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In this paper, we study the indirect relationship between the adoption of Computer-aided Detection or Diagnostic (CADe or CADx) systems for Hepatic Resection (HR) and the patient’s health post-surgery. We vary the number, actual size, and the estimated size of tumors along with model parameters of tumor growth over 1000 simulations of HR according to predefined statistical distributions of parameter values. The average time (t) taken by the tumors to relapse is assessed for the non-adoption of CAD (Case 1), the adoption of semi-automatic CAD (Case 2) and the adoption of automatic CAD (Case 3) in HR. In this study, we have simulated 126 automatic CAD algorithms (Case 3). For tumor volumes (TV) less than 50 cm, if administration of bevacizumab, a post-operative therapy, is (not) adopted in the simulation, t is found to be 646, 84, and 60 days (40, 24, and 17 days) for Case 1, Case 2, and Case 3, respectively. For TV greater than 50 cm, and with (without) bevacizumab, t is found to be 86, 1, and 6 days (28, 6, and 3 days) for Case 1, Case 2, and Case 3, respectively. For with (without) bevacizumab treatment and for all tumor volumes, t is found to be 260, 90, and 104 days (38, 13, and 11 days) for Case 1, Case 2, and Case 3, respectively. We have observed that the tumors relapsed quickly in those cases where CAD was adopted.

Introduction: Percutaneous thermal ablation is widely adopted as a curative treatment approach for unresectable liver neoplasms. Accurate immediate assessment of therapeutic response post-ablation is critical to achieve favourable outcomes. The conventional technique of side-by-side comparison of pre- and post-ablation scans is challenging and hence there is a need for improved methods, which will accurately evaluate the immediate post-therapeutic response. Objectives and Significance: This review summarizes the findings of studies investigating the feasibility and efficacy of the fusion imaging systems in the immediate post-operative assessment of the therapeutic response to thermal ablation in liver neoplasms. The findings could potentially empower the clinicians with updated knowledge of the state-of-the-art in the assessment of treatment response for unresectable liver neoplasms. Methods and Analysis: A rapid review will be performed on publicly available major electronic databases to identify articles reporting the feasibility and efficacy of the fusion imaging systems in the immediate assessment of the therapeutic response to thermal ablation in liver neoplasms. The risk of bias and quality of articles will be assessed using the Cochrane risk of bias tool 2.0 and Newcastle Ottawa tool. Ethics and Dissemination: Being a review, we do not anticipate the need for any approval from the Institutional Review Board. The outcomes of this study will be published in a peer-reviewed journal. Highlights Evaluation of the therapeutic response in liver neoplasms immediately post-ablation is critical to achieve favourable patient outcomes. We will examine the feasibility and technical efficacy of different fusion imaging systems in assessing the immediate treatment response post-ablation. The findings are expected to guide the clinicians with updated knowledge on the state-of-the-art when assessing the immediate treatment response for unresectable liver neoplasms.

Recent tele-mentoring technologies for minimally invasive surgery (MIS) augments the operative field with movements of virtual surgical instruments as visual cues. The objective of this work is to assess different user-interfaces that effectively transfer mentor's hand gestures to the movements of virtual surgical instruments.A user study was conducted to assess three different user-interface devices (Oculus-Rift, SpaceMouse, Touch Haptic device) under various scenarios. The devices were integrated with a MIS tele-mentoring framework for control of both manual and robotic virtual surgical instruments.The user study revealed that Oculus Rift is preferred during robotic scenarios, whereas the touch haptic device is more suitable during manual scenarios for tele-mentoring.A user-interface device in the form of a stylus controlled by fingers for pointing in 3D space is more suitable for manual MIS, whereas a user-interface that can be moved and oriented easily in 3D space by wrist motion is more suitable for robotic MIS.

Medical images (e.g., magnetic resonance imaging (MRI) and computed tomography (CT)) provide critical information to the clinicians in order to diagnose pathology and plan interventions. Image segmentation is the first and foremost step taken by the clinicians while optimizing analytic diagnosis and treatment planning for interventions (e.g., transplantation and complete resection) and therapeutic procedures (e.g., radiotherapy, PVE, and embolization approaches), especially in hepatocellular carcinoma. Thus, segmentation techniques certainly impact the diagnosis and treatment outcomes. This paper studies the literature during the year 2012 until 2021 and reviews the segmentation methods classifying them into three categories based on their clinical utility (i.e., surgical and radiological interventions). The classification is based on the parameters such as precision, accuracy, location, liver condition, and other clinical considerations.

Mixed reality-based medical holography is expected to have powerful applications in many surgical fields through easy and intuitive interaction with anatomic holograms using gestures. However, interaction with nested holograms using default gesture interaction, as is the case in visualized complex anatomic structures, is found to be challenging. This work develops, implements, and compares two modes of interaction with nested holograms, using native gestures and 3D SpaceMouse. Each of this mode uses ray casting and either Box Collider (BC) or Mesh Collider (MC) techniques to select target hologram. The use of SpaceMouse is found to have superior control over the selection of nested holograms irrespective of the mode of interaction, while a combination of native gestures and BC mode seems to most improve the efficiency of interaction of a selected nested hologram.

The blood-brain barrier (BBB) is a prime focus for clinicians to maintain the homeostatic function in health and deliver the theranostics in brain cancer and number of neurological diseases. The structural hierarchy and in situ biochemical signaling of BBB neurovascular unit have been primary targets to recapitulate into the in vitro modules. The microengineered perfusion systems and development in 3D cellular and organoid culture have given a major thrust to BBB research for neuropharmacology. In this review, we focus on revisiting the nanoparticles based bimolecular engineering to enable them to maneuver, control, target, and deliver the theranostic payloads across cellular BBB as nanorobots or nanobots. Subsequently we provide a brief outline of specific case studies addressing the payload delivery in brain tumor and neurological disorders (e.g., Alzheimer's disease, Parkinson's disease, multiple sclerosis, etc.). In addition, we also address the opportunities and challenges across the nanorobots' development and design. Finally, we address how computationally powered machine learning (ML) tools and artificial intelligence (AI) can be partnered with robotics to predict and design the next generation nanorobots to interact and deliver across the BBB without causing damage, toxicity, or malfunctions. The content of this review could be references to multidisciplinary science to clinicians, roboticists, chemists, and bioengineers involved in cutting-edge pharmaceutical design and BBB research.

Training and skills assessment for robotic surgeries has received unprecedented attention in technological research in the last few years due to the gradual adoption of minimally invasive robotic interventions. Robot-assisted radical prostatectomy (RARP) is one of these interventions that help cure cancer by completely removing the prostate. Trainers currently use numerous training methodologies to teach novice surgeons macro RARP skills. However, limited resources for teaching and assessing micro-skills, such as the optimal urethra dissection ranges given basic variables: prostate size and prostate cancer location, are used in practice. Therefore, we built an interactive prototype to teach these skills. This paper validates the prototype using content validity and Questionnaire for User Interaction Satisfaction (QUIS) with five surgeons. The results demonstrate high content validity and increased end-user satisfaction.

Background User interfaces play a vital role in the planning and execution of an interventional procedure. The objective of this study is to investigate the effect of using different user interfaces for planning transrectal robot-assisted MR-guided prostate biopsy (MRgPBx) in an augmented reality (AR) environment. Method End-user studies were conducted by simulating an MRgPBx system with end- and side-firing modes. The information from the system to the operator was rendered on HoloLens as an output interface. Joystick, mouse/keyboard, and holographic menus were used as input interfaces to the system. Results The studies indicated that using a joystick improved the interactive capacity and enabled operator to plan MRgPBx in less time. It efficiently captures the operator's commands to manipulate the augmented environment representing the state of MRgPBx system. Conclusions The study demonstrates an alternative to conventional input interfaces to interact and manipulate an AR environment within the context of MRgPBx planning.

This work presents an interventional planning software to be used in conjunction with a robotic manipulator to perform transrectal MR guided prostate biopsies. The interventional software was designed taking in consideration a generic manipulator used under the two modes of operation: side-firing and end-firing of the biopsy needle. Studies were conducted with urologists using the software to plan virtual biopsies. The results show features of software relevant for operating efficiently under the two modes of operation.

Cerebral aneurysm is a cerebrovascular disorder caused by a weakness in the wall of an artery or vein, which causes a localized dilation or ballooning of the blood vessel. It is life-threatening; hence, an early and accurate diagnosis would be a great aid to medical professionals in making the correct choice of treatment. HemeLB is a massively parallel Lattice-Boltzmann simulation software, which is designed to provide the radiologist with estimates of flow rates, pressures, and shear stresses throughout the relevant vascular structures, intended to eventually permit greater precision in the choice of therapeutic intervention. However, in order to allow surgeries and doctors to view and visualize the results in real-time at medical environments, a cost-efficient, practical platform is needed. In this article, we have developed and evaluated a version of HemeLB on various heterogeneous system-on-chip platforms, allowing users to run HemeLB on a low-cost embedded platform and to visualize the simulation results in real-time. A comprehensive evaluation of implementation on the Zynq SoC and Jetson TX1 embedded graphic processing unit platforms are reported. The achieved results show that the proposed Jetson TX1 implementation outperforms the Zynq implementation by a factor of 19 in terms of site updates per second. 2007-2012 IEEE. Manuscript received February 19, 2019; revised September 20, 2019; accepted November 4, 2019. Date of publication December 2, 2019; date of current version June 3, 2020. This paper was supported by the National Priorities Research Program (NPRP) under Grant 5-792-2-328 from the Qatar National Research Fund (a member of Qatar Foundation). X. Zhai is partially supported by the UK Engineering and Physical Sciences Research Council under Grants EP/R02572X/1 and EP/P017487/1. (Corresponding author: Xiaojun Zhai.) X. Zhai is with the School of Computer Science and Electronic Engineering, University of Essex, CO4 3SQ Colchester, U.K. (e-mail: xzhai@essex.ac.uk). Scopus

Purpose: Cerebral aneurysms are one of the prevalent cerebrovascular disorders in adults worldwide and caused by a weakness in the brain artery. The most impressive treatment for a brain aneurysm is interventional radiology treatment, which is extremely dependent on the skill level of the radiologist. Hence, accurate detection and effective therapy for cerebral aneurysms still remain important clinical challenges. In this work, we have introduced a pipeline for cerebral blood flow simulation and real-time visualization incorporating all aspects from medical image acquisition to real-time visualization and steering. Methods: We have developed and employed an improved version of HemeLB as the main computational core of the pipeline. HemeLB is a massive parallel lattice-Boltzmann fluid solver optimized for sparse and complex geometries. The visualization component of this pipeline is based on the ray marching method implemented on CUDA capable GPU cores. Results: The proposed visualization engine is evaluated comprehensively and the reported results demonstrate that it achieves significantly higher scalability and sites updates per second, indicating higher update rate of geometry sites' values, in comparison with the original HemeLB. This proposed engine is more than two times faster and capable of 3D visualization of the results by processing more than 30 frames per second. Conclusion: A reliable modeling and visualizing environment for measuring and displaying blood flow patterns in vivo, which can provide insight into the hemodynamic characteristics of cerebral aneurysms, is presented in this work. This pipeline increases the speed of visualization and maximizes the performance of the processing units to do the tasks by breaking them into smaller tasks and working with GPU to render the images. Hence, the proposed pipeline can be applied as part of clinical routines to provide the clinicians with the real-time cerebral blood flow-related information. 2020, CARS. This study was made possible by a National Priorities Research Program (NPRP) Grant No. 5-792-2-328 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors. Scopus