Artificial Intelligence (AI) is becoming more powerful but is barely used to counter the growth in health care burden. AI applications to increase efficiency in orthopedics are rare. We questioned if (1) we could train machine learning (ML)
Introduction and Objective. Despite the low incidence of pilon fractures among lower limb injuries, their high-impact nature presents difficulties in surgical management and recovery. Current literature includes a wide range of different management strategies, however there is no universal treatment
Partial meniscectomy patients have a greater likelihood for the development of early osteoarthritis (OA). To prevent the onset of early OA, patient-specific treatment
With advances in artificial intelligence, the use of computer-aided detection and diagnosis in clinical imaging is gaining traction. Typically, very large datasets are required to train machine-learning models, potentially limiting use of this technology when only small datasets are available. This study investigated whether pretraining of fracture detection models on large, existing datasets could improve the performance of the model when locating and classifying wrist fractures in a small X-ray image dataset. This concept is termed “transfer learning”. Firstly, three detection models, namely, the faster region-based convolutional neural network (faster R-CNN), you only look once version eight (YOLOv8), and RetinaNet, were pretrained using the large, freely available dataset, common objects in context (COCO) (330000 images). Secondly, these models were pretrained using an open-source wrist X-ray dataset called “Graz Paediatric Wrist Digital X-rays” (GRAZPEDWRI-DX) on a (1) fracture detection dataset (20327 images) and (2) fracture location and classification dataset (14390 images). An orthopaedic surgeon classified the small available dataset of 776 distal radius X-rays (Introduction
Method
Summary. Management of metal on metal hip replacements can be accomplished with a simple
Abstract. Objectives. Young patients receiving metallic bone implants after surgical resection of bone cancer require implants that last into adulthood, and ideally life-long. Porous implants with similar stiffness to bone can promote bone ingrowth and thus beneficial clinical outcomes. A mechanical remodelling stimulus, strain energy density (SED), is thought to be the primary control variable of the process of bone growth into porous implants. The sequential process of bone growth needs to be taken into account to develop an accurate and validated bone remodelling
Abstract. Objectives. Ultrasound speckle tracking is a safe and non-invasive diagnostic tool to measure soft tissue deformation and strain. In orthopaedics, it could have broad application to measure how injury or surgery affects muscle, tendon or ligament biomechanics. However, its application requires custom tuning of the speckle-tracking
The optimal treatment strategy for post-traumatic long bone non-unions is subject of an ongoing discussion. At the Maastricht University Medical Center (MUMC+) the induced membrane technique is used to treat post-traumatic long bone non-unions. This technique uses a multimodal treatment
Introduction:. Most of the published papers on AI based diagnosis have focused on the
Currently implemented accuracy metrics in open-source libraries for segmentation by supervised machine learning are typically one-dimensional scores [1]. While extremely relevant to evaluate applicability in clinics, anatomical location of segmentation errors is often neglected. This study aims to include the three-dimensional (3D) spatial information in the development of a novel framework for segmentation accuracy evaluation and comparison between different methods. Predicted and ground truth (manually segmented) segmentation masks are meshed into 3D surfaces. A template mesh of the same anatomical structure is then registered to all ground truth 3D surfaces. This ensures all surface points on the ground truth meshes to be in the same anatomically homologous order. Next, point-wise surface deviations between the registered ground truth mesh and the meshed segmentation prediction are calculated and allow for color plotting of point-wise descriptive statistics. Statistical parametric mapping includes point-wise false discovery rate (FDR) adjusted p-values (also referred to as q-values). The framework reads volumetric image data containing the segmentation masks of both ground truth and segmentation prediction. 3D color plots containing descriptive statistics (mean absolute value, maximal value,…) on point-wise segmentation errors are rendered. As an example, we compared segmentation results of nnUNet [2], UNet++ [3] and UNETR [4] by visualizing the mean absolute error (surface deviation from ground truth) as a color plot on the 3D model of bone and cartilage of the mean distal femur. A novel framework to evaluate segmentation accuracy is presented. Output includes anatomical information on the segmentation errors, as well as point-wise comparative statistics on different segmentation
Abstract. Objectives. Current literature on pilon fracture includes a range of different management strategies, however there is no universal treatment
Patients with advanced cancer can develop bone metastases in the femur which are often painful and increase the risk of pathological fracture. Accurate segmentation of bone metastases is, amongst others, important to improve patient-specific computer models which calculate fracture risk, and for radiotherapy planning to determine exact radiation fields. Deep learning
Syndesmotic ankle lesions involve disruption of the osseous tibiofibular mortise configuration as well as ligamentous structures stabilizing the ankle joint. Incomplete diagnosis and maltreatment of these injuries is frequent, resulting in chronic pain and progressive instability thus promoting development of ankle osteoarthritis in the long term. Although the pathogenesis is not fully understood, abnormal mechanics has been implicated as a principal determinant of ankle joint degeneration after syndesmotic ankle lesions. Therefore, the focus of this presentation will be on our recent development of a computationally efficient
Chronic low back pain (cLBP) is a complex, multifaceted disorder where biological, psychological, and social factors affect its onset and trajectory. Consequently, cLBP encompasses many different disease variants, with multiple patient-specific mechanisms. The goal of NIH Back Pain Consortium (BACPAC) Research Program is to develop understanding of cLBP mechanisms and to develop
We performed this systematic overview on the overlapping meta-analyses that analyzed autologous platelet-rich plasma (PRP) as an adjuvant in the repair of rotator cuff tears and identify the studies which provide the current best evidence on this subject and generate recommendations for the same. We conducted independent and duplicate electronic database searches in PubMed, Web of Science, Scopus, Embase, Cochrane Database of Systematic Reviews, and the Database of Abstracts of Reviews of Effects on September 8, 2021, to identify meta-analyses that analyzed the efficacy of PRP as an adjuvant in the repair of rotator cuff tears. Methodological quality assessment was made using Oxford Levels of Evidence, AMSTAR scoring, and AMSTAR 2 grades and used the Jadad decision
Varus ankle osteoarthritis (OA) is typically associated with peritalar instability, which may result in altered subtalar joint position. This study aimed to determine the extent to which total ankle replacement (TAR) in varus ankle OA can restore the subtalar position alignment using 3-dimensional semi-automated measurements on WBCT. Fourteen patients (15 ankles, mean age 61) who underwent TAR for varus ankle OA were retrospectively analyzed using semi- automated measurements of the hindfoot based on pre-and postoperative weightbearing WBCT (WBCT) imaging. Eight 3-dimensional angular measurements were obtained to quantify the ankle and subtalar joint alignment. Twenty healthy individuals were served as a control groups and were used for reliability assessments. All ankle and hindfoot angles improved between preoperative and a minimum of 1 year (mean 2.1 years) postoperative and were statistically significant in 6 out of 8 angles (P<0.05). Values The post-op angles were in a similar range to as those of healthy controls were achieved in all measurements and did not demonstrated statistical difference (P>0.05). Our findings indicate that talus repositioning after TAR within the ankle mortise improves restores the subtalar position joint alignment within normal values. These data inform foot and ankle surgeons on the amount of correction at the level of the subtalar joint that can be expected after TAR. This may contribute to improved biomechanics of the hindfoot complex. However, future studies are required to implement these findings in surgical
The most important outcome predictor of Legg-Calvé-Perthes disease (LCPD) is the shape of the healed femoral head. However, the deformity of the femoral head is currently evaluated by non-reproducible, categorical, and qualitative classifications. In this regard, recent advances in computer vision might provide the opportunity to automatically detect and delineate the outlines of bone in radiographic images for calculating a continuous measure of femoral head deformity. This study aimed to construct a pipeline for accurately detecting and delineating the proximal femur in radiographs of LCPD patients employing existing
Introduction. The surgical treatment of critical-sized bone defects with complex three-dimensional (3D) geometries is a challenge for the treating surgeon. Additive manufacturing such as 3D printing enables the production of highly individualized bone implants meeting the shape of the patient's bone defect and including a tunable internal structure. In this study, we showcase the design process for patient-specific implants with critical-sized tibia defects. Methods. Two clinical cases of patients with critical tibia defects (size 63×20×21 mm and 50×24×17 mm) were chosen. Brainlab software was used for segmentation of CT data generating 3D models of the defects. The implant construction involves multiple stages. Initially, the outer shell is precisely defined. Subsequently, the specified volume is populated with internal structures using Voronoi, Gyroid, and NaCl crystal structures. Variation in pore size (1.6 mm and 1.0 mm) was accomplished by adjusting scaffold size and material thickness. Results. An
Several emerging reports suggest an important involvement of the hindfoot alignment in the outcome of knee osteotomy. At present, studies lack a comprehensive overview. Therefore, we aimed to systematically review all biomechanical and clinical studies investigating the role of the hindfoot alignment in the setting of osteotomies around the knee. A systematic literature search was conducted on multiple databases combining “knee osteotomy” and “hindfoot/ankle alignment” search terms. Articles were screened and included according to the PRISMA guidelines. A quality assessment was conducted using the Quality Appraisal for Cadaveric Studies (QUACS) - and modified methodologic index for non-randomized studies (MINORS) scales. Three cadaveric, fourteen retrospective cohort and two case-control studies were eligible for review. Biomechanical hindfoot characteristics were positively affected (n=4), except in rigid subtalar joint (n=1) or talar tilt (n=1) deformity. Patient symptoms and/or radiographic alignment at the level of the hindfoot did also improve after knee osteotomy (n=13), except in case of a small pre-operative lateral distal tibia- and hip knee ankle (HKA) angulation or in case of a large HKA correction (>14.5°). Additionally, a pre-existent hindfoot deformity (>15.9°) was associated with undercorrection of lower limb alignment following knee osteotomy. The mean QUACS score was 61.3% (range: 46–69%) and mean MINORS score was 9.2 out of 16 (range 6–12) for non-comparative and 16.5 out of 24 (range 15–18) for comparative studies. Osteotomies performed to correct knee deformity have also an impact on biomechanical and clinical outcomes of the hindfoot. In general, these are reported to be beneficial, but several parameters were identified that are associated with newly onset – or deterioration of hindfoot symptoms following knee osteotomy. Further prospective studies are warranted to assess how diagnostic and therapeutic
Neurological complications in oncological and degenerative spine surgery represent one of the most feared risks of these procedures. Multimodal intraoperative neurophysiological monitoring (IONM) mainly uses methods to detect changes in the patient's neurological status in a timely manner, thus allowing actions that can reverse neurological deficits before they become irreversible. The utopian goal of spinal surgery is the absence of neurological complications while the realistic goal is to optimize the responses to changes in neuromonitoring such that permanent deficits occur less frequently as possible. In 2014, an