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Image-based patient-specific modelling of hemodynamics are gaining increased popularity as a diagnosis and outcome prediction solution for a variety of cardiovascular diseases. While their potential to improve diagnostic capabilities and thereby clinical outcome is widely recognized, these methods require considerable computational resources since they are mostly based on conventional numerical methods such as computational fluid dynamics (CFD). As an alternative to the numerical methods, we propose a machine learning (ML) based approach to calculate patient-specific hemodynamic parameters. Compared to CFD based methods, our approach holds the benefit of being able to calculate a patient-specific hemodynamic outcome instantly with little need for computational power. In this proof-of-concept study, we present a deep artificial neural network (ANN) capable of computing hemodynamics for patients with aortic coarctation in a centerline aggregated (i.e., locally averaged) form. Considering the complex relation between vessels shape and hemodynamics on the one hand and the limited availability of suitable clinical data on the other, a sufficient accuracy of the ANN may however not be achieved with available data only. Another key aspect of this study is therefore the successful augmentation of available clinical data. Using a statistical shape model, additional training data was generated which substantially increased the ANN's accuracy, showcasing the ability of ML based methods to perform in-silico modelling tasks previously requiring resource intensive CFD simulations.

The aim of this paper is to provide a comprehensive overview of the MICCAI 2020 AutoImplant Challenge. The approaches and publications submitted and accepted within the challenge will be summarized and reported, highlighting common algorithmic trends and algorithmic diversity. Furthermore, the evaluation results will be presented, compared and discussed in regard to the challenge aim: seeking for low cost, fast and fully automated solutions for cranial implant design. Based on feedback from collaborating neurosurgeons, this paper concludes by stating open issues and post-challenge requirements for intra-operative use. The codes can be found at https://github.com/Jianningli/tmi .

Vertebral labelling and segmentation are two fundamental tasks in an automated spine processing pipeline. Reliable and accurate processing of spine images is expected to benefit clinical decision-support systems for diagnosis, surgery planning, and population-based analysis on spine and bone health. However, designing automated algorithms for spine processing is challenging predominantly due to considerable variations in anatomy and acquisition protocols and due to a severe shortage of publicly available data. Addressing these limitations, the Large Scale Vertebrae Segmentation Challenge (VerSe) was organised in conjunction with the International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) in 2019 and 2020, with a call for algorithms towards labelling and segmentation of vertebrae. Two datasets containing a total of 374 multi-detector CT scans from 355 patients were prepared and 4505 vertebrae have individually been annotated at voxel-level by a human-machine hybrid algorithm (https://osf.io/nqjyw/, https://osf.io/t98fz/). A total of 25 algorithms were benchmarked on these datasets. In this work, we present the the results of this evaluation and further investigate the performance-variation at vertebra-level, scan-level, and at different fields-of-view. We also evaluate the generalisability of the approaches to an implicit domain shift in data by evaluating the top performing algorithms of one challenge iteration on data from the other iteration. The principal takeaway from VerSe: the performance of an algorithm in labelling and segmenting a spine scan hinges on its ability to correctly identify vertebrae in cases of rare anatomical variations. The content and code concerning VerSe can be accessed at: https://github.com/anjany/verse., Comment: Challenge report for the VerSe 2019 and 2020. Published in Medical Image Analysis (DOI: https://doi.org/10.1016/j.media.2021.102166)

The objective of the study was to suggest a novel quantitative assessment of acetabular bone defects based on a statistical shape model, validate the method, and present preliminary results. Two exemplary CT‐data sets with acetabular bone defects were segmented to obtain a solid model of each defect pelvis. The pathological areas around the acetabulum were excluded and a statistical shape model was fitted to the remaining healthy bone structures. The excluded areas were extrapolated such that a solid model of the native pelvis per specimen resulted (i.e., each pelvis without defect). The validity of the reconstruction was tested by a leave‐one‐out study. Validation results showed median reconstruction errors of 3.0 mm for center of rotation, 1.7 mm for acetabulum diameter, 2.1° for inclination, 2.5° for anteversion, and 3.3 mm3 for bone volume around the acetabulum. By applying Boolean operations on the solid models of defect and native pelvis, bone loss and bone formation in four different sectors were assessed. For both analyzed specimens, bone loss and bone formation per sector were calculated and were consistent with the visual impression. In specimen_1 bone loss was predominant in the medial wall (10.8 ml; 79%), in specimen_2 in the posterior column (15.6 ml; 46%). This study showed the feasibility of a quantitative assessment of acetabular bone defects using a statistical shape model‐based reconstruction method. Validation results showed acceptable reconstruction accuracy, also when less healthy bone remains. The method could potentially be used for implant development, pre‐clinical testing, pre‐operative planning, and intra‐operative navigation. © 2018 The Authors. Journal of Orthopaedic Research® Published by Wiley Periodicals, Inc. on behalf of Orthopaedic Research Society. J Orthop Res 9999:1–9, 2018.

Changes in knee shape and geometry resulting from total knee arthroplasty can affect patients in numerous important ways: pain, function, stability, range of motion, and kinematics. Quantitative data concerning these changes have not been previously available, to our knowledge, yet are essential to understand individual experiences of total knee arthroplasty and thereby improve outcomes for all patients. The limiting factor has been the challenge of accurately measuring these changes. Our study objective was to develop a conceptual framework and analysis method to investigate changes in knee shape and geometry, and prospectively apply it to a sample total knee arthroplasty population. Using clinically available computed tomography and radiography imaging systems, the three-dimensional knee shape and geometry of nine patients (eight varus and one valgus) were compared before and after total knee arthroplasty. All patients had largely good outcomes after their total knee arthroplasty. Knee shape changed both visually and numerically. On average, the distal condyles were slightly higher medially and lower laterally (range: +4.5 mm to −4.4 mm), the posterior condyles extended farther out medially but not laterally (range: +1.8 to −6.4 mm), patellofemoral distance increased throughout flexion by 1.8–3.5 mm, and patellar thickness alone increased by 2.9 mm (range: 0.7–5.2 mm). External femoral rotation differed preop and postop. Joint line distance, taking cartilage into account, changed by +0.7 to −1.5 mm on average throughout flexion. Important differences in shape and geometry were seen between pre-total knee arthroplasty and post-total knee arthroplasty knees. While this is qualitatively known, this is the first study to report it quantitatively, an important precursor to identifying the reasons for the poor outcome of some patients. Using the developed protocol and visualization techniques to compare patients with good versus poor clinical outcomes could lead to changes in implant design, implant selection, component positioning, and surgical technique. Recommendations based on this sample population are provided. Intraoperative and postoperative feedback could ultimately improve patient satisfaction.

Hintergrund Die Positionierung des B-FMT der Vibrant Bonebridge kann aufgrund der anatomischen Verhaltnisse des Mastoids und der Grose des Aktuators ohne eine vorherige Beurteilung der individuellen Computertomographie (CT) des Felsenbeins problematisch sein. Die Entwicklung eines einfach zu bedienenden Viewers, welcher eine Positionierung des B-FMT im Felsenbeinmodell ermoglicht und hier auf individuelle potenzielle anatomische Konflikte hinweist sowie Losungsmoglichkeiten anbietet, kann ein hilfreiches Werkzeug zur praoperativen Positionierung sein.

BACKGROUND Pelvic tilt influences acetabular orientation (AO). Anatomical AO can be measured in relation to the anterior pelvic plane (APP), functional AO can be calculated relative to table's plane. OBJECTIVE To assess to what extent functional AO is determined by pelvic tilt and if APP and table plane give equal information for correct AO. METHODS AO was evaluated by computed tomography (CT) scans of 138 patients. Pelvic tilt, anatomical and functional AO were measured, differences between the two reference planes were calculated. RESULTS Anatomical and functional acetabular anteversion (AA) were found to be different in 21% of individuals with an enhanced extent of pelvic tilt. Functional AA was increased compared to anatomical AA at high posterior pelvic tilt (p < 0.001). Enlarged anterior tilting of the pelvis reduced APP-related AA (p < 0.002). Anatomical AA positively correlated with pelvic tilt, particularly in females (p < 0.01, correlation coefficient = 0.698, R2 = 0.523). CONCLUSIONS APP and table plane do not provide equal information about AO at enhanced pelvic tilt. Functional orientation of the acetabulum is dependent on pelvic tilt, which itself is influenced by anatomical AA and should therefore be analyzed for precise AO.

Objectives Numerous complications following total knee replacement (TKR) relate to the patellofemoral (PF) joint, including pain and patellar maltracking, yet the options for in vivo imaging of the PF joint are limited, especially after TKR. We propose a novel sequential biplane radiological method that permits accurate tracking of the PF and tibiofemoral (TF) joints throughout the range of movement under weightbearing, and test it in knees pre- and post-arthroplasty. Methods A total of three knees with end-stage osteoarthritis and three knees that had undergone TKR at more than one year’s follow-up were investigated. In each knee, sequential biplane radiological images were acquired from the sagittal direction (i.e. horizontal X-ray source and 10° below horizontal) for a sequence of eight flexion angles. Three-dimensional implant or bone models were matched to the biplane images to compute the six degrees of freedom of PF tracking and TF kinematics, and other clinical measures. Results The mean and standard deviation for the six degrees of freedom of PF tracking and TF kinematics were computed. TF and PF kinematics were highly accurate (< 0.9 mm, < 0.6°) and repeatable. Conclusions The developed method permitted measuring of in vivo PF tracking and TF kinematics before and after TKR throughout the range of movement. This method could be a useful tool for investigating differences between cohorts of patients (e.g., with and without pain) impacting clinical decision-making regarding surgical technique, revision surgery or implant design.

Pelvic tilt determines functional orientation of the acetabulum. In this study, we investigated the interaction of pelvic tilt and functional acetabular anteversion (AA) in supine position. Pelvic tilt and AA of 138 individuals were measured by computed tomography (CT). AA was calculated in relation to the anterior pelvic plane (APP) and relative to the table plane. We analysed these parameters for gender-specific and age-related differences. The mean pelvic tilt was -0.1 ± 5.5°. Pelvic sagittal rotation displayed no gender nor age related differences. Females showed higher angles of AA compared with males (20.0° vs 17.2°, p

AimInformation about the temporal bone size and variations of anatomical structures are crucial for a safe positioning of the Vibrant Bonebridge B-FMT. A radiological based preoperative planning of the surgical procedure decreases the surgical time and minimizes the risk of complications.Materials and methodsWe developed a software tool, which allows a catch up of foreign DICOM data based CT temporal bone scans. The individual CT scan is transmitted into a 3D reconstructed pattern of the temporal bone. In this 3D reconstruction the individually favored position of the B- FMT should be found.ResultsThe software allows a determination of a safe B-FMT position by identifying the individual relation of middle fossa, jugular bulb and external auditory canal. Skull thickness and screw length are contained parameters for the surgical planning.ConclusionAn easy to handle software tool allows a radiologically data based safe and fast surgical positioning of the B-FMT.

The aim of this study was to investigate the performance of a cementless osseointegrated tibial tray (P.F.C. ® Sigma®, Depuy® Inc, USA) in a general population using finite element (FE) analysis. Computational testing of total knee replacements (TKRs) typically only use a model of a single patient and assume the results can be extrapolated to the general population. In this study, two statistical models (SMs) were used; one of the shape and elastic modulus of the tibia, and one of the tibiofemoral joint loads over a gait cycle, to generate a population of FE models. A method was developed to automatically size, position and implant the tibial tray in each tibia, and 328 models were successfully implanted and analysed. The peak strain in the bone of the resected surface was examined and the percentage surface area of bone above yield strain (PSAY) was used to determine the risk of failure of a model. Using an arbitrary threshold of 10% PSAY, the models were divided into two groups ('higher risk' and 'lower risk') in order to explore factors that may influence potential failure. In this study, 17% of models were in the 'higher risk' group and it was found that these models had a lower elastic modulus (mean 275.7MPa), a higher weight (mean 85.3kg), and larger peak loads, of which the axial force was the most significant. This study showed the mean peak strain of the resected surface and PSAY were not significantly different between implant sizes.

In the ongoing debate about gender-specific (GS) vs. traditional knee implants, there is limited information about patella-specific outcomes. GS femoral component features should provide better patellar tracking, but techniques have not existed previously to test this accurately. Using novel computed tomography and radiography imaging protocols, 15 GS knees were compared to 10 traditional knees, for the 6 degrees of freedom of the patellofemoral and tibiofemoral joints throughout the range of motion, plus other geometric measures and quality of life (QOL). Significant differences were found for patellar medial/lateral shift, where the patella was shifted more laterally for the GS femoral component. Neither group demonstrated patellar maltracking. There were no other significant differences in this well-functioning group.

Using a three-dimensional (3D) modality to image patients' knees before and after total knee arthroplasty (TKA) allows researchers and clinicians to evaluate causes of pain after TKA, differences in implant design, and changes in the articular geometry as a result of surgery. Computed tomography (CT) has not been fully utilized to date for evaluating the knee after TKA due to metal artifacts obscuring part of the image. We describe an accurate, validated protocol, which has been implemented in vivo, that improves visibility of the patellofemoral joint, matches implant models automatically in 3D, segments preoperative bone semi-automatically, detects and sets coordinate systems automatically, determines the six degrees of freedom of knee pose and geometry, and allows for multiple other measurements that are clinically relevant. Subjects are imaged at 0° and 30° knee flexion, while pushing on a custom-made knee rig to provide partial loadbearing. With some modifications, the protocol can be adopted by any group with access to a CT scanner and image analysis software, allowing for the investigation of numerous clinical and biomechanical questions.