Evidence map›Paper›PMID 26493206›Full record

Observational studyJournal of nuclear medicine : official publication, Society of Nuclear Medicine2016

Multicenter Clinical Trials Using 18F-FDG PET to Measure Early Response to Oncologic Therapy: Effects of Injection-to-Acquisition Time Variability on Required Sample Size.

Brenda F Kurland, Mark Muzi, Lanell M Peterson, Robert K Doot, Kristen A Wangerin, David A Mankoff, Hannah M Linden, Paul E Kinahan

Open access · bronzeAbstract readMulticenter StudyObservational Study
In one paragraph

Observational study in Journal of nuclear medicine : official publication, Society of Nuclear Medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
2.7field-weighted citation impact, top 10% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

16 citing papers in PubMed, 25 citations in OpenAlex.

  1. Whole-Body [Tomography (Ann Arbor, Mich.) · 2021
    Trial
  2. Trial
  3. Article
  4. Review
  5. Principles of Tracer Kinetic Analysis in Oncology, Part II: Examples and Future Directions.Journal of nuclear medicine : official publication, Society of Nuclear Medicine · 2022
    Article
  6. Normal values forEJNMMI research · 2022
    Article
  7. Principles of Tracer Kinetic Analysis in Oncology, Part I: Principles and Overview of Methodology.Journal of nuclear medicine : official publication, Society of Nuclear Medicine · 2022
    Article
  8. Article
  9. Association of Tumor [Molecular imaging and biology · 2019
    Article
  10. Test-Retest Reproducibility ofJournal of nuclear medicine : official publication, Society of Nuclear Medicine · 2019
    Article
  11. Article
  12. Review
  13. Article
  14. Repeatability of SUV in OncologicJournal of nuclear medicine : official publication, Society of Nuclear Medicine · 2017
    Review
  15. Getting the Most out of 18F-FDG PET Scans: The Predictive Value of 18F-FDG PET-Derived Blood Flow Estimates for Breast Cancer.Journal of nuclear medicine : official publication, Society of Nuclear Medicine · 2016
    Article
  16. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 4 institutions in 1 country.

Brenda F KurlandDepartment of Biostatistics, University of Pittsburgh, Pittsburgh, Pennsylvania bfk10@pitt.edu.
Mark MuziDepartment of Radiology, University of Washington, Seattle, Washington.
Lanell M PetersonDepartment of Radiology, University of Washington, Seattle, Washington.
Robert K DootDepartment of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania; and.
Kristen A WangerinDepartment of Radiology, University of Washington, Seattle, Washington.
David A MankoffDepartment of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania; and.
Hannah M LindenDivision of Medical Oncology, University of Washington, Seattle, Washington.
Paul E KinahanDepartment of Radiology, University of Washington, Seattle, Washington.
University of Washington · USUniversity of Pennsylvania · USUniversity of Pittsburgh · USUniversity of Washington Medical Center · US

Funding

UNIVERSITY OF PENNSYLVANIA CAN CTR SUPPORT GRANTP30CA016520 · NCI · UNIVERSITY OF PENNSYLVANIA · PI SHELLEY L BERGER · 1985 to 2026
$222.3M
VECTOR CORE FACILITYP30CA047904 · NCI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI Jessie Nedrow · 1988 to 2026
$158.0M
RadiochemistryP01CA042045 · NCI · UNIVERSITY OF WASHINGTON · PI LINK, JEANNE MEYERS · 1986 to 2015
$23.2M
Advanced PET/CT Imaging for Improving Clinical TrialsU01CA148131 · NCI · UNIVERSITY OF WASHINGTON · PI KINAHAN, PAUL E., LINDEN, HANNAH M · 2010 to 2019
$6.0M
IMAGING THE RESPONSE OF LOCALLY ADVANCED BREAST CANCERR01CA072064 · NCI · UNIVERSITY OF WASHINGTON · PI MANKOFF, DAVID A. · 1996 to 2006
$3.1M
NCI NIH HHS P01 CA042045NCI NIH HHS P01-CA42045NCI NIH HHS P30 CA016520NCI NIH HHS P30 CA047904NCI NIH HHS P30-CA047904NCI NIH HHS R01 CA072064NCI NIH HHS R01-CA72064NCI NIH HHS U01 CA148131NCI NIH HHS U01-CA148131
6 · The paper itself

Abstract

unlabelledUptake time (interval between tracer injection and image acquisition) affects the SUV measured for tumors in (18)F-FDG PET images. With dissimilar uptake times, changes in tumor SUVs will be under- or overestimated. This study examined the influence of uptake time on tumor response assessment using a virtual clinical trials approach.

methodsTumor kinetic parameters were estimated from dynamic (18)F-FDG PET scans of breast cancer patients and used to simulate time-activity curves for 45-120 min after injection. Five-minute uptake time frames followed 4 scenarios: the first was a standardized static uptake time (the SUV from 60 to 65 min was selected for all scans), the second was uptake times sampled from an academic PET facility with strict adherence to standardization protocols, the third was a distribution similar to scenario 2 but with greater deviation from standards, and the fourth was a mixture of hurried scans (45- to 65-min start of image acquisition) and frequent delays (58- to 115-min uptake time). The proportion of out-of-range scans (<50 or >70 min, or >15-min difference between paired scans) was 0%, 20%, 44%, and 64% for scenarios 1, 2, 3, and 4, respectively. A published SUV correction based on local linearity of uptake-time dependence was applied in a separate analysis. Influence of uptake-time variation was assessed as sensitivity for detecting response (probability of observing a change of ≥30% decrease in (18)F-FDG PET SUV given a true decrease of 40%) and specificity (probability of observing an absolute change of <30% given no true change).

resultsSensitivity was 96% for scenario 1, and ranged from 73% for scenario 4 (95% confidence interval, 70%-76%) to 92% (90%-93%) for scenario 2. Specificity for all scenarios was at least 91%. Single-arm phase II trials required an 8%-115% greater sample size for scenarios 2-4 than for scenario 1. If uptake time is known, SUV correction methods may raise sensitivity to 87%-95% and reduce the sample size increase to less than 27%.

conclusionUptake-time deviations from standardized protocols occur frequently, potentially decreasing the performance of (18)F-FDG PET response biomarkers. Correcting SUV for uptake time improves sensitivity, but algorithm refinement is needed. Stricter uptake-time control and effective correction algorithms could improve power and decrease costs for clinical trials using (18)F-FDG PET endpoints.

Indexed as

Fluorodeoxyglucose F18RadiopharmaceuticalsAgedAlgorithmsBiomarkersBreast NeoplasmsFemaleHumansMiddle AgedPositron-Emission TomographyProspective StudiesReference StandardsReproducibility of ResultsSample SizeBiomarkersFluorodeoxyglucose F18Radiopharmaceuticals18F-FDG PET standardization18F-FDG PET SUV18F-FDG PET uptake timevirtual clinical trial

Identifiers

PMID26493206
PMCPMC4749350
OpenAlexW2261283658

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.