SU‐EE‐A4‐04: Compartment Modeling Analysis of Cu‐ATSM Dynamic PET Images

Purpose: Copper labeled diacetyl‐bis(N4‐methylthiosemicarbazone) (Cu‐ATSM) has been reported to selectively bind to hypoxic tumor cells. This makes Cu‐ATSM PET a promising modality to image tumor hypoxia. However, intravascular Cu‐ATSM that is not related to hypoxia, can also contribute to the PET signal. The purpose of this study is to use compartment modeling analysis to separate tumor tissue time‐activity Cu‐ATSM signal into intravascular and extravascular components. Method and Materials: A dynamic Cu‐ATSM PET scanning was performed on tumor‐bearing (R3230 mammary adenocarcinoma) rats. The Cu‐ATSM concentration is separated into an intravascular concentration (Cp) with vascular volume fraction (vp) and extravascular concentration (Ce). The transfer between the intra‐ and extra‐vascular compartments is described by rate constant k. The time activity data of Cu‐ATSM were fed into the compartment model. After non‐linear least square (NLLS) fitting of the model, tumor signal was separated into intravascular and extravascular components. Vascular volume fraction vp and rate constant k were also obtained from the fitting. Results: The time courses of the intravascular and extravascular Cu‐ATSM signals were obtained from the NLLS fitting and are shown in figure 1 in the supporting document. The fitted Cu‐ATSM uptake signals match closely with the measured results. The vascular volume fraction obtained from the fitting for three tumors was 2.4%, 2.3% and 2.9%, and the transfer rate from blood to tissue was 0.045, 0.043, and 0.047 (1/minute), respectively. Conclusion: Compartment modeling analysis can effectively remove the intravascular Cu‐ATSM signal from the overall tissue signals, reflecting more accurately the tissue uptake and tumor hypoxia. Tumor vascular volume fraction and Cu‐ATSM transfer rate constant can be obtained from the compartment modeling analysis. © 2005, American Association of Physicists in Medicine. All rights reserved.

Duke Scholars

Author Christopher G. Willett Radiation Oncology

Author Mark Wesley Dewhirst Radiation Oncology

Author Fang-Fang Yin Radiation Oncology