Contrast-enhanced ultrasound guided core needle biopsy for soft tissue tumors: Accuracy and applicability.

OBJECTIVE: To evaluate the effectiveness of contrast-enhanced ultrasound (CEUS) guided core needle biopsy (CNB) in diagnosing soft tissue tumors (STTs) and to identify the conventional ultrasonography (US) features of STTs that are recommended for CEUS-guided CNB. MATERIALS AND METHODS: A retrospective study was conducted on 123 patients with surgically confirmed STTs. Before surgeries, all subjects underwent CNB under the guidance of US or CEUS. The histopathological results of surgical specimens were considered as the gold standards. A successful biopsy diagnosis was defined as the pathological subtypes obtained by biopsy consistent with the gold standard. The diagnostic yields were compared between the US and CEUS groups, and the diagnostic yields based on various conventional US features of STTs were also compared between the two groups. RESULTS: Sixty-seven cases underwent US-guided CNB and fifty-six cases underwent CEUS-guided CNB. The clinical, biopsy, and conventional US characteristics revealed no significant difference between the two groups. The diagnostic yield of the CEUS group was statistically higher than that of the US group (p = 0.011). In the CEUS group, more STTs with the anechoic areas were identified after CEUS examination (p = 0.031). Furthermore, the diagnostic yields based on the conventional US features of STTs, including deep fascia layer (p = 0.010), a maximum diameter ≥5 cm (p = 0.037), rough margin (p = 0.016), heterogeneous echotexture (p = 0.017), and absence of anechoic area (p = 0.013), were significantly different between the two groups, and the CEUS group exhibited higher diagnostic yields. CONCLUSION: CEUS-guided CNB was found to be an efficient method for STTs diagnosis. It is particularly recommended for STTs with the following conventional US features, including location in deep fascia layer, a maximum diameter ≥5 cm, rough margin, heterogeneous echotexture, or absence of anechoic area.

Non-contact heart rate estimation based on singular spectrum component reconstruction using low-rank matrix and autocorrelation.

The remote photoplethysmography (rPPG) based on cameras, a technology for extracting pulse wave from videos, has been proved to be an effective heart rate (HR) monitoring method and has great potential in many fields; such as health monitoring. However, the change of facial color intensity caused by cardiovascular activities is weak. Environmental illumination changes and subjects' facial movements will produce irregular noise in rPPG signals, resulting in distortion of heart rate pulse signals and affecting the accuracy of heart rate measurement. Given the irregular noises such as motion artifacts and illumination changes in rPPG signals, this paper proposed a new method named LA-SSA. It combines low-rank sparse matrix decomposition and autocorrelation function with singular spectrum analysis (SSA). The low-rank sparse matrix decomposition is employed to globally optimize the components of the rPPG signal obtained by SSA, and some irregular noise is removed. Then, the autocorrelation function is used to optimize the global optimization results locally. The periodic components related to the heartbeat signal are selected, and the denoised rPPG signal is obtained by weighted reconstruction with a singular value ratio. The experiment using UBFC-RPPG and PURE database is performed to assess the performance of the method proposed in this paper. The average absolute error was 1.37 bpm, the 95% confidence interval was -7.56 bpm to 6.45 bpm, and the Pearson correlation coefficient was 98%, superior to most existing video-based heart rate extraction methods. Experimental results show that the proposed method can estimate HR effectively.

Identification of three novel pathogenic mutations in sarcomere genes associated with familial hypertrophic cardiomyopathy based on multi-omics study.

BACKGROUND: Familial hypertrophic cardiomyopathy (HCM) is a leading cause of sudden cardiac death, but exhibits heterogeneous clinical features. A major research focus is to identify specific ultrasonic phenotypes, and causal gene mutations, as well as to elucidate the possible metabolic pathogenic effects in familial HCM through multi-omics study. METHODS: Nine members of two familial HCM pedigrees were enrolled in this study. Their clinical data were collected, and the data of multiparameter ultrasound, whole-exome sequencing, and untargeted metabolomics were analyzed. RESULTS: We identified three novel pathogenic sarcomere gene mutations, TNNT2-rs397516484, MYH6-rs372446459 and MYBPC3-rs786204339 in two familial HCM pedigrees. The proband of Family 1 and his father carried TNNT2-rs397516484 and MYH6-rs372446459 missense mutations, while the proband of Family 2 and her brother carried MYBPC3-rs786204339 frameshift mutation. They presented with heart failure and abnormal electrocardiogram, accompanied by diastolic and systolic dysfunction and impaired myocardial work. They also showed disturbances of carbohydrate metabolism, including the citrate cycle (TCA cycle), glycolysis/gluconeogenesis, fructose and mannose metabolism, pentose and glucuronate interconversions and amino sugar and nucleotide sugar metabolism. CONCLUSIONS: Novel TNNT2-rs397516484, MYH6-rs372446459, and MYBPC3-rs786204339 are pathogenic sarcomere gene mutations in familial HCM, leading to decreased cardiac function and metabolic disturbances of carbohydrate metabolism, which have important implications for biologically defined diagnoses and precision medicine.