Design,characterisation,and clinical evaluation of a novel porous Ti-6Al-4V hemipelvic prosthesis based on Voronoi diagram

Three-dimensional printed Ti-6Al-4V hemipelvic prosthesis has become a current popular method for pelvic defect reconstruction.This paper presents a novel biomimetic hemipelvic prosthesis design that utilises patient-specific anatomical data in conjunction with the Voronoi diagram algorithm.Unlike traditional design methods that rely on fixed,homogeneous unit cell,the Voronoi diagram enables to create imitation of trabecular structure(ITS).The proposed approach was conducted for six patients.The entire contour of the customised prosthesis matched well with the residual bone.The porosity and pore size of the ITS were evaluated.The distribution of the pore size ranged from 500 to 1400μm.Porosity calculations indicated the average porosity was 63.13±0.30%.Cubic ITS samples were fabricated for micrograph and mechanical analysis.Scanning electron microscopy images of the ITS samples exhibited rough surface morphology without obvious defects.The Young’s modulus and compressive strength were 1.68±0.05 GPa and 174±8 MPa,respectively.Post-operative X-rays confirmed proper matching of the customised prostheses with the bone defect.Tomosynthesis-Shimadzu metal artifact reduction technology images indicated close contact between the implant and host bone,alongside favourable bone density and absence of resorption or osteolysis around the implant.At the last follow-up,the average Musculoskeletal Tumour Society score was 23.2(range,21-26).By leveraging additive manufacturing and Voronoi diagram algorithm,customised implants tailored to individual patient anatomy can be fabricated,offering wide distribution of the pore size,reasonable mechanical properties,favourable osseointegration,and satisfactory function.

Direct Current Control Strategy of SVG Based on Dual Sequence dq Coordinates Under Asymmetric Load Condition

In the case of asymmetric loads of power grid,load currents are composed of four components:positive sequence active and reactive components and negative sequence active and reactive components that can pollute the power grid with harmonics and reactive power and interrupt the normal operation of power grid.Therefore,increasing numbers of static var generators(SVGs)are used to stabilize the power grid.In this study,a new type of current compensation control strategy of a three-phase three-wire SVG under an asymmetric load is proposed.According to the symmetric component method and dual dq synchronous transformation theory,the load currents are transformed into four components under dual dq coordinates.Each component is compensated separately by the SVG.Simultaneously,the proportional-limiter method is adopted to minimize the harmonics from the SVG by optimizing the waveform of the modulation wave and limiting its amplitude.Finally,the validity and feasibility of the control strategy are verified by simulation and experimental results.

A systematic analysis of diagnostic performance for Alzheimer’s disease using structural MRI

Background:Alzheimer’s disease(AD)is one of the most common neurodegenerative disorders in the elderly.Although numerous structural magnetic resonance imaging(sMRI)studies have reported diagnostic models that could distinguish AD from normal controls(NCs)with 80–95%accuracy,limited efforts have been made regarding the clinically practical computer-aided diagnosis(CAD)system for AD.Objective:To explore the potential factors that hinder the clinical translation of the AD-related diagnostic mod-els based on sMRI.Methods:To systematically review the diagnostic models for AD based on sMRI,we identified relevant studies published in the past 15 years on PubMed,Web of Science,Scopus,and Ovid.To evaluate the heterogeneity and publication bias among those studies,we performed subgroup analysis,meta-regression,Begg’s test,and Egger’s test.Results:According to our screening criterion,101 studies were included.Our results demonstrated that high diagnostic accuracy for distinguishing AD from NC was obtained in recently published studies,accompanied by significant heterogeneity.Meta-analysis showed that many factors contributed to the heterogeneity of high diagnostic accuracy of AD using sMRI,which included but was not limited to the following aspects:(i)different datasets;(ii)different machine learning models,e.g.traditional machine learning or deep learning model;(iii)different cross-validation methods,e.g.k-fold cross-validation leads to higher accuracies than leave-one-out cross-validation,but both overestimate the accuracy when compared to validation in independent samples;(iv)different sample sizes;and(v)the publication times.We speculate that these complicated variables might be the adverse factor for developing a clinically applicable system for the early diagnosis of AD.Conclusions:Our findings proved that previous studies reported promising results for classifying AD from NC with different models using sMRI.However,considering the many factors hindering clinical radiology practice,there would still be a long way to go to improve.