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 ArticleOncology

Prediction of Response to Immune Checkpoint Inhibitor Therapy Using Early-Time-Point 18F-FDG PET/CT Imaging in Patients with Advanced Melanoma

Steve Y. Cho, Evan J. Lipson, Hyung-Jun Im, Steven P. Rowe, Esther Mena Gonzalez, Amanda Blackford, Alin Chirindel, Drew M. Pardoll, Suzanne L. Topalian and Richard L. Wahl
Journal of Nuclear Medicine September 2017, 58 (9) 1421-1428; DOI: https://doi.org/10.2967/jnumed.116.188839
Steve Y. Cho
1Johns Hopkins University School of Medicine and Sidney Kimmel Comprehensive Cancer Center, Baltimore, Maryland
2University of Wisconsin School of Medicine and Public Health and Carbone Comprehensive Cancer Center, Madison, Wisconsin
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Evan J. Lipson
1Johns Hopkins University School of Medicine and Sidney Kimmel Comprehensive Cancer Center, Baltimore, Maryland
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Hyung-Jun Im
2University of Wisconsin School of Medicine and Public Health and Carbone Comprehensive Cancer Center, Madison, Wisconsin
3Department of Transdisciplinary Studies, Graduate School of Convergence Science and Technology, Seoul National University, Seoul, Korea; and
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Steven P. Rowe
1Johns Hopkins University School of Medicine and Sidney Kimmel Comprehensive Cancer Center, Baltimore, Maryland
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Esther Mena Gonzalez
1Johns Hopkins University School of Medicine and Sidney Kimmel Comprehensive Cancer Center, Baltimore, Maryland
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Amanda Blackford
1Johns Hopkins University School of Medicine and Sidney Kimmel Comprehensive Cancer Center, Baltimore, Maryland
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Alin Chirindel
1Johns Hopkins University School of Medicine and Sidney Kimmel Comprehensive Cancer Center, Baltimore, Maryland
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Drew M. Pardoll
1Johns Hopkins University School of Medicine and Sidney Kimmel Comprehensive Cancer Center, Baltimore, Maryland
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Suzanne L. Topalian
1Johns Hopkins University School of Medicine and Sidney Kimmel Comprehensive Cancer Center, Baltimore, Maryland
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Richard L. Wahl
1Johns Hopkins University School of Medicine and Sidney Kimmel Comprehensive Cancer Center, Baltimore, Maryland
4Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri
  • 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 1.
    • Download figure
    • Open in new tab
    • Download powerpoint
    FIGURE 1.

    Scatterplot comparing early CT- and PET-based changes with response to ICI at ≥ 4 mo. Each dot represents a single patient, color coded according to best overall response at ≥ 4 mo. Two horizontal dashed lines on y-axis (+20% and −30%) correspond to thresholds for PD and PR, respectively, using RECIST 1.1, in absence of appearance of new tumor lesions. Vertical dashed line at +15.5% on x-axis represents a threshold associated with eventual response according to criteria proposed in Figure 2.

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

    Patients whose CT scans performed 3–4 wk into therapy demonstrate an objective response (PR or CR by RECIST 1.1) are predicted to maintain a response at 4 mo. Similarly, PD detected at that same interval predicts continued disease progression at 4 mo. In patients with stable disease by RECIST 1.1 at 3–4 wk, an increase > 15.5% in SULpeak of hottest lesion by PET is associated with eventual clinical benefit (PR or CR at 4 mo or stable disease ≥ 6 mo). Sensitivity, specificity, and accuracy of algorithm to predict response at 4 mo were 100%, 93.3%, and 95.0%, respectively. CR = complete response; PD = progressive disease; PR = partial response; SD = stable disease; SULpeak = average SUV corrected by lean body mass within a 1-cm3 spheric volume of interest.

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

    PET/CT images demonstrating representative changes in melanoma inguinal lymph node metastasis (red arrowheads) at 4 wk and 4 mo after initiation of ipilimumab. At about 4 wk (SCAN-2), sum of target lesion diameters assessed by CT scan (top) increased by 18.6% (stable disease by RECIST 1.1). During that same interval, PET imaging revealed 25.1% increase in SULpeak (average SUV corrected by lean body mass within a 1-cm3 spheric volume of interest) (PERCIST). Imaging at approximately 4 mo revealed a marked improvement in 18F-FDG avidity of inguinal lymph node metastasis. Similar pattern was observed in this patient’s other sites of disease, including hepatic, nodal, and soft-tissue metastases. Patient’s metastases outside of brain remained stable for 51 wk.

Tables

  • Figures
  • Additional Files
    • View popup
    TABLE 1

    Summary of Treatment Response Criteria

    CT-based criteriaPET-based criteria
    ResponseRECIST 1.1irRCPERCIST 1.0EORTC
    Complete responseDisappearance of all TLs and NLs; all LNs < 10 mm short axisResolution of all lesions (whether measurable or not) and no new lesionsComplete metabolic responseComplete resolution of 18F-FDG uptake within measurable TL and disappearance of all other lesions to BBP levelsComplete resolution of 18F-FDG uptake within TV so that it is indistinguishable from surrounding NT
    Partial response≥30% decrease in SoDs of TLs; NLs may persist but not unequivocally progressDecrease in TB ≥ 50%, measured as SoPs of 2 largest perpendicular diameters of all ILs, relative to BLPartial metabolic response>30% RD and >0.8 AD in SULpeak of HLReduction of 15%–25% in tumor SUV after 1 CoT and >25% after more than 1 CoT
    Stable diseaseNeither sufficient TR nor TG to qualify for PR or PDNot meeting criteria for irCR or irPR, in absence of irPDStable metabolic diseaseNot meeting criteria for CMR, PMR, or PMDIncrease in tumor SUV of <25% or decrease of <15% and no visible increase in extent of 18F-FDG TU (20% in LD)
    Progressive disease≥20% increase in sum of diameters of TLs or unequivocal progression of NL or appearance of new lesionIncrease in TB ≥ 25% relative to nadir, measured as SoPs of 2 largest perpendicular diameters of all ILsProgressive metabolic disease>30% RI and >0.8 AI in SULpeak of HL or unequivocal progression of 18F-FDG–avid NL or appearance of new 18F-FDG–avid lesionIncrease from BL in tumor SUV of >25% within tumor region, visible increase in extent of 18F-FDG TU (20% in LD), or appearance of new 18F-FDG uptake in MLs
    • TL = target lesion; NL = nontarget lesion; LN = lymph node; BBP = background blood-pool; TV = tumor volume; NT = normal tissue; SoDs = sum of diameters; TB = tumor burden; SoPs = sum of the products; IL = index lesion; BL = baseline; RD = relative decrease; AD = absolute decrease; SULpeak = average SUV corrected by lean body mass within a 1-cm3 spheric volume of interest; HL = hottest lesion; CoT = cycle of therapy; TR = tumor regression; TG = tumor growth; PR = partial response; PD = progressive disease; irCR = immune-related complete response; irPR = immune-related partial response; irPD = immune-related progressive disease; CMR = complete metabolic response; PMR = partial metabolic response; PMD = progressive metabolic disease; TU = tumor uptake; LD = longest dimension; RI = relative increase; AI = absolute increase; ML = metastatic lesion; SUV = for EORTC we used SUVmax (maximum voxel value of SUV).

    • View popup
    TABLE 2

    Response Assessments, Excluding Brain Lesions, in 20 Patients with Metastatic Melanoma Receiving ICI Therapies

    Response at SCAN-2 (21–28 d)Response at SCAN-3 (∼4 mo)
    Patient no.TreatmentRECIST 1.1irRCPERCISTEORTCRECIST 1.1irRCPERCISTEORTCBest overall response at ≥ 4 mo (RECIST 1.1)Duration of observation(wk)*Best overall response before SCAN-3 (RECIST 1.1)†
    1IpilimumabPDPDPMDPMDPDPDPMDPMDPD10—
    2IpilimumabSDPDSMDSMDSDSDPMRPMRSD > 6 mo51—
    3IpilimumabPDPDPMDPMDPDPDPMDPMDPD15—
    4IpilimumabPDPDPMDPMDPDPDPMDPMDPD15—
    5IpilimumabPDPDPMDPMDPDPDPMDPMDPD18—
    6BMS-936559SDSDPMRPMRPDPDPMDPMDPD23uSD at 6 wk, PD at 12 wk
    7BMS-936559SDSDSMDSMDPDPDPMDPMDPD18—
    8BMS-936559PDPDPMDPMDPDPDPMDPMDPD18uSD at 6 wk, PD at 12 wk
    9IpilimumabPDPDPMDPMDPDPDPMDPMDPD16—
    10IpilimumabSDSDPMDPMDPDPDPMDPMDPD17—
    11IpilimumabSDSDPMDPMDCRCRPMRPMRCR184—
    12IpilimumabSDSDPMRPMRPDPDSMDSMDPD17—
    13IpilimumabPDPDPMDPMDPDPDPMDPMDPD16—
    14IpilimumabSDSDSMDPMDPRPRPMRPMRPR28—
    15IpilimumabPDPDPMDPMDPDPDPMDPMDPD19—
    16IpilimumabSDSDPMDPMDPRSDPMDSMDPR40—
    17IpilimumabPRPRSMDPMRCRCRPMRPMRCR31—
    18NivolumabSDSDPMRSMDPDSDPMDPMDPD23SD at 8 and 15 wk
    19IpilimumabPDPDPMDPMDPDPDPMDPMDPD17—
    20IpilimumabPDPDPMDPMDPDSDPMDPMDPD16—
    • ↵* Duration of observation is calculated from time of first administration of ICI therapy on this trial. Patients who received ipilimumab were treated with maximum of 4 doses and observed thereafter. Patients who received anti–PD-1/PD-L1 continued to receive therapy until disease progression.

    • ↵† Standard of care on-treatment radiographic assessments performed between SCAN-2 and SCAN-3 for 3 patients demonstrated transient disease stability. Their responses are characterized in last column.

    • PD = progressive disease; PMD = progressive metabolic disease; SD = stable disease; SMD = stable metabolic disease; PMR = partial metabolic response; PR = partial response; u = unconfirmed, seen only on 1 set of scans; CR = complete response.

    • Responses based on 4 criteria in 20 patients with metastatic melanoma after receiving ipilimumab (anti–CTLA-4), nivolumab (anti–PD-1), or BMS-936559 (anti–PD-L1). 18F-FDG PET/CT imaging was performed before therapy (SCAN-1), again between days 21 and 28 (SCAN-2), and at approximately 4 mo posttreatment initiation (SCAN-3).

    • View popup
    TABLE 3

    Performance of 4 Radiologic Evaluation Criteria Applied to Early (3–4 Week) PET/CT Scans in Predicting Best Overall Response (RECIST 1.1) to ICI Therapy at ≥ 4 Months

    Response evaluation criteriaSensitivity (%)Specificity (%)PPV (%)NPV (%)Accuracy (%)
    RECIST1.1100.0 (48.0–100.0)66.7 (38.4–88.1)50.0 (18.9–81.1)100.0 (69.0–100.0)75.0
    irRC80.0 (28.8–96.7)66.7 (38.4–88.1)44.4 (14.0–78.6)90.9 (58.7–98.5)70.0
    PERCIST60.0 (15.4–93.5)73.3 (44.9–92.0)42.9 (10.4–81.2)84.6 (54.5–97.6)70.0
    EORTC40.0 (6.5–84.6)73.3 (44.9–92.0)33.3 (5.3–77.3)78.6 (49.2–95.1)65.0
    • PPV = positive predictive value; NPV = negative predictive value.

    • Data in parentheses are 95% confidence intervals.

    • View popup
    TABLE 4

    Performance Characteristics of 5 Methods of Early Tumor Response Evaluation in Predicting Response (RECIST 1.1) to ICI Therapy at 4 Months

    Method no.Tumor response evaluation method descriptionSCAN-1 to SCAN-2 optimal percentage change cutoffSensitivity (%)Specificity (%)PPV (%)NPV (%)Accuracy (%)
    1Change in sum of RECIST 1.1–based target lesion diameters≤080.0 (28.8–96.7)86.7 (59.5–98.0)66.7 (22.7–94.7)92.9 (66.1–98.8)85.0
    2Change in sum of the products of the 2 largest perpendicular diameters of irRC-based index lesions≤ −14.760.0 (15.4–93.5)93.3 (68.0–98.9)75.0 (20.3–95.9)87.5 (61.6–98.1)85.0
    3Change in SULpeak of the hottest lesion>15.580.0 (28.8–96.7)73.3 (44.9–92.0)50.0 (16.0–84.0)91.7 (61.5–98.6)75.0
    4Change in sum of SUVmax of all 18F-FDG–avid metastatic lesions>14.780.0 (28.8–96.7)66.7 (38.4–88.1)44.4 (14.0–78.6)90.9 (58.7–98.5)70.0
    Methods 1 and 3, above, combined (PECRIT)100.0 (48.0–100)93.3 (68.0–98.9)83.3 (36.1–97.2)100.0 (76.7–100.0)95.0
    • PPV = positive predictive value; NPV = negative predictive value; method 1 = change in sum of target lesion diameters, selected based on RECIST 1.1; method 2 = change in sum of the products of the 2 largest perpendicular diameters of index lesions, selected based on irRC criteria; method 3 = change in peak SUV, normalized by lean body mass, of the hottest lesion (SULpeak) seen on PET scan (PERCIST 1.0); method 4 = change in the SUVmax of all 18F-FDG–avid metastatic lesions; PECRIT = PET/CT Criteria for early prediction of Response to Immune checkpoint inhibitor Therapy.

    • Changes in tumor burden seen on PET/CT scans from baseline (SCAN-1) to 3–4 wk (SCAN-2) were calculated using 4 methods, each based on standard response criteria. Optimal cutoff percentage changes to predict response to ICI therapy based on RECIST 1.1 at 4 mo were determined from ROC analysis. Data in parentheses are 95% confidence intervals.

Additional Files

  • Figures
  • Tables
  • Supplemental Data

    Files in this Data Supplement:

    • Supplemental Data
PreviousNext
Back to top

In this issue

Journal of Nuclear Medicine: 58 (9)
Journal of Nuclear Medicine
Vol. 58, Issue 9
September 1, 2017
  • Table of Contents
  • Table of Contents (PDF)
  • 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.

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.
Prediction of Response to Immune Checkpoint Inhibitor Therapy Using Early-Time-Point 18F-FDG PET/CT Imaging in Patients with Advanced Melanoma
(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
Prediction of Response to Immune Checkpoint Inhibitor Therapy Using Early-Time-Point 18F-FDG PET/CT Imaging in Patients with Advanced Melanoma
Steve Y. Cho, Evan J. Lipson, Hyung-Jun Im, Steven P. Rowe, Esther Mena Gonzalez, Amanda Blackford, Alin Chirindel, Drew M. Pardoll, Suzanne L. Topalian, Richard L. Wahl
Journal of Nuclear Medicine Sep 2017, 58 (9) 1421-1428; DOI: 10.2967/jnumed.116.188839

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Share
Prediction of Response to Immune Checkpoint Inhibitor Therapy Using Early-Time-Point 18F-FDG PET/CT Imaging in Patients with Advanced Melanoma
Steve Y. Cho, Evan J. Lipson, Hyung-Jun Im, Steven P. Rowe, Esther Mena Gonzalez, Amanda Blackford, Alin Chirindel, Drew M. Pardoll, Suzanne L. Topalian, Richard L. Wahl
Journal of Nuclear Medicine Sep 2017, 58 (9) 1421-1428; DOI: 10.2967/jnumed.116.188839
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
    • DISCLOSURE
    • Acknowledgments
    • Footnotes
    • REFERENCES
  • Figures & Data
  • Supplemental
  • Info & Metrics
  • PDF

Related Articles

  • This Month in JNM
  • PubMed
  • Google Scholar

Cited By...

  • Approaches to Imaging Immune Activation Using PET
  • Imaging endpoints for clinical trial use: a RECIST perspective
  • Dynamic Tumor-Specific MHC-II Immuno-PET Predicts the Efficacy of Checkpoint Inhibitor Immunotherapy in Melanoma
  • CD8-Targeted PET Imaging of Tumor-Infiltrating T Cells in Patients with Cancer: A Phase I First-in-Humans Study of 89Zr-Df-IAB22M2C, a Radiolabeled Anti-CD8 Minibody
  • Efficacy and safety of neoadjuvant sintilimab, oxaliplatin and capecitabine in patients with locally advanced, resectable gastric or gastroesophageal junction adenocarcinoma: early results of a phase 2 study
  • Response Evaluation and Survival Prediction After PD-1 Immunotherapy in Patients with Non-Small Cell Lung Cancer: Comparison of Assessment Methods
  • Multimodal Molecular Imaging Detects Early Responses to Immune Checkpoint Blockade
  • Mars Shot for Nuclear Medicine, Molecular Imaging, and Molecularly Targeted Radiopharmaceutical Therapy
  • Radiomics, Tumor Volume, and Blood Biomarkers for Early Prediction of Pseudoprogression in Patients with Metastatic Melanoma Treated with Immune Checkpoint Inhibition
  • Is there a link between very early changes of primary and secondary lymphoid organs in 18F-FDG-PET/MRI and treatment response to checkpoint inhibitor therapy?
  • Immune Checkpoint Imaging in Oncology: A Game Changer Toward Personalized Immunotherapy?
  • Comparison Between 18F-FDG PET-Based and CT-Based Criteria in Non-Small Cell Lung Cancer Patients Treated with Nivolumab
  • Imaging the Cancer Immune Environment and Its Response to Pharmacologic Intervention, Part 1: The Role of 18F-FDG PET/CT
  • Preclinical PERCIST and 25% of SUVmax Threshold: Precision Imaging of Response to Therapy in Co-clinical 18F-FDG PET Imaging of Triple-Negative Breast Cancer Patient-Derived Tumor Xenografts
  • Detecting Early Response to Immune Checkpoint Blockade by Multimodal Molecular Imaging
  • Predictive value of integrated 18F-FDG PET/MRI in the early response to nivolumab in patients with previously treated non-small cell lung cancer
  • 18F-FDG PET/CT for Monitoring of Ipilimumab Therapy in Patients with Metastatic Melanoma
  • The Immunoimaging Toolbox
  • Google Scholar

More in this TOC Section

Oncology

  • Chimeric antigen receptor (CAR) T cells Imaging: Clinical Needs and Strategies for Success
  • Metastatic NUT Midline Carcinoma
  • Radionuclides used in Nuclear Therapeutic Medicine: a brief history, properties and main relevant studies of radionuclides with mass number less than 100
Show more Oncology

Clinical

  • Chimeric antigen receptor (CAR) T cells Imaging: Clinical Needs and Strategies for Success
  • Metastatic NUT Midline Carcinoma
  • Radionuclides used in Nuclear Therapeutic Medicine: a brief history, properties and main relevant studies of radionuclides with mass number less than 100
Show more Clinical

Similar Articles

Keywords

  • FDG
  • PET/CT
  • immune checkpoint inhibitor
  • melanoma
  • response assessment
SNMMI

© 2025 SNMMI

Powered by HighWire