Preoperative Imaging for Thoracic Branch of Supraclavicular Artery Flap A Comparative Study of Contrast-Enhanced Ultrasound With Three-Dimensional Reconstruction and Color Duplex Ultrasound

Objective: The thoracic branch of supraclavicular artery (TBSA) flap has been widely used to reconstruct face and neck defects. However, the branches of the supraclavicular artery (SCA) exhibit considerable anatomical variations. The aim of this study was to evaluate and compare the role of contrast-enhanced ultrasound (CEUS) with 3-dimensional (3D) reconstruction and regular color duplex ultrasonography (CDUS) in the preoperative assessment of TBSA flap. Methods: From May 2009 to October 2013, 20 patients (involving 26 flaps) receiving anterior chest flaps for lower face and neck reconstruction underwent both CDUS and CEUS with 3D reconstruction preoperatively for detecting the TBSAs. The number of TBSAs, their caliber, peak systolic velocity (PSV), and course were recorded. In case of an absent TBSA, the second and third perforators of the internal mammary artery were detected. The preoperative imaging data were compared with the intraoperative findings to evaluate the value of CDUS and CEUS with 3D reconstruction for planning and performing the TBSA flaps. All patients were followed up for more than 1 year. Results: A total of 37 TBSAs in 16 flaps were found by CDUS with a mean caliber of 0.6 +/- 0.1 mm and a mean PSV of 13.1 +/- 1.6 cm/s, whereas 48 TBSAs in 20 flaps were found by CEUS with a mean caliber of 0.8 +/- 0.2 mm and a mean PSVof 12.5 +/- 2.1 cm/sec. In 18 flaps with TBSA PSV above 10 cm/s, pedicled TBSA flaps were performed, whereas pedicled or free internal mammary artery flaps were chosen as alternative for the remaining 8 flaps. All 48 TBSAs were found intraoperatively and their origin from the SCA confirmed, indicating specificity and positive predictive value of both CDUS and CEUS were 100% in localizing TBSA preoperatively, whereas sensitivity and negative predictive value of CEUS were higher than using CDUS. Conclusions: The branches of SCA have marked anatomical variations. CEUS with 3D reconstruction has advantages over CDUS for the preoperative assessment of the donor-site vascular supply of TBSA flaps

Adaptive parameter estimation-based observer design for nonlinear systems

Trabajo presentado en el IEEE Conference on Decision and Control (CDC), celebrado en Jeju (Corea del Sur) de forma virtual, del 14 al 18 de diciembre de 2020In this paper, alternative adaptive observers are developed for nonlinear systems to achieve state observation and parameter estimation of nonlinear systems simultaneously. The proposed observers are derived from the perspective of adaptive parameter estimation method, which leads to the reduced-order observers to deal with partially unknown system states and unknown parameters. To be specific, the nonlinear parametric function of unknown states to be identified is first transformed into a cascade form, which is linearly independent of unknown constant parameters. This transformation is achieved by finding an unmeasurable injective mapping function. Then, the functions related to measurable states are injected into a set of low- pass filters to derive the relationship between the mapping function and unknown parameters. In this line, the observer design problem is transformed into an equivalent parameter estimation problem. Consequently, we further exploit a recently proposed parameter estimation method that differs from the classical gradient descent algorithm to estimate the mapping function and unknown constant parameters. Finally, the unknown system states can be reconstructed by inverting this mapping function. A simulation example of DC-DC Cuk converter illustrates the effectiveness of proposed method

Adaptive parameter estimation-based observer design for nonlinear systems

© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other worksIn this paper, alternative adaptive observers are developed for nonlinear systems to achieve state observation and parameter estimation of nonlinear systems simultaneously. The proposed observers are derived from the perspective of adaptive parameter estimation method, which leads to the reduced-order observers to deal with partially unknown system states and unknown parameters. To be specific, the nonlinear parametric function of unknown states to be identified is first transformed into a cascade form, which is linearly independent of unknown constant parameters. This transformation is achieved by finding an unmeasurable injective mapping function. Then, the functions related to measurable states are injected into a set of lowpass filters to derive the relationship between the mapping function and unknown parameters. In this line, the observer design problem is transformed into an equivalent parameter estimation problem. Consequently, we further exploit a recently proposed parameter estimation method that differs from the classical gradient descent algorithm to estimate themapping function and unknown constant parameters. Finally, the unknown system states can be reconstructed by inverting this mapping function. A simulation example of DC-DC Cuk converter illustrates the effectiveness of proposed method.Peer ReviewedPostprint (author's final draft

Modeling and Parameter Identification of a 3D Measurement System Based on Redundant Laser Range Sensors for Industrial Robots

The low absolute positioning accuracy of industrial robots is one of the bottlenecks preventing industrial robots from precision applications. Kinematic calibration is the main way to improve the absolute positioning accuracy of industrial robots, which greatly relies on three-dimensional (3D) measurement instruments, including laser trackers and pull rope mechanisms. These instruments are costly, and their required intervisibility space is large. In this paper, a precision 3D measurement instrument integrating multiple laser range sensors is designed, which fuses the information of multiple redundant laser range sensors to obtain the coordinates of a 3D position. An identification model of laser beam position and orientation parameters based on redundant distance information and standard spherical constraint is then developed to reduce the requirement for the assembly accuracy of laser range sensors. A hybrid identification algorithm of PSO-LM (particle swarm optimization Levenberg Marquardt) is designed to solve the high-order nonlinear problem of the identification model, where PSO is used for initial value identification, and LM is used for final value identification. Experiments of identification of position and orientation, verifications of the measuring accuracy, and the calibration of industrial robots are conducted, which show the effectiveness of the proposed 3D measurement instrument and identification methods. Moreover, the proposed instrument is small in size and can be used in narrow industrial sites

Modeling and Parameter Identification of a 3D Measurement System Based on Redundant Laser Range Sensors for Industrial Robots

The low absolute positioning accuracy of industrial robots is one of the bottlenecks preventing industrial robots from precision applications. Kinematic calibration is the main way to improve the absolute positioning accuracy of industrial robots, which greatly relies on three-dimensional (3D) measurement instruments, including laser trackers and pull rope mechanisms. These instruments are costly, and their required intervisibility space is large. In this paper, a precision 3D measurement instrument integrating multiple laser range sensors is designed, which fuses the information of multiple redundant laser range sensors to obtain the coordinates of a 3D position. An identification model of laser beam position and orientation parameters based on redundant distance information and standard spherical constraint is then developed to reduce the requirement for the assembly accuracy of laser range sensors. A hybrid identification algorithm of PSO-LM (particle swarm optimization Levenberg Marquardt) is designed to solve the high-order nonlinear problem of the identification model, where PSO is used for initial value identification, and LM is used for final value identification. Experiments of identification of position and orientation, verifications of the measuring accuracy, and the calibration of industrial robots are conducted, which show the effectiveness of the proposed 3D measurement instrument and identification methods. Moreover, the proposed instrument is small in size and can be used in narrow industrial sites

Fine-needle aspiration for periprosthetic fluid removal after implantation of a remote internal-port tissue expander

Background: Use of internal filling ports in tissue expander–based reconstructions are advantageous because of easier self-care, lower infection rates, and fewer instances of capsule formation. The appearance of periprosthetic fluid accumulation after internal-port tissue expander implantation is a common complication that warrants treatment. In this study, we introduced a noninvasive method using fine-needle aspiration (FNA) to remove fluids accumulated after implantation of a remote internal-port tissue expander. Methods: In this study, 245 patients who underwent implantation of remote internal-port tissue expanders in our hospital from July 1, 2012, to July 1, 2019, were included and divided into two groups. In the control group, patients underwent tissue expander implantation before July 1, 2016, and large quantities of fluids were removed with surgical aspiration procedures in most cases. In the FNA group, the patients underwent implantation after July 1, 2016, and large quantities of fluids were removed first with the FNA procedure. Patients’ demographic data, indications for FNA application, and related complications were collected and analyzed. Results: Overall, 395 expanders were placed in 245 patients. Postoperative management was similar in both groups. Fluids were managed with 23 expanders in the control group and with 31 expanders in the FNA group. There was no difference in the fluid aspiration rate between the two groups. The surgical aspiration rate was 11.1% (23/208) in the control group. The success rate of FNA was 90.3% (28/31). In the FNA group, the surgical aspiration rate was 1.6% (3/187), which was significantly lower than that in the control group. There were no significant differences in complications between the two groups. Conclusion: FNA can be used for periprosthetic fluid removal after the implantation of a remote internal-port tissue expander in most cases. This method is more convenient and safer than surgical aspiration for the postoperative management of internal-port tissue expander implantation