CT screening for lung cancer: frequency and significance of part-solid and nonsolid nodules.

By C. Henschke, D. Yankelevitz, Rosna M Mirtcheva, G. McGuinness, D. McCauley, O. Miettinen. AJR. American journal of roentgenology, 2002

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Validation, comparison, and combination of algorithms for automatic detection of pulmonary nodules in computed tomography images: The LUNA16 challenge (2016, methodology): “The candidate detection algorithm was built to detect subsolid nodules, which are less common but more likely to be cancerous (Henschke et al. (2002)).”
Guidelines for management of small pulmonary nodules detected on CT scans: a statement from the Fleischner Society. (2005, background): “Solid versus nonsolid appearance, spiculation, or other characteristics influence the likelihood of malignancy and probable growth rate in any given case (19,39,49,51,52).”
Computer-aided diagnosis in medical imaging: Historical review, current status and future potential (2007, background): “[82] Henschke CI, Yankelevitz DF, Mirtcheva R, McGuinness G, McCauley D, Miettinen OS.”
Three-dimensional segmentation and growth-rate estimation of small pulmonary nodules in helical CT images (2003, background): “Nonsolid and part-solid nodules (lesions with mixed solid and nonsolid components), also known as ground glass opacities, frequently require a much lower threshold (or more than one) for accurate segmentation [22].”