Radiographic Assessment of Bone Quality Using 4 Radiographic Indexes: Canal Diaphysis Ratio Is Superior.

BACKGROUND: Osteoporosis increases the risk of periprosthetic fracture and loosening in hip arthroplasty. Many methods have been proposed to assess bone quality in X-rays, including both qualitative such as the Dorr classification and quantitative such as the Calcar-Canal Ratio (CCR) and Cortical-Thickness index/Canal-Bone ratio (CTI/CBR). The Canal-Diaphysis ratio (CDR) has been described as a predictor for hip fragility fractures; however, its relationship with bone mineral density (BMD) has not been described. The purpose of this study was to evaluate the correlation of the Dorr classification, CCR, CTI/CBR, and CDR with BMD of the proximal femur in patients without hip fracture. METHODS: Forty-seven patients over 45 years of age who had less than 6 months between radiographs and dual-energy X-ray absorptiometry were evaluated. Measurements of CCR, CBR, CDR, and Dorr classification were performed in all radiographs by 2 independent observers. RESULTS: The CDR had a high correlation (r = 0.74, P=<0.01) with BMD, whereas the CTI/CBR had a moderate correlation (r = 0.49, P=<0.01), and the CCR had no correlation with BMD (r = 0.06, P = .96). When evaluating the receiver operating characteristic curve, CDR showed the best performance (area under curve [AUC] = 0.75) followed by CBR (AUC = 0.73) and CCR (AUC = 0.61). The optimal cutoff value for the CDR was 0.49, with 100% sensitivity and 58% specificity. The inter- and intra-observer variability was good for all methods. No differences were found between Dorr classification of patients who had or did not have osteoporosis. CONCLUSION: Of all the analyzed methods, the CDR was found to have the best correlation with BMD. This study proposes the use of CDR as a tool for assessing bone quality when deciding the implant fixation method in hip arthroplasty.

Traction images heavily influence lateral wall measurement in trochanteric hip fractures. A prospective study.

INTRODUCTION: hip fracture represents a global health problem, with a high morbidity and mortality rate and an increasing incidence. The treatment of trochanteric fractures is reduction and osteosynthesis, and implant selection depends mainly on the stability of the fracture and lateral wall competence. Lateral wall competence has gained relevance in recent years, which led to the modification of the AO/OTA classification. However, determination of lateral wall integrity is difficult from plain radiographs; the influence of images with traction on its measurement has not been evaluated. METHODS: prospective concordance study, emergency and post-traction radiographs of 65 patients with trochanteric fracture were evaluated by six orthopedic surgeons independently, measuring the lateral wall, classifying the fracture according to the AO/OTA 2018 classification and selecting the implant for osteosynthesis. A comparison of incompetent to intact lateral wall proportion between each image set was made. Secondary outcomes were the inter-observer correlation of lateral wall measurement and inter-observer agreement of classification and implant choice. RESULTS: the proportion of patients with an incompetent lateral wall in emergency x-ray was 37.43% (CI 95% 0.326-0.422), while the proportion in post-traction fluoroscopy was 15% (CI 95% 0.115-0.185), with a statistically significant difference (p < 0.001). 40.1% of patients with an incompetent lateral wall changed to an intact one. Inter-observer correlation for the lateral wall thickness was 0.399 (CI 95% 0.292-0.519) in emergency x-ray and 0.658 (CI 95% 0.564-0.748) in post-traction fluoroscopy, with a substantial agreement. Inter-observer agreement for the fracture classification was fair to moderate using emergency x-ray (κ 0.369 95%CI 0.330-0.408) and fair to moderate with post-traction fluoroscopy (κ 0.400, 95% CI 0.334-0.466). CONCLUSION: traction images significantly change the measurement of the lateral wall in trochanteric fractures, changing from an incompetent to a competent wall in 40% of patients. The correct classification of trochanteric fractures is crucial to make the best decision when deciding which implant to use, and the measurement of the lateral wall is determinant in the actual AO/OTA classification. Therefore, traction images appear as necessary for correct decision-making.

The Río Hortega University Hospital Glioblastoma dataset: A comprehensive collection of preoperative, early postoperative and recurrence MRI scans (RHUH-GBM).

Glioblastoma, a highly aggressive primary brain tumor, is associated with poor patient outcomes. Although magnetic resonance imaging (MRI) plays a critical role in diagnosing, characterizing, and forecasting glioblastoma progression, public MRI repositories present significant drawbacks, including insufficient postoperative and follow-up studies as well as expert tumor segmentations. To address these issues, we present the "Río Hortega University Hospital Glioblastoma Dataset (RHUH-GBM)," a collection of multiparametric MRI images, volumetric assessments, molecular data, and survival details for glioblastoma patients who underwent total or near-total enhancing tumor resection. The dataset features expert-corrected segmentations of tumor subregions, offering valuable ground truth data for developing algorithms for postoperative and follow-up MRI scans.

Predicting Regions of Local Recurrence in Glioblastomas Using Voxel-Based Radiomic Features of Multiparametric Postoperative MRI.

The globally accepted surgical strategy in glioblastomas is removing the enhancing tumor. However, the peritumoral region harbors infiltration areas responsible for future tumor recurrence. This study aimed to evaluate a predictive model that identifies areas of future recurrence using a voxel-based radiomics analysis of magnetic resonance imaging (MRI) data. This multi-institutional study included a retrospective analysis of patients diagnosed with glioblastoma who underwent surgery with complete resection of the enhancing tumor. Fifty-five patients met the selection criteria. The study sample was split into training (N = 40) and testing (N = 15) datasets. Follow-up MRI was used for ground truth definition, and postoperative structural multiparametric MRI was used to extract voxel-based radiomic features. Deformable coregistration was used to register the MRI sequences for each patient, followed by segmentation of the peritumoral region in the postoperative scan and the enhancing tumor in the follow-up scan. Peritumoral voxels overlapping with enhancing tumor voxels were labeled as recurrence, while non-overlapping voxels were labeled as nonrecurrence. Voxel-based radiomic features were extracted from the peritumoral region. Four machine learning-based classifiers were trained for recurrence prediction. A region-based evaluation approach was used for model evaluation. The Categorical Boosting (CatBoost) classifier obtained the best performance on the testing dataset with an average area under the curve (AUC) of 0.81 ± 0.09 and an accuracy of 0.84 ± 0.06, using region-based evaluation. There was a clear visual correspondence between predicted and actual recurrence regions. We have developed a method that accurately predicts the region of future tumor recurrence in MRI scans of glioblastoma patients. This could enable the adaptation of surgical and radiotherapy treatment to these areas to potentially prolong the survival of these patients.

Estudio clínico, radiológico y derivación en tumores musculoesqueléticos / Diagnosis and referral of musculoskeletal tumors

Musculoskeletal tumors are uncommon. However, the true burden of all bone and soft tissue tumors of extremities is underestimated. Usually, the diagnosis of sarcomas is missed or delayed. Therefore, an adequate clinical and radiological assessment, along with the awareness and application of simple guidelines for referral to a specialized center, are of utmost importance. These are critical steps for an appropriate diagnosis and treatment of sarcomas, improving their prognosis.

Six Commonly Used Postoperative Radiographic Alignment Parameters Do Not Predict Clinical Outcome Scores after Unrestricted Caliper-Verified Kinematically Aligned TKA.

BACKGROUND: Unrestricted caliper-verified kinematically aligned (KA) TKA restores patient's prearthritic coronal and sagittal alignments, which have a wide range containing outliers that concern the surgeon practicing mechanical alignment (MA). Therefore, knowing which radiographic parameters are associated with dissatisfaction could help a surgeon decide whether to rely on them as criteria for revising an unhappy patient with a primary KA TKA using MA principles. Hence, we determined whether the femoral mechanical angle (FMA), hip-knee-ankle angle (HKAA), tibial mechanical angle (TMA), tibial slope angle (TSA), and the indicators of patellofemoral tracking, including patella tilt angle (PTA) and the lateral undercoverage of the trochlear resection (LUCTR), are associated with clinical outcome scores. METHODS: Forty-three patients with a CT scan and skyline radiograph after a KA TKA with PCL retention and medial stabilized design were analyzed. Linear regression determined the strength of the association between the FMA, HKA angle, PTS, PTA, and LUCTR and the forgotten joint score (FJS), Oxford knee score (OKS), and KOOS Jr score obtained at a mean of 23 months. RESULTS: There was no correlation between the FMA (range 2° varus to -10° valgus), HKAA (range 10° varus to -9° valgus), TMA (range 10° varus to -0° valgus), TSA (range 14° posterior to -4° anterior), PTA (range, -10° medial to 14° lateral), and the LUCTR resection (range 2 to 9 mm) and the FJS (median 83), the OKS (median 44), and the KOOS Jr (median 85) (r = 0.000 to 0.079). CONCLUSIONS: Surgeons should be cautious about using postoperative FMA, HKAA, TMA, TSA, PTA, and LUCTR values within the present study's reported ranges to explain success and dissatisfaction after KA TKA.

Inter- and intra-observer agreement using the new AOSpine sacral fracture classification, with a comparison between spine and pelvic trauma surgeons.

BACKGROUND: Sacral fractures treatment frequently involves both spine and pelvic trauma surgeons; therefore, a consistent communication among surgical specialists is required. We independently assessed the new AOSpine sacral fracture classification's agreement from the perspective of spine and pelvic trauma surgeons. METHODS: Complete computerized tomography (CT) scans of 80 patients with sacral fractures were selected and classified using the new AOSpine sacral classification system by six spine surgeons and three pelvic trauma surgeons. After four weeks, the 80 cases were presented and reassessed by the same raters in a new random sequence. The Kappa coefficient (κ) was used to measure the inter-and intra-observer agreement. RESULTS: The inter-observer agreement considering the fracture severity types (A, B, or C) was substantial for spine surgeons (κ= 0.68 [0.63 - 0.72]) and pelvic trauma surgeons (κ= 0.74 (0.64 - 0.84). Regarding the subtypes, both groups achieved moderate agreement with κ= 0.52 (0.49 - 0.54) for spine surgeons and κ= 0.51 (0.45 - 0.57) for pelvic trauma surgeons. The intra-observer agreement considering the fracture types was substantial for spine surgeons (κ= 0.74 [0.63 - 0.75]) and almost perfect for pelvic trauma surgeons (κ= 0.84 [0.74 - 0.93]). Concerning the subtypes, both groups achieved substantial agreement with, κ= 0.61 (0.56 - 0.67) for spine surgeons and κ= 0.68 (0.62 - 0.74) for pelvic trauma surgeons. CONCLUSION: This classification allows an adequate communication for spine surgeons and pelvic trauma surgeons at the fracture severity type, but the agreement is only moderate at the subtype level. Future prospective studies are required to evaluate whether this classification allows for treatment recommendations and establishing prognosis in patients with sacral fractures.

[Diagnosis and referral of musculoskeletal tumors]. / Estudio clínico, radiológico y derivación en tumores musculoesqueléticos.

Musculoskeletal tumors are uncommon. However, the true burden of all bone and soft tissue tumors of extremities is underestimated. Usually, the diagnosis of sarcomas is missed or delayed. Therefore, an adequate clinical and radiological assessment, along with the awareness and application of simple guidelines for referral to a specialized center, are of utmost importance. These are critical steps for an appropriate diagnosis and treatment of sarcomas, improving their prognosis.

Which Asymmetric Tibial Component Is Optimally Designed for Calipered Kinematically Aligned Total Knee Arthroplasty?

Calipered kinematically aligned (KA) total knee arthroplasty (TKA) restores the patient's prearthritic joint lines and sets internal-external rotation of the tibial component parallel to the flexion-extension (FE) plane, which is not a mechanical alignment (MA) target. Two asymmetric tibial components designed for MA set the tibial component to either a femoral component (FC) target or a tibial tubercle (TT) target. The study determined the optimal asymmetric tibial component to use with KA as the one with smaller IE deviation from the MA target, greater coverage of tibial resection, and lower incidence of cortical overhang. The study included 40 patients treated with bilateral calipered KA TKA with different asymmetric tibial components in opposite knees. A best-fit of a kinematic tibial template to the tibial resection set the template's slot parallel to the knee's FE plane. Each asymmetric tibial component's anterior-posterior (AP) axis was set parallel to the slot. Computer tomography analysis determined the IE deviation (-internal/+ external) of each tibial component from its MA target, tibial resection coverage by the baseplate and insert, and incidence of cortical overhang. The patient-reported Forgotten Joint Score (FJS) and Oxford Knee Score (OKS) determined outcomes. The mean IE deviation from the MA target was 2 degrees external for the FC-target asymmetric tibial component and -8 degrees internal for the TT-target asymmetric tibial component (p < 0.001). Tibial resection coverage by the baseplate (insert) was 88% (84%) for the FC target and 84% (79%) for the TT target (p < 0.001 for baseplate and insert). The FC target insert covered 3 mm more of the posterolateral resection (p < 0.001). Posteromedial coverage was comparable. The incidence of cortical overhang was 2.5% for each baseplate. There was no difference in FJS and OKS. When performing calipered KA, the more optimal design was the asymmetric tibial component with the FC target because of the smaller deviation from its MA target and the greater coverage of the tibial resection by the baseplate and insert.

Predicting Short-Term Survival after Gross Total or Near Total Resection in Glioblastomas by Machine Learning-Based Radiomic Analysis of Preoperative MRI.

Radiomics, in combination with artificial intelligence, has emerged as a powerful tool for the development of predictive models in neuro-oncology. Our study aims to find an answer to a clinically relevant question: is there a radiomic profile that can identify glioblastoma (GBM) patients with short-term survival after complete tumor resection? A retrospective study of GBM patients who underwent surgery was conducted in two institutions between January 2019 and January 2020, along with cases from public databases. Cases with gross total or near total tumor resection were included. Preoperative structural multiparametric magnetic resonance imaging (mpMRI) sequences were pre-processed, and a total of 15,720 radiomic features were extracted. After feature reduction, machine learning-based classifiers were used to predict early mortality (<6 months). Additionally, a survival analysis was performed using the random survival forest (RSF) algorithm. A total of 203 patients were enrolled in this study. In the classification task, the naive Bayes classifier obtained the best results in the test data set, with an area under the curve (AUC) of 0.769 and classification accuracy of 80%. The RSF model allowed the stratification of patients into low- and high-risk groups. In the test data set, this model obtained values of C-Index = 0.61, IBS = 0.123 and integrated AUC at six months of 0.761. In this study, we developed a reliable predictive model of short-term survival in GBM by applying open-source and user-friendly computational means. These new tools will assist clinicians in adapting our therapeutic approach considering individual patient characteristics.

Hip Fractures in the Elderly During the COVID-19 Pandemic: A Latin-American Perspective With a Minimum 90-Day Follow-Up.

INTRODUCTION: Hip fracture patients have been severely affected by the COVID-19 pandemic; however, the sub acute effects of a concomitant SARS-CoV-2 infection and the outcomes in highly exposed developing countries are still unknown. Our objective is to describe the morbidity and mortality of elderly patients admitted for a hip fracture during the COVID-19 pandemic in Chile, with a minimum 90-day follow-up. Also, to elucidate predictors for mortality and to compare mortality results with the pre-pandemic era. MATERIAL AND METHODS: Multicentric retrospective review of patients admitted for a fragility hip fracture in 3 hospitals during the COVID-19 pandemic, and during the same time in 2019. All clinical information and images were recorded, and patients were followed for a minimum of 90-days. Morbidity and mortality were the primary outcomes. Uni/multivariable models were performed to elucidate predictors for mortality utilizing the Weibull's regression. RESULTS: Three hundred ninety-one cases were included. From the 2020 cohort (162 patients), 24 (15%) had a concomitant SARS-CoV-2 infection. Fourteen patients (58%) tested positive after admission. The COVID-19(+) group had a higher risk of in-hospital, 30-day, and 90-day mortality (p < 0.001). They also had a prolonged hospital stay and presented with more complications and readmissions (p < 0.05). Only COVID-19(+) status and older age were independent predictors for mortality with a HR = 6.5 (p = < 0.001) and 1.09 (p = 0.001), respectively. The 2020 cohort had twice the risk of mortality with a HR = 2.04 (p = 0.002) compared to the 2019 cohort. However, comparing only the COVID-19 (-) patients, there was no difference in mortality risk, with a HR = 1.30 (p = 0.343). DISCUSSION: The COVID-19 pandemic has significantly affected healthcare systems and elderly patients. CONCLUSIONS: Hip fracture patients with a concomitant SARS-CoV-2 virus infection were associated with increased morbidity and mortality throughout the first 3 months. COVID-19 status and older age were significant predictors for mortality. Efforts should be directed into nosocomial infection reduction and prompt surgical management. LEVEL OF EVIDENCE: Level III.

Is There a Relationship between the Elasticity of Brain Tumors, Changes in Diffusion Tensor Imaging, and Histological Findings? A Pilot Study Using Intraoperative Ultrasound Elastography.

Intraoperative ultrasound elastography (IOUS-E) is a novel image modality applied in brain tumor assessment. However, the potential links between elastographic findings and other histological and neuroimaging features are unknown. This study aims to find associations between brain tumor elasticity, diffusion tensor imaging (DTI) metrics, and cell proliferation. A retrospective study was conducted to analyze consecutively admitted patients who underwent craniotomy for supratentorial brain tumors between March 2018 and February 2020. Patients evaluated by IOUS-E and preoperative DTI were included. A semi-quantitative analysis was performed to calculate the mean tissue elasticity (MTE). Diffusion coefficients and the tumor proliferation index by Ki-67 were registered. Relationships between the continuous variables were determined using the Spearman ρ test. A predictive model was developed based on non-linear regression using the MTE as the dependent variable. Forty patients were evaluated. The pathologic diagnoses were as follows: 21 high-grade gliomas (HGG); 9 low-grade gliomas (LGG); and 10 meningiomas. Cases with a proliferation index of less than 10% had significantly higher medians of MTE (110.34 vs. 79.99, p < 0.001) and fractional anisotropy (FA) (0.24 vs. 0.19, p = 0.020). We found a strong positive correlation between MTE and FA (rs (38) = 0.91, p < 0.001). A cubic spline non-linear regression model was obtained to predict tumoral MTE from FA (R2 = 0.78, p < 0.001). According to our results, tumor elasticity is associated with histopathological and DTI-derived metrics. These findings support the usefulness of IOUS-E as a complementary tool in brain tumor surgery.

The new AO classification system for intertrochanteric fractures allows better agreement than the original AO classification. An inter- and intra-observer agreement evaluation.

BACKGROUND: A new AO classification for intertrochanteric fractures was recently published; no studies have evaluated its inter- and intra-observer agreement. METHODS: Six evaluators (three hip subspecialists and three residents) assessed radiographs of 68 intertrochanteric fractures; fractures were classified using the original and the new AO classifications. The cases were displayed in a random sequence after a six-week interval for repeat evaluation. We used the Kappa coefficient (k) to determine inter- and intra-observer agreement. RESULTS: Inter-observer agreement was slight (k = 0.128 [0.092-0.170]) using the original and fair (k = 0.250 [0.186-0.327]), with the new AO classification. Orthopedic residents exhibited better agreement than hip surgeons using the original classification (k = 0.302 [0.210-0.416] and k= -0.018 [-0.058-0.029], respectively) and the new classification (k = 0.388 [0.294-0.514] and k = 0.109 [0.031-0.192], respectively). Using both classifications as dichotomous variables (stable or unstable patterns), the agreement was slight (k = 0.158 [0.074-0.246]) using the original classification and moderate (k = 0.425 [0.308-0.550]) with the new AO classification. INTRA-OBSERVER: The agreement was fair using the original (k = 0.350 [0.278-0.424]) and the new (k = 0.295 [0.239 to 0.353]) AO classifications, respectively. Residents had better agreement than hip specialists using the original (k = 0.405 [0.303-0.512]) versus (k = 0.292 [0.193-0.293]) and the new classification (k = 0.449 [0.370 to 0.528] versus k = 0.129 [0.064 to 0.208]). CONCLUSION: The inter-observer agreement using the new AO classification was significantly better than using its original version. Also, the new AO classification system allowed better agreement when distinguishing stable from unstable patterns.

A Best-Fit of an Anatomic Tibial Baseplate Closely Parallels the Flexion-Extension Plane and Covers a High Percentage of the Proximal Tibia.

There are no reports of in vivo internal-external (I-E) rotational alignment and coverage of the proximal tibia after performing a best-fit method of an anatomically designed and asymmetrically shaped tibial baseplate during calipered kinematically aligned (KA) total knee arthroplasty (TKA). We hypothesized that a best-fit plane sets the anterior-posterior (A-P) axis of the anatomic baseplate closely parallel to the flexion-extension (F-E) plane of the knee and covers a high percentage of the proximal tibia. A total of 145 consecutive primary TKAs were prospectively collected. The calipered KA method and verification checks set the positions and orientations of the components without ligament release in all knees without restrictions on the preoperative deformities. A best-fit method selected one of six trials of anatomic baseplates that maximized coverage and set I-E rotation parallel to and within the cortical edge of the proximal tibia. The angle between the transverse axes of the components (i.e., the deviation of the A-P axis of the anatomic baseplate from the F-E plane of the native knee) and the cross-sectional area (CSA) of the proximal tibia were measured on postoperative computerized tomographic scans. The mean deviation of the anatomic baseplate from the F-E plane was 2-degree external ± 5 degrees. The mean coverage of the proximal tibia was 87 ± 6% (CSA of baseplate from the manufacturer/CSA of proximal tibia × 100). The anatomic baseplate and best-fit method adequately set I-E rotation of the baseplate closely parallel to the F-E plane of the knee and cover a high percentage of the proximal tibia.

Meningioma Consistency Can Be Defined by Combining the Radiomic Features of Magnetic Resonance Imaging and Ultrasound Elastography. A Pilot Study Using Machine Learning Classifiers.

BACKGROUND: The consistency of meningioma is a factor that may influence surgical planning and the extent of resection. The aim of our study is to develop a predictive model of tumor consistency using the radiomic features of preoperative magnetic resonance imaging and the tumor elasticity measured by intraoperative ultrasound elastography (IOUS-E) as a reference parameter. METHODS: A retrospective analysis was performed on supratentorial meningiomas that were operated on between March 2018 and July 2020. Cases with IOUS-E studies were included. A semiquantitative analysis of elastograms was used to define the meningioma consistency. MRIs were preprocessed before extracting radiomic features. Predictive models were built using a combination of feature selection filters and machine learning algorithms: logistic regression, Naive Bayes, k-nearest neighbors, Random Forest, Support Vector Machine, and Neural Network. A stratified 5-fold cross-validation was performed. Then, models were evaluated using the area under the curve and classification accuracy. RESULTS: Eighteen patients were available for analysis. Meningiomas were classified as hard or soft according to a mean tissue elasticity threshold of 120. The best-ranked radiomic features were obtained from T1-weighted post-contrast, apparent diffusion coefficient map, and T2-weighted images. The combination of Information Gain and ReliefF filters with the Naive Bayes algorithm resulted in an area under the curve of 0.961 and classification accuracy of 94%. CONCLUSIONS: We have developed a high-precision classification model that is capable of predicting consistency of meningiomas based on the radiomic features in preoperative magnetic resonance imaging (T2-weighted, T1-weighted post-contrast, and apparent diffusion coefficient map).

An articulated spacer made of new primary implants in two-stage exchange for infected total knee arthroplasty may provide durable results.

AIMS: Our objective is to describe our early and mid-term results with the use of a new simple primary knee prosthesis as an articulating spacer in planned two-stage management for infected knee arthroplasty. As a second objective, we compared outcomes between the group with a retained first stage and those with a complete two-stage revision. METHODS: We included 47 patients (48 knees) with positive criteria for infection, with a minimum two-year follow-up, in which a two-stage approach with an articulating spacer with new implants was used. Patients with infection control, and a stable and functional knee were allowed to retain the initial first-stage components. Outcomes recorded included: infection control rate, reoperations, final range of motion (ROM), and quality of life assessment (QoL) including Western Ontario and McMaster Universities osteoarthritis index, Knee Injury and Osteoarthritis Outcome Score, Oxford Knee Score, 12-Item Short-Form Health Survey questionnaire, and University of California Los Angeles (UCLA) activity score and satisfaction score. These outcomes were evaluated and compared to additional cohorts of patients with retained first-stage interventions and those with a complete two-stage revision. Mean follow-up was 3.7 years (2.0 to 6.5). RESULTS: Eight knees failed directly related to lack of infection control (16%), and two patients (two knees) died within the first year for causes not directly related, giving an initial success rate of 79% (38/48). Secondary success rate after a subsequent procedure was 91% (44/48 knees). From the initially retained spacers, four knees (22%) required a second-stage revision for continuous symptoms and one (5%) for an acute infection. There were no significant differences regarding the failure rate due to infection, ROM, and QoL assessment between patients with a retained first-stage procedure and those who underwent a second-stage operation. CONCLUSION: Our protocol of two-stage exchange for infected knee arthroplasties with an articulating spacer and using new primary knee implants achieves adequate infection control. Retained first-stage operations achieve comparable results in selected cases, with no difference in infection control, ROM, and QoL assessment in comparison to patients with completed two-stage revision surgery. Cite this article: Bone Joint J 2020;102-B(7):852-860.

Comparison of Intraoperative Ultrasound B-Mode and Strain Elastography for the Differentiation of Glioblastomas From Solitary Brain Metastases. An Automated Deep Learning Approach for Image Analysis.

BACKGROUND: The differential diagnosis of glioblastomas (GBM) from solitary brain metastases (SBM) is essential because the surgical strategy varies according to the histopathological diagnosis. Intraoperative ultrasound elastography (IOUS-E) is a relatively novel technique implemented in the surgical management of brain tumors that provides additional information about the elasticity of tissues. This study compares the discriminative capacity of intraoperative ultrasound B-mode and strain elastography to differentiate GBM from SBM. METHODS: We performed a retrospective analysis of patients who underwent craniotomy between March 2018 to June 2020 with glioblastoma (GBM) and solitary brain metastases (SBM) diagnoses. Cases with an intraoperative ultrasound study were included. Images were acquired before dural opening, first in B-mode, and then using the strain elastography module. After image pre-processing, an analysis based on deep learning was conducted using the open-source software Orange. We have trained an existing neural network to classify tumors into GBM and SBM via the transfer learning method using Inception V3. Then, logistic regression (LR) with LASSO (least absolute shrinkage and selection operator) regularization, support vector machine (SVM), random forest (RF), neural network (NN), and k-nearest neighbor (kNN) were used as classification algorithms. After the models' training, ten-fold stratified cross-validation was performed. The models were evaluated using the area under the curve (AUC), classification accuracy, and precision. RESULTS: A total of 36 patients were included in the analysis, 26 GBM and 10 SBM. Models were built using a total of 812 ultrasound images, 435 of B-mode, 265 (60.92%) corresponded to GBM and 170 (39.8%) to metastases. In addition, 377 elastograms, 232 (61.54%) GBM and 145 (38.46%) metastases were analyzed. For B-mode, AUC and accuracy values of the classification algorithms ranged from 0.790 to 0.943 and from 72 to 89%, respectively. For elastography, AUC and accuracy values ranged from 0.847 to 0.985 and from 79% to 95%, respectively. CONCLUSION: Automated processing of ultrasound images through deep learning can generate high-precision classification algorithms that differentiate glioblastomas from metastases using intraoperative ultrasound. The best performance regarding AUC was achieved by the elastography-based model supporting the additional diagnostic value that this technique provides.

High prevalence of deep vein thrombosis in elderly hip fracture patients with delayed hospital admission.

PURPOSE: Deep vein thrombosis (DVT) is a common complication in hip fracture patients, associated with significant morbidity and mortality. Research has focused on postoperative DVT, with scant reports on preoperative prevalence. The aim of this study was to describe the prevalence of preoperative DVT in patients accessing medical care ≥ 48 h after a hip fracture. METHODS: We included elderly patients admitted ≥ 48 h after sustaining a hip fracture, between September 2015 and October 2017. Patients with a previous episode of DVT, undergoing anticoagulation therapy, with pathologic fractures or undergoing cancer treatment were excluded. Of 273 patients, 59 were admitted at least 48 h after the fracture. DVT screening by Doppler ultrasound of both lower extremities was carried upon hospital admission. We recorded age, sex, Charlson comorbidity index and ASA score, fracture type, time since injury, time from admission to surgery and total length of hospital stay. RESULTS: We studied 41 patients, 79 (± 10.34) years old. The delay from injury to admission was 120 h (48-696 h). Seven patients (17.1%) had a DVT upon admission. There were no significant differences between patients with and without DVT, regarding time from admission to surgery or the total length of the hospital stay. CONCLUSIONS: The prevalence of DVT in patients admitted ≥ 48 h after a hip fracture was 17.1%. The diagnosis and management of DVT did not increase time to surgery or hospital stay. Our results suggest routine screening for DVT in patients consulting emergency services ≥ 48 h after injury.

[Management of hip fractures in the elderly. A national survey among Chilean orthopaedic surgeons]. / Controversias en el manejo de la fractura de cadera en el adulto mayor. Encuesta nacional a Traumatólogos especialistas en cirugía de cadera.

BACKGROUND: As the population ages, patients exposed to osteoporotic fractures increase, especially hip fracture, which is the most severe and costly. AIM: To characterize surgical practices in the management of hip fractures in older patients through a nationwide survey of specialized hip surgeons dedicated to the care of these patients. MATERIAL AND METHODS: A survey composed of 32 questions was formulated, including demographic factors, preoperative evaluation, definitive treatment, and postoperative management. It was sent to 140 specialists. 84 of them replied (61%), and 71 answers were included. RESULTS: Eighty six percent of respondents agreed that orthogeriatric management is fundamental in the outcome of these patients, but only 73% had the collaboration of an internist or a geriatrician. Although 97% considered 72 hours or less the ideal time to perform surgery, only 52% of the respondents declared performing surgery within that timeframe, with differences between private and public system. Regarding surgical treatment, 94-98% of femoral neck fractures are treated with an arthroplasty and 98-99% of per-subtrochanteric fractures are treated with internal fixation and osteosynthesis. Osteoporosis treatment is only carried out by 51% of the respondents and with significant variation. CONCLUSIONS: This survey shows that there is agreement in surgical practice between specialists treating these patients, but clear differences in preoperative optimization, treatment timeframe, and post fracture medical treatment.