In Vitro Testing of Femoral Impaction Grafting With Porous Titanium Particles: A Pilot Study

The disadvantages of allografts to restore femoral bone defects during revision hip surgery have led to the search for alternative materials. We investigated the feasibility of using porous titanium particles and posed the following questions: (1) Is it possible to create a high-quality femoral graft of porous titanium particles in terms of graft thickness, cement thickness, and cement penetration? (2) Does this titanium particle graft layer provide initial stability when a femoral cemented stem is implanted in it? (3) What sizes of particles are released from the porous titanium particles during impaction and subsequent cyclic loading of the reconstruction? We simulated cemented revision reconstructions with titanium particles in seven composite femurs loaded for 300,000 cycles and measured stem subsidence. Particle release from the titanium particle grafts was analyzed during impaction and loading. Impacted titanium particles formed a highly interlocked graft layer. We observed limited cement penetration into the titanium particle graft. A total mean subsidence of 1.04 mm was observed after 300,000 cycles. Most particles released during impaction were in the phagocytable range (< 10 μm). There was no detectable particle release during loading. Based on the data, we believe titanium particles are a promising alternative for allografts. However, animal testing is warranted to investigate the biologic effect of small-particle release

Dynamic Computed Tomography Angiography for capturing vessel wall motion:A phantom study for optimal image reconstruction

Background Reliably capturing sub-millimeter vessel wall motion over time, using dynamic Computed Tomography Angiography (4D CTA), might provide insight in biomechanical properties of these vessels. This may improve diagnosis, prognosis, and treatment decision making in vascular pathologies. Purpose The aim of this study is to determine the most suitable image reconstruction method for 4D CTA to accurately assess harmonic diameter changes of vessels. Methods An elastic tube (inner diameter 6 mm, wall thickness 2 mm) was exposed to sinusoidal pressure waves with a frequency of 70 beats-per-minute. Five flow amplitudes were set, resulting in increasing sinusoidal diameter changes of the elastic tube, measured during three simulated pulsation cycles, using ECG-gated 4D CTA on a 320-detector row CT system. Tomographic images were reconstructed using one of the following three reconstruction methods: hybrid iterative (Hybrid-IR), model-based iterative (MBIR) and deep-learning based (DLR) reconstruction. The three reconstruction methods where based on 180 degrees (half reconstruction mode) and 360 degrees (full reconstruction mode) raw data. The diameter change, captured by 4D CTA, was computed based on image registration. As a reference metric for diameter change measurement, a 9 MHz linear ultrasound transducer was used. The sum of relative absolute differences (SRAD) between the ultrasound and 4D CTA measurements was calculated for each reconstruction method. The standard deviation was computed across the three pulsation cycles. Results MBIR and DLR resulted in a decreased SRAD and standard deviation compared to Hybrid-IR. Full reconstruction mode resulted in a decreased SRAD and standard deviations, compared to half reconstruction mode. Conclusions 4D CTA can capture a diameter change pattern comparable to the pattern captured by US. DLR and MBIR algorithms show more accurate results than Hybrid-IR. Reconstruction with DLR is &gt;3 times faster, compared to reconstruction with MBIR. Full reconstruction mode is more accurate than half reconstruction mode.</p

Augmented reality—The way forward in patient education for intracranial aneurysms? A qualitative exploration of views, expectations and preferences of patients suffering from an unruptured intracranial aneurysm regarding augmented reality in patient education

Objectives: The goal of this project is to explore the views, expectations and preferences of patients with an unruptured intracranial aneurysm regarding the use of AR in patient education.Methods: To gain an in-depth understanding of the patients’ perspective, a face-to-face interview study was conducted using an interview protocol with a predefined topic list. All interviews were audio-recorded and transcribed verbatim afterwards. Transcripts were analyzed using thematic content analyses. Coding was performed using Atlas.ti software.Results: Seventeen interviews were conducted. The views, expectations and preferences of patients regarding patient education with AR could be subdivided into 15 categories, which could be grouped into 4 general themes: 1) experiences with current patient education, 2) expectations of AR in patient education, 3) opportunities and limitations of AR, and 4) out-of-hospital use of an AR application. Patients’ expectations were predominantly positive regarding improving patients’ understanding of their medical situation and doctor-patient communication.Discusssion: This study suggests that patients with unruptured intracranial aneurysms are open to receive patient education regarding their disease with AR. Patients expect that AR models can help patients with intra-cranial aneurysms better understand their disease, treatment options and risks. Additionally, patients expect AR could improve doctor-patient communication

Combining deep learning with 3D stereophotogrammetry for craniosynostosis diagnosis

Craniosynostosis is a condition in which cranial sutures fuse prematurely, causing problems in normal brain and skull growth in infants. To limit the extent of cosmetic and functional problems, swift diagnosis is needed. The goal of this study is to investigate if a deep learning algorithm is capable of correctly classifying the head shape of infants as either healthy controls, or as one of the following three craniosynostosis subtypes; scaphocephaly, trigonocephaly or anterior plagiocephaly. In order to acquire cranial shape data, 3D stereophotographs were made during routine pre-operative appointments of scaphocephaly (n = 76), trigonocephaly (n = 40) and anterior plagiocephaly (n = 27) patients. 3D Stereophotographs of healthy infants (n = 53) were made between the age of 3–6 months. The cranial shape data was sampled and a deep learning network was used to classify the cranial shape data as either: healthy control, scaphocephaly patient, trigonocephaly patient or anterior plagiocephaly patient. For the training and testing of the deep learning network, a stratified tenfold cross validation was used. During testing 195 out of 196 3D stereophotographs (99.5%) were correctly classified. This study shows that trained deep learning algorithms, based on 3D stereophotographs, can discriminate between craniosynostosis subtypes and healthy controls with high accuracy

Navigating PROSPERO4animals: 10 top tips for efficient pre-registration of your animal systematic review protocol

Abstract Systematic reviews are an essential tool in identifying knowledge gaps and synthesizing evidence from in vivo animal research to improve human health. The review process follows an explicit and systematic methodology to minimize bias, but is not immune to biases or methodological flaws. Pre-registering a systematic review protocol has several benefits, including avoiding unplanned duplication of reviews, reducing reporting biases, and providing structure throughout the review process. It also helps to align the opinions of review team members and can shield researchers from post-hoc critique. PROSPERO4animals is the international prospective register of systematic reviews (PROSPERO) for the preregistration of systematic review of animal studies. As administrators, here we provide 10 tips to facilitate pre-registration in PROSPERO4animals. These tips address common difficulties that both beginners and experienced researchers may face when pre-registering their systematic review protocols. This article aims to help authors write and register a detailed systematic review protocol on PROSPERO4animals

Aneurysm-on-a-Chip: Setting Flow Parameters for Microfluidic Endothelial Cultures Based on Computational Fluid Dynamics Modeling of Intracranial Aneurysms

Intracranial aneurysms are pouch-like extrusions from the vessels at the base of the brain which can rupture and cause a subarachnoid hemorrhage. The pathophysiological mechanism of aneurysm formation is thought to be a consequence of blood flow (hemodynamic) induced changes on the endothelium. In this study, the results of a personalized aneurysm-on-a-chip model using patient-specific flow parameters and patient-specific cells are presented. CT imaging was used to calculate CFD parameters using an immersed boundary method. A microfluidic device either cultured with human umbilical vein endothelial cells (HUVECs) or human induced pluripotent stem cell-derived endothelial cells (hiPSC-EC) was used. Both types of endothelial cells were exposed for 24 h to either 0.03 Pa or 1.5 Pa shear stress, corresponding to regions of low shear and high shear in the computational aneurysm model, respectively. As a control, both cell types were also cultured under static conditions for 24 h as a control. Both HUVEC and hiPSC-EC cultures presented as confluent monolayers with no particular cell alignment in static or low shear conditions. Under high shear conditions HUVEC elongated and aligned in the direction of the flow. HiPSC-EC exhibited reduced cell numbers, monolayer gap formation and cells with aberrant, spread-out morphology. Future research should focus on hiPSC-EC stabilization to allow personalized intracranial aneurysm models