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Probability of Malignancy in Solitary Versus Multiple Pulmonary Nodules in Positive FDG PET Scan FREE TO VIEW

Deepak Donthi, MBBS; Ajay Kumar, MBBS; Marwan Daoud, PhD; Majid Khalaf, MD
Chest. 2011;140(4_MeetingAbstracts):953A. doi:10.1378/chest.1117622
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PURPOSE: Determination of the performance of PET in predicting the probability of malignancy in patients with solitary versus multiple pulmonary nodules with/without hilar and mediastinal lymphadenopathy.

METHODS: 269 consecutive patients who underwent FDG PET-CT for the evaluation of lung lesion(s) were considered for this retrospective study. They were divided into 4 groups according to CT scan findings: i) single pulmonary nodule (SPN) without hilar or mediastinal involvement, ii) SPN with hilar or mediastinal lymph node(s), iii) multiple pulmonary nodules (MPN) without hilar or mediastinal involvement, and iv) MPN with hilar or mediastinal lymph node(s). PET findings were categorized as positive or negative, and compared against histopathological findings and clinical outcome after > 1 year of follow-up and the predictive performance of FDG PET was estimated using logistic regression analysis.

RESULTS: Performance of FDG PET is given in the Table below. The probability of malignancy in case of positive FDG PET scan was 0.76, 0.9, 0.92, 0.89 in group 1, 2, 3 and 4 respectively. Likelihood ratio for positive PET scan was 3.7, 2.2, 4.5 and 2.5 in group 1, 2, 3 and 4, respectively.

CONCLUSIONS: The probability of malignancy is higher when FDG PET shows multiple pulmonary nodules without hilar/mediastinal adenopathy. There is no clinically significant difference in the probability of malignancy for positive PET scan among patients having SPN with or without hilar/mediastinal lymphadenopathy, or MPN with hilar/mediastinal lymphadenopathy.

CLINICAL IMPLICATIONS: To help clinicians in predicting the probability of malignancy in FDG-PET positive pulmonary nodule(s).

DISCLOSURE: The following authors have nothing to disclose: Deepak Donthi, Ajay Kumar, Marwan Daoud, Majid Khalaf

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