Towards real-time topical detection and characterization of FDG dose infiltration prior to PET imaging

  • Jason M. Williams
  • Lori R. Arlinghaus
  • Sudheer D. Rani
  • Martha D. Shone
  • Vandana G. Abramson
  • Praveen Pendyala
  • A. Bapsi Chakravarthy
  • William J. Gorge
  • Joshua G. Knowland
  • Ronald K. Lattanze
  • Steven R. Perrin
  • Charles W. Scarantino
  • David W. Townsend
  • Richard G. Abramson
  • Thomas E. Yankeelov
Original Article

Abstract

Purpose

To dynamically detect and characterize 18F-fluorodeoxyglucose (FDG) dose infiltrations and evaluate their effects on positron emission tomography (PET) standardized uptake values (SUV) at the injection site and in control tissue.

Methods

Investigational gamma scintillation sensors were topically applied to patients with locally advanced breast cancer scheduled to undergo limited whole-body FDG-PET as part of an ongoing clinical study. Relative to the affected breast, sensors were placed on the contralateral injection arm and ipsilateral control arm during the resting uptake phase prior to each patient’s PET scan. Time-activity curves (TACs) from the sensors were integrated at varying intervals (0–10, 0–20, 0–30, 0–40, and 30–40 min) post-FDG and the resulting areas under the curve (AUCs) were compared to SUVs obtained from PET.

Results

In cases of infiltration, observed in three sensor recordings (30 %), the injection arm TAC shape varied depending on the extent and severity of infiltration. In two of these cases, TAC characteristics suggested the infiltration was partially resolving prior to image acquisition, although it was still apparent on subsequent PET. Areas under the TAC 0–10 and 0–20 min post-FDG were significantly different in infiltrated versus non-infiltrated cases (Mann–Whitney, p < 0.05). When normalized to control, all TAC integration intervals from the injection arm were significantly correlated with SUVpeak and SUVmax measured over the infiltration site (Spearman ρ ≥ 0.77, p < 0.05). Receiver operating characteristic (ROC) analyses, testing the ability of the first 10 min of post-FDG sensor data to predict infiltration visibility on the ensuing PET, yielded an area under the ROC curve of 0.92.

Conclusions

Topical sensors applied near the injection site provide dynamic information from the time of FDG administration through the uptake period and may be useful in detecting infiltrations regardless of PET image field of view. This dynamic information may also complement the static PET image to better characterize the true extent of infiltrations.

Keywords

Infiltration Extravasation Standardized uptake value accuracy Time-activity curve Topical scintillation device Radiotracer injection 

Supplementary material

259_2016_3477_MOESM1_ESM.pdf (551 kb)
Supplemental Figure 1(PDF 550 kb)
259_2016_3477_MOESM2_ESM.pdf (98 kb)
Supplemental Table 1(PDF 97 kb)

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Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  • Jason M. Williams
    • 1
  • Lori R. Arlinghaus
    • 1
  • Sudheer D. Rani
    • 1
    • 2
  • Martha D. Shone
    • 2
  • Vandana G. Abramson
    • 3
    • 4
  • Praveen Pendyala
    • 5
  • A. Bapsi Chakravarthy
    • 4
    • 5
  • William J. Gorge
    • 6
  • Joshua G. Knowland
    • 6
  • Ronald K. Lattanze
    • 6
  • Steven R. Perrin
    • 6
  • Charles W. Scarantino
    • 6
    • 7
  • David W. Townsend
    • 6
    • 8
  • Richard G. Abramson
    • 1
    • 2
    • 4
  • Thomas E. Yankeelov
    • 9
  1. 1.Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical CenterNashvilleUSA
  2. 2.Department of Radiology and Radiological SciencesVanderbilt University Medical CenterNashvilleUSA
  3. 3.Department of MedicineVanderbilt University Medical CenterNashvilleUSA
  4. 4.Vanderbilt-Ingram Cancer CenterNashvilleUSA
  5. 5.Department of Radiation OncologyVanderbilt University Medical CenterNashvilleUSA
  6. 6.Lucerno Dynamics, LLCMorrisvilleUSA
  7. 7.Department of Radiation OncologyUniversity of North CarolinaChapel HillUSA
  8. 8.Clinical Imaging Research Centre, Agency for ScienceTechnology and Research-National University of SingaporeSingaporeSingapore
  9. 9.Institute for Computational and Engineering Sciences, and Departments of Biomedical Engineering and Internal MedicineThe University of Texas at AustinAustinUSA

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