Search Results (372)

The accuracy of static computer-aided implant surgery (s-CAIS) is fundamental for predictable clinical outcomes. The objective of this study was to evaluate the influence of different guide-support modalities on the linear and angular accuracy of implant placement. In this retrospective clinical investigation conducted at a single specialty hospital, a total of 180 implants were analyzed, divided into three equal groups (n = 60) based on the guide support type: tooth-supported, bone-supported, and mucosa-supported. Accuracy was assessed by superimposing preoperative virtual plans with postoperative cone-beam computed tomography (CBCT) scans, measuring linear deviations at the neck and apex of the implant, as well as angular discrepancies. The type of guide support was found to be a significant factor associated with surgical accuracy (p < 0.001). Tooth-supported guides demonstrated the highest level of accuracy, with a mean angular deviation of 1.81° ± 0.45° and linear deviations at the neck and apex of 0.59 ± 0.18 mm and 0.73 ± 0.19 mm, respectively. These were followed by bone-supported guides (2.14° ± 0.48°; 1.04 ± 0.26 mm; 1.61 ± 0.31 mm), while mucosa-supported guides exhibited the greatest deviations (2.95° ± 0.60°; 1.47 ± 0.29 mm; 1.87 ± 0.37 mm). Significant intergroup differences and large effect sizes were observed, particularly regarding angular and horizontal discrepancies. These findings demonstrate a distinct gradient of accuracy based on guide support, establishing tooth-supported guides as the most accurate, followed by bone-supported and, lastly, mucosa-supported guides. While all modalities are clinically applicable, the use of mucosa-supported guides necessitates increased safety margins to account for the increased risk of linear and angular discrepancies inherent to mucosal tissue displacement. Full article

Background/Objectives: Pterygoid implant placement represents a valuable alternative to conventional bone grafting procedures in the rehabilitation of the atrophic posterior maxilla; however, the procedure remains technically demanding because of limited visibility, difficult access, complex pterygomaxillary anatomy, and the need for precise angulation and distal bicortical anchorage. Although digital guidance has increasingly been applied in implant dentistry, a clearly described workflow integrating automatic segmentation, selective virtual trimming of the posterior maxillary anatomy, and direct three-dimensional planning for static-guided pterygoid implant placement remains insufficiently detailed in the literature. The aim of this report was to describe and illustrate such a workflow in a proof-of-concept clinical application. Methods: This work was designed as a methodological proof-of-concept with a single clinical illustration. A CBCT dataset was imported into BlueSkyPlan, where automatic segmentation was used to generate three-dimensional models of the maxilla, teeth, and pterygoid process. The segmented volumes were then selectively trimmed to expose the relevant pterygomaxillary anatomy and to support direct three-dimensional planning of the implant axis in the rendered model. A static surgical guide with combined tooth and mucosal support was subsequently designed, positioned on a printed jaw model derived from the intraoral scan, and assessed by CBCT-based internal verification. Results: In this proof-of-concept application, the workflow enabled three-dimensional visualization of the pterygomaxillary trajectory, supported implant axis planning in the rendered model, and facilitated guide design and radiographic verification of the planned trajectory. The verification step provided an internal methodological consistency check between the planned implant axis and the drill-guided direction visible on CBCT. Conclusions: The present report describes a segmentation-assisted three-dimensional planning workflow for static-guided pterygoid implant placement in a single proof-of-concept clinical application. The workflow should be interpreted as a methodological illustration rather than a quantitative validation study. Further investigations are required to evaluate accuracy, inter-operator reproducibility, and broader clinical applicability. Full article

Reconstruction in head and neck surgery requires restoration of complex functions, including speech, swallowing, and breathing, while preserving as much facial form and patient identity as possible. Over the past decade, advances in preoperative digital planning, intraoperative technologies, and robotic platforms have reshaped reconstructive strategies, giving rise to the concept of hybrid reconstruction. Hybrid approaches integrate free tissue transfer with computer-aided design and manufacturing (CAD/CAM), virtual surgical planning, intraoperative navigation, and robot-assisted microsurgery to enhance precision, reproducibility, and functional outcomes. This narrative review examines the principles and applications of hybrid reconstruction in head and neck surgery with particular emphasis on osseous reconstruction of the mandible, maxilla, and midface. The roles of intraoperative navigation and robotic assistance as enabling tools are discussed, along with their potential benefits and current limitations. Functional and morphologic outcomes, patient-reported quality of life, and challenges related to cost, access, training, and evidence heterogeneity are critically reviewed. Hybrid reconstruction represents an advancement toward outcomes-driven, patient-centered care; however, thoughtful integration of emerging technologies and continued emphasis on rigorous outcome assessment are essential to guide responsible adoption in contemporary head and neck reconstructive surgery. Full article

Purpose: The posterior tibial plateau offset (PTPO) is a parameter of sagittal plane bony tibia morphology with high variability and clinical relevance, particularly in cases involving stemmed tibial implants, where posterior tibial cortex interference may occur. However, its change during total knee arthroplasty (TKA), and its relationship to tibial component positioning remain unknown. Methods: Pre- and postoperative sagittal radiographs of 98 patients undergoing primary, mechanically aligned TKA using a single implant system were retrospectively analyzed. PTPO was measured as the distance between the tibial anatomical axis and the center of the tibial plateau or tibial component. Tibial component placement (TCP) was assessed anteriorly and posteriorly and categorized as anatomical (0–1 mm), mild (1–3 mm), or moderate (>3 mm) underhang (TCU) or overhang (TCO). Pre- and postoperative changes in PTPO were analyzed, preoperative PTPO was compared across TCP categories. Correlations with absolute anterior and posterior deviation from anatomical component placements were calculated. Results: PTPO showed high preoperative variability (mean 6.89 ± 3.69 mm) and was significantly reduced after TKA (5.89 ± 3.44 mm; mean change −1.06 ± 3.44 mm; p < 0.001). Higher preoperative PTPO was associated with anterior (p = 0.01) and posterior TCU (p = 0.02). PTPO showed a moderate correlation with anterior (r = 0.53, p < 0.01) and a strong correlation with posterior implant deviation (r = 0.68, p < 0.01). Conclusions: PTPO shows high variability among patients undergoing TKA, is significantly altered through surgery and correlates with tibial component malposition, particularly TCU. Surgeons should consider PTPO during preoperative planning to optimize tibial component positioning and reduce the risk of implant-to-bone conflict, especially when using stemmed implants. In patients with a high preoperative PTPO, accuracy-enhancing techniques such as computer navigation or robotic assistance may be considered. Full article

Patellar maltracking is among the most common causes of anterior knee pain after total knee arthroplasty (TKA), underscoring the need for accurate prevention and treatment. Therefore, the purpose of this narrative review is to provide a comprehensive overview of current evidence on post-TKA tracking, focusing on component alignment, preoperative patient assessment, and revision treatment options. A PubMed database search was performed, leveraging the literature from the last 20 years, and the results were qualitatively synthesized. According to current studies, several precautions should be taken to prevent patellofemoral stress and, consequently, patellar maltracking, such as avoiding internal rotation, valgus alignment, and excessive flexion of the femoral component and internal rotation of the tibial component. Regarding alignment strategies, kinematic alignment appears to offer potential benefits over mechanical alignment in certain functional outcomes and patient satisfaction scores. However, these differences should be interpreted cautiously as they may not always exceed the minimal clinically important difference. Furthermore, recent evidence indicates that quadriceps biomechanics influence TKA outcomes, potentially suggesting that conventional surgical approaches may need to be individualized, though these preliminary findings require prospective validation. Currently, robotic-assisted surgery represents a developmental direction for patient-tailored interventions and offers great promise for better prosthesis customization to the individual patient. Integration of imaging data with dynamic soft-tissue assessment enables more predictable reconstruction of joint kinematics. Regarding surgical treatment, the selection of specific methods requires a prior clinical and radiographic assessment. Indications range from patellar maltracking direction and component malrotation to patient preferences and rehabilitation potential. Ultimately, the future of TKA relies on personalized interventions to prevent complications and improve patient outcomes. This evolution is driven by the shift from mechanical alignment to kinematic alignment, alongside quadriceps tendon assessment and intraoperative robotic-assisted measurement, all aimed at optimizing the accuracy of implant positioning. Full article

Artificial intelligence (AI) is increasingly transforming spine surgery, with expanding applications in diagnostics, intraoperative imaging, and surgical navigation. As the field advances toward greater precision and safety, machine learning (ML) and deep learning technologies are being integrated to augment surgeon expertise and optimize operative workflows. In particular, AI-driven innovations in image acquisition and navigation are reshaping intraoperative decision-making and technical execution. This narrative review provides an overview of AI applications relevant to intraoperative imaging and navigation in spine surgery. We begin by defining key concepts in AI, ML, and deep learning and briefly outline the historical evolution of AI within spine practice. We then examine current capabilities in image recognition and automated pathology detection, emphasizing their clinical relevance. Given the central role of imaging accuracy in modern navigation-assisted procedures, we review conventional acquisition platforms, including intraoperative computed tomography (CT) systems (e.g., O-arm, GE, Airo), surface-based registration to preoperative CT (Stryker, Medtronic), and optical surface mapping technologies (e.g., 7D Surgical). Emerging AI-optimized advancements are subsequently discussed, including low-dose intraoperative CT protocols, expanded scan windows, metal artifact reduction algorithms, integration of 2D fluoroscopy with preoperative CT datasets, and 3D reconstruction derived from 2D imaging. These developments aim to improve image quality, reduce radiation exposure, and enhance navigational accuracy. By synthesizing current evidence and technological progress, this review highlights how AI-enhanced imaging systems are redefining intraoperative spine surgery and shaping the future of precision-based care. The primary purpose of this review is to outline the applications of AI and its potential for perioperative and intraoperative optimization, including radiation exposure reduction, workflow streamlining, preoperative planning, robot-assisted surgery, and navigation. The secondary purpose is to define AI, machine learning, and deep learning within the medical context, describe image and pathology recognition, and provide a historical overview of AI in orthopedic spine surgery. Full article

Historically, stage T4 non-small cell lung cancer (NSCLC) with direct spinal invasion was considered a definitive surgical contraindication due to the perceived inability to achieve negative margins without catastrophic morbidity. This paradigm has shifted through the advancement of specialized surgical techniques, which facilitate radical en-bloc resection in highly selected candidates by adhering to the en-bloc concept. This concept mandates the retrieval of the tumor and invaded vertebral segments as a single, contiguous unit to prevent intralesional transgression and local recurrence. Achieving microscopic negative margins (R0) stands as the most critical prognostic factor, as radical resection offers a significantly improved potential for long-term survival. Technical success requires a meticulously planned multidisciplinary approach encompassing varied surgical corridors—ranging from combined anterior–posterior windows to single-stage posterior-only approaches—tailored to the tumor’s anatomical level. Furthermore, preoperative hemostatic optimization using dual-energy computed tomography (DECT) for vascular assessment and transarterial embolization (TAE) has become indispensable for managing the hypervascularity of the invaded vertebral bone. This review synthesizes these evolving strategies, illustrated by a case of a 74-year-old male with stage T4 NSCLC where an R0 resection was achieved through a two-stage approach integrating uniportal video-assisted thoracoscopic surgery (VATS). Ultimately, en-bloc management provides a feasible and potential surgical strategy toward long-term survival for localized, spine-invasive lung cancer within a multidisciplinary treatment framework. Full article

Neoadjuvant strategies in head and neck squamous cell carcinoma (HNSCC) are reshaping therapeutic paradigms by shifting emphasis from anatomical staging toward biology-driven response stratification. The transition from induction chemotherapy to immune checkpoint–based and combination regimens has transformed the perioperative setting into a translational platform that enables interrogation of tumor–immune interactions and clonal selection under therapeutic pressure prior to surgery. In this context, pathological response assessment has emerged as a robust surrogate endpoint, overcoming the limitations of radiologic evaluation, which often fails to capture immune-mediated pseudoprogression and spatially heterogeneous regression. Quantification of residual viable tumor (RVT) provides a reproducible metric of therapeutic efficacy, while characterization of immune-related regression beds, tertiary lymphoid structures, macrophage polarization states, and compartment-specific nodal responses offers mechanistic insight into tumor clearance and resistance evolution. Evidence from phase II trials, single-cell sequencing, spatial transcriptomics, and multiplex immune profiling supports the prognostic relevance of pathology-driven endpoints. Integration of digital pathology and artificial intelligence–assisted image analysis further enhances reproducibility and enables high-resolution mapping of residual disease and immune architecture. Within this modern oncologic framework, the neoadjuvant-treated specimen functions as a dynamic biomarker platform guiding response-adapted surgical strategies and biomarker-driven clinical trial design. This study was designed as a narrative review. A structured literature search was performed using PubMed and major oncology journals to identify relevant studies on pathology-driven response assessment in neoadjuvant-treated head and neck squamous cell carcinoma. The review focused on publications addressing histopathological response criteria, immune microenvironment remodeling, spatial profiling technologies, and computational pathology approaches. Full article

Surgical navigation and augmented reality (AR) are widely used in neurosurgery, spinal surgery, and orthopedics. However, their use in minimally invasive abdominal and thoracic soft-tissue surgery is limited, as tracking deformable, mobile organs is challenging. Recent advances in AR may address these challenges to improve intraoperative navigation. This systematic review, registered in PROSPERO (2024) and based on PRISMA guidelines, analyzes literature from 2014 to 2024 about AR in minimally invasive abdominal and thoracic soft-tissue surgery. It identifies target organs, describes AR hardware and software, and evaluates accuracy levels, usability outcomes, clinical benefits, technical limitations, and research needs. Searches of PubMed, Web of Science, and Embase for English-language studies found 1297 records, of which only 28 (2%) met the inclusion criteria. Nearly half (n =12; 42%) focused on liver surgery; none on gynecologic surgery. The AR devices varied in tracking methods, image processing, visualization, and display. Overall, AR improved anatomical guidance and procedural planning, especially in complex surgeries. Integration with robotic systems may further boost visualization, precision, and workflow, though challenges remain in standardization, large-cohort validation, and workflow integration. Full article

Background: Temporomandibular joint (TMJ) ankylosis is an uncommon condition in the modern world, yet it remains a significant treatment challenge. One of the main intraoperative difficulties is accurately and safely resecting the ankylotic mass. Objective: This study seeks to share our clinical experience with various types of complications and to review the literature on the clinical and technological evidence regarding the accuracy of surgical detachment of the ankylotic mass from the skull. Methods: A literature review was conducted using PRISMA (Preferred Reporting Items for Systematic Review and Meta-Analysis) guidelines. Search strategies were categorized into search 1 for evaluating 3D-printed technology and search 2 for computer-assisted surgical navigation. Results: One study was selected for search 1 and 2 for search 2. Also, three cases of intraoperative surgical complications associated with the resection of the ankylotic mass were presented. The 3D surgical cutting guides were found to be accurate in guiding the superior, inferior, and depth of the osteotomy. Angulation control was less than optimal. Navigation guiding proved accurate in maintaining the planned thickness of the skull base and the anterior wall of the external auditory canal. Conclusion: Navigation guiding is a superior method for achieving predictable anatomical resection of the ankylotic mass. Full article

Optical reflective markers are widely used in precision medicine, computer-assisted surgery, and robotic interventions. Nevertheless, intraoperative tracking still faces challenges such as sensor saturation, Point Spread Function (PSF) blooming, and flat-top artifacts, which affect localization precision and stability. Traditional deep learning detectors perform well in general object recognition but are limited in handling saturated infrared reflective markers due to their neglect of optical physics and inability to separate signal from blooming interference. This paper presents a physics-prior-guided network integrating a Brightness-Prior-Enhanced Spatial Attention (BPESA) mechanism for high-precision sub-pixel marker localization under saturation conditions. The method achieves a Root Mean Square (RMS) error of 0.52 pixels (approximately 0.11 mm) on a dataset of 8000 binocular images and reduces the localization error by approximately 54.4% compared with the baseline YOLOv8 model, while maintaining an inference speed of 134.6 FPS. The results demonstrate that optical blooming interference can be effectively mitigated by a learnable physics-prior branch, providing accurate marker coordinates that form a foundation for potential downstream tracking or navigation tasks. Full article

Background/Objectives: Accurate pedicle screw placement is critical in spine surgery, as malposition can cause neurological, vascular, or visceral injuries and compromise construct stability. The primary objective of this study was to develop and experimentally validate a dual quantitative framework for assessing pedicle screw placement accuracy, combining (1) coaxiality, a standardized geometric metric of trajectory alignment, and (2) pedicle wall distance (dpw), a novel parameter defined as the minimal distance between the screw axis and the pedicle cortex providing surgeons with direct, millimetric, clinically actionable feedback. A secondary objective was to compare these parameters: dpw, coaxiality, entry point errors and orientation angle errors between senior surgeons and residents to evaluate the influence of surgical experience. We hypothesized that this framework would provide reproducible quantitative measurements, demonstrate strong agreement with established CBCT-based grading systems, and allow meaningful subgroup comparisons by experience level. Methods: Eight operators (four senior surgeons, four residents) performed 240 pedicle screw insertions on synthetic polyurethane lumbar spine models using freehand, CBCT-assisted, and navigation-assisted techniques. Predefined 3D trajectories were compared with actual screw positions digitized with sub-millimetric precision. Errors, coaxiality, and dpw were computed, and dpw was validated against CBCT-based Gertzbein and Heary classifications. Agreement and diagnostic performance metrics (Kappa, sensitivity, specificity) were calculated. Results: Of 236 analyzable screws, coaxiality correlated with entry point errors (ρ = 0.41), target point errors (ρ = 0.85), and orientation angle errors (ρ = 0.48), confirming its robustness as an engineering metric. dpw provided immediate, interpretable feedback and demonstrated near-perfect agreement with CBCT grading (Kappa = 0.86; sensitivity = 0.96; specificity = 0.97), detecting breaches missed by qualitative classifications. Subgroup analyses indicated small but significant differences between senior and junior surgeons for target point errors (p = 0.006), orientation angle errors (p = 0.025), and coaxiality (p = 0.023), whereas entry point errors (p = 0.201) and dpw (p = 0.163) did not differ significantly. Conclusions: This dual-metric framework bridges engineering rigor and intraoperative applicability. Coaxiality supports reproducible research assessment, while dpw enables actionable surgical feedback. The framework allows objective comparison across operators of different experience levels. Together, these metrics offer a standardized, clinically relevant, and quantitative method for evaluating pedicle screw placement, with potential to enhance surgical safety, education, and patient outcomes. Full article

Background and Clinical Significance: Needle fracture during inferior alveolar nerve block is a rare complication, but it can nevertheless result in serious complications, especially when the fragment migrates into deep anatomical spaces like the pterygomandibular region. Accurate localization and safe retrieval are vital in preventing infection, chronic pain, neurovascular injury, and long-term functional impairment. Case Presentation: We present a case of a 27-year-old patient who had a fractured needle fragment from a local anesthetic procedure retained in the left pterygomandibular space. Cone beam computed tomography (CBCT) was carried out to verify the presence of the metallic foreign body and to define its exact three-dimensional position in relation to adjacent bone and soft tissue landmarks. The approach was transoral, and the surgery was done under general anesthesia. During the surgery C-arm fluoroscopy was used to help guide localization and retrieval, along with the help of radiopaque reference markers to assist in determining the trajectory. The fragment was removed without any issue. After the surgery, the patient’s condition improved well, and he showed no signs of functional deficits. Conclusions: The management of broken needle fragments in the pterygomandibular space can be safely and effectively done using a combination of preoperative CBCT and intraoperative C-arm guidance. This technique allows for exact location determination, minimizes unnecessary dissection of the tissue, and will make the surgery safer in complicated areas. Full article

Background/Objectives: Virtual surgical planning (VSP) and CAD/CAM technologies have revolutionized complex maxillofacial reconstruction. While high-resolution imaging is critical for these workflows, the specific clinical impact of photon-counting computed tomography (PCCT) remains to be fully established. This prospective pilot study evaluates the feasibility and clinical utility of integrating PCCT into the preoperative planning and surgical workflow of complex maxillofacial reconstructive cases. Methods: This feasibility study included ten patients requiring complex maxillofacial reconstruction with microvascular free flaps. All underwent preoperative imaging with photon-counting CT. Primary endpoints included clinical assessment of osseous invasion, reliability of donor-site vascular mapping from a single acquisition, and compatibility of PCCT datasets with VSP/CAD-CAM platforms. Secondary endpoints included resection margin status, flap survival, and short-term oncologic outcomes. Results: PCCT provided high-resolution visualization of cortical and medullary bone, enabling detailed assessment of tumor-related osseous involvement. In selected cases, findings supported refinement of resection planning when prior imaging had been inconclusive. Spectral reconstructions reduced metal artifacts and facilitated precise segmentation for multi-segment osteotomies. Donor-site vascular anatomy was successfully evaluated within the same scan, supporting operative planning without additional imaging. PCCT datasets were fully compatible with the virtual surgical planning (VSP) software used in this study (CMX Portal, version 2.6.1158, Medartis AG, Basel, Switzerland; or ProPlan CMF, version 5.7.8.025, Materialise NV, Leuven, Belgium) in all cases (100%). Reconstruction was completed successfully in all patients, with 100% flap survival and R0 margins in all malignant cases. No technical failures occurred during imaging transfer or CAD/CAM fabrication. Conclusions: The integration of PCCT into the surgical workflow proved technically feasible and clinically impactful. This pilot data supports its potential to enhance surgical precision and preoperative planning in complex jaw reconstruction. Full article

Objectives: To synthesize evidence on artificial intelligence (AI)-enabled medical history taking (anamnesis)—beyond large language models (LLMs) alone—and to translate findings into implications and research priorities for head and neck surgery. Methods: We performed a PRISMA-informed narrative review. Searches from database inception to 31 December 2025 (updated 3 January 2026) were conducted in MEDLINE (PubMed), Embase, Scopus, Web of Science Core Collection, IEEE Xplore, and ACM Digital Library, supplemented by medRxiv/arXiv screening and citation chasing. We included studies evaluating or describing AI-supported history capture/summarization, conversational interviewing, symptom checker/digital triage, EHR-integrated intake-to-decision support pipelines, voice interviewing, education/training systems, and governance/ethical considerations related to digital anamnesis. Findings were synthesized by system category and by cross-cutting outcome domains, with a head and neck surgery interpretive lens. Results: Fifty studies (2014–2025) were included. Evidence most consistently suggested feasibility and acceptability of pre-consultation computer-assisted history taking and the potential to reduce documentation burden and improve structured capture. In contrast, symptom checkers and digital triage tools showed highly variable diagnostic/triage performance and prominent safety concerns, highlighting the importance of conservative red-flag escalation strategies, continuous monitoring, and clear accountability. LLM-based diagnostic dialogue demonstrated strong performance in controlled evaluations, but prospective real-world validation, governance, and workflow integration remain limited. Conclusions: AI-enabled anamnesis comprises heterogeneous tools with uneven evidence. For head and neck surgery, potential near-term applications may include structured pre-visit intake, clinician-facing summarization, and training applications, whereas autonomous triage warrants harm-oriented, specialty-calibrated validation and robust governance prior to broader clinical reliance. Full article