Surgical Innovation最新文献_第8页

Artificial Intelligence-Based Prediction of Recurrence and Personalized Treatment Planning in Pediatric Pilonidal Sinus Disease. 基于人工智能的小儿毛窦病复发预测及个性化治疗方案。

IF 1.6 4区医学

Surgical Innovation Pub Date : 2026-06-01 Epub Date: 2025-12-23 DOI: 10.1177/15533506251411009

Tülin Öztaş, Suat Çal, Sevinç Akdeniz, Serdest Teğin

{"title":"Artificial Intelligence-Based Prediction of Recurrence and Personalized Treatment Planning in Pediatric Pilonidal Sinus Disease.","authors":"Tülin Öztaş, Suat Çal, Sevinç Akdeniz, Serdest Teğin","doi":"10.1177/15533506251411009","DOIUrl":"10.1177/15533506251411009","url":null,"abstract":"PurposeThis study aimed to assess the feasibility of artificial intelligence (AI)-based models for predicting recurrence risk and supporting individualized treatment strategies in pediatric pilonidal sinus disease (PSD).MethodsClinical data from 242 pediatric PSD patients were retrospectively analyzed. Two machine learning (ML) models were developed: (1) a binary classifier for recurrence prediction and (2) a multiclass classifier for treatment modality selection. Model performance was evaluated using 5-fold cross-validation based on accuracy, area under the receiver operating characteristic curve (ROC-AUC), F1 score, and confusion matrix. Model interpretability was assessed using SHapley Additive exPlanations (SHAP) analysis to identify the most influential predictive features.ResultsAmong 242 patients, 59.1% underwent surgical excision (unroofing with secondary healing), 33.1% received crystallized phenol, and 7.8% were treated with silver nitrate. The overall recurrence rate was 5.7%, with no significant differences among treatment modalities. Longer healing duration, larger lesion size, higher body mass index (BMI), and an increased number of sinus tracts were associated with higher recurrence risk. SHAP analysis revealed that healing time, BMI, age, and the number of sinus tracts were the most influential predictors in both recurrence and treatment selection models.ConclusionAI-based predictive models can effectively estimate recurrence risk and assist in tailoring individualized management strategies for pediatric PSD. Further multicenter, prospective studies are warranted to validate these findings and support clinical integration of AI-assisted decision systems.","PeriodicalId":22095,"journal":{"name":"Surgical Innovation","volume":" ","pages":"225-233"},"PeriodicalIF":1.6,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145811449","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Learning Curve of Robotic Liver Surgery: Preliminary Experience. 机器人肝脏手术的学习曲线：初步经验。

IF 1.6 4区医学

Surgical Innovation Pub Date : 2026-06-01 Epub Date: 2025-11-23 DOI: 10.1177/15533506251403590

Gaetano Piccolo, Matteo Barabino, Giampaolo Formisano, Laura Benuzzi, Adelona Salaj, Paolo Pietro Bianchi

{"title":"Learning Curve of Robotic Liver Surgery: Preliminary Experience.","authors":"Gaetano Piccolo, Matteo Barabino, Giampaolo Formisano, Laura Benuzzi, Adelona Salaj, Paolo Pietro Bianchi","doi":"10.1177/15533506251403590","DOIUrl":"10.1177/15533506251403590","url":null,"abstract":"BackgroundThe daily implementation of robotic programmes for general surgery has allowed for the diffusion of the robotic approach in clinical practice in many centres with relatively little experience in laparoscopic liver resection.MethodsThis study describes our preliminary experience with robotic liver resection (RLR) using the da Vinci Xi Surgical System®, beginning with assistance provided by an expert robotic colorectal team. Between 2022 and 2024, data on 61 consecutive minor RLRs performed by a single hepatobiliary team were retrospectively analysed. Intraoperative blood loss and operative time were used to construct learning curves.ResultsIn the first phase of the learning curve (competency; cases 1-20), surgeons focused on acquiring basic surgical skills. Most cases involved non-anatomical wedge resections of superficial liver lesions with a low IWATE score. From the 14th case onwards, a significant improvement in operative time and a reduction in blood loss were observed. During the second phase of the learning curve (proficiency; cases 21-50), the surgical cases became more complex. The cumulative operative time increased progressively, reaching a plateau around the forty-first case. Blood loss initially increased but then gradually stabilised below 400 mL. During the early mastery phase of the learning curve (cases 51-61), the IWATE score continued to increase (mean 8), whereas the cumulative operative time and blood loss were stable.ConclusionsWe believe that the success of our initial robotic programme is due not only to technological advancement, but also to the continuous development and effective collaboration of the multidisciplinary colorectal and liver team.","PeriodicalId":22095,"journal":{"name":"Surgical Innovation","volume":" ","pages":"283-293"},"PeriodicalIF":1.6,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145588738","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Biphasic Use of ICG for Delineation of Bilio-Vascular Anatomy During Lymph Node Clearance. 双相应用ICG描绘淋巴结清除过程中的胆管解剖。

IF 2.2 4区医学

Surgical Innovation Pub Date : 2026-06-01 Epub Date: 2025-12-23 DOI: 10.1177/15533506251411014

Roy Patankar, Avinash Supe

引用次数: 0

Viclean®: A Novel Wound Protector Equipped With a Waste Collection Bag for Abdominal Surgery. Viclean®：一种装有腹部手术废物收集袋的新型伤口保护器。

IF 1.6 4区医学

Surgical Innovation Pub Date : 2026-06-01 Epub Date: 2025-12-25 DOI: 10.1177/15533506251413061

Jianmin Qian, Ying Xiong, Hailong Ju, Ben Ouyang, Sheng Xu

{"title":"Viclean®: A Novel Wound Protector Equipped With a Waste Collection Bag for Abdominal Surgery.","authors":"Jianmin Qian, Ying Xiong, Hailong Ju, Ben Ouyang, Sheng Xu","doi":"10.1177/15533506251413061","DOIUrl":"10.1177/15533506251413061","url":null,"abstract":"BackgroundSurgical site infection (SSI) remains a leading health care-associated complication in open abdominal surgery. Conventional wound protectors reduce SSI risk but often fail to reliably prevent contamination of the wound edges and operative field when intraoperative effluent is substantial, such as during cesarean delivery.Device DescriptionWe developed Viclean®, a dual-ring wound protector equipped with a waste collection bag. A newly added middle ring links the dual-ring frame to a flexible drainage system, and a support strip maintains channel patency for continuous drainage, thereby isolating effluent and preventing contact with the incision and surrounding tissues. All components are made of medical-grade thermoplastic polyurethane (TPU) to ensure biocompatibility, flexibility, and durability.Preliminary ResultsIn clinical observations, Viclean® demonstrated favorable intraoperative performance. In an emergency cesarean section, amniotic fluid was rapidly diverted into the bag, preventing contamination of the incision and operative field. In an elective open left hemicolectomy, enteric effluent and irrigation fluids were effectively drained into the bag, maintaining clean and dry wound edges. Surgical teams provided positive evaluations regarding its clinical utility.Current StatusViclean® has completed sterility, biocompatibility, and packaging validation and operates under an ISO 13485:2016-certified quality system. Regulatory registrations have been obtained in multiple areas. The device is authorized in more than 20 countries; however, it is not yet commercially available outside China.","PeriodicalId":22095,"journal":{"name":"Surgical Innovation","volume":" ","pages":"306-309"},"PeriodicalIF":1.6,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145834843","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Conventional Laparoscopic vs Multi-Degree of Freedom Articulating Instruments in Minimally Invasive Surgical Suturing. 传统腹腔镜与多自由度关节器械在微创手术缝合中的比较。

IF 1.6 4区医学

Surgical Innovation Pub Date : 2026-06-01 Epub Date: 2025-12-07 DOI: 10.1177/15533506251407183

Maggie Jiang, Alexis Samples, Austin Garcia, Yufan Brandon Chen

{"title":"Conventional Laparoscopic vs Multi-Degree of Freedom Articulating Instruments in Minimally Invasive Surgical Suturing.","authors":"Maggie Jiang, Alexis Samples, Austin Garcia, Yufan Brandon Chen","doi":"10.1177/15533506251407183","DOIUrl":"10.1177/15533506251407183","url":null,"abstract":"Study ObjectiveThe Artisential instruments are multi-degree-of-freedom laparoscopic instruments compatible with traditional ports. Their articulation may offer advantages over conventional instruments, particularly in suturing. This study aimed to compare suturing times between conventional laparoscopic instruments and the Artisential device.DesignInternally controlled prospective cohort/case series.InterventionsA power analysis determined that 16 knots per group were needed to detect a 20s difference with 80% power and 5% alpha. Two patients undergoing laparoscopic sacrocolpopexy were enrolled. During anterior and posterior mesh fixation, half the knots were tied using two conventional laparoscopic needle drivers; the other half used an Artisential needle driver in one hand and a conventional driver in the other. All knots were tied by the same surgeon, positioned adjacently to minimize bias from laterality or pelvic depth. Each knot consisted of a surgeon's knot followed by two square knots. All cases were recorded and evaluated by 2 reviewers, using time stamps to determine knot tying duration. T-tests compared times between the groups.Measurements and Main ResultsThirty-two knots were analyzed. Mean knot time was 119 s (SD 43) with conventional instruments vs 66 s (SD 14) using the Artisential device (P < .01). All individual components-needling, surgeon's knot, and both square knots-were significantly faster with the Artisential driver (all P < .05).ConclusionThe Artisential articulating laparoscopic instrument nearly halved knot-tying time during laparoscopic sacrocolpopexy. This novel instrument may improve surgical efficiency in minimally invasive gynecologic procedures.","PeriodicalId":22095,"journal":{"name":"Surgical Innovation","volume":" ","pages":"294-299"},"PeriodicalIF":1.6,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145701722","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Fifty Shades of Red! - Utilizing Machine Learning for Estimating Blood Loss on Surgical Sponges. 《五十度红》！-利用机器学习来估计手术海绵的出血量。

IF 1.6 4区医学

Surgical Innovation Pub Date : 2026-06-01 Epub Date: 2025-11-19 DOI: 10.1177/15533506251400113

Duygu Kara, Hüseyin Abacı, Fatih Soygazi, Feray Gürsoy

{"title":"Fifty Shades of Red! - Utilizing Machine Learning for Estimating Blood Loss on Surgical Sponges.","authors":"Duygu Kara, Hüseyin Abacı, Fatih Soygazi, Feray Gürsoy","doi":"10.1177/15533506251400113","DOIUrl":"10.1177/15533506251400113","url":null,"abstract":"BackgroundAccurate intraoperative blood loss estimation is crucial, particularly for pediatric and adolescent patients. Traditional methods (visual, gravimetric, formula-based) are often imprecise and unreliable, highlighting a need for objective and efficient approaches.MethodsThis study proposes a novel machine learning (ML) approach to predict blood loss from surgical sponges via a pixel-counting rate system. We utilized image preprocessing, including edge detection, and evaluated various ML algorithms with hyperparameter tuning. Details include deployment on commodity smartphones, a deterministic preprocessing pipeline, and app-level measures to mitigate folding, lighting, and motion blur. Model accuracy was assessed using RMSE and R2. A lightweight CNN baseline on raw images was also evaluated, positioning our system as a low-cost, mobile alternative to proprietary solutions.ResultsThe ML-based method significantly reduced reliance on subjective visual estimation. Gradient Boosting (GB) and Artificial Neural Networks (ANN) achieved a minimum RMSE of 0.91 and a maximum R2 of 0.93, outperforming traditional methods. The system demonstrates strong potential for integration into mobile phone applications for practical clinical use.ConclusionsOur machine learning-based pixel-counting approach offers a more accurate and efficient alternative for intraoperative blood loss estimation. Future research will expand the dataset, refine ML algorithms, and adapt the system for specialized equipment. While a CNN baseline approached GB performance, GB remained superior at the current data scale. A prospective paired-data plan is outlined for future benchmarking. Clinically, the per-sponge RMSE (∼0.9 cc) aligns with an acceptable error margin (0.5-1.0 cc) for decision support, noting that pediatric transfusion decisions rely on cumulative loss and multimodal monitoring.","PeriodicalId":22095,"journal":{"name":"Surgical Innovation","volume":" ","pages":"263-275"},"PeriodicalIF":1.6,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145551080","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Risk Factors for Conversion in Laparoscopic Cholecystectomy and Development of a Predictive Nomogram. 腹腔镜胆囊切除术转换的危险因素及预测Nomogram发展。

IF 1.6 4区医学

Surgical Innovation Pub Date : 2026-06-01 Epub Date: 2025-12-24 DOI: 10.1177/15533506251413062

Mehmet Berksun Tutan, Ramazan Topcu, Veysel Barış Turhan, İbrahim Tayfun Şahiner

{"title":"Risk Factors for Conversion in Laparoscopic Cholecystectomy and Development of a Predictive Nomogram.","authors":"Mehmet Berksun Tutan, Ramazan Topcu, Veysel Barış Turhan, İbrahim Tayfun Şahiner","doi":"10.1177/15533506251413062","DOIUrl":"10.1177/15533506251413062","url":null,"abstract":"BackgroundLaparoscopic cholecystectomy (LC) is the gold standard for gallbladder disease, yet conversion to open cholecystectomy (OC) remains necessary in 2-15% of cases. Although often life-saving, conversion increases operative time, morbidity, and hospital stay. Identifying reliable predictors is therefore crucial for surgical planning and patient counseling.MethodsA retrospective cohort study was conducted on 4535 patients who underwent LC at a tertiary center between January 2018 and May 2024. Demographic, clinical, laboratory, radiological, intraoperative, and histopathological data were extracted from medical records. Univariate and multivariate logistic regression analyses were used to identify independent predictors of conversion. A nomogram was developed to estimate individualized conversion risk.ResultsConversion to OC occurred in 304 patients (6.7%). Independent predictors included male sex (OR 1.65, 95% CI 1.09-2.50), ASA IV classification (OR 4.84, 95% CI 2.51-9.33), elevated CRP (OR 1.007 per mg/L, 95% CI 1.004-1.010), reduced lymphocyte count (OR 0.42, 95% CI 0.21-0.84), gastric or intestinal complications (OR 3.38, 95% CI 1.01-11.38), gangrenous gallbladder (OR 2.39, 95% CI 1.45-3.93), and xanthogranulomatous cholecystitis (OR 5.42, 95% CI 1.61-18.25). Gallbladder wall thickness was the strongest preoperative predictor (OR 1.20 per mm, 95% CI 1.13-1.27, P < 0.001), and existence of dense adhesions were the strongest intraoperative predictor (OR 26.77, 95% CI 16.64-43.07).ConclusionConversion to OC reflects anatomical complexity and advanced disease rather than surgical failure. Gallbladder wall thickness, inflammatory markers, adhesions, gangrene, and xanthogranulomatous cholecystitis are consistent predictors. The proposed nomogram provides individualized risk estimation to improve preoperative planning and patient counseling. Prospective multicenter validation is warranted.","PeriodicalId":22095,"journal":{"name":"Surgical Innovation","volume":" ","pages":"234-243"},"PeriodicalIF":1.6,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145820671","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Evaluating the Impact of Surgeon Preference Card Age on Surgical Waste and Costs. 评估外科医生偏好卡年龄对手术浪费和费用的影响。

IF 2.2 4区医学

Surgical Innovation Pub Date : 2026-05-29 DOI: 10.1177/15533506261455385

Philomena Colagiuri, Kristen Pickles, Rohan Hutchins, Erin Mathieu

{"title":"Evaluating the Impact of Surgeon Preference Card Age on Surgical Waste and Costs.","authors":"Philomena Colagiuri, Kristen Pickles, Rohan Hutchins, Erin Mathieu","doi":"10.1177/15533506261455385","DOIUrl":"10.1177/15533506261455385","url":null,"abstract":"BackgroundDisposal of unused surgical items exacerbates the environmental footprint and costs of hospitals. Surgeon preference cards (SPCs), which specify equipment needed for surgeries, impact inventory control and wasted supplies. This study assessed the effect of SPC age on surgical waste and costs, and examined staff attitudes towards SPC systems.MethodsA random selection of elective surgeries was observed in four operating theatres (March - October 2023) at a regional public hospital in New South Wales, Australia. Wasted items per procedure and the age of SPCs were recorded. Waste cost calculations were based on hospital records. An online survey measured perioperative nursing staff and surgeon attitudes. Data analysis involved simple linear regression, descriptive and summary statistics.ResultsData from 35 of 1456 (2.4%) elective surgical procedures showed that 285 single use items were unused (median 2 per procedure, IQR 7). Each year the SPC aged, 1.6 additional items were wasted (95% CI 1.3-1.9, P < 0.01). The total waste from unused single-use items amounted to 22.4 kg (18.7 kg general waste, 1.9 kg sharps waste, and 1.9 kg recycled) and purchase price totalled $3543.07 AUD. Survey respondents (n = 36) expressed mixed opinions about the current SPC system, with concerns about waste, cost, and environmental consequences. They favoured an electronic system for its potential to enhance efficiency and patient safety but noted barriers such as resource constraints and costs.ConclusionUpdating SPCs is an effective strategy to minimise surgical waste and costs. Hospitals using paper based SPCs should consider transitioning to electronic systems for better sustainability.","PeriodicalId":22095,"journal":{"name":"Surgical Innovation","volume":" ","pages":"15533506261455385"},"PeriodicalIF":2.2,"publicationDate":"2026-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148057060","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Two-port Video-Assisted Thoracoscopic Plication Using Porous Nitinol Pledgets for Diaphragmatic Paralysis. 双端口视频胸腔镜应用多孔镍钛诺材料治疗膈肌麻痹。

IF 1.6 4区医学

Surgical Innovation Pub Date : 2026-05-26 DOI: 10.1177/15533506261455435

Evgeniy Topolnitskiy, Timofey Chekalkin, Ekaterina Marchenko, Ji-Hoon Kang

{"title":"Two-port Video-Assisted Thoracoscopic Plication Using Porous Nitinol Pledgets for Diaphragmatic Paralysis.","authors":"Evgeniy Topolnitskiy, Timofey Chekalkin, Ekaterina Marchenko, Ji-Hoon Kang","doi":"10.1177/15533506261455435","DOIUrl":"https://doi.org/10.1177/15533506261455435","url":null,"abstract":"BackgroundDiaphragmatic plication is a standard treatment for symptomatic unilateral diaphragmatic paralysis, but the best minimally invasive technique and reinforcement material remain debated. We evaluated a two-port VATS plication technique using porous Nitinol pledgets.MethodsThis retrospective single-center study included 30 consecutive adults with symptomatic unilateral diaphragmatic paralysis who underwent two-port VATS plication between 2018 and 2024. All procedures were performed using porous NiTi pledgets (7 × 5 × 3 mm) and non-absorbable sutures. Perioperative outcomes included operative time, blood loss, extubation, ICU use, chest tube duration, pain scores, complications, and length of stay. Functional outcomes comprised spirometry (FVC, FEV1), MRC dyspnea scores, and radiographic hemidiaphragm elevation at 1, 6, and 12 months.ResultsMean age was 61.3 ± 10.3 years; 66.7% of patients were female. Mean operative time was 123.1 ± 29.0 min and blood loss 20.3 ± 20.8 mL. Immediate extubation occurred in 86.7%; 40% required brief ICU monitoring. Chest tube duration and hospital stay were 2.2 ± 1.3 and 5.5 ± 2.9 days. Complications occurred in 13.3%, all grade I-II. At 12 months, FVC increased from 60.2 ± 12.2% to 82.1 ± 10.6%, FEV1 from 60.2 ± 14.5% to 81.1 ± 11.8%, MRC score improved from 3.8 ± 0.4 to 0.5 ± 0.6, diaphragm elevation decreased by ∼34%, and 90% of patients reported symptomatic improvement.ConclusionsTwo-port VATS diaphragmatic plication reinforced with porous NiTi pledgets demonstrates feasibility, safety, and reproducibility with sustained functional and symptomatic improvement and low morbidity. The absence of a control group precludes claims of material superiority; observed benefits primarily reflect the mechanical restoration achieved by plication itself, with porous NiTi serving as a biocompatible alternative to standard PTFE pledgets.","PeriodicalId":22095,"journal":{"name":"Surgical Innovation","volume":" ","pages":"15533506261455435"},"PeriodicalIF":1.6,"publicationDate":"2026-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148034833","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

LUCID: An AI-Powered System for Real-Time Laparoscopic Lens Cleanliness Classification. LUCID：人工智能驱动的实时腹腔镜镜头清洁度分类系统。

IF 1.6 4区医学

Surgical Innovation Pub Date : 2026-05-23 DOI: 10.1177/15533506261451747

Eshan Sayani, Faiza Quadri, Rishit Yokananth, Sriya Dommaraju, Lisa Du, Tony Zhu, Maansi Srinivasan, Kathleen Schmidt, John Uecker, Christopher Idelson

{"title":"LUCID: An AI-Powered System for Real-Time Laparoscopic Lens Cleanliness Classification.","authors":"Eshan Sayani, Faiza Quadri, Rishit Yokananth, Sriya Dommaraju, Lisa Du, Tony Zhu, Maansi Srinivasan, Kathleen Schmidt, John Uecker, Christopher Idelson","doi":"10.1177/15533506261451747","DOIUrl":"https://doi.org/10.1177/15533506261451747","url":null,"abstract":"BackgroundIn minimally invasive surgery (MIS), maintaining consistent optical clarity is essential for surgical safety and efficiency. However, lens contamination events (LCEs) such as fogging and debris accumulation continue to disrupt visualization, requiring frequent camera removal and cleaning that prolongs operative time and is linked to surgical injuries.ObjectiveDetermine performance of an artificial intelligence (AI) model, LUCID, for the detection of laparoscopic lens contamination.MethodsSurgical video footage was collected from the central Texas region and annotated to classify the lens state as \"clean\" or \"dirty.\" An AI model was trained on this dataset to detect lens contamination. 9 additional laparoscopic procedures were analyzed by the model and validated by human reviewers to determine true model performance.ResultsAcross the 9 cases analyzed by LUCID and validated by reviewers, the model achieved an overall accuracy of 90.42%, with a precision of 94.45%, sensitivity of 91.19%, and specificity of 88.80%, demonstrating potential for the use of LUCID to assess optical clarity in MIS.ConclusionAI-enhanced visualization assessment presents a promising approach to enable objective detection of visual clarity in MIS. With compromised vision being a known problem with serious safety concerns, and future applications for AI-enhanced surgery requiring clear visualization for high performance, the importance of clear visualization is paramount more than ever before. Future work may look to standardize visual clarity across operative settings to mitigate variability in clinical outcomes.","PeriodicalId":22095,"journal":{"name":"Surgical Innovation","volume":" ","pages":"15533506261451747"},"PeriodicalIF":1.6,"publicationDate":"2026-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148006887","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0