Identification of fibrosis in hypertrophic cardiomyopathy: a radiomic study on cardiac magnetic resonance cine imaging.

OBJECTIVES: Hypertrophic cardiomyopathy (HCM) often requires repeated enhanced cardiac magnetic resonance (CMR) imaging to detect fibrosis. We aimed to develop a practical model based on cine imaging to help identify patients with high risk of fibrosis and screen out patients without fibrosis to avoid unnecessary injection of contrast. METHODS: A total of 273 patients with HCM were divided into training and test sets at a ratio of 7:3. Logistic regression analysis was used to find predictive image features to construct CMR model. Radiomic features were derived from the maximal wall thickness (MWT) slice and entire left ventricular (LV) myocardium. Extreme gradient boosting was used to build radiomic models. Integrated models were established by fusing image features and radiomic models. The model performance was validated in the test set and assessed by ROC and calibration curve and decision curve analysis (DCA). RESULTS: We established five prediction models, including CMR, R1 (based on the MWT slice), R2 (based on the entire LV myocardium), and two integrated models (ICMR+R1 and ICMR+R2). In the test set, ICMR+R2 model had an excellent AUC value (0.898), diagnostic accuracy (89.02%), sensitivity (92.54%), and F1 score (93.23%) in identifying patients with positive late gadolinium enhancement. The calibration plots and DCA indicated that ICMR+R2 model was well-calibrated and presented a better net benefit than other models. CONCLUSIONS: A predictive model that fused image and radiomic features from the entire LV myocardium had good diagnostic performance, robustness, and clinical utility. KEY POINTS: • Hypertrophic cardiomyopathy is prone to fibrosis, requiring patients to undergo repeated enhanced cardiac magnetic resonance imaging to detect fibrosis over their lifetime follow-up. • A predictive model based on the entire left ventricular myocardium outperformed a model based on a slice of the maximal wall thickness. • A predictive model that fused image and radiomic features from the entire left ventricular myocardium had excellent diagnostic performance, robustness, and clinical utility.

A Risk Score to Diagnose Cardiac Involvement and Provide Prognosis Information in Patients at Risk of Cardiac Light-Chain Amyloidosis.

Background: Cardiac light-chain amyloidosis (AL CA) portends poor prognosis. Contrast cardiac magnetic resonance (CMR) with late gadolinium enhancement (LGE) imaging is an important tool in recognizing AL CA. But contraindications to contrast CMR would significantly restrict its clinical application value. Our study aims to construct a convenient risk score to help identify cardiac involvement in patients at risk of AL CA. Moreover, we also investigate whether this risk score could provide prognosis information. Materials and Methods: Sixty-three patients at risk of AL CA were retrospectively included in our study. Basic clinical characters, lab results, 12-lead electrocardiogram data, and cardiac magnetic resonance image data were collected. AL CA was diagnosed according to typical CA LGE pattern. Logistic analysis was used to figure out predictive parameters of AL CA and their ß coefficients, further constructing the risk score. Receiver operating characteristics (ROC) curve was used to find the cut-off point best distinguishing AL CA+ from AL CA-patients. Bootstrapping was used for internal validation. All patients were divided into high-risk and low-risk group according to the diagnostic cut-off point, and followed up for survival information. Kaplan-Meier plots and log-rank test were performed to analyze if this score had prognostic value. Results: The risk score finally consisted of 4 parameters: pericardial effusion (PE) (1 point), low electrocardiographic QRS voltages (LQRSV) (1 point), CMR-derived impaired global radial strain (GRS) (<15.14%) (1 point) and increased left ventricular maximum wall thickness (LVMWT) (>13 mm) (2 points). Total score ranged from 0 to 5 points. A cut-off point of 1.5 showed highest accuracy in diagnosing AL CA with an AUC of 0.961 (95% CI: 0.924-0.997, sensitivity: 90.6%, specificity: 83.9%). Kaplan-Meier plots and log-rank test showed that the high-risk group had significantly poor overall survival rates. Conclusion: In patients at risk of AL CA, a risk score incorporating the presence of PE, LQRSV, and CMR-derived impaired GRS and increased LVMWT is predictive of a diagnosis of AL CA by LGE criteria. This risk score may be helpful especially when contrast CMR is not available or contraindicated, and further studies should be considered to validate this score.

Radiological insights of ectopic thyroid in the porta hepatis: A case report and review of the literature.

BACKGROUND: Ectopic thyroid is defined as a rare developmental anomaly where thyroid tissues are atypically found in locations other than its normal anatomical position: Anterolateral to the second, third, and fourth tracheal cartilages. An intemperate descent or a migration failure of the thyroid anlage results in sub-diaphragmatic thyroid ectopia, a sparse clinical entity. CASE SUMMARY: This case portrays a 63-year-old female patient presenting with chronic abdominal discomfort at a local hospital whereby a computed tomography (CT) scan revealed a well-defined mass in the hepatic entrance. For further examination, the patient underwent a CT scan with contrast, magnetic resonance imaging (MRI), and CT-angiography (CTA) at our department. The CT scan showed a well-defined and high attenuated mass measuring 43 mm × 38 mm in the hepatic entrance with calcification. The CTA revealed an additional finding: Blood supply to the mass from the right hepatic artery. MRI of the upper abdomen demonstrated a mass with mixed signal intensity on T1 and T2 weighted images in the hepatic entrance. The patient underwent surgery with resection of the mass which was sent for histopathology. Ectopic thyroid at the level of porta hepatis with nodules was the definitive diagnosis since histopathological report revealed presence of thyroid tissue in the resected liver mass. CONCLUSION: This case delivers a rare insight of pre-operative radiological imaging of an ectopic thyroid located in the liver. These findings can aid in narrowing down potential differential diagnosis when managing a patient with those subsequent findings.

Global Circumferential Strain by Cardiac Magnetic Resonance Tissue Tracking Associated With Ventricular Arrhythmias in Hypertrophic Cardiomyopathy Patients.

Background: Hypertrophic cardiomyopathy (HCM) is prone to myocardial heterogeneity and fibrosis, which are the substrates of ventricular arrhythmias (VAs). Cardiac magnetic resonance tissue tracking (CMR-TT) can quantitatively reflect global and regional left ventricular strain from different directions. It is uncertain whether the change of myocardial strain detected by CMR-TT is associated with VAs. The aim of the study is to explore the differential diagnostic value of VAs in HCM by CMR-TT. Materials and Methods: We retrospectively included 93 HCM patients (38 with VAs and 55 without VAs) and 30 healthy cases. Left ventricular function, myocardial strain parameters and percentage of late gadolinium enhancement (%LGE) were evaluated. Results: Global circumferential strain (GCS) and %LGE correlated moderately (r = 0.51, P < 0.001). HCM patients with VAs had lower left ventricular ejection fraction (LVEF), global radial strain (GRS), GCS, and global longitudinal strain (GLS), but increased %LGE compared with those without VAs (P < 0.01 for all). %LGE and GCS were indicators of VAs in HCM patients by multivariate logistic regression analysis. HCM patients with %LGE >5.35% (AUC 0.81, 95% CI 0.70-0.91, P < 0.001) or GCS >-14.73% (AUC 0.79, 95% CI 0.70-0.89, P < 0.001) on CMR more frequently had VAs. %LGE + GCS were able to better identify HCM patients with VAs (AUC 0.87, 95% CI 0.79-0.95, P < 0.001). Conclusion: GCS and %LGE were independent risk indicators of VAs in HCM. GCS is expected to be a good potential predictor in identifying HCM patients with VAs, which may provide important values to improve risk stratification in HCM in clinical practice.