Optimized acquisition time and image sampling for dynamic SPECT of Tl-201

Chi Hoi Lau, Stefan Eberl, Dagan Feng, Hidehiro Lida, Pak Kong Lun, Wan Chi Siu, Yoshikazu Tamura, George J. Bautovich, Yukihiko Ono

Research output: Journal article publicationJournal articleAcademic researchpeer-review

17 Citations (Scopus)


With the recent development in scatter and attenuation correction algorithms, dynamic single photon emission computerized tomography (SPECT) can potentially yield physiological parameters, with tracers exhibiting suitable kinetics such as thallium-201 (Tl-201). A systematic way is proposed to investigate the minimum data acquisition times and sampling requirements for estimating physiological parameters with quantitative dynamic SPECT. Two different sampling schemes were investigated with Monte Carlo simulations: 1) Continuous data collection for total study duration ranging from 30-240 min. 2) Continuous data collection for first 10-45 min followed by a delayed study at approximately 3 h. Tissue time activity curves with realistic noise were generated from a mean plasma time activity curve and rate constants (Ki - fc4) derived from Tl-201 kinetic studies in 16 dogs. Full dynamic sampling schedules (DynSS) were compared to optimum sampling schedules (OSS). We found that OSS can reliably estimate the blood flow related K\ and Vd comparable to DynSS. A 30-min continuous collection was sufficient if only K\ was of interest. A split session schedule of a 30-min dynamic followed by a static study at 3 h allowed reliable estimation of both K\ and Vd avoiding the need for a prolonged (>60-min) continuous dynamic acquisition. The methodology developed should also be applicable to optimizing sampling schedules for other SPECT tracers.
Original languageEnglish
Pages (from-to)334-343
Number of pages10
JournalIEEE Transactions on Medical Imaging
Issue number3
Publication statusPublished - 1 Dec 1998


  • Compartmental modeling
  • Optimum image sampling schedule
  • tl-201 tracer kinetics

ASJC Scopus subject areas

  • Software
  • Radiological and Ultrasound Technology
  • Computer Science Applications
  • Electrical and Electronic Engineering


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