Skip to main content

Main menu

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

User menu

  • Subscribe
  • My alerts
  • Log in
  • My Cart

Search

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

Advanced Search

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

Quantitative 68Ga-DOTATATE PET/CT Parameters for the Prediction of Therapy Response in Patients with Progressive Metastatic Neuroendocrine Tumors Treated with 177Lu-DOTATATE

Claudia Ortega, Rebecca K.S. Wong, Josh Schaefferkoetter, Patrick Veit-Haibach, Sten Myrehaug, Rosalyn Juergens, David Laidley, Reut Anconina, Amy Liu and Ur Metser
Journal of Nuclear Medicine October 2021, 62 (10) 1406-1414; DOI: https://doi.org/10.2967/jnumed.120.256727
Claudia Ortega
1Joint Department of Medical Imaging, University Health Network, Mount Sinai Hospital and Women’s College Hospital, University of Toronto, Toronto, Ontario, Canada;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Rebecca K.S. Wong
2Department of Radiation Oncology, Princess Margaret Cancer Centre, University Health Network and University of Toronto, Toronto, Ontario, Canada;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Josh Schaefferkoetter
3Siemens Medical Solutions USA, Inc., Knoxville, Tennessee;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Patrick Veit-Haibach
1Joint Department of Medical Imaging, University Health Network, Mount Sinai Hospital and Women’s College Hospital, University of Toronto, Toronto, Ontario, Canada;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Sten Myrehaug
4Division of Radiation Oncology, Odette Cancer Centre, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Rosalyn Juergens
5Department of Oncology, Juravinski Cancer Centre, McMaster University, Hamilton, Ontario, Canada;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
David Laidley
6Division of Nuclear Medicine, St. Joseph’s Health Care London, University of Western Ontario, London, Ontario, Canada; and
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Reut Anconina
1Joint Department of Medical Imaging, University Health Network, Mount Sinai Hospital and Women’s College Hospital, University of Toronto, Toronto, Ontario, Canada;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Amy Liu
7Department of Biostatistics, Princess Margaret Cancer Centre, Toronto, Ontario, Canada
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Ur Metser
1Joint Department of Medical Imaging, University Health Network, Mount Sinai Hospital and Women’s College Hospital, University of Toronto, Toronto, Ontario, Canada;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • Article
  • Figures & Data
  • Supplemental
  • Info & Metrics
  • PDF
Loading

Article Figures & Data

Figures

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

    60-y-old woman with metastases of well-differentiated small bowel NET to liver and retroperitoneal lymph nodes (G1; Ki-67 index, 6%). Lesion-based assessment was done with bPET and iPET before cycle 2 of 177Lu-DOTATATE therapy. (A) Metastatic nodal mass chosen as marker lesion at bPET (SUVmax, 38.7) (outlined in red). (B) Same lesion before cycle 2 of therapy (SUVmax, 49.2) (outlined in red).

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

    68Ga-DOTATATE tumor volume analysis using in-house automated segmentation software. (A) Multiplanar segmentation tool (to identify and confirm tumor sites). (B) Mask generated using tracer uptake in spleen as threshold (tumor lesions with SUVmax above that of spleen are outlined in green).

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

    Lesion-based measures. Distributions of median SUVmax (P = 0.018) (A) and SUVmax T/L (P = 0.024) (B) are shown. Box plots represent median and upper and lower quartiles of each distribution, with whiskers showing limits of distribution (1.5 times interquartile range). NR = nonresponders; R = responders.

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

    DTTV parameters. Distributions of mean DTTV SUVmax (P = 0.025) (A) and SUVmean obtained with liver as threshold (SUVmean Liver) (P = 0.0055) (B) are shown. Box plots represent median and upper and lower quartiles of each distribution, with whiskers showing limits of distribution (1.5 times interquartile range). NR = nonresponders; R = responders.

  • FIGURE 5.
    • Download figure
    • Open in new tab
    • Download powerpoint
    FIGURE 5.

    Kurtosis on baseline 68Ga-DOTATATE PET/CT. Distribution of kurtosis was estimated from 68Ga-DOTATATE tumor volumes (P = 0.031). Box plot represents median and upper and lower quartiles of each distribution, with whiskers showing limits of distribution (1.5 times interquartile range). NR = nonresponders; R = responders.

Tables

  • Figures
  • Additional Files
    • View popup
    TABLE 1

    Patient Characteristics for Entire Cohort and Subgroup with iPET

    CharacteristicEntire cohortiPET cohort
    No. of patients9136
    Sex (M:F)53:3820:16
    Mean age (y)62.5 (SD = 12.9)59.7 (SD = 14.2)
    Primary site (No. of patients)
      Gastrointestinal tract4819
      Pancreas198
      Unknown primary92
      Bronchopulmonary63
      Adrenal42
      Other52
    Mean tumor Ki-67 index (%)8.3 (SD = 7.8)10.5 (SD = 8.3)
    Response status
      Nonresponders206
      Other7130
    Mean follow-up (mo)12.2 (SD = 7.2)20.1 (SD = 9.7)
    • View popup
    TABLE 2

    bPET Reference Parameters, Lesion-Based Parameters, DTTV Parameters, and First-Order Heterogeneity Parameters

    bPET ParameterAll Patients (n = 91)Responders (n = 71)Nonresponders (n = 20)P*
    Reference tissue
     SUVmax liver0.49
      Mean (SD)5.7 (2.1)5.8 (2.3)5.3 (1.6)
      Minimum–maximum2–13.13.2–8.22–13.1
     SUVmax spleen0.30
      Mean (SD)13.8 (6.9)14.1 (6.9)12.6 (6.7)
      Minimum–maximum4.4–45.84.4–26.75–45.8
    Lesion based
     Mean SUVmax0.018
      Mean (SD)38.7 (25.1)41.7 (26.8)28.2 (14.2)
      Minimum–maximum11–137.713.4–77.411–137.7
     Mean SUVmax T/L0.024
      Mean (SD)8.3 (6.4)9 (7)5.8 (2.9)
      Minimum–maximum1.4–40.51.4–40.52.9–14.6
     Mean SUVmax T/S0.13
      Mean (SD)3.5 (2.7)3.7 (2.9)2.8 (1.8)
      Minimum–maximum0.2–14.60.2–14.61–8.3
    DTTV
     DTTV liver†0.12
      Mean (SD)554.1 (853.8)611.5 (921.7)350.4 (516.8)
      Minimum–maximum4.7–4,891.84.7–4,891.88.1–2,200.9
    DTTV spleen†0.06
      Mean (SD)317.1 (616.3)363.9 (677.6)150.9 (265.4)
      Minimum–maximum0–3,825.30–3,825.30–1,049.6
     DTTV SUVmax0.025
      Mean (SD)62.8 (46.4)66.8 (48.4)48.4 (36.2)
      Minimum–maximum15.6–307)17.1–30715.6–186.6
     DTTV SUVmean liver0.0055
      Mean (SD)15.6 (7.3)16.7 (7.7)11.6 (3.6)
      Minimum–maximum5.1–41.45.8–41.45.1–19.4
     DTTV SUVmean spleen0.06
      Mean (SD)23.5 (10.3)24.5 (10.4)20 (9.3)
      Minimum–maximum0–50.40–50.47.7–45.3
    Heterogeneity
     CoV0.17
      Mean (SD)0.6 (0.2)0.6 (0.2)0.6 (0.3)
      Minimum–maximum0.2–1.60.3–1.50.2–1.6
     Skewness0.055
      Mean (SD)1.5 (0.8)1.4 (0.8)1.9 (1.0)
      Minimum–maximum0.1–40.1–40.6–4
     Kurtosis0.031
      Mean (SD)6.4 (4.8)5.8 (4.1)8.6 (6.4)
      Minimum–maximum1.7–26.71.7–25.82.8–26.7
    • * P value.

    • ↵† Measured in cubic centimeters.

    • DTTV SUVmean liver = SUVmean in segmented volume obtained with liver as threshold; DTTV SUVmean spleen = SUVmean in segmented volume obtained with spleen as threshold; DTTV liver = DTTV obtained with liver as threshold; DTTV spleen = DTTV obtained with spleen as threshold; DTTV SUVmean liver = DTTV SUVmean obtained with liver as threshold; DTTV SUVmean spleen = DTTV SUVmean obtained with spleen as threshold; CoV = coefficient of variation.

    • Wilcoxon rank sum test P values are shown.

    • View popup
    TABLE 3

    iPET Reference Parameters, Lesion-Based Parameters, DTTV Parameters, and First-Order Heterogeneity Measures, Part 1

    iPETAll patients (n = 36)Responders (n = 30)Nonresponders (n = 6)P*
    Reference tissue
     SUVmax liver0.011
      Mean (SD)5.8 (1.8)6.1 (1.8)4.2 (1.2)
      Minimum–maximum2.8–11.23.6–11.22.8–6.4
     SUVmax spleen0.0085
      Mean (SD)19.4 (10.6)21.2 (10.7)10.6 (3.8)
      Minimum–maximum4.3–49.17.3–49.14.3–14.6
    Lesion based
     Mean SUVmax0.048
      Mean (SD)34.3 (19.4)37 (20.2)21.2 (6)
      Minimum–maximum6.8–93.16.8–93.112.4–29.9
     Mean SUVmax T/L0.57
      Mean (SD)6.1 (3.2)6.3 (3.5)5.2 (1.4)
      Minimum–maximum0.9–17.40.9–17.42.9–6.8
     Mean SUVmax T/S0.92
      Mean (SD)2.1 (1.2)2.1 (1.3)2.2 (0.9)
      Minimum–maximum0.1–6.10.1–6.11.5–3.9
    • * P value.

    • † Measured in cubic centimeters.

    • DTTV SUVmean liver = SUVmean in segmented volume obtained with liver as threshold; DTTV SUVmean spleen = SUVmean in segmented volume obtained with spleen as threshold; DTTV liver = DTTV obtained with liver as threshold; DTTV spleen = DTTV obtained with spleen as threshold; DTTV SUVmean liver = DTTV SUVmean obtained with liver as threshold; DTTV SUVmean spleen = DTTV SUVmean obtained with spleen as threshold; CoV = coefficient of variation.

    • Wilcoxon rank sum test P values are shown.

    • View popup
    TABLE 4

    Univariable (UVA) and Multivariable (MVA) Analyses of Lesion-Based, Tumor Volume–Based, and Heterogeneity Parameters as Predictors of PFS

    UVAMVA
    bPET covariateHR (95% CI)PHR (95% CI)P
    Lesion based
      Mean SUVmax0.98 (0.97–1)0.0230.98 (0.96–1)0.019
      SUVmax T/L0.92 (0.85–0.99)0.0280.89 (0.8–0.98)0.018
      SUVmax T/S0.86 (0.75–1)0.0470.83 (0.69–0.99)0.041
    Tumor volume
      DTTV SUVmean liver0.92 (0.87–0.98)0.00530.9 (0.83–0.97)0.0052
    Heterogeneity
      Skewness1.49 (1.07–2.07)0.0171.48 (1–2.18)0.048
    • DTTV SUVmean liver = SUVmean from tumor volume obtained with liver or spleen as threshold.

    • Cox proportional hazards model P values are shown.

Additional Files

  • Figures
  • Tables
  • Supplemental Data

    Files in this Data Supplement:

    • Supplemental Data
PreviousNext
Back to top

In this issue

Journal of Nuclear Medicine: 62 (10)
Journal of Nuclear Medicine
Vol. 62, Issue 10
October 1, 2021
  • Table of Contents
  • Table of Contents (PDF)
  • About the Cover
  • Index by author
  • Complete Issue (PDF)
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.

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.
Quantitative 68Ga-DOTATATE PET/CT Parameters for the Prediction of Therapy Response in Patients with Progressive Metastatic Neuroendocrine Tumors Treated with 177Lu-DOTATATE
(Your Name) has sent you a message from Journal of Nuclear Medicine
(Your Name) thought you would like to see the Journal of Nuclear Medicine web site.
Citation Tools
Quantitative 68Ga-DOTATATE PET/CT Parameters for the Prediction of Therapy Response in Patients with Progressive Metastatic Neuroendocrine Tumors Treated with 177Lu-DOTATATE
Claudia Ortega, Rebecca K.S. Wong, Josh Schaefferkoetter, Patrick Veit-Haibach, Sten Myrehaug, Rosalyn Juergens, David Laidley, Reut Anconina, Amy Liu, Ur Metser
Journal of Nuclear Medicine Oct 2021, 62 (10) 1406-1414; DOI: 10.2967/jnumed.120.256727

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Share
Quantitative 68Ga-DOTATATE PET/CT Parameters for the Prediction of Therapy Response in Patients with Progressive Metastatic Neuroendocrine Tumors Treated with 177Lu-DOTATATE
Claudia Ortega, Rebecca K.S. Wong, Josh Schaefferkoetter, Patrick Veit-Haibach, Sten Myrehaug, Rosalyn Juergens, David Laidley, Reut Anconina, Amy Liu, Ur Metser
Journal of Nuclear Medicine Oct 2021, 62 (10) 1406-1414; DOI: 10.2967/jnumed.120.256727
Twitter logo Facebook logo LinkedIn logo Mendeley logo
  • Tweet Widget
  • Facebook Like
  • Google Plus One
Bookmark this article

Jump to section

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

Related Articles

  • This Month in JNM
  • PubMed
  • Google Scholar

Cited By...

  • Dual Somatostatin Receptor/18F-FDG PET/CT Imaging in Patients with Well-Differentiated, Grade 2 and 3 Gastroenteropancreatic Neuroendocrine Tumors
  • Interim Analysis of a Prospective Validation of 2 Blood-Based Genomic Assessments (PPQ and NETest) to Determine the Clinical Efficacy of 177Lu-DOTATATE in Neuroendocrine Tumors
  • Google Scholar

More in this TOC Section

  • [18F]FDG PET/CT Predicts Patient Survival in Patients with Systemic Sclerosis–Associated Interstitial Lung Disease
  • Whole-Body [18F]DPA-714 Kinetic Assessment Using PET/CT Scanner with Long Axial Field of View
  • Clinical Outcomes of 177Lu-DOTATATE Peptide Receptor Radionuclide Therapy in Patients with Skeletal Metastases from Neuroendocrine Tumors: Insights from Real-World Experience
Show more Clinical Investigation

Similar Articles

Keywords

  • 68Ga-DOTATATE
  • PET/CT
  • neuroendocrine tumors
  • PRRT
  • response
  • survival
SNMMI

© 2025 SNMMI

Powered by HighWire