Background The left atrial strain and strain rate in patients with myocardial infarction (MI) were measured using the cardiac magnetic resonance tissue tracking (CMR-TT) technique, and its usefulness in the quantitative assessment of myocardial infarction for differentiating between acute and chronic myocardial infarction was assessed. Methods Consecutive 36 AMI patients and 29 CMI patients who underwent CMR were retrospectively analyzed as well as 30 controls. By analyzing the strain from long and short left ventricular view cines from CMR-TT, the left atrial and ventricular functions were measured. Receiver operating characteristic(ROC) analysis was used to test the diagnostic accuracy of the CMR-TT strain parameters in distinguishing acute from chronic myocardial infarction. Results Participants in both AMI and CMI demonstrated decreased LA reservoir function, conduit function, and LA booster pump dysfunction as compared to the controls. The LA strain was more sensitive than the LV global strain for determining the stage of MI. Of all the LA strain parameters measured, SRa produced the best areas under the ROC curve (AUC) of 0.879 in demonstrating distinction between acute and chronic myocardial infarction. The LV strain and LA functional parameters showed the largest significant differences between chronic myocardial infarction and normal (P < 0.001, respectively), while there was no difference between AMI and normals. Conclusions CMR-TT-derived LA strain is a promising and robust tool for demonstrating impaired LA mechanics and quantifying LA dynamics, both of which have high sensitivity and specificity in the differential diagnosis of acute versus chronic myocardial infarction, and their use in clinical application is thus worth promoting.

Background The cardiac magnetic resonance tissue tracking (CMR-TT) technique was used to obtain left atrial strain and strain rate in patients with myocardial infarction (MI) and to evaluate the utility of this technique in the quantitative assessment of myocardial infarction for distinguishing acute from chronic myocardial infarction. Methods We retrospectively analyzed 36 consecutive patients with acute myocardial infarction (AMI) and 29 patients with chronic myocardial infarction (CMI) who underwent CMR and 30 controls. Left atrial (LA) and ventricular functions were quantified by volumetric, and CMR-TT derived strain analysis from long and short left ventricular view cines. Receiver Operating Characteristics (ROC) analysis was used to determine the diagnostic accuracy of CMR-TT strain parameters for discriminating between acute and chronic myocardial infarction. Results AMI and CMI participants had impaired LA reservoir function, conduit function and LA booster pump dysfunction compared to the controls. LA strain was more sensitive than LV global strain for the assessment of the MI stage. Peak late-negative SR yielded the best areas under the ROC curve (AUC) of 0.879, showing differentiation between acute and chronic myocardial infarction of all the LA strain parameters obtained. The highest significant differences between chronic myocardial infarction and normal myocardium were also found in the LV strain (p < 0.001) and LA functional parameters (p < 0.001), but there was no difference between AMI and normals. Conclusions CMR-TT-derived LA strain is a potential and robust tool in demonstrating impaired LA mechanics and quantifying LA dynamics, which have high sensitivity and specificity in the differential diagnosis of acute versus chronic myocardial infarction. Their use is thus worth popularizing in clinical application.

With the rapid growth of multimodal media data on the Web in recent years, hash learning methods as a way to achieve efficient and flexible cross-modal retrieval of massive multimedia data have received a lot of attention from the current Web resource retrieval research community. Existing supervised hashing methods simply transform label information into pairwise similarity information to guide hash learning, leading to a potential risk of semantic error in the face of multi-label data. In addition, most existing hash optimization methods solve NP-hard optimization problems by employing approximate approximation strategies based on relaxation strategies, leading to a large quantization error. In order to address above obstacles, we present a simple yet efficient Adaptive Asymmetric Label-guided Hashing, named A2LH, for Multimedia Search. Specifically, A2LH is a two-step hashing method. In the first step, we design an association representation model between the different modality representations and semantic label representation separately, and use the semantic label representation as an intermediate bridge to solve the semantic gap existing between different modalities. In addition, we present an efficient discrete optimization algorithm for solving the quantization error problem caused by relaxation-based optimization algorithms. In the second step, we leverage the generated hash codes to learn the hash mapping functions. The experimental results show that our proposed method achieves optimal performance on all compared baseline methods.