ArticleEuropean journal of radiology open2018
Hilly or mountainous surface: a new CT feature to predict the behavior of pure ground glass nodules?
Article in European journal of radiology open, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
8 citing papers in PubMed.
- Software-based quantitative CT analysis to predict the growth trend of persistent nonsolid pulmonary nodules: a retrospective study.La Radiologia medica · 2023Article
- What's New on Quantitative CT Analysis as a Tool to Predict Growth in Persistent Pulmonary Subsolid Nodules? A Literature Review.Diagnostics (Basel, Switzerland) · 2020Review
- Solid Indeterminate Pulmonary Nodules of Less Than 300 mmDiagnostics (Basel, Switzerland) · 2019Article
- Spread through air spaces in lung adenocarcinoma: is radiology reliable yet?Journal of thoracic disease · 2019Article
- Two synchronous lung metastases from malignant melanoma: the same patient but different morphological patterns.European journal of radiology open · 2019Article
- Solid Indeterminate Pulmonary Nodules Less Than or Equal to 250 mmRadiology research and practice · 2019Article
- Pulmonary metastases from malignant epithelioid schwannoma of the arm presenting as fast-growing subsolid nodules: Report of an unusual case.European journal of radiology open · 2019Article
- Look around your target: a new approach to early diagnosis of lung cancer.Annals of translational medicine · 2018Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Persistent pure ground-glass nodules (pGGNs) typically show an indolent course with very slow growth rates. These slow-growing lesions exhibit different growth patterns regardless of their initial computed tomography (CT) features. Therefore, predicting the aggressive behavior of pGGNs on initial CT remains a diagnostic challenge. The literature reports that computerized analysis and various quantitative features have been tested to improve the risk stratification for pGGNs. The present article describes the long-term follow-up of two pGGNs with different behavior and introduces, for the first time, a new computerized method of analysis that could be helpful for predicting the future behavior of pGGNs.
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Registered trials
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