Statistical error analysis based on non-parametric bootstrap method of quantitative MBF measurement with H2 15O_PET

Naoki Kawachi, Hiroshi Watabe, Noboru Teramoto, Yoichiro Ohta, Hiroshi Jino, Nobuyuki Kudimo, Kazuyuki Koshino, Kyeong Min Kim, Takuya Hayashi, Hidehiro Iida

Research output: Contribution to journalConference articlepeer-review

Abstract

Knowledg of the precision in the physiological parameters estimated by positron emission tomography (PET) is helpful for optimizing PET study and accurate diagnosis. Nonparametric bootstrap method proposed by Buvat is resampling techniques that can be used to accurately estimate the statistical properties of PET images in one scan and determine statistics of pixel values. The standard deviation (SD) of time activity curves (TAC) generated by region of interests (ROI) also are estimated by using the bootstrap method and the SD would propagate to estimated parameters such as blood flow. In order to evaluate the present method, a PET study for myocardial Mood flow (MBF) measurement with H215O_PET was performed. The statistical properties of MBF were estimated and the effects of scan-duration time and ROI size on the SD of MBF were developed.

Original languageEnglish
Pages (from-to)2660-2663
Number of pages4
JournalIEEE Nuclear Science Symposium Conference Record
Volume4
Publication statusPublished - 2004
Event2004 Nuclear Science Symposium, Medical Imaging Conference, Symposium on Nuclear Power Systems and the 14th International Workshop on Room Temperature Semiconductor X- and Gamma- Ray Detectors - Rome, Italy
Duration: 2004 Oct 162004 Oct 22

ASJC Scopus subject areas

  • Radiation
  • Nuclear and High Energy Physics
  • Radiology Nuclear Medicine and imaging

Fingerprint Dive into the research topics of 'Statistical error analysis based on non-parametric bootstrap method of quantitative MBF measurement with H<sub>2</sub> <sup>15</sup>O_PET'. Together they form a unique fingerprint.

Cite this