Effects of scatter subtraction on detection and quantitation in hepatic SPECT

Daniel J. De Vries, Michael A. King, Edward J. Soares, Benjamin M.W. Tsui, Charles E. Metz

Research output: Contribution to journalArticlepeer-review

Abstract

The purpose of this investigation was to examine the effects of subtractive scatter compensation methods on lesion detection and quantitation. Methods: Receiver operating characteristic (ROC) methodology was used to measure human observer detection accuracy for tumors in the liver using synthetic images. Furthermore, ROC results were compared with mathematical models for detection and activity quantitation to examine (a) the potential for predicting human performance and (b) the relationship between the detection and quantitation tasks. Images with both low and high amounts of scatter were compared with the ideal case of images of primary photons only (i.e., perfect scatter rejection) and with images corrected by subtracting a scatter image estimated by the dual photopeak window method. Results: With low contrast tumors in a low count background, the results showed that scatter subtraction improved quantitation but did not produce statistically significant increases in detection accuracy. However, primary images did produce some statistically significant improvements in detection accuracy when compared with uncorrected images, particularly for high levels of scatter. Conclusion: Although scatter subtraction methods may provide improved activity quantitation, they may not significantly improve detection for liver SPECT. The results imply that significant improvement in detection accuracy for the conditions tested may depend on the development of gamma cameras with better scatter rejection.

Original languageEnglish (US)
Pages (from-to)1011-1023
Number of pages13
JournalJournal of Nuclear Medicine
Volume40
Issue number6
StatePublished - Jun 1999
Externally publishedYes

Keywords

  • Lesion detection
  • Receiver operating characteristic analysis
  • Scatter correction

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging

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