Virtual reduction is crucial for successful and accurate reduction of pelvic fractures.Various methods have been proposed in this regard.However,not all of them are applicable to every pelvic fracture.Among these meth...Virtual reduction is crucial for successful and accurate reduction of pelvic fractures.Various methods have been proposed in this regard.However,not all of them are applicable to every pelvic fracture.Among these methods,the efficiency and accuracy of the method based on statistical shape models in clinical applications require further improvement.This study proposes a virtual reduction method for pelvic fractures that uses statistical shape models and partial surface data of a broken pelvis.Simulated fracture and clinical case experiments were conducted to validate the accuracy and effectiveness of the proposed method.The simulated fracture experiments yielded an average error of 1.57±0.39 mm and a maximum error of 12.82±3.54 mm.The virtual reduction procedure takes approximately 40 s.Based on three clinical case experiments,the proposed method achieves an acceptable level of accuracy compared with manual reduction by a surgeon.The proposed method offers the advantages of shorter virtual reduction times and satisfactory reduction accuracy.In the future,it will be integrated into the preoperative planning system for pelvic fracture reduction,thereby improving patient outcomes.展开更多
Skull structures are important for biomechanical head simulations,but they are mostly reconstructed frommedical images.These reconstruction methods harmthe human body and have a long processing time.Currently,skull st...Skull structures are important for biomechanical head simulations,but they are mostly reconstructed frommedical images.These reconstruction methods harmthe human body and have a long processing time.Currently,skull structures canbe straightforwardly predictedfromthe head,but a fullheadshapemust be available.Most scanning devices can only capture the face shape.Consequently,a method that can quickly predict the full skull structures from the face is necessary.In this study,a novel face-to-skull prediction procedure is introduced.Given a threedimensional(3-D)face shape,a skull mesh could be predicted so that its shape would statistically fit the face shape.Several prediction strategies were conducted.The optimal prediction strategy with its optimal hyperparameters was experimentally selected through a ten-fold cross-validation with 329 subjects.As a result,the face-to-skull prediction strategy based on the relations between face head shape and back head shape,between face head shape and face skull shape,and between back head shape and back skull shape was optimal.The optimal mean mesh-to-mesh distance(mean±SD)between the predicted skull shapes and the ground truth skull shapes was 1.93±0.36 mm,and those between the predicted skull meshes and the ground truth skull meshes were 2.65±0.36 mm.Moreover,the prediction errors in back-skull and muscle attachment regions were 1.7432±0.5217 mm and 1.7671±0.3829 mm,respectively.These errors are within the acceptable range of facial muscle simulation.In perspective,this method will be employed in our clinical decision support system to enhance the accuracy of biomechanical head simulation based on a stereo fusion camera system.Moreover,we will also enhance the accuracy of the face-to-skull prediction by diversifying the dataset intomore varied geographical regions and genders.More types of parameters,such as BodyMass Index(BMI),coupled with head-to-skull thicknesses,will be fused with the proposed face-to-skull procedure.展开更多
Lumbar degeneration leads to changes in geometry and density distribution of vertebrae,which could further influence the mechanical property and behavior.This study aimed to quantitatively describe the variations in s...Lumbar degeneration leads to changes in geometry and density distribution of vertebrae,which could further influence the mechanical property and behavior.This study aimed to quantitatively describe the variations in shape and density distribution for degenerated vertebrae by statistical models,and utilized the specific statistical shape model(SSM)/statistical appearance model(SAM)modes to assess compressive strength and fracture behavior.Highly detailed SSM and SAM were developed based on the 75 L1 vertebrae of elderly men,and their variations in shape and density distribution were quantified with principal component(PC)modes.All vertebrae were classified into mild(n=22),moderate(n=29),and severe(n=24)groups according to the overall degree of degeneration.Quantitative computed tomography-based finite element analysis was used to calculate compressive strength for each L1 vertebra,and the associations between compressive strength and PC modes were evaluated by multivariable linear regression(MLR).Moreover,the distributions of equivalent plastic strain(PEEQ)for the vertebrae assigned with the first modes of SSM and SAM at mean±3SD were investigated.The Leave-One-Out analysis showed that our SSM and SAM had good performance,with mean absolute errors of 0.335±0.084 mm and 64.610±26.620 mg/cm3,respectively.A reasonable accuracy of bone strength prediction was achieved by using four PC modes(SSM 1,SAM 1,SAM 4,and SAM 5)to construct the MLR model.Furthermore,the PEEQ values were more sensitive to degeneration-related variations of density distribution than those of morphology.The density variations may change the deformity type(compression deformity or wedge deformity),which further affects the fracture pattern.Statistical models can identify the morphology and density variations in degenerative vertebrae,and the SSM/SAM modes could be used to assess compressive strength and fracture behavior.The above findings have implications for assisting clinicians in pathological diagnosis,fracture risk assessment,implant design,and preoperative planning.展开更多
Background： The conventional method cannot guarantee the precise osteotomies required for a perfect realignment and a better prognosis after total knee arthroplasty （TKA）.This study investigated a customized guide ...Background： The conventional method cannot guarantee the precise osteotomies required for a perfect realignment and a better prognosis after total knee arthroplasty （TKA）.This study investigated a customized guide plate for osteotomy placement in TKAs with the aid of the statistical shape model technique using weight-bearing lower-extremity X-rays and computed tomography （CT） images of the knee.Methods： From October 2014 to June 2015, 42 patients who underwent a TKA in Guizhou Provincial People＆#39;s Hospital were divided into a guide plate group （GPG, 21 cases） and a traditional surgery group （TSG, 21 cases） using a random number table method.In the GPG group, a guide plate was designed and printed using preoperative three-dimensional measurements to plan and digitally simulate the operation.TSG cases were treated with the conventional method.Outcomes were obtained from the postoperative image examination and short-term follow-up.Results： Operative time was 49.0 ＆#177; 10.5 min for GPG, and 62.0 ＆#177; 9.7 min in TSG.The coronal femoral angle, coronal tibial angle, posterior tibial slope, and the angle between the posterior condylar osteotomy surface and the surgical transepicondylar axis were 89.2 ＆#177; 1.7＆#176;, 89.0 ＆#177; 1.1＆#176;, 6.6 ＆#177; 1.4＆#176;, and 0.9 ＆#177; 0.3＆#176; in GPG, and 86.7 ＆#177; 2.9＆#176;, 87.6 ＆#177; 2.1＆#176;, 8.9 ＆#177; 2.8＆#176;, and 1.7 ＆#177; 0.8＆#176; in TSG, respectively.The Hospital for Special Surgery scores 3 months after surgery were 83.7 ＆#177; 18.4 in GPG and 71.5 ＆#177; 15.2 in TSG.Statistically significant differences were found between GPG and TSG in all measurements.Conclusions： A customized guide plate to create an accurate osteotomy in TKAs may be created using lower-extremity X-ray and knee CT images.This allows for shorter operative times and better postoperative alignment than the traditional surgery.Application of the digital guide plate may also result in better short-term outcomes.展开更多
基金supported by the National Key Research and Development Program of China(2020YFB1313800)the Key Research and Development Program of Shandong Province,China(2022CXGC020510).
文摘Virtual reduction is crucial for successful and accurate reduction of pelvic fractures.Various methods have been proposed in this regard.However,not all of them are applicable to every pelvic fracture.Among these methods,the efficiency and accuracy of the method based on statistical shape models in clinical applications require further improvement.This study proposes a virtual reduction method for pelvic fractures that uses statistical shape models and partial surface data of a broken pelvis.Simulated fracture and clinical case experiments were conducted to validate the accuracy and effectiveness of the proposed method.The simulated fracture experiments yielded an average error of 1.57±0.39 mm and a maximum error of 12.82±3.54 mm.The virtual reduction procedure takes approximately 40 s.Based on three clinical case experiments,the proposed method achieves an acceptable level of accuracy compared with manual reduction by a surgeon.The proposed method offers the advantages of shorter virtual reduction times and satisfactory reduction accuracy.In the future,it will be integrated into the preoperative planning system for pelvic fracture reduction,thereby improving patient outcomes.
基金funded by the International University,VNU-HCM,under grant number T2023-01-BME.
文摘Skull structures are important for biomechanical head simulations,but they are mostly reconstructed frommedical images.These reconstruction methods harmthe human body and have a long processing time.Currently,skull structures canbe straightforwardly predictedfromthe head,but a fullheadshapemust be available.Most scanning devices can only capture the face shape.Consequently,a method that can quickly predict the full skull structures from the face is necessary.In this study,a novel face-to-skull prediction procedure is introduced.Given a threedimensional(3-D)face shape,a skull mesh could be predicted so that its shape would statistically fit the face shape.Several prediction strategies were conducted.The optimal prediction strategy with its optimal hyperparameters was experimentally selected through a ten-fold cross-validation with 329 subjects.As a result,the face-to-skull prediction strategy based on the relations between face head shape and back head shape,between face head shape and face skull shape,and between back head shape and back skull shape was optimal.The optimal mean mesh-to-mesh distance(mean±SD)between the predicted skull shapes and the ground truth skull shapes was 1.93±0.36 mm,and those between the predicted skull meshes and the ground truth skull meshes were 2.65±0.36 mm.Moreover,the prediction errors in back-skull and muscle attachment regions were 1.7432±0.5217 mm and 1.7671±0.3829 mm,respectively.These errors are within the acceptable range of facial muscle simulation.In perspective,this method will be employed in our clinical decision support system to enhance the accuracy of biomechanical head simulation based on a stereo fusion camera system.Moreover,we will also enhance the accuracy of the face-to-skull prediction by diversifying the dataset intomore varied geographical regions and genders.More types of parameters,such as BodyMass Index(BMI),coupled with head-to-skull thicknesses,will be fused with the proposed face-to-skull procedure.
基金supported by the National Natural Science Foundation of China(Grant No.12272029).
文摘Lumbar degeneration leads to changes in geometry and density distribution of vertebrae,which could further influence the mechanical property and behavior.This study aimed to quantitatively describe the variations in shape and density distribution for degenerated vertebrae by statistical models,and utilized the specific statistical shape model(SSM)/statistical appearance model(SAM)modes to assess compressive strength and fracture behavior.Highly detailed SSM and SAM were developed based on the 75 L1 vertebrae of elderly men,and their variations in shape and density distribution were quantified with principal component(PC)modes.All vertebrae were classified into mild(n=22),moderate(n=29),and severe(n=24)groups according to the overall degree of degeneration.Quantitative computed tomography-based finite element analysis was used to calculate compressive strength for each L1 vertebra,and the associations between compressive strength and PC modes were evaluated by multivariable linear regression(MLR).Moreover,the distributions of equivalent plastic strain(PEEQ)for the vertebrae assigned with the first modes of SSM and SAM at mean±3SD were investigated.The Leave-One-Out analysis showed that our SSM and SAM had good performance,with mean absolute errors of 0.335±0.084 mm and 64.610±26.620 mg/cm3,respectively.A reasonable accuracy of bone strength prediction was achieved by using four PC modes(SSM 1,SAM 1,SAM 4,and SAM 5)to construct the MLR model.Furthermore,the PEEQ values were more sensitive to degeneration-related variations of density distribution than those of morphology.The density variations may change the deformity type(compression deformity or wedge deformity),which further affects the fracture pattern.Statistical models can identify the morphology and density variations in degenerative vertebrae,and the SSM/SAM modes could be used to assess compressive strength and fracture behavior.The above findings have implications for assisting clinicians in pathological diagnosis,fracture risk assessment,implant design,and preoperative planning.
文摘Background： The conventional method cannot guarantee the precise osteotomies required for a perfect realignment and a better prognosis after total knee arthroplasty （TKA）.This study investigated a customized guide plate for osteotomy placement in TKAs with the aid of the statistical shape model technique using weight-bearing lower-extremity X-rays and computed tomography （CT） images of the knee.Methods： From October 2014 to June 2015, 42 patients who underwent a TKA in Guizhou Provincial People＆#39;s Hospital were divided into a guide plate group （GPG, 21 cases） and a traditional surgery group （TSG, 21 cases） using a random number table method.In the GPG group, a guide plate was designed and printed using preoperative three-dimensional measurements to plan and digitally simulate the operation.TSG cases were treated with the conventional method.Outcomes were obtained from the postoperative image examination and short-term follow-up.Results： Operative time was 49.0 ＆#177; 10.5 min for GPG, and 62.0 ＆#177; 9.7 min in TSG.The coronal femoral angle, coronal tibial angle, posterior tibial slope, and the angle between the posterior condylar osteotomy surface and the surgical transepicondylar axis were 89.2 ＆#177; 1.7＆#176;, 89.0 ＆#177; 1.1＆#176;, 6.6 ＆#177; 1.4＆#176;, and 0.9 ＆#177; 0.3＆#176; in GPG, and 86.7 ＆#177; 2.9＆#176;, 87.6 ＆#177; 2.1＆#176;, 8.9 ＆#177; 2.8＆#176;, and 1.7 ＆#177; 0.8＆#176; in TSG, respectively.The Hospital for Special Surgery scores 3 months after surgery were 83.7 ＆#177; 18.4 in GPG and 71.5 ＆#177; 15.2 in TSG.Statistically significant differences were found between GPG and TSG in all measurements.Conclusions： A customized guide plate to create an accurate osteotomy in TKAs may be created using lower-extremity X-ray and knee CT images.This allows for shorter operative times and better postoperative alignment than the traditional surgery.Application of the digital guide plate may also result in better short-term outcomes.
