Objective: To demonstrate proof-of-concept for a quantitative MRI method using histographic
analysis to assess bone marrow oedema and fat metaplasia in the sacroiliac joints.
Materials and Methods: Fifty-three adolescents aged 12-23 with known or suspected sacroiliitis
were prospectively recruited and underwent quantitative MRI (qMRI) scans, consisting of chemical
shift-encoded (at 3T) and diffusion-weighted imaging (at 1.5T), plus conventional MRI (at 1.5T) and
clinical assessment. qMRI scans produced proton-density fat fraction (PDFF) and apparent diffusion
coefficient (ADC) maps of the sacroiliac joints (SIJs), which were analyzed using an in-house software
tool enabling partially-automated ROI definition and histographic analysis. Logistic regression and
receiver operating characteristic (ROC) analyses assessed the predictive performance of ADC- and
PDFF-based parameters in identifying active inflammation (oedema) and structural damage (fat
metaplasia).
Results: ADC-based parameters were associated with increased odds of oedema (all P<0.05); ROCAUC was higher for histographic parameters representing the upper end of the ADC distribution
than for simple averages. Similarly, PDFF-based parameters were associated with increased odds of
fat metaplasia (all P<0.05); ROC area-under-the-curve was higher for histographic parameters
representing the upper end of the PDFF distribution than for simple averages. Both ADC- and
PDFF-based histographic parameters demonstrated excellent inter- and intra-observer agreement
(ICC >0.9).
Conclusions: ADC-based parameters can differentiate patients with bone marrow oedema from those
without, whilst PDFF-based parameters can differentiate patients with fat metaplasia from those
without. Histographic analysis might improve performance compared to simple averages such as the
mean and median and offers excellent agreement within and between observers
