Real-time Guidance Research Articles

Ultrasound imaging guided precision histotripsy: Effects of pulse settings on ablation properties in rat brain.

A high-frequency 6 MHz miniature handheld histotripsy device with an endoscopic form factor and co-registered high-resolution ultrasound imaging was developed. This device could allow precision histotripsy ablation during minimally invasive brain tumor surgeries with real-time image guidance. This study characterized the outcome of acute histotripsy in the normal in vivo rat brain using the device with a range of histotripsy pulse settings, including number of cycles, pulse repetition frequency, and pressure, as well as other experimental factors. The stability and shape of the bubble cloud were measured during ablations, as well as the post-histotripsy ablation shape in ultrasound B-mode and histology. The results were compared between histological images and the ultrasound imaging data to determine how well ultrasound data reflected observable damage in histology. The results indicated that while pulse settings can have some influence on ablation shape, sample-to-sample variation had a larger influence on ablation shape. This suggests that real-time ablation monitoring is essential for accurate knowledge of outcomes. Ultrasound imaging provided an accurate real-time indication of ablation shape both during ablation and post-ablation.

User Experience Evaluation of a Spinal Surgery Robot: Workload, Usability, and Satisfaction Study.

Robotic spine surgery has continued to evolve since its US Food and Drug Administration approval in 2004, with products now including real-time video guidance and navigation during surgery. As the market for robotic surgical devices evolves, it is important to consider usability factors. The primary objective of this study was to determine the user experience of a surgical-assistive robotic device. The secondary objective was to evaluate workload, usability, the After-Scenario Questionnaire (ASQ), and the System Usability Scale (SUS). In addition, this study compares the workload, usability, and satisfaction survey of the device among different occupational groups using the device. Doctors (n=15) and nurses (n=15), the intended users of the surgical assistant robot, participated in the usability evaluation. Participants performed essential scenarios for the surgical assistant robot and provided scenario-specific satisfaction (ASQ), workload (NASA Task Load Index), and usability (SUS) scores. Both doctors and nurses had task success rates of 85% or higher for each scenario. ASQ results showed that both doctors and nurses were least satisfied with ease of completing the task of registration (group 1: mean 4.73, SD 1.57 and group 2: mean 4.47, SD 1.8), amount of time it took (group 1: mean 4.47, SD 1.63 and group 2: mean 4.40, SD 2.09), and support information satisfaction (group 1: mean 5.13, SD 1.50 and group 2: mean 5.13, SD 1.89). All participants had low workloads, and the overall Task Load Index score had a P value of .77, which is greater than .05. The SUS results showed that the overall usability mean for doctors was 64.17 (SD 16.52) and the mean for nurses was 61.67 (SD 19.18), with a P value of .84, which is greater than .05, indicating no difference between the 2 groups. In this study, doctors and nurses evaluated the interaction of the device in a simulated environment, the operating room. By evaluating the use experience and usability of the device with real intended users, we can develop a more effective and convenient user interface.

Click, Track and Eat: The Power of Nutrition Apps

Nutrition apps enhances the nutrition guidance and suitability in balancing and tracking food intakes. They expand knowledge and awareness about nutrition as well. The modern technologies connect users to have wearable devices and data analytics with motivations, visions and support on their journey towards healthy lifestyles. Instead of hunting through books and contacting nutritionists, you can find all information about healthy lifestyles into single solution and easily assessable platforms.
 As it provides more flexibility, it allows the users to interact at their own ease and make healthier choices by obtaining nutritious recipes and advices, which makes it more convenient and cost effective. In addition, these apps provide users to give real-time feedbacks and guidance, monitor their diet behaviors and physical activities and supplementation information They also facilitate them in weight calculations and calories-tracking to manage their whole diet plans. Furthermore, these offer several healthier activities like exercising and staying hydrated alerts.
 However, nutrition apps have many limitations and challenges; users may consider it time consuming with recent study highlighting that the calorie and fitness tracking may be related to eating disorders [1]. Additionally, another study on eating disorders found that body dissatisfaction and preoccupations with body shape tend to be high in the individuals using nutrition apps [2]. Despite these issues, the accuracy of these app can vary depending on user’s capability to record their food intake.
 Nevertheless, this does not deny the significance of dietary compositions in health and illness prevention and management. Appropriate nutritional intake is crucial to maintain a healthy life, avoid nutrient deficiencies and lower the risk of diseases. Therefore, it is imperative to establish effective methods so that the dietary can be tracked and thus improved. It is equally important to address the concerns related to negative impacts of nutrition apps such as unhealthy eating habits due to overdependence.
 In conclusion, this editorial sheds light on the significance of nutrition apps that provide user-friendly interactions for improving dietary habits. While many of nutrition apps have positively improved user behaviors and diet quality, addressing challenges such as users’ annoyance and disengagements still remains. Looking forward, prioritizing user satisfaction and enhancing functionality is crucial to unlocking the nutrition apps potential for achieving long-term impacts in diet quality and promoting healthier lifestyles.

Application of Laennec extrathecal blockade combined with indocyanine green fluorescence imaging in laparoscopic anatomic hepatectomy.

To investigate the safety and application value of combining Laennec extracapsular occlusion with ICG fluorescence imaging in laparoscopic anatomic hepatectomy. Complete laparoscopic dissection was performed outside the Laennec sheath, blocking Glisson's pedicle of the corresponding liver segment or lobe. An appropriate amount of indocyanine green (ICG) dye was intravenously injected, and the boundary line between the pre-cut liver segment and liver lobe was identified using fluorescence laparoscopy. Complete resection of the liver segment or lobe was performed based on anatomical markers. Clinical data, including operation time, intraoperative blood loss, postoperative hospital stay, and postoperative complications, were collected. A total of 14 cases were included in the study, including seven cases of primary liver cancer, three cases of metastatic liver cancer, three cases of intrahepatic bile duct calculi, and one case of hepatic hemangioma. All 14 patients underwent anatomic hepatectomy under fluorescent laparoscopy, with four cases involving the right liver, seven cases involving the left liver, two cases involving the right anterior lobe, and one case involving the right posterior lobe. Combining laparoscopic follow-up of the Laennec membrane with Glisson outer sheath block and intraoperative ICG fluorescence imaging provides real-time guidance for locating the resection boundaries during anatomic hepatectomy. This approach helps in controlling intraoperative bleeding, reducing operation time, and ensuring high safety. It holds significant value in clinical application.

An augmented reality-guided biopsy system using a high-speed motion tracking and real-time registration platform.

Biopsies play a crucial role in diagnosis of various diseases including cancers. In this study, we developed an augmented reality (AR) system to improve biopsy procedures and increase targeting accuracy. Our AR-guided biopsy system uses a high-speed motion tracking technology and an AR headset to display a holographic representation of the organ, lesions, and other structures of interest superimposed on real physical objects. The first application of our AR system is prostate biopsy. By incorporating preoperative scans, such as computed tomography (CT) or magnetic resonance imaging (MRI), into real-time ultrasound-guided procedures, this innovative AR-guided system enables clinicians to see the lesion as well as the organs in real time. With the enhanced visualization of the prostate, lesion, and surrounding organs, surgeons can perform prostate biopsies with an increased accuracy. Our AR-guided biopsy system yielded an average targeting accuracy of 2.94 ± 1.04 mm and can be applied for real-time guidance of prostate biopsy as well as other biopsy procedures.

Innovative multimodal Open Distance e-Learning (ODeL) supervision practices for master’s and doctoral candidates

Open Distance e-Learning (ODeL) is on the rise to cater to non-traditional students. However, the surge in master's and doctoral students opting for ODeL raises concerns about the quality and timely completion of degrees. Existing literature on student attrition in higher education indicates that both student-related factors and institutional variables significantly impact completion rates. Factors such as students' sense of connection or isolation, as well as institutional aspects like supervisor responsiveness to feedback and feedforward, contribute to student persistence. To address this early attrition and extended stays in postgraduate studies, a community of practice (CoP), comprising lecturers and master’s and doctoral students was formed. The CoP employed the Social Learning Theory (SLT) approach to initiate collaborative partnerships designed to promote a research culture and explore alternative approaches to curb master’s and doctoral late completion and attrition. This paper reports on a study undertaken to explore the experiences, perceptions and insights of master’s and doctoral candidates regarding the implementation of innovative multimodal Open Distance e-Learning supervision practices. Grounded in SLT, the exploratory case study employed an open-ended questionnaire to gather data from the students participating in the support programme. The findings revealed the positive impact of innovative practices on candidates' academic development and overall research experience. The findings further demonstrated that virtual communication tools have significantly enhanced collaboration between candidates and supervisors, breaking down geographical barriers and facilitating real-time feedback and guidance. The innovative multimodal OdeL supervision practices gave master’s and doctoral candidates flexibility and increased their learning engagement.

PitSurgRT: real-time localization of critical anatomical structures in endoscopic pituitary surgery

PurposeEndoscopic pituitary surgery entails navigating through the nasal cavity and sphenoid sinus to access the sella using an endoscope. This procedure is intricate due to the proximity of crucial anatomical structures (e.g. carotid arteries and optic nerves) to pituitary tumours, and any unintended damage can lead to severe complications including blindness and death. Intraoperative guidance during this surgery could support improved localization of the critical structures leading to reducing the risk of complications.MethodsA deep learning network PitSurgRT is proposed for real-time localization of critical structures in endoscopic pituitary surgery. The network uses high-resolution net (HRNet) as a backbone with a multi-head for jointly localizing critical anatomical structures while segmenting larger structures simultaneously. Moreover, the trained model is optimized and accelerated by using TensorRT. Finally, the model predictions are shown to neurosurgeons, to test their guidance capabilities.ResultsCompared with the state-of-the-art method, our model significantly reduces the mean error in landmark detection of the critical structures from 138.76 to 54.40 pixels in a 1280 ×\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ imes $$\\end{document} 720-pixel image. Furthermore, the semantic segmentation of the most critical structure, sella, is improved by 4.39% IoU. The inference speed of the accelerated model achieves 298 frames per second with floating-point-16 precision. In the study of 15 neurosurgeons, 88.67% of predictions are considered accurate enough for real-time guidance.ConclusionThe results from the quantitative evaluation, real-time acceleration, and neurosurgeon study demonstrate the proposed method is highly promising in providing real-time intraoperative guidance of the critical anatomical structures in endoscopic pituitary surgery.

Towards Automating Personal Exercise Assessment and Guidance with Affordable Mobile Technology.

Physical activity (PA) offers many benefits for human health. However, beginners often feel discouraged when introduced to basic exercise routines. Due to lack of experience and personal guidance, they might abandon efforts or experience musculoskeletal injuries. Additionally, due to phenomena such as pandemics and limited access to supervised exercise spaces, especially for the elderly, the need to develop personalized systems has become apparent. In this work, we develop a monitored physical exercise system that offers real-time guidance and recommendations during exercise, designed to assist users in their home environment. For this purpose, we used posture estimation interfaces that recognize body movement using a computer or smartphone camera. The chosen pose estimation model was BlazePose. Machine learning and signal processing techniques were used to identify the exercise currently being performed. The performances of three machine learning classifiers were evaluated for the exercise recognition task, achieving test-set accuracy between 94.76% and 100%. The research methodology included kinematic analysis (KA) of five selected exercises and statistical studies on performance and range of motion (ROM), which enabled the identification of deviations from the expected exercise execution to support guidance. To this end, data was collected from 57 volunteers, contributing to a comprehensive understanding of exercise performance. By leveraging the capabilities of the BlazePose model, an interactive tool for patients is proposed that could support rehabilitation programs remotely.

Coupled simulation-optimization model for pedestrian evacuation guidance planning

Effective evacuation guidance can guarantee people's safety by facilitating their swiftly exit hazardous areas during an emergency. However, pre-determined guidance plans based solely on distance comparisons to exits may not always be the most effective due to unstable accessibility conditions and uneven crowd distribution. Therefore, it is imperative to incorporate real-time optimal guidance information in the plan. Coupling simplified CTM (Cell Transmission Model)-based simulation, this study proposed a computationally efficient DRF (Directed Rooted Forest)-encoded planning for developing evacuation guidance plan. Taking them as a holistic model, the simulator predicts evacuation dynamics at a constant computational cost regardless of crowd size, while the planning module optimizes the guidance plan directionally by leveraging the simulation's intermediate and final outputs. Numerical tests have demonstrated that the tight coupling between optimization and simulation module has substantially enhanced the model's capacity to fine-tune the guidance plan and optimization efficiency. The proposed model may serve as the foundation for developing real-time evacuation guidance plans for large-scale crowded buildings, either on the premise of accelerated simulation or as an efficient generator of training data for machine learning models.

Narrative-guided synthesis: Revolutionizing text-to-image translation based on Generative Adversarial Networks

Synthesizing images from textual descriptions remains an intricate yet essential task in the field of artificial intelligence. However, this process often encounters challenges related to intricacy and time consumption. This study introduces a pioneering approach known as narrative-guided synthesis, harnessing the power of Generative Adversarial Networks (GANs) in conjunction with platforms such as Midjournary. This innovative technique transforms abstract narratives into stunning visual creations, streamlining the image generation process by providing real-time feedback and guidance. This research showcases an optimized framework that integrates diverse modules into a unified system, effectively reducing computational complexity and boosting overall efficiency. Central to this framework is an attention-guided mechanism that emphasizes semantic nuances within the text, ensuring greater fidelity in the generated images. This is complemented by spatially adaptive normalization techniques that maintain contextual relevance within the visual outputs. Preliminary results indicate that this approach not only competes with existing models but potentially surpasses them in producing visually and contextually accurate images, heralding a new era of digital innovation where technology and creativity converge seamlessly. Furthermore, this study underscores the transformative potential of AI in revolutionizing content production, interactive design, and user interfaces, promising a future where textual narratives can be visualized with unprecedented accuracy and creativity.

Development of an augmented reality system for tracheal intubation guidance of airway management.

Tracheal intubation is a crucial procedure performed in airway management to sustain life during various procedures. However, difficult airways can make intubation challenging, which is associated with increased mortality and morbidity. This is particularly important for children who undergo intubation where the situation is difficult. Improved airway management will decrease incidences of repeated attempts, decrease hypoxic injuries in patients, and decrease hospital stays, resulting in better clinical outcomes and reduced costs. Currently, 3D printed models based on CT scans and ultrasound-guided intubation are being used or tested for device fitting and procedure guidance to increase the success rate of intubation, but both have limitations. Maintaining a 3D printing facility can be logistically inconvenient, and it can be time consuming and expensive. Ultrasound-guided intubation can be hindered by operator dependence, limited two-dimensional visualization, and potential artifacts. In this study, we developed an augmented reality (AR) system that allows the overlay of intubation tools and internal airways, providing real-time guidance during the procedure. A child manikin was used to develop and test the AR system. Three-dimensional CT images were acquired from the manikin. Different tissues were segmented to generate the 3D models that were imported into Unity to build the holograms. Phantom experiments demonstrated the AR-guided system for potential applications in tracheal intubation guidance.

Self-administered at-home lung ultrasound with remote guidance in patients without clinical training

BackgroundAccess to timely and accurate diagnostic imaging is essential for high-quality healthcare. Point-of-care ultrasound has been shown to be accessible and effective in many aspects of healthcare, including assessing changes in lung pathology. However, few studies have examined self-administered at-home lung ultrasound (SAAH-LUS), in particular performed by non-clinical patients (NCPs).Research questionAre NCPs able to perform SAAH-LUS using remote teleguidance and produce interpretable images?Study designPatients were enrolled to the study in a mix of in-person and virtual recruitment, and shipped a smartphone as well as a point of care ultrasound device. Tele-guidance was provided by a remote physician using software integrated with the point of care ultrasound device, allowing real-time remote visualization and guidance of a patient scanning their own chest. A post-intervention survey was conducted to assess patient satisfaction, feasibility, and acceptability of SAAH-LUS. Two POCUS expert reviewers reviewed the scans for interpretability, and inter-rater agreement between the two reviewers was also computed.ResultsEighteen patients successfully underwent 7–14 days of daily telemedicine in parallel to daily SAAH-LUS. Across 1339 scans obtained from ten different lung zones, the average proportion of interpretability was 96% with a chance-corrected agreement, or Cohen’s kappa, reported as κ = 0.67 (significant agreement). 100% of NCPs surveyed found SAAH-LUS to be a positive experience, particularly for its ease of operation and ability to increase access to healthcare services.InterpretationThis study demonstrates that NCPs can obtain interpretable LUS images at home, highlighting the potential for SAAH-LUS to increase diagnostic capacity, particularly for rural and remote regions where complex imaging and healthcare providers are difficult to obtain.Trial registration The clinical trials has been registered (clinicaltrials.gov). Registration number: NCT04967729

Real-Time Gated Proton Therapy: Commissioning and Clinical Workflow for the Hitachi System

PurposeTo describe the commissioning of real-time gated proton therapy (RGPT) and the establishment of an appropriate clinical workflow for the treatment of patients. Materials and MethodsHitachi PROBEAT provides pencil beam scanning proton therapy with an advanced onboard imaging system including real-time fluoroscopy. RGPT utilizes a matching score to provide instantaneous system performance feedback and quality control for patient safety. The CIRS Dynamic System combined with a Thorax Phantom or plastic water was utilized to mimic target motion. The OCTAVIUS was utilized to measure end-to-end dosimetric accuracy for a moving target across a range of simulated situations. Using this dosimetric data, the gating threshold was carefully evaluated and selected based on the intended treatment sites and planning techniques. An image-guidance workflow was developed and applied to patient treatment. ResultsDosimetric data demonstrated that proton plan delivery uncertainty could be within 2 mm for a moving target. The dose delivery to a moving target could pass 3%/3 mm gamma analysis following the commissioning process and application of the clinical workflow detailed in this manuscript. A clinical workflow was established and successfully applied to patient treatment utilizing RGPT. Prostate cancer patients with implanted platinum fiducial markers were treated with RGPT. Their target motion and gating signal data were available for intrafraction motion analysis. ConclusionReal-time gated proton therapy with the Hitachi System has been fully investigated and commissioned for clinical application. RGPT can provide advanced and reliable real-time image guidance to enhance patient safety and inform important treatment planning parameters, such as planning target volume margins and uncertainty parameters for robust plan optimization. RGPT improved the treatment of patients with prostate cancer in situations where intrafraction motion is more than defined tolerance.

Managing pediatric-onset multiple sclerosis in an austere setting: A case report.

Pediatric-onset multiple sclerosis (POMS) is the most common demyelinating disease in children. Patients suffer from physical disability, cognitive impairment, and psychosocial challenges. Management requires a multidisciplinary care team. Here we present a case of an 11-year-old boy with POMS who relocated to Guam prior to initiation of a disease-modifying treatment and who experienced a flare without immediate access to an MRI or a child neurologist. Care required the combined efforts of ophthalmology, pediatrics, and emergency medicine in Guam, real-time remote guidance by child neurology, and asynchronous collaboration with cardiology and child neurology. As a result, the immediate flare was accurately diagnosed and treated with steroids, the patient was started on Fingolimod, and an emergency management plan for future flares was constructed. This case illustrates the nuances of both the acute and chronic management of multiple sclerosis in a resource-limited setting and how a combination of synchronous and asynchronous telemedicine was able to achieve a satisfactory treatment plan.

Next-generation endoscopic probe for detection of esophageal dysplasia using combined OCT and angle-resolved low-coherence interferometry.

Angle-resolved low-coherence interferometry (a/LCI) is an optical technique that enables depth-specific measurements of nuclear morphology, with applications to detecting epithelial cancers in various organs. Previous a/LCI setups have been limited by costly fiber-optic components and large footprints. Here, we present a novel a/LCI instrument incorporating a channel for optical coherence tomography (OCT) to provide real-time image guidance. We showcase the system's capabilities by acquiring imaging data from in vivo Barrett's esophagus patients. The main innovation in this geometry lies in implementing a pathlength-matched single-mode fiber array, offering substantial cost savings while preserving signal fidelity. A further innovation is the introduction of a specialized side-viewing probe tailored for esophageal imaging, featuring miniature optics housed in a custom 3D-printed enclosure attached to the tip of the endoscope. The integration of OCT guidance enhances the precision of tissue targeting by providing real-time morphology imaging. This novel device represents a significant advancement in clinical translation of an enhanced screening approach for esophageal precancer, paving the way for more effective early-stage detection and intervention strategies.

Safety and efficacy of indocyanine green fluorescence imaging for real-time guidance of laparoscopic thermal ablation in patients with liver cancer

Purpose To evaluate the safety and efficacy of indocyanine green fluorescence imaging for real-time guidance of laparoscopic thermal ablation in patients with liver cancer. Materials and methods A total of 27 patients with 40 liver lesions underwent fluorescence-assisted laparoscopic ablation between January 2020 to March 2023. The sensitivity of indocyanine green (ICG)-fluorescence imaging, technique effectiveness rate and complications of fluorescence-assisted laparoscopic thermal ablation were evaluated. Results In total, 33 out of the 40 lesions were identified by ICG-fluorescence imaging technique, with the sensitivity of 82.5%. The sensitivity of ICG-fluorescence imaging of tumor detection in liver surface of parenchyma was significantly higher than that in the deeply located hepatic parenchyma (96.8% vs 33.3%, p = 0.002). ICG-fluorescence imaging procedures detected 4 lesions that cannot be seen on intraoperative ultrasound. It provides clear demarcation lines on the hepatic surface. Technical success is achieved if the necrotic zone had at least a 5 mm ablative margin around the outer edge of the ICG-fluorescence image. Technical success of fluorescence laparoscopic radiofrequency ablation (FLRFA) and fluorescence laparoscopic microwave ablation (FLMWA) was 100% (27/27). Technical effectiveness is defined by the complete necrotic lesions of the local tumor tissue during follow-up. According to the CT/MRI one month after FLRFA or FLMWA, the technical efficacy rate was 92.5% (37/40) and local tumor progression occurred in 7.5% (3/40) of the enrolled lesions. During the follow-up period, no major complications were observed. Conclusion ICG-fluorescence imaging guided laparoscopic thermal ablation was feasible, safe and effective.

The COVID guidelines India project: A rapid living evidence synthesis during a pandemic in a LMIC setting

BackgroundCOVID-19 has had an unprecedented impact worldwide. Evidence for management interventions emerged rapidly but was difficult for clinicians and others to assess and decide how to use. Our team in India set up a national and international collaboration preparing guidance in real time to help guide clinical practice in the country during a pandemic setting. We describe our methods and the product in this paper. MethodsSpecialized groups comprising core, steering, methodology, evidence synthesis, dissemination and intervention expert working groups were formed. A Cochrane Rapid Review approach was used for prioritized questions in areas of clinical equipoise in management of COVID-19. GRADE methodology was incorporated into this process and expert working groups tailored guidelines for India using the WHO Evidence to Decision framework. This was then disseminated on a widely accessible platform: indiacovidguidelines.org. A questionnaire was then used to obtain end-user feedback on the guidelines. ResultsSince May 2021, a total of 20 guidelines have been developed spanning pharmacological, respiratory and other supportive interventions for management of COVID-19, with over 83,600 unique page views up to December 2023. Results from a pilot survey suggest usefulness of the guidelines, but also highlighted areas for improvement. A key output was adoption of our anticoagulation recommendation in state level COVID-19 guidelines (Kerala, India). National and institutional capacity for evidence synthesis and guidelines was strengthened. ConclusionsThe COVID Guidelines India project successfully developed contextually relevant, nationally applicable, evidence-based guidelines in a timely manner, and disseminated these freely through a dedicated website while successfully building capacity amongst Indian clinicians for evidence-based guideline development. Throughout the ongoing COVID Guidelines India project, the team has maintained a 'living' approach, continuously updating and refining recommendations in response to emerging evidence during the ever-evolving pandemic landscape.

Image fusion guidance for left subclavian artery in situ fenestration during thoracic endovascular repair.

To evaluate the feasibility and clinical benefit of utilizing image fusion for thoracic endovascular repair (TEVAR) with in situ fenestration (ISF-TEVAR). Between January 2020 and December 2020, we prospectively collected 18 consecutive cases with complex thoracic aortic lesions who underwent image fusion guided ISF-TEVAR. As a control group, 18 patients were collected from historical medical records from June 2019 to December 2019. The fusion group involved the use of 3D fusion of CTA and fluoroscopic images for real-time 3D guidance, and the control group involved the use of only regular fluoroscopic images for guidance. The total contrast medium volume, hand-injected contrast medium volume, overall operative time, radiation dose and fluoroscopy time were compared between the two groups. Accuracy was measured based on preoperative CTA and intraoperative digital subtraction angiography. 3D fusion imaging guidance was successfully implemented in all patients in the fusion group. Hand-injected contrast medium volume and overall operative time were significantly lower in the fusion group than in the control group (p = .028 and p = .011). Compared with the control group, the fusion group showed a significant reduction in time and radiation dose-area product (DAP) for fluoroscopy (p = .004 and p = .010). No significant differences in total radiation dose (DAP) or total contrast medium volume were observed (p = .079 and p = .443). Full accuracy was achieved in 8 cases (44%), with a mean deviation of 2.61mm ± 3.1 (range 0.0-8.4mm). 3D image fusion for ISF-TEVAR was associated with a significant reduction in hand-injected contrast medium, time and radiation exposure for fluoroscopy and overall operative time. The image fusion guidance showed potential clinical benefits towards improved treatment safety and accuracy for complex thoracic endovascular interventions.

CBCT-based three-dimensional dual-phase vascular image fusion: anovel technique for interventional real-time TIPS guidance.

Due to the invisibility of the portal vein (PV), how to puncture the PV accurately and safely in transjugular intrahepatic portosystemic shunt (TIPS) creation remains achallenge of the procedure. We aimed to provide the first evaluation of the safety, feasibility, and efficiency of cone beam computed tomography (CBCT)-based three-dimensional (3D) dual-phase vascular image fusion for interventional real-time guided PV puncture during TIPS procedures. From January 2021 to May 2021, 13patients undergoing TIPS were prospectively enrolled in this study. Images of the hepatic artery (HA) and PV in 3D were acquired and overlaid on interventional fluoroscopy images in adual-phase display mode for real-time PV puncture guidance. The number of PV puncture attempts, puncture time, overlaid image accuracy, dose area product, fluoroscopy time, and interventional complications were recorded. Portal vein puncture guided by CBCT-based 3D dual-phase vascular image fusion was successfully performed on 92.3% (12/13) patients. The mean number of PV puncture attempts was 1.8 ± 0.7 (1-3). The mean puncture time and fluoroscopy time was 3.5 ± 1.2 (2-6) min and 25.1 ± 9.4 (15-45) min, respectively. The mean dose area product was 39.49 ± 7.88 (28.81-52.87) mGym2. The error between the reference position of the fusion image and the interventional PV angiography image was less than 0.5 cm. No interventional complication was observed. Our results show that 3D dual-phase vascular image fusion might be asafe and feasible technique for interventional real-time guided PV puncture during TIPS. This novel technique might help to reduce the number of PV puncture attempts and the puncture time as well as lower the risks of interventional complications.

Stereotactic Navigation-Assisted Laparoscopic Resection of Challenging Low Pelvic Tumors: A Case Series.

(1) Introduction: The laparoscopic approach to low pelvic tumors is challenging and hindered by suboptimal tumor visualization and dissection, with possible oncological failure. Stereotactic navigation provides real-time image guidance that may optimize safety, accuracy, and precision when dissecting challenging low pelvic tumors. (2) Methods: Preoperative CT images were acquired with eight skin-fixed fiducials and loaded into a navigation system. A patient tracker was mounted on the bed side. Patient-to-image paired point registration was performed, and an instrument tracker was mounted on a laparoscopic instrument and calibrated for instrument tracking. Surgical operations were performed with real-time stereotactic navigation assistance. (3) Results: Three patients underwent stereotactic navigation surgery. Fiducial registration errors were good to optimal (±1.9, ±3.4, and ±3.4 mm). Lesions were easily identified and targeted with real-time navigation. Surgeries were uneventful. Histopathology examinations identified one retro-rectal schwannoma, one lateral pelvic recurrence from rectal adenocarcinoma, and one advanced anal canal carcinoma. No navigation-related complications, readmissions, or postoperative mortalities were observed. (4) Conclusions: The application of laparoscopic stereotactic navigation surgery to complex low pelvic tumors is feasible and could impact oncological surgical quality by enabling tumor targeting and ensuring resection margins. Further wider series are needed to confirm stereotactic navigation's impact on challenging low pelvic tumors.