European Radiology

, Volume 26, Issue 9, pp 3071–3076 | Cite as

Solid pulmonary nodule risk assessment and decision analysis: comparison of four prediction models in 285 cases

  • Simone PerandiniEmail author
  • Gian Alberto Soardi
  • Massimiliano Motton
  • Arianna Rossi
  • Manuel Signorini
  • Stefania Montemezzi
Computer Applications



The aim of this study was to compare classification results from four major risk prediction models in a wide population of incidentally detected solitary pulmonary nodules (SPNs) which were selected to crossmatch inclusion criteria for the selected models.


A total of 285 solitary pulmonary nodules with a definitive diagnosis were evaluated by means of four major risk assessment models developed from non-screening populations, namely the Mayo, Gurney, PKUPH and BIMC models. Accuracy was evaluated by receiver operating characteristic (ROC) area under the curve (AUC) analysis. Each model’s fitness to provide reliable help in decision analysis was primarily assessed by adopting a surgical threshold of 65 % and an observation threshold of 5 % as suggested by ACCP guidelines.


ROC AUC values, false positives, false negatives and indeterminate nodules were respectively 0.775, 3, 8, 227 (Mayo); 0.794, 41, 6, 125 (Gurney); 0.889, 42, 0, 144 (PKUPH); 0.898, 16, 0, 118 (BIMC).


Resultant data suggests that the BIMC model may be of greater help than Mayo, Gurney and PKUPH models in preoperative SPN characterization when using ACCP risk thresholds because of overall better accuracy and smaller numbers of indeterminate nodules and false positive results.

Key Points

The BIMC and PKUPH models offer better characterization than older prediction models

Both the PKUPH and BIMC models completely avoided false negative results

The Mayo model suffers from a large number of indeterminate results


Solitary pulmonary nodule Decision analysis Computer aided diagnosis Lung cancer CT 



The scientific guarantor of this publication is Simone Perandini. The authors of this manuscript declare no relationships with any companies whose products or services may be related to the subject matter of the article. The authors state that this work has not received any funding. One of the authors has significant statistical expertise (S.P.). Institutional review board approval was not required because the research involved collection and analysis of existing data. Data and diagnostic specimens were recorded by the investigator in such a manner that subjects cannot be identified. Written informed consent was not required for this study because the research involved collection and analysis of existing data. Data and diagnostic specimens were recorded by the investigator in such a manner that subjects cannot be identified. Methodology: retrospective, diagnostic or prognostic study, performed at one institution.


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Copyright information

© European Society of Radiology 2015

Authors and Affiliations

  • Simone Perandini
    • 1
    Email author
  • Gian Alberto Soardi
    • 1
  • Massimiliano Motton
    • 1
  • Arianna Rossi
    • 1
  • Manuel Signorini
    • 1
  • Stefania Montemezzi
    • 1
  1. 1.Department of RadiologyAzienda Ospedaliera Universitaria Integrata di VeronaVeronaItaly

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