Monte Carlo validation in diagnostic radiological imaging

John M Boone, Michael H. Buonocore, Virgil N. Cooper

Research output: Contribution to journalArticlepeer-review

47 Scopus citations


Monte Carlo analysis in the radiological sciences has been used for several decades, however with the ever-increasing power of desktop computers, the utility of Monte Carlo simulation is increasing. A Monte Carlo code called the Simple Investigative Environment for Radiological Research Applications (SIERRA) is described mathematically, and is then compared against an array of published and unpublished results determined by other means. A series of 32 comparisons between data sets, 22 from independent Monte Carlo simulations and 10 from physically measured data, were assessed. The compared parameters included depth dose curves, lateral energy scattering profiles, scatter to primary ratios, normalized glandular doses, angular scattering distributions, and computed tomography dose index (CTDI) values. Three of the 32 comparisons data sets were excluded as they were identified as outliers. Of the remaining 29 data sets compared, the mean differences ranged from - 14.8% to +17.2%, and the average of the mean differences was 0.12% (σ=1.64%, and the median difference was 1.57%. Fifty percent of the comparisons showed mean differences of ~5% or less, and 93% of the comparisons showed mean differences of 12% or less. We conclude that for research applications in diagnostic radiology, the SIERRA Monte Carlo code demonstrates accuracy and precision to well within acceptable levels. (C) 2000 American Association of Physicists in Medicine.

Original languageEnglish (US)
Pages (from-to)1294-1304
Number of pages11
JournalMedical Physics
Issue number6
StatePublished - Jun 2000

ASJC Scopus subject areas

  • Biophysics


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