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Figure 1.
Literature Search of Eligible Studies
Literature Search of Eligible Studies

FDG indicates fludeoxyglucose F 18; PET, positron emission tomography.

aThe same study could be excluded for multiple reasons.

bPopulations subjected to preselection of specific histologies or tumor characteristics in imaging (eg, minimum standard uptake value, ground glass opacity, lesion location).

Figure 2.
Individual Study Estimates of Sensitivity and Specificity With Average Adjusted Results
Individual Study Estimates of Sensitivity and Specificity With Average Adjusted Results
Figure 3.
Performance of FDG-PET to Diagnose Lung Nodules by Endemic Status for 70 Studies
Performance of FDG-PET to Diagnose Lung Nodules by Endemic Status for 70 Studies

The operating points for endemic and nonendemic infectious lung disease studies and 95% confidence and prediction intervals for those operating points are shown. The horizontal box and whiskers plot represents the distribution of study specificity, and the vertical box and whiskers plot represents the distribution of study sensitivity. The box limits are the closest data point to the interquartile range of 25% and 75% with the bar being the median (50%). Error bar whiskers represent the data point closest to 1.5 times the interquartile range and the dots outside the whiskers represent outlier study values. FDG indicates fludeoxyglucose F 18; HSROC, hierarchical summary receiver operator curve; PET, positron emission tomography.

1.
Humphrey  LL, Deffebach  M, Pappas  M,  et al.  Screening for lung cancer with low-dose computed tomography: a systematic review to update the U.S. Preventive Services Task Force recommendation. Ann Intern Med. 2013;159(6):411-420.
PubMedArticle
2.
Gould  MK, Donington  J, Lynch  WR,  et al.  Evaluation of individuals with pulmonary nodules: when is it lung cancer? diagnosis and management of lung cancer, 3rd ed: American College of Chest Physicians evidence-based clinical practice guidelines. Chest. 2013;143(5)(suppl):e93S-e120S.
PubMedArticle
3.
National Comprehensive Cancer Network. National Comprehensive Cancer Network clinical practice guidelines in oncology. http://www.nccn.org/professionals/physician_gls/recently_updated.asp. Accessed May 20, 2014.
4.
MacMahon  H, Austin  JH, Gamsu  G,  et al; Fleischner Society.  Guidelines for management of small pulmonary nodules detected on CT scans: a statement from the Fleischner Society. Radiology. 2005;237(2):395-400.
PubMedArticle
5.
Cronin  P, Dwamena  BA, Kelly  AM, Carlos  RC.  Solitary pulmonary nodules: meta-analytic comparison of cross-sectional imaging modalities for diagnosis of malignancy. Radiology. 2008;246(3):772-782.
PubMedArticle
6.
Gould  MK, Maclean  CC, Kuschner  WG, Rydzak  CE, Owens  DK.  Accuracy of positron emission tomography for diagnosis of pulmonary nodules and mass lesions: a meta-analysis. JAMA. 2001;285(7):914-924.
PubMedArticle
7.
Herder  GJ, Golding  RP, Hoekstra  OS,  et al.  The performance of (18)F-fluorodeoxyglucose positron emission tomography in small solitary pulmonary nodules. Eur J Nucl Med Mol Imaging. 2004;31(9):1231-1236.
PubMedArticle
8.
Silvestri  GA, Gould  MK, Margolis  ML,  et al; American College of Chest Physicians.  Noninvasive staging of non-small cell lung cancer: ACCP evidenced-based clinical practice guidelines (2nd edition). Chest. 2007;132(3)(suppl):178S-201S.
PubMedArticle
9.
Detterbeck  FC, Postmus  PE, Tanoue  LT.  The stage classification of lung cancer: diagnosis and management of lung cancer, 3rd ed: American College of Chest Physicians evidence-based clinical practice guidelines. Chest. 2013;143(5)(suppl):e191S-e210S.
PubMedArticle
10.
Deppen  S, Putnam  JB  Jr, Andrade  G,  et al.  Accuracy of FDG-PET to diagnose lung cancer in a region of endemic granulomatous disease. Ann Thorac Surg. 2011;92(2):428-433.
PubMedArticle
11.
Croft  DR, Trapp  J, Kernstine  K,  et al.  FDG-PET imaging and the diagnosis of non-small cell lung cancer in a region of high histoplasmosis prevalence. Lung Cancer. 2002;36(3):297-301.
PubMedArticle
12.
Mason  R, Broaddus  V, Martin  T. In: Murray  J, Nadel  J, eds. Murray and Nadel's Textbook of Respiratory Medicine.5th ed. Philadelphia, PA: Saunders; 2010.
13.
Bradsher  RW.  Histoplasmosis and blastomycosis. Clin Infect Dis. 1996;22(suppl 2):S102-S111.
PubMedArticle
14.
Sathekge  MM, Maes  A, Pottel  H, Stoltz  A, van de Wiele  C.  Dual time-point FDG PET-CT for differentiating benign from malignant solitary pulmonary nodules in a TB endemic area. S Afr Med J. 2010;100(9):598-601.
PubMed
15.
Mamede  M, Higashi  T, Kitaichi  M,  et al.  [18F]FDG uptake and PCNA, Glut-1, and Hexokinase-II expressions in cancers and inflammatory lesions of the lung. Neoplasia. 2005;7(4):369-379.
PubMedArticle
16.
Moher  D, Liberati  A, Tetzlaff  J, Altman  DG; PRISMA group.  Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Ann Intern Med. 2009;151(4):264-269, W64.
PubMedArticle
17.
Rutter  CM, Gatsonis  CA.  A hierarchical regression approach to meta-analysis of diagnostic test accuracy evaluations. Stat Med. 2001;20(19):2865-2884.
PubMedArticle
18.
Deeks  JJ, Macaskill  P, Irwig  L.  The performance of tests of publication bias and other sample size effects in systematic reviews of diagnostic test accuracy was assessed. J Clin Epidemiol. 2005;58(9):882-893.
PubMedArticle
19.
Fontela  PS, Pant Pai  N, Schiller  I, Dendukuri  N, Ramsay  A, Pai  M.  Quality and reporting of diagnostic accuracy studies in TB, HIV and malaria: evaluation using QUADAS and STARD standards. PLoS One. 2009;4(11):e7753.
PubMedArticle
20.
Whiting  P, Rutjes  AW, Reitsma  JB, Bossuyt  PM, Kleijnen  J.  The development of QUADAS: a tool for the quality assessment of studies of diagnostic accuracy included in systematic reviews. BMC Med Res Methodol. 2003;3(1):25.
PubMedArticle
21.
Ost  D, Fein  AM, Feinsilver  SH.  Clinical practice: the solitary pulmonary nodule. N Engl J Med. 2003;348(25):2535-2542.
PubMedArticle
22.
Patel  VK, Naik  SK, Naidich  DP,  et al.  A practical algorithmic approach to the diagnosis and management of solitary pulmonary nodules: part 2: pretest probability and algorithm. Chest. 2013;143(3):840-846.
PubMedArticle
23.
Gould  MK, Kuschner  WG, Rydzak  CE,  et al.  Test performance of positron emission tomography and computed tomography for mediastinal staging in patients with non-small-cell lung cancer: a meta-analysis. Ann Intern Med. 2003;139(11):879-892.
PubMedArticle
24.
Chundru  S, Wong  CY, Wu  D,  et al.  Granulomatous disease: is it a nuisance or an asset during PET/computed tomography evaluation of lung cancers? Nucl Med Commun. 2008;29(7):623-627.
PubMedArticle
25.
Kim  SC, Machac  J, Krynyckyi  BR,  et al.  Fluoro-deoxy-glucose positron emission tomography for evaluation of indeterminate lung nodules: assigning a probability of malignancy may be preferable to binary readings [published correction appears in Ann Nucl Med. 2010;24(3):231]. Ann Nucl Med. 2008;22(3):165-170.
PubMedArticle
26.
Bryant  AS, Cerfolio  RJ.  The maximum standardized uptake values on integrated FDG-PET/CT is useful in differentiating benign from malignant pulmonary nodules. Ann Thorac Surg. 2006;82(3):1016-1020.
PubMedArticle
27.
Li  Y, Su  M, Li  F, Kuang  A, Tian  R.  The value of ¹⁸F-FDG-PET/CT in the differential diagnosis of solitary pulmonary nodules in areas with a high incidence of tuberculosis. Ann Nucl Med. 2011;25(10):804-811.
PubMedArticle
28.
Kadaria  D, Archie  DS, SultanAli  I, Weiman  DS, Freire  AX, Zaman  MK.  Dual time point positron emission tomography/computed tomography scan in evaluation of intrathoracic lesions in an area endemic for histoplasmosis and with high prevalence of sarcoidosis. Am J Med Sci. 2013;346(5):358-362.
PubMedArticle
29.
Sebro  R, Aparici  CM, Hernandez-Pampaloni  M.  FDG PET/CT evaluation of pathologically proven pulmonary lesions in an area of high endemic granulomatous disease. Ann Nucl Med. 2013;27(4):400-405.
PubMedArticle
30.
Halter  G, Storck  M, Guhlmann  A, Frank  J, Grosse  S, Liewald  F.  FDG positron emission tomography in the diagnosis of peripheral pulmonary focal lesions. Thorac Cardiovasc Surg. 2000;48(2):97-101.
PubMedArticle
31.
Menda  Y, Bushnell  DL, Madsen  MT, McLaughlin  K, Kahn  D, Kernstine  KH.  Evaluation of various corrections to the standardized uptake value for diagnosis of pulmonary malignancy. Nucl Med Commun. 2001;22(10):1077-1081.
PubMedArticle
32.
Higashi  K, Ueda  Y, Sakuma  T,  et al.  Comparison of [(18)F]FDG PET and (201)Tl SPECT in evaluation of pulmonary nodules. J Nucl Med. 2001;42(10):1489-1496.
PubMed
33.
Skehan  SJ, Coates  G, Otero  C, O’Donovan  N, Pelling  M, Nahmias  C.  Visual and semiquantitative analysis of 18F-fluorodeoxyglucose positron emission tomography using a partial-ring tomograph without attenuation correction to differentiate benign and malignant pulmonary nodules. Can Assoc Radiol J. 2001;52(4):259-265.
PubMed
34.
Imdahl  A, Jenkner  S, Brink  I,  et al.  Validation of FDG positron emission tomography for differentiation of unknown pulmonary lesions. Eur J Cardiothorac Surg. 2001;20(2):324-329.
PubMedArticle
35.
Sasaki  M, Kuwabara  Y, Yoshida  T,  et al.  Comparison of MET-PET and FDG-PET for differentiation between benign lesions and malignant tumors of the lung. Ann Nucl Med. 2001;15(5):425-431.
PubMedArticle
36.
Uppot  RN, Conde  K, Sagar  V, Manzone  T.  Positron emission tomography (PET) imaging for solitary pulmonary nodules—review of the Delaware experience. Del Med J. 2001;73(10):381-385.
PubMed
37.
Yang  SN, Liang  JA, Lin  FJ, Kwan  AS, Kao  CH, Shen  YY.  Differentiating benign and malignant pulmonary lesions with FDG-PET. Anticancer Res. 2001;21(6A):4153-4157.
PubMed
38.
Keith  CJ, Miles  KA, Griffiths  MR, Wong  D, Pitman  AG, Hicks  RJ.  Solitary pulmonary nodules: accuracy and cost-effectiveness of sodium iodide FDG-PET using Australian data. Eur J Nucl Med Mol Imaging. 2002;29(8):1016-1023.
PubMedArticle
39.
Lee  J, Aronchick  JM, Alavi  A.  Accuracy of F-18 fluorodeoxyglucose positron emission tomography for the evaluation of malignancy in patients presenting with new lung abnormalities: a retrospective review. Chest. 2001;120(6):1791-1797.
PubMedArticle
40.
Pastorino  U, Bellomi  M, Landoni  C,  et al.  Early lung-cancer detection with spiral CT and positron emission tomography in heavy smokers: 2-year results. Lancet. 2003;362(9384):593-597.
PubMedArticle
41.
Demura  Y, Tsuchida  T, Ishizaki  T,  et al.  18F-FDG accumulation with PET for differentiation between benign and malignant lesions in the thorax. J Nucl Med. 2003;44(4):540-548.
PubMed
42.
Buck  AK, Hetzel  M, Schirrmeister  H,  et al.  Clinical relevance of imaging proliferative activity in lung nodules. Eur J Nucl Med Mol Imaging. 2005;32(5):525-533.
PubMedArticle
43.
Kahn  D, Menda  Y, Kernstine  K,  et al.  The utility of 99mTc depreotide compared with F-18 fluorodeoxyglucose positron emission tomography and surgical staging in patients with suspected non-small cell lung cancer. Chest. 2004;125(2):494-501.
PubMedArticle
44.
Sachs  S, Bilfinger  TV.  The impact of positron emission tomography on clinical decision making in a university-based multidisciplinary lung cancer practice. Chest. 2005;128(2):698-703.
PubMedArticle
45.
Nomori  H, Watanabe  K, Ohtsuka  T, Naruke  T, Suemasu  K, Uno  K.  Visual and semiquantitative analyses for F-18 fluorodeoxyglucose PET scanning in pulmonary nodules 1 cm to 3 cm in size. Ann Thorac Surg. 2005;79(3):984-989.
PubMedArticle
46.
Ding  QY, Hua  YQ, Zhang  GZ,  et al.  A controlled study of positron-emission-tomography and positron-emission-tomography/computed tomography in differential diagnosis of solitary pulmonary nodules—report of 60 cases. Chin Med J (Engl). 2005;118(18):1572-1576.
PubMed
47.
Chhajed  PN, Bernasconi  M, Gambazzi  F,  et al.  Combining bronchoscopy and positron emission tomography for the diagnosis of the small pulmonary nodule < or = 3 cm. Chest. 2005;128(5):3558-3564.
PubMedArticle
48.
Bastarrika  G, García-Velloso  MJ, Lozano  MD,  et al.  Early lung cancer detection using spiral computed tomography and positron emission tomography. Am J Respir Crit Care Med. 2005;171(12):1378-1383.
PubMedArticle
49.
Herder  GJ, van Tinteren  H, Golding  RP,  et al.  Clinical prediction model to characterize pulmonary nodules: validation and added value of 18F-fluorodeoxyglucose positron emission tomography. Chest. 2005;128(4):2490-2496.
PubMedArticle
50.
Christensen  JA, Nathan  MA, Mullan  BP, Hartman  TE, Swensen  SJ, Lowe  VJ.  Characterization of the solitary pulmonary nodule: 18F-FDG PET versus nodule-enhancement CT. AJR Am J Roentgenol. 2006;187(5):1361-1367.
PubMedArticle
51.
Yi  CA, Lee  KS, Kim  B-T,  et al.  Tissue characterization of solitary pulmonary nodule: comparative study between helical dynamic CT and integrated PET/CT. J Nucl Med. 2006;47(3):443-450.
PubMed
52.
Kim  SK, Allen-Auerbach  M, Goldin  J,  et al.  Accuracy of PET/CT in characterization of solitary pulmonary lesions. J Nucl Med. 2007;48(2):214-220.
PubMed
53.
Orlacchio  A, Schillaci  O, Antonelli  L,  et al.  Solitary pulmonary nodules: morphological and metabolic characterisation by FDG-PET-MDCT. Radiol Med. 2007;112(2):157-173.
PubMedArticle
54.
Tsunezuka  Y, Shimizu  Y, Tanaka  N, Takayanagi  T, Kawano  M.  Positron emission tomography in relation to Noguchi’s classification for diagnosis of peripheral non-small-cell lung cancer 2 cm or less in size. World J Surg. 2007;31(2):314-317.
PubMedArticle
55.
Wang  F, Wang  Z, Yao  W, Xie  H, Xu  J, Tian  L.  Role of 99mTc-octreotide acetate scintigraphy in suspected lung cancer compared with 18F-FDG dual-head coincidence imaging. J Nucl Med. 2007;48(9):1442-1448.
PubMedArticle
56.
Veronesi  G, Bellomi  M, Veronesi  U,  et al.  Role of positron emission tomography scanning in the management of lung nodules detected at baseline computed tomography screening. Ann Thorac Surg. 2007;84(3):959-966.
PubMedArticle
57.
Núñez  R, Kalapparambath  A, Varela  J.  Improvement in sensitivity with delayed imaging of pulmonary lesions with FDG-PET. Rev Esp Med Nucl. 2007;26(4):196-207.
PubMedArticle
58.
Ohno  Y, Koyama  H, Takenaka  D,  et al.  Dynamic MRI, dynamic multidetector-row computed tomography (MDCT), and coregistered 2-[fluorine-18]-fluoro-2-deoxy-D-glucose-positron emission tomography (FDG-PET)/CT: comparative study of capability for management of pulmonary nodules. J Magn Reson Imaging. 2008;27(6):1284-1295.
PubMedArticle
59.
Yamamoto  Y, Nishiyama  Y, Ishikawa  S,  et al.  3′-Deoxy-3′-18F-fluorothymidine as a proliferation imaging tracer for diagnosis of lung tumors: comparison with 2-deoxy-2-18f-fluoro-D-glucose. J Comput Assist Tomogr. 2008;32(3):432-437.
PubMedArticle
60.
Jeong  SY, Lee  KS, Shin  KM,  et al.  Efficacy of PET/CT in the characterization of solid or partly solid solitary pulmonary nodules. Lung Cancer. 2008;61(2):186-194.
PubMedArticle
61.
Pauls  S, Buck  AK, Halter  G,  et al.  Performance of integrated FDG-PET/CT for differentiating benign and malignant lung lesions—results from a large prospective clinical trial. Mol Imaging Biol. 2008;10(2):121-128.
PubMedArticle
62.
Alkhawaldeh  K, Bural  G, Kumar  R, Alavi  A.  Impact of dual-time-point (18)F-FDG PET imaging and partial volume correction in the assessment of solitary pulmonary nodules. Eur J Nucl Med Mol Imaging. 2008;35(2):246-252.
PubMedArticle
63.
Baram  D, Bilfinger  TV.  Interaction of clinical suspicion and PET in the diagnosis of suspected thoracic malignancy. Med Sci Monit. 2008;14(7):CR379-CR383.
PubMed
64.
Degirmenci  B, Wilson  D, Laymon  CM,  et al.  Standardized uptake value-based evaluations of solitary pulmonary nodules using F-18 fluorodeoxyglucose-PET/computed tomography. Nucl Med Commun. 2008;29(7):614-622.
PubMedArticle
65.
Lan  XL, Zhang  YX, Wu  ZJ, Jia  Q, Wei  H, Gao  ZR.  The value of dual time point (18)F-FDG PET imaging for the differentiation between malignant and benign lesions. Clin Radiol. 2008;63(7):756-764.
PubMedArticle
66.
Aukema  TS, Valdés Olmos  RA, Klomp  HM,  et al.  Evaluation of (18)F-FDG PET-CT for differentiation of pulmonary pathology in an approach of outpatient fast track assessment. J Thorac Oncol. 2009;4(10):1226-1230.
PubMedArticle
67.
Ohba  Y, Nomori  H, Shibata  H,  et al.  Evaluation of semiquantitative assessments of fluorodeoxyglucose uptake on positron emission tomography scans for the diagnosis of pulmonary malignancies 1 to 3 cm in size. Ann Thorac Surg. 2009;87(3):886-891.
PubMedArticle
68.
Schillaci  O, Travascio  L, Bolacchi  F,  et al.  Accuracy of early and delayed FDG PET-CT and of contrast-enhanced CT in the evaluation of lung nodules: a preliminary study on 30 patients. Radiol Med. 2009;114(6):890-906.
PubMedArticle
69.
Kagna  O, Solomonov  A, Keidar  Z,  et al.  The value of FDG-PET/CT in assessing single pulmonary nodules in patients at high risk of lung cancer. Eur J Nucl Med Mol Imaging. 2009;36(6):997-1004.
PubMedArticle
70.
Chang  C-Y, Tzao  C, Lee  S-C,  et al.  Incremental value of integrated FDG-PET/CT in evaluating indeterminate solitary pulmonary nodule for malignancy. Mol Imaging Biol. 2010;12(2):204-209.
PubMedArticle
71.
Grgic  A, Yüksel  Y, Gröschel  A,  et al.  Risk stratification of solitary pulmonary nodules by means of PET using (18)F-fluorodeoxyglucose and SUV quantification. Eur J Nucl Med Mol Imaging. 2010;37(6):1087-1094.
PubMedArticle
72.
Barnett  PG, Ananth  L, Gould  MK; Veterans Affairs Positron Emission Tomography Imaging in the Management of Patients with Solitary Pulmonary Nodules (VA SNAP) Cooperative Study Group.  Cost and outcomes of patients with solitary pulmonary nodules managed with PET scans. Chest. 2010;137(1):53-59.
PubMedArticle
73.
Huang  Y-E, Pu  Y-L, Huang  Y-J,  et al.  The utility of the nonattenuation corrected 18F-FDG PET images in the characterization of solitary pulmonary lesions. Nucl Med Commun. 2010;31(11):945-951.
PubMedArticle
74.
Ohno  Y, Koyama  H, Matsumoto  K,  et al.  Differentiation of malignant and benign pulmonary nodules with quantitative first-pass 320-detector row perfusion CT versus FDG PET/CT. Radiology. 2011;258(2):599-609.
PubMedArticle
75.
Macdonald  K, Searle  J, Lyburn  I.  The role of dual time point FDG PET imaging in the evaluation of solitary pulmonary nodules with an initial standard uptake value less than 2.5. Clin Radiol. 2011;66(3):244-250.
PubMedArticle
76.
Okereke  IC, Gangadharan  SP, Kent  MS, Nicotera  SP, DeCamp  MM.  [(18)F]Fluorodeoxyglucose positron emission tomography-computerized tomography and lung cancer: a significant referral bias exists. Eur J Cardiothorac Surg. 2011;39(4):560-564.
PubMedArticle
77.
Kubota  K, Murakami  K, Inoue  T, Saga  T, Shiomi  S.  Additional effects of FDG-PET to thin-section CT for the differential diagnosis of lung nodules: a Japanese multicenter clinical study. Ann Nucl Med. 2011;25(10):787-795.
PubMedArticle
78.
Nguyen  NC, Kaushik  A, Wolverson  MK, Osman  MM.  Is there a common SUV threshold in oncological FDG PET/CT, at least for some common indications? a retrospective study. Acta Oncol. 2011;50(5):670-677.
PubMedArticle
79.
Xu  B, Guan  Z, Liu  C,  et al.  Can multimodality imaging using 18F-FDG/18F-FLT PET/CT benefit the diagnosis and management of patients with pulmonary lesions? Eur J Nucl Med Mol Imaging. 2011;38(2):285-292.
PubMedArticle
80.
García Vicente  AM, Castrejón  AS, León Martín  AA, García  BG, Pilkington Woll  JP, Muñoz  AP.  Value of 4-dimensional 18F-FDG PET/CT in the classification of pulmonary lesions. J Nucl Med Technol. 2011;39(2):91-99.
PubMedArticle
81.
Ashraf  H, Dirksen  A, Loft  A,  et al.  Combined use of positron emission tomography and volume doubling time in lung cancer screening with low-dose CT scanning. Thorax. 2011;66(4):315-319.
PubMedArticle
82.
van’t Westeinde  SC, de Koning  HJ, Thunnissen  FB,  et al.  The role of the ¹⁸f-fluorodeoxyglucose-positron emission tomography scan in the Nederlands Leuvens Longkanker screenings Onderzoek lung cancer screening trial. J Thorac Oncol. 2011;6(10):1704-1712.
PubMedArticle
83.
Harders  SW, Madsen  HH, Hjorthaug  K,  et al.  Characterization of pulmonary lesions in patients with suspected lung cancer: computed tomography versus [¹⁸F] fluorodeoxyglucose-positron emission tomography/computed tomography. Cancer Imaging. 2012;12(3):437-446.
PubMedArticle
84.
Fiorelli  A, Rizzo  A, Messina  G,  et al.  Correlation between matrix metalloproteinase 9 and 18F-2-fluoro-2-deoxyglucose-positron emission tomography as diagnostic markers of lung cancer. Eur J Cardiothorac Surg. 2012;41(4):852-860.
PubMedArticle
85.
Dalli  A, Selimoglu Sen  H, Coskunsel  M,  et al.  Diagnostic value of PET/CT in differentiating benign from malignant solitary pulmonary nodules. J BUON. 2013;18(4):935-941.
PubMed
86.
Lopes Pegna  A, Picozzi  G, Falaschi  F,  et al; ITALUNG Study Research Group.  Four-year results of low-dose CT screening and nodule management in the ITALUNG trial. J Thorac Oncol. 2013;8(7):866-875.
PubMedArticle
87.
Ohno  Y, Nishio  M, Koyama  H,  et al.  Comparison of quantitatively analyzed dynamic area-detector CT using various mathematic methods with FDG PET/CT in management of solitary pulmonary nodules. AJR Am J Roentgenol. 2013;200(6):W593-W602.
PubMedArticle
88.
Minamimoto  R, Senda  M, Jinnouchi  S,  et al.  Detection of lung cancer by FDG-PET cancer screening program: a nationwide Japanese survey. Anticancer Res. 2014;34(1):183-189.
PubMed
89.
Zhang  J, Cui  L-B, Tang  X,  et al.  DW MRI at 3.0 T versus FDG PET/CT for detection of malignant pulmonary tumors. Int J Cancer. 2014;134(3):606-611.
PubMedArticle
90.
Menda  Y, Kahn  D.  Somatostatin receptor imaging of non-small cell lung cancer with 99mTc depreotide. Semin Nucl Med. 2002;32(2):92-96.
PubMedArticle
91.
Acker  MR, Burrell  SC.  Utility of 18F-FDG PET in evaluating cancers of lung. J Nucl Med Technol. 2005;33(2):69-74.
PubMed
92.
Delbeke  D, Coleman  RE, Guiberteau  MJ,  et al.  Procedure guideline for tumor imaging with 18F-FDG PET/CT 1.0. J Nucl Med. 2006;47(5):885-895.
PubMed
93.
Beyer  T, Antoch  G, Müller  S,  et al.  Acquisition protocol considerations for combined PET/CT imaging. J Nucl Med. 2004;45(1)(suppl 1):25S-35S.
PubMed
94.
Beyer  T, Townsend  DW, Brun  T,  et al.  A combined PET/CT scanner for clinical oncology. J Nucl Med. 2000;41(8):1369-1379.
PubMed
95.
Yang  W, Zhang  Y, Fu  Z, Sun  X, Mu  D, Yu  J.  Imaging proliferation of ¹⁸F-FLT PET/CT correlated with the expression of microvessel density of tumour tissue in non-small-cell lung cancer. Eur J Nucl Med Mol Imaging. 2012;39(8):1289-1296.
PubMedArticle
96.
Dittmann  H, Dohmen  BM, Paulsen  F,  et al.  [18F]FLT PET for diagnosis and staging of thoracic tumours. Eur J Nucl Med Mol Imaging. 2003;30(10):1407-1412.
PubMedArticle
97.
Baylin  SB, Jackson  RD, Goodwin  G, Gazdar  AF.  Neuroendocrine-related biochemistry in the spectrum of human lung cancers. Exp Lung Res. 1982;3(3-4):209-223.
PubMedArticle
98.
Zhuang  H, Pourdehnad  M, Lambright  ES,  et al.  Dual time point 18F-FDG PET imaging for differentiating malignant from inflammatory processes. J Nucl Med. 2001;42(9):1412-1417.
PubMed
99.
Gould  MK, Fletcher  J, Iannettoni  MD,  et al; American College of Chest Physicians.  Evaluation of patients with pulmonary nodules: when is it lung cancer?: ACCP evidence-based clinical practice guidelines (2nd edition). Chest. 2007;132(3)(suppl):108S-130S.
PubMedArticle
100.
Aberle  DR, Adams  AM, Berg  CD,  et al; National Lung Screening Trial Research Team.  Reduced lung-cancer mortality with low-dose computed tomographic screening. N Engl J Med. 2011;365(5):395-409.
PubMedArticle
Original Investigation
September 24, 2014

Accuracy of FDG-PET to Diagnose Lung Cancer in Areas With Infectious Lung DiseaseA Meta-analysis

Author Affiliations
  • 1Veterans Affairs Hospital, Tennessee Valley Healthcare System, Nashville
  • 2Department of Thoracic Surgery, Vanderbilt University Medical Center, Nashville, Tennessee
  • 3Department of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee
  • 4Department of Surgery, Vanderbilt University Medical Center, Nashville, Tennessee
  • 5School of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
  • 6Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
  • 7Division of Pulmonary and Critical Care Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
  • 8Department of Medical Imaging, Tennessee Valley Healthcare System-Veterans Affairs, Nashville
  • 9Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, Tennessee
  • 10Division of Obstetrics and Gynecology, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
JAMA. 2014;312(12):1227-1236. doi:10.1001/jama.2014.11488
Abstract

Importance  Positron emission tomography (PET) combined with fludeoxyglucose F 18 (FDG) is recommended for the noninvasive diagnosis of pulmonary nodules suspicious for lung cancer. In populations with endemic infectious lung disease, FDG-PET may not accurately identify malignant lesions.

Objectives  To estimate the diagnostic accuracy of FDG-PET for pulmonary nodules suspicious for lung cancer in regions where infectious lung disease is endemic and compare the test accuracy in regions where infectious lung disease is rare.

Data Sources and Study Selection  Databases of MEDLINE, EMBASE, and the Web of Science were searched from October 1, 2000, through April 28, 2014. Articles reporting information sufficient to calculate sensitivity and specificity of FDG-PET to diagnose lung cancer were included. Only studies that enrolled more than 10 participants with benign and malignant lesions were included. Database searches yielded 1923 articles, of which 257 were assessed for eligibility. Seventy studies were included in the analysis. Studies reported on a total of 8511 nodules; 5105 (60%) were malignant.

Data Extraction and Synthesis  Abstracts meeting eligibility criteria were collected by a research librarian and reviewed by 2 independent reviewers. Hierarchical summary receiver operating characteristic curves were constructed. A random-effects logistic regression model was used to summarize and assess the effect of endemic infectious lung disease on test performance.

Main Outcome and Measures  The sensitivity and specificity for FDG-PET test performance.

Results  Heterogeneity for sensitivity (I2 = 87%) and specificity (I2 = 82%) was observed across studies. The pooled (unadjusted) sensitivity was 89% (95% CI, 86%-91%) and specificity was 75% (95% CI, 71%-79%). There was a 16 percentage point–lower average adjusted specificity in regions with endemic infectious lung disease (61% [95% CI, 49%-72%]) compared with nonendemic regions (77% [95% CI, 73%-80%]). Lower specificity was observed when the analysis was limited to rigorously conducted and well-controlled studies. In general, sensitivity did not change appreciably by endemic infection status, even after adjusting for relevant factors.

Conclusions and Relevance  The accuracy of FDG-PET for diagnosing lung nodules was extremely heterogeneous. Use of FDG-PET combined with computed tomography was less specific in diagnosing malignancy in populations with endemic infectious lung disease compared with nonendemic regions. These data do not support the use of FDG-PET to diagnose lung cancer in endemic regions unless an institution achieves test performance accuracy similar to that found in nonendemic regions.

Introduction

Clinicians rely heavily on radiographic imaging to identify and noninvasively diagnose lung nodules between 3 and 30 mm in diameter. The advent of lung cancer screening in high-risk populations using low-dose computed tomographic (CT) scans will increase the number of lung nodules detected, requiring clinical evaluation and diagnosis.1 Depending on the risk for cancer, diagnostic guidelines suggest or recommend fludeoxyglucose F 18 (FDG) combined with positron emission tomography (PET) as a noninvasive test to assess the risk of cancer or benign disease.24

In previously published meta-analyses,5,6 FDG-PET was reported to be 90% to 94% accurate in the characterization of malignant or benign lung nodules, with a sensitivity of 94% to 96% and a specificity of 78% to 86%. Furthermore, combined FDG-PET and CT (FDG-PET/CT) scans have demonstrated a reduction in nontherapeutic resections (eg, resection for benign lesions or metastatic disease) by 17% to 20%.7,8 For these reasons, FDG-PET/CT is widely accepted for the clinical diagnosis and staging of lung cancer in patients with suspicious lung nodules.2,9

Recent studies examining FDG-PET accuracy in diagnosing lung cancer in patients with lung lesions who reside in regions where fungal and other infectious lung diseases are endemic have shown mixed results.10,11 Histoplasmosis, coccidioidomycosis, and blastomycosis are the most prevalent fungal lung diseases in the United States,12,13 and are common etiologies of lung granulomas.12 Histoplasmosis and blastomycosis are endemic across much of the Mississippi, Ohio, and Missouri river valley regions through southern Ontario, Canada, whereas coccidioidomycosis is prevalent in the southwestern United States.12 Two international studies in areas with endemic tuberculosis found reduced FDG-PET/CT specificities of 25%14 and 21%.15

We undertook a systematic review and meta-analysis of the literature published after the 2001 meta-analysis by Gould et al6 describing FDG-PET accuracy to diagnose lung cancer among patients being evaluated with lung nodules or masses. This updated meta-analysis investigates the accuracy of FDG-PET to diagnose lung lesions in regions with locally endemic infectious lung diseases.

Methods

Studies evaluating individuals for possible lung cancer using FDG-PET, FDG-PET/CT, or FDG-PET combined with another imaging modality were reviewed. We searched MEDLINE using the PubMed interface, EMBASE, and the Web of Science for studies published between October 1, 2000, and April 28, 2014 (eTable 1 in the Supplement). The guidelines for Preferred Reporting Items for Systematic Reviews and Meta-Analyses were followed.16 Reasons for study exclusion are detailed in Figure 1.

A study was classified as being from an endemic infectious region or population when the study reported presence of infectious lung diseases in the population from which participants were recruited or if granulomas arising from infectious lung diseases comprised at least 50% of reported benign etiologies. PET scan results were described by method of measuring FDG-PET avidity, the levels of risk or avidity, and the standardized uptake value threshold used to differentiate benign and cancerous diagnosis of disease. Details of study selection, data extraction, and synthesis are described in the eMethods in the Supplement.

Data Synthesis and Analysis

The sensitivity and specificity for FDG-PET test performance (pooled across studies) are displayed using forest plots. Study heterogeneity was assessed with the I2 statistic. Test performance in the presence of heterogeneity17 was summarized using hierarchical summary receiver operator curves (HSROC). Stability of test accuracy over time was assessed with diagnostic odds ratios and in the context of a random-effects model.

Publication bias was visually inspected using a funnel plot and quantitatively measured (eMethods in the Supplement).18 Study quality was measured using a modified Quality Assessment of Diagnostic Accuracy Studies questionnaire (eMethods in the Supplement).19,20 Verification bias was defined as occurring when all diagnoses were determined pathologically or when a pathological diagnosis was coupled with a period of radiographic surveillance shorter than 12 months.21,22

A large I2 value indicates the data are not consistent with a simple pooling model; a more sophisticated model is needed to properly combine the data. Accordingly, a random-effects logistic regression was used to model test performance and account for heterogeneity among studies not attributable to observed study characteristics.

Study characteristics included in the model were endemic infectious lung disease in the study population, mean or median lesion diameter of less than 2 cm, scanner type as either PET only, combined PET and CT, or PET and another scanning modality (eg, time-delayed PET, magnetic resonance imaging, volumetric CT), study quality score, and whether the study relied on only pathological determination of diagnosis. In studies with multiple imaging modalities, only the FDG-PET/CT portion of the results were used (eTable 2 in the Supplement).

Quality score was dichotomized with higher-quality studies (defined as those having at least 70% [≥11] affirmative quality questions).23 The final model equations, procedures used for model selection, methods of assessing model fit, and details on numerical fitting appear in the eMethods in the Supplement. Missing data were handled with multiple imputation performed using chained equations (10 imputations were used; details appear in the eMethods and eTable 3 in the Supplement).

The regression model provides an estimate of sensitivity (or specificity) adjusted to a particular set of study characteristics (ie, a particular study profile). These adjusted estimates are then averaged together to yield a single, average estimate of sensitivity (or specificity). This estimate, which we refer to as the average adjusted estimate, is similar to a simple pooled unadjusted estimate of sensitivity or specificity, except that the average adjusted estimate now properly accounts for the various study profiles observed in our sample.

To maintain generalizability, the averaging of adjusted estimates occurs with respect to the observed frequency of study profiles in our sample. We report the average adjusted estimates of sensitivity and specificity because of the ease of their interpretation and general applicability. We also calculated certain adjusted estimates of sensitivity and specificity as a sensitivity analysis to ensure result robustness. We defined rigorously conducted and well-controlled studies as studies with high quality, lesion size of less than 2 cm, use of a diagnostic method that minimizes the likelihood of verification bias, and use of combined PET and CT.

In addition to using 95% confidence intervals to estimate population parameters, we used 95% prediction intervals (PIs) to estimate the anticipated performance of a single study randomly chosen from this population of studies. The PIs describe the population heterogeneity of test performance. All statistical tests were 2-sided with a type I error of .05. All analyses were performed with Stata version 12 (StataCorp) and R version 2.15.3 (R Foundation for Statistical Computing).

Results

A total of 1923 articles were found; 16 articles were added from bibliography reviews along with an unpublished abstract. Forty-six articles were removed as duplicates and 1893 studies were screened. Upon initial abstract review, 1636 articles were excluded. An article could be excluded for multiple reasons, but the most common reason for exclusion during either portion of the review was inclusion of participants with 100% cancer prevalence (n = 1025).

Two hundred and fifty-seven studies received full review, of which 187 were excluded upon secondary review. The remaining 70 studies met all inclusion criteria and were used for the final analysis (eTable 4 in the Supplement). The total number of reported nodules being evaluated by FDG-PET among the 70 studies was 8511 and the median number of nodules per study was 83 (interquartile range, 56-140 nodules/study). Pooled cancer prevalence among nodules was 60% (n=5105 nodules). Individual study cancer prevalence varied from 21% to 86% across studies. Ten of 70 studies documented endemic infectious lung disease.10,11,14,15,2429

The overall agreement for study eligibility between reviewers was 94.8% and the κ was 0.72 (using the method by Cohen), showing moderate agreement between reviewers. Consensus was used when reviewers disagreed; agreement was not reviewed quantitatively. Despite contacting corresponding authors, missing data on mean or median nodule size remained in 12 studies. Among the 49 studies reporting a mean or median lesion size, the median lesion size across studies was 2 cm (interquartile range, 1.7-2.8 cm).

Meta-analysis

An unadjusted pooled analysis of the 70 studies showed evidence of significant heterogeneity among studies in sensitivity (I2 of 87% [95% CI, 85%-90%]) and specificity (I2 of 82% [95% CI, 78%-86%]). Pooled sensitivity of FDG-PET for diagnosing lung cancer was 89% (95% CI, 86%-91%) and pooled specificity was 75% (95% CI, 71%-79%).

Ten studies reporting endemic disease had an unadjusted pooled specificity of 54% (95% CI, 37%-69%)10,11,14,15,2429 compared with 78% (95% CI, 74%-81%) in the remaining 60 studies. The asymmetry test (using the method by Deeks et al18) did not show evidence of publication bias (P = .14). No trend over time or between periods in diagnostic accuracy was observed (eResults in the Supplement).

A random-effects model that included a random intercept for each study and various fixed effects for the study characteristics (eMethods, eTable 5, and the eFigure in the Supplement) was used to account for the observed heterogeneity. The model yielded an average adjusted estimate of sensitivity of 89% (95% CI, 87%-91%) and specificity of 75% (95% CI, 71%-78%) (Figure 2).3089

The area under the HSROC curve (Figure 3) was 0.90 (95% CI, 0.87-0.92). The PIs show the extreme amount of heterogeneity among studies that remains after adjusting for study characteristics. The sensitivity of a randomly chosen study was predicted as 89% (95% PI, 70%-97%) and specificity was 75% (95% PI, 45%-91%). Similar increases in PI length were observed for all analyses. The results presented in the following sections are adjusted results from the random-effects model using multiple imputation.

Infectious Lung Disease

Ten studies reporting infectious lung disease endemic to the local population comprised 1431 individuals, of whom 1082 had cancer (76%). Granulomas as a percentage of benign diagnoses ranged from 45%26 to 75%.14 Studies of populations in China,27 South Africa,14 and Japan15 reported tuberculosis as the common etiology for granulomatous disease.

The remaining North American studies found histoplasmosis, coccidioidomycosis, inflammation, and unspecified granuloma as common etiologies for pathologically diagnosed benign disease. Four of the 10 studies were retrospective10,25,28,29 and 7 studies10,11,14,15,25,26,29 determined diagnosis with pathology only.

The specificity was estimated to be 16 percentage points lower in populations with endemic infectious lung disease. This lower specificity persisted at 14% even for rigorously conducted and well-controlled studies. The average adjusted estimate of specificity in regions with endemic disease was 61% (95% CI, 49%-72%) compared with 77% (95% CI, 73%-80%) for nonendemic regions (Figure 3). For rigorously conducted and well-controlled studies, the estimates of specificity in endemic and nonendemic regions were 66% (95% CI, 51%-78%) and 80% (95% CI, 74%-85%), respectively.

The average adjusted sensitivity did not significantly differ by endemic status (94% [95% CI, 90%-96%] vs 88% [95% CI, 85%-90%] in nonendemic regions). The adjusted estimate of sensitivity in rigorously conducted and well-controlled studies was slightly higher in endemic regions (96% [95% CI, 92%-98%] vs 90% [95% CI, 86%-93%] in nonendemic regions).

Size of Lesion

Among the 34 studies reporting average or median lesion diameters of less than or equal to 2 cm, the average adjusted sensitivity was 87% (95% CI, 84%-90%).14,24,2629,32,39,45,46,48,50,5254,58,60,62,64,6769,72,74,75,77,8083,8588 In comparison, 23 studies with average or median diameters of greater than 2 cm had a slightly higher average adjusted sensitivity (91% [95% CI, 89%-93%]).10,11,15,25,30,31,34,35,37,41,43,44,5557,61,63,73,76,78,79,84,86 Specificity of FDG-PET to diagnose lung cancer was not significantly influenced by lesion size (74% for studies with lesions ≤2 cm and 75% for studies with larger average lesion size).

Type of FDG-PET Scan

The 40 studies using FDG-PET/CT demonstrated slightly better average adjusted sensitivity (90% [95% CI, 88%-92%]) compared with the 19 studies using only FDG-PET (89% [95% CI, 84%-92%]) or the studies combining FDG-PET with another method of imaging (82% [95% CI, 75%-89%]).11,15,25,30,3237,39,40,47,4951,54,57,75,90 Scanner type had little association with specificity. The average adjusted specificity for studies that used a FDG-PET or FDG-PET/CT in combination with another imaging modality (75%) was similar to studies using only FDG-PET/CT (76%).38,4143,53,62,75,79,80,87

PET not combined with CT or with other imaging modalities had a slightly worse average adjusted specificity of 70% (95% CI, 62%-77%) compared with FDG-PET/CT or FDG-PET plus another imaging modality. Among the other imaging modalities reported, 2 studies used single-photon emission CT as the alternative secondary scanning modality.41,43 Two studies used dynamic, 3-dimensional CT scanning.53,87 Two studies reported using F18-fluorothyminidine in conjunction with FDG.42,79 One study used a sodium iodide detector38 and 3 studies created algorithms of staggered PET scans and changes in standard uptake values (dual-time point).28,62,80

Study Quality

Study quality scores ranged from 3 to 14 (median score was 10 of 15 possible points). The quality metric that most studies failed to meet was patients receiving the same reference standard regardless of index test result (67%). Studies often lacked sufficient numbers of benign cases (29 studies had <25 benign cases). Most studies (81%) emulated the use of the FDG-PET scan in current clinical practice.

Lower-quality studies had reduced average adjusted sensitivity (87% [95% CI, 85%-90%]) compared with higher-quality studies (91% [95% CI, 88%-93%]) after controlling for other study characteristics in the regression model. Average adjusted specificity was similar across lower-quality studies (75%) compared with higher-quality studies (74%). Studies that relied on either pathological diagnosis or less than 1 year of follow-up had similar average adjusted sensitivity (87% [95% CI, 83%-90%]) compared with those that did not (90% [95% CI, 88%-92%]).

The average adjusted specificity among studies that relied on a combination of prolonged surveillance and pathological diagnosis had higher average adjusted specificity (77% [95% CI, 73%-81%]) than those that exhibited possible verification bias (69% [95% CI, 61%-75%]). Additional study quality results are provided in the eResults in the Supplement.

Sensitivity Analysis for the Effect of Individual Studies on Pooled Estimates

Removal of the largest study by Bryant and Cerfolio26 (n = 585), which reported endemic infectious lung disease, reduced the average adjusted specificity from 61% to 56% in studies with endemic infectious lung disease. Its removal had little influence on the sensitivity of the test in either average adjusted results or in the endemic infectious lung disease populations. A sensitivity analysis using the distance method by Cook identified 1 study (García Vicente et al80) as potentially overly influential. However, its exclusion did not noticeably change results. No individual study unduly influenced the estimated sensitivity or specificity of FDG-PET.

Discussion

For the last decade, molecular imaging with FDG-PET has become part of the diagnostic arsenal of tests considered for the evaluation of suspicious lung nodules. This method of imaging is suggested based on low-quality evidence (grade 2C) for the diagnosis of solid nodules larger than 8 mm.2 The limitation of FDG-PET in the diagnosis of smaller lesions is well documented and this meta-analysis also found studies reporting lesions smaller than 2 cm had lower sensitivity compared with studies reporting on larger nodules.3,91,92 Previous meta-analyses found FDG-PET to be highly sensitive (94% to 96%) and reasonably specific (78% to 86%) in the diagnosis of lung cancer.5,6 Compared with prior studies, the sensitivity and specificity in our meta-analysis was lower. The HSROC was 0.9, which is similar to that reported by Gould et al,6 and our study also exhibited heterogeneity across studies.

In the 2001 meta-analysis,6 727 of the 1474 lesions (49%) were from Japanese or European populations. Also, a portion of the studies in the meta-analysis were populations from the northeast or other areas of the United States where granulomatous disease is less common. Similarly in the study by Cronin et al,5 860 of the 1190 lesions (72%) reported in the 22 studies reviewed were from geographic areas where infectious lung disease is rare.

In regions where infectious lung disease is highly prevalent, the specificity of FDG-PET scans to diagnose lung nodules suspicious for lung cancer in our study was approximately 61%. However, the best specificity in endemic regions (from either the average adjusted or adjusted results) was 66%. Therefore, in individuals being evaluated for a suspicious lung lesion, and who reside in a region with significant endemic infectious lung disease, FDG-PET/CT does not reliably distinguish benign disease from lung cancer.

We have shown that the specificity of FDG-PET/CT for the diagnosis of lung cancer was overstated in regions with endemic infectious lung disease and could lead to unnecessary biopsies or thoracotomies for indeterminate lung nodules. Knowledge of this limitation in such regions is especially important if low-dose CT screening for lung cancer is widely adopted and should be reflected in current nodule management guidelines.2,3

Our review included more studies and had greater heterogeneity in both sensitivity and specificity compared with the earlier meta-analyses by Gould et al6 and Cronin et al.5 Some heterogeneity across studies arises from the scanning method, the size of the lesion examined, whether the study relied only on pathological verification of cancer, and the prevalence of endemic infectious lung disease in the study population. However, there remained substantial variability among studies in test performance that was not accounted for by these factors.

We observed a transition in the literature from scanners using FDG-PET only to FDG-PET/CT since their introduction into clinical practice in 2001.93,94 Recently, radiologists have undertaken significant efforts to find a complement or replacement for the FDG radionuclide or the positron emission image-generating scanner.42,9598

We attempted to include the breadth of research in PET for lung nodule diagnosis by searching for studies that compared new modalities or radionuclides with existing FDG-PET or PET plus CT. Multimodality studies collectively had a higher specificity (80%) compared with studies using either FDG-PET or CT alone, but as a group they may be susceptible to publication bias that potentially decreases the accuracy of FDG-PET compared with the newer imaging methods.

To date, no replacement for FDG has been suggested for the diagnosis of lung nodules suspicious for lung cancer.91,99 In addition, a majority of participants (n = 4615) were in studies in which the mean or median lesion size was less than or equal to 2 cm. The lower sensitivity observed in this analysis arises, in part, from the application of this diagnostic modality to a broader clinical population with both smaller lesions and a greater likelihood of infectious disease.

After adjusting for study characteristics in our model, the precision of estimated sensitivity and specificity is quite good (shown by the narrow 95% CIs in Figure 3). However, variability remains even after adjusting for known study characteristics as shown in the distribution of individual study sensitivity and specificity estimates and combined PIs.

The range of test performance observed in practice is quite large (shown by the wide PIs in Figure 3). These reflect a lack of consistency in the application of FDG-PET diagnosis for lung nodules that is concerning and this meta-analysis suggests significant variability in practice patterns. Accordingly, technical standards and consistent adherence to imaging protocols and image interpretation should be strictly followed to reduce these inconsistencies. This is especially important in smaller lesions (<2 cm) and in regions with endemic infectious lung disease to prevent false-positive and negative test results that could cause harm to patients.

The limitations of this analysis are those common to meta-analyses (eg, publication bias, selection bias, limited information from study reports, and potential for ecological fallacy). Even though we did not find evidence of significant publication bias, this does not exclude its possibility. Because FDG-PET was recommended for the diagnosis of lung cancer, a publication bias to report poor FDG-PET accuracy or negative results may exist.

Studies reporting results from scanners with FDG-PET only may no longer reflect clinical practice and arguably should not be included in this analysis. However, we controlled for the shortcomings of scanners with FDG-PET only in the regression model so that additional studies reporting results from smaller lesions and from regions with endemic infectious lung disease could be explored.

Although the accuracy of FDG-PET/CT is superior to the accuracy of FDG-PET only, we included both modalities because they are still in use in the United States and elsewhere, and, as previously stated, we did not find a significant difference in specificity based on these 2 scanner types. To avoid selection bias, this meta-analysis attempted to broadly review studies reporting use of FDG-PET to characterize lung nodules and examined studies in which FDG-PET/CT was compared with other imaging modalities for the diagnosis and staging of lung cancer. We controlled for study heterogeneity using a random-effects regression model with a number of clinically important covariates; however, residual confounding may still be present.

In this large meta-analysis, the observed association between lower specificity and endemic infectious lung disease appeared robust across sensitivity analyses. We found that studies that fully used the metabolic and anatomic information from a FDG-PET/CT scan in a semiquantitative interpretation (rather than a simplified dichotomizing of a standard uptake value) demonstrated improved test accuracy. Even in regions of endemic disease, robust reading methods by experienced readers generated accurate scans.26,27

Until this expertise and method is more uniformly applied among scan readers, FDG-PET for the diagnosis of lung cancer in patients who reside in a region with significant endemic infectious lung disease should be recognized as having lower specificity (approximately 61%) than previously reported. Knowledge of this reduction in specificity should limit the use of FDG-PET to diagnose lung cancer unless substantial institutional expertise in FDG-PET interpretation has been proven. Should low-dose CT screening for lung cancer become the diagnostic standard, knowledge of FDG-PET/CT performance is even more critical because the vast majority of indeterminate lung nodules detected through screening are benign.100

Conclusions

The accuracy of FDG-PET for diagnosing lung nodules was extremely heterogeneous. Use of FDG-PET/CT was less specific in diagnosing malignancy in populations with endemic infectious lung disease compared with nonendemic regions. These data do not support the use of FDG-PET to diagnose lung cancer in endemic regions unless an institution achieves test performance accuracy similar to that found in nonendemic regions.

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Article Information

Corresponding Author: Eric L. Grogan, MD, MPH, Vanderbilt University Medical Center, 1313 21st Ave S, 609 Oxford House, Nashville, TN 37232 (eric.grogan@vanderbilt.edu).

Author Contributions: Drs Deppen and Grogan had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Study concept and design: Deppen, Aldrich, Massion, Putnam, Grogan.

Acquisition, analysis, or interpretation of data: Deppen, Blume, Kensinger, Morgan, Massion, Walker, McPheeters, Putnam.

Drafting of the manuscript: Deppen, Blume, Walker.

Critical revision of the manuscript for important intellectual content: All authors.

Statistical analysis: Deppen, Blume.

Obtained funding: Deppen, Putnam, Grogan.

Administrative, technical, or material support: Deppen, Kensinger, Walker.

Study supervision: Blume, Aldrich, Massion, Walker, McPheeters, Putnam, Grogan.

Conflict of Interest Disclosures: The authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest and none were reported.

Funding/Support: This work was supported by grant R03HS021554-01 from the Agency for Healthcare Research and Quality (Dr Grogan). This work was also supported by the Department of Veterans Affairs, Veterans Health Administration, Health Services Research and Development Service Career Development award 10-024 (Dr Grogan), grant K07CA172294 from the National Institutes of Health and the National Cancer Institute (Dr Aldrich), Vanderbilt Institute for Clinical and Translational Research grant UL1TR000011 from the National Center for Advancing Translational Sciences at the National Institutes of Health (REDCap database), the lung SPORE grant CA90949 from the National Cancer Institute (Dr Massion), and grant U01CA152662 from the Early Detection Research Network (an initiative of the National Cancer Institute) (Dr Massion).

Role of the Funder/Sponsor: The funders/sponsors had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Additional Contributions: We thank Rebecca Jerome, MLS, MPH (research librarian at Vanderbilt University Medical Center), for her uncompensated assistance in the literature review.

Correction: This article was corrected on September 30, 2014, to fix 16% to 16 percentage points for specificity in regions with endemic disease in the abstract and Results section.

References
1.
Humphrey  LL, Deffebach  M, Pappas  M,  et al.  Screening for lung cancer with low-dose computed tomography: a systematic review to update the U.S. Preventive Services Task Force recommendation. Ann Intern Med. 2013;159(6):411-420.
PubMedArticle
2.
Gould  MK, Donington  J, Lynch  WR,  et al.  Evaluation of individuals with pulmonary nodules: when is it lung cancer? diagnosis and management of lung cancer, 3rd ed: American College of Chest Physicians evidence-based clinical practice guidelines. Chest. 2013;143(5)(suppl):e93S-e120S.
PubMedArticle
3.
National Comprehensive Cancer Network. National Comprehensive Cancer Network clinical practice guidelines in oncology. http://www.nccn.org/professionals/physician_gls/recently_updated.asp. Accessed May 20, 2014.
4.
MacMahon  H, Austin  JH, Gamsu  G,  et al; Fleischner Society.  Guidelines for management of small pulmonary nodules detected on CT scans: a statement from the Fleischner Society. Radiology. 2005;237(2):395-400.
PubMedArticle
5.
Cronin  P, Dwamena  BA, Kelly  AM, Carlos  RC.  Solitary pulmonary nodules: meta-analytic comparison of cross-sectional imaging modalities for diagnosis of malignancy. Radiology. 2008;246(3):772-782.
PubMedArticle
6.
Gould  MK, Maclean  CC, Kuschner  WG, Rydzak  CE, Owens  DK.  Accuracy of positron emission tomography for diagnosis of pulmonary nodules and mass lesions: a meta-analysis. JAMA. 2001;285(7):914-924.
PubMedArticle
7.
Herder  GJ, Golding  RP, Hoekstra  OS,  et al.  The performance of (18)F-fluorodeoxyglucose positron emission tomography in small solitary pulmonary nodules. Eur J Nucl Med Mol Imaging. 2004;31(9):1231-1236.
PubMedArticle
8.
Silvestri  GA, Gould  MK, Margolis  ML,  et al; American College of Chest Physicians.  Noninvasive staging of non-small cell lung cancer: ACCP evidenced-based clinical practice guidelines (2nd edition). Chest. 2007;132(3)(suppl):178S-201S.
PubMedArticle
9.
Detterbeck  FC, Postmus  PE, Tanoue  LT.  The stage classification of lung cancer: diagnosis and management of lung cancer, 3rd ed: American College of Chest Physicians evidence-based clinical practice guidelines. Chest. 2013;143(5)(suppl):e191S-e210S.
PubMedArticle
10.
Deppen  S, Putnam  JB  Jr, Andrade  G,  et al.  Accuracy of FDG-PET to diagnose lung cancer in a region of endemic granulomatous disease. Ann Thorac Surg. 2011;92(2):428-433.
PubMedArticle
11.
Croft  DR, Trapp  J, Kernstine  K,  et al.  FDG-PET imaging and the diagnosis of non-small cell lung cancer in a region of high histoplasmosis prevalence. Lung Cancer. 2002;36(3):297-301.
PubMedArticle
12.
Mason  R, Broaddus  V, Martin  T. In: Murray  J, Nadel  J, eds. Murray and Nadel's Textbook of Respiratory Medicine.5th ed. Philadelphia, PA: Saunders; 2010.
13.
Bradsher  RW.  Histoplasmosis and blastomycosis. Clin Infect Dis. 1996;22(suppl 2):S102-S111.
PubMedArticle
14.
Sathekge  MM, Maes  A, Pottel  H, Stoltz  A, van de Wiele  C.  Dual time-point FDG PET-CT for differentiating benign from malignant solitary pulmonary nodules in a TB endemic area. S Afr Med J. 2010;100(9):598-601.
PubMed
15.
Mamede  M, Higashi  T, Kitaichi  M,  et al.  [18F]FDG uptake and PCNA, Glut-1, and Hexokinase-II expressions in cancers and inflammatory lesions of the lung. Neoplasia. 2005;7(4):369-379.
PubMedArticle
16.
Moher  D, Liberati  A, Tetzlaff  J, Altman  DG; PRISMA group.  Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Ann Intern Med. 2009;151(4):264-269, W64.
PubMedArticle
17.
Rutter  CM, Gatsonis  CA.  A hierarchical regression approach to meta-analysis of diagnostic test accuracy evaluations. Stat Med. 2001;20(19):2865-2884.
PubMedArticle
18.
Deeks  JJ, Macaskill  P, Irwig  L.  The performance of tests of publication bias and other sample size effects in systematic reviews of diagnostic test accuracy was assessed. J Clin Epidemiol. 2005;58(9):882-893.
PubMedArticle
19.
Fontela  PS, Pant Pai  N, Schiller  I, Dendukuri  N, Ramsay  A, Pai  M.  Quality and reporting of diagnostic accuracy studies in TB, HIV and malaria: evaluation using QUADAS and STARD standards. PLoS One. 2009;4(11):e7753.
PubMedArticle
20.
Whiting  P, Rutjes  AW, Reitsma  JB, Bossuyt  PM, Kleijnen  J.  The development of QUADAS: a tool for the quality assessment of studies of diagnostic accuracy included in systematic reviews. BMC Med Res Methodol. 2003;3(1):25.
PubMedArticle
21.
Ost  D, Fein  AM, Feinsilver  SH.  Clinical practice: the solitary pulmonary nodule. N Engl J Med. 2003;348(25):2535-2542.
PubMedArticle
22.
Patel  VK, Naik  SK, Naidich  DP,  et al.  A practical algorithmic approach to the diagnosis and management of solitary pulmonary nodules: part 2: pretest probability and algorithm. Chest. 2013;143(3):840-846.
PubMedArticle
23.
Gould  MK, Kuschner  WG, Rydzak  CE,  et al.  Test performance of positron emission tomography and computed tomography for mediastinal staging in patients with non-small-cell lung cancer: a meta-analysis. Ann Intern Med. 2003;139(11):879-892.
PubMedArticle
24.
Chundru  S, Wong  CY, Wu  D,  et al.  Granulomatous disease: is it a nuisance or an asset during PET/computed tomography evaluation of lung cancers? Nucl Med Commun. 2008;29(7):623-627.
PubMedArticle
25.
Kim  SC, Machac  J, Krynyckyi  BR,  et al.  Fluoro-deoxy-glucose positron emission tomography for evaluation of indeterminate lung nodules: assigning a probability of malignancy may be preferable to binary readings [published correction appears in Ann Nucl Med. 2010;24(3):231]. Ann Nucl Med. 2008;22(3):165-170.
PubMedArticle
26.
Bryant  AS, Cerfolio  RJ.  The maximum standardized uptake values on integrated FDG-PET/CT is useful in differentiating benign from malignant pulmonary nodules. Ann Thorac Surg. 2006;82(3):1016-1020.
PubMedArticle
27.
Li  Y, Su  M, Li  F, Kuang  A, Tian  R.  The value of ¹⁸F-FDG-PET/CT in the differential diagnosis of solitary pulmonary nodules in areas with a high incidence of tuberculosis. Ann Nucl Med. 2011;25(10):804-811.
PubMedArticle
28.
Kadaria  D, Archie  DS, SultanAli  I, Weiman  DS, Freire  AX, Zaman  MK.  Dual time point positron emission tomography/computed tomography scan in evaluation of intrathoracic lesions in an area endemic for histoplasmosis and with high prevalence of sarcoidosis. Am J Med Sci. 2013;346(5):358-362.
PubMedArticle
29.
Sebro  R, Aparici  CM, Hernandez-Pampaloni  M.  FDG PET/CT evaluation of pathologically proven pulmonary lesions in an area of high endemic granulomatous disease. Ann Nucl Med. 2013;27(4):400-405.
PubMedArticle
30.
Halter  G, Storck  M, Guhlmann  A, Frank  J, Grosse  S, Liewald  F.  FDG positron emission tomography in the diagnosis of peripheral pulmonary focal lesions. Thorac Cardiovasc Surg. 2000;48(2):97-101.
PubMedArticle
31.
Menda  Y, Bushnell  DL, Madsen  MT, McLaughlin  K, Kahn  D, Kernstine  KH.  Evaluation of various corrections to the standardized uptake value for diagnosis of pulmonary malignancy. Nucl Med Commun. 2001;22(10):1077-1081.
PubMedArticle
32.
Higashi  K, Ueda  Y, Sakuma  T,  et al.  Comparison of [(18)F]FDG PET and (201)Tl SPECT in evaluation of pulmonary nodules. J Nucl Med. 2001;42(10):1489-1496.
PubMed
33.
Skehan  SJ, Coates  G, Otero  C, O’Donovan  N, Pelling  M, Nahmias  C.  Visual and semiquantitative analysis of 18F-fluorodeoxyglucose positron emission tomography using a partial-ring tomograph without attenuation correction to differentiate benign and malignant pulmonary nodules. Can Assoc Radiol J. 2001;52(4):259-265.
PubMed
34.
Imdahl  A, Jenkner  S, Brink  I,  et al.  Validation of FDG positron emission tomography for differentiation of unknown pulmonary lesions. Eur J Cardiothorac Surg. 2001;20(2):324-329.
PubMedArticle
35.
Sasaki  M, Kuwabara  Y, Yoshida  T,  et al.  Comparison of MET-PET and FDG-PET for differentiation between benign lesions and malignant tumors of the lung. Ann Nucl Med. 2001;15(5):425-431.
PubMedArticle
36.
Uppot  RN, Conde  K, Sagar  V, Manzone  T.  Positron emission tomography (PET) imaging for solitary pulmonary nodules—review of the Delaware experience. Del Med J. 2001;73(10):381-385.
PubMed
37.
Yang  SN, Liang  JA, Lin  FJ, Kwan  AS, Kao  CH, Shen  YY.  Differentiating benign and malignant pulmonary lesions with FDG-PET. Anticancer Res. 2001;21(6A):4153-4157.
PubMed
38.
Keith  CJ, Miles  KA, Griffiths  MR, Wong  D, Pitman  AG, Hicks  RJ.  Solitary pulmonary nodules: accuracy and cost-effectiveness of sodium iodide FDG-PET using Australian data. Eur J Nucl Med Mol Imaging. 2002;29(8):1016-1023.
PubMedArticle
39.
Lee  J, Aronchick  JM, Alavi  A.  Accuracy of F-18 fluorodeoxyglucose positron emission tomography for the evaluation of malignancy in patients presenting with new lung abnormalities: a retrospective review. Chest. 2001;120(6):1791-1797.
PubMedArticle
40.
Pastorino  U, Bellomi  M, Landoni  C,  et al.  Early lung-cancer detection with spiral CT and positron emission tomography in heavy smokers: 2-year results. Lancet. 2003;362(9384):593-597.
PubMedArticle
41.
Demura  Y, Tsuchida  T, Ishizaki  T,  et al.  18F-FDG accumulation with PET for differentiation between benign and malignant lesions in the thorax. J Nucl Med. 2003;44(4):540-548.
PubMed
42.
Buck  AK, Hetzel  M, Schirrmeister  H,  et al.  Clinical relevance of imaging proliferative activity in lung nodules. Eur J Nucl Med Mol Imaging. 2005;32(5):525-533.
PubMedArticle
43.
Kahn  D, Menda  Y, Kernstine  K,  et al.  The utility of 99mTc depreotide compared with F-18 fluorodeoxyglucose positron emission tomography and surgical staging in patients with suspected non-small cell lung cancer. Chest. 2004;125(2):494-501.
PubMedArticle
44.
Sachs  S, Bilfinger  TV.  The impact of positron emission tomography on clinical decision making in a university-based multidisciplinary lung cancer practice. Chest. 2005;128(2):698-703.
PubMedArticle
45.
Nomori  H, Watanabe  K, Ohtsuka  T, Naruke  T, Suemasu  K, Uno  K.  Visual and semiquantitative analyses for F-18 fluorodeoxyglucose PET scanning in pulmonary nodules 1 cm to 3 cm in size. Ann Thorac Surg. 2005;79(3):984-989.
PubMedArticle
46.
Ding  QY, Hua  YQ, Zhang  GZ,  et al.  A controlled study of positron-emission-tomography and positron-emission-tomography/computed tomography in differential diagnosis of solitary pulmonary nodules—report of 60 cases. Chin Med J (Engl). 2005;118(18):1572-1576.
PubMed
47.
Chhajed  PN, Bernasconi  M, Gambazzi  F,  et al.  Combining bronchoscopy and positron emission tomography for the diagnosis of the small pulmonary nodule < or = 3 cm. Chest. 2005;128(5):3558-3564.
PubMedArticle
48.
Bastarrika  G, García-Velloso  MJ, Lozano  MD,  et al.  Early lung cancer detection using spiral computed tomography and positron emission tomography. Am J Respir Crit Care Med. 2005;171(12):1378-1383.
PubMedArticle
49.
Herder  GJ, van Tinteren  H, Golding  RP,  et al.  Clinical prediction model to characterize pulmonary nodules: validation and added value of 18F-fluorodeoxyglucose positron emission tomography. Chest. 2005;128(4):2490-2496.
PubMedArticle
50.
Christensen  JA, Nathan  MA, Mullan  BP, Hartman  TE, Swensen  SJ, Lowe  VJ.  Characterization of the solitary pulmonary nodule: 18F-FDG PET versus nodule-enhancement CT. AJR Am J Roentgenol. 2006;187(5):1361-1367.
PubMedArticle
51.
Yi  CA, Lee  KS, Kim  B-T,  et al.  Tissue characterization of solitary pulmonary nodule: comparative study between helical dynamic CT and integrated PET/CT. J Nucl Med. 2006;47(3):443-450.
PubMed
52.
Kim  SK, Allen-Auerbach  M, Goldin  J,  et al.  Accuracy of PET/CT in characterization of solitary pulmonary lesions. J Nucl Med. 2007;48(2):214-220.
PubMed
53.
Orlacchio  A, Schillaci  O, Antonelli  L,  et al.  Solitary pulmonary nodules: morphological and metabolic characterisation by FDG-PET-MDCT. Radiol Med. 2007;112(2):157-173.
PubMedArticle
54.
Tsunezuka  Y, Shimizu  Y, Tanaka  N, Takayanagi  T, Kawano  M.  Positron emission tomography in relation to Noguchi’s classification for diagnosis of peripheral non-small-cell lung cancer 2 cm or less in size. World J Surg. 2007;31(2):314-317.
PubMedArticle
55.
Wang  F, Wang  Z, Yao  W, Xie  H, Xu  J, Tian  L.  Role of 99mTc-octreotide acetate scintigraphy in suspected lung cancer compared with 18F-FDG dual-head coincidence imaging. J Nucl Med. 2007;48(9):1442-1448.
PubMedArticle
56.
Veronesi  G, Bellomi  M, Veronesi  U,  et al.  Role of positron emission tomography scanning in the management of lung nodules detected at baseline computed tomography screening. Ann Thorac Surg. 2007;84(3):959-966.
PubMedArticle
57.
Núñez  R, Kalapparambath  A, Varela  J.  Improvement in sensitivity with delayed imaging of pulmonary lesions with FDG-PET. Rev Esp Med Nucl. 2007;26(4):196-207.
PubMedArticle
58.
Ohno  Y, Koyama  H, Takenaka  D,  et al.  Dynamic MRI, dynamic multidetector-row computed tomography (MDCT), and coregistered 2-[fluorine-18]-fluoro-2-deoxy-D-glucose-positron emission tomography (FDG-PET)/CT: comparative study of capability for management of pulmonary nodules. J Magn Reson Imaging. 2008;27(6):1284-1295.
PubMedArticle
59.
Yamamoto  Y, Nishiyama  Y, Ishikawa  S,  et al.  3′-Deoxy-3′-18F-fluorothymidine as a proliferation imaging tracer for diagnosis of lung tumors: comparison with 2-deoxy-2-18f-fluoro-D-glucose. J Comput Assist Tomogr. 2008;32(3):432-437.
PubMedArticle
60.
Jeong  SY, Lee  KS, Shin  KM,  et al.  Efficacy of PET/CT in the characterization of solid or partly solid solitary pulmonary nodules. Lung Cancer. 2008;61(2):186-194.
PubMedArticle
61.
Pauls  S, Buck  AK, Halter  G,  et al.  Performance of integrated FDG-PET/CT for differentiating benign and malignant lung lesions—results from a large prospective clinical trial. Mol Imaging Biol. 2008;10(2):121-128.
PubMedArticle
62.
Alkhawaldeh  K, Bural  G, Kumar  R, Alavi  A.  Impact of dual-time-point (18)F-FDG PET imaging and partial volume correction in the assessment of solitary pulmonary nodules. Eur J Nucl Med Mol Imaging. 2008;35(2):246-252.
PubMedArticle
63.
Baram  D, Bilfinger  TV.  Interaction of clinical suspicion and PET in the diagnosis of suspected thoracic malignancy. Med Sci Monit. 2008;14(7):CR379-CR383.
PubMed
64.
Degirmenci  B, Wilson  D, Laymon  CM,  et al.  Standardized uptake value-based evaluations of solitary pulmonary nodules using F-18 fluorodeoxyglucose-PET/computed tomography. Nucl Med Commun. 2008;29(7):614-622.
PubMedArticle
65.
Lan  XL, Zhang  YX, Wu  ZJ, Jia  Q, Wei  H, Gao  ZR.  The value of dual time point (18)F-FDG PET imaging for the differentiation between malignant and benign lesions. Clin Radiol. 2008;63(7):756-764.
PubMedArticle
66.
Aukema  TS, Valdés Olmos  RA, Klomp  HM,  et al.  Evaluation of (18)F-FDG PET-CT for differentiation of pulmonary pathology in an approach of outpatient fast track assessment. J Thorac Oncol. 2009;4(10):1226-1230.
PubMedArticle
67.
Ohba  Y, Nomori  H, Shibata  H,  et al.  Evaluation of semiquantitative assessments of fluorodeoxyglucose uptake on positron emission tomography scans for the diagnosis of pulmonary malignancies 1 to 3 cm in size. Ann Thorac Surg. 2009;87(3):886-891.
PubMedArticle
68.
Schillaci  O, Travascio  L, Bolacchi  F,  et al.  Accuracy of early and delayed FDG PET-CT and of contrast-enhanced CT in the evaluation of lung nodules: a preliminary study on 30 patients. Radiol Med. 2009;114(6):890-906.
PubMedArticle
69.
Kagna  O, Solomonov  A, Keidar  Z,  et al.  The value of FDG-PET/CT in assessing single pulmonary nodules in patients at high risk of lung cancer. Eur J Nucl Med Mol Imaging. 2009;36(6):997-1004.
PubMedArticle
70.
Chang  C-Y, Tzao  C, Lee  S-C,  et al.  Incremental value of integrated FDG-PET/CT in evaluating indeterminate solitary pulmonary nodule for malignancy. Mol Imaging Biol. 2010;12(2):204-209.
PubMedArticle
71.
Grgic  A, Yüksel  Y, Gröschel  A,  et al.  Risk stratification of solitary pulmonary nodules by means of PET using (18)F-fluorodeoxyglucose and SUV quantification. Eur J Nucl Med Mol Imaging. 2010;37(6):1087-1094.
PubMedArticle
72.
Barnett  PG, Ananth  L, Gould  MK; Veterans Affairs Positron Emission Tomography Imaging in the Management of Patients with Solitary Pulmonary Nodules (VA SNAP) Cooperative Study Group.  Cost and outcomes of patients with solitary pulmonary nodules managed with PET scans. Chest. 2010;137(1):53-59.
PubMedArticle
73.
Huang  Y-E, Pu  Y-L, Huang  Y-J,  et al.  The utility of the nonattenuation corrected 18F-FDG PET images in the characterization of solitary pulmonary lesions. Nucl Med Commun. 2010;31(11):945-951.
PubMedArticle
74.
Ohno  Y, Koyama  H, Matsumoto  K,  et al.  Differentiation of malignant and benign pulmonary nodules with quantitative first-pass 320-detector row perfusion CT versus FDG PET/CT. Radiology. 2011;258(2):599-609.
PubMedArticle
75.
Macdonald  K, Searle  J, Lyburn  I.  The role of dual time point FDG PET imaging in the evaluation of solitary pulmonary nodules with an initial standard uptake value less than 2.5. Clin Radiol. 2011;66(3):244-250.
PubMedArticle
76.
Okereke  IC, Gangadharan  SP, Kent  MS, Nicotera  SP, DeCamp  MM.  [(18)F]Fluorodeoxyglucose positron emission tomography-computerized tomography and lung cancer: a significant referral bias exists. Eur J Cardiothorac Surg. 2011;39(4):560-564.
PubMedArticle
77.
Kubota  K, Murakami  K, Inoue  T, Saga  T, Shiomi  S.  Additional effects of FDG-PET to thin-section CT for the differential diagnosis of lung nodules: a Japanese multicenter clinical study. Ann Nucl Med. 2011;25(10):787-795.
PubMedArticle
78.
Nguyen  NC, Kaushik  A, Wolverson  MK, Osman  MM.  Is there a common SUV threshold in oncological FDG PET/CT, at least for some common indications? a retrospective study. Acta Oncol. 2011;50(5):670-677.
PubMedArticle
79.
Xu  B, Guan  Z, Liu  C,  et al.  Can multimodality imaging using 18F-FDG/18F-FLT PET/CT benefit the diagnosis and management of patients with pulmonary lesions? Eur J Nucl Med Mol Imaging. 2011;38(2):285-292.
PubMedArticle
80.
García Vicente  AM, Castrejón  AS, León Martín  AA, García  BG, Pilkington Woll  JP, Muñoz  AP.  Value of 4-dimensional 18F-FDG PET/CT in the classification of pulmonary lesions. J Nucl Med Technol. 2011;39(2):91-99.
PubMedArticle
81.
Ashraf  H, Dirksen  A, Loft  A,  et al.  Combined use of positron emission tomography and volume doubling time in lung cancer screening with low-dose CT scanning. Thorax. 2011;66(4):315-319.
PubMedArticle
82.
van’t Westeinde  SC, de Koning  HJ, Thunnissen  FB,  et al.  The role of the ¹⁸f-fluorodeoxyglucose-positron emission tomography scan in the Nederlands Leuvens Longkanker screenings Onderzoek lung cancer screening trial. J Thorac Oncol. 2011;6(10):1704-1712.
PubMedArticle
83.
Harders  SW, Madsen  HH, Hjorthaug  K,  et al.  Characterization of pulmonary lesions in patients with suspected lung cancer: computed tomography versus [¹⁸F] fluorodeoxyglucose-positron emission tomography/computed tomography. Cancer Imaging. 2012;12(3):437-446.
PubMedArticle
84.
Fiorelli  A, Rizzo  A, Messina  G,  et al.  Correlation between matrix metalloproteinase 9 and 18F-2-fluoro-2-deoxyglucose-positron emission tomography as diagnostic markers of lung cancer. Eur J Cardiothorac Surg. 2012;41(4):852-860.
PubMedArticle
85.
Dalli  A, Selimoglu Sen  H, Coskunsel  M,  et al.  Diagnostic value of PET/CT in differentiating benign from malignant solitary pulmonary nodules. J BUON. 2013;18(4):935-941.
PubMed
86.
Lopes Pegna  A, Picozzi  G, Falaschi  F,  et al; ITALUNG Study Research Group.  Four-year results of low-dose CT screening and nodule management in the ITALUNG trial. J Thorac Oncol. 2013;8(7):866-875.
PubMedArticle
87.
Ohno  Y, Nishio  M, Koyama  H,  et al.  Comparison of quantitatively analyzed dynamic area-detector CT using various mathematic methods with FDG PET/CT in management of solitary pulmonary nodules. AJR Am J Roentgenol. 2013;200(6):W593-W602.
PubMedArticle
88.
Minamimoto  R, Senda  M, Jinnouchi  S,  et al.  Detection of lung cancer by FDG-PET cancer screening program: a nationwide Japanese survey. Anticancer Res. 2014;34(1):183-189.
PubMed
89.
Zhang  J, Cui  L-B, Tang  X,  et al.  DW MRI at 3.0 T versus FDG PET/CT for detection of malignant pulmonary tumors. Int J Cancer. 2014;134(3):606-611.
PubMedArticle
90.
Menda  Y, Kahn  D.  Somatostatin receptor imaging of non-small cell lung cancer with 99mTc depreotide. Semin Nucl Med. 2002;32(2):92-96.
PubMedArticle
91.
Acker  MR, Burrell  SC.  Utility of 18F-FDG PET in evaluating cancers of lung. J Nucl Med Technol. 2005;33(2):69-74.
PubMed
92.
Delbeke  D, Coleman  RE, Guiberteau  MJ,  et al.  Procedure guideline for tumor imaging with 18F-FDG PET/CT 1.0. J Nucl Med. 2006;47(5):885-895.
PubMed
93.
Beyer  T, Antoch  G, Müller  S,  et al.  Acquisition protocol considerations for combined PET/CT imaging. J Nucl Med. 2004;45(1)(suppl 1):25S-35S.
PubMed
94.
Beyer  T, Townsend  DW, Brun  T,  et al.  A combined PET/CT scanner for clinical oncology. J Nucl Med. 2000;41(8):1369-1379.
PubMed
95.
Yang  W, Zhang  Y, Fu  Z, Sun  X, Mu  D, Yu  J.  Imaging proliferation of ¹⁸F-FLT PET/CT correlated with the expression of microvessel density of tumour tissue in non-small-cell lung cancer. Eur J Nucl Med Mol Imaging. 2012;39(8):1289-1296.
PubMedArticle
96.
Dittmann  H, Dohmen  BM, Paulsen  F,  et al.  [18F]FLT PET for diagnosis and staging of thoracic tumours. Eur J Nucl Med Mol Imaging. 2003;30(10):1407-1412.
PubMedArticle
97.
Baylin  SB, Jackson  RD, Goodwin  G, Gazdar  AF.  Neuroendocrine-related biochemistry in the spectrum of human lung cancers. Exp Lung Res. 1982;3(3-4):209-223.
PubMedArticle
98.
Zhuang  H, Pourdehnad  M, Lambright  ES,  et al.  Dual time point 18F-FDG PET imaging for differentiating malignant from inflammatory processes. J Nucl Med. 2001;42(9):1412-1417.
PubMed
99.
Gould  MK, Fletcher  J, Iannettoni  MD,  et al; American College of Chest Physicians.  Evaluation of patients with pulmonary nodules: when is it lung cancer?: ACCP evidence-based clinical practice guidelines (2nd edition). Chest. 2007;132(3)(suppl):108S-130S.
PubMedArticle
100.
Aberle  DR, Adams  AM, Berg  CD,  et al; National Lung Screening Trial Research Team.  Reduced lung-cancer mortality with low-dose computed tomographic screening. N Engl J Med. 2011;365(5):395-409.
PubMedArticle
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