Skip to main content

Main menu

  • Home
  • Content
    • Current
      • JNMT Supplement
    • Ahead of print
    • Past Issues
    • Continuing Education
    • JNMT Podcast
    • SNMMI Annual Meeting Abstracts
  • Subscriptions
    • Subscribers
    • Rates
    • Journal Claims
    • Institutional and Non-member
  • Authors
    • Submit to JNMT
    • Information for Authors
    • Assignment of Copyright
    • AQARA Requirements
  • Info
    • Reviewers
    • Permissions
    • Advertisers
    • Corporate & Special Sales
  • About
    • About Us
    • Editorial Board
    • Contact Information
  • More
    • Alerts
    • Feedback
    • Help
    • SNMMI Journals
  • SNMMI
    • JNMT
    • JNM
    • SNMMI Journals
    • SNMMI

User menu

  • Subscribe
  • My alerts
  • Log in
  • My Cart

Search

  • Advanced search
Journal of Nuclear Medicine Technology
  • SNMMI
    • JNMT
    • JNM
    • SNMMI Journals
    • SNMMI
  • Subscribe
  • My alerts
  • Log in
  • My Cart
Journal of Nuclear Medicine Technology

Advanced Search

  • Home
  • Content
    • Current
    • Ahead of print
    • Past Issues
    • Continuing Education
    • JNMT Podcast
    • SNMMI Annual Meeting Abstracts
  • Subscriptions
    • Subscribers
    • Rates
    • Journal Claims
    • Institutional and Non-member
  • Authors
    • Submit to JNMT
    • Information for Authors
    • Assignment of Copyright
    • AQARA Requirements
  • Info
    • Reviewers
    • Permissions
    • Advertisers
    • Corporate & Special Sales
  • About
    • About Us
    • Editorial Board
    • Contact Information
  • More
    • Alerts
    • Feedback
    • Help
    • SNMMI Journals
  • Watch or Listen to JNMT Podcast
  • Visit SNMMI on Facebook
  • Join SNMMI on LinkedIn
  • Follow SNMMI on Twitter
  • Subscribe to JNMT RSS feeds
Research ArticleIMAGING

Value of 4-Dimensional 18F-FDG PET/CT in the Classification of Pulmonary Lesions

Ana María García Vicente, Angel Soriano Castrejón, Antonio Alberto León Martín, Beatriz González García, John Patrick Pilkington Woll and Azahara Palomar Muñoz
Journal of Nuclear Medicine Technology June 2011, 39 (2) 91-99; DOI: https://doi.org/10.2967/jnmt.110.082719
Ana María García Vicente
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Angel Soriano Castrejón
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Antonio Alberto León Martín
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Beatriz González García
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
John Patrick Pilkington Woll
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Azahara Palomar Muñoz
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • Article
  • Figures & Data
  • Info & Metrics
  • PDF
Loading

Article Figures & Data

Figures

  • Tables
  • FIGURE 1.
    • Download figure
    • Open in new tab
    • Download powerpoint
    FIGURE 1.

    ROC curves of 3D and 4D (best bin and average gated) statistical parameters. Area under curve was 0.5185 for 3D, 0.5938 for 4D best bin, and 0.5093 for 4D average gated. 4D best bin showed best value, with no statistically significant differences from the other techniques. a.g. = average gated; b.b. = best bin.

  • FIGURE 2.
    • Download figure
    • Open in new tab
    • Download powerpoint
    FIGURE 2.

    Example of lesion that cannot be visualized on 3D axial image but is detectable on 4D best-bin axial image. Study is of patient 11, who had small cell lung cancer with 2 pulmonary lesions. CT image (center) shows one lesion in right lower lobe (maximum diameter, 4 cm) and another in right upper lobe (8 mm). Larger lesion has high avidity for 18F-FDG (SUVmax in 3D and in best bin of 4D, 8.4 and 11.1, respectively), whereas smaller lesion (arrow) is detectable only in 4D study (SUVmax, 1.1).

  • FIGURE 3.
    • Download figure
    • Open in new tab
    • Download powerpoint
    FIGURE 3.

    Example of higher lesion contrast with respect to background lung activity in 4D study than in 3D study in patient with 2 pulmonary lesions smaller than 1 cm. Study is of patient 26, who had history of treated non–small cell lung cancer. CT images (center) show one lesion in right upper lobe (maximum diameter, 8 mm) and another in left lower lobe (8 mm). Both (arrows) show faint uptake on 3D axial images (SUVmax, 0.8 and 1.4, respectively) that improves in best-bin 4D images (SUVmax, 1.9 and 2.9, respectively).

  • FIGURE 4.
    • Download figure
    • Open in new tab
    • Download powerpoint
    FIGURE 4.

    Correlation between lesion size and SUVmax percentage difference between 3D and best-bin 4D studies (A) and between 3D and average gated 4D studies (B). Both graphs show statistically significant (P < 0.05) higher increase in SUVmax in smaller lesions than in larger ones.

Tables

  • Figures
    • View popup
    TABLE 1

    Patient Data, Lesion Data, Final Diagnosis, and Imaging Results

    ClassificationImaging result
    Les no.Pt no.SexAge (y)NBLCHy NBDiam (cm)LocationSUVmax 3D (A)SUVmax BB 4D (B)Bin% Dif (B − A)SUVmax AG 4D (C)% Dif (C − A)3DBB 4DAG 4DHy3DBB 4DAG 4D
    11M73——1.0LUL2.43.1229.22.712.5BMMTNFPFP
    211.3LUL1.41.6114.31.57.1BBBTNTNTN
    32F71Y—Testicular2.1LUL17.421.5214.920.517.8MMMMts melanomaTPTPTP
    43F54——2.8LUL1.93.3673.72.742.1BMMHamartomaTNFPFP
    54M68Y—Prostate2.0RLL6.89.7642.69.235.2MMMNSCLCTPTPTP
    65M78Y—Melanoma2.5LUL1.72.7558.81.911.7BMBFNTPFN
    76F54——1.3LUL2.22.324.52.20BBBTNTNTN
    87M60——1.0LLL1.82.2322.21.80BBBEpidermalFNFNFN
    98M70Y—Larynx3.5LUL4.15.2326.84.817.0MMMTPTPTP
    1082.0RUL3.02.92−3.32.7−10.0MMMTPTPTP
    1181.7Lingula1.72.3235.31.70BBBFNFNFN
    129M80——1.6RUL1.21.4116.61.416.7BBBTNTNTN
    1390.8Lingula1.21.7141.61.416.7BBBTNTNTN
    1410M80YYNSCLC3.2LUL22.530.3434.720.8−7.6MMMAdenocaTPTPTP
    15102.0LUL2.43.1229.22.816.7BMMAdenocaFNTPTP
    1611M51YYSCLC4.0RLL8.411.1232.110.727.4MMMSCLCTPTPTP
    17110.9RUL—1.11—1.0—BBBSCLCFNFNFN
    1812M52YYNSCLC2.1RUL2.42.618.32.40BMBAdenocaFNTPFN
    1913M71Y—Colorectal0.7ML0.81.5287.51.587.5BBBTNTNTN
    20130.7RLL1.72.2329.41.85.9BBBTNTNTN
    2114M73Y—HD1.8RUL1.21.318.31.20BBBTNTNTN
    2215F73Y—Colorectal2.4RLL10.112.7525.711.816.8MMMTPTPTP
    2316M84YYEpidermoid1.6RLL3.24.8350.04.231.2MMMEpidermoidTPTPTP
    2417F50Y—Ovarian0.6RUL1.32.0153.81.730.8BBBTNTNTN
    2518M58Y—Renal0.8RUL0.52.32360.02.3360.0BBBNegativeTNTNTN
    26181.0RUL1.23.21166.73.0150.0BMMNegativeTNFPFP
    27182.0RUL1.82.6453.82.433.3BMBNegativeTNFPTN
    28180.8ML0.40.4————BBBNegativeTNTNTN
    2919M73Y—Colorectal2.0LUL3.05.3676.74.963.3MMMTPTPTP
    30190.9LUL1.22.0166.71.525.0BBBFNFNFN
    31190.7RUL0.81.3162.51.137.5BBBFNFNFN
    3220M65——0.5RUL0.41.16175.01.0150.0BBBTNTNTN
    3321F61Y—Melanoma1.3Lingula0.51.53200.01.4180.0BBBTNTNTN
    3422M70Y—Colorectal0.9LLL2.83.4221.43.110.7MMMTPTPTP
    3523M70Y—Colorectal0.6LLL1.11.9472.71.318.2BBBFNFNFN
    36231.2RLL0.92.54177.71.788.9BMBFNTPFN
    3724M57Y—Epidermoid1.6RLL3.15.4174.24.854.8MMMTPTPTP
    38241.2Lingula2.02.7335.02.420.0BMBFNTPFN
    3925F61Y—Endometrial0.7RUL0.92.82211.12.1133.3BMBFNTPFN
    40250.9RUL1.02.91190.02.7170.0BMMFNTPTP
    41251.2RLL2.44.7195.83.650.0BMMFNTPTP
    4226F67YYNSCLC0.8RUL0.81.93137.51.6100.0BBBTNTNTN
    43260.8LLL1.42.95107.12.578.6BMMTNFPFP
    4427M69Y—Colorectal1.2LLL0.81.1137.50.912.5BBBFNFNFN
    45271.0RLL1.51.7113.31.50BBBFNFNFN
    4628M41Y—Testicular1.5RLL1.42.4571.42.150.0BBBNegativeTNTNTN
    4729F68Y—Colorectal0.8RUL1.12.52127.32.190.9BMBFNTPFN
    48291.0RLL1.23.42183.32.391.7BMBFNTPFN
    49290.7RLL1.23.22166.62.5108.3BMMFNTPTP
    5030F79Y—Renal2.4LLL1.81.8201.3−27.8BBBMtsFNFNFN
    5131M58——2.2RLL10.914.8135.813.120.2MMMEpidermoidTPTPTP
    5232F57Y—Cervix1.2RLL1.72.3235.32.123.5BBBFNFNFN
    5333M81Y—Colorectal1.0LUL1.34.24223.13.8192.3BMMFNTPTP
    5434M65Y—Renal1.6LUL1.21.4616.71.20BBBFNFNFN
    5535M61Y—SCLC2.2RLL4.710.24117.08.887.2MMMSCLCTPTPTP
    5636M62Y—Larynx4.7RUL18.621.6316.120.49.7MMMPositiveTPTPTP
    5737M80——2.4RUL2.75.2392.64.877.8MMMFPFPFP
    • Les = lesion; Pt = patient; NB = neoplastic background; LC = lung cancer; Hy = histopathology; Diam = diameter; BB = best bin; Dif = difference; AG = average gated; NSCLC = non–small cell lung cancer; SCLC = small cell lung cancer; HD = Hodgkin disease; RUL: right upper lobe; LUL = left upper lobe; RLL = right lower lobe; LLL = left lower lobe; ML = middle lobe; B = benign; M = malignant; Mts = metastases; adenoca = adenocarcinoma; TN = true negative; FP = false positive; TP = true positive; FN = false negative.

    • View popup
    TABLE 2

    Statistical Parameters for the 3 Techniques

    3DBest-bin 4D
    Index (%)Total>1 cm≥1.5 cmAG 4D totalTotal>1 cm≥1.5 cm
    Sensitivity37.852.268.451.370.379.284.2
    Specificity959083.3757066.750
    Positive predictive value9392.392.979.281.290.584.2
    Negative predictive value454545.445.45654.550
    Accuracy57.963.67259.670.275.776
    • AG = average gated.

    • View popup
    TABLE 3

    SUVmax Data with Reference to Lesion Location

    Mean SUVmax ± SDSUVmax percentage difference ± SD
    Lesion locationLesion distribution3DBB 4DAG 4D3D vs. BB 4D3D vs. AG 4D
    RUL172.29 ± 4.283.45 ± 4.783.17 ± 4.5398.60 ± 99.1984.37 ± 95.08
    LUL134.82 ± 6.846.61 ± 8.835.48 ± 6.8351.48 ± 56.9230.62 ± 52.03
    RLL153.63 ± 3.335.71 ± 4.324.96 ± 4.0279.86 ± 59.2547.42 ± 34.72
    LLL62.59 ± 2.643.49 ± 3.443.08 ± 3.4441.86 ± 36.2317.08 ± 32.28
    Lingula41.35 ± 0.652.05 ± 0.551.72 ± 0.4777.97 ± 81.4054.17 ± 84.34
    ML20.60 ± 0.280.95 ± 0.780.75 ± 1.0643.75 ± 61.87−6.25 ± 132.58
    • RUL = right upper lobe; LUL = left upper lobe; RLL = right lower lobe; LLL = left lower lobe; ML = middle lobe; BB = best bin; AG = average gated.

PreviousNext
Back to top

In this issue

Journal of Nuclear Medicine Technology: 39 (2)
Journal of Nuclear Medicine Technology
Vol. 39, Issue 2
June 1, 2011
  • Table of Contents
  • About the Cover
  • Index by author
Print
Download PDF
Article Alerts
Sign In to Email Alerts with your Email Address
Email Article

Thank you for your interest in spreading the word on Journal of Nuclear Medicine Technology.

NOTE: We only request your email address so that the person you are recommending the page to knows that you wanted them to see it, and that it is not junk mail. We do not capture any email address.

Enter multiple addresses on separate lines or separate them with commas.
Value of 4-Dimensional 18F-FDG PET/CT in the Classification of Pulmonary Lesions
(Your Name) has sent you a message from Journal of Nuclear Medicine Technology
(Your Name) thought you would like to see the Journal of Nuclear Medicine Technology web site.
Citation Tools
Value of 4-Dimensional 18F-FDG PET/CT in the Classification of Pulmonary Lesions
Ana María García Vicente, Angel Soriano Castrejón, Antonio Alberto León Martín, Beatriz González García, John Patrick Pilkington Woll, Azahara Palomar Muñoz
Journal of Nuclear Medicine Technology Jun 2011, 39 (2) 91-99; DOI: 10.2967/jnmt.110.082719

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Share
Value of 4-Dimensional 18F-FDG PET/CT in the Classification of Pulmonary Lesions
Ana María García Vicente, Angel Soriano Castrejón, Antonio Alberto León Martín, Beatriz González García, John Patrick Pilkington Woll, Azahara Palomar Muñoz
Journal of Nuclear Medicine Technology Jun 2011, 39 (2) 91-99; DOI: 10.2967/jnmt.110.082719
Twitter logo Facebook logo LinkedIn logo Mendeley logo
  • Tweet Widget
  • Facebook Like
  • Google Plus One
Bookmark this article

Jump to section

  • Article
    • Abstract
    • MATERIALS AND METHODS
    • RESULTS
    • DISCUSSION
    • CONCLUSION
    • REFERENCES
  • Figures & Data
  • Info & Metrics
  • PDF

Related Articles

  • No related articles found.
  • PubMed
  • Google Scholar

Cited By...

  • Quantitative Volumetric CT-Histogram Analysis in N-Staging of 18F-FDG-Equivocal Patients with Lung Cancer
  • Google Scholar

More in this TOC Section

  • Early 10-Minute Postinjection [18F]F-FAPI-42 uEXPLORER Total-Body PET/CT Scanning Protocol for Staging Lung Cancer Using HYPER Iterative Reconstruction
  • Single- Versus Dual-Time-Point Imaging for Transthyretin Cardiac Amyloid Using 99mTc-Pyrophosphate
  • Software Discrepancies in Radionuclide-Derived Left Ventricular Ejection Fraction
Show more Imaging

Similar Articles

SNMMI

© 2025 SNMMI

Powered by HighWire