Intra-articular patellar dislocation due to acute trauma is considered a rare presentation and is less commonly encountered in practice than extra-articular patellar dislocation. This case study presents a rare type 2...Intra-articular patellar dislocation due to acute trauma is considered a rare presentation and is less commonly encountered in practice than extra-articular patellar dislocation. This case study presents a rare type 2 inferior dislocation of the patella in an elderly patient which was successfully reduced and managed non-operatively.展开更多
BACKGROUND Artificial intelligence and deep learning have shown promising results in medical imaging and interpreting radiographs.Moreover,medical community shows a gaining interest in automating routine diagnostics i...BACKGROUND Artificial intelligence and deep learning have shown promising results in medical imaging and interpreting radiographs.Moreover,medical community shows a gaining interest in automating routine diagnostics issues and orthopedic measurements.AIM To verify the accuracy of automated patellar height assessment using deep learning-based bone segmentation and detection approach on high resolution radiographs.METHODS 218 Lateral knee radiographs were included in the analysis.82 radiographs were utilized for training and 10 other radiographs for validation of a U-Net neural network to achieve required Dice score.92 other radiographs were used for automatic(U-Net)and manual measurements of the patellar height,quantified by Caton-Deschamps(CD)and Blackburne-Peel(BP)indexes.The detection of required bones regions on high-resolution images was done using a You Only Look Once(YOLO)neural network.The agreement between manual and automatic measurements was calculated using the interclass correlation coefficient(ICC)and the standard error for single measurement(SEM).To check U-Net's generalization the segmentation accuracy on the test set was also calculated.RESULTS Proximal tibia and patella was segmented with accuracy 95.9%(Dice score)by U-Net neural network on lateral knee subimages automatically detected by the YOLO network(mean Average Precision mAP greater than 0.96).The mean values of CD and BP indexes calculated by orthopedic surgeons(R#1 and R#2)was 0.93(±0.19)and 0.89(±0.19)for CD and 0.80(±0.17)and 0.78(±0.17)for BP.Automatic measurements performed by our algorithm for CD and BP indexes were 0.92(±0.21)and 0.75(±0.19),respectively.Excellent agreement between the orthopedic surgeons’measurements and results of the algorithm has been achieved(ICC>0.75,SEM<0.014).CONCLUSION Automatic patellar height assessment can be achieved on high-resolution radiographs with the required accuracy.Determining patellar end-points and the joint line-fitting to the proximal tibia joint surface allows for accurate CD and BP index calculations.The obtained results indicate that this approach can be valuable tool in a medical practice.展开更多
Background:Impairments in hamstring strength,flexibility,and morphology have been associated with altered knee biomechanics,pain,and function.Determining the presence of these impairments in individuals with gradual-o...Background:Impairments in hamstring strength,flexibility,and morphology have been associated with altered knee biomechanics,pain,and function.Determining the presence of these impairments in individuals with gradual-onset knee disorders is important and may indicate targets for assessment and rehabilitation.This systematic review aimed to synthesize the literature to determine the presence of impairments in hamstring strength,flexibility,and morphology in individuals with gradual-onset knee disorders.Methods:Five databases(MEDLINE,Embase,CINAHL,SPORTDiscus,and Web of Science)were searched from inception to September 2022.Only studies comparing hamstring outcomes(e.g.,strength,flexibility,and/or morphology)between individuals with gradual-onset knee disorders and their unaffected limbs or pain-free controls were included.Meta-analyses for each knee disorder were performed.Outcome-level certainty was assessed using the Grading of Recommendations Assessment,Development,and Evaluation,and evidence gap maps were created.Results:Seventy-nine studies across 4 different gradual-onset knee disorders(i.e.,knee osteoarthritis(OA),patellofemoral pain(PFP),chondromalacia patellae,and patellar tendinopathy)were included.Individuals with knee OA presented with reduced hamstring strength compared to pain-free controls during isometric(standard mean difference(SMD)=-0.76,95%confidence interval(95%CI):-1.32 to-0.21)and concentric contractions(SMD=-0.97,95%CI:-1.49 to-0.45).Individuals with PFP presented with reduced hamstring strength compared to painfree controls during isometric(SMD=-0.48,95%CI:-0.82 to-0.14),concentric(SMD=-1.07,95%CI:-2.08 to-0.06),and eccentric contractions(SMD=-0.59,95%CI:-0.97 to-0.21).No differences were observed in individuals with patellar tendinopathy.Individuals with PFP presented with reduced hamstring flexibility when compared to pain-free controls(SMD=-0.76,95%CI:-1.15 to-0.36).Evidence gap maps identified insufficient evidence for chondromalacia patellae and hamstring morphology across all gradual-onset knee disorders.Conclusion:Our findings suggest that assessing and targeting impairments in hamstring strength and flexibility during rehabilitation may be recommended for individuals with knee OA or PFP.展开更多
文摘Intra-articular patellar dislocation due to acute trauma is considered a rare presentation and is less commonly encountered in practice than extra-articular patellar dislocation. This case study presents a rare type 2 inferior dislocation of the patella in an elderly patient which was successfully reduced and managed non-operatively.
文摘BACKGROUND Artificial intelligence and deep learning have shown promising results in medical imaging and interpreting radiographs.Moreover,medical community shows a gaining interest in automating routine diagnostics issues and orthopedic measurements.AIM To verify the accuracy of automated patellar height assessment using deep learning-based bone segmentation and detection approach on high resolution radiographs.METHODS 218 Lateral knee radiographs were included in the analysis.82 radiographs were utilized for training and 10 other radiographs for validation of a U-Net neural network to achieve required Dice score.92 other radiographs were used for automatic(U-Net)and manual measurements of the patellar height,quantified by Caton-Deschamps(CD)and Blackburne-Peel(BP)indexes.The detection of required bones regions on high-resolution images was done using a You Only Look Once(YOLO)neural network.The agreement between manual and automatic measurements was calculated using the interclass correlation coefficient(ICC)and the standard error for single measurement(SEM).To check U-Net's generalization the segmentation accuracy on the test set was also calculated.RESULTS Proximal tibia and patella was segmented with accuracy 95.9%(Dice score)by U-Net neural network on lateral knee subimages automatically detected by the YOLO network(mean Average Precision mAP greater than 0.96).The mean values of CD and BP indexes calculated by orthopedic surgeons(R#1 and R#2)was 0.93(±0.19)and 0.89(±0.19)for CD and 0.80(±0.17)and 0.78(±0.17)for BP.Automatic measurements performed by our algorithm for CD and BP indexes were 0.92(±0.21)and 0.75(±0.19),respectively.Excellent agreement between the orthopedic surgeons’measurements and results of the algorithm has been achieved(ICC>0.75,SEM<0.014).CONCLUSION Automatic patellar height assessment can be achieved on high-resolution radiographs with the required accuracy.Determining patellar end-points and the joint line-fitting to the proximal tibia joint surface allows for accurate CD and BP index calculations.The obtained results indicate that this approach can be valuable tool in a medical practice.
基金This work was supported by the Sao Paulo Research Foundation(FAPESP),which provided scholarships to HSL(Grant No.2021/09393-1)RVB(Grant No.2021/08644-0)and a research grant to FMA(Grant No.2020/14715-5).The financial sponsors played no role in the design,execution,analysis and interpretation of data,or the writing of the study。
文摘Background:Impairments in hamstring strength,flexibility,and morphology have been associated with altered knee biomechanics,pain,and function.Determining the presence of these impairments in individuals with gradual-onset knee disorders is important and may indicate targets for assessment and rehabilitation.This systematic review aimed to synthesize the literature to determine the presence of impairments in hamstring strength,flexibility,and morphology in individuals with gradual-onset knee disorders.Methods:Five databases(MEDLINE,Embase,CINAHL,SPORTDiscus,and Web of Science)were searched from inception to September 2022.Only studies comparing hamstring outcomes(e.g.,strength,flexibility,and/or morphology)between individuals with gradual-onset knee disorders and their unaffected limbs or pain-free controls were included.Meta-analyses for each knee disorder were performed.Outcome-level certainty was assessed using the Grading of Recommendations Assessment,Development,and Evaluation,and evidence gap maps were created.Results:Seventy-nine studies across 4 different gradual-onset knee disorders(i.e.,knee osteoarthritis(OA),patellofemoral pain(PFP),chondromalacia patellae,and patellar tendinopathy)were included.Individuals with knee OA presented with reduced hamstring strength compared to pain-free controls during isometric(standard mean difference(SMD)=-0.76,95%confidence interval(95%CI):-1.32 to-0.21)and concentric contractions(SMD=-0.97,95%CI:-1.49 to-0.45).Individuals with PFP presented with reduced hamstring strength compared to painfree controls during isometric(SMD=-0.48,95%CI:-0.82 to-0.14),concentric(SMD=-1.07,95%CI:-2.08 to-0.06),and eccentric contractions(SMD=-0.59,95%CI:-0.97 to-0.21).No differences were observed in individuals with patellar tendinopathy.Individuals with PFP presented with reduced hamstring flexibility when compared to pain-free controls(SMD=-0.76,95%CI:-1.15 to-0.36).Evidence gap maps identified insufficient evidence for chondromalacia patellae and hamstring morphology across all gradual-onset knee disorders.Conclusion:Our findings suggest that assessing and targeting impairments in hamstring strength and flexibility during rehabilitation may be recommended for individuals with knee OA or PFP.
