of the study. To analyze the possibility of using artificial intelligence as a decision support system for radiologists for pulmonary nodules detection on Chest CT before and during the COVID-19 pandemic on the example of the system Botkin.AI.Materials and methods. Two groups of Chest CT studies were identified: those performed before (group 1) and during the COVID-19 pandemic (group 2). Each group contains anonymized CT data of 150 patients. Chest CT scans for group 2 were selected based on the percentage of coronavirus lung damage from 0 to 25%. The research was analyzed by the artificial intelligence system Botkin. AI for the presence of peripheral pulmonary nodes up to 6 mm, followed by a “blind” check of the analysis results by three radiologists.Results. In group 1, the sensitivity of the method was 1.0; specificity – 0.88 and AUC – 0.94. In the 2nd group 0.93; 0.81 and 0.86, respectively.In group 2, a slight decrease in specificity is mainly associated with an increase in false positive results in the pulmonary opcities, as manifestations of coronavirus lung damage, taken by the AI model for pulmonary nodes.Conclusion. The platform has a high accuracy of detecting pulmonary nodules on computed tomography of the chest both in studies conducted before and during the COVID-19 pandemic. It can be useful to prevent possible omissions of important findings in conditions of increased workload for radiologists.

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Metastatic pulmonary dissemination as differential diagnosis of COVID-19 disease

Cited by 3 publications

References 9 publications

Radiomics in Lung Metastases: A Systematic Review

Radiomics in Lung Metastases: A Systematic Review

Delayed Diagnosis of an Atypical Pneumonia Resembling a Solitary Pulmonary Nodule

Evaluation of the prospects for using artificial intelligence technologies to analyze CT scans of the chest organs in order to identify signs of malignant neoplasms in the lungs

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