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Abstract #0546

Testing the Quantitative Imaging Biomarkers Alliance (QIBA) PDFF Profile in the Liver: Results from 416 Scanners at 1.5T and 3T

Adrienne G. Siu1, Mary Jean Solywoda1, Tom Davis1, Matthew D. Robson1, and Roberto Salvati1
1Perspectum, Oxford, United Kingdom

Synopsis

Keywords: Quantitative Imaging, Validation, Liver, Phantoms

Motivation: The Quantitative Imaging Biomarkers Alliance (QIBA) PDFF Profile describes the expected performance of an imaging technique when measuring PDFF. However, the expected performance in phantoms was determined in one phantom on 27 scanners and may not be applicable widely.

Goal(s): We tested the hypothesis that the QIBA PDFF bias criteria (mean:within ±5.0%, maximum:within ±7.0% (percentage points)) cannot be attained at scale with multiple phantoms on >400 scanners.

Approach: We calculated the QIBA PDFF criteria using phantom data from 416 scanners across three vendors at 1.5T and 3T.

Results: All six combinations of scanner vendor and field strength passed the QIBA PDFF criteria.

Impact: The hypothesis that the QIBA PDFF bias criteria cannot be maintained with multiple phantoms on >400 scanners was disproven in a novel dataset with 416 scanners, strongly suggesting that it is possible to achieve this level of performance at scale.

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Keywords