Role In Navigation Research Articles

The Role of Peer Support and Patient Navigation for Empowerment in Breast Cancer Survivors: Implications for Community Cancer Control.

Community-based organizations (CBO) offer support, including patient navigation (PN), to women at-risk for (e.g., those with BRCA pathogenic variants) and surviving with breast cancer. However, the impacts of CBO efforts on survivors' empowerment (e.g., control, self-confidence, knowledge/skills, coping) are largely unknown. As part of a quality improvement initiative (N=2,247) focused on PN, care satisfaction, peer support, and quality of life (QoL), we conducted a secondary analysis of a CBO care delivery model on women's empowerment. Under CBO-led cancer control, empowerment was high: most survivors felt confident in (71.2%) and knowledgeable about (66.4%) managing their care. Perceived care quality was also high (91%): it was recommendable to others (93.9%), helpful (92.7%), informative (92.6%), timely (92.2%), reliable (91.5%), supportive (91.3%), and effective (88.7%). Regarding CBO care satisfaction, survivors felt supported by abundant resources (92.8%) and programs (91.2%), understood (92.0%), and helped (91.6%). Peer support (offered to >25%) demonstrated high engagement (>85%). Regarding QoL, 25.3% were in fair/poor health and 25.6% endorsed frequent mental distress (M=7.2 physically unhealthy days, M=7.8 mentally unhealthy days, and M=6.4 activity-limited days within the past month). Disparities in empowerment were observed as a function of survivors' QoL: lowest among those with more frequent mental distress (t=-2.13, p<.05), mentally unhealthy days (r=-.083, p<.05), and activity-limited days (r=-.058, p<.05)). These burdens may have influenced survivors' feelings of empowerment, especially among those without peer support (t=3.77, p<.001), who downgraded the quality of PN (t=.60, p<.01), and were least satisfied with CBO cancer control (t=.57, p<.01). In a multivariable model adjusting for mental distress, both perceived PN quality (B=.16, SE=.01, p<.001) and peer support (B=.24, SE=.13, p=.05) were positively associated with empowerment: survivors who rated their PN higher, and offered peer support, felt more empowered. CBO cancer control can uplift most survivors: addressing socially determined disparities, through programs such as peer support, may enhance their effectiveness and particularly among those with poor mental health.

Navigating a Hostile Medium: Observations of the Environment As an Aid to Oceanic Voyaging in the Age of Sail

AbstractEuropean navigation in the age of sail owes much to the scientific revolution of the seventeenth century and the development of instruments and advanced mathematical techniques. Important though these developments were, it is argued here that close observation of the environment: of the weather, ocean currents, clouds, birds, mammals, and a host of other factors played a far more important role in safe navigation from one part of the globe to another.

28 Impact of a Radiology cancer navigator role in conjunction with a chest reporting radiographer service on the lung cancer pathway

28 Impact of a Radiology cancer navigator role in conjunction with a chest reporting radiographer service on the lung cancer pathway

Advancing the Care Experience for patients receiving Palliative care as they Transition from hospital to Home (ACEPATH): Codesigning an intervention to improve patient and family caregiver experiences.

Returning home from the hospital for palliative-focused care is a common transition, but the process can be emotionally distressing and logistically challenging for patients and caregivers. While interventions exist to aid in the transition, none have been developed in partnership with patients and caregivers. To undergo the initial stages of codesign to create an intervention (Advancing the Care Experience for patients receiving Palliative care as they Transition from hospital to Home [ACEPATH]) to improve the experience of hospital-to-home transitions for adult patients receiving palliative care and their caregiver(s). The codesign process consisted of (1) the development of codesign workshop (CDW) materials to communicate key findings from prior research to CDW participants; (2) CDWs with patients, caregivers and healthcare providers (HCPs); and (3) low-fidelity prototype testing to review CDW outputs and develop low-fidelity prototypes of interventions. HCPs provided feedback on the viability of low-fidelity prototypes. Three patients, seven caregivers and five HCPs participated in eight CDWs from July 2022 to March 2023. CDWs resulted in four intervention prototypes: a checklist, quick reference sheets, a patient/caregiver workbook and a transition navigator role. Outputs from CDWs included descriptions of interventions and measures of success. In April 2023, the four prototypes were presented in four low-fidelity prototype sessions to 20 HCPs. Participants in the low-fidelity prototype sessions provided feedback on what the interventions could look like, what problems the interventions were trying to solve and concerns about the interventions. Insights gained from this codesign work will inform high-fidelity prototype testing and the eventual implementation and evaluation of an ACEPATH intervention that aims to improve hospital-to-home transitions for patients receiving a palliative approach to care. Patients and caregivers with lived experience attended CDWs aimed at designing an intervention to improve the transition from hospital to home. Their direct involvement aligns the intervention with patients' and caregivers' needs when transitioning from hospital to home. Furthermore, four patient/caregiver advisors were engaged throughout the project (from grant writing through to manuscript writing) to ensure all stages were patient- and caregiver-centred.

AONN+ Navigation Metrics That Support the Oncology Navigation Standards of Professional Practice

ObjectivesTo offer a comprehensive overview of the critical elements contributing to the achievements of oncology navigation, address challenges in standardized implementation, and examine recent advancements influencing the acknowledgment and reimbursement of navigation services. Lastly, the AONN+ 35 evidence-based navigation metrics will be shared, emphasizing the five core metrics that should be utilized by all navigation models in all settings. MethodsEmployed in this review involves synthesizing information from established oncology organizations, documenting the development of navigator professional standards of practice and navigation metrics that measure patient experience, clinical outcomes, and return on investment, and analyzing outcomes from national studies and collaborations to present a summary of advancements in oncology navigation. ResultsThe key components vital for ensuring the enduring success of programs encompass the core competencies of navigators, adherence to standards of navigation practice set by the Professional Oncology Navigation Taskforce, and the establishment of well-defined metrics specific to oncology navigation. ConclusionsDespite these advancements, challenges persist in implementing and recognizing the newly defined standards and metrics. Effective solutions involve aligning navigation programs with leadership, integrating standards into daily practice, defining navigator roles, measuring navigation program outcomes through defined metrics, and leveraging certifications. Standardized measurement and practice are imperative for national policy development and reimbursement models, aligning with the Cancer Moonshot's goal of high-quality, patient-centered, and cost-effective cancer care. Implications for Nursing PracticeTo contribute to standardizing measurement and practice in oncology navigation for national policy development and reimbursement models.

Accurate semantic segmentation of small-body craters for navigation

Feature extraction and matching play integral roles in autonomous vision navigation. As a typical morphological feature, craters can be used as navigation landmarks. However, the spin of small bodies introduces substantial variations in illumination and viewing angles within acquired images, thereby posing challenges to feature extraction and matching algorithms. Addressing these challenges, a deep learning-based approach emerges as pivotal in mitigating the limitations of existing navigation algorithms. This paper presents an algorithm designed to segment noteworthy craters and irregular regions on such small bodies, thereby furnishing crucial autonomous navigation data for missions involving uncharted terrains. By seamlessly integrating deep learning techniques with conventional computer vision-based feature description methods, the algorithm achieves matching segmentation results of noteworthy precision. The experimental results show that the algorithm has better results compared to the existing mainstream segmentation networks. And it can achieve the accurate matching of segmentation results.

Role of Neuro Navigation in Enhancing Surgical Precision: A Single-Center Experience – A Comprehensive Review Article

Background: Neuronavigation represents a transformative advance in neurosurgery, combining advanced imaging, navigation systems, and software algorithms to guide surgical procedures with high precision. Its integration into clinical practice has revolutionized the approach to complex neurosurgical interventions, enhancing the accuracy of tumor resections, vascular interventions, and spine surgeries, among others. Objective: This review aims to assess the role of Neuronavigation in enhancing surgical precision and improving patient outcomes, with a particular focus on its application and impact at Shifa International Hospital, Islamabad, Pakistan. Methods: A narrative review was conducted, employing a comprehensive search strategy across databases including PubMed, Scopus, and Web of Science. Studies were selected based on predefined inclusion and exclusion criteria, focusing on the use of Neuronavigation in neurosurgery, its clinical outcomes, technological advancements, and challenges. Results: Neuronavigation has been instrumental in improving surgical outcomes, with applications ranging from tumor resection to deep brain stimulation. At Shifa International Hospital, the integration of Neuronavigation has led to a notable enhancement in surgical precision and patient safety, as evidenced by a 95% success rate in over 500 neurosurgical procedures. Despite its benefits, challenges such as technical limitations and high costs persist, highlighting the need for ongoing innovation and training. Conclusion: Neuronavigation significantly improves surgical precision and patient outcomes in neurosurgery. The experience at Shifa International Hospital exemplifies its potential to set new standards in surgical care. Future advancements in technology and wider accessibility are essential to fully realize its benefits across the global healthcare landscape.

Unpredictable chronic mild stress shows neuronal remodeling in multipolar projection neurons of hippocampal complex in postnatal chicks.

The hippocampal complex of birds is a narrow-curved strip of tissue that plays a crucial role in learning, memory, spatial navigation, and emotional and sexual behavior. This study was conducted to evaluate the effect of unpredictable chronic mild stress in multipolar neurons of 3-, 5-, 7-, and 9-week-old chick's hippocampal complex. This study revealed that chronic stress results in neuronal remodeling by causing alterations in dendritic field, axonal length, secondary branching, corrected spine number, and dendritic branching at 25, 50, 75, and 100µm. Due to stress, the overall dendritic length was significantly retracted in 3-week-old chick, whereas no significant difference was observed in 5- and 7-week-old chick, but again it was significantly retracted in 9-week-old chick along with the axonal length. So, this study indicates that during initial days of stress exposure, the dendritic field shows retraction, but when the stress continues up to a certain level, the neurons undergo structural modifications so that chicks adapt and survive in stressful conditions. The repeated exposure to chronic stress for longer duration leads to the neuronal structural disruption by retraction in the dendritic length as well as axonal length. Another characteristic which leads to structural alterations is the dendritic spines which significantly decreased in all age groups of stressed chicks and eventually leads to less synaptic connections, disturbance in physiology, and neurology, which affects the learning, memory, and coping ability of an individual.

Independently Trained Multi-Scale Registration Network Based on Image Pyramid.

Image registration is a fundamental task in various applications of medical image analysis and plays a crucial role in auxiliary diagnosis, treatment, and surgical navigation. However, cardiac image registration is challenging due to the large non-rigid deformation of the heart and the complex anatomical structure. To address this challenge, this paper proposes an independently trained multi-scale registration network based on an image pyramid. By down-sampling the original input image multiple times, we can construct image pyramid pairs, and design a multi-scale registration network using image pyramid pairs of different resolutions as the training set. Using image pairs of different resolutions, train each registration network independently to extract image features from the image pairs at different resolutions. During the testing stage, the large deformation registration is decomposed into a multi-scale registration process. The deformation fields of different resolutions are fused by a step-by-step deformation method, thereby addressing the challenge of directly handling large deformations. Experiments were conducted on the open cardiac dataset ACDC (Automated Cardiac Diagnosis Challenge); the proposed method achieved an average Dice score of 0.828 in the experimental results. Through comparative experiments, it has been demonstrated that the proposed method effectively addressed the challenge of heart image registration and achieved superior registration results for cardiac images.

Sea ice detection network for icebreakers in polar environments with attention-based deeplabv3+ architecture

Shipborne sea ice detection aboard icebreakers plays a paramount role in polar navigation. The continuous evolution of deep learning semantic segmentation networks has promoted the advancement of sea ice detection tasks. At this stage, there are relatively few studies on shipboard sea ice detection, and the accuracy of polar sea ice detection will be reduced due to problems such as blurred sea fog and indistinct boundaries. In this study, a shipboard sea ice detection dataset is constructed, and a sea ice detection method that combines multi-branch attention feature alignment and multi-scale feature extraction is proposed. The heterogeneous receptive field enhancement atrous spatial convolution pooling pyramid module is designed, and the feature alignment module based on the attention mechanism is constructed, which strengthens the model’s extraction of sea ice features and elevates representation performance. Experimental results underscore the heightened precision of our approach in sea ice detection, to some extent alleviating the issue of missed detections in new ice. It constitutes a positive contribution towards advancing shipborne sea ice detection in polar environments.

Improving patient outcomes while reducing readmissions with data analytics

As post-acute care spend continues to rise and the Centers for Medicare and Medicaid Services (CMS) moves forward with promoting both value-based and risk-bearing models of care, it is essential for accountable care organisations (ACOs), payers and hospital providers to take proactive measures to find innovative and data-driven strategies to meet the future demands of healthcare. Yet disparate electronic health record (EHR) systems between acute and post-acute providers continue to pose challenges in the ability to access live patient data across care settings, which enables clinical line of sight to manage both patient and population-level quality outcomes. Utilisation of an EHR-agnostic platform, which mitigates interoperability issues, can improve care transitions, provide data analytics to manage the patient care journey, foster seamless implementation of standardised care pathways and ultimately reduce total costs within post-acute networks by decreasing readmissions and length of stay. St. Joseph’s Health implemented such a data analytics platform and instituted a post-acute nurse navigator, social worker and care manager roles to manage their value-based patients in the postacute setting. As a result, their Medicare Shared Savings Plan ACO, Mission Health Coordinated Care, achieved a significant reduction in readmissions from 24 per cent to 17.8 per cent, as well as a total cost of care savings of US$1.6m in its first year. Currently, the readmission rate is down to 13.6 per cent, and there has also been a 3.2-day reduction in average length of stay. Owing to their successful post-acute strategy and programming, the project was scaled to include all patients in value-based contracts.

Research on the technology of intelligent vehicle sensor positioning system in autonomous driving

In this comprehensive exploration of positioning and navigation technologies, we have delved into the intricacies of GPS (Global Positioning System), IMU (Inertial Measurement Unit), and VPS (Visual Positioning Systems) systems, shedding light on their unique attributes and applications. GPS, a global satellite-based system, offers precise positioning on a worldwide scale, although it encounters challenges in complex urban and environmental conditions. Its role in navigation and tracking is undeniable. IMU, characterized by accelerometers and gyroscopes, excels in delivering high-precision positioning over short durations, making it invaluable for applications in aviation, robotics, and virtual reality. However, it is susceptible to drift over time. Visual Positioning Systems (VPS), harnessing computer vision and visual sensors, provide remarkable sub-meter to centimeter-level accuracy when conditions are optimal. Their significance is particularly pronounced in indoor navigation, augmented reality, and robotics, although they may face challenges in less favorable environments. These technologies are not isolated but can synergize to enhance accuracy and reliability. GPS and IMU collaborate to compensate for signal disruptions, while GPS and VPS join forces to tackle urban complexities. IMU and VPS integration offer precise indoor navigation and augmented reality experiences, delivering impeccable positioning and orientation data. Ultimately, the choice of technology hinges on specific application requirements, encompassing accuracy, environmental considerations, cost factors, and the need for complementary systems. As these technologies advance, they hold the promise of revolutionizing navigation across various domains, from autonomous vehicles to immersive augmented reality environments.

Vessel trajectory prediction based on spatio-temporal graph convolutional network for complex and crowded sea areas

In order to improve the navigation ability of vessels and ensure the safety of maritime traffic, vessel trajectory prediction plays a crucial role in the intelligent navigation and collision avoidance. Especially for complex and crowded waters, autonomous vessels must have high situational awareness to detect other vessels, and predict their future trajectories and assess collision risks. In this work, a deep attention-aware spatio-temporal graph convolutional network based on AIS data (DAA-SGCN) is proposed to predict the future trajectories of vessels. It mainly includes three modules: motion information encoding of vessel trajectories, the spatio-temporal feature extraction module and the trajectory prediction module. The LSTM is used to extract the motion features of vessels, the spatio-temporal graph is constructed based on deep attention mechanism. The spatial social interaction features are extracted by ST-GCN, and the temporal correlation are extracted by RT-CNN, to obtain the high-level spatio-temporal features of vessel trajectories. Then, the feature embedding is fed into the trajectory prediction module to predict the future trajectories of vessels. On the basis of a large number of experiments, the prediction performance of the DAA-SGCN compared to the optimal baseline model is improved by about 74% and 69% in ADE and FDE metrics.

Mid-term Results Following Reverse Shoulder Arthroplasty and the Role of Navigation in the Management of Glenoid Bone Loss.

Background Inaccurate positioning of the glenoid component has been well described as the most common cause of early failure following a reverse shoulder arthroplasty (RSA). Among the latest developments in operative technique, three-dimensional preoperative planning and navigation intraoperative systems have been developed to improve the accuracy of the baseplate positioning during RSA. The primary purpose of this retrospective analysis was to investigate the mid-term results of patients who underwent an elective RSA or for acute highly comminuted proximal humerus fractures. The secondary goal was to investigate the role of navigation in the execution of preoperative planning, especially in the management of glenoid bone loss. Methodology In total, 101 cases were included in this study. Patients were divided into the following two groups: 88 cases of RSA performed without the use of navigation (conventional RSA) and 13 cases performed using intraoperative navigation (navigated RSA). For all patients included in the study, preoperative planning software was employed. Patient demographics, gender, past medical history, indication of procedure, operated site, type of glenoid component used, length of baseplate screws, and clinical assessment scores (Oxford Shoulder Score, OSS) were reported for all patients. Cases of revision shoulder arthroplasty were excluded from this study. Results The postoperative clinical assessment of patients revealed that following RSA, all patients improved significantly with a consistently upward trend of the OSS noted for both groups (conventional and navigated RSA) throughout the postoperative assessment. Despite no statistically significant difference detected, the clinical scores of the navigated RSA group outperformed those of the conventional RSA group in the postoperative period. A higher incidence of augmented baseplate use was noted in the navigated RSA group than in the conventional group (23.07% vs. 5.68%, p < 0.001). Conclusions Our results indicate that the use of intraoperative navigation appears to be a valuable tool in preoperative planning, providing accurate positioning of the baseplate, a better understanding of the glenoid anatomy, and real-time monitoring of the length and direction of the baseplate screws. It is difficult to conclude if the use of navigation leads to superior clinical outcomes, and the cost-effectiveness of its use needs to be further analyzed. Prospective randomized trials are required to assess the cost-effectiveness of routine use of navigation in RSA.

"Somebody That can Meet you on Your Level:" Cancer Survivors' Perspectives on the Role of Indigenous Patient Navigators in Cancer Care.

Cancer incidence has increased for First Nations and Métis Peoples in Canada over recent years. Despite a growing cancer burden, there remain challenges to accessing culturally appropriate and quality care in Saskatchewan. The study aimed to explore, from cancer survivors' perspectives, the potential of Indigenous patient navigators to enhance the healthcare experiences of First Nations and Métis cancer survivors in Saskatchewan. We conducted semi-structured interviews with 19 First Nations and Métis cancer survivors. Participants were interviewed by phone between May 2022 to March 2023. Thematic analysis was conducted to generate themes, categories, and codes reflecting participants' experiences with patient navigators. Participants reported several supports to help patients with cancer through their cancer journey, including family, community, traditional ways, and First Nations and Métis health support services. Challenges to accessing care included language and communication barriers, logistical challenges, cultural differences, financial challenges, and gaps in care. Indigenous patient navigators may play a critical role in overcoming barriers by providing communication, translation, coordination, education, advocacy, and guidance to Indigenous cancer survivors. In participants' view, the tasks of Indigenous patient navigators could vary, ranging from helping schedule appointments to advocating for the patient's treatment preferences. In addition, Indigenous patient navigators could be helpful bridging Western medicine with traditional medicine when supporting patients seeking cancer care. According to study participants, Indigenous patient navigators could be beneficial to Indigenous cancer survivors in Saskatchewan.

RatInABox, a toolkit for modelling locomotion and neuronal activity in continuous environments.

Generating synthetic locomotory and neural data is a useful yet cumbersome step commonly required to study theoretical models of the brain's role in spatial navigation. This process can be time consuming and, without a common framework, makes it difficult to reproduce or compare studies which each generate test data in different ways. In response, we present RatInABox, an open-source Python toolkit designed to model realistic rodent locomotion and generate synthetic neural data from spatially modulated cell types. This software provides users with (i) the ability to construct one- or two-dimensional environments with configurable barriers and visual cues, (ii) a physically realistic random motion model fitted to experimental data, (iii) rapid online calculation of neural data for many of the known self-location or velocity selective cell types in the hippocampal formation (including place cells, grid cells, boundary vector cells, head direction cells) and (iv) a framework for constructing custom cell types, multi-layer network models and data- or policy-controlled motion trajectories. The motion and neural models are spatially and temporally continuous as well as topographically sensitive to boundary conditions and walls. We demonstrate that out-of-the-box parameter settings replicate many aspects of rodent foraging behaviour such as velocity statistics and the tendency of rodents to over-explore walls. Numerous tutorial scripts are provided, including examples where RatInABox is used for decoding position from neural data or to solve a navigational reinforcement learning task. We hope this tool will significantly streamline computational research into the brain's role in navigation.

Breaking barriers: Indigenous nurse navigator role in oncology care for the Inuit

Les personnes qui reçoivent un diagnostic de cancer dans le nord du Canada doivent relever de nombreux défis particuliers. Pour accéder à des soins oncologiques, elles doivent généralement se rendre dans un centre de cancérologie situé dans le sud du pays et séjourner dans une ville loin de leur famille, de leur communauté, de leur langue et de leur culture. Le Programme de cancérologie pour les Autochtones de l’Hôpital d’Ottawa a été créé pour aider ces personnes à s’orienter dans un système de soins oncologiques complexe et peu familier. L’infirmière pivot auprès des Premières Nations, des Inuits et des Métis (PNIM) a pour mission de collaborer avec ces patients et de mettre au point des stratégies d’aide répondant à leurs besoins. Une clinique satellite d’oncologie a récemment été ouverte sur l’île de Baffin, dans le Nunavut, où les patients peuvent être évalués, recevoir un traitement d’immunothérapie anticancéreuse si nécessaire et être suivis après leur traitement primaire. L’ouverture de cette clinique en région éloignée permet aux patients atteints d’un cancer de réduire leurs déplacements et d’éviter de longs séjours loin de chez eux. On espère que ce type de soins pourra être étendu ailleurs au Canada.

Transport makes cities: transit maps as major cognitive frames of metropolitan areas.

Spatial representations play a fundamental role in navigation, decision-making, and overall interaction with our environments. Understanding how individuals construct and use them holds significant importance in spatial cognition research, and even bears practical implications for urban planning as it can explain how we interact with the spaces we inhabit. In large urban areas, transit maps stand as prominent visual aids, guiding people through public transportation systems. These maps, while designed for navigational purposes, may influence how individuals perceive and represent their cities. For instance, Vertesi (Social Studies of Science 38:09-35, 2008) showed through a series of interviews including a "sketch mapping" phase, that London Tube Map seems to structure residents' spatial representation of their city. However, thorough quantitative research on this subject have not been carried out yet. Two experimental studies have been conducted to demonstrate how residents' representations of metropolitan areas closely resemble the schematic representations of their public transport networks. First, we show that residents of Greater Paris-public and private transport users alike-plot city landmarks in a layout more closely resembling that of the Parisian transit map than the geographical map. Next, we asked Greater Berlin, London and Paris residents to place landmarks of their cities on different map backgrounds. A similar procedure was followed for landmarks from an unknown city, after a dedicated learning phase. For known cities, the sketch maps produced were closer to transit maps than to the geographical ones, although less so if the test map background presented topographical elements (e.g., rivers, etc.). For learnt cities, participants' sketch maps were almost exclusively dependent on the map provided during the learning phase. These results suggest that familiarity with transit maps has a direct impact on the metric properties of spatial representation in memory, a phenomenon we propose to call the 'schema effect'.

Exploring software navigation tools for liver tumour angiography: a scoping review.

Liver cancer presents a growing global health concern, necessitating advanced approaches for intervention. This review investigates the use and effectiveness of software navigation in interventional radiology for liver tumour procedures. In accordance with Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines, a scoping review was conducted of the literature published between 2013 and 2023 sourcing articles through MEDLINE, Scopus, CINAHL and Embase. Eligible studies focused on liver cancer, utilised cone-beam computed tomography (CBCT), and employed software for intervention. Twenty-one articles were deemed eligible for data extraction and analysis. Categorised by type, software applications yielded diverse benefits. Feeder detection software significantly enhanced vessel identification, reducing non-target embolisation by up to 43%. Motion correction software demonstrated a 20% enhancement in image quality, effectively mitigating breathing-induced motion artefacts. Liver perfusion software facilitated efficient tumour targeting while simultaneously reducing the occurrence of side effects. Needle guide software enabled precise radiofrequency ablation needle placement. Additionally, these software applications provided detailed anatomical simulations. Overall, software integration resulted in shorter procedures, reduced radiation exposure and decreased contrast media usage. This scoping review highlights the innovative yet relatively underexplored role of software navigation for liver tumour procedures. The integration of software applications not only enhances procedural efficiency but also bolsters operator confidence, and contributes to improved patient outcomes. Despite the current lack of uniformity and standardisation, these software-driven advancements hold significant promise for transforming liver tumour interventions. To realise these benefits, further research is needed to explore the clinical impact and optimal utilisation of software navigation tools in interventional radiology.

Distinct manifold encoding of navigational information in the subiculum and hippocampus.

The subiculum (SUB) plays a crucial role in spatial navigation and encodes navigational information differently from the hippocampal CA1 area. However, the representation of subicular population activity remains unknown. Here, we investigated the neuronal population activity recorded extracellularly from the CA1 and SUB of rats performing T-maze and open-field tasks. The trajectory of population activity in both areas was confined to low-dimensional neural manifolds homoeomorphic to external space. The manifolds conveyed position, speed, and future path information with higher decoding accuracy in the SUB than in the CA1. The manifolds exhibited common geometry across rats and regions for the CA1 and SUB and between tasks in the SUB. During post-task ripples in slow-wave sleep, population activity represented reward locations/events more frequently in the SUB than in CA1. Thus, the CA1 and SUB encode information distinctly into the neural manifolds that underlie navigational information processing during wakefulness and sleep.