Optimal Target Research Articles

Optimize individualized energy delivery for septic patients using predictive deep learning models.

We aim to establish deep learning models to optimize the individualized energy delivery for septic patients. We conducted a study of adult septic patients in ICU, collecting 47 indicators for 14 days. We filtered out nutrition-related features and divided the data into datasets according to the three metabolic phases proposed by ESPEN: acute early, acute late, and rehabilitation. We then established optimal energy target models for each phase using deep learning and conducted external validation. A total of 179 patients in training dataset and 98 patients in external validation dataset were included in this study, and total data size was 3115 elements. The age, weight and BMI of the patients were 63.05 (95%CI 60.42-65.68), 61.31(95%CI 59.62-63.00) and 22.70 (95%CI 22.21-23.19), respectively. And 26.0% (72) of the patients were female. The models indicated that the optimal energy targets in the three phases were 900kcal/d, 2300kcal/d, and 2000kcal/d, respectively. Excessive energy intake increased mortality rapidly in the early period of the acute phase. Insufficient energy in the late period of the acute phase significantly raised the mortality as well. For the rehabilitation phase, too much or too little energy delivery were both associated with elevated death risk. Our study established time-series prediction models for septic patients to optimize energy delivery in the ICU. We recommended permissive underfeeding only in the early acute phase. Later, increased energy intake may improve survival and settle energy debts caused by underfeeding.

Navigating Specific Targets of Breast Cancer Symptoms: An Innovative Computer-Simulated Intervention Analysis

PurposeTo pinpoint optimal interventions by dissecting the complex symptom interactions, encompassing both their static and temporal dimensions. MethodsThe study incorporated a cross-sectional survey utilizing the MD Anderson Symptom Inventory. Participants with breast cancer undergoing chemotherapy were recruited from the “Be Resilient to Breast Cancer” from April 2023 to June 2024. Static symptom interrelationships were elucidated using undirected and Bayesian network models, complemented by an exploration of their dynamic counterparts through computer-simulated interventions. ResultsThe study included 602 patients with breast cancer. Both undirected networks and computer-simulated interventions concurred on the symptoms of distress and fatigue as optimal alleviation targets. The Bayesian network and computer-simulated interventions both emphasized “shortness of breath” as preventive care. Notably, Distress appeared to be the most effective target for interventions, and compared to fatigue (decreasing score=1.84∼2.20, decreasing prevalence=14.2∼16.7%). Conversely, disturbed sleep, despite its high position in Bayesian network, had no propelling effects on increasing the network’s overall symptom activity levels (increasing score<1). ConclusionsComputer-simulated intervention integrating with traditional network analysis can improve intervention precision and efficacy by prioritizing individual symptom impacts, both statically and dynamically.

Optimal Agile Satellite Target Scheduling with Learned Dynamics

Target sequencing is an important aspect of agile Earth-observing satellite scheduling. The objective of the problem is to find a feasible imaging sequence that maximizes the cumulative value of unique heterogeneously valued requests; no expendable resource constraints (power and data storage) are considered. Two challenges are encountered: transition times between targets are dictated by dynamics of an arbitrary controller, and the solution space is combinatorial with respect to request count. To find dynamically accurate time-dependent attitude maneuver transition times, a neural network is trained on simulated slew data; this allows for the generation of more physically accurate, and thus better performing, schedules than when using the traditional approach of lower-order models for slew feasibility. Next, slews between requests are represented by a sparsified graph, and a mixed-integer linear program is formulated to solve them; the sparse formulation keeps the problem tractable over longer planning horizons and larger numbers of requests when compared to the standard approach. The solutions are optimal up to the quality of the transition time estimator and a time discretization. Finally, the solutions are verified in a high-fidelity simulation, demonstrating validity when deployed on a lifelike system. Time-dependent request values and multiple satellites are also considered.

Brain targeting for focused ultrasound essential tremor ablation: proceedings from the 2023 Focused Ultrasound Foundation workshop.

Essential tremor (ET) is the most common movement disorder globally and has negative impacts on quality of life. While medical treatments exist, approximately 50% of patients have tremor that is refractory to medication or experience intolerable medication side effects. Magnetic resonance-guided focused ultrasound (MRgFUS) thalamotomy is an option for these patients and while incisionless, it is still invasive, although less so than other surgical treatments such as deep brain stimulation and radiofrequency thalamotomy. Despite MRgFUS being FDA-approved since 2016, there is still no current consensus on the best approaches for targeting, imaging, and outcome measurement. A 2-day workshop held by the Focused Ultrasound Foundation in September of 2023 convened experts and critical stakeholders in the field to share their knowledge and experiences. The goals of the workshop were to determine the optimal target location within the thalamus and compare best practices for localizing the target and tracking patient outcomes. This paper summarizes the current landscape, important questions, and discussions that will help direct future treatments to improve patient care and outcomes.

Exploring the Lower Limit of Target Concentration in Capture-SELEX Using Guanine as a Model Target.

During an aptamer selection, using a lower target concentration may result in aptamers with a higher binding affinity. Consequently, this begs the question of whether there is a lower limit for target concentration. In this work, we conducted three aptamer selections using 5 µM, 500 nM and 50 nM guanine as the targets, respectively. Successful enrichment of the same guanine aptamers was achieved at both 5 µM and 500 nM guanine, but not with 50 nM. Using 5 µM guanine, the aptamer was enriched in eight rounds of selection, compared to that for 500 nM, which was accomplished in 17 rounds. We discuss the relation of optimal target concentration to the observed Kd value of the resulting aptamers, of which the highest affinity aptamer had a measured Kd of 200 nM. Additionally, we investigated the binding of the aptamers through mutation studies, revealing a critical cytosine. Mutating this cytosine to a thymine switched the selectivity from guanine to adenine, which is reminiscent of the guanine riboswitch. This study revealed a limit in using low target concentration, and the insights described in this article will be useful for guiding the choice of target concentration during capture-SELEX.

Coherent X-ray diffraction imaging of single particles: background impact on 3D reconstruction.

Coherent diffractive imaging with X-ray free-electron lasers could enable structural studies of macromolecules at room temperature. This type of experiment could provide a means to study structural dynamics on the femtosecond timescale. However, the diffraction from a single protein is weak compared with the incoherent scattering from background sources, which negatively affects the reconstruction analysis. This work evaluates the effects of the presence of background on the analysis pipeline. Background measurements from the European X-ray Free-Electron Laser were combined with simulated diffraction patterns and treated by a standard reconstruction procedure, including orientation recovery with the expand, maximize and compress algorithm and 3D phase retrieval. Background scattering did have an adverse effect on the estimated resolution of the reconstructed density maps. Still, the reconstructions generally worked when the signal-to-background ratio was 0.6 or better, in the momentum transfer shell of the highest reconstructed resolution. The results also suggest that the signal-to-background requirement increases at higher resolution. This study gives an indication of what is possible at current setups at X-ray free-electron lasers with regards to expected background strength and establishes a target for experimental optimization of the background.

In-silico identification of 3,4-Diarylpyrazoles-based small molecules as potential Hsp90 inhibitors

The ATP-dependent molecular chaperone, Hsp90, is crucial for the activity of hundreds of client proteins. Several of Hsp90 clients are involved in cancer cell growth and proliferation. Thus, numerous Hsp90 inhibitors have been developed to target Hsp90′s ATPase activity in cancer cells. CCT018159 is a pyrazole-based compound that successfully inhibited Hsp90 oncogenic activity by binding deeply to the ATP binding pocket in the Hsp90 N-terminal domain (N-Hsp90). In the present study, we utilized the CCT018159 structure to identify new potential Hsp90 inhibitors using a set of in-silico approaches. The ZINC database was virtually screened for CCT018159 analogs using the SwissSimilarity webpage. Ten molecules were selected for further investigation based on their drug-likeness, pharmacokinetics, and physiochemical properties. The molecular docking simulation analysis revealed that these ZINC compounds have Ligand Binding Energies (LBEs) ranging from −8.61 to −9.73 Kcal/mol, which reflects a high binding affinity compared to CCT018159 (LBE of −6.31 Kcal/mol). These compounds exhibited diverse interactions, including critical hydrogen bonds and hydrophobic contacts with crucial residues like Asn51, Ala55, and Leu107. Further optimization targeting unique interactions (e.g., ZINC000008973382 with Asp93, Met98, and Thr184) and exploiting the versatile Lys58 could lead to novel, potent anticancer agents targeting Hsp90.

Rationale and design of ELIXIR, a randomized, controlled trial to evaluate efficacy and safety of XyloCore, a glucose-sparing solution for peritoneal dialysis.

Peritoneal dialysis adoption and technique survival is affected by limitations related to peritoneal membrane longevity and metabolic alterations. Indeed, almost all peritoneal dialysis fluids exploit glucose as an osmotic agent that rapidly diffuses across the peritoneal membrane, potentially resulting in metabolic abnormalities such as hyperglycemia, hyperinsulinemia, obesity, and hyperlipidemia. Moreover, glucose-degradation products generated during heat sterilization, other than glucose itself, induce significant morphological and functional changes in the peritoneum leading to ultrafiltration failure. The partial substitution of glucose with osmotic agents characterized by a better local and systemic biocompatibility has been suggested as a potential strategy to innovate peritoneal dialysis fluids. The approach aims to minimize glucose-associated toxicity, preserving the peritoneal membrane welfare and counteracting common comorbidities. In this work, we report the clinical trial design of ELIXIR, a phase III randomized, controlled, blinded outcome assessment study comparing Xylocore®, an innovative formulation based on Xylitol and l-carnitine, to standard glucose-based regimens, in end-stage kidney disease patients treated with continuous ambulatory peritoneal dialysis; 170 patients will be randomized (1:1) to receive XyloCore® or to continue their pre-randomization peritoneal dialysis (PD) therapy with glucose-only PD solutions, for 6 months. The primary study's objective is to demonstrate the noninferiority of XyloCore® in terms of Kt/V urea, for which a clinically acceptable noninferiority margin of -0.25 has been determined, assuming that all patients will be treated aiming to a minimum target of 1.7 and an optimal target of 2.0.

Whale Optimization Algorithm BP Neural Network with Chaotic Mapping Improving for SOC Estimation of LMFP Battery

The state of charge (SOC) is a core parameter in the battery management system for LMFP batteries. Accurate SOC estimation is crucial for ensuring the safety and reliability of energy storage applications and new energy vehicles. In order to achieve better SOC estimation accuracy, this article proposes an adaptive whale optimization algorithm (WOA) with chaotic mapping to improve the BP neural network (BPNN) model. The SOC estimation accuracy of the BPNN model was improved by utilizing WOA to find the optimal target weight values and thresholds. Comparative simulation experiments (including constant current and working condition discharge experiments) were conducted in Matlab/Simulink R2018a to verify the proposed algorithm and the other four algorithms. The experimental results show that the proposed algorithm had higher SOC estimation accuracy than the other four algorithms, and its prediction errors were less than 1%. This indicates that the proposed SOC estimation method has better prediction accuracy and stability, and has certain theoretical research significance.

Improving efficacy of repetitive transcranial magnetic stimulation for treatment of Parkinson disease gait disorders.

Parkinson disease (PD) is a neurodegenerative disorder that causes motor and cognitive deficits, presenting complex challenges for therapeutic interventions. Repetitive transcranial magnetic stimulation (rTMS) is a type of neuromodulation that can produce plastic changes in neural activity. rTMS has been trialed as a therapy to treat motor and non-motor symptoms in persons with Parkinson disease (PwP), particularly treatment-refractory postural instability and gait difficulties such as Freezing of Gait (FoG), but clinical outcomes have been variable. We suggest improving rTMS neuromodulation therapy for balance and gait abnormalities in PwP by targeting brain regions in cognitive-motor control networks. rTMS studies in PwP often targeted motor targets such as the primary motor cortex (M1) or supplementary motor area (SMA), overlooking network interactions involved in posture-gait control disorders. We propose a shift in focus toward alternative stimulation targets in basal ganglia-cortex-cerebellum networks involved in posture-gait control, emphasizing the dorsolateral prefrontal cortex (dlPFC), cerebellum (CB), and posterior parietal cortex (PPC) as potential targets. rTMS might also be more effective if administered during behavioral tasks designed to activate posture-gait control networks during stimulation. Optimizing stimulation parameters such as dosage and frequency as used clinically for the treatment of depression may also be useful. A network-level perspective suggests new directions for exploring optimal rTMS targets and parameters to maximize neural plasticity to treat postural instabilities and gait difficulties in PwP.

Novel Insecticidal Pyridylhydrazono Derivatives Identified via Scaffold Hopping and Conformation Regulation Strategies.

Insect transient receptor potential vanilloid (TRPV) channels are critical targets for insecticides. In this study, various scaffold-hopping strategies were employed in the rational design of pyridylhydrazono derivatives as potential insect TRPV channels modulators. Insecticidal bioassay demonstrated that the initial target compounds exhibited lower insecticidal activity compared to pymetrozine, with the optimal compound B3 exhibiting a mortality rate of 53.3 % against Aphis craccivora at 400 mg L-1. Conformation analysis indicated that the high energy barrier required for the transition from the lowest-energy conformation to the active conformation may be a key factor contributing to the reduced insecticidal activities of the target compounds. Further structural optimizations aimed at reducing this energy barrier through binding mode-based conformation regulation led to the identification of optimal target 4-(3'-pyridylhydrazono)pyrazol-5-one derivatives C1 and C2. These compounds exhibited reduced transition energy barriers and improved insecticidal activity, with moderate mortality rate of 66.3 % and 75.7 % against A. craccivora at 400 mg L-1, respectively. These findings provide valuable insights for future research on the discovery of insect TRPV modulators and have significant implications for the development of more effective agricultural insecticides.

Novel physics-informed optimization framework for complex multi-physics problems: Implementation for a sweeping gas membrane distillation module

The application of advanced machine learning algorithms such as deep learning is limited for the surrogate-based process optimization of complex multi-physics problems because high-quality experimental and numerical training samples required for deep-learning model training are expensive and scarce. To address this issue, in this study, a novel physics-informed process optimization (PIPO) framework was introduced. In the first step, surrogate models based on conventional neural networks (NN) were trained using a few available high-quality training samples. In the second step, the trained NN models were coupled to the process optimization solver in which the loss of physical laws was added to the optimizer’s objective function to find optimal design points that satisfy the laws of physics. As a result, the generalization performance of the framework was greatly improved for design targets outside the training range of NN models. PIPO is substantially different from the physics-informed neural networks where the loss of physics is added to the loss function used during NN model training. The PIPO framework was used to optimize a sweeping gas membrane distillation (SGMD) module. Eight input design variables, including process and geometrical parameters, were optimized for different challenging targets to achieve the best SGMD performance in terms of ammonia recovery ratio and concentration. It was shown that for noticeably few training samples of 68 experiments, the proposed framework was able to achieve the optimization targets within a reasonable computational cost. The optimum designs were verified and analyzed in detail by high-resolution computational fluid dynamics models.

Patient selection, ventricular tachycardia substrate delineation and data transfer for stereotactic arrhythmia radioablation. A Clinical Consensus Statement of the European Heart Rhythm Association (EHRA) of the ESC and the Heart Rhythm Society (HRS).

Stereotactic arrythmia radioablation (STAR) is a novel, non-invasive and promising treatment option for ventricular arrythmias (VA). It has been applied in highly selected patients mainly as bail-out procedure, when (multiple) catheter-ablations, together with anti-arrhythmic drugs, were unable to control the VAs. Despite the increasing clinical use there is still limited knowledge of the acute and long-term response of normal and diseased myocardium to STAR. Acute toxicity appeared to be reasonably low but potential late adverse effects may be underreported. Among published studies, the provided methodological information is often limited, and patient selection, target volume definition, methods for determination and transfer of target volume, and techniques for treatment planning and execution differ across studies, hampering pooling of data and comparison across studies. In addition, STAR requires close and new collaboration between clinical electrophysiologists and radiation oncologists, which is facilitated by shared knowledge in each collaborator's area of expertise and a common language. This clinical consensus statement provides uniform definition of cardiac target volumes. It aims to provide advice in patient selection for STAR including etiology specific aspects, and advice in optimal cardiac target volume identification based on available evidence. Safety concerns and the advice for acute and long-term monitoring including the importance of standardized reporting and follow-up are covered by this document. Areas of uncertainty are listed, which require high-quality, reliable pre-clinical and clinical evidence before expansion of STAR beyond clinical scenarios in which proven therapies are ineffective or unavailable.

Assembly Simulation and Optimization Method for Underconstrained Frame Structures of Aerospace Vehicles

Aerodynamic contour dimensional accuracy is very important for the stable and safe flight of aerospace vehicles. Nevertheless, due to the influence of various factors such as material properties, machining and manufacturing deviations, and assembly and installation deviations, key structural geometric dimensions are frequently exceeded. Therefore, this paper investigates a data-driven combined vector loop method (VLM)–Skin Model Shapes (SMS) method to realize aerospace vehicle structural geometric accuracy analysis; assembly optimization targeting contour deviation is also achieved. Tests are carried out on a typical aerospace vehicle’s underconstrained structural workpieces to validate the effectiveness of the proposed method.

Detection of Epstein‒Barr virus DNA methylation as tumor markers of nasopharyngeal carcinoma patients in saliva, oropharyngeal swab, oral swab, and mouthwash.

Saliva biopsy of nasopharyngeal carcinoma (NPC) has been developed in our latest study, indicating the application of oral sampling in NPC detection. Further exploration of the potential for self-sampling from the oral cavity is necessary. A total of 907 various samples from oral cavity, including saliva (n=262), oropharyngeal swabs (n=250), oral swabs (n=210), and mouthwash (n=185), were collected. Epstein‒Barr virus (EBV) DNA methylation at the 12,420bp CpG site in EBV genome from the repeat-copy W promoter (Wp) region and at the 11,029bp CpG site in the single-copy C promoter (Cp) region were simultaneously detected in these samples. A significant increase in EBV methylation, no matter at Wp or Cp region, was found in all types of samples from NPC patients. However, EBV DNA methylation in saliva and oropharyngeal swab showed a better diagnostic performance in detecting NPC. The combination of these two sample types and two markers could help to improve the detection of NPC. Our study further explored the optimal self-sampling methods and detection target in the detection of NPC and may facilitate the application of EBV DNA methylation detection in a home-based large-scale screening of NPC.

Enhancing Access Through Language-Tailored Approach in Telehealth and Veterans Video Connect: Traumatic Brain Injury (TBI) Veterans Satisfaction Assessment.

Traumatic brain injury (TBI) can impact language processing, necessitating language-tailored approaches. Telehealth may expand rural Veterans' access but has unknown feasibility for language preferences. This study explored telehealth/Veterans Video Connect satisfaction for Spanish/English TBI screening. The study was approved by the VA Caribbean Healthcare System Institutional Review Board and the Research and Development Committee. Mixed methods evaluated telehealth satisfaction in Veterans receiving TBI assessments from October 2021 to October 2023. Surveys included the 16-item Clinical Video Telehealth (CVT) questionnaire on communication, technical factors, coordination, and overall satisfaction, and the 21-item Telemedicine Satisfaction and Usefulness Questionnaire (TSUQ) examining usefulness, ease of use, manners, quality, and satisfaction. Mean domain/item scores were calculated among 57 Veterans, 12 English, and 45 Spanish-speaking. Semi-structured interviews also elicited user experiences from 4 providers and 5 Veterans. Transcripts underwent qualitative coding for themes using Atlas.ti.8. On CVT (0-5 scale), overall satisfaction averaged 4.50 (English) and 4.69 (Spanish). Lowest scoring item for English users was easy video connection (4.25), while unclear expectations had the lowest Spanish score (3.60). For TSUQ, overall mean scores were 4.50 (English) and 4.67 (Spanish), with improved health post-telehealth having the lowest average (English 3.33, Spanish 3.67). Qualitatively, Veterans and providers noted strengths like access and communication but weaknesses around connectivity, care delays, and privacy. Differences emerged regarding convenience (Veterans) versus operational barriers (providers). There was a strong positive correlation for Spanish surveys and a moderate correlation for English surveys (r = 0.71 Spanish surveys, r = 0.69 English surveys) between TSUQ and CVT for individual respondents. Patients conveyed positive experiences, but qualitative data revealed actionable targets for optimization like infrastructure and coordination improvements. Key limitations include small samples and lack of comparison to in-person care. Still, high satisfaction coupled with specific user feedback highlights telehealth's potential while directing enhancements. The results found high Veteran satisfaction with Spanish/English TBI telehealth, but mixed methods illuminated salient domains for better accommodating user needs, particularly regarding logistics and technology. Rigorously integrating experiences with metrics over expanded diverse samples and modalities can further guide refinements to enhance telehealth with a language-tailored approach.

A Dynamic Thickening Strategy for High-Fidelity CFD Analyses of Multi-Regime Combustion

Abstract In this study, a dynamic thickening strategy for DTFLES application to multi-regime combustion is proposed. The main idea lies in using the numerical solution of an Ordinary Differential Equation (ODE) as a thickening factor. The equation relates the time derivative of the local thickening factor to its production and destruction rates, which are proportional to the gap between the instantaneous value and optimal target values. The smoothness of the thickening factor in time is ensured by the ODE solution, while in space it is achieved through a mathematical function defined in a continuous flame index space. The equation is numerically integrated with a semi-implicit scheme by making use of the backward Euler formula. The strategy has been implemented in a commercial Computational Fluid Dynamics (CFD) solver and it has been tested by performing Large Eddy Simulations of the hydrogen/air flame produced by the HYLON injector, which has been individuated as an interesting test case for the proposed dynamic strategy. Turbulence-chemistry interactions are recovered by means of a well-assessed subgrid efficiency model. Numerical results are compared with the experimental ones obtained at Institut de Mécanique des Fluides de Toulouse (IMFT).

Sustained efficacy of angioplasty for cerebral vasospasm after aneurysmal subarachnoid hemorrhage: Risk features and device comparison

BackgroundCerebral vasospasm is a leading source of delayed morbidity and mortality after aneurysmal subarachnoid hemorrhage (aSAH). Angioplasty may improve vasospasm, while optimal target and device selection remains controversial. This study aimed to identify features and devices associated with sustained efficacy. MethodsWe identified consecutive patients who underwent angioplasty for aSAH vasospasm. The primary outcome was a composite of adequate angioplasty (residual narrowing < 50 %) without complications. Secondary outcomes included rates of refractory/recurrent vasospasm and sustained improvement at follow-up. Associated features were identified through multivariable analysis. Outcomes were compared between balloon and Comaneci/stentriever in a propensity-score-matched cohort. ResultsA total of 149 vasospastic segments underwent angioplasty: 61.7 % in the proximal anterior circulation (ICA, M1, A1), 20.1 % in distal segments (A2 and M2) and 18.1 % in the posterior circulation. Adequate angioplasty was achieved without complication in 83.2 % of vessels, with a sustainable effect in 84.3 % at follow-up. Refractory/recurrent vasospasm was observed in 17.4 %, yielding a 10.1 % retreatment rate. Notably, only 35.3 % of vessels undergoing inadequate angioplasty demonstrated improvement at follow-up. Angioplasty targeting distal MCA (adjusted OR, 0.10) or BA-V4 (aOR, 0.10), and inadequate angioplasty (aOR, 0.03) were unfavorable predictors for sustained improvement. Efficacy outcomes were similar between balloon and Comaneci/stentriever in a matched subgroup analysis. ConclusionAngioplasty, when achieving residual narrowing < 50 %, demonstrated sustained improvement for vasospasm. Novel devices may exhibit comparable efficacy to balloon angioplasty for selected segments.

Study Protocol for a Prospective Self-Controlled Trial on Success in Meeting Comprehensive Genomic Profiling Analysis Criteria for Specimens Obtained by Endoscopic Ultrasound-Guided Tissue Acquisition Using a 19G Needle from Primary and Metastatic Lesions in Pancreatic Cancer with Metastatic Lesions: The PRIMATE Study.

EUS-TA in unresectable pancreatic cancer requires not only a tissue diagnosis but also tissue collection in anticipation of comprehensive genomic profiling. However, the optimal puncture target remains controversial. Therefore, the Primary and Metastatic Lesions in Pancreatic Cancer (PRIMATE) study was designed to clarify the optimal target by comparing the success rates for meeting OncoGuide NCC Oncopanel (NOP) analysis criteria on pre-check primary and metastatic lesion specimens obtained during the same EUS-TA session in patients with invasive pancreatic ductal adenocarcinoma. In this ongoing prospective study, two specimens, each from primary and metastatic lesions, are obtained by EUS-TA (typically using a 19G fine-needle biopsy needle) in patients with invasive pancreatic ductal adenocarcinoma. The primary endpoint is the proportion of EUS-TA specimens that meet NOP analysis criteria during pre-check (i.e., tumor cellularity of ≥20% and a tissue area of ≥4 mm2), which are then compared between primary and metastatic lesions. This study has been approved by the National Cancer Center Institutional Review Board (Research No. 2022-168). The results of this study will be reported at an international conference and published in an international peer-reviewed journal. The trial registration number is UMIN 000048966.

Step-by-Step Description of Percutaneous Full-Endoscopic C2 Ganglionectomy: An Anatomic Feasibility Study in Human Cadavers.

The percutaneous full-endoscopic C2 ganglionectomy (PEC2G), an innovative procedure developed for the surgical treatment of intractable occipital neuralgia, was firstly reported by us in 2021. However, a universally accepted and well-articulated protocol modality remains elusive. The primary objective of this anatomic investigation was to meticulously elucidate the standard procedural steps of PEC2G and assess the anatomic features supporting the safe implementation of PEC2G. Eighteen fresh adult cadavers were incorporated into this study. From this sample, 3 cadavers were subjected to bilateral PEC2G. Each procedure was documented and assessed, leading to the formulation of standard procedure criteria for PEC2G. Subsequently, 10 sets of anatomic parameters pertinent to this procedure were identified, quantified, and analyzed in 15 cadavers after complete bilateral endoscopic exposure of the C2 ganglion. An assessment of the technical feasibility and potential constraints associated with PEC2G was conducted, providing invaluable insights into the procedure's anatomic considerations. All 3 cadavers successfully underwent the PEC2G without any observed complications, such as dura tears or vertebral artery injuries. The C2 inferior articular process emerged as the optimal bony target for puncture, with the C2 pedicle serving as the standard guiding landmark en route to the C2 ganglion. In the 15 cadavers subjected to the planned procedure, 10 sets of anatomic parameters were quantified, establishing a foundational understanding of the anatomy in the context of PEC2G procedure. The results demonstrated that the characteristic of anatomic data pertinent to surgical site supported the safe implementation of PEC2G. This study contributes the standard surgical steps and crucial anatomic parameters relevant to PEC2G. The characteristic of anatomic data bolsters the safety credentials of this technique, which offers a reliable approach to achieve C2 ganglionectomy. These insights undeniably establish a robust foundation for the ongoing refinement and broader adoption of PEC2G.