Computer Assisted Surgery最新文献

{"title":"A shape-partitioned statistical shape model for highly deformed femurs using X-ray images.","authors":"Jongho Chien,&nbsp;Ho-Gun Ha,&nbsp;Seongpung Lee,&nbsp;Jaesung Hong","doi":"10.1080/24699322.2022.2083016","DOIUrl":"https://doi.org/10.1080/24699322.2022.2083016","url":null,"abstract":"<p><p>To develop a patient-specific 3 D reconstruction of a femur modeled using the statistical shape model (SSM) and X-ray images, it is assumed that the target shape is not outside the range of variations allowed by the SSM built from a training dataset. We propose the shape-partitioned statistical shape model (SPSSM) to cover significant variations in the target shape. This model can divide a shape into several segments of anatomical interest. We break up the eigenvector matrix into the corresponding representative matrices for the SPSSM by preserving the relevant rows of the original matrix without segmenting the shape and building an independent SSM for each segment. To quantify the reconstruction error of the proposed method, we generated two groups of deformation models of the femur which cannot be easily represented by the conventional SSM. One group of femurs had an anteversion angle deformation, and the other group of femurs had two different scales of the femoral head. Each experiment was performed using the leave-one-out method for twelve femurs. When the femoral head was rotated by 30°, the average reconstruction error of the conventional SSM was 5.34 mm, which was reduced to 3.82 mm for the proposed SPSSM. When the femoral head size was decreased by 20%, the average reconstruction error of the SSM was 4.70 mm, which was reduced to 3.56 mm for the SPSSM. When the femoral head size was increased by 20%, the average reconstruction error of the SSM was 4.28 mm, which was reduced to 3.10 mm for the SPSSM. The experimental results for the two groups of deformation models showed that the proposed SPSSM outperformed the conventional SSM.</p>","PeriodicalId":56051,"journal":{"name":"Computer Assisted Surgery","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10639060","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bias in machine learning for computer-assisted surgery and medical image processing.","authors":"John S H Baxter,&nbsp;Pierre Jannin","doi":"10.1080/24699322.2021.2013619","DOIUrl":"https://doi.org/10.1080/24699322.2021.2013619","url":null,"abstract":"","PeriodicalId":56051,"journal":{"name":"Computer Assisted Surgery","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39898788","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Corrective osteotomy for complex tibial deformity in a patient with hereditary vitamin D-resistant hypophosphatemic rickets (HVDRR) using CT-based navigation system and 3D printed osteotomy model.","authors":"Masatoshi Oba,&nbsp;Hyonmin Choe,&nbsp;Shunsuke Yamada,&nbsp;Yuto Gondai,&nbsp;Koki Abe,&nbsp;Taro Tezuka,&nbsp;Hiroyuki Ike,&nbsp;Yutaka Inaba","doi":"10.1080/24699322.2022.2086485","DOIUrl":"https://doi.org/10.1080/24699322.2022.2086485","url":null,"abstract":"<p><p>Planning a three-dimensional (3D) osteotomy using computed tomography (CT) data is useful especially in cases with complex deformities. Furthermore, CT-based navigation system allows the preoperative virtual planning to be replicated in actual surgery. However, one disadvantage when using navigation systems is that when osteotomies are performed on tracker-attached bone, the bone fragments on the side that were cut away cannot be tracked. This is especially problematic when performing multiple osteotomies on bones with complex deformities. We solved this problem by creating a 3D printed bone model that can be referenced intraoperatively and used in combination with the navigation system. We applied these techniques to perform segmental corrective osteotomy for a complex tibial deformity with intramedullary nail (IMN) fixation case of hereditary vitamin D-resistant hypophosphatemic rickets (HVDRR) in an adult man. Due to the patient's history of multiple surgeries, the affected tibia had a narrow and partially closed medullary canal. Therefore, we planned to use an IMN for correction and fixation of tibial deformity to protect the thin and stretched skin around the deformed tibia. With the assistance of CT-based navigation, we could perform an accurate three-dimensional tibial osteotomy. Moreover, we could perform accurate preparation of closed medullary canal for the IMN placement by referring to the 3D printed bone models. Six months after the operation, the bone union at the osteotomy sites was confirmed and the patient was able to return to his normal life and work.</p>","PeriodicalId":56051,"journal":{"name":"Computer Assisted Surgery","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40122420","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effect of image-guided systems in phacoemulsification with intraocular lens (IOL) implantation: a systematic review and meta-analysis.","authors":"Yang Su,&nbsp;Min Fu,&nbsp;Yifan Chen,&nbsp;Rui Qiao,&nbsp;Guo-Guo Yi","doi":"10.1080/24699322.2022.2047787","DOIUrl":"https://doi.org/10.1080/24699322.2022.2047787","url":null,"abstract":"<p><strong>Purpose: </strong>To explore the effect of image-guided systems in phacoemulsification with intraocular lens (IOL) implantation.</p><p><strong>Methods: </strong>We searched Pubmed, Embase and China National Knowledge Infrastructure (inception to January 20, 2021). Two researchers extracted data and assessed paper quality independently. Uncorrected distance visual acuity (UDVA) before and after surgery, best corrected visual acuity (BCVA) before and after surgery, preoperative cylinder, postoperative residual refractive cylinder, postoperative corneal cylinder, IOL misalignment, and intraocular pressure (IOP) were compared.</p><p><strong>Results: </strong>We included 14 studies with 885 cataract eyes. All data were performed using Review Manager 5.3 (RevMan 5.3) (https://revman.cochrane.org/). Cases of all preoperative outcomes showed no significant difference between image-guided group and manual group. There was no significant difference in postoperative UDVA (Standard mean difference (SMD: -0.11, 95% CI: -0.32 to 0.11, <i>I</i>² = 59%, <i>p</i> = 0.33)), BCVA (SMD: 0.03, 95% CI: -0.12 to 0.18, <i>I</i>² = 36%, <i>p</i> = 0.72), corneal cylinder (Weighted mean difference WMD: 0.13, 95% CI: -0.06 to -0.32, <i>I</i>² = 0%, <i>p</i> = 0.17), IOP (WMD: -0.37, 95% CI: -1.36 to -0.62, <i>I</i>² = 9%, <i>p</i> = 0.46) between two groups. There was less residual refractive cylinder in image-guided group than in manual group (WMD: -0.20, 95% CI: -0.26 to -0.14, <i>I</i>² = 59%, <i>p</i>＜0.00001). It is more accurate in IOL alignment when combined with image-guided systems (WMD: -1.20, 95% CI: -1.43 to -0.96, <i>I</i>² = 14%, <i>p</i> < 0.00001).</p><p><strong>Conclusion: </strong>Image-guided systems can improve the effect in phacoemulsification with intraocular lens (IOL) implantation.</p>","PeriodicalId":56051,"journal":{"name":"Computer Assisted Surgery","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40310658","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparison of computer-assisted navigated technology and conventional technology in high tibial osteotomy (HTO): a meta-analysis.","authors":"Keteng Xu,&nbsp;Weichao Wang,&nbsp;Qin Wang,&nbsp;Jun Sun,&nbsp;Chen Fang,&nbsp;Yusheng Sun,&nbsp;Tulong Shi,&nbsp;Xun Wu,&nbsp;Qing Yan","doi":"10.1080/24699322.2022.2078739","DOIUrl":"https://doi.org/10.1080/24699322.2022.2078739","url":null,"abstract":"<p><strong>Background: </strong>Though some studies have reported navigated high tibial osteotomy (HTO) is a useful procedure to correct knee deformity. There is still great controversy whether navigated HTO can achieve better accuracy of limb alignment and greater clinical outcomes. Current meta-analysis was conducted to investigate whether better radiographic outcomes and clinical outcomes could be acquired in navigated HTO compared with the conventional procedure.</p><p><strong>Method: </strong>We conducted a literature search in the electronic databases, including Medline, Embase, the Cochrane Library, and Web of Science. We identified studies published before August 2020. We also checked the references of the related articles for any relevant studies. We strictly followed the Preferred Reporting Items for Systematics reviews and Meta-Analysis (PRISMA) guidelines in this review. This research was performed using Review Manager 5.4 software.</p><p><strong>Results: </strong>Fourteen articles were included, involving 1399 knees. Our meta-analysis indicated that patients undergoing navigated HTO had significantly better outcomes in outliers of aimed limb alignment (RD=-0.24, 95% CI: =-0.34 to -0.13, <i>p</i> < 0.01), outliers of aimed tibial posterior slope (TPS) (RD=-0.41, 95% CI: -0.51 to -0.30, <i>p</i> < 0.01), Range of Motion (ROM) (MD = 6.37, 95%CI: 0.83-11.91, <i>p</i> = 0.02), and American knee society knee score (AKS knee score) (MD = 3.88, 95%CI: 1.37-6.39, <i>p</i> = 0.002). No significant differences were found in Lysholm score (MD = 1.30, 95%CI: -0.31 to 2.90, <i>p</i> = 0.11), American knee society function score (AKS function score) (RD = 1.42, 95%CI: -0.15 to 2.99, <i>p</i> = 0.08), complications (RD=-0.01, 95% CI: = -0.05 to 0.04, <i>p</i> = 0.77), delayed union (RD=-0.01, 95% CI: = -0.02 to 0.03, <i>p</i> = 0.59), and reoperation (RD = 0, 95% CI: -0.09 to 0.10, <i>p</i> = 0.98) between the two groups. The operation time in the navigated group was 15.46 min longer than in the conventional group.</p><p><strong>Conclusion: </strong>Navigated HTO provided more accurate and reproducible radiographic outcomes in the correction of the malalignment than conventional techniques, and there is no difference in the risk of complications compared with conventional HTO. However, it is unclear whether navigation HTO can achieve better clinical results. More randomized controlled trials (RCTs) with high quality, large sample size, and sufficient follow-up period are required.</p>","PeriodicalId":56051,"journal":{"name":"Computer Assisted Surgery","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40540155","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Tibial component rotation alters soft tissue balance in a cruciate retaining total knee arthroplasty","authors":"G. Clark, M. Quinn, J. Murgier, D. Wood","doi":"10.1080/24699322.2022.2078738","DOIUrl":"https://doi.org/10.1080/24699322.2022.2078738","url":null,"abstract":"Abstract Our aim was to understand whether using different landmarks for tibial component rotation influenced articular contact pressures in a balanced total knee arthroplasty (TKA). Twelve patients underwent TKA (Triathlon CR, Stryker Inc., Mahwah, NJ) and contact pressures were assessed using a wireless sensor. Robotic arm assisted TKA using a functional alignment technique was performed, with balanced gaps between medial and lateral compartments. Compartment pressures were measured with the trial tibial component rotated to Akagi's line and to Insall's axis respectively. Rotating the tibial component to Akagi's line resulted in a significantly greater proportion of knees being balanced and lower contact pressures than when the tibial component was rotated to Insall's axis at 10°, 45° and 90° of flexion (p < 0.05). Medial compartment pressures were significantly increased in 10° of flexion, as were lateral compartment pressures in all positions when the tibial component was aligned to Insall's axis (p < 0.05). The mean difference in rotation observed with the two landmarks was 6.9° (range 4.1–9.1°). Rotational alignment of the tibial component using Akagi's line reduced contact pressures, improved balance and reduced the need for soft tissue release when compared with Insall's axis in robotic arm assisted TKA.","PeriodicalId":56051,"journal":{"name":"Computer Assisted Surgery","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42933436","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dimensional accuracy of TKA cut surfaces with an active robotic system","authors":"S. Kreuzer, A. Brar, V. Campanelli","doi":"10.1080/24699322.2022.2080116","DOIUrl":"https://doi.org/10.1080/24699322.2022.2080116","url":null,"abstract":"Abstract This is a study of the dimensional accuracy of the bone cut surfaces in robotic TKA. One surgeon performed robotic TKA on four cadaveric knees. A novel technique was developed for measuring the dimensional accuracy of both the femoral and tibial cut surfaces. CT scans were used to create a pre-operative plan and generate nominal cut surfaces on the 3D bone model. After TKA, the cut surfaces were then laser scanned. Two femoral components were also scanned and compared to nominal dimensions. Flatness was computed as the standard deviation between each of the cut surfaces and the best-fit plane. The angles between the five femoral best-fit planes were compared to the nominal values. The point-to-point distances between the femoral cut surfaces and the nominal cut planes were computed to estimate the bone-to-implant gap. The cut surfaces had an average flatness of 0.16 ± 0.06 mm with low variability between different cut planes. The femoral cut surfaces had average angular errors of 0.47 ± 0.39°, which are of similar magnitude as the errors found for the implants. The bone-to-implant gap was within ±1 mm for 97.9% of the surface on average. Using a novel methodology, the dimensional accuracy of an active robotic system for TKA was found to be very high for both the femoral and tibial bone cuts. Comparison studies are needed with other robotic systems as well as studies comparing manual and robotic techniques.","PeriodicalId":56051,"journal":{"name":"Computer Assisted Surgery","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2022-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44754199","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimal definitions for computing HKA angle in caos: an in-vitro comparison study","authors":"G. Dardenne, B. Borotikar, H. Letissier, A. Zemirline, E. Stindel","doi":"10.1080/24699322.2022.2066023","DOIUrl":"https://doi.org/10.1080/24699322.2022.2066023","url":null,"abstract":"Abstract The goal of this study was to assess and compare the precision and accuracy of nine and seven methods usually used in Computer Assisted Orthopedic Surgery (CAOS) to estimate respectively the Knee Center (KC) and the Frontal Plane (FP) for the determination of the HKA angle (HKAA). An in-vitro experiment has been realized on thirteen cadaveric lower limbs. A CAOS software application was developed and allowed the computation of the HKAA according to these nine KC and seven FP methods. The precision and the accuracy of the HKAA measurements were measured. The HKAA precision was highest when the FP is determined using the helical method. The HKAA accuracy was highest using the helical approach to determine the FP and either the notch or the tibial spines to determine the KC. This study shows that the helical approach to determine the FP and either the notch or the middle of tibia spines are the combinations that provide both a good enough accuracy and precision to estimate the HKA.","PeriodicalId":56051,"journal":{"name":"Computer Assisted Surgery","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2022-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48667374","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deep learning for assessing liver fibrosis based on acoustic nonlinearity maps: an in vivo study of rabbits","authors":"Jinzhen Song, Hao Yin, Jianbo Huang, Zhenru Wu, Chenchen Wei, Tingting Qiu, Yan Luo","doi":"10.1080/24699322.2022.2063760","DOIUrl":"https://doi.org/10.1080/24699322.2022.2063760","url":null,"abstract":"Abstract This study aimed to assess liver fibrosis in rabbits by deep learning models based on acoustic nonlinearity maps. Injection of carbon tetrachloride was used to induce liver fibrosis. Acoustic nonlinearity maps, which were built by data of echo signals, were used as input data for deep learning model. Convolutional neural network (CNN), CNN combined with support vector machine (SVM), CNN combined with random forest and CNN combined with logistic regression were used as deep learning model. Nested 10-fold cross-validation was used to search hyperparameters and evaluate performance of models. Histologic examination of liver specimens of the rabbits was performed to evaluate the fibrosis stage. Receiver operator characteristic curve and area under curve (AUC) were used for estimating the probability of the correct prediction of liver fibrosis stages. A total of 600 acoustic nonlinearity maps were used. Model of CNN combined with SVM demonstrated the best diagnostic performance compared with all other methods for diagnosis of significant fibrosis (≥F2, AUC = 0.82), advanced fibrosis (≥F3, AUC = 0.88) and cirrhosis (F4, AUC = 0.90). Model of CNN showed the second highest AUCs. The deep learning model based on acoustic nonlinearity maps demonstrated potential for evaluation of liver fibrosis.","PeriodicalId":56051,"journal":{"name":"Computer Assisted Surgery","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2022-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"60126434","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing perioperative landmark detection during sacroiliac joint fusion in patients suffering from low back pain.","authors":"Bas Schippers,&nbsp;Edsko Hekman,&nbsp;Sven van Helden,&nbsp;Martijn Boomsma,&nbsp;Jochen van Osch,&nbsp;Robert Nijveldt","doi":"10.1080/24699322.2021.1916600","DOIUrl":"https://doi.org/10.1080/24699322.2021.1916600","url":null,"abstract":"<p><p>Over the past decade, minimally invasive sacroiliac joint (SIJ) fusion has become an effective treatment for patients suffering from low back pain (LBP) originating from the SIJ. Perioperative C-arm fluoroscopy-assisted surgical navigation during SIJ fusion remains challenging due to the lack of 3D spatial information. This study developed and assessed a 3D CT/2D fluoroscopy integration approach based on digitally reconstructed radiographs (DRRs) obtained from pre-operative CT scans. Development of this approach proved feasible and landmarks were successfully translated, in retrospect, to perioperatively acquired fluoroscopies. Further expansion of and research into the proposed approach to increase perioperative navigation is indicated and additional validation should be performed.</p>","PeriodicalId":56051,"journal":{"name":"Computer Assisted Surgery","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/24699322.2021.1916600","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38953997","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}