Optimal HMPAO α value for Lassen’s correction algorithm obscured by statistical noise

Masashi Kameyama, Koji Murakami, Masahiro Jinzaki

Research output: Contribution to journalArticle

Abstract

Objective: [99mTc] d,l-hexamethyl-propyeneamine oxime (99mTc-HMPAO), a brain perfusion tracer, suffers significant underestimation of regional cerebral blood flow (rCBF). Lassen et al. developed their linearization algorithm to correct the influence of back-diffusion of the tracer, and proposed their parameter α as 1.5. Based on mathematical modeling and literature review, recently, a new α value of 0.5 has been proposed for Lassen’s correction algorithm for 99mTc-HMPAO, although correction using the old α value of 1.5 was confirmed to be sufficient. Inugami et al. reported that linearization correction gives a stable correlation coefficient over a wide range of α. Our hypotheses are that statistical noise is the source of the stable correlation coefficient presented by them and that the robustness of the correlation coefficient is the reason why many studies confirmed the value of α as 1.5. Methods: Statistical noise was added in silico to the count, whose relationship with flow was α = 0.5. Then, the count was corrected by Lassen’s linearization algorithm with a variety of α. Results: This study confirmed the hypothesis that smaller α values (strong correction) increase the noise at high flow values, leading to nominal increases in correlation coefficient as α decreases. Conclusion: Despite this, adoption of the new, smaller α value of 0.5 would be more useful clinically in regaining the contrast between low-flow and high-flow areas of the brain.

Original languageEnglish
Pages (from-to)1-5
Number of pages5
JournalAnnals of Nuclear Medicine
DOIs
Publication statusAccepted/In press - 2016 Mar 26

Keywords

  • Tc-HMPAO
  • Image contrast
  • Lassen’s linearization correction algorithm
  • Renkin–Crone’s equation
  • Single photon emission computed tomography

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging

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