6
views
0
recommends
+1 Recommend
1 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Use of PET/CT to aid clinical decision-making in cases of solitary pulmonary nodule: a probabilistic approach

      research-article

      Read this article at

      ScienceOpenPublisherPMC
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Objective

          To determine the frequency with which 18F-FDG-PET/CT findings change the probability of malignancy classification of solitary pulmonary nodules.

          Materials and Methods

          This was a retrospective analysis of all 18F-FDG-PET/CT examinations performed for the investigation of a solitary pulmonary nodule between May 2016 and May 2017. We reviewed medical records and PET/CT images to collect the data necessary to calculate the pre-test probability of malignancy using the Swensen model and the Herder model. The probability of malignancy was classified as low if < 5%, intermediate if 5-65%, and high if > 65%. Cases classified as intermediate in the Swensen model were reclassified by the Herder model.

          Results

          We reviewed the records for 33 patients, of whom 17 (51.5%) were male. The mean age was 68.63 ± 12.20 years. According to the Swensen model, the probability of malignancy was intermediate in 23 cases (69.7%). Among those, the application of the Herder model resulted in the probability of malignancy being reclassified as low in 6 (26.1%) and as high in 8 (34.8%).

          Conclusion

          18F-FDG-PET/CT was able to modify the probability of malignancy classification of a solitary pulmonary nodule in more than 50% of the cases evaluated.

          Related collections

          Most cited references32

          • Record: found
          • Abstract: found
          • Article: not found

          The probability of malignancy in solitary pulmonary nodules. Application to small radiologically indeterminate nodules.

          A clinical prediction model to identify malignant nodules based on clinical data and radiological characteristics of lung nodules was derived using logistic regression from a random sample of patients (n = 419) and tested on data from a separate group of patients (n = 210). To use multivariate logistic regression to estimate the probability of malignancy in radiologically indeterminate solitary pulmonary nodules (SPNs) in a clinically relevant subset of patients with SPNs that measured between 4 and 30 mm in diameter. A retrospective cohort study at a multispecialty group practice included 629 patients (320 men, 309 women) with newly discovered (between January 1, 1984, and May 1, 1986) 4- to 30-mm radiologically indeterminate SPNs on chest radiography. Patients with a diagnosis of cancer within 5 years prior to the discovery of the nodule were excluded. Clinical data included age, sex, cigarette-smoking status, and history of extrathoracic malignant neoplasm, asbestos exposure, and chronic interstitial or obstructive lung disease; chest radiological data included the diameter, location, edge characteristics (eg, lobulation, spiculation, and shagginess), and other characteristics (eg, cavitation) of the SPNs. Predictors were identified in a random sample of two thirds of the patients and tested in the remaining one third. Sixty-five percent of the nodules were benign, 23% were malignant, and 12% were indeterminate. Three clinical characteristics (age, cigarette-smoking status, and history of cancer [diagnosis, > or = 5 years ago]) and 3 radiological characteristics (diameter, spiculation, and upper lobe location of the SPNs) were independent predictors of malignancy. The area (+/-SE) under the evaluated receiver operating characteristic curve was 0.8328 +/- 0.0226. Three clinical and 3 radiographic characteristics predicted the malignancy in radiologically indeterminate SPNs.
            Bookmark
            • Record: found
            • Abstract: not found
            • Article: not found

            Clinical practice. The solitary pulmonary nodule.

              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Clinical prediction model to characterize pulmonary nodules: validation and added value of 18F-fluorodeoxyglucose positron emission tomography.

              The added value of 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) scanning as a function of pretest risk assessment in indeterminate pulmonary nodules is still unclear. To obtain an external validation of the prediction model according to Swensen and colleagues, and to quantify the potential added value of FDG-PET scanning as a function of its operating characteristics in relation to this prediction model, in a population of patients with radiologically indeterminate pulmonary nodules. Between August 1997 and March 2001, all patients with an indeterminate solitary pulmonary nodule who had been referred for FDG-PET scanning were retrospectively identified from the database of the PET center at the VU University Medical Center. One hundred six patients were eligible for the study, and 61 patients (57%) proved to have malignant nodules. The goodness-of-fit statistic for the model (according to Swensen) indicated that the observed proportion of malignancies did not differ from the predicted proportion (p = 0.46). PET scan results, which were classified using the 4-point intensity scale reading, yielded an area under the evaluated receiver operating characteristic curve of 0.88 (95% confidence interval [CI], 0.77 to 0.91). The estimated difference of 0.095 (95% CI, -0.003 to 0.193) between the PET scan results classified using the 4-point intensity scale reading and the area under the curve (AUC) from the Swensen prediction was not significant (p = 0.058). The PET scan results, when added to the predicted probability calculated by the Swensen model, improves the AUC by 13.6% (95% CI, 6 to 21; p = 0.0003). The clinical prediction model of Swensen et al was proven to have external validity. However, especially in the lower range of its estimates, the model may underestimate the actual probability of malignancy. The combination of visually read FDG-PET scans and pretest factors appears to yield the best accuracy.
                Bookmark

                Author and article information

                Journal
                Radiol Bras
                Radiol Bras
                rb
                Radiologia Brasileira
                Colégio Brasileiro de Radiologia e Diagnóstico por Imagem
                0100-3984
                1678-7099
                Jan-Feb 2020
                Jan-Feb 2020
                : 53
                : 1
                : 1-6
                Affiliations
                [1 ] Real Hospital Português de Beneficência em Pernambuco, Recife, PE, Brazil.
                Author notes
                Correspondence: Dr. Felipe Alves Mourato. Real Hospital Português de Beneficência em Pernambuco - Real Nuclear. Avenida Portugal, 163, Paissandu. Recife, PE, Brazil, 52010-010. Email: felipe.a.mourato@ 123456gmail.com .
                Author information
                http://orcid.org/0000-0001-8102-9654
                http://orcid.org/0000-0002-1065-9672
                http://orcid.org/0000-0003-0043-213X
                http://orcid.org/0000-0002-5201-5066
                http://orcid.org/0000-0002-9400-7099
                http://orcid.org/0000-0002-3584-5316
                http://orcid.org/0000-0002-3050-1119
                Article
                10.1590/0100-3984.2019.0034
                7159041
                d03963e6-7faf-40a9-8ada-190d5fda8999

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 28 February 2019
                : 12 July 2019
                Categories
                Original Articles

                solitary pulmonary nodule,positron emission tomography,decision support techniques,clinical decision-making,medical oncology,pulmonary medicine

                Comments

                Comment on this article