Left Ventricular Strain Is Abnormal in Preclinical and Overt Hypertrophic Cardiomyopathy: Cardiac MR Feature Tracking.

Purpose To evaluate myocardial strain and circumferential transmural strain difference (cTSD; the difference between epicardial and endocardial circumferential strain) in a genotyped cohort with hypertrophic cardiomyopathy (HCM) and to explore correlations between cTSD and other anatomic and functional markers of disease status. Left ventricular (LV) dysfunction may indicate early disease in preclinical HCM (sarcomere mutation carriers without LV hypertrophy). Cardiac MRI feature tracking may be used to evaluate myocardial strain in carriers of HCM sarcomere mutation. Materials and Methods Participants with HCM and their family members participated in a prospective, multicenter, observational study (HCMNet). Genetic testing was performed in all participants. Study participants underwent cardiac MRI with temporal resolution at 40 msec or less. LV myocardial strain was analyzed by using feature-tracking software. Circumferential strain was measured at the epicardial and endocardial surfaces; their difference yielded the circumferential transmural strain difference (cTSD). Multivariable analysis to predict HCM status was performed by using multinomial logistic regression adjusting for age, sex, and LV parameters. Results Ninety-nine participants were evaluated (23 control participants, 34 participants with preclinical HCM [positive for sarcomere mutation and negative for LV hypertrophy], and 42 participants with overt HCM [positive for sarcomere mutation and negative for LV hypertrophy]). The average age was 25 years ± 11 and 44 participants (44%) were women. Maximal LV wall thickness was 9.5 mm ± 1.4, 9.8 mm ± 2.2, and 16.1 mm ± 5.3 in control participants, participants with preclinical HCM (P = .496 vs control participants), and participants with overt HCM (P < .001 vs control participants), respectively. cTSD for control participants, preclinical HCM, and overt HCM was 14% ± 4, 17% ± 4, and 22% ± 7, respectively (P < .01 for all comparisons). In multivariable models (controlling for septal thickness and log-transformed N-terminal brain-type natriuretic peptide), cTSD was predictive of preclinical and overt HCM disease status (P < .01). Conclusion Cardiac MRI feature tracking identifies myocardial dysfunction not only in participants with overt hypertrophic cardiomyopathy, but also in carriers of sarcomere mutation without left ventricular hypertrophy, suggesting that contractile abnormalities are present even when left ventricular wall thickness is normal. © RSNA, 2018 Online supplemental material is available for this article.

Technical Note: High temporal resolution characterization of gating response time.

PURPOSE: Low temporal latency between a gating ON/OFF signal and the LINAC beam ON/OFF during respiratory gating is critical for patient safety. Here the authors describe a novel method to precisely measure gating lag times at high temporal resolutions. METHODS: A respiratory gating simulator with an oscillating platform was modified to include a linear potentiometer for position measurement. A photon diode was placed at linear accelerator isocenter for beam output measurement. The output signals of the potentiometer and diode were recorded simultaneously at 2500 Hz with an analog to digital converter for four different commercial respiratory gating systems. The ON and OFF of the beam signal were located and compared to the expected gating window for both phase and position based gating and the temporal lag times extracted. RESULTS: For phase based gating, a real-time position management (RPM) infrared marker tracking system with a single camera and a RPM system with a stereoscopic camera were measured to have mean gate ON/OFF lag times of 98/90 and 86/44 ms, respectively. For position based gating, an AlignRT 3D surface system and a Calypso magnetic fiducial tracking system were measured to have mean gate ON/OFF lag times of 356/529 and 209/60 ms, respectively. CONCLUSIONS: Temporal resolution of the method was high enough to allow characterization of individual gate cycles and was primary limited by the sampling speed of the data recording device. Significant variation of mean gate ON/OFF lag time was found between different gating systems. For certain gating devices, individual gating cycle lag times can vary significantly.