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We present a framework with two options for selecting a subgroup of training cases for intracranial aneurysm (IA) treatment. Option one, general training, describes training cases that represent a variety of different IAs that represent the diversity of real world cases. This can be achieved via instance selection (IS), which reduces size of a dataset by eliminating redundancies via outlier removal and clustering. Option two, a specific training scenario, describes training that is specialized based on IA features of a specific case, for which we present the novel reverse instance selection (RIS), which introduces similarity to the specific case to the IS methodology. We evaluated our IS and RIS by comparing them to subsets selected based on similarity (SIM) and random sampling (RndS). RIS outperformed SIM and RndS in 79% of experiments. IS outperformed RndS in 33% of experiments. In both scenarios, we observed that our approaches, which balance the weaknesses of SIM and RndS, perform best for small subset sizes close to the database cluster size. Our IS and RIS are flexible in regards to the underlying machine learning and weighting of metrics for evaluation, thus providing a way to select a representative and diverse subset not just for IAs, but also for different kinds of data.

We present a novel tool designed for the semiautomatic detection and assessment of prostate cancer during recurrence diagnostics using PET-CT with prostate-specific membrane antigen (PSMA). The tool automatically generates a structured report, which is enhanced by 3D images and ensures the reproducibility of the findings. Moreover, the area of the findings is automatically determined and can be corrected manually. Image data from 50 patients following radical prostatectomy was used. Our approach and its user interface were qualitatively evaluated by a nuclear medicine specialist. The segmentation analysis revealed a requirement for further automation. The resulting report was deemed highly beneficial, particularly in terms of the resulting reproducibility and the presentation of 3D images depicting the findings. The presented tool has great potential for much-needed support in everyday clinical practice, as it facilitates the communication of the diagnostic results to colleagues and patients and thus prevents misunderstandings.

Intracranial mirror aneurysms are pathologic dilatations of cerebral arteries that occur at identical locations in both hemispheres. They do not always have identical sizes, shapes, or rupture states, despite identical patient-specific risk factors. As a subgroup of multiple aneurysms and thus small amounts of data, clinical research about their causes and development has not been conclusive. Using eight patients with 16 mirror aneurysms with different rupture states, we investigated differences between the hemispheres. We virtually performed stitching: detaching the aneurysm domes to place them on the opposite parent vessel to assess the influence of aneurysm morphology and upstream parent vessel shape on hemodynamics. In the unaltered datasets, we found that blood flow within aneurysms in the left hemisphere has higher wall shear stress and velocity. After stitching, we found that both upstream parent vessel as well as aneurysm morphology influence hemodynamics. Morphologic parameters like size, undulation index, and aneurysm angle had a higher influence. In a short rupture risk analysis we found a correlation between rupture and aspect ratio and non-sphericity index. Overall, we found possible indicators for mirror aneurysm analysis that illustrated the importance of morphological analysis, though more datasets are necessary for conclusive statements about special treatment for mirror aneurysms.

Simulations and measurements of blood and airflow inside the human circulatory and respiratory system play an increasingly important role in personalized medicine for prevention, diagnosis and treatment of diseases. This survey focuses on three main application areas. (1) Computational fluid dynamics (CFD) simulations of blood flow in cerebral aneurysms assist in predicting the outcome of this pathologic process and of therapeutic interventions. (2) CFD simulations of nasal airflow allow for investigating the effects of obstructions and deformities and provide therapy decision support. (3) 4D phase‐contrast (4D PC) magnetic resonance imaging of aortic haemodynamics supports the diagnosis of various vascular and valve pathologies as well as their treatment. An investigation of the complex and often dynamic simulation and measurement data requires the coupling of sophisticated visualization, interaction and data analysis techniques. In this paper, we survey the large body of work that has been conducted within this realm. We extend previous surveys by incorporating nasal airflow, addressing the joint investigation of blood flow and vessel wall properties and providing a more fine‐granular taxonomy of the existing techniques. From the survey, we extract major research trends and identify open problems and future challenges. The survey is intended for researchers interested in medical flow but also more general, in the combined visualization of physiology and anatomy, the extraction of features from flow field data and feature‐based visualization, the visual comparison of different simulation results and the interactive visual analysis of the flow field and derived characteristics. Simulations and measurements of blood and airflow inside the human circulatory and respiratory system play an increasingly important role in personalized medicine for prevention, diagnosis and treatment of diseases. This survey focuses on three main application areas. (1) Computational fluid dynamics (CFD) simulations of blood flow in cerebral aneurysms assist in predicting the outcome of this pathologic process and of therapeutic interventions. (2) CFD simulations of nasal airflow allow for investigating the effects of obstructions and deformities and provide therapy decision support. (3) 4D phase‐contrast (4D PC) magnetic resonance imaging of aortic haemodynamics supports the diagnosis of various vascular and valve pathologies as well as their treatment. An investigation of the complex and often dynamic simulation and measurement data requires the coupling of sophisticated visualization, interaction and data analysis techniques. [ABSTRACT FROM AUTHOR]

Background Computational fluid dynamics (CFD) blood flow predictions in intracranial aneurysms promise great potential to reveal patient-specific flow structures. Since the workflow from image acquisition to the final result includes various processing steps, quantifications of the individual introduced potential error sources are required. Methods Three-dimensional (3D) reconstruction of the acquired imaging data as input to 3D model generation was evaluated. Six different reconstruction modes for 3D digital subtraction angiography (DSA) acquisitions were applied to eight patient-specific aneurysms. Segmentations were extracted to compare the 3D luminal surfaces. Time-dependent CFD simulations were carried out in all 48 configurations to assess the velocity and wall shear stress (WSS) variability due to the choice of reconstruction kernel. Results All kernels yielded good segmentation agreement in the parent artery; deviations of the luminal surface were present at the aneurysm neck (up to 34.18%) and in distal or perforating arteries. Observations included pseudostenoses as well as noisy surfaces, depending on the selected reconstruction kernel. Consequently, the hemodynamic predictions show a mean SD of 11.09% for the aneurysm neck inflow rate, 5.07% for the centerline-based velocity magnitude, and 17.83%/9.53% for the mean/max aneurysmal WSS, respectively. In particular, vessel sections distal to the aneurysms yielded stronger variations of the CFD values. Conclusions The choice of reconstruction kernel for DSA data influences the segmentation result, especially for small arteries. Therefore, if precise morphology measurements or blood flow descriptions are desired, a specific reconstruction setting is required. Furthermore, research groups should be encouraged to denominate the kernel types used in future hemodynamic studies. [ABSTRACT FROM AUTHOR]

Abstract: Medical visualizations are highly adapted to a specific medical application scenario. Therefore, many researchers conduct qualitative evaluations with a low number of physicians or medical experts to assess the benefits of their visualization technique. Although this type of research has advantages, it is difficult to reproduce and can be subjectively biased. This makes it problematic to quantify the benefits of a new visualization technique. Quantitative evaluation can objectify research and help bringing new visualization techniques into clinical practice. To support researchers, we present guidelines to quantitatively evaluate medical visualizations, considering specific characteristics and difficulties. We demonstrate the adaptation of these guidelines on the example of comparative aneurysm surface visualizations. We developed three visualization techniques to compare aneurysm volumes. The visualization techniques depict two similar, but not identical aneurysm surface meshes. In a user study with 34 participants and five aneurysm data sets, we assessed objective measures (accuracy and required time) and subjective ratings (suitability and likeability). The provided guidelines and presentation of different stages of the evaluation allow for an easy adaptation to other application areas of medical visualization. [ABSTRACT FROM AUTHOR]

Background and Objectives: Traditional neurosurgical education has relied heavily on the Halstedian "see one, do one, teach one" approach which is increasingly perceived as inefficient in contemporary settings marked by a steady decline in surgical caseload. In recent years, simulation training has emerged as an effective and accessible training alternative. To date, however, there is no standardized criterion pertaining to the quality and implementation of simulators in neurosurgical education and training. This research aims to compare the efficacy of virtual reality (VR) and Phantom-based simulation training in the context of neurosurgical skill acquisition, with a focus on middle cerebral artery aneurysm clipping., Methods: An immersive VR clipping tool and a haptic clipping simulator incorporating 3-dimensional printing, additive manufacturing, and rheological analyses were developed. Twenty-two participants, comprising 12 medical students, 6 neurosurgical residents, and 4 experienced neurosurgeons, tested and evaluated both simulators for face and content validity. Construct and predictive validity of the simulators were assessed using an objective structured assessment scale for aneurysm clipping, measuring participants' performances and progress., Results: Both modalities were deemed highly advantageous for educational purposes. Objective evaluations, however, revealed measurable differences in usability, efficacy, and transferability of the learned skills with VR excelling in procedural planning and visualization while Phantom simulation being noticeably superior in conveying surgical skills., Conclusion: Simulation training can accelerate the neurosurgical learning curve. The results of this study highlight the importance of establishing standardized criteria for the implementation and assessment of simulation modalities, ensuring consistent quality and efficacy in neurosurgical education., (Copyright © Congress of Neurological Surgeons 2024. All rights reserved.)

Deep learning-based image analysis offers great potential in clinical practice. However, it faces mainly two challenges: scarcity of large-scale annotated clinical data for training and susceptibility to adversarial data in inference. As an example, an artificial intelligence (AI) system could check patient positioning, by segmenting and evaluating relative positions of anatomical structures in medical images. Nevertheless, data to train such AI system might be highly imbalanced with mostly well-positioned images being available. Thus, we propose the use of synthetic X-ray images and annotation masks forward projected from 3D photon-counting CT volumes to create realistic non-optimally positioned X-ray images for training. An open-source model (TotalSegmentator) was used to annotate the clavicles in 3D CT volumes. We evaluated model robustness with respect to the internal (simulated) patient rotation α on real-data-trained models and real&synthetic-data-trained models. Our results showed that real&synthetic- data-trained models have Dice score percentage improvements of 3% to 15% across different α groups compared to the real-data-trained model. Therefore, we demonstrated that synthetic data could be supplementary used to train and enrich heavily underrepresented conditions to increase model robustness., (© 2024. The Author(s).)

Interventional neuroradiologists carry out their minimally-invasive procedure by using X-rays within the setup of a Bi-plane Digital Subtraction Angiography. This work provides an immersive virtual reality (VR) environment where the physicians can perform an simulated catheter-based intervention. Since radiation is invisible, the risk of radiation exposure can be enhanced virtually. Our goal is to see whether radiation visualization influences medical professionals such that they take a more mindful approach towards interactions on the operating table then without one. We tested our scenario within an expert study where ten neuroradiologists participated and solved intervention-related tasks. Our expert study found that while visualization does not affect the placement of the radiation shield by the physician, the overall radiation exposure using visualization does decrease as users standing very close move to a greater distance from the table. Furthermore, our System Usability Scale evaluation revealed a high score for this approach's usability., Competing Interests: Declaration of competing interest The authors declare that they have no conflict of interest., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Purpose: Most recently transformer models became the state of the art in various medical image segmentation tasks and challenges, outperforming most of the conventional deep learning approaches. Picking up on that trend, this study aims at applying various transformer models to the highly challenging task of colorectal cancer (CRC) segmentation in CT imaging and assessing how they hold up to the current state-of-the-art convolutional neural network (CNN), the nnUnet. Furthermore, we wanted to investigate the impact of the network size on the resulting accuracies, since transformer models tend to be significantly larger than conventional network architectures., Methods: For this purpose, six different transformer models, with specific architectural advancements and network sizes were implemented alongside the aforementioned nnUnet and were applied to the CRC segmentation task of the medical segmentation decathlon., Results: The best results were achieved with the Swin-UNETR, D-Former, and VT-Unet, each transformer models, with a Dice similarity coefficient (DSC) of 0.60, 0.59 and 0.59, respectively. Therefore, the current state-of-the-art CNN, the nnUnet could be outperformed by transformer architectures regarding this task. Furthermore, a comparison with the inter-observer variability (IOV) of approx. 0.64 DSC indicates almost expert-level accuracy. The comparatively low IOV emphasizes the complexity and challenge of CRC segmentation, as well as indicating limitations regarding the achievable segmentation accuracy., Conclusion: As a result of this study, transformer models underline their current upward trend in producing state-of-the-art results also for the challenging task of CRC segmentation. However, with ever smaller advances in total accuracies, as demonstrated in this study by the on par performances of multiple network variants, other advantages like efficiency, low computation demands, or ease of adaption to new tasks become more and more relevant., (© 2024. CARS.)

Background/Objectives: Microwave ablation (MWA) is the leading therapy method for treating patients with liver cancer. MWA simulation is used to further improve the therapy and to help develop new devices. Methods: A water-cooled ablation needle was reconstructed. MWA simulations of a polyacrylamide phantom were carried out and compared with a representative clinical example (tumor diameter: 8.75 mm). The Arrhenius damage model and a critical temperature approach of 60 °C were applied to assess the necrosis zones. Finally, the simulation results were compared to the corresponding MR measurements. Results: Most of the heating in the simulation took place at a distance of 5 mm along the transverse axis and 20 mm along the longitudinal axis above the needle tip. The calculated Dice scores for the Arrhenius model were 0.77/0.53 for the phantom/clinical case. For the critical temperature approach, Dice scores of 0.60/0.66 for the phantom/clinical case were achieved. Conclusions: The comparison between simulated and measured temperature increases showed an excellent agreement. However, differences in the predicted necrosis volume might be caused by omitting consideration of the heat sink effect, especially in the clinical case. Nevertheless, this workflow enables short MWA simulation times (approximately 3 min) and demonstrates a step towards possible integration into daily clinical use.

Background: Aneurysmal subarachnoid hemorrhage (SAH) predominantly affects women, accounting for 65% of cases. Women have a 1.3 times higher relative risk than men, with the incidence rising particularly in women aged 55-85 years. Women also have a higher prevalence of unruptured intracranial aneurysms (IAs), especially after the age of 50 years, and are at greater risk of aneurysm growth and rupture. This study aimed to isolate the influence of sex on rupture rate, bleeding severity, functional outcomes, and complications by using a matched cohort, while also examining the impact of sex on aneurysm localization and multiplicity. Methods: We utilized a retrospectively collected database of 300 patients with 511 IAs. Inclusion criteria included the availability of clinical data and 3D angiography for semi-automatic reconstruction of IA morphology. Female patients and their IA were matched with male patients according to clinical parameters and 21 morphological characteristics using an interactive visual exploration tool for multidimensional matching. Results: Contrary to previously published results, our study found no significant sex differences in rupture rates or vasospasm rates between male and female patients. The severity of SAH, functional outcomes, and complications such as hydrocephalus were also similar in women and men. However, women exhibited a higher prevalence of multiple aneurysms and distinct localization patterns. Conclusions: This study underscores the complex role of sex in IA development and rupture. Although sex-specific biological factors influence aneurysm characteristics, they do not necessarily translate into differences in clinical outcomes. Further research is needed to explore these factors and their impact on aneurysm development and management.

Decades of iteration on scientific imaging hardware and software has yielded an explosion in not only the size, complexity, and heterogeneity of image datasets but also in the tooling used to analyze this data. This wealth of image analysis tools, spanning different programming languages, frameworks, and data structures, is itself a problem for data analysts who must adapt to new technologies and integrate established routines to solve increasingly complex problems. While many "bridge" layers exist to unify pairs of popular tools, there exists a need for a general solution to unify new and existing toolkits. The SciJava Ops library presented here addresses this need through two novel principles. Algorithm implementations are declared as plugins called Ops, providing a uniform interface regardless of the toolkit they came from. Users express their needs declaratively to the Op environment, which can then find and adapt available Ops on demand. By using these principles instead of direct function calls, users can write streamlined workflows while avoiding the translation boilerplate of bridge layers. Developers can easily extend SciJava Ops to introduce new libraries and more efficient, specialized algorithm implementations, even immediately benefitting existing workflows. We provide several use cases showing both user and developer benefits, as well as benchmarking data to quantify the negligible impact on overall analysis performance. We have initially deployed SciJava Ops on the Fiji platform, however it would be suitable for integration with additional analysis platforms in the future., Competing Interests: Authors DK, MW, CB, SH, AW, and MB were employed by KNIME GmbH. Author JS was employed by Microsoft Corporation. Author BN was employed by True North Intelligent Algorithms. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision., (Copyright © 2024 Selzer, Rueden, Hiner, Evans, Kolb, Wiedenmann, Birkhold, Buchholz, Helfrich, Northan, Walter, Schindelin, Pietzsch, Saalfeld, Berthold and Eliceiri.)

The surgical management of anterior communicating artery aneurysms (AcomA) is challenging due to their deep midline position and proximity to complex skull base anatomy. This study compares the pterional craniotomy with the interhemispheric approach based on the specific aneurysm angulation. A total of 129 AcomA cases were analyzed, with 50 undergoing microsurgical clipping via either the pterional or interhemispheric approach. All selected cases had computed tomography-angiography with sagittal imaging slices and 2D-angiography. Using an interactive tool, 14 cases treated via the interhemispheric approach were matched with 14 cases approached pterionally based on clinical and morphological parameters, emphasizing intracranial aneurysm (IA) dome angulation relative to the frontal skull base. Outcomes included IA occlusion, temporary clipping incidence, intraoperative rupture, postoperative strokes, hemorrhages, hydrocephalus, vasospasm, and patient functionality. Matched cohorts had consistent demographics. Both approaches resulted in similar IA occlusion rates, but the interhemispheric approach led to improved clinical outcomes, measured by the modified Rankin Scale. It also had a lower incidence of hydrocephalus and reduced need for permanent ventriculoperitoneal shunt placement. Vasospasms and postoperative infarction rates were comparable between the groups. Our findings suggest potential advantages of the interhemispheric approach in managing AcomA, depending on aneurysm angulation. Despite a small sample size, the results highlight the importance of customized surgical decision-making based on the unique traits of each aneurysm and the surgeon's expertise., (© 2024. The Author(s).)

Vision provides animals with detailed information about their surroundings, conveying diverse features such as color, form, and movement across the visual scene. Computing these parallel spatial features requires a large and diverse network of neurons, such that in animals as distant as flies and humans, visual regions comprise half the brain's volume. These visual brain regions often reveal remarkable structure-function relationships, with neurons organized along spatial maps with shapes that directly relate to their roles in visual processing. To unravel the stunning diversity of a complex visual system, a careful mapping of the neural architecture matched to tools for targeted exploration of that circuitry is essential. Here, we report a new connectome of the right optic lobe from a male Drosophila central nervous system FIB-SEM volume and a comprehensive inventory of the fly's visual neurons. We developed a computational framework to quantify the anatomy of visual neurons, establishing a basis for interpreting how their shapes relate to spatial vision. By integrating this analysis with connectivity information, neurotransmitter identity, and expert curation, we classified the ~53,000 neurons into 727 types, about half of which are systematically described and named for the first time. Finally, we share an extensive collection of split-GAL4 lines matched to our neuron type catalog. Together, this comprehensive set of tools and data unlock new possibilities for systematic investigations of vision in Drosophila , a foundation for a deeper understanding of sensory processing.

Purpose: The contour neurovascular system (CNS) is a novel device to treat intracranial wide-necked bifurcation aneurysms, with few studies assessing its long-term effects. Particularly its impact on aneurysm morphology has not been explored yet. We present a preliminary study to explore this impact for the first time, focusing on the neck curve and ostium of the aneurysm., Methods: We investigated seven aneurysms treated with the CNS to assess ostium deformation after CNS deployment by comparing models extracted from in vivo medical pre-treatment and follow-up scans via morphological analysis. Time between pre- and follow-up scans was ten months on average. Size and shape indices like area, neck diameter, ellipticity index, undulation index, and more were assessed., Results: Ostium size was reduced after treatment. On average, ostium area was reduced at a rate of - 0.58 (± 4.88) mm 2 per year, from 15.52 (± 3.51) mm 2 to 13.30 (± 2.27) mm 2 , and ostium width from 5.01 (± 0.54) mm to 4.49 (± 0.45) mm, with an average reduction of - 0.59 (± 0.87) mm. This shrinking positively correlated with time passing. Shape deformation was low, though notably mean ellipticity index was reduced by 0.06 (± 0.15) on average, indicating ostia were less elongated after treatment., Conclusion: We interpret the shrinking of the ostium as part of the healing process. Shape changes were found to be small enough to conclude no shape deformation of the ostium from CNS deployment, but the analysis of more cases with more parameters and information is necessary., (© 2024. The Author(s).)