Quantitative computed tomographic (CT) evaluation of lung nodules has achieved significant
progress through the continued evolution of technical imaging and data-processing
capabilities, with an ever-growing body of literature using first- and second-order
statistical evaluation.
Keywords
To read this article in full you will need to make a payment
Purchase one-time access:
Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online accessOne-time access price info
- For academic or personal research use, select 'Academic and Personal'
- For corporate R&D use, select 'Corporate R&D Professionals'
Subscribe:
Subscribe to Advances in Clinical RadiologyAlready a print subscriber? Claim online access
Already an online subscriber? Sign in
Register: Create an account
Institutional Access: Sign in to ScienceDirect
References
- Interobserver and intraobserver variability in measurement of non-small-cell carcinoma lung lesions: implications for assessment of tumor response.J Clin Oncol. 2003; 21: 2574-2582
- Are two-dimensional CT measurements of small noncalcified pulmonary nodules reliable?.Radiology. 2004; 231: 453-458
- Use of volumetry for lung nodule management: theory and practice.Radiology. 2017; 284: 630-644
- Guidelines for management of incidental pulmonary nodules detected on CT images: from the Fleischner Society 2017.Radiology. 2017; 284: 228-243
- Lung cancer probability in patients with CT-detected pulmonary nodules: a prespecified analysis of data from the NELSON trial of low-dose CT screening.Lancet Oncol. 2014; 15: 1332-1341
- Management of lung nodules detected by volume CT scanning.N Engl J Med. 2009; 361: 2221-2229
- Evaluation of individuals with pulmonary nodules: when is it lung cancer? Diagnosis and management of lung cancer, 3rd ed: American College of Chest Physicians evidence-based clinical practice guidelines.Chest. 2013; 143: e93S-e120S
- Evaluation of patients with pulmonary nodules: when is it lung cancer?: ACCP evidence-based clinical practice guidelines (2nd edition).Chest. 2007; 132: 108S-130S
- Optimisation of volume-doubling time cutoff for fast-growing lung nodules in CT lung cancer screening reduces false-positive referrals.Eur Radiol. 2013; 23: 1836-1845
- The utility of nodule volume in the context of malignancy prediction for small pulmonary nodules.Chest. 2014; 145: 464-472
- Inherent variability of CT lung nodule measurements in vivo using semiautomated volumetric measurements.AJR Am J Roentgenol. 2006; 186: 989-994
- Interobserver and intraobserver variability in the assessment of pulmonary nodule size on CT using film and computer display methods.Acad Radiol. 2005; 12: 948-956
- Volumetric measurements of pulmonary nodules at multi-row detector CT: in vivo reproducibility.Eur Radiol. 2004; 14: 86-92
- Pulmonary ground-glass nodules: increase in mass as an early indicator of growth.Radiology. 2010; 255: 199-206
- Management of incidental lung nodules.Semin Ultrasound CT MR. 2018; 39: 249-259
- The IASLC lung cancer staging project: proposals for coding T categories for subsolid nodules and assessment of tumor size in part-solid tumors in the forthcoming eighth edition of the TNM classification of lung cancer.J Thorac Oncol. 2016; 11: 1204-1223
- Solid part size is an important predictor of nodal metastasis in lung cancer with a subsolid tumor.BMC Pulm Med. 2018; 18: 151
- Cardiac computed tomography radiomics: a comprehensive review on radiomic techniques.J Thorac Imaging. 2018; 33: 26-34
- Measuring skewness: a forgotten statistic?.J Stat Educ. 2011; 19: 18
- On the meaning and use of kurtosis.Psychol Methods. 1997; 2: 292-307
- Radiologic implications of the 2011 classification of adenocarcinoma of the lung.Radiology. 2013; 266: 62-71
- Persistent pure ground-glass opacity lung nodules ≥ 10 mm in diameter at CT scan: histopathologic comparisons and prognostic implications.Chest. 2013; 144: 1291-1299
- CT quantitative parameters to predict the invasiveness of lung pure ground-glass nodules (pGGNs).Clin Radiol. 2018; 73: 504.e1-504.e7
- Lung adenocarcinoma: correlation of quantitative CT findings with pathologic findings.Radiology. 2016; 280: 931-939
- Quantitative CT analysis of pulmonary pure ground-glass nodule predicts histological invasiveness.Eur J Radiol. 2017; 89: 67-71
- Lepidic predominant pulmonary lesions (LPL): CT-based distinction from more invasive adenocarcinomas using 3D volumetric density and first-order CT texture analysis.Acad Radiol. 2017; 24: 1604-1611
- Quantitative CT analysis of pulmonary ground-glass opacity nodules for the distinction of invasive adenocarcinoma from pre-invasive or minimally invasive adenocarcinoma.PLoS One. 2014; 9: e104066
- Persistent pure ground-glass nodules larger than 5 mm: differentiation of invasive pulmonary adenocarcinomas from preinvasive lesions or minimally invasive adenocarcinomas using texture analysis.Invest Radiol. 2015; 50: 798-804
- Computerized texture analysis of persistent part-solid ground-glass nodules: differentiation of preinvasive lesions from invasive pulmonary adenocarcinomas.Radiology. 2014; 273: 285-293
- The emerging science of quantitative imaging biomarkers terminology and definitions for scientific studies and regulatory submissions.Stat Methods Med Res. 2015; 24: 9-26
- Role of the quantitative imaging biomarker alliance in optimizing CT for the evaluation of lung cancer screen-detected nodules.J Am Coll Radiol. 2015; 12: 390-395
- Algorithm variability in the estimation of lung nodule volume from phantom CT scans: results of the QIBA 3A public challenge.Acad Radiol. 2016; 23: 940-952
Article info
Publication history
Published online: May 29, 2019
Footnotes
There are no commercial or financial conflicts of interest to disclose. No funding was provided for this work.
Identification
Copyright
© 2019 Elsevier Inc. All rights reserved.