Search Results (85)

Atrial fibrillation remains the most frequent sustained arrhythmia, particularly in the elderly population, and is associated with increased risks of stroke, heart failure, and reduced quality of life. While catheter ablation is widely used for rhythm control, its efficacy is limited in persistent and long-standing atrial fibrillation. Over the past two decades, minimally invasive surgical strategies have emerged as effective alternatives, aiming to replicate the success of the Cox-Maze procedure while reducing surgical trauma. This overview critically summarizes the current minimally invasive techniques available for atrial fibrillation treatment, including mini-thoracotomy ablation, thoracoscopic ablation, and hybrid procedures such as the convergent approach. These methods offer the potential for durable sinus rhythm restoration by enabling direct visualization, transmural lesion creation, and left atrial appendage exclusion, with lower perioperative morbidity compared to traditional open surgery. The choice of energy source plays a key role in lesion efficacy and safety. Particular attention is given to the technical steps of each procedure, patient selection criteria, and the role of left atrial appendage closure in stroke prevention. Hybrid strategies, which combine epicardial surgical ablation with endocardial catheter-based procedures, have shown encouraging outcomes in patients with refractory or long-standing atrial fibrillation. Despite the steep learning curve, minimally invasive techniques provide significant benefits in terms of recovery time, reduced hospital stay, and fewer complications. As evidence continues to evolve, these approaches represent a key advancement in the surgical management of atrial fibrillation, deserving integration into contemporary treatment algorithms and multidisciplinary heart team planning. Full article

Accurate liver segmentation and volume estimation from CT images are critical for diagnosis, surgical planning, and treatment monitoring. This paper proposes a GPU-accelerated voxel-level cropping method that localizes the liver region in a single pass, significantly reducing unnecessary computation and memory transfers. We integrate this pre-processing step into two segmentation pipelines: a traditional Chan-Vese model and a deep learning U-Net trained on the LiTS dataset. After segmentation, a seeded region growing algorithm is used for 3D liver volume assessment. Our method reduces unnecessary image data by an average of 90%, speeds up segmentation by 1.39× for Chan-Vese, and improves dice scores from 0.938 to 0.960. When integrated into U-Net pipelines, the post-processed dice score rises drastically from 0.521 to 0.956. Additionally, the voxel-based cropping approach achieves a 2.29× acceleration compared to state-of-the-art slice-based methods in 3D volume assessment. Our results demonstrate high segmentation accuracy and precise volume estimates with errors below 2.5%. This proposal offers a scalable, interpretable, efficient liver segmentation and volume assessment solution. It eliminates unwanted artifacts and facilitates real-time deployment in clinical environments where transparency and resource constraints are critical. It is also tested in other anatomical structures such as skin, lungs, and vessels, enabling broader applicability in medical imaging. Full article

Background: Advanced sensor insoles and motion capture technology can significantly enhance the monitoring of rehabilitation progress for patients with distal tibial fractures. This study leverages the potential of these innovative tools to provide a more comprehensive assessment of a patient’s gait and weight-bearing capacity following surgical intervention, thereby offering the possibility of improved patient outcomes. Methods: A patient who underwent distal medial tibial plating surgery in August 2023 and subsequently required revision surgery due to implant failure, involving plate removal and the insertion of an intramedullary nail in December 2023, was meticulously monitored over a 12-week period. Initial assessments in November 2023 revealed pain upon full weight-bearing without crutches. Following the revision, precise weekly measurements were taken, starting two days after surgery, which instilled confidence in accurately tracking the patient’s progress from initial crutch-assisted walking to full recovery. The monitoring tools included insoles, hand pads for force absorption of the crutches, and a motion capture system. The patient was accompanied throughout all steps of his daily life. Objectives: The study aimed to evaluate the hypothesis that the approximation and formation of a healthy gait curve are decisive tools for monitoring healing. Specifically, it investigated whether cadence, imbalance factors, and ground reaction forces could be significant indicators of healing status and potential disorders. Results: The gait parameters, cadence, factor of imbalance ground reaction forces, and the temporal progression of kinematic parameters significantly correlate with the patient’s recovery trajectory. These metrics enable the early identification of deviations from expected healing patterns, facilitating timely interventions and underscoring the transformative potential of these technologies in patient care. Conclusions: Integrating sensor insoles and motion capture technology offers a promising approach for monitoring the recovery process in patients with distal tibial fractures. This method provides valuable insights into the patient’s healing status, potentially predicting and addressing healing disorders more effectively. Future studies are recommended to validate these findings in a larger cohort and explore the potential integration of these technologies into clinical practice. Full article

Trapeziometacarpal joint osteoarthritis (TMJ OA) is a progressive condition, particularly affecting postmenopausal women. Various surgical techniques have been proposed, but the optimal approach remains debated. This clinical study compares the clinical, functional, and radiological outcomes of two surgical treatments: suspension tenoplasty using the flexor carpi radialis tendon (Altissimi technique, AST) and a dual-mobility prosthesis. The main complications associated with these procedures include postoperative pain, De Quervain’s syndrome, radial nerve injuries, and prosthetic component mobilization. In prosthetic arthroplasty, the most common complication is component mobilization (8%), while in tenoplasty, postoperative pain is the most frequent (15%). A total of 36 patients were randomized into two groups: 18 patients underwent AST (Group A), and 18 received trapeziometacarpal joint arthroplasty (Group B). Functional outcomes were assessed using the Disabilities of the Arm, Shoulder and Hand (DASH), Visual Analogue Score (VAS), and Michigan Hand Outcomes Questionnaire (MHQ) at 3, 6, 12, and 24 months. Range of motion (ROM), Kapandji score, pulp pinch strength, hand grip strength (Jamar dynamometer), and radiological maintenance of the trapezial space (step-off measurement) were also evaluated. Both procedures resulted in significant pain reduction (VAS, p < 0.05) and functional improvement (DASH, MHQ, p < 0.05). ROM increased significantly in both groups. The Kapandji scores improved from 4.0 ± 1.1 to 9.2 ± 1.2 (Group A) and 4.3 ± 0.8 to 7.8 ± 1.4 (Group B) (p < 0.05). Group B grip strength results showed a greater increase in hand grip strength than Group A (p = 0.23). The radiographic step-off showed slight proximal migration of the first metacarpal in Group A, whereas Group B maintained joint height. No implant loosening or major complications were reported in either group. Both suspension tenoplasty and dual-mobility arthroplasty are effective in TMJ OA. AST ensures joint stability with minimal radiographic changes, whereas TJA provides superior grip strength and ROM recovery. The absence of major complications suggests that TJA is a safe alternative to AST, but its higher cost and potential for implant-related complications must be considered. Full article

Background/Objectives: Clinical imaging techniques, such as magnetic resonance imaging and computed tomography, play a vital role in supporting clinicians by aiding disease diagnosis and facilitating the planning of appropriate interventions. This is particularly important in malignant conditions like hepatocellular carcinoma, where accurate image segmentation, delineating the liver and tumor, is a critical initial step in optimizing diagnosis, staging, and treatment planning, including interventions like transplantation, surgical resection, radiotherapy, portal vein embolization, and other procedures. Therefore, effective segmentation methods can significantly influence both diagnostic accuracy and treatment outcomes. Method: In this paper, we propose a deep learning-based approach aimed at accurately segmenting the liver in medical images, thus addressing a critical need in hepatic disease diagnosis and treatment planning. We consider a U-Net architecture with residual connections to capture fine-grained anatomical details. We also take into account the prediction explainability, aiming to highlight, in the image under analysis, the areas that are symptomatic for a certain segmentation. In detail, by exploiting the U-Net architecture, two different models are trained with two annotated datasets of computed tomography medical images, resulting in four different experiments. Results: We consider two different datasets to improve robustness and generalization across diverse patient populations and imaging conditions. Experimental results demonstrate that the proposed method obtains interesting performances, with an accuracy ranging from 0.81 to 0.93. Conclusions: We thus show that the proposed method can provide a reliable and efficient solution for automated liver segmentation, promising significant advancements in clinical workflows and precision medicine. Full article

Introduction: Consent-taking for surgery evolved from a historical paternalistic approach to informed consent in the mid-20th century. Modern healthcare models prioritize patient-centric care, and the use of multimedia tools may overcome challenges such as language barriers and complex medical surgical steps. This study evaluates the impact of an educational video on patient satisfaction for those undergoing percutaneous nephrolithotomy (PCNL), a procedure where explaining complexities verbally can be challenging. Materials and Methods: A randomized control trial was conducted at a tertiary care center in India from July 2022 to April 2024. A total of 232 adult patients scheduled for PCNL were randomly assigned to a study group (Group A) or a control group (Group B). Group A viewed an educational video about PCNL, while Group B provided standard written consent. The video, presented in patients’ native languages, covered procedural details, potential outcomes, and post-operative care. Patient satisfaction was assessed using a 10-question questionnaire at discharge, with scores ranging from one (poor) to five (best). Statistical analysis was performed using SPSS software to compare outcomes between the two groups. Results: The study found that Group A exhibited significantly higher satisfaction compared to Group B across all domains. Group A demonstrated a better understanding of the procedure, improved knowledge of post-operative care, reduced anxiety, and a greater awareness of potential complications. Specifically, the mean satisfaction scores for Group A were higher in understanding the procedure (13.15 vs. 10.00), post-operative care (8.46 vs. 6.84), and overall anxiety (8.65 vs. 6.96). The video also improved patients’ comprehension regarding potential complications and the need for further procedures. Complication rates and hospital stay durations were similar between both groups. Discussion: The educational video significantly enhanced patient satisfaction and the understanding of PCNL. This multimedia approach provided a consistent, clear explanation of the procedure, which improved patient comprehension and reduced anxiety, irrespective of literacy levels. These findings support the integration of video-assisted consent in pre-operative education to enhance patient engagement and satisfaction. Conclusions: The use of an educational video for consent in PCNL improves patient understanding and satisfaction. This method effectively complements traditional consent processes, providing a valuable tool for patient education in complex procedures. Full article

Background: Vaginal reconstruction procedures for patients with Mayer–Rokitansky–Küster–Hauser syndrome (MRKH) have the main purpose of restoring the anatomy to increase the quality of life of these patients. To describe the surgical treatment of patients with type I Mayer–Rokitansky–Küster–Hauser (MRKH) syndrome with complete vaginal agenesis in 10 steps, using a sacropexy technique by a double approach (laparoscopic and perineal), which could help make this procedure more accessible and safer. Methods: The surgical technique was used in a group of three patients diagnosed with MRKH syndrome with vaginal agenesis, in which a neovagina with peritoneal flaps was created, and the reconstruction of the vaginal apex and its sacropexy created the conditions for a favorable and lasting result. Results: Annual reevaluations for up to 5 years revealed a functional neovagina with an average length of approximately 11.33 cm, without stenotic aspects, and no granulation tissue formation. All three cases in which this technique was performed reported sexual activity as expected, excellent quality of life, and good psycho-emotional reintegration. It should be noted that two of the three patients also resolved their marital situation. Conclusions: Although the number of patients in this preliminary report is limited, the surgical technique presented is an effective, safe approach with very good anatomical and functional results at the 5-year follow-up. The favorable surgical outcome of these cases also determined the social integration of the patients, solving some ethnic and religious problems. Full article

Background: Involutional lower eyelid ectropion is a common disorder of the elderly population. Several surgical approaches have been described in the literature to address the multifactorial nature of this condition, each targeting different factors contributing to its development. Nevertheless, no single procedure has proven to be superior to the others. This study aims to assess the safety and effectiveness of a new 3-step combined technique in treating involutional ectropion. Methods: The surgical technique consists of a combination of lateral lid-shortening with removal of a base-up triangle (modified Bick procedure), lower eyelid skin release, and transposition of a laterally based myocutaneous flap from the upper eyelid. A retrospective chart review was conducted for all patients treated with this procedure at our institution between 2012 and 2023 was performed. Self-reported patient satisfaction with functional and esthetic outcomes was evaluated three months after surgery. Results: A total of thirty-six patients (forty-five eyelids) were included in the study, with a mean follow-up period of 22 months (range 3–144). Minor surgical revision was performed in one case for early wound dehiscence following premature stitches removal. The overall success rate was 93.2%, with one case of undercorrection and two cases of recurrence recorded at three years postoperatively. No additional complications or recurrences were observed during the follow-up period. Conclusions: The 3-step combined procedure demonstrated high efficacy and safety, offering excellent functional and esthetic outcomes. This approach provides a reliable solution for treating involutional ectropion, making it a valuable addition to the surgical options for this condition. Full article

Paranasal sinus surgery, a common treatment for chronic rhinosinusitis, requires exceptional precision due to the proximity of critical anatomical structures. To ensure accurate instrument control and clear visualization of the surgical site, surgeons utilize computer-aided surgical navigation (CSN). A key component of CSN is the registration process, which is traditionally reliant on manual or marker-based techniques. However, there is a growing shift toward marker-less registration methods. In previous work, we investigated a mesh-based registration approach using a Mixed Reality Head-Mounted Display (MR-HMD), specifically the Microsoft HoloLens 2. However, this method faced limitations, including depth holes and invalid values. These issues stemmed from the device’s low-resolution camera specifications and the 3D projection steps required to upscale RGB camera spaces. In this study, we propose a novel automated marker-less registration method leveraging Neural Radiance Field (NeRF) technology with an MR-HMD. To address insufficient depth information in the previous approach, we utilize rendered-depth images generated by the trained NeRF model. We evaluated our method against two other techniques, including prior mesh-based registration, using a facial phantom and three participants. The results demonstrate our proposed method achieves at least a 0.873 mm (12%) improvement in registration accuracy compared to others. Full article

Background: Aspergilloma disease is a fungal mass found in organs such as the sinuses and lungs, caused by the fungus Aspergillus. This disease occurs due to the accumulation of mucus, inflamed cells, and altered blood elements. Various surgical methods are used in clinical settings for the treatment of aspergilloma disease. Expert opinion is crucial for the diagnosis of the disease. Recent advancements in next-generation technologies have made them crucial for disease detection. Deep-learning models, which benefit from continuous technological advancements, are already integrated into current early diagnosis systems. Methods: This study is distinguished by the use of vision transformers (ViTs) rather than traditional deep-learning models. The data used in this study were obtained from patients treated at the Department of Thoracic Surgery at Fırat University. The dataset consists of two class types: aspergilloma disease images and non-aspergilloma disease images. The proposed approach consists of pre-processing, model training, feature extraction, efficient feature selection, feature fusion, and classification processes. In the pre-processing step, unnecessary regions of the images were cropped and data augmentation techniques were applied for model training. Three types of ViT models (vit_base_patch16, vit_large_patch16, and vit_base_resnet50) were used for model training. The feature sets obtained from training the models were merged, and the combined feature set was processed using feature selection methods (Chi2, mRMR, and Relief). Efficient features selected by these methods (Chi2 and mRMR, Chi2 and Relief, and mRMR and Relief) were combined in certain proportions to obtain more effective feature sets. Machine-learning methods were used in the classification process. Results: The most successful result in the detection of aspergilloma disease was achieved using Support Vector Machines (SVMs). The SVM method achieved a 99.70% overall accuracy with the cross-validation technique in classification. Conclusions: These results highlight the benefits of the suggested method for identifying aspergilloma. Full article

Background: Malnutrition affects patients undergoing surgery for gastrointestinal cancers and contributes to poor postoperative outcomes, including increased complication rates, longer hospital stays, and higher mortality. Despite the availability of several malnutrition screening tools and prognostic scores, their effectiveness in predicting postoperative outcomes remains unclear. This study aimed to compare the predictive accuracy of Patient-Generated Subjective Global Assessment (PG-SGA), Global Leadership Initiative on Malnutrition (GLIM), Geriatric Nutritional Risk Index (GNRI), and Controlling Nutritional Status (CONUT) score for postoperative outcomes in patients undergoing surgery for colorectal, hepato-pancreato-biliary and upper gastrointestinal cancers. Methods: A cross-sectional observational study from March 2022 to October 2023 was conducted in two university surgical departments, after registration on ClinicalTrials database (NCT05795374). Patient characteristics, preoperative nutritional status and postoperative outcomes were analyzed. Results: In total, 480 patients were enrolled. CONUT and GNRI demonstrated high specificity (over 90% and 80%, respectively) for predicting overall complications, major complications, prolonged hospital stay, mortality, and advanced disease stage across all cancer types. Notably, CONUT showed a specificity over 97% and GNRI over 89.7% for colorectal and upper gastrointestinal cancer patients, respectively, despite their lower sensitivity. On the contrary, PG-SGA and GLIM presented better sensitivity (up to 50%), but slightly lower specificity (up to 86.4%). Conclusions: CONUT and GNRI are valuable for ruling out non-at-risk patients for adverse postoperative outcomes, while PG-SGA and GLIM provide better sensitivity. A step-up approach—initial screening with PG-SGA and GLIM, followed by detailed evaluation with CONUT or GNRI— should be validated in future studies across diverse clinical settings. Full article

Detailed evaluation of prostate cancer glands is an essential yet labor-intensive step in grading prostate cancer. Gland segmentation can serve as a valuable preliminary step for machine-learning-based downstream tasks, such as Gleason grading, patient classification, cancer biomarker building, and survival analysis. Despite its importance, there is currently a lack of a reliable gland segmentation model for prostate cancer. Without accurate gland segmentation, researchers rely on cell-level or human-annotated regions of interest for pathomic and deep feature extraction. This approach is sub-optimal, as the extracted features are not explicitly tailored to gland information. Although foundational segmentation models have gained a lot of interest, we demonstrated the limitations of this approach. This work proposes a prostate gland segmentation framework that utilizes a dual-path Swin Transformer UNet structure and leverages Masked Image Modeling for large-scale self-supervised pretaining. A tumor-guided self-distillation step further fused the binary tumor labels of each patch to the encoder to ensure the encoders are suitable for the gland segmentation step. We united heterogeneous data sources for self-supervised training, including biopsy and surgical specimens, to reflect the diversity of benign and cancerous pathology features. We evaluated the segmentation performance on two publicly available prostate cancer datasets. We achieved state-of-the-art segmentation performance with a test mDice of 0.947 on the PANDA dataset and a test mDice of 0.664 on the SICAPv2 dataset. Full article

Background/Objectives: Surgical treatment of thoracic disc herniation (TDH) is risky and technically demanding due to its proximity to the spinal cord and the high possibility of the TDH being calcified (up to 40%), making the resection even more complex. Calcified TDH may be resected from an anterior via thoracotomy/thoracoscopy, lateral extra-cavitary, or a postero-lateral approach. Here, we present our experience in managing such pathology with an original technique Methods: This original technique, used successfully in more than 40 patients, is introduced, with a precise description of the surgical anatomy and the surgical steps to take. Indications for surgical management and neurological outcomes are also analyzed. This surgical approach consisted of transverso-pediculectomy, most often bilaterally, partial vertebral body drilling, 360° release of the cord, and short fixation. Results: A total of 44 patients were collected, with a mean age of 52.4 ± 11.7 years. Seven patients (15.9%) had complete calcifications, and thirty-one had partial calcifications (70.5%), while the remaining six did not have signs of calcifications. There were only 4 intraoperative complications (2 dural tears and 2 loss of evoked potentials). The TDH could be resected in total for 39 patients (88.6%) and partially, according to the “floating” technique, in 5 patients (11.4%). In the postoperative follow-up, all of the patients except two (presenting with sensory aggravation) reported an improvement in neurological conditions leading to an overall risk of neurological aggravation of 4.5%. Conclusions: The bilateral postero-lateral approach provides a large decompression of the cord (360°) and gives safe access to the TDH, even calcified, permitting high rates of total resection. It also prevents any prejudicial pressure on the spinal cord, reducing the risk of severe postoperative deficits and permitting optimal instrumentation (pedicle screw-based) of the spinal segment. The surgical sequence to resect the bony structures around the spinal cord is of great importance. Full article

Background: In patients treated with partial nephrectomy, prior evidence showed that peri-operative outcomes, such as complications and ischemia time, improved as a function of the surgical experience of the surgeon, but data on functional outcomes after surgery are still scarce. Methods: We retrospectively analyzed data of 4011 patients with a single, unilateral cT1a-b renal mass treated with laparoscopic or robot-assisted partial nephrectomy. The operations were performed by 119 surgeons at 22 participating institutions between 1997 and 2022. Multivariable models investigated the association between surgical experience (number of prior operations) and acute kidney injury (AKI) and recovery of at least 90% of baseline estimated glomerular filtration rate (eGFR) 1 yr after partial nephrectomy. The adjustment for case mix included age, Body Mass Index, preoperative serum creatinine, clinical T stage, PADUA score, warm ischemia time, pathologic tumor size, and year of surgery. Results: A total of 753 (19%) and 3258 (81%) patients underwent laparoscopic and robot-assisted partial nephrectomy, respectively. Overall, 37 (31%) and 55 (46%) surgeons contributed only to laparoscopic and robotic learning curves, respectively, whereas 27 (23%) contributed to the learning curves of both approaches. In the laparoscopic group, 8% and 55% of patients developed AKI and recovered at least 90% of their baseline eGFR, respectively. After adjusting for confounders, we did not find evidence of an association between surgical experience and AKI after laparoscopic partial nephrectomy (odds ratio [OR]: 0.9992; 95% confidence interval [CI]: 0.9963, 1.0022; p = 0.6). Similar results were found when 1-year renal function was the outcome of interest (OR: 0.9996; 95% CI: 0.9988, 1.0005; p = 0.5). Among patients who underwent robot-assisted partial nephrectomy, AKI occurred in 11% of patients, whereas 54% recovered at least 90% of their baseline eGFR. On multivariable analyses, the relationship between surgical experience and AKI after surgery was not statistically significant (OR: 1.0015; 95% CI: 0.9992, 1.0037; p = 0.2), with similar results when the outcome of interest was renal function one year after surgery (OR: 1.0001; 95% CI: 0.9980, 1.0022; p = 0.9). Virtually the same findings were found on sensitivity analyses. Conclusions: In patients treated with laparoscopic or robot-assisted partial nephrectomy, our data suggest that the surgical experience of the operating surgeon might not be a key determinant of functional recovery after surgery. This raises questions about the use of serum markers to assess functional recovery in patients with two kidneys and opens the discussion on what are the key steps of the procedure that allowed surgeons to achieve optimal outcomes since their initial cases. Full article

Background: Thymoma is a tumor that originates in the thymus gland, a part of the human body located behind the breastbone. It is a malignant disease that is rare in children but more common in adults and usually does not spread outside the thymus. The exact cause of thymic disease is not known, but it is thought to be more common in people infected with the EBV virus at an early age. Various surgical methods are used in clinical settings to treat thymoma. Expert opinion is very important in the diagnosis of the disease. Recently, next-generation technologies have become increasingly important in disease detection. Today’s early detection systems already use transformer models that are open to technological advances. Methods: What makes this study different is the use of transformer models instead of traditional deep learning models. The data used in this study were obtained from patients undergoing treatment at Fırat University, Department of Thoracic Surgery. The dataset consisted of two types of classes: thymoma disease images and non-thymoma disease images. The proposed approach consists of preprocessing, model training, feature extraction, feature set fusion between models, efficient feature selection, and classification. In the preprocessing step, unnecessary regions of the images were cropped, and the region of interest (ROI) technique was applied. Four types of transformer models (Deit3, Maxvit, Swin, and ViT) were used for model training. As a result of the training of the models, the feature sets obtained from the best three models were merged between the models (Deit3 and Swin, Deit3 and ViT, Deit3 and ViT, Swin and ViT, and Deit3 and Swin and ViT). The combined feature set of the model (Deit3 and ViT) that gave the best performance with fewer features was analyzed using the mRMR feature selection method. The SVM method was used in the classification process. Results: With the mRMR feature selection method, 100% overall accuracy was achieved with feature sets containing fewer features. The cross-validation technique was used to verify the overall accuracy of the proposed approach and 99.22% overall accuracy was achieved in the analysis with this technique. Conclusions: These findings emphasize the added value of the proposed approach in the detection of thymoma. Full article