Quality assurance multicenter comparison of different MR scanners for quantitative diffusion-weighted imaging

Giacomo Belli1, Simone Busoni2, Antonio Ciccarone3

  • 1Health Physics Unit, USL 8, Arezzo, Italy.

Abstract

Insights

A new quality assurance protocol for diffusion-weighted imaging (DWI) ensures reliable magnetic resonance imaging (MRI) scanner comparisons. This DWI quality control method demonstrates high accuracy and repeatability across multiple centers and scanner types.

Area of Science:

  • Medical Imaging
  • Radiology
  • Biophysics

Background:

  • Quantitative diffusion-weighted imaging (DWI) is crucial for various clinical applications.
  • Standardized quality assurance (QA) protocols are needed for multicenter magnetic resonance imaging (MRI) comparisons.
  • Current DWI protocols lack widespread acceptance for quality control.

Purpose of the Study:

  • To propose a standardized MRI quality assurance procedure for multicenter DWI comparisons.
  • To evaluate the reliability of quantitative DWI metrics across different MR scanners.
  • To establish a benchmark for assessing DWI data integrity.

Main Methods:

  • Twenty-six centers with 35 MR scanners (1T, 1.5T, 3T) participated.
  • Two DWI acquisition series (b-values 0-1000 and 0-3000 s/mm(2)) were performed using a doped water phantom.
  • Mean apparent diffusion coefficient (ADC) values and their repeatability were calculated for each scanner.

Main Results:

  • Excellent agreement between nominal and measured mean ADC values across centers (over 80% within 5% deviation).
  • Highest deviation of mean ADC was 9.3%, with an overall standard deviation of 3.5%.
  • Short-term repeatability of ADC measurements was consistently below 2.5% for all scanners.

Conclusions:

  • The proposed DWI QA protocol is effective for assessing MR scanner reliability.
  • This protocol can be applied to ensure the quality of DWI-derived indices in multicenter studies.
  • Implementation of this QA procedure will enhance the consistency and comparability of quantitative DWI data.

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