Pediatric Bone Tumors: Location and Age Distribution of 420 Cases.

Background/objectives: One of the most important diagnostic tools in bone tumors is X-rays. Preliminary and, in the case of some benign lesions, definitive diagnoses are formed using this basic tool. Part of the decision making in this stage is based on statistical probability using the patient's age, as well as the incidence and predilection sites of different entities.

[Digital tools in primary total knee arthroplasty-Prevalence in the German-speaking region].

Background: Digital tools are being increasingly used worldwide in primary knee arthroplasty. This study aimed to analyze the utilization density of digital tools, the preferred alignment strategies, and the obstacles and benefits of implementing these technologies in German-speaking countries.

Materials And Methods: An online survey with 57 questions about digital tools in primary knee arthroplasty and their usage was conducted among members of the Arthroplasty Working Group (AE).

Impact of metadata in multimodal classification of bone tumours.

Unlabelled: The accurate classification of bone tumours is crucial for guiding clinical decisions regarding treatment and follow-up. However, differentiating between various tumour types is challenging due to the rarity of certain entities, high intra-class variability, and limited training data in clinical practice. This study proposes a multimodal deep learning model that integrates clinical metadata and X-ray imaging to improve the classification of primary bone tumours.

Chondrosarcoma of the Pelvis and Extremities: A Review of 77 Cases of a Tertiary Sarcoma Center with a Minimum Follow-Up of 10 Years.

Background: Chondrosarcomas (CS) are a rare and heterogenic group of primary malignant bone tumors. In the literature, data on prognostic factors in chondrosarcomas are scarce, and most studies are limited by a short follow-up. The aim of this retrospective study was therefore to determine factors associated with the survival and local recurrence of chondrosarcomas and to compare the results with previous studies.

[The potential of wearable technology in knee arthroplasty].

Background: Wearable technology has developed rapidly in recent years and offers promising possibilities for supporting and optimizing orthopaedic procedures, especially pre- and postoperatively. The continuous monitoring and precise analysis of movement patterns, as well as the individual adaptation of rehabilitation processes are just some of the potential benefits of wearable technology. The aim of this paper is to evaluate the potential of wearable technology in knee arthroplasty and to provide an overview of the evidence that is currently available.

[Endoprosthetic treatment of femoral neck fractures in Germany : Cumulative analysis of EPRD registry data from 2013 to 2020].

Background: The German Arthroplasty Registry (EPRD) recorded nearly 52,000 femoral neck fractures treated with arthroplasty by 2020. This study aimed to identify survival rates and risk factors for hip prosthesis failure.

Material And Methods: The study included all patients with arthroplasty after hip fractures documented in the EPRD.

Childhood Tumors around the Knee Revisited: Predilection Sites for Most Entities Confirmed.

The diagnostic work-up of musculoskeletal tumors is a multifactorial process. During the early phase, differential diagnoses are made using basic radiological imaging. In this phase, part of the decision making is based on the patient's age, as well as the incidence and predilection sites of different entities.

C-Reactive Protein Pretreatment-Level Evaluation with Histopathological Correlation for Chondrosarcoma Prognosis Assessment-A 15-Year Retrospective Single-Center Study.

Background: An aberrant cellular microenvironment characterized by pathological cells or inflammation represents an added risk factor across various cancer types. While the significance of chronic inflammation in the development of most diffuse tumors has been extensively studied, an exception to this analysis exists in the context of chondrosarcomas. Chondrosarcomas account for 20-30% of all bone sarcomas, with an estimated global incidence of 1 in 100,000.

Multicentric development and validation of a multi-scale and multi-task deep learning model for comprehensive lower extremity alignment analysis.

Osteoarthritis of the knee, a widespread cause of knee disability, is commonly treated in orthopedics due to its rising prevalence. Lower extremity misalignment, pivotal in knee injury etiology and management, necessitates comprehensive mechanical alignment evaluation via frequently-requested weight-bearing long leg radiographs (LLR). Despite LLR's routine use, current analysis techniques are error-prone and time-consuming.

Recommender-based bone tumour classification with radiographs-a link to the past.

Objectives: To develop an algorithm to link undiagnosed patients to previous patient histories based on radiographs, and simultaneous classification of multiple bone tumours to enable early and specific diagnosis.

Materials And Methods: For this retrospective study, data from 2000 to 2021 were curated from our database by two orthopaedic surgeons, a radiologist and a data scientist. Patients with complete clinical and pre-therapy radiographic data were eligible.

A New Method for Assessing Patients' Obesity-Associated Infection Risk Using X-rays in Hip Arthroplasties.

Overweight patients have higher complication rates during and after surgical procedures. In total hip arthroplasty (THA), postoperative infection is a major complication. In this study, we show that the patient's body mass index (BMI) can be approximated by a newly developed grading system using preoperative X-rays.

Deep Learning-Based Detection of Bone Tumors around the Knee in X-rays of Children.

Even though tumors in children are rare, they cause the second most deaths under the age of 18 years. More often than in other age groups, underage patients suffer from malignancies of the bones, and these mostly occur in the area around the knee. One problem in the treatment is the early detection of bone tumors, especially on X-rays.

Spotlight on Nerves: Portable Multispectral Optoacoustic Imaging of Peripheral Nerve Vascularization and Morphology.

Various morphological and functional parameters of peripheral nerves and their vascular supply are indicative of pathological changes due to injury or disease. Based on recent improvements in optoacoustic image quality, the ability of multispectral optoacoustic tomography, to investigate the vascular environment and morphology of peripheral nerves is explored in vivo in a pilot study on healthy volunteers in tandem with ultrasound imaging (OPUS). The unique ability of optoacoustic imaging to visualize the vasa nervorum by observing intraneural vessels in healthy nerves is showcased in vivo for the first time.

Postoperative full leg radiographs exhibit less residual coronal varus deformity compared to intraoperative measurements in robotic arm-assisted total knee arthroplasty with the MAKO™ system.

Purpose: Robotic arm-assisted total knee arthroplasty (raTKA), currently a major trend in knee arthroplasty, aims to improve the accuracy of implant positioning and limb alignment. However, it is unclear whether and to what extent manual radiographic and navigation measurements with the MAKO™ system correlate. Nonetheless, a high agreement would be crucial to reliably achieve the desired limb alignment.

C-Reactive Protein Pretreatment-Level Evaluation for Ewing's Sarcoma Prognosis Assessment-A 15-Year Retrospective Single-Centre Study.

Background: A pathological/inflamed cellular microenvironment state is an additional risk factor for any cancer type. The importance of a chronic inflammation state in most diffuse types of tumour has already been analysed, except for in Ewing’s sarcoma. It is a highly malignant blue round cell tumour, with 90% of cases occurring in patients aged between 5 and 25 years.

SAM-X: sorting algorithm for musculoskeletal x-ray radiography.

Objective: To develop a two-phased deep learning sorting algorithm for post-X-ray image acquisition in order to facilitate large musculoskeletal image datasets according to their anatomical entity.

Methods: In total, 42,608 unstructured and pseudonymized radiographs were retrieved from the PACS of a musculoskeletal tumor center. In phase 1, imaging data were sorted into 1000 clusters by a self-supervised model.

Two-Phase Deep Learning Algorithm for Detection and Differentiation of Ewing Sarcoma and Acute Osteomyelitis in Paediatric Radiographs.

Background/aim: Ewing sarcoma is a highly malignant tumour predominantly found in children. The radiological signs of this malignancy can be mistaken for acute osteomyelitis. These entities require profoundly different treatments and result in completely different prognoses.

Applications of machine learning for imaging-driven diagnosis of musculoskeletal malignancies-a scoping review.

Musculoskeletal malignancies are a rare type of cancer. Consequently, sufficient imaging data for machine learning (ML) applications is difficult to obtain. The main purpose of this review was to investigate whether ML is already having an impact on imaging-driven diagnosis of musculoskeletal malignancies and what the respective reasons for this might be.

Development of an Exoskeleton Platform of the Finger for Objective Patient Monitoring in Rehabilitation.

This paper presents the application of an adaptive exoskeleton for finger rehabilitation. The system consists of a force-controlled exoskeleton of the finger and wireless coupling to a mobile application for the rehabilitation of complex regional pain syndrome (CRPS) patients. The exoskeleton has sensors for motion detection and force control as well as a wireless communication module.

Prediction of Complications and Surgery Duration in Primary Total Hip Arthroplasty Using Machine Learning: The Necessity of Modified Algorithms and Specific Data.

Background: Machine Learning (ML) in arthroplasty is becoming more popular, as it is perfectly suited for prediction models. However, results have been heterogeneous so far. We hypothesize that an accurate ML model for outcome prediction in THA must be able to compute arthroplasty-specific data.

Prediction of complications and surgery duration in primary TKA with high accuracy using machine learning with arthroplasty-specific data.

Purpose: The number of primary total knee arthroplasties (TKA) is expected to rise constantly. For patients and healthcare providers, the early identification of risk factors therefore becomes increasingly fundamental in the context of precision medicine. Others have already investigated the detection of risk factors by conducting literature reviews and applying conventional statistical methods.

Machine learning in knee arthroplasty: specific data are key-a systematic review.

Purpose: Artificial intelligence (AI) in healthcare is rapidly growing and offers novel options of data analysis. Machine learning (ML) represents a distinct application of AI, which is capable of generating predictions and has already been tested in different medical specialties with various approaches such as diagnostic applications, cost predictions or identification of risk factors. In orthopaedics, this technology has only recently been introduced and the literature on ML in knee arthroplasty is scarce.

Minimally Invasive Total Hip Arthroplasty: A Comparison of Restoring Hip Biomechanics With and Without a Traction Table.

Background/aim: The aim of the study was to analyze operative time and restoration of hip biomechanics in total hip arthroplasty (THA) via direct anterior approach (DAA) with and without the use of a traction table.

Patients And Methods: We retrospectively compared 97 cases where a traction table was used to 92 cases without a table. Ninety-seven patients received THA with a traction table (AMIS technique) and 92 patients with conventional DAA.