Negative Pressure Wound Therapy (NPWT) is a treatment that promotes healing of chronic wounds. Despite high prevalence of chronic wounds in Low- and Middle-Income Countries (LMICs), NPWT devices are not available nor affordable. This study aims to improve chronic wound care in LMICs by presenting the Wound Care (WOCA) system, designed for building, testing and use in LMICs. Design requirements were formulated using input from literature, ISO standards, and wound care experts. The WOCA design was developed to provide safe, portable, user-friendly and affordable NPWT to patients in LMICs. The design features an adjustable operating pressure ranging from −75 to −125 mmHg, a battery for portability, a 300 ml canister, overflow protection, and system state alarms. An Arduino controls the pressure and monitors the system state. Three prototypes were developed and built in Nepal, and their performance was evaluated. Pressure control was 125 ± 10 % mmHg, internal leakage was 7.5 ± 4.3 mmHg/min, reserve capacity was 189 ± 16.9 ml/min, and overflow protection and alarm systems were effectively working. Prototype cost was approximately 280 USD. The WOCA demonstrates to be a locally producible NPWT device that can safely generate a stable vacuum. Future research will include clinical trials situated in LMICs.

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Since the introduction of robot-assisted laparoscopic surgery, efforts have been made to incorporate force sensing technologies to monitor critical components and to provide force feedback. The advanced laparoscopic robotic system (AdLap RS) is a robotic platform that aims to make robot technology more sustainable through the use of the fully reusable shaft-actuated tip-articulating (SATA) instruments. The SATA instrument driver features electronics and sensors exposed to the sterile environment, which complicate the sterilisation process. The aim of this study was to develop and validate smart sensing in stepper motors using the back electromotive force in a newly developed Smart SATA Driver (SSD), eliminating the need for sensors in the sterile environment. Methods: The stepper drivers were equipped with TMC2209 ICs featuring StallGuard technology to measure back EMF. The tip was actuated up until a set StallGuard threshold value was reached, at which the resulting tip force was measured. This cycle was repeated ten times for a range of threshold levels. A regression analysis with a power series model was used to determine the quality of the fit. Results: The SSD is capable of exerting tip forces between 2.4 and 8.2 N. The back EMF force test demonstrated a strong correlation between obtained StallGuard values and measured tip forces. The regression analysis showed an R-squared of 0.95 and a root Mean squared error of 0.4 N. Discussion: The back EMF force test shows promise for force feedback, but its accuracy limits real-time use due to back EMF fluctuations. Future improvements in motor stability and refining the back EMF model are needed to enable real-time feedback. Conclusion: The strong correlation during the back EMF force test shows its potential as a low-budget method for detecting motor stalls and estimating tool–tissue forces without the need for sensors in laparoscopic instruments.@en

Endovascular intervention is a minimally invasive method for treating cardiovascular diseases. Although fluoroscopy, known for real-time catheter visualization, is commonly used, it exposes patients and physicians to ionizing radiation and lacks depth perception due to its 2D nature. To address these limitations, a study was conducted using teleoperation and 3D visualization techniques. This in-vitro study involved the use of a robotic catheter system and aimed to evaluate user performance through both subjective and objective measures. The focus was on determining the most effective modes of interaction. Three interactive modes for guiding robotic catheters were compared in the study: 1) Mode GM, using a gamepad for control and a standard 2D monitor for visual feedback; 2) Mode GH, with a gamepad for control and HoloLens providing 3D visualization; and 3) Mode HH, where HoloLens serves as both control input and visualization device. Mode GH outperformed other modalities in subjective metrics, except for mental demand. It exhibited a median tracking error of 4.72 mm, a median targeting error of 1.01 mm, a median duration of 82.34 s, and a median natural logarithm of dimensionless squared jerk of 40.38 in the in-vitro study. Mode GH showed 8.5%, 4.7%, 6.5%, and 3.9% improvements over Mode GM and 1.5%, 33.6%, 34.9%, and 8.1% over Mode HH for tracking error, targeting error, duration, and dimensionless squared jerk, respectively. To sum up, the user study emphasizes the potential benefits of employing HoloLens for enhanced 3D visualization in catheterization. The user study also illustrates the advantages of using a gamepad for catheter teleoperation, including user-friendliness and passive haptic feedback, compared to HoloLens. To further gauge the potential of using a more traditional joystick as a control input device, an additional study utilizing the Haption Virtuose robot was conducted. It reveals the potential for achieving smoother trajectories, with a 38.9% reduction in total path length compared to a gamepad, potentially due to its larger range of motion and single-handed control.

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Background: Laparoscopic surgery requires a complex set of motor skills. Currently, basic laparoscopic skills training is performed in a static environment, while intraoperatively, abdominal tissue is often moving. The aim of this study was to develop a dynamic training platform and evaluate its impact on laparoscopic skills acquisition in a box trainer. Methods: The Dynamic Laparoscopic Platform (DyLaP) includes a moving base which has been intergrated with the Lapron box trainer and the ForceSense objective measurement system. Dynamic training was evaluated in a comparative study where novices were divided into a static and dynamic training group, performing six training trials of a peg transfer task with the DyLaP. Afterwards, both groups performed a dynamic exam task. Task manipulation (force) and instrument efficiency (path length and time) were measured. Results: Participants (n = 12) exhibited a significant difference (p < 0.05) in time, path length, and maximum force between the static and dynamic groups in the first trial. Learning curves were most prevalent in the dynamic group. Conclusions: The DyLaP can be used to provide a challenging and realistic training environment. From the comparative peg transfer study, it can be concluded that dynamic training significantly affects laparoscopic skill acquisition. More research is needed to evaluate dynamic training effects in force-based training tasks.

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Background: Preoperative planning of patients diagnosed with pancreatic head cancer is difficult and requires specific expertise. This pilot study assesses the added value of three-dimensional (3D) patient models and computer-aided detection (CAD) algorithms in determining the resectability of pancreatic head tumors. Methods: This study included 14 hepatopancreatobiliary experts from eight hospitals. The participants assessed three radiologically resectable and three radiologically borderline resectable cases in a simulated setting via crossover design. Groups were divided in controls (using a CT scan), a 3D group (using a CT scan and 3D models), and a CAD group (using a CT scan, 3D and CAD). For the perceived fulfillment of preoperative needs, the quality and confidence of clinical decision-making were evaluated. Results: A higher perceived ability to determine degrees and the length of tumor–vessel contact was reported in the CAD group compared to controls (p = 0.022 and p = 0.003, respectively). Lower degrees of tumor–vessel contact were predicted for radiologically borderline resectable tumors in the CAD group compared to controls (p = 0.037). Higher confidence levels were observed in predicting the need for vascular resection in the 3D group compared to controls (p = 0.033) for all cases combined. Conclusions: “CAD (including 3D) improved experts’ perceived ability to accurately assess vessel involvement and supports the development of evolving techniques that may enhance the diagnosis and treatment of pancreatic cancer”.

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Objective: Navigation through tortuous and deformable vessels using catheters with limited steering capability underscores the need for reliable path planning. State-of-the-art path planners do not fully account for the deformable nature of the environment. Methods: This work proposes a robust path planner via a learning from demonstrations method, named Curriculum Generative Adversarial Imitation Learning (C-GAIL). This path planning framework takes into account the interaction between steerable catheters and vessel walls and the deformable property of vessels. Results: In-silico comparative experiments show that the proposed network achieves a 38% higher success rate in static environments and 17% higher in dynamic environments compared to a state-of-the-art approach based on GAIL. In-vitro validation experiments indicate that the path generated by the proposed C-GAIL path planner achieves a targeting error of 1.26±0.55mm and a tracking error of 5.18±3.48mm. These results represent improvements of 41% and 40% over the conventional centerline-following technique for targeting error and tracking error, respectively. Conclusion: The proposed C-GAIL path planner outperforms the state-of-the-art GAIL approach. The in-vitro validation experiments demonstrate that the path generated by the proposed C-GAIL path planner aligns better with the actual steering capability of the pneumatic artificial muscle-driven catheter utilized in this study. Therefore, the proposed approach can provide enhanced support to the user in navigating the catheter towards the target with greater accuracy, effectively meeting clinical accuracy requirements. Significance: The proposed path planning framework exhibits superior performance in managing uncertainty associated with vessel deformation, thereby resulting in lower tracking errors.

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Laparoscopic surgery offers significant benefits to patients in low-resource settings compared to open surgery such as faster recovery, less pain, and lower infection rate. However, there exist significant barriers to the safe introduction of laparoscopy such as high costs and limited availability of trained staff. Low- and middle-income country (LMIC) hospitals suffer from higher post-surgical infection which might be due to the limited facilities for the sterile reprocessing of laparoscopic instruments. To design a solution to this issue, a detailed understanding of local settings was needed. Therefore, this research applied a context-driven design approach, based on the Roadmap for Design of Surgical Equipment for Safe Surgery Worldwide. Over several design phases, the need for a reprocessing device was established. An analysis of the sterile reprocessing of laparoscopic instruments led to a list of context-specific design requirements. These were translated to a final conceptual design of a laparoscopic instrument cleaner using a waterfall design method. Finally, a usability study of the loading system of the device was conducted with nurses in four Indian hospitals. A root-cause analysis of the usability study showed that the device was not intuitive enough to use for Indian nurses. A redesign of the loading system was made to improve its ease of use. The design process used in this study can be used as an example for designers wanting to address the critical issue of context-specific medical devices worldwide, or more specifically, the sterile supply of surgical instruments in resource-constrained environments.

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This systematic review explores machine learning (ML) applications in surgical motion analysis using non-optical motion tracking systems (NOMTS), alone or with optical methods. It investigates objectives, experimental designs, model effectiveness, and future research directions. From 3632 records, 84 studies were included, with Artificial Neural Networks (38%) and Support Vector Machines (11%) being the most common ML models. Skill assessment was the primary objective (38%). NOMTS used included internal device kinematics (56%), electromagnetic (17%), inertial (15%), mechanical (11%), and electromyography (1%) sensors. Surgical settings were robotic (60%), laparoscopic (18%), open (16%), and others (6%). Procedures focused on bench-top tasks (67%), clinical models (17%), clinical simulations (9%), and non-clinical simulations (7%). Over 90% accuracy was achieved in 36% of studies. Literature shows NOMTS and ML can enhance surgical precision, assessment, and training. Future research should advance ML in surgical environments, ensure model interpretability and reproducibility, and use larger datasets for accurate evaluation.

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Manipulating a flexible ureteroscope is difficult, due to its bendable body and hand–eye coordination problems, especially when exploring the lower pole of the kidney. Though robotic interventions have been adopted in various clinical scenarios, they are rarely used in ureteroscopy. This study proposes a teleoperation system consists of a soft robotic endoscope together with a Guidance Virtual Fixture (GVF) to help users explore the kidney’s lower pole. The soft robotic arm was a cable-driven, 3D-printed design with a helicoid structure. GVF was dynamically constructed using video streams from an endoscopic camera. With a haptic controller, GVF can provide haptic feedback to guide the users in following a trajectory. In the user study, participants were asked to follow trajectories when the soft robotic arm was in a retroflex posture. The results suggest that the GVF can reduce errors in the trajectory tracking tasks when the users receive the proper training and gain more experience. Based on the NASA Task Load Index questionnaires, most participants preferred having the GVF when manipulating the robotic arm. In conclusion, the results demonstrate the benefits and potential of using a robotic arm with a GVF. More research is needed to investigate the effectiveness of the GVFs and the robotic endoscope in ureteroscopic procedures.@en

Endovascular interventions are minimally invasive procedures that utilize the vascular system to access anatomical regions deep within the body. Image-guided assistance provides valuable real-time information about the dynamic state of the vascular environment. However, the reliance on intraoperative 2-D fluoroscopy images limits depth perception, prompting the demand for intraoperative 3-D imaging. Existing image registration methods face difficulties in accurately incorporating tissue deformations compared to the preoperative 3-D model, particularly in a weakly supervised manner. Additionally, reconstructing deformations from 2-D to 3-D space and presenting this intraoperative model visually to clinicians poses further complexities. To address these challenges, this study introduces a novel deformable model-to-image registration framework using deep learning. Furthermore, this research proposes a visualization method through augmented reality to guide endovascular interventions. This study utilized image data collected from nine patients who underwent transcatheter aortic valve implantation (TAVI) procedures. The registration results in 2-D indicate that the proposed deformable model-to-image registration framework achieves a modified dice similarity coefficient (MDSC) value of 0.89±0.02 and a penalization of deformations in spare space (PDSS) value of 0.04±0.01, offering an improvement of 3.5%-98.6% over the state-of-the-art image registration approach. Additionally, the accuracy of registration in 3-D was evaluated using a dataset obtained from an intervention simulator, resulting in a mean absolute error (MAE) of 1.51±1.02 mm within the region of interest. Overall, the study validates the feasibility and accuracy of the proposed weakly supervised deformable model-to-image registration framework, demonstrating its potential to provide intraoperative 3-D imaging as intervention assistance in dynamic vascular environments.

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Background: The steep radiation dose gradients in cervical cancer brachytherapy (BT) necessitate a thorough understanding of the behavior of afterloader source cables or needles in the curved channels of (patient-tailored) applicators. Purpose: The purpose of this study is to develop and validate computer models to simulate: (1) BT source positions, and (2) insertion forces of needles in curved applicator channels. The methodology presented can be used to improve the knowledge of instrument behavior in current applicators and aid the development of novel (3D-printed) BT applicators. Methods: For the computer models, BT instruments were discretized in finite elements. Simulations were performed in SPACAR by formulating nodal contact force and motion input models and specifying the instruments’ kinematic and dynamic properties. To evaluate the source cable model, simulated source paths in ring applicators were compared with manufacturer-measured source paths. The impact of discrepancies on the dosimetry was estimated for standard plans. To validate needle models, simulated needle insertion forces in curved channels with varying curvature, torsion, and clearance, were compared with force measurements in dedicated 3D-printed templates. Results: Comparison of simulated with manufacturer-measured source positions showed 0.5–1.2 mm median and <2.0 mm maximum differences, in all but one applicator geometry. The resulting maximum relative dose differences at the lateral surface and at 5 mm depth were 5.5% and 4.7%, respectively. Simulated insertion forces for BT needles in curved channels accurately resembled the forces experimentally obtained by including experimental uncertainties in the simulation. Conclusion: The models developed can accurately predict source positions and insertion forces in BT applicators. Insights from these models can aid novel applicator design with improved motion and force transmission of BT instruments, and contribute to the estimation of overall treatment precision. The methodology presented can be extended to study other applicator geometries, flexible instruments, and afterloading systems.

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While articulated surgical instruments have enabled the proliferation of minimally invasive interventions, procedures such as laparo-endoscopic single-site surgery are waning in popularity. One potential reason for this decline is a lack of sufficiently dexterous instruments. Although multi-steerable instruments exist, these are often complex and therefore expensive assemblies. Even when 3D printing was used to simplify the design of these instruments, the requirement for high-performance 3D printers limited the reduction in manufacturing costs. To tackle this issue, we propose six guidelines for converting a 3D printed compliant medical instrument from printing on a Digital Light Processing (DLP) printer to a Fused Filament Fabrication (FFF) printer. These guidelines provide a framework to manage and compensate for differences in the two processes to achieve comparable results at a reduced cost. The proposed guidelines were evaluated by assembling a FFF 3D printed prototype that shows equivalent performance to its DLP 3D printed counterpart.

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The demographic shift has increased the demand for surgical interventions to address age-related degenerative diseases, such as spinal fusion. Accurate placement of pedicle screws, crucial for successful spinal fusion, varies widely with physician experience. Integrating tissue sensing into spine surgical instruments allows intraoperative examination of tissue properties, providing surgeons with additional information to prevent screw misplacement. This paper introduces a handheld fiber-optic tissue sensing device for real-time bone tissue differentiation during spine surgery using Diffuse Reflectance Spectroscopy (DRS). Our prototype employs laser diodes at two distinct wavelengths for tissue illumination, eliminating the need for a spectrometer and enabling direct light collection with a photodiode. The device includes a printed circuit board (PCB) with driver circuits that are adjustable for varying laser diode output power, and signal amplification to convert the photodiode current to a measurable voltage signal. Controlled by a microcontroller, the device computes a reflectance ratio from both laser diode signals to provide real-time audio feedback to surgeons across various healthcare settings. Despite challenges in coupling efficiencies from manual fiber-coupling of the diodes, our prototype is able to emit and collect light to distinguish bone tissues with DRS, demonstrating feasibility. It is compact, made of low-cost and readily available components, and offers fast, real-time feedback, thus serving as a successful proof-of-concept for enhancing surgical accuracy during spinal fusion procedures.@en

BACKGROUND AND PURPOSE: Although MRI-based image guided adaptive brachytherapy (IGABT) for locally advanced cervical cancer (LACC) has resulted in favorable outcomes, it can be logistically complex and time consuming compared to 2D image-based brachytherapy, and both physically and emotionally intensive for patients. This prospective study aims to perform time-action and patient experience analyses during IGABT to guide further improvements. MATERIALS AND METHODS: LACC patients treated with IGABT were included for the time-action (56 patients) and patient experience (29 patients) analyses. Times per treatment step were reported on a standardized form. For the patient experience analysis, a baseline health status was established with the EQ-5D-5L questionnaire and the perceived pain, anxiety and duration for each treatment step were assessed with the NRS-11. RESULTS: The median total procedure time from arrival until discharge was 530 (IQR: 480–565) minutes. Treatment planning (delineation, reconstruction, optimization) required the most time and took 175 (IQR: 145–195) minutes. Highest perceived pain was reported during applicator removal and treatment planning, anxiety during applicator removal, and duration during image acquisition and treatment planning. Perceived pain, anxiety and duration were correlated. Higher pre-treatment pain and anxiety scores were associated with higher perceived pain, anxiety and duration. CONCLUSION: This study highlights the complexity, duration and impact on patient experience of the current IGABT workflow. Patient reported pre-treatment pain and anxiety can help identify patients that may benefit from additional support. Research and implementation of measures aiming at shortening the overall procedure duration, which may include logistical, staffing and technological aspects, should be prioritized.

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It is estimated that in Africa 30,000-130,000 new cases arise annually and a total of 3 million women suffer from untreated vesicovaginal fistulas (VVFs) in Low- and Middle-Income Countries (LMICs) worldwide. A VVF is an abnormal communication between the bladder and vagina that can result in urine leakage through the vagina. This does not only lead to physical but also psychological problems. In LIMCs, the most common cause of a VVF is obstructed labour. Early childbearing (before full pelvic growth is achieved), poor socioeconomic status, low literacy rate, malnourishment, inadequately developed infrastructure for health care for pregnant women and lack of access to emergency obstetric services are factors that impact the high rate of cases in LIMCs. Some of the consequences are stigmatization and social isolation, because obstructed labour is often seen as a punishment from God and patients are abandoned by their families because of the smell of urine. [...]@en

Introduction: In clinical practice, fetal heart rate monitoring is performed intermittently using Doppler ultrasound, typically for 30 minutes. In case of a non-reassuring heart rate pattern, monitoring is usually prolonged. Noninvasive fetal electrocardiography may be more suitable for prolonged monitoring due to improved patient comfort and signal quality. This study evaluates the performance and patient experience of four noninvasive electrocardiography devices to assess candidate devices for prolonged noninvasive fetal heart rate monitoring. Material and methods: Non-critically sick women with a singleton pregnancy from 24 weeks of gestation were eligible for inclusion. Fetal heart rate monitoring was performed during standard care with a Doppler ultrasound device (Philips Avalon-FM30) alone or with this Doppler ultrasound device simultaneously with one of four noninvasive electrocardiography devices (Nemo Fetal Monitoring System, Philips Avalon-Beltless, Demcon Dipha-16 and Dräger Infinity-M300). Performance was evaluated by: success rate, positive percent agreement, bias, 95% limits of agreement, regression line, root mean square error and visual agreement using FIGO guidelines. Patient experience was captured using a self-made questionnaire. Results: A total of 10 women were included per device. For fetal heart rate, Nemo performed best (success rate: 99.4%, positive percent agreement: 94.2%, root mean square error 5.1 BPM, bias: 0.5 BPM, 95% limits of agreement: −9.7 – 10.7 BPM, regression line: y = −0.1x + 11.1) and the cardiotocography tracings obtained simultaneously by Nemo and Avalon-FM30 received the same FIGO classification. Comparable results were found with the Avalon-Beltless from 36 weeks of gestation, whereas the Dipha-16 and Infinity-M300 performed significantly worse. The Avalon-Beltless, Nemo and Infinity-M300 closely matched the performance of the Avalon-FM30 for maternal heart rate, whereas the performance of the Dipha-16 deviated more. Patient experience scores were higher for the noninvasive electrocardiography devices. Conclusions: Both Nemo and Avalon-Beltless are suitable devices for (prolonged) noninvasive fetal heart rate monitoring, taking their intended use into account. But outside its intended use limit of 36 weeks’ gestation, the Avalon-Beltless performs less well, comparable to the Dipha-16 and Infinity-M300, making them currently unsuitable for (prolonged) noninvasive fetal heart rate monitoring. Noninvasive electrocardiography devices appear to be preferred due to greater comfort and mobility.

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Minimally Invasive Procedures (MIPs) emerged as an alternative to more invasive surgical approaches, offering patient benefits such as smaller incisions, less pain, and shorter hospital stay. In one class of MIPs, where natural body lumens or small incisions are used to access deeper anatomical locations, Flexible Surgical and Interventional Robots (FSIRs) such as catheters and endoscopes are widely used. Due to their flexible and compliant nature, FSIRs can be inserted via natural orifices or small incisions, then moved towards hard-to-reach targets to perform interventional tasks. However, existing FSIRs are confronted with challenges in sensing, control, and navigation. These issues stem from the robot's non-linear behavior and the intricate nature of the lumens, where accurately modeling the complex interactions and disturbances proves to be exceptionally difficult. The rapid advances in Machine Learning (ML) have facilitated the widespread adoption of ML techniques in FSIRs. This article provides an overview of these efforts by first introducing a classification of existing ML algorithms, including traditional ML methods and modern Deep Learning (DL) approaches, commonly used in FSIRs. Next, the use of ML algorithms is surveyed per sub-domain, namely for perception, modeling, control, and navigation. Trends, popularity, strengths, and/or limitations of different ML algorithms are analyzed. The different roles that ML plays among tasks are investigated and described. Finally, discussions are conducted on the limitations and the prospects of ML in MIPs.

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Diffuse Reflectance Spectroscopy (DRS) can provide tissue feedback for pedicle screw placement in spine surgery, yet the integration of fiber optics into the tip of the pedicle probe, a device used to pierce through bone, is challenging, since the optical probing depth and signal-to-noise ratio (SNR) are affected negatively compared to those of a blunt DRS probe. Through Monte Carlo simulations and optical phantom experiments, we show how differences in the shape of the instrument tip influence the acquired spectrum. Our findings demonstrate that a single bevel with an angle of 30∘ offers a solution to anticipate cortical breaches during pedicle screw placement. Compared to a blunt probe, the optical probing depth and SNR of a cone tip are reduced by 50%. The single bevel tip excels with 75% of the optical probing depth and a SNR remaining at approximately ⅔, facilitating the construction of a surgical instrument with integrated DRS.@en

Introduction: Most robotic instruments and their drives still risk residual contamination due to cleaning complexities, rendering them limited reusable, and tend to have larger instruments than the 5mm laparoscopic standard. The novel steerable laparoscopic SATA-LRS uses modularity for cleanability and exchangeability. The SATA-Drive: a robotic driver designed for the actuation of a 3mm scaled version of the SATA-LRS is presented. Methods: A modular, expandable gear mechanism was designed to efficiently rotate and translate the instrument shafts. The 3mm SATA-LRS is controlled as proof. An user-experiment is conducted to test the (de)coupling of the instrument to and from the drive. Results: A video shows the SATA-Driver successfully articulating, rotating and grasping the end-effector. End-effector dis- and reassembly is possible in 36 (13 SD) seconds, while complete instrument coupling requires 28(8 SD) seconds and de-coupling requires 16 (7 SD) seconds. Discussion: A non-surgical robot arm, mounted with the SATA-drive has effectively been transformed into a system similar to robot assisted laparoscopy. The modularity of the drive's segmented build can easily be adapted and could benefit the adoption of future instruments. The SATA-LRS's cleanability features and its end-effector changes without disassembly are expected to benefit medical robotics. The 3mm SATA-LRS shows the instrument's potential for mini-laparoscopy.

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