Editorial for “Left Ventricular Hemodynamic Forces Changes in Fabry Disease: A Cardiac Magnetic Resonance Study”

Cardiac MR is advantaged in critically defining cardiovascular disease with its wealth of tools that can elucidate the breadth of cardiac function, flow, and tissue characterization (via late gadolinium enhancement imaging), all of which are readily considered gold standards among noninvasive imaging techniques.1 Further, for more than a decade marked attention has been paid to deeper tissue characterization using parametric mapping, including T1- and T2-mapping approaches, and T2* techniques, allowing for even greater discrimination of multiple myocardial disease states.2 Lastly, while the analysis of myocardial mechanics via strain (and associated) techniques has been studied for over two decades, it has been somewhat slower to gain clinical acceptance despite a plethora of data indicating earlier detection of cardiac dysfunction in particular disease states.3 Perhaps the most important arena for the use of advanced imaging metrics for detecting subclinical cardiac dysfunction is in rare diseases, such as Fabry disease (FD), where early diagnosis and intervention hold out promise for significantly influencing outcomes. Fabry disease, an X-linked lysosomal storage disorder caused by mutations in the GLA gene, is marked by progressive cardiac involvement, with left ventricular hypertrophy (LVH) being a prominent morphologic risk factor for adverse outcomes. While morphologic features and tissue characterization have been shown to be important parameters in categorizing disease severity, alterations in myocardial mechanics present a potential earlier point in the disease progression where the entity can be recognized. In this issue of JMRI, Chen et al4 present intriguing findings on the potential utility of hemodynamic force (HDF) analysis in identifying early cardiac changes in FD. The HDF technique, considered an extension of deformation imaging, employs a mathematical model to estimate the integral of the pressure gradients generated in the ventricle over the cardiac cycle in combination with the areas of the aortic and mitral valve orifices. HDF analysis is performed using standard cine Cardiac MR images, and potentially offers a novel perspective on myocardial function and performance highlighting cardiac physiology not captured by traditional metrics.5 Chen et al's investigation explores the ability of HDF metrics to identify subclinical cardiac dysfunction even earlier than T1-mapping or standard strain techniques. The findings are intriguing specifically for parametric mapping, as native T1 mapping, while invaluable in characterizing tissue changes by detecting myocardial fibrosis, nonetheless has limitations in certain FD phenotypes, particularly in advanced stages where T1 values may “pseudonormalize.” For strain imaging, the specific parameter of global longitudinal strain has been recognized as a fairly robust marker of early myocardial dysfunction that in FD demonstrates relatively small overlap across different disease stages.6 While HDF results suggest an even earlier identification of disease in those without LVH, the not insignificant overlap seen in HDF metrics, particularly systolic peak force, raises questions about its broader discriminatory power. The cornerstone of FD management, enzyme replacement therapy (ERT), is potentially most effective when initiated early, and it is here that the integration of HDF metrics to guide such early intervention is its most enticing opportunity. If HDF metrics can reliably identify pre-hypertrophic stages of cardiac involvement, trials proving that the timely initiation of ERT can potentially prevent irreversible myocardial damage could present a paradigm shift for the treatment and care of FD patients. While this early work into HDF analysis in FD as a diagnostic and prognostic tool raises hope for earlier disease detection, the typical limitations of single center data, a relatively small N, and the associated broad standard deviations in HDF quantification, as well as the overlap among groups, point to the need for more data with larger, multicenter investigations. In addition, defining thresholds for clinical decision-making and predicting adverse outcomes remains a critical challenge for clinical acceptance. It remains to be determined whether HDF assessment of FD, alone or in combination with other known biomarkers for FD, will find a vital role in clinical imaging practice. Nonetheless, the publication by Chen et al4 is an important early step in advancing Cardiac MR's utility in the care of FD patients.