Search Results (299)

Endoscopic spine surgery (ESS)—including full-endoscopic transforaminal and interlaminar techniques, and unilateral biportal endoscopy (UBE)—offers patients smaller incisions, preserved paraspinal muscle, and faster recovery. Because the working corridor is narrow, intraoperative fluoroscopy plays a larger role than in open or microscopic approaches, making radiation exposure worthy of attention for both patients and surgeons. This narrative review aims to be a practical resource for the endoscopic spine surgeon. We synthesize the available literature on typical radiation doses across the main ESS techniques, compare them with minimally invasive transforaminal lumbar interbody fusion (MIS-TLIF) and open alternatives, review the factors that drive exposure, and walk through the full menu of dose-optimization options—from simple measures such as collimation, pulsed fluoroscopy, and leaded eyewear, through navigation platforms, to robotic guidance. A consistent practical observation is that the simplest, least expensive interventions often deliver the largest dose reductions. Capital-intensive technologies add real value, particularly for endoscopic interbody fusion, and work best alongside rather than in place of these basics. With routine dosimetry and straightforward as-low-as-reasonably-achievable (ALARA) practices, surgeons can continue to build on the already favourable profile of ESS while keeping radiation exposure low. Conclusions are tempered by the largely retrospective and heterogeneous nature of the underlying evidence. Full article

Background/Objectives: Artificial intelligence (AI) is increasingly proposed to improve surgical planning, guidance, and postoperative surveillance. Yet many promising applications remain disconnected from the full surgical pathway and the feasible limitations of clinical deployment. In contrast to prior reviews that primarily catalog AI use cases, this review combines the literature to define the translational pathway—from label design through staged validation to workflow integration—required for clinically deployable computed tomography (CT)-based surgical AI. CT and particularly computed tomography angiography (CTA) are especially usable sources for surgical AI because they provide a standardized three-dimensional anatomic model that is already embedded in many clinical workflows. In autologous breast reconstruction, deep inferior epigastric perforator (DIEP) flap CTA offers an unusually strong model system: the anatomy is discrete, surgeon decisions are actionable, and downstream operative and postoperative outcomes are measurable. These characteristics make DIEP reconstruction suitable not only for technical model development, but also for exacting testing of how CT-based AI should be annotated, validated, displayed, and governed. Methods: This focused narrative review combines evidence across the surgical workflow, spanning preoperative planning and risk stratification, intraoperative support, and postoperative monitoring. Reporting standards, implementation frameworks, governance, and regulatory sources were also considered when directly relevant to clinical deployment. Results: Across the available literature on breast reconstruction with the DIEP flap, preoperative CTA has been associated with reductions in operative time of approximately 54–76 min in individual studies. Semi-automated perforator mapping can reduce review time from 2 to 3 h to approximately 30 min. Intraoperative extended-reality tools and surgeon-facing navigation systems illustrate the importance of the ‘last mile’ of translation, while postoperative monitoring models show how imaging-linked data can support a closed-loop learning system. Across these stages, recurring limits include target mismatch, weak external validation, protocol variability, inconsistent reporting, limited subgroup analysis, and inadequate integration of economic and governance considerations. Conclusions: We argue that the next important step is not a generic autonomous model, but a clinically deployable DIEP-CTA-AI program. The practical blueprint proposed here is staged: structured anatomical labels, separate imaging, surgeons’ decisions, and outcome reference standards, dense intermediate endpoints, retrospective and external validation, reader studies, prospective silent deployment, and workflow-impact assessment. If implemented in this way, DIEP flap CTA can serve as a practical blueprint for CT-based AI translation in surgery more broadly. Full article

Dental implant placement has evolved from conventional freehand techniques toward digitally guided workflows integrating cone-beam computed tomography (CBCT), computer-aided design/computer-aided manufacturing (CAD/CAM), and dynamic navigation systems. Although guided surgery improves positional accuracy, its clinical relevance compared with freehand placement remains debated. This narrative review, based on a systematic and structured literature search following predefined selection criteria, analyzes studies published between 2000 and 2025 comparing guided and freehand implant placement regarding accuracy, survival, complications, biological outcomes, and workflow efficiency. Searches of PubMed/MEDLINE, Embase, and Web of Science identified 40 eligible human clinical studies for qualitative synthesis. Guided placement consistently demonstrated greater positional accuracy, with angular deviations of approximately 2–4° versus 5–9° for freehand placement and linear deviations reduced by about 1 mm. Nevertheless, implant survival rates were high and comparable for both techniques, generally exceeding 95% across short- and medium-term follow-up. Overall complication rates were low; guided approaches reduced anatomical risk and improved prosthetic predictability in complex or multi-implant cases, while freehand placement allowed greater intraoperative flexibility and tactile feedback, potentially optimizing primary stability in variable bone conditions. Marginal bone loss and peri-implant tissue outcomes were similar between approaches. Guided workflows required additional planning time and costs but enhanced reproducibility in complex rehabilitations. Guided and freehand implant placement should therefore be considered complementary strategies, with optimal outcomes depending on case selection, surgical expertise, and the balanced integration of digital technologies into contemporary implant practice. Full article

The convergence of artificial intelligence and robotic surgery is redefining the management of genitourinary cancers by enhancing diagnostic accuracy, surgical precision, and training efficiency. This narrative review explores recent advancements in artificial intelligence applications across the cancer care continuum, with a focus on prostate, kidney, and bladder malignancies. Artificial intelligence tools, particularly those based on machine learning and deep learning, have demonstrated strong performance in analyzing imaging data, segmenting tumors, predicting pathological features, and supporting clinical decision-making. Intraoperatively, artificial intelligence enables skill assessment, personalized feedback, and real-time navigation by processing data from surgical videos and robotic system sensors. Augmented reality and intraoperative modeling further enhance visualization and margin control during complex procedures. The review also discusses emerging technologies such as single-port robotic platforms, which offer advantages in confined anatomical spaces and support less invasive approaches. Additionally, the growing field of telesurgery is addressed, highlighting its feasibility for complex urologic operations across vast distances. While many of these innovations are still in early stages of clinical validation, their integration into practice has the potential to improve oncologic and functional outcomes, expand access to expert care, and foster the development of next-generation surgical strategies in urologic oncology. Full article

Background and Objectives: Minimally invasive cervical spine surgery (MIS-CSS) relies heavily on intraoperative fluoroscopic imaging, raising concerns about radiation exposure to patients and surgical staff. Unlike lumbar MIS, cervical-specific radiation exposure has not been systematically reviewed, despite distinct anatomical considerations, including proximity to the thyroid gland and lens of the eye. This review aims to quantify intraoperative radiation exposure during MIS cervical spine procedures and evaluate available dose-reduction strategies. Materials and Methods: A systematic literature search was conducted across PubMed/MEDLINE, Scopus, and Google Scholar in April 2026 following PRISMA 2020 guidelines. Studies reporting original quantitative radiation data during minimally invasive cervical spine procedures in adult patients (≥10 patients) were included. Quality was assessed using the MINORS tool and the JBI checklist. Results: Seven studies encompassing 380 patients were included. Procedures comprised ACDF (four studies), minimally invasive posterior cervical laminoforaminotomy (two studies), and CT-navigated cervical instrumentation (one study). Patient effective doses during ACDF ranged from 0.015 to 1.3 mSv, with thyroid doses of 0.194–0.290 mGy. Standalone ACDF reduced patient dose by 36–58% compared to plated ACDF (p < 0.001). Navigation-assisted posterior cervical foraminotomy achieved a median fluoroscopy time of 10 s with negligible staff exposure. Surgeon per-procedure exposure during cervical discectomy (chest 0.122 µSv, lens 3.1 µSv, hands 7.1 µSv) was approximately half that of lumbar discectomy. Conclusions: Radiation doses during individual MIS cervical procedures appear to be within occupational safety limits, though the current evidence is insufficient to establish definitive dose thresholds. Standalone implant designs and intraoperative navigation represent effective, complementary dose-reduction strategies. Standardized prospective research is needed to establish cervical-specific radiation safety benchmarks. Full article

Unicompartmental knee arthroplasty (UKA) is an effective treatment for anteromedial osteoarthritis in carefully selected patients. Increasing attention has recently been directed toward restoration of pre-arthritic coronal alignment, supported by the use of the arithmetic hip–knee–ankle angle (aHKA) to estimate constitutional lower limb alignment. In medial UKA, kinematic alignment principles derived from the original technique described by Cartier et al. may help to reproduce native joint-line orientation while preserving physiological soft-tissue balance. This technical note details the indications, preoperative assessment, planning strategy, and operative steps of the procedure. Preoperative long-leg weight-bearing radiographs are used to estimate constitutional alignment through the aHKA and to plan the coronal inclination of the tibial cut. Intraoperatively, the distal position of the extramedullary guide is reproduced according to the preoperative planning in order to restore the native inclination of the medial tibial plateau. The sagittal tibial cut, posterior tibial slope, distal femoral cut, component sizing, gap assessment, and cementation technique are described, with emphasis on anatomical landmarks and technical pearls to improve reproducibility. The described technique provides a practical method for approximating constitutional coronal alignment in medial UKA without the use of robotic or navigated systems. The key feature of the procedure is accurate planning and execution of the tibial cut in both the coronal and sagittal planes in order to reproduce native joint-line orientation and preserve appropriate ligament balance. Full article

Background: With the rising volume of knee arthroplasty and increasing adoption of robotic- and computer-assisted systems, the routine use of tracker pins has introduced procedure-specific risks. This systematic review aimed to characterize the types and incidence of pin-site complications associated with robotic-assisted and computer-navigated primary knee arthroplasty and to describe the timing, management strategies, and reported outcomes. Methods: A PRISMA-guided search of PubMed/MEDLINE was performed using terms related to pin-related complications, robotic assistance, computer navigation, total and unicompartmental knee arthroplasty procedures. Clinical studies (RCTs, cohorts, case series, and case reports) that explicitly documented pin-related complications in robotic- or computer-assisted knee arthroplasty in English were included. Two independent reviewers performed study selection and data extraction; the methodological quality of non-randomized studies was assessed with the MINORS instrument. Extracted variables encompassed study design, patient demographics, pin characteristics, type and timing of complications, treatments, and outcomes. Descriptive statistics and means were used where appropriate. Results: From 1231 initial records, 28 studies met the inclusion criteria, comprising 15,004 cases in cohort/series analyses. The aggregate pin-related complication incidence in non-case-report series was 0.95% (142 events). Of these, 13.4% were intraoperative and 86.6% postoperative. The most common postoperative events were pin-site wound issues and infections (each ≈35.7% of complications); pin-site fractures accounted for 0.16% in cohort/series data. Case reports (n = 17 patients) showed fractures chiefly at femoral pin sites, arising on average 8.5 weeks postoperatively; management ranged from protected weight-bearing to intramedullary nailing or ORIF. Potential risk factors suggested in the literature include higher BMI, bicortical or transcortical fixation, metaphyseal pin placement, and larger pin diameter, but findings were inconsistent. Conclusions: Pin-related complications after robotic- and computer-assisted knee arthroplasty are uncommon but clinically significant (≈0.95%). There is insufficient evidence to define optimal pin-placement strategies or fixation configurations. Surgeons should include pin-related risks in informed consent discussions. Further prospective research is required to identify patient- and technique-specific risk factors and to establish evidence-based pin-placement guidelines. Full article

Background/Objectives: Reliable intraoperative imaging is essential for robotic-assisted (RA) pedicle screw placement. Mobile intraoperative cone-beam CT (iCBCT) systems like Loop-X have been introduced into RA workflows, but implementation data remain limited. We evaluated whether Loop-X introduction was associated with efficiency or safety, and whether associations differed by surgeon experience. Methods: We performed a retrospective epoch-based cohort study of 146 patients undergoing RA pedicle screw placement using 3D C-arm navigation (3D-BV) or Loop-X iCBCT. Outcomes were operating room (OR) time, estimated blood loss (EBL), and length of stay (LOS). The safety endpoint was 30-day complications (Clavien–Dindo grade III or higher). Multivariable regression models adjusted for patient- and procedure-related covariates; the complication model was kept parsimonious because of the limited number of events. Interaction terms tested surgeon experience. Results: After adjustment, implementation phase was not independently associated with OR time (β 30.76 min, 95% CI −31.97 to 93.48; p = 0.33), EBL (β −19.94 mL, 95% CI −287.01 to 247.14; p = 0.88), or LOS (β 3.21 days, 95% CI −3.31 to 9.72; p = 0.33). No significant interaction with surgeon experience was detected. Major complications occurred in 16 of 146 cases (11.0%) and were not associated with Loop-X implementation (OR 0.41, 95% CI 0.10–1.74; p = 0.224). Patient factors and procedural complexity were the main determinants of outcomes. Conclusions: In this cohort, Loop-X implementation in an RA pedicle screw program was not associated with deterioration in perioperative efficiency or short-term safety after adjustment. These findings support feasibility in practice, but do not establish superiority, equivalence, or imaging-specific effects. Full article

Background: Accurate three-dimensional positioning of dental implants is critical for ensuring biomechanical stability, prosthetic passivity, and long-term clinical success. While computer-assisted navigation systems achieve high precision, their complexity and cost often limit accessibility. This study presents the development and preclinical experimental validation of a low-cost prototype designed to enhance angular accuracy in dental implant placement within a controlled 3D haptic simulation environment. Methods: A preclinical experimental design was implemented using a 3D haptic simulator (Virteasy, Montpellier, France). The prototype incorporated high-precision inertial measurement units (IMUs) and an Extended Kalman Filter (EKF) for real-time angular feedback. Ninety-seven simulated implant placements were performed—both freehand and with prototype assistance—under identical virtual conditions by a single experienced operator. Angular deviations in mesiodistal and buccolingual planes were recorded, combined into a composite 3D index, and analyzed using paired t-tests and linear mixed-effects models. The study was conducted in a controlled simulation environment, which does not fully replicate clinical conditions. Results: The prototype significantly reduced angular deviation from 13.49° to 2.99° in the mesiodistal plane (−77.8%) and from 13.56° to 5.59° in the buccolingual plane (−58.8%), achieving an overall 67% improvement in three-dimensional orientation (p < 0.001; Cohen’s d = 1.47). Agreement with an optical reference system (OptiTrack) was excellent (bias = +0.36°, RMSE = 0.39°). Intra-operator reliability exceeded 0.95 (ICC), confirming strong reproducibility and measurement stability. Conclusions: The proposed inertial sensor-based prototype achieved angular accuracy within the range reported for computer-guided systems while maintaining advantages of portability, low cost, and usability. Its integration into haptic simulators provides a valid tool for both educational and preclinical applications, offering real-time feedback that enhances spatial perception and psychomotor learning. Future clinical studies should validate its performance in cadaveric and patient-based contexts to determine its practical impact on surgical precision and implant success. Full article

Photodynamic therapy (PDT) is a promising treatment for pleural malignancies, yet accurate dosimetry remains challenging due to complex cavity geometries and the need to protect surrounding critical structures. The reactive oxygen species ([ROS]_rx) generated during treatment serve as a direct predictor of therapeutic efficacy. We developed a finite element model using COMSOL Multiphysics to simulate macroscopic photophysical kinetics, using clinical data inputs, including light fluence derived from a navigation system and patient-specific photosensitizer concentrations. Crucially, we integrated a deformable image registration framework to align intra-operative navigation data with pre-treatment CT scans, enabling the calculation of [ROS]_rx dose accumulation in critical Organs at Risk (OARs), such as the lung, heart, and esophagus. The model successfully reconstructed 3D [ROS]_rx distributions for multiple clinical cases. Point-to-point comparison at 32 detector locations across ten patients showed strong agreement between COMSOL-simulated and clinically calculated [ROS]_rx (mean percentage difference 0.6 ± 5.8%), while volume-averaged values differed by −6.0%, reflecting the enhanced spatial coverage of the 3D model relative to discrete sampling. The two-stage deformable registration improved CT-to-navigation surface alignment from HD95 = 4.08 mm to 1.78 mm (56.4% reduction) and MSD = 1.77 mm to 0.68 mm (61.5% reduction), enabling the first patient-specific mapping of [ROS]_rx onto OAR structures. This study demonstrates the feasibility of a comprehensive 3D dosimetry system for pleural PDT. By integrating kinetic modeling with deformable registration, we provide a robust platform for evaluating treatment efficacy and ensuring OAR safety, paving the way for eventual integration into treatment planning and real-time feedback. Full article

The available literature provides limited and inadequate data regarding the association between intraoperative knee kinematics, long-term clinical outcomes and survivorship after total knee arthroplasty (TKA). This study aimed to examine the potential relationship between specific intraoperative kinematics laxity assessment, acquired with a computer navigation system, and the long-term clinical outcomes and survivorship in patients undergoing TKA. This study consists of a retrospective cohort analysis of consecutive TKA procedures, in which a surgical navigation system was utilized to intra-operatively assess bone resections, implant positioning and gap balancing. The intraoperative kinematic parameters included varus-valgus laxity at 0° (VV 0) and 30° of flexion (VV 30), anterior–posterior displacement at 90° of flexion (AP 90), and passive range of motion (ROM). Different prosthesis designs were used, with a predominance of the posterior stabilized (PS)-type implant. The Knee Injury and Osteo-arthritis Outcome Score (KOOS) was used to investigate patients’ clinical and functional status. Survival was analyzed with the Kaplan–Meier method. Between-group comparisons were performed using the Mann–Whitney U test. A univariate logistic regression analysis was conducted to identify factors associated with clinical failure. Of 165 eligible patients, 120 were included in the final analysis, with a mean follow-up of 7.7 ± 2.8 years. Revision surgery was required in seven cases, representing surgical failure and an overall survival rate of 94.2%, with survival probabilities of 98.8%, 97.4%, and 93.6% at 6, 8, and 10 years, respectively. Clinical failure (KOOS < 70 in three domains) occurred in 23 patients. No intra-operative surgical parameters, including Hip-Knee-Ankle angle, Preoperative KL grade, prostheses design, VV 0, VV 30, AP 90 and ROM, or demographic variables, were found to be statistically correlated with clinical failure at follow-up. Although, in this navigated TKA cohort, survivorship was acceptable and consistent with previously reported benchmarks, it was not possible to reliably predict survival probability based solely on the intra-operative laxity parameters measured. Nevertheless, the use of surgical navigation can help surgeons accurately assess bone resections and the balance of prosthetic components. Full article

Background/Objectives: Preservation of critical white matter (WM) pathways is essential for maximizing surgical safety in neuro-oncology and functional neurosurgery. Constrained spherical deconvolution (CSD) offers superior modeling of complex fiber architecture compared to diffusion tensor imaging (DTI). This case series evaluates the clinical utility of CSD in surgical planning and intraoperative navigation. Methods: A retrospective review of 20 patients (15 brain tumors, 5 functional disorders) treated between September 2022, and September 2024 was performed. All patients underwent preoperative MRI with CSD-based reconstruction of eloquent WM tracts. Clinical presentation, tract involvement, surgical strategy, and postoperative outcomes were analyzed. Results: CSD reliably reconstructed CST, AF, IFOF, OT, and DRTT depending on tumor location or DBS target. Compared with standard DTI, CSD provided improved delineation of tract extent and tumor–tract interfaces. Gross total resection (GTR) was achieved in all tumor patients without new neurological deficits. DBS cases showed precise correlation between stimulation thresholds, side effects, and CSD-predicted distances to critical WM tracts. DRTT targeting resulted in marked clinical improvement in Holmes tremor. Conclusions: CSD enhances anatomical accuracy in WM tract visualization, supporting safer resections in eloquent areas and improving DBS targeting. Its integration into routine workflow may optimize neurosurgical outcomes. Full article

Background/Objectives: Accurate intraoperative tumour localisation remains challenging in minimally invasive colorectal surgery, where conventional tattooing methods suffer from marker migration, tissue diffusion, and potential allergic reactions. Radio frequency identification (RFID) technology offers a promising alternative through implantable passive transponders detectable via electromagnetic coupling, eliminating ionising radiation exposure. Methods: This preclinical feasibility study evaluated three RFID frequency bands for surgical tumour marking: 134 kHz (low frequency, LF), 13.56 MHz (high frequency, HF), and 868 MHz (ultra-high frequency, UHF). Finite element electromagnetic simulations characterised antenna field distributions, while experimental validation employed glass-encapsulated transponders in air and tissue-simulating saline (0.9% NaCl, σ ≈ 1.5 S/m). Detection ranges were measured across 28 angular configurations with expanded measurement uncertainty (k = 2) ranging from ±0.9 to ±3.2 mm. Results: Maximum detection distances in air were 25.0 ± 0.9 mm (LF), 23.0 ± 1.1 mm (HF), and 68.0 ± 2.3 mm (UHF). In saline, ranges decreased to 22.5 ± 1.0 mm, 20.7 ± 1.2 mm, and 18.0 ± 1.4 mm, respectively, demonstrating tissue attenuation of 10% at LF/HF vs. 74% at UHF. Angular characterisation revealed 64–70% range reduction at orthogonal orientation for LF/HF systems. Computational–experimental correlation yielded r² = 0.975 across 154 paired observations. Conclusions: The 13.56 MHz HF band emerges as the optimal candidate for clinical translation, offering adequate tissue penetration (20.7 mm), superior antenna miniaturisation potential (5 mm diameter), established biocompatibility pathways, and mature near-field communication ecosystem support. Future development should address angular sensitivity through multi-axis antenna configurations and validation in anatomically realistic tissue phantoms. This study establishes the electromagnetic evidence base for clinical system development; translation to clinical practice requires sequential preclinical and clinical evaluation. Full article

Electricity price forecasting has become a critical tool for decision-making in energy markets, particularly as the increasing penetration of renewable energy has introduced greater volatility and uncertainty. Historically, research in this field has been dominated by point forecasting methods, which provide single-value predictions but fail to quantify uncertainty. However, as power markets evolve due to renewable integration, smart grids, and regulatory changes, the need for probabilistic forecasting has become more pronounced, offering a more comprehensive approach to risk assessment and market participation. This paper presents a review of probabilistic forecasting methods, tracing their evolution from Bayesian and distribution based approaches to quantile regression techniques to recent developments in conformal prediction. Particular emphasis is placed on advancements in probabilistic forecasting, including validity-focused methods that address key limitations in uncertainty estimation. Additionally, this review extends beyond the day-ahead market to include the intra-day and balancing markets, where forecasting challenges are intensified by higher temporal granularity and real-time operational constraints. We examine state-of-the-art methodologies, key evaluation metrics, and ongoing challenges, such as forecast validity, model selection, and the absence of standardised benchmarks, providing researchers and practitioners with a comprehensive and timely resource for navigating the complexities of modern electricity markets. Full article

Arctic sea ice is a critical indicator of global climate dynamics, directly influencing maritime navigation, polar biodiversity, and offshore engineering safety. The precise mapping of diverse ice types, such as frazil ice, slush, melt ponds, and open water, is essential for environmental monitoring; however, it remains a formidable challenge in satellite remote sensing. These difficulties arise from low-contrast imagery, overlapping spectral signatures, and the subtle textural nuances characteristic of polar regions. Traditional entropy-based thresholding techniques often falter when segmenting these complex scenes, as they typically rely on Gaussian distribution assumptions that do not align with the stochastic nature of Arctic data. To address these limitations, this paper presents a novel unsupervised segmentation framework based on symmetric cross-entropy (SCE). Unlike standard directional measures, SCE provides a more robust objective function for multi-level thresholding by simultaneously maximizing intra-class cohesion and minimizing inter-class ambiguity. The proposed method uses an optimized search strategy to identify intensity levels that best delineate complex Arctic features. We conducted an extensive entropy-based comparative study that benchmarked SCE against 25 state-of-the-art entropy measures, including Shannon, Kapur, Rényi, Tsallis, and Masi entropies. Our experimental results demonstrate that the SCE method: (i) achieves superior accuracy by consistently outperforming established models in segmentation precision and boundary definition; (ii) provides visual clarity by producing segments with significantly reduced noise, making them ideal for identifying small-scale melt ponds and slush zones; and (iii) demonstrates computational robustness by providing stable threshold values even in datasets with non-Gaussian class distributions and poor illumination. Ultimately, these improvements deliver high-quality ice feature data that enhance risk assessment, operational planning, and predictive modeling. This research marks a major step forward in Arctic sea studies and introduces a valuable new tool for wider image processing and computer vision communities. Full article