Free breathing three-dimensional cardiac quantitative susceptibility mapping for differential cardiac chamber blood oxygenation – initial validation in patients with cardiovascular disease inclusive of direct comparison to invasive catheterization

BACKGROUND: Differential blood oxygenation between left (LV) and right ventricles (RV; ΔSaO(2)) is a key index of cardiac performance; LV dysfunction yields increased RV blood pool deoxygenation. Deoxyhemoglobin increases blood magnetic susceptibility, which can be measured using an emerging cardiovascular magnetic resonance (CMR) technique, Quantitative Susceptibility Mapping (QSM) – a concept previously demonstrated in healthy subjects using a breath-hold 2D imaging approach (2D(BH)QSM). This study tested utility of a novel 3D free-breathing QSM approach (3D(NAV)QSM) in normative controls, and validated 3D(NAV)QSM for non-invasive ΔSaO(2) quantification in patients undergoing invasive cardiac catheterization (cath). METHODS: Initial control (n = 10) testing compared 2D(BH)QSM (ECG-triggered 2D gradient echo acquired at end-expiration) and 3D(NAV)QSM (ECG-triggered navigator gated gradient echo acquired in free breathing using a phase-ordered automatic window selection algorithm to partition data based on diaphragm position). Clinical testing was subsequently performed in patients being considered for cath, including 3D(NAV)QSM comparison to cine-CMR quantified LV function (n = 39), and invasive-cath quantified ΔSaO(2) (n = 15). QSM was acquired using 3 T scanners; analysis was blinded to comparator tests (cine-CMR, cath). RESULTS: 3D(NAV)QSM generated interpretable QSM in all controls; 2D(BH)QSM was successful in 6/10. Among controls in whom both pulse sequences were successful, RV/LV susceptibility difference (and ΔSaO(2)) were not significantly different between 3D(NAV)QSM and 2D(BH)QSM (252 ± 39 ppb [17.5 ± 3.1%] vs. 211 ± 29 ppb [14.7 ± 2.0%]; p = 0.39). Acquisition times were 30% lower with 3D(NAV)QSM (4.7 ± 0.9 vs. 6.7 ± 0.5 min, p = 0.002), paralleling a trend towards lower LV mis-registration on 3D(NAV)QSM (p = 0.14). Among cardiac patients (63 ± 10y, 56% CAD) 3D(NAV)QSM was successful in 87% (34/39) and yielded higher ΔSaO(2) (24.9 ± 6.1%) than in controls (p < 0.001). QSM-calculated ΔSaO(2) was higher among patients with LV dysfunction as measured on cine-CMR based on left ventricular ejection fraction (29.4 ± 5.9% vs. 20.9 ± 5.7%, p < 0.001) or stroke volume (27.9 ± 7.5% vs. 22.4 ± 5.5%, p = 0.013). Cath measurements (n = 15) obtained within a mean interval of 4 ± 3 days from CMR demonstrated 3D(NAV)QSM to yield high correlation (r = 0.87, p < 0.001), small bias (− 0.1%), and good limits of agreement (±8.6%) with invasively measured ΔSaO(2). CONCLUSION: 3D(NAV)QSM provides a novel means of assessing cardiac performance. Differential susceptibility between the LV and RV is increased in patients with cine-CMR evidence of LV systolic dysfunction; QSM-quantified ΔSaO(2) yields high correlation and good agreement with the reference of invasively-quantified ΔSaO(2).