Literature DB >> 8421743

Determining the likelihood of malignancy in solitary pulmonary nodules with Bayesian analysis. Part I. Theory.

J W Gurney1.   

Abstract

Only two radiographic findings allow reliable distinction of benign from malignant solitary pulmonary nodules. Intuitively, it is clear that other radiographic and clinical findings should also be important in making this distinction. Subjectively incorporating these other findings into the decision of whether a nodule is benign or malignant is difficult. Likelihood ratios, which indicate the degree of malignancy or benignity represented by a test result or clinical finding, can be combined by means of the Bayes theorem to quantitate the probability of malignancy of a given nodule. From a literature survey, likelihood ratios were derived for six radiographic and four clinical characteristics associated with solitary pulmonary nodules. There were a total of 15 malignant and 19 benign findings, the most important of which were radiographic characteristics. For malignant nodules, the most important radiographic characteristics were thickness of the cavity wall spicular edge, and diameter of over 3 cm. For benign nodules, the most important radiographic characteristics were benign growth rate and a benign pattern of calcification.

Entities:  

Mesh:

Year:  1993        PMID: 8421743     DOI: 10.1148/radiology.186.2.8421743

Source DB:  PubMed          Journal:  Radiology        ISSN: 0033-8419            Impact factor:   11.105


  52 in total

1.  Improved pulmonary nodule classification utilizing quantitative lung parenchyma features.

Authors:  Samantha K N Dilger; Johanna Uthoff; Alexandra Judisch; Emily Hammond; Sarah L Mott; Brian J Smith; John D Newell; Eric A Hoffman; Jessica C Sieren
Journal:  J Med Imaging (Bellingham)       Date:  2015-09-01

Review 2.  Identifying lung cancer in patients with active pulmonary tuberculosis.

Authors:  Cassandra S Parker; Carrie G Siracuse; Virginia R Litle
Journal:  J Thorac Dis       Date:  2018-10       Impact factor: 2.895

3.  Performance of FDG-PET/CT in solitary pulmonary nodule based on pre-test likelihood of malignancy: results from the ITALIAN retrospective multicenter trial.

Authors:  Laura Evangelista; Alberto Cuocolo; Leonardo Pace; Luigi Mansi; Silvana Del Vecchio; Paolo Miletto; Silvia Sanfilippo; Sara Pellegrino; Luca Guerra; Giovanna Pepe; Giuseppina Peluso; Marco Salvatore; Rosj Galicchio; Michele Zuffante; Salvatore Annunziata; Mohsen Farsad; Agostino Chiaravalloti; Marco Spadafora
Journal:  Eur J Nucl Med Mol Imaging       Date:  2018-05-07       Impact factor: 9.236

4.  Computer-aided diagnosis of pulmonary nodules on CT scans: segmentation and classification using 3D active contours.

Authors:  Ted W Way; Lubomir M Hadjiiski; Berkman Sahiner; Heang-Ping Chan; Philip N Cascade; Ella A Kazerooni; Naama Bogot; Chuan Zhou
Journal:  Med Phys       Date:  2006-07       Impact factor: 4.071

Review 5.  Management of an incidentally discovered pulmonary nodule.

Authors:  Catherine Beigelman-Aubry; Catherine Hill; Philippe A Grenier
Journal:  Eur Radiol       Date:  2006-10-05       Impact factor: 5.315

Review 6.  Recent progress in computer-aided diagnosis of lung nodules on thin-section CT.

Authors:  Qiang Li
Journal:  Comput Med Imaging Graph       Date:  2007-03-21       Impact factor: 4.790

Review 7.  The pulmonary nodule: clinical and radiological characteristics affecting a diagnosis of malignancy.

Authors:  L Cardinale; F Ardissone; S Novello; M Busso; F Solitro; M Longo; D Sardo; M Giors; C Fava
Journal:  Radiol Med       Date:  2009-05-29       Impact factor: 3.469

8.  The utility of nodule volume in the context of malignancy prediction for small pulmonary nodules.

Authors:  Hiren J Mehta; James G Ravenel; Stephanie R Shaftman; Nichole T Tanner; Luca Paoletti; Katherine K Taylor; Martin C Tammemagi; Mario Gomez; Paul J Nietert; Michael K Gould; Gerard A Silvestri
Journal:  Chest       Date:  2014-03-01       Impact factor: 9.410

9.  Multicenter external validation of two malignancy risk prediction models in patients undergoing 18F-FDG-PET for solitary pulmonary nodule evaluation.

Authors:  Simone Perandini; G A Soardi; A R Larici; A Del Ciello; G Rizzardi; A Solazzo; L Mancino; F Zeraj; M Bernhart; M Signorini; M Motton; S Montemezzi
Journal:  Eur Radiol       Date:  2016-09-15       Impact factor: 5.315

Review 10.  Current role of positron emission tomography in thoracic oncology.

Authors:  V J Lowe; K S Naunheim
Journal:  Thorax       Date:  1998-08       Impact factor: 9.139

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.