Author + information
- Lingcong Kong1
Differentiating hypertrophic cardiomyopathy (HCM) from hypertensive heart disease (HHD) unavoidably encounters diagnostic challenges in cases such as a patient with a history of hypertension was suspected with HCM. Diverse and overlapping forms of HCM can often lead to ambiguity when the diagnosis is based on a single genetic or morphological index. Combining feature tracking (FT) and late gadolinium enhancement (LGE) using cardiac magnetic resonance (CMR) imaging, we aim to identify the difference between the two disorders.
Proposing and validation procedures were conducted in patients with documented HCM and HHD. Principal component analysis (PCA) was conducted on CMR indices selected by univariate analysis to model an integrated algorithm (IntA) in screening the two disorders. K-folding validation and second phase recruited subjects were to validate the algorithm.
One hundred and seventy-eight subjects were prospectively included: 75 HCM, 33 HHD were to generate algorithm and 55 HCM, 16 HHD were for the validation. IntA was formulated through PCA includes left ventricular ejection fraction, left ventricular volume, end diastolic wall thickness and global circumferential strain. Notably, in late gadolinium enhancement (LGE)-positive subjects, the cutoff point of IntA≥81 indicates HCM (83% sensitivity, 91% specificity), and the area under the curve (AUC) of IntA reached 0.900. In LGE-negative subjects, higher possibility of HCM is indicated by a cutoff point of IntA ≥84 (100% sensitivity, 82% specificity), and the AUC reached 0.947. IntA also exhibited diagnostic value in sub-group with HCM companioned with hypertension and in sub-group with non-obstructive hypertrophy compared with single indices. Validation of IntA witnessed the AUC of 0.846 in LGE-negative subjects, and 0.86 in LGE-positive subjects.
A per-patient based IntA formula was deduced from CMR exam containing FT, LGE, and conventional parameters. The workflow provides a useful approach for differentiating between HCM and HHD and might contribute to the more accurate identification of disease, especially in clinically ambiguous status.