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Background: In patients with suspected or known hypertrophic cardiomyopathy (HCM), late gadolinium enhancement (LGE) provides diagnostic and prognostic value. However, contraindications and long-term retention of gadolinium have raised concern about repeated gadolinium administration in this population. Alternatively, native T1 -mapping enables identification of focal fibrosis, the substrate of LGE. However HCM-specific heterogeneous fibrosis distribution leads to subtle T1 -maps changes that are difficult to identify.Purpose: To apply radiomic texture analysis on native T1 -maps to identify patients with a low likelihood of LGE(+), thereby reducing the number of patients exposed to gadolinium administration.Study Type: Retrospective interpretation of prospectively acquired data.Subjects: In all, 188 (54.7 ± 14.4 years, 71% men) with suspected or known HCM.Field Strength/sequence: A 1.5T scanner; slice-interleaved native T1 -mapping (STONE) sequence and 3D LGE after administration of 0.1 mmol/kg of gadobenate dimeglumine.Assessment: Left ventricular LGE images were location-matched with native T1 -maps using anatomical landmarks. Using a split-sample validation approach, patients were randomly divided 3:1 (training/internal validation vs. test cohorts). To balance the data during training, 50% of LGE(-) slices were discarded.Statistical Tests: Four sets of texture descriptors were applied to the training dataset for capture of spatially dependent and independent pixel statistics. Five texture features were sequentially selected with the best discriminatory capacity between LGE(+) and LGE(-) T1 -maps and tested using a decision tree ensemble (DTE) classifier.Results: The selected texture features discriminated between LGE(+) and LGE(-) T1 -maps with a c-statistic of 0.75 (95% confidence interval [CI]: 0.70-0.80) using 10-fold cross-validation during internal validation in the training dataset and 0.74 (95% CI: 0.65-0.83) in the independent test dataset. The DTE classifier provided adequate labeling of all (100%) LGE(+) patients and 37% of LGE(-) patients during testing.Data Conclusion: Radiomic analysis of native T1 -images can identify ~1/3 of LGE(-) patients for whom gadolinium administration can be safely avoided.Level Of Evidence: 2 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2020. J. Magn. Reson. Imaging 2020;52:906-919. [ABSTRACT FROM AUTHOR]

Background: The pattern of myocardial fibrosis differs significantly between different cardiomyopathies. Fibrosis in hypertrophic cardiomyopathy (HCM) is characteristically as patchy and regional but in dilated cardiomyopathy (DCM) as diffuse and global. We sought to investigate if texture analyses on myocardial native T1 mapping can differentiate between fibrosis patterns in patients with HCM and DCM. Methods: We prospectively acquired native myocardial T1 mapping images for 321 subjects (55±15 years, 70% male): 65 control, 116 HCM, and 140 DCM patients. To quantify different fibrosis patterns, four sets of texture descriptors were used to extract 152 texture features from native T1 maps. Seven features were sequentially selected to identify HCM- and DCM-specific patterns in 70% of data (training dataset). Pattern reproducibility and generalizability were tested on the rest of data (testing dataset) using support vector machines (SVM) and regression models. Results: Pattern-derived texture features were capable to identify subjects in HCM, DCM, and controls cohorts with 202/237(85.2%) accuracy of all subjects in the training dataset using 10-fold cross-validation on SVM (AUC = 0.93, 0.93, and 0.93 for controls, HCM and DCM, respectively), while pattern-independent global native T1 mapping was poorly capable to identify those subjects with 121/237(51.1%) accuracy (AUC = 0.78, 0.51, and 0.74) (P<0.001 for all). The pattern-derived features were reproducible with excellent intra- and inter-observer reliability and generalizable on the testing dataset with 75/84(89.3%) accuracy. Conclusion: Texture analysis of myocardial native T1 mapping can characterize fibrosis patterns in HCM and DCM patients and provides additional information beyond average native T1 values. [ABSTRACT FROM AUTHOR]

Purpose: To develop a gadolinium‐free cardiac MR technique that simultaneously exploits native T1 and magnetization transfer (MT) contrast for the imaging of myocardial infarction. Methods: A novel hybrid T one and magnetization transfer (HYTOM) method was developed based on the modified look‐locker inversion recovery (MOLLI) sequence, with a train of MT‐prep pulses placed before the balanced SSFP (bSSFP) readout pulses. Numerical simulations, based on Bloch‐McConnell equations, were performed to investigate the effects of MT induced by (1) the bSSFP readout pulses, and (2) the MT‐prep pulses, on the measured, "apparent," native T1 values. The HYTOM method was then tested on 8 healthy adult subjects, 6 patients, and a swine with prior myocardial infarction (MI). The resulting imaging contrast between normal myocardium and infarcted tissues was compared with that of MOLLI. Late gadolinium enhancement (LGE) images were also obtained for infarct assessment in patients and swine. Results: Numerical simulation and in vivo studies in healthy volunteers demonstrated that MT effects, resulting from on‐resonance bSSFP excitation pulses and off‐resonance MT‐prep pulses, reduce the measured T1 in both MOLLI and HTYOM. In vivo studies in patients and swine showed that the HYTOM sequence can identify locations of MI, as seen on LGE. Furthermore, the HYTOM method yields higher myocardium‐to‐scar contrast than MOLLI (contrast‐to‐noise ratio: 7.33 ± 1.67 vs. 3.77 ± 0.66, P < 0.01). Conclusion: The proposed HYTOM method simultaneously exploits native T1 and MT contrast and significantly boosts the imaging contrast for myocardial infarction. [ABSTRACT FROM AUTHOR]

Purpose: To develop and evaluate an integrated motion correction and dictionary learning (MoDic) technique to accelerate data acquisition for myocardial T1 mapping with improved accuracy. Methods: MoDic integrates motion correction with dictionary learning–based reconstruction. A random undersampling scheme was implemented for slice‐interleaved T1 mapping sequence to allow prospective undersampled data acquisition. Phantom experiments were performed to evaluate the effect of reconstruction on T1 measurement. In vivo T1 mappings were acquired in 8 healthy subjects using 6 different acceleration approaches: uniform or randomly undersampled k‐space data with reduction factors (R) of 2, 3, and 4. Uniform undersampled data were reconstructed with SENSE, and randomly undersampled k‐space data were reconstructed using dictionary learning, compressed sensing SENSE, and MoDic methods. Three expert readers subjectively evaluated the quality of T1 maps using a 4‐point scoring system. The agreement between T1 values was assessed by Bland‐Altman analysis. Results: In the phantom study, the accuracy of T1 measurements improved with increasing reduction factors (-31 ± 35 ms, -13 ± 18 ms, and -5 ± 11 ms for reduction factor (R) = 2 to 4, respectively). The image quality of in vivo T1 maps assessed by subjective scoring using MoDic was similar to that of SENSE at R = 2 (P =.61) but improved at R = 3 and 4 (P <.01). The scores of dictionary learning (2.98 ± 0.71, 2.91 ± 0.60, and 2.67 ± 0.71 for R = 2 to 4) and CS‐SENSE (3.32 ± 0.42, 3.05 ± 0.43, and 2.53 ± 0.43) were lower than those of MoDic (3.48 ± 0.46, 3.38 ± 0.52, and 2.9 ± 0.60) for all reduction factors (P <.05 for all). Conclusion: The MoDic method accelerates data acquisition for myocardial T1 mapping with improved T1 measurement accuracy. [ABSTRACT FROM AUTHOR]

Purpose: To develop a black blood heart‐rate adaptive T2‐prepared balanced steady‐state free‐precession (BEATS) sequence for myocardial T2 mapping. Methods: In BEATS, blood suppression is achieved by using a combination of preexcitation and double inversion recovery pulses. The timing and flip angles of the preexcitation pulse are auto‐calculated in each patient based on heart rate. Numerical simulations, phantom studies, and in vivo studies were conducted to evaluate the performance of BEATS. BEATS T2 maps were acquired in 36 patients referred for clinical cardiac MRI and in 1 swine with recent myocardial infarction. Two readers assessed all images acquired in patients to identify the presence of artifacts associated with slow blood flow. Results: Phantom experiments showed that the BEATS sequence provided accurate T2 values over a wide range of simulated heart rates. Black blood myocardial T2 maps were successfully obtained in all subjects. No significant difference was found between the average T2 measurements obtained from the BEATS and conventional bright‐blood T2; however, there was a decrease in precision using the BEATS sequence. A suppression of the blood pool resulted in sharper definition of the blood–myocardium border and reduced partial voluming effect. The subjective assessment showed that 16% (18 out of 108) of short‐axis slices have residual blood artifacts (12 in the apical slice, 4 in the midventricular slice, and 2 in the basal slice). Conclusion: The BEATS sequence yields dark blood myocardial T2 maps with better definition of the blood–myocardium border. Further studies are warranted to evaluate diagnostic accuracy of black blood T2 mapping. [ABSTRACT FROM AUTHOR]