A novel latex patch model enables cost-effective hands-on teaching in vascular surgery.

Objectives: We developed a new simulator for hands-on teaching of vascular surgical skills, the Leipzig Latex Patch Model (LPM). This study aimed to quantify the effectiveness and acceptance of the LPM evaluated by students, as well as evaluation of the results by experienced vascular surgeons. Methods: A prospective, single-center, single-blinded, randomized study was conducted. Fifty 5th-year medical students were randomized into two groups, first performing a patch suture on the LPM (study group) or established synthetic tissue model (control), then on porcine aorta. The second suture was videotaped and scored by two surgeons using a modified Objective Structured Assessment of Technical Skill (OSATS) score. We measured the time required for suturing; the participants completed questionnaires. Results: Participants required significantly less time for the second suture than the first (median: LPM 30 min vs. control 28.5 min, p = 0.0026). There was no significant difference in suture time between the groups (median: 28 min vs. 30 min, p = 0.2958). There was an increase in confidence from 28 % of participants before to 58 % after the course (p < 0.0001). The cost of materials per participant was 1.05€ (LPM) vs. 8.68€ (control). The OSATS-scores of the LPM group did not differ significantly from those of the control (median: 20.5 points vs. 23.0 points, p = 0.2041). Conclusions: This pilot study demonstrated an increase in technical skills and confidence through simulator-based teaching. Our data suggests comparable results of the LPM compared to the conventional model, as assessed by the OSATS-score. This low-cost, low-threshold training model for vascular suturing skills should make hands-on training more accessible to students and surgical residents. Key message: We developed and validated a low-cost, low-threshold training model for vascular suturing skills. This should make hands-on training more accessible to medical students and surgical residents in the future.

Classification of anatomic patterns of peripheral artery disease with automated machine learning (AutoML).

AIM: The aim of this study was to investigate the potential of novel automated machine learning (AutoML) in vascular medicine by developing a discriminative artificial intelligence (AI) model for the classification of anatomical patterns of peripheral artery disease (PAD). MATERIAL AND METHODS: Random open-source angiograms of lower limbs were collected using a web-indexed search. An experienced researcher in vascular medicine labelled the angiograms according to the most applicable grade of femoropopliteal disease in the Global Limb Anatomic Staging System (GLASS). An AutoML model was trained using the Vertex AI (Google Cloud) platform to classify the angiograms according to the GLASS grade with a multi-label algorithm. Following deployment, we conducted a test using 25 random angiograms (five from each GLASS grade). Model tuning through incremental training by introducing new angiograms was executed to the limit of the allocated quota following the initial evaluation to determine its effect on the software's performance. RESULTS: We collected 323 angiograms to create the AutoML model. Among these, 80 angiograms were labelled as grade 0 of femoropopliteal disease in GLASS, 114 as grade 1, 34 as grade 2, 25 as grade 3 and 70 as grade 4. After 4.5 h of training, the AI model was deployed. The AI self-assessed average precision was 0.77 (0 is minimal and 1 is maximal). During the testing phase, the AI model successfully determined the GLASS grade in 100% of the cases. The agreement with the researcher was almost perfect with the number of observed agreements being 22 (88%), Kappa = 0.85 (95% CI 0.69-1.0). The best results were achieved in predicting GLASS grade 0 and grade 4 (initial precision: 0.76 and 0.84). However, the AI model exhibited poorer results in classifying GLASS grade 3 (initial precision: 0.2) compared to other grades. Disagreements between the AI and the researcher were associated with the low resolution of the test images. Incremental training expanded the initial dataset by 23% to a total of 417 images, which improved the model's average precision by 11% to 0.86. CONCLUSION: After a brief training period with a limited dataset, AutoML has demonstrated its potential in identifying and classifying the anatomical patterns of PAD, operating unhindered by the factors that can affect human analysts, such as fatigue or lack of experience. This technology bears the potential to revolutionize outcome prediction and standardize evidence-based revascularization strategies for patients with PAD, leveraging its adaptability and ability to continuously improve with additional data. The pursuit of further research in AutoML within the field of vascular medicine is both promising and warranted. However, it necessitates additional financial support to realize its full potential.

CT Texture Analysis and Node-RADS CT Score of Lymph Nodes in Patients With Perihilar Cholangiocarcinoma.

BACKGROUND/AIM: Texture analysis can provide quantitative imaging markers from computed tomography (CT) images. The Node-RADS classification was recently published as a classification system to better characterize lymph nodes in oncological imaging. The present analysis investigated the diagnostic benefit of CT texture analysis and the Node-RADS classification to categorize and stage lymph nodes in patients with perihilar cholangiocarcinoma. PATIENTS AND METHODS: Overall, 25 patients (n=9 females, 36%) with a mean age of 72.4±8.1 years were included. All patients were surgically resected and the lymph nodes were histopathologically analyzed. CT-texture analysis was performed with the Mazda package. All investigated lymph nodes were scored in accordance with the Node-RADS classification. RESULTS: Regarding lymph node discrimination (N- versus N+), Node-RADS classification achieved an area under the curve (AUC) of 0.86 resulting in a sensitivity of 78% and a specificity of 86%. Multiple investigated texture features were different between negative and positive lymph nodes. The "S(0,1)SumVarnc" achieved the best AUC of 0.75 resulting in a sensitivity of 0.91 and a specificity of 0.67. Correlation analysis showed various statistically significant associations between CT texture features and Node-RADS score. CONCLUSION: Several CT texture features and the Node-RADS score derived from preoperative staging CT were associated with the malignancy of the hilar lymph nodes and might aid for preoperative staging. This could change surgical treatment planning in hilar cholangiocarcinoma.

Feasibility and Safety of Percutaneous Axillary Artery Access in a Prospective Series of 100 Complex Aortic and Aortoiliac Interventions.

We aimed to review the feasibility and safe use of the percutaneous axillary artery (AxA, 100 patients) approach for endovascular repair (ER) of thoraco-abdominal aortic aneurysms (TAAA, 90 patients) using fenestrated, branched, and chimney stent grafts and other complex endovascular procedures (10 patients) necessitating AxA access. Percutaneous puncture of the AxA in its third segment was performed using sheaths sized between 6 to 14F. For closing puncture sites greater than 8F, two Perclose ProGlide percutaneous vascular closure devices (PVCDs) (Abbott Vascular, Santa Clara, CA, USA) were deployed in the pre-close technique. The median maximum diameter of the AxA in the third segment was 7.27 mm (range 4.50-10.80). Device success, defined as successful hemostasis by PVCD, was reported in 92 patients (92.0%). As recently reported results in the first 40 patients suggested that adverse events, including vessel stenosis or occlusion, occurred only in cases with a diameter of the AxA < 5 mm, in all subsequent 60 cases AxA access was restricted to a vessel diameter ≥ 5 mm. In this late group, no hemodynamic impairment of the AxA occurred except in six early cases below this diameter threshold, all of which could be repaired by endovascular measures. Overall mortality at 30 days was 8%. In conclusion, percutaneous approach of the AxA in its third segment is feasible and represents a safe alternative access to open access for complex endovascular aorto-iliac procedures. Complications are rare, especially if the maximum diameter of the access vessel (AxA) is ≥5 mm.