Diagnostic Performance of Dual-time18 F-FDG PET in the Diagnosis of Pulmonary Nodules A Meta-analysis

Rationale and Objective

Perform a comprehensive meta-analysis evaluating the diagnostic performance of dual time point deoxy-2-[ 18 F]fluoro-D-glucose positron emission tomography (FDG-PET) in the diagnosis of pulmonary nodules.

Materials and Methods

MEDLINE, EMBASE, and PUBMED were queried between January 2000 and January 2011. Studies were included if they: 1) used dual time point FDG-PET as a diagnostic test for pulmonary nodules, 2) used pathology or clinical follow-up as the reference standard, and 3) reported absolute number of true-positive (TP), true-negative (TN), false-positive (FP), and false-negative (FN) results or stated sufficient data to derive these values. Summary sensitivity (SN), summary specificity (SP), positive and negative likelihood ratios (LR+) and (LR−), and diagnostic odds ratio were calculated. Heterogeneity of the results was assessed using Forest plots and the value of inconsistency index (I 2 ).

Results

Inclusion criteria were fulfilled by 10 articles with a total of 816 patients and 890 pulmonary nodules. The summary sensitivity was 85% (82%–89% at 95% confidence interval [CI]) and summary specificity was 77% (CI: 72%–81%), with a LR+ of 2.7 (CI: 1.4–5.2) and a LR− of 0.26 (CI: 0.14–0.49). Diagnostic odds ratio was 11 (CI: 3.8–32.2). Significant heterogeneity was found in the sensitivity (I 2 = 77%) and specificity (90.3%).

Conclusion

Dual time point FDG-PET demonstrates similar sensitivity and specificity to single time point FDG-PET in the diagnosis of pulmonary nodules. The additive value of the dual time point FDG-PET is questionable, primarily because of the significant overlap of benign and malignant nodule FDG-PET characteristics and lack of consensus criteria for quantitative thresholds to define nodules as malignant.

2-deoxy-2-[ 18 F]-fluoro-D-glucose positron emission tomography (FDG-PET) is well established in the management of pulmonary malignancy, primarily as a staging imaging modality . FDG-PET has also been used as a diagnostic problem-solving tool. One of the most common diagnostic indications for FDG-PET is for the determination of benign versus malignant pulmonary nodules. Approximately 150,000 new pulmonary nodules are found in the United States annually, with 60%–70% of these being benign . Furthermore, recently published data from the National Lung Screening Trial showed that screening low-dose computed tomography (CT) decreased mortality of lung cancer, but 96.4% of the positive results in the CT group and 94.5% of the positive results in the radiography group were false-positive (FP) results . Currently, the gold standard for diagnosing pulmonary nodules is pathology, with tissue obtained either surgically or by percutaneous biopsy, but both of these techniques are invasive and may involve significant risk to the patient . Using FDG-PET as a diagnostic tool could reduce the number of unwanted interventions on benign pulmonary nodules. As determined in a previous meta-analysis, the sensitivity and specificity of single time point FDG-PET for characterizing pulmonary nodules is 96.8% and 77.8%, respectively . Primary speculations regarding the low specificity for determining nature of pulmonary nodules are the wide ranges of standardized uptake values (SUV) and sizes of both malignant and benign pulmonary nodules .

Dual time point FDG-PET has been investigated as a potential technique to improve the specificity of FDG-PET in the diagnosis of pulmonary nodules . The theoretical reasoning is based on the fact that in vitro malignancy demonstrates deranged glucose metabolism, higher surface glucose receptor expression, and different glycolysis enzyme production compared to inflammation/infection . Based on this, the hypothesis is that on delayed imaging, malignant nodules will demonstrate increased FDG avidity, whereas a benign process should demonstrate a plateau or decreasing FDG avidity. Multiple studies have been done investigating the clinical application of dual time point FDG-PET in the diagnosis of pulmonary nodules.

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Materials and methods

Execution of Data Collection and Statistical Analysis

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Data Sources and Searches

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Study Selection

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Data Extraction and Quality Assessment

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Data Synthesis and Statistical Analysis

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I2=100[(Q−df)/Q] I

100

[

(

Q−df

)

]

where Q is Cochran’s heterogeneity statistic and df is the degrees of freedom. A value of 0% indicates no heterogeneity and any value greater than 50% may be considered significant heterogeneity .

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Results

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Table 1

Basic Study Information of Articles Included in this Meta-Analysis

First Author Journal Year Number of Patients Age (y) Scanner Study Type TP FP FN TN SN SP Alkhawaldeh Eur J Nucl Med Mol Imaging 2008 255 67 No Data Retrospective 59 20 3 173 0.95 0.90 Chen Am J Roentgenol 2008 27 68 Siemens Retrospective 10 9 6 6 0.63 0.40 Laffon Nucl Med Commun 2008 38 60 General Electric Prospective 27 19 3 3 0.90 0.14 Claron Lung Cancer 2010 67 No data Siemens Retrospective 24 12 14 17 0.63 0.59 Lan Clin Radiol 2008 96 54 General Electric Retrospective 25 4 3 14 0.89 0.78 Matthies J Nucl Med 2002 36 67 ADAC Labs Retrospective 20 2 0 16 1.00 0.89 Nunez Rev Esp Med Nucl 2007 83 69 ADAC Labs Prospective 67 8 4 4 0.95 0.33 Schillaci Radiol Med 2009 30 59 General Electric Prospective 15 6 3 6 0.83 0.50 Suga Ann Nucl Med 2009 138 63 Gemini; Philips Retrospective 59 11 17 46 0.78 0.81 Xui Clin Nucl Med 2007 46 No data Allegro; Philips Retrospective 13 4 3 26 0.81 0.87

FN, false negatives; FP, false positives; SN, summary sensitivity; SP, summary specificity; TN, true negatives; TP, true positives.

Ages are given as mean.

Table 2

Nodule Statistics and Basic Definition Used to Define Malignancy by the Articles of this Meta-Analysis

First Author Nodule Size SUVmax Initial SUVmax Delayed Alkhawaldeh Not given Not given Not given Chen 1.75 (0.68) 2.12 (0.80) 2.60 (1.23) Laffon 3.26 (1.95) 10.4 (8.44) 10.6 (10.63) Claron Not given 2.65 (2.60) 2.90 (2.90) Lan Not given 4.65 (3.73) 5.93 (4.84) Matthies 1.9 (1.21) 2.5 (1.93) 2.9 (2.46) Nunez 3.3 (2.2) 4.7 (5.4) 7.5 (9.3) Schillaci 1.9 (0.75) 4.76 (4.58) 5.6 (5.72) Suga ∗ 2.95 (1.35) 6.2 (4.5) 7.2 (5.1) Xui 1.1 (0.3) 1.7 (1.1–2.3) Not given

SUV, standardized uptake values.

Nodule sizes are the mean in centimeters. SUV values are the mean values.

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Discussion

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References

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Diagnostic Performance of Dual-time18 F-FDG PET in the Diagnosis of Pulmonary Nodules A Meta-analysis

Rationale and Objective

Materials and Methods

Results

Conclusion

Materials and methods

Execution of Data Collection and Statistical Analysis

Data Sources and Searches

Study Selection

Data Extraction and Quality Assessment

Data Synthesis and Statistical Analysis

Results

Discussion

References

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