Bridging the gap: robotic applications in cerebral aneurysms neurointerventions - a systematic review.

Cerebral aneurysm is a life-threatening condition, which requires high precision during the neurosurgical procedures. Increasing progress of evaluating modern devices in medicine have led to common usage of robotic systems in many fields, including cranial aneurysm operations. However, currently no systematic review describes up-to date knowledge of this topic. Following PRISMA guidelines, we have independently screened and extracted works from seven databases. Only studies fulfilling inclusion criteria were presented in this study. Device used, operation time, complications, aneurysm type and patient demographics were extracted from each work. We identified a total of 995 articles from databases. We have found six original works and one supplementary article eligible for this synthesis. Majority of works (4/6) have implemented CorPath GRX in cerebral aneurysm procedures. The procedures involved diverse aneurysm locations, utilizing flow diverters, stents, or coiling. One study described implementation of robot-assist on 117 patients and compared results to randomized clinical trials. One work with a small patient cohort described use of the magnetically-controlled microguidewire in the coiling procedures, without any complications. Additionally, one case-series study described use of a robotic arm for managing intraoperative aneurysm rupture. Currently, robotical devices for cerebral aneurysm treatment mainly lack jailing and haptic feedback feature. Further development of these devices will certainly be beneficial for operators and patients, allowing for more precise and remote surgeries.

Machine Meets Brain: A Systematic Review of Effectiveness of Robotically Performed Cerebral Angiography Interventions.

BACKGROUND: Stroke is a leading cause of death in the United States, with significant economic and human costs. Early diagnosis and rapid treatment are critical for preventing stroke-related morbidity and mortality. However, accessibility to neurointerventional medical centers remains a challenge for many Americans, highlighting the need for innovative solutions to improve stroke management. METHODS: This systematic review adhered to the PRISMA (preferred reporting items for systematic reviews and meta-analyses) guidelines and included 5 medical databases to identify relevant studies on robotically assisted cerebral angiography (RCA). Studies focusing on in-human robotic intracranial cerebral angiography were included. A bias assessment was conducted using appropriate tools for randomized controlled trials (RCTs) and non-RCTs. RESULTS: A total of 7 studies met the inclusion criteria, with 1 RCT and 6 non-RCTs included in the analysis. Robotic systems such as CorPath GRX, Magellan robot, YDHB-NS01, VIR-2 (vascular interventional robot), and RobEnt were evaluated. The studies reported various success rates, procedure times, and complications associated with robotically assisted procedures. Overall, the robotic interventions demonstrated promising results in terms of safety and efficacy, with comparable outcomes to manual methods. Despite the promising findings, several limitations were identified, including technical issues with the robotic systems, the high costs, and limited long-term data. Future research should focus on standardizing protocols, conducting larger trials with longer follow-up periods, and assessing cost-effectiveness to determine the role of RCA in clinical practice. CONCLUSIONS: RCA shows potential as a valuable tool in neuroendovascular interventions. Addressing the technical challenges and conducting further research will be crucial to fully realize the clinical benefits of this innovative technology and improve patient outcomes in stroke management.

Mobile applications in radiology: own study based on polish data.

As the number of smartphones increases, so does the number of medical apps. Medical mobile applications are widely used in many medical fields by both patients and doctors. However, there are still few approved mobile applications that can be used in the diagnostic-therapeutic process and radiological apps are affected as well. We conducted our research by classifying radiological applications from the Google Play® store into appropriate categories, according to our own qualification system developed by researchers for the purposes of this study. In addition, we also evaluated apps from the App Store®. The radiology application rating system we created has not been previously used in other articles. Out of 228 applications from the Google Play store, only 6 of them were classified as "A" category with the highest standard. Apps from the App Store (157) were not categorized due to the lack of download counts, which was necessary in our app-rating system. The vast majority of applications are for educational purposes and are not used in clinical practice. This is due to the need of obtaining special permits and certificates from relevant institutions in order to use them in medical practice. We recommend applications from the Google Play store that have been classified in the "A" category, evaluating them as the most valuable. App Store apps data is described and presented in the form of diagrams and tables.

Multi-Label Classification of Chest X-ray Abnormalities Using Transfer Learning Techniques.

In recent years, deep neural networks have enabled countless innovations in the field of image classification. Encouraged by success in this field, researchers worldwide have demonstrated how to use Convolutional Neural Network techniques in medical imaging problems. In this article, the results were obtained through the use of the EfficientNet in the task of classifying 14 different diseases based on chest X-ray images coming from the NIH (National Institutes of Health) ChestX-ray14 dataset. The approach addresses dataset imbalances by introducing a custom split to ensure fair representation. Binary cross entropy loss is utilized to handle the multi-label difficulty. The model architecture comprises an EfficientNet backbone for feature extraction, succeeded by sequential layers including GlobalAveragePooling, Dense, and BatchNormalization. The main contribution of this paper is a proposed solution that outperforms previous state-of-the-art deep learning models average area under the receiver operating characteristic curve-AUC-ROC (score: 84.28%). The usage of the transfer-learning technique and traditional deep learning engineering techniques was shown to enable us to obtain such results on consumer-class GPUs (graphics processing units).

Chest X-ray Foreign Objects Detection Using Artificial Intelligence.

Diagnostic imaging has become an integral part of the healthcare system. In recent years, scientists around the world have been working on artificial intelligence-based tools that help in achieving better and faster diagnoses. Their accuracy is crucial for successful treatment, especially for imaging diagnostics. This study used a deep convolutional neural network to detect four categories of objects on digital chest X-ray images. The data were obtained from the publicly available National Institutes of Health (NIH) Chest X-ray (CXR) Dataset. In total, 112,120 CXRs from 30,805 patients were manually checked for foreign objects: vascular port, shoulder endoprosthesis, necklace, and implantable cardioverter-defibrillator (ICD). Then, they were annotated with the use of a computer program, and the necessary image preprocessing was performed, such as resizing, normalization, and cropping. The object detection model was trained using the You Only Look Once v8 architecture and the Ultralytics framework. The results showed not only that the obtained average precision of foreign object detection on the CXR was 0.815 but also that the model can be useful in detecting foreign objects on the CXR images. Models of this type may be used as a tool for specialists, in particular, with the growing popularity of radiology comes an increasing workload. We are optimistic that it could accelerate and facilitate the work to provide a faster diagnosis.

What Is Machine Learning, Artificial Neural Networks and Deep Learning?-Examples of Practical Applications in Medicine.

Machine learning (ML), artificial neural networks (ANNs), and deep learning (DL) are all topics that fall under the heading of artificial intelligence (AI) and have gained popularity in recent years. ML involves the application of algorithms to automate decision-making processes using models that have not been manually programmed but have been trained on data. ANNs that are a part of ML aim to simulate the structure and function of the human brain. DL, on the other hand, uses multiple layers of interconnected neurons. This enables the processing and analysis of large and complex databases. In medicine, these techniques are being introduced to improve the speed and efficiency of disease diagnosis and treatment. Each of the AI techniques presented in the paper is supported with an example of a possible medical application. Given the rapid development of technology, the use of AI in medicine shows promising results in the context of patient care. It is particularly important to keep a close eye on this issue and conduct further research in order to fully explore the potential of ML, ANNs, and DL, and bring further applications into clinical use in the future.

Usability of Mobile Solutions Intended for Diagnostic Images-A Systematic Review.

Despite the growing popularity of mobile devices, they still have not found widespread use in medicine. This is due to the procedures in a given place, differences in the availability of mobile devices between individual institutions or lack of appropriate legal regulations and accreditation by relevant institutions. Numerous studies have been conducted and compared the usability of mobile solutions designed for diagnostic images evaluation on various mobile devices and applications with classic stationary descriptive stations. This study is an attempt to compare the usefulness of currently available mobile applications which are used in the medical industry, focusing on imaging diagnostics. As a consequence of the healthcare sector's diversity, it is also not possible to design a universal mobile application, which results in a multitude of software available on the market and makes it difficult to reliably compile and compare studies included in this systematic review. Despite these differences, it was possible to identify both positive and negative features of portable methods analyzing radiological images. The mobile application of the golden mean in hospital infrastructure should be widely available, with convenient and simple usage. Our future research will focus on development in the use of mobile devices and applications in the medical sector.

Medical robots in cardiac surgery - application and perspectives.

Medical robots offer new standards and opportunities for treatment. This paper presents a review of the literature and market information on the current situation and future perspectives for the applications of robots in cardiac surgery. Currently in the United States, only 10% of thoracic surgical procedures are conducted using robots, while globally this value remains below 1%. Cardiac and thoracic surgeons use robotic surgical systems increasingly often. The goal is to perform more than one hundred thousand minimally invasive robotic surgical procedures every year. A surgical robot can be used by surgical teams on a rotational basis. The market of surgical robots used for cardiovascular and lung surgery was worth 72.2 million dollars in 2014 and is anticipated to reach 2.2 billion dollars by 2021. The analysis shows that Poland should have more than 30 surgical robots. Moreover, Polish medical teams are ready for the introduction of several robots into the field of cardiac surgery. We hope that this market will accommodate the Polish Robin Heart robots as well.

Total mesorectal excision using a soft and flexible robotic arm: a feasibility study in cadaver models.

BACKGROUND: Sponsored by the European Commission, the FP7 STIFF-FLOP project aimed at developing a STIFFness controllable Flexible and Learn-able manipulator for surgical operations, in order to overcome the current limitations of rigid-link robotic technology. Herein, we describe the first cadaveric series of total mesorectal excision (TME) using a soft and flexible robotic arm for optic vision in a cadaver model. METHODS: TME assisted by the STIFF-FLOP robotic optics was successfully performed in two embalmed male human cadavers. The soft and flexible optic prototype consisted of two modules, each measuring 60 mm in length and 14.3 mm in maximum outer diameter. The robot was attached to a rigid shaft connected to an anthropomorphic manipulator robot arm with six degrees of freedom. The controller device was equipped with two joysticks. The cadavers (BMI 25 and 28 kg/m2) were prepared according to the Thiel embalming method. The procedure was performed using three standard laparoscopic instruments for traction and dissection, with the aid of a 30° rigid optics in the rear for documentation. RESULTS: Following mobilization of the left colonic flexure and division of the inferior mesenteric vessels, TME was completed down to the pelvic floor. The STIFF-FLOP robotic optic arm seemed to acquire superior angles of vision of the surgical field in the pelvis, resulting in an intact mesorectum in both cases. Completion times of the procedures were 165 and 145 min, respectively. No intraoperative complications occurred. No technical failures were registered. CONCLUSIONS: The STIFF-FLOP soft and flexible robotic optic arm proved effective in assisting a laparoscopic TME in human cadavers, with a superior field of vision compared to the standard laparoscopic vision, especially low in the pelvis. The introduction of soft and flexible robotic devices may aid in overcoming the technical challenges of difficult laparoscopic procedures based on standard rigid instruments.

State of the art in medical robotics in Poland: development of the Robin Heart and other robots.

The first Polish project in medical robotics began in 2000. Now, a decade later, the Robin Heart surgical telemanipulator has the potential to become widely used in many branches of surgery. The original robot and mechatronic tools have successfully completed the required laboratory tests and animal studies. The Foundation of Cardiac Surgery Development in Zabrze, Poland, has launched a series of large-scale educational and awareness-raising activities aiming to promote medical robotics in Poland. At present, works on a rehabilitation robot are in progress in two centers. This article is an attempt to summarize the advances in medical robotics in Poland, to present the most interesting achievements to date and to discuss the prospects for further development.

Desarrollo de un modelo generalizado para realimentación de fuerza y torque en cirugía cardiotorácica robótica mínimamente invasiva: determinación de condiciones y restricciones / Development of a generalized model for force and torque feedback in robotic minimally invasive cardiothoracic surgery: identification of conditions and restrictions

INTRODUCCIÓN: los procedimientos de cirugía cardiotorácica mínimamente invasiva (MICS, su sigla en Inglés) buscan reducir las complicaciones de las grandes disecciones. No obstante, ante la falta de contacto directo con el tejido por parte del cirujano, éste recibe una sensación parcial de tacto y fuerza, lo que puede originar errores de procedimiento, inadecuada fuerza aplicada al tejido y fatiga durante el acto quirúrgico. La inclusión de dispositivos robóticos con la técnica MICS ha potencializado las habilidades del cirujano para la manipulación de los tejidos, y aunque los desarrollos del mercado no cuentan aún con retroalimentación táctil, se trabaja en prototipos robóticos que incorporan realimentación de fuerza y torque. OBJETIVO: proponer las condiciones y restricciones relacionadas con la incorporación de realimentación de fuerza y torque en MICS robótica, aplicables a diferentes configuraciones de manipuladores, y analizar la implementación de dichas condiciones en un simulador quirúrgico. MATERIAL Y MÉTODOS: partiendo del análisis de necesidades durante procedimientos cardiotorácicos y las condiciones de cirugía mínimamente invasiva, se identificaron los requerimientos para garantizar reflexión de fuerza y se realizó un análisis matemático de dichas consideraciones. Finalmente, se verificaron los análisis matemáticos mediante técnicas de modelización y simulación utilizando la plataforma computacional Matlab®. RESULTADOS: se argumentaron tres tipos de consideraciones: a) Cinemático: la existencia de un punto fijo, las formas de garantizarlo durante procedimientos MICS robóticos, y las trayectorias de movimiento que el manipulador sigue en aplicaciones de cirugía cardiotorácica; b) Dinámico: la repercusión de fuerzas externas en el manipulador y la manera de considerarlas en el desarrollo de controladores que permitan al cirujano percibir una sensación de contacto con el tejido; c) Sensorial: requerimientos de los sensores de fuerza y relación necesaria entre el número de sensores y actuadores para realimentar fuerza en MICS robótica. Posteriormente se implementaron dichas consideraciones en un simulador y se verificó el cumplimiento de las mismas. CONCLUSIONES: las condiciones relacionadas con la incorporación de un sensor de fuerza y la percepción del cirujano en cuanto al tacto y la fuerza aplicada, resultan ser importantes en procedimientos de MICS robótica y requiere la inclusión de un sistema de control que permita la optimización de procedimientos por telepresencia.

INTRODUCTION: the procedures in minimally invasive cardiothoracic surgery (MICS) aim to reduce the complications of major dissections. However, in the absence of direct contact of the surgeon with the tissue, he receives a partial sense of touch and strength, which can lead to procedural errors, inadequate force applied to the tissue and fatigue during surgery. The inclusion of robotic devices with the MICS technique has enhanced the technical skills of the surgeon to manipulate tissue, and although the market devices still do not have tactile feedback, research in robotic prototypes that incorporate feedback of force and torque is being done. OBJECTIVE: to propose the conditions and restrictions related to the integration of force and torque feedback in robotics MICS applicable to different configurations of manipulators and analyze the implementation of those conditions in a surgical simulator. MATERIAL AND METHODS: from the analysis of needs during cardiothoracic procedures and conditions of minimally invasive surgery, we identified the requirements to ensure reflection of force and performed a mathematical analysis of such considerations. Finally, mathematical analysis were verified by modeling and simulation techniques using the Matlab® computing platform. RESULTS: three types of considerations were argued: a) Kinematic: the existence of a fixed point; the way to guarantee it for robotic MICS procedures, and the trajectories of motion followed by the controller in the applications of Cardiothoracic Surgery, b) Dynamic: the impact of external forces on the manipulator and the way to consider them in the development of controllers that allow the surgeon to feel a sense of contact with the tissue, c) Sensory: requirements of the force sensors and necessary relationship between the number of sensors and actuators to feedback force in MICS robotics. Subsequently these considerations were implemented in a simulator and were checked for compliance. CONCLUSIONS: the conditions related to the incorporation of a force sensor and the perception of the surgeon in terms of touch and force applied turns out to be important in robotics MICS procedures and requires the inclusion of a control system that enables the optimization of telepresence procedures.

Norwood with right ventricle-to-pulmonary artery conduit is more effective than Norwood with Blalock-Taussig shunt for hypoplastic left heart syndrome: mathematic modeling of hemodynamics.

OBJECTIVE: The introduction of right ventricle to pulmonary artery (RV-PA) conduit in the Norwood procedure for hypoplastic left heart syndrome resulted in a higher survival rate in many centers. A higher diastolic aortic pressure and a higher mean coronary perfusion pressure were suggested as the hemodynamic advantage of this source of pulmonary blood flow. The main objective of this study was the comparison of two models of Norwood physiology with different types of pulmonary blood flow sources and their hemodynamics. METHOD: Based on anatomic details obtained from echocardiographic assessment and angiographic studies, two three-dimensional computer models of post-Norwood physiology were developed. The finite-element method was applied for computational hemodynamic simulations. Norwood physiology with RV-PA 5-mm conduit and Blalock-Taussig shunt (BTS) 3.5-mm shunt were compared. Right ventricle work, wall stress, flow velocity, shear rate stress, energy loss and turbulence eddy dissipation were analyzed in both models. RESULTS: The total work of the right ventricle after Norwood procedure with the 5-mm RV-PA conduit was lower in comparison to the 3.5-mm BTS while establishing an identical systemic blood flow. The Qp/Qs ratio was higher in the BTS group. CONCLUSIONS: Hemodynamic performance after Norwood with the RV-PA conduit is more effective than after Norwood with BTS. Computer simulations of complicated hemodynamics after the Norwood procedure could be helpful in establishing optimal post-Norwood physiology.

The influence of physical and chemical agents on photooxidation of porcine pericardial collagen.

Photooxidation is a method of tissue fixation resulting in protein crosslinking due to illumination in the presence of a dye. The aim of the study was to evaluate the impact of dyes, photooxidation time and the type of applied light on the porcine pericardial collagen crosslinking. The collagen modifications were evaluated on the basis of pericardial sensitivity to pepsin digestion. The hydrolysate components were evaluated qualitatively and quantitatively. All hydrolysates contained collagen alpha chains, their aggregates and degradation products. Methylene blue and methylene green-mediated 4 h photooxidation in the presence of visible light caused similar decrease in pericardium sensitivity to pepsin. However, both fixation types generated remarkable amounts of alpha chain degradation products. The prolongation of photooxidation time to 8 h did not increase the pericardial sample resistance to pepsin. Moreover, these sample hydrolysates revealed an elevated alpha chain content. Violet light mediated photooxidation did not alter pericardial sensitivity to pepsin when compared with fixation under visible light. Nevertheless, violet light fixed tissues displayed a decrease in collagen degradation products. The application of violet light in photooxidation of porcine pericardium will probably allow to obtain enzyme resistant bioprostheses with better mechanical properties compared with those obtained after visible light mediated process.

[Methods of collagenous tissue fixation in the preparation of bioprostheses]. / Metody stabilizacji materialu kolagenowego wykorzystywane w bioprotetyce.

The use of biological materials in construction of bioprostheses requires the application of different chemical or physical procedures of fixation increasing bioprostheses resistance to enzymatic or chemical degradation and reducing their antigenicity. Methods typically concentrate on creating additional intra- and intermolecular chemical bonds between collagen molecules. This review focuses on the various methods of stabilization of collagenous tissues including chemical fixatives and physical agents.