Technologist performance on liver fat/iron MR quantification studies: Can we do better?

Purpose: Liver fat and iron overload can lead to cirrhosis requiring early detection. Magnetic resonance (MR) imaging utilizing chemical-shift-encoded (CSE) sequences and multi-time-of-echo (TE) single-voxel spectroscopy (SVS) are frequently used for assessment. Poor sequence implementation and data quality may lead to misdiagnosis or repeat patient examinations. This study assesses various quality factors of technical acceptability and identifies deficiencies in technologist performance of these fat/iron MR quantification studies at a single institution.

Methods/Materials: IRB waived retrospective quality improvement review of 87 fat/iron MR studies performed over a six-month period across 9 scanners and 5 hospitals. Technical acceptability for CSE sequences (q-Dixon and IDEAL-IQ) included data handling errors (missing maps including water only, fat fraction, and R2*), anatomic coverage, fat/water swap, motion, or other artifacts. Similarly, data handling (missing table/spectroscopy), curve-fit, fat and water peaks separation, and water-peak sharpness were evaluated for SVS technical acceptability.

Results: Data handling errors were found in 11% (10/87) of studies with missing maps (6 cases) or entire sequence (three missed SVS and one missed CSE). 27% (23/86) of the CSE studies were technically suboptimal [incomplete liver-field (39%), other artifacts (35%), significant/severe motion (18%), global fat/water swap (4%), and multiple reasons (4%)]. 28% (21/75) of SVS sequences were suboptimal [water-peak broadness (67%), poor curve-fit (19%) overlapping fat and water peaks (5%), and multiple reasons (9%)].

Conclusions: A high rate of preventable errors in fat/iron MR quantification studies necessitates routine quality control and evaluation of technologist performance for technical deficiencies that may exist within a radiology practice. Potential helpful solutions include periodic training, routine QC auditing, and implementing a protocol acquisition checklist for technologists. Future studies should evaluate the efficacy of these potential interventions.