There are several kinds of PICC tip positioning method in clinic at present,including body surface measurement, X-ray tip location, ultrasound guided assisted positioning and venous ECG. The limitations of former three methods were that the physical structure of the individual differences may affect the results of surface measurement accuracy; the differences of visual and subjective judgment may exist between different observers and the patient may easy to be affected by X-ray radiation; B ultrasound guidance assisted positioning can not show the whole process, and some of the central vein in the discount or too deep in the catheter tip can not be judged. The localization of the P wave in the center of the tube was observed by the technique of the intra cavity ECG localization to judge the position of the catheter tip, which can be positioned in a timely manner in order to reduce the risks caused by incorrect position of the catheter tip, avoid postoperative X-ray radiation and readjust the tube, reduce the cost of inspection. This study summarizes the PICC tip localization method, the principle, advantage, stability, influence factor and the method of improving the stability of the electrocardiogram.

Objective To observe the value of ultrasound vector flow imaging(VFI)combined with singular value decomposition(SVD)filtering for depicting deep microvasculature flow velocity of liver.Methods Grayscale ultrasound,CDFI and contrast-enhanced ultrasound(CEUS)were prospectively performed in a patient with suspected liver hemangioma.Images of CEUS were dealt with SVD filtering.Cross-correlation algorithm was used to obtain images of VFI based on grayscale ultrasound,original CEUS and SVD filtered CEUS,respectively,and the ability of the above images for depicting liver microvascular flow direction and velocity were compared.Results The signal-to-noise ratio(SNR)of liver grayscale ultrasound,original CEUS and SVD filtered CEUS images was 7.56,17.65 and 22.43 dB,respectively,while their contrast-to-issue ratio(CTR)was 1.12,7.56 and 16.34 dB,respectively.Compared with VFI based on grayscale ultrasound and original CEUS,VFI based on SVD filtered CEUS could display faster velocity and more uniform direction of blood flow.Before and after SVD filtering,liver microvascular flow velocity measured with VFI was 1.91(0.81,4.11)and 6.83(4.25,9.41)mm/s,respectively,which were significantly different(Z=-10.671,P＜0.001).Conclusion Combined with SVD filtering could significantly improve the efficiency of VFI for depicting liver deep microvasculature flow velocity.

Objective:To explore the application value of singular value decomposition(SVD)in optimizing the image quality of contrast-enhanced ultrasound(CEUS)and perioperative CEUS assessment of microwave ablation(MWA)for thyroid nodule.Methods:The data sets of two-dimensional ultrasound and CEUS images of two patients with thyroid nodules,who underwent MWA in China Resources&Wisco General Hospital affiliated to Wuhan University of Science and Technology from April 2023,were collected.The contrast images based on CEUS images after SVD filtering were obtained according to the normalized cross-correlation algorithm,and the differences of signal-to-noise ratio(SNR)and micro-vessel density(MVD)between the contrast images after SVD filtering and original CEUS images were compared.Results:Compared with the original CEUS images of thyroid nodules before and after MWA,the contrast images that were processed by SVD filtering can more clearly show the vascular structure with thyroid nodules,and can detect more signals of blood flow.The results showed that the average SNR of the original CEUS images after operation was(1.07±0.66)dB,and the average SNR of the contrast images by SVD filtering after operation was(6.21±1.01)dB(t=-6.015,P=0.038).The average MVD of the original CEUS images after operation was(0.60±0.33)%,and the average MVD of the contrast images of SVD filtering after operation was(5.42±0.67)%(t=-9.076,P=0.029).It can show that the SNR and MVD of the contrast images of SVD-filtering after operation were significantly higher than these of the original CEUS images after operation,and the results of these studies were significant.Conclusion:SVD filtering can effectively suppress noise and enhance the signals of micro-blood flow.The improved quality of contrast images can be used in the accurate diagnosis of perioperative MWA of thyroid nodules,it can sensitively detect the residually incomplete areas of ablation after operation,so as to guide clinicians to carry out more thorough ablation treatment and provide decision support for the assessment of curative effect of accurate ablation.

Objective To observe the feasibility of Fourier ring correlation(FRC)for measuring the overall resolution of ultrasonic microvascular images.Methods Liver contrast-enhanced ultrasound(CEUS)images of 1 patient with suspected hepatic hemangioma(dataset 1)were processed with singular value decomposition(SVD)filter(dataset 2)and Frangi filter(dataset 3),respectively.Three ROI were selected on CEUS image in each dataset,and the signal-intensity curves were drawn,and local resolution of CEUS image in each dataset was measured using full width at half maxima(FWHM)method.Then the above datasets were divided into odd frame subset and even frame subset,respectively,which were converted into frequency domain using fast Fourier transform.FRC curves were generated to calculate the overall resolution of each kind images.Results The signal-to-noise ratio(SNR)of CEUS images in dataset 1,2,3 was(19.94±2.33),(30.36±0.78)and(69.52±16.38)dB,respectively,the local resolution was(4.07±9.82),(1.53±0.04)and(1.27±0.06)mm,both successively increased(all P＜0.05).The overall resolution of CEUS images in dataset 1,2,3 was 2.07,0.91 and 0.51 mm,respectively.Conclusion FRC was feasible for measuring the overall resolution of ultrasonic microvascular images.

Objective To observe the effect of extracting different speed contrast-enhanced ultrasound(CEUS)signals using singular value decomposition filtering and implementing fused imaging for improving visualization of microvascular structures.Methods Singular value decomposition and filtering were performed on 200 frames of mouse subcutaneous tumor and 250 frames of human liver CEUS image datasets.The singular value inflection point was used as the threshold for separating low-speed and high-speed contrast signals by exponential projection of singular values on the singular value sequence.The low-speed and high-speed signals in dataset were extracted,and dual-modal fusion imaging was performed on the processed images.The image resolution differences of ultrasound microvascular imaging regions with different flow velocities were evaluated.Results The high-speed blood flow images processed by the high singular value sequence range retained the fast-moving contrast signals which mainly showed the thicker blood vessel structures,while the low-speed blood flow images processed by the low singular value sequence range retained the low-speed moving contrast signals which reflected the microvascular structures on high singular value images.The fusion imaging displayed microvascular network more completely.Conclusion Appropriate selection of singular value range was crucial to optimization of CEUS images using singular value decomposition filtering.Fusion imaging was beneficial to improving visualization of microvascular structures.