Search Results (1,552)

Background/Objectives: Colorectal cancer (CRC) is a leading cause of cancer-related morbidity and mortality worldwide. This study evaluates the predictive value of Carcinoembryonic Antigen (CEA) in identifying CRC recurrence following surgical resection. Methods: This retrospective study was realized in the Oncology Institute in Cluj-Napoca and included 88 patients diagnosed with CRC. Clinical, demographic, and tumor-specific data were collected, including TNM staging, tumor histology. CEA levels were recorded before surgery. Receiver Operating Characteristic (ROC) analysis was performed to determine the diagnostic accuracy of CEA in predicting tumor relapse, and the sensitivity and specificity of various CEA cut-off values were assessed. Results: Most patients presented with advanced-stage tumors (T3/T4, 80.6%). CEA levels were significantly higher in patients with lymphatic and perineural invasion and in those with metastases (mean CEA: 45.0 ng/mL for M1 vs. 13.2 ng/mL for M0, p = 0.032). ROC analysis revealed an area under the curve (AUC) of 0.877 (95% CI: 0.763–0.949). A CEA cut-off value of 11.73 ng/mL yielded 100% sensitivity and 74.5% specificity for detecting recurrence; Conclusions: CEA is a valuable non-invasive biomarker for predicting CRC relapse, with high sensitivity and acceptable specificity. Regular CEA monitoring post-surgery can facilitate early detection of recurrence, improving prognosis. Full article

In surgical navigation-assisted pedicle screw fixation, cross-source pre- and intra-operative point clouds registration faces challenges like significant initial pose differences and low overlapping ratio. Classical algorithms based on feature descriptor have high computational complexity and are less robust to noise, leading to a decrease in accuracy and navigation performance. To address these problems, this paper proposes a coarse-to-fine registration framework. In the coarse registration stage, a Point Matching algorithm based on Curvature Feature Learning (CFL-PM) is proposed. Through CFL-PM and Farthest Point Sampling (FPS), the coarse registration of overlapping regions between the two point clouds is achieved. In the fine registration stage, the Iterative Closest Point (ICP) is used for further optimization. The proposed method effectively addresses the challenges of noise, initial pose and low overlapping ratio. In noise-free point cloud registration experiments, the average rotation and translation errors reached 0.34° and 0.27 mm. Under noisy conditions, the average rotation error of the coarse registration is 7.28°, and the average translation error is 9.08 mm. Experiments on pre- and intra-operative point cloud datasets demonstrate the proposed algorithm outperforms the compared algorithms in registration accuracy, speed, and robustness. Therefore, the proposed method can achieve the precise alignment of the surgical navigation-assisted pedicle screw fixation. Full article

Background/Objectives: This study aimed to evaluate the effectiveness of core needle biopsy (CNB) by comparing its diagnostic yield to fine needle aspiration cytology (FNAC) across primary and secondary examinations. Methods: This retrospective review analyzed medical records of patients who visited Soonchunhyang University Cheonan Hospital between January 2021 and August 2023 for thyroid nodule evaluation. Demographic data and the malignancy risk of thyroid nodules were collected based on the 2021 Korean Thyroid Imaging Reporting and Data System. FNAC and CNB results, classified using the Bethesda system for reporting thyroid cytopathology and diagnostic categories for thyroid CNB, were categorized as either “conclusive” or “inconclusive.” The rates of conclusive results in the primary examination and nodules transitioning from inconclusive to conclusive results during the secondary examination were analyzed. Finally, the diagnostic yields of FNAC and CNB were assessed using histopathological findings from surgically excised nodules. Results: The rate of nodules classified as “conclusive” was significantly higher in the CNB group than that in the FNAC group. Among nodules subjected to secondary examination, only the group with FNAC followed by CNB demonstrated a significant improvement in the rate of transition from inconclusive to conclusive results. Although FNAC and CNB showed comparable sensitivity and accuracy, the specificity of CNB was greater than that of FNAC. Conclusions: This study confirms the clinical utility of CNB by demonstrating its higher rate of conclusive results than FNAC. Future prospective studies, including cost–benefit analyses, are warranted to further define the indications for CNB. Full article

Background/Objectives: Postoperative complications such as wound infections and sepsis are common in diabetic patients, often resulting in longer hospital stays and higher morbidity. This study hypothesizes that a Random Forest Classifier can accurately predict these complications, enabling early clinical interventions. The model utilizes ensemble learning to integrate diverse patient data and improve predictive accuracy beyond traditional risk assessments. Methods: A comprehensive retrospective analysis was performed using data extracted from the National Surgical Quality Improvement Program (NSQIP) database. The dataset encompassed a wide array of variables, including demographic factors, clinical markers, and detailed surgical data (specialty, type of anesthesia, duration of surgery). Each variable was meticulously encoded into numerical formats, with categorical variables transformed through one-hot encoding, and continuous variables were normalized. The dataset was partitioned into training (80%) and testing (20%) subsets, ensuring a balanced representation of the target outcomes. The Random Forest Classifier was selected due to its robustness in handling high-dimensional data and its ability to model complex interactions between variables. Results: The Random Forest model showed accuracy rates of 94.38% for wound infection and 94.94% for sepsis. Precision and recall metrics also exceeded 94%, highlighting the model’s accuracy in identifying true positives and reducing false positives. ROC curve analysis yielded AUC values of 0.92 for wound infection and 0.95 for sepsis, indicating strong discriminative capability. Feature importance analysis further identified key predictors, including surgical duration, specific laboratory markers, and patient comorbidities. Conclusions: This study demonstrates the Random Forest Classifier’s strong predictive ability for postoperative wound infections and sepsis in diabetic patients. The model’s high-performance metrics indicate its potential for real-time risk stratification in clinical workflows. Future research should validate these findings in diverse populations and surgical settings. Incorporating this predictive model into clinical practice has the potential to significantly improve patient outcomes and reduce healthcare costs. Full article

Background: Deep infiltrating endometriosis (DIE) frequently affects the posterior pelvic compartment, where accurate non-invasive imaging is essential for diagnosis and surgical planning. Aim: This systematic review evaluates the diagnostic performance of transvaginal ultrasound (TVUS) in detecting posterior compartment DIE, specifically rectosigmoid lesions, uterosacral ligament involvement, and pouch of Douglas obliteration. Material and Methods: A comprehensive literature search of PubMed, Scopus, and Web of Science was performed for studies published between 2015 and 2025. Eligible studies assessed the accuracy of TVUS for posterior compartment DIE using laparoscopy and histology as reference standards. Data on sensitivity, specificity, and overall diagnostic accuracy were extracted or derived. The study’s quality was evaluated using the QUADAS-2 tool. Results: Thirty eligible studies were included. The mean sensitivities and specificities reported in the included studies reached 83.05% and 90.53% for rectosigmoid disease, 78.07% and 90.49% for uterosacral ligament involvement, and 79.58% and 89.75% for pouch of Douglas obliteration, respectively. Adjunctive techniques such as gel sonovaginography, rectal water contrast, or saline instillation into the pouch of Douglas were described, but their use was inconsistent. Marked heterogeneity in patient preparation, scanning protocols, and reporting limited comparability across studies. Despite this, TVUS demonstrated diagnostic performance within a similar range to that reported for MRI in prior systematic reviews, with the advantages of lower cost, accessibility, and integration into routine gynecological practice. Conclusions: TVUS is consistently reported as a reliable and cost-effective imaging modality and, in line with international guidelines, should be considered the first-line option for posterior compartment DIE, though further standardization of scanning and reporting protocols is needed to optimize reproducibility and clinical utility. Full article

Background/Objectives: In oral and maxillofacial surgery, apicoectomy is a standard procedure for treating persistent periapical infections after insufficient conservative treatment. Traditional techniques rely on direct visualization, while navigated methods offer advantages in precision and safety. This in vitro study compared conventional apicoectomy with dynamically guided navigation. The aim was to assess the feasibility, accuracy, and safety of dynamic navigation and to determine whether it reduces complication risks, improves surgical predictability, and minimizes bone loss. Methods: Ten experienced surgeons performed both techniques on custom-designed models. Operation time was assessed, as well as cavity volume, resected root length, incision width and height, and preservation of adjacent structures. Results: The navigated approach demonstrated significantly improved accuracy in root-end resection, with a reduction in access cavity volume (p < 0.001). No significant differences were found in operation time (p = 0.499), resection length (p = 0.054), or incision dimensions (p > 0.05). The risk of damaging adjacent structures was not significantly different between the two methods. Conclusions: Dynamic navigation for apicoectomy can offer an alternative in cases requiring high precision to conventional techniques. However, the routine clinical implementation of dynamic navigation remains limited due to the extensive preoperative planning required. The necessity for additional planning increases complexity, time, and cost. Full article

Background and Objectives: Primary vesicoureteral reflux (VUR) is a common pediatric urological disorder that can lead to significant renal morbidity if undetected or improperly managed. Ultrasound (US) plays a pivotal role in its assessment, providing a radiation-free tool to prenatal assessment, diagnosis, treatment, and long-term follow-up. This study aims to systematically review the literature on the use of US in pediatric primary VUR, emphasizing its applications in prenatal and postnatal diagnosis, intraoperative guidance, and follow-up monitoring. Methods: A systematic review of the literature was performed on PubMed in accordance with PRISMA guidelines. The research strategy used the following keywords: Ultrasound Vesicoureteral reflux, VUR Ultrasound, and VUR Sonography. A total of 2222 records were initially identified. After screening titles and abstracts for relevance, 2165 studies were excluded because they did not focus on ultrasound procedures, did not specify age limits, were redundant, involved non-homogeneous populations, or were unavailable in full text. Results: Prenatal US enables early identification of urinary tract anomalies suggestive of VUR, facilitating targeted postnatal evaluation. Postnatally, contrast-enhanced voiding ultrasound (CEVUS) offers a non-ionizing method for VUR confirmation or exclusion. Intraoperatively, US improves the accuracy and efficacy of bulking agent placement, potentially enhancing surgical outcomes. In follow-up, US remains essential for both conservatively managed and surgically treated patients, enabling timely detection of complications or recurrence. Conclusions: Ultrasound represents a useful tool in the management of pediatric primary VUR, applicable across all clinical stages, avoiding radiation exposure, and improving surgical effectiveness and follow-up management. Full article

Implant placement requires a digital workflow and the use of surgical guides. However, there is divergence in the angulation length of influence and precision. Therefore, a 3D assessment is also required. This insertion study aims to evaluate the accuracy in vitro by utilizing guided templates, deviation analysis, depth, and orientation over different lengths and angles. Methods and Materials: This study comprises a total of 180 implants placed in 90 resin-printed mandibular models, divided into nine groups (a 3 × 3 factorial design, n = 20/group). A reference model was created using Real GUIDE software (version 5.3), integrating a CBCT scanner (Carestream CS 9600, Medit Corp., Seoul, Republic of Korea) and an intraoral scanner (Medit i900) (Medit Corp., Seoul, Republic of Korea). Implant planning and surgical guide design were digitally executed and printed with Mazic resin (Vericom Co., Ltd., Chuncheon, Republic of Korea). Implants were placed using Oxy Implant PSK Line (Oxy Implant, Brescia, Italy) fixtures in mannequins. Postoperative CBCT scans were used to measure deviations in angular, vertical, and lateral dimensions using CS Imaging (v8.0.22) (Carestream Dental LLC, Atlanta, GA, USA). Statistical analysis was run by using SPSS v26. Results: The results demonstrated that implant angulation significantly impacted the precision of placement. Angulating escalation leads to intensive deviations, which are linear and angular calculations. On the one hand, the most significant deviations were observed at a 25° angulation, particularly in the buccal and lingual apex regions. On the other hand, 0° exhibited minimal deviations. Longer implants showed reduced angular deviations, whereas shorter implants (8.5 mm) exhibited higher vertical deviations, particularly at 0° of angulation. Moderate angulation (15°) with 11.5 mm implants provided the highest precision, while 0° angulation with 15 mm implants consistently exhibited the least deviation. These findings pinpoint the fundamental importance of angulation and implant length for exceptional placement accuracy. Conclusions: This study demonstrates the influence of placement accuracy with static guides on implant angulation and length. Moderate angulation, which is (15°), enhances accuracy, particularly within 11.5 mm implants. On the other hand, steeper angles (25°) and longer implants (15 mm) result in elevated deviations. Guidance formation and operator experience are also vital. Full article

Background: Robotic-assisted systems have transformed total knee arthroplasty (TKA), promising improved accuracy and intraoperative consistency, yet real-world data from non-academic centers remain limited. Objective: This study evaluates five-year clinical integration of a semi-autonomous, CT-based, robotic-arm-assisted TKA at a tertiary non-teaching hospital in Germany, focusing on planning accuracy, gap balancing, and intraoperative outcomes. Methods: We retrospectively analyzed all patients (n = 457) who underwent MAKO-assisted TKA from 2020 to 2025, performed by three orthopedic surgeons using a standardized subvastus approach. We assessed preoperative deformities, intraoperative alignment, implant sizing, and gap balancing. Surgical plans were adapted intraoperatively when indicated. Pre- vs. post-implantation values were compared using slopes to evaluate execution consistency. Results: Median patient age was 67.0 years (IQR: 60.0–75.0), with varus in 84.1% (7.0°, IQR: 4.0°–10.0°), valgus in 13.2% (3.0°, IQR: 1.5°–5.8°), and neutral alignment in 2.7%. Flexion contracture occurred in 80.4% (6.0°, IQR: 3.0–10.0%), hyperextension in 12.7% (2.0°, IQR: 1.5°–5.0°). Planning-to-execution consistency was high, even with plan adaptations. Slope values for alignment parameters were: tibial rotation in degrees (slope value: 1.0), femoral sagittal angle in degrees (0.8), tibial sagittal angle in degrees (0.9), coronal posterior condylar angle in degrees (0.9), femoral component size (1.0), tibial component size (1.0). Over 95% of cases showed ≤3.0° deviation between planned and final values. Bone resection concordance showed moderate agreement, with slopes from 0.8 (posterior medial femoral cut in mm) to 0.5 (lateral tibial cut in mm). Gap balancing improved at all stages, with reduced variability in medial/lateral extension and flexion gaps (all p < 0.05). Functional reconstruction showed significant improvements in extension, flexion, and deformities (all p < 0.001). Conclusions: Semi-autonomous, CT-based, robotic-arm-assisted TKA was successfully implemented in this non-academic setting, demonstrating acceptable intraoperative and functional reconstruction outcomes, supporting the feasibility of robotic-assisted surgery outside academic centers. Full article

Objectives: To predict the progression of knee osteoarthritis (OA), a deep convolutional neural network model was developed and applied to basic images and clinical data. Design: A vision transformer-based model was trained using 5565 knee radiographs as baseline images from the osteoarthritis initiative (OAI), including 578 testing images. Each knee had a corresponding Kellgren and Lawrence (KL) stage after 48 months of follow-up. Another 274 cases from the Far Eastern Memorial Hospital were used for external validation. The data included a combination of single/pairing images and full/essential clinical factors. Area under the receiver operating characteristics (AUROC), accuracy, sensitivity, specificity, odds ratio, and ability to discriminate surgical candidates were applied to evaluate model performance. Results: In cases with OA progression, the AUROC for identifying surgical candidates was 0.844, 0.804, 0.766, and 0.718 in the combination of a single image with essential factors, single image with full factors, pairing images with essential factors, and pairing images with full factors, respectively. In OAI testing using the simplest input, AUROC of identifying OA progression was 0.808, with 74.1% accuracy, 91.8% sensitivity, and 71% specificity. In external validation, AUROC of identifying OA progression was 0.709, with 71.2% accuracy, 72.2% sensitivity, and 70.3% specificity. Positive model prediction had an odds ratio of 23.87 (CI: 11.24~50.67) in OAI and 5.92 (CI: 3.50~10.03) in external validation. Conclusions: Our model provides reliable prediction results for knee OA cases with the advantages of simplicity and flexibility. The model performance was excellent in progression cases, potentially making early intervention in OA patients more efficient. Full article

Background: The majority of parotid gland tumors are benign, while malignant forms are uncommon, affecting fewer than 1 in 100,000 individuals. The main challenge resides in the histopathological complexity and the clinical overlap between benign and malignant parotid tumors, which frequently results in misdiagnosis. Aim: The objective of this research was to evaluate the clinical and histopathological characteristics of parotid gland tumors at a Romanian healthcare center. Materials and methods: A five-year retrospective study was conducted, with the inclusion criterion being the presence of complete clinical, pathological, and surgical records. Results: Of 156 patients included in the study, 67.3% were found to have benign lesions (male/female ratio 1.14:1), and there was a slight male predominance (53.3%). Partial parotidectomy was the most common surgical intervention for benign parotid tumors (59.6%), whereas total parotidectomy was predominantly indicated for malignant tumors, with facial nerve sacrifice occurring in 20% of cases to ensure complete tumor excision. Patients with benign tumors were found to be younger. Malignant tumors were commonly diagnosed at stage III (36.4%), indicative of more advanced disease at the time of diagnosis. Clinical diagnosis showed a high specificity of 96.9%, indicating high accuracy in malignancy suspicion, yet the sensitivity of 56% indicates that a significant number of malignancies were not detected during the initial evaluation. Tumor size was found to be influenced by gender and correlated with surgical methods, suggesting that patient characteristics and tumor biology may impact surgical strategy. Conclusions: This retrospective study highlights differences in gender, tumor size, and surgical approach between benign and malignant parotid gland tumors, offering valuable contributions in terms of diagnostic accuracy and treatment patterns despite a limited number of malignant cases. Full article

Background: This study aimed to develop and evaluate machine learning (ML) models to predict biochemical recurrence (BCR) after robot-assisted radical prostatectomy (RARP). Methods: We retrospectively analyzed clinical data from 1125 patients who underwent RARP between July 2013 and December 2023. The dataset was divided into a training set (70%) and a testing set (30%) using a stratified sampling strategy. Five ML models were developed using the training set. Model performance was evaluated on the testing set using the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity, and F1 scores. Additionally, model interpretability was assessed using SHapley Additive exPlanations (SHAP) values to determine the contribution of individual features. Results: Among the five ML models, the LightGBM model achieved the best prediction ability with an AUC of 0.881 (95%CI: 0.840–0.922) in the testing set. For model interpretability, SHAP values explained the contribution of individual features to the model, revealing that pathological T stage (pT), positive surgical margin (PSM), prostate-specific antigen (PSA) nadir, initial PSA, systematic prostate biopsy positive rate, seminal vesicle invasion (SVI), pathological International Society of Urological Pathology Grade Group (pGG), and perineural invasion (PI) were the key contributors to the predictive performance. Conclusions: We developed and validated ML models to predict BCR following RARP and identified that the LightGBM model with 8 variables achieved promising performance and demonstrated a high level of clinical applicability. Full article

Microbial forensics involves analyzing biological evidence to evaluate weaponized microorganisms or their toxins. This study aimed to detect and type Yersinia pestis from four simulated forensic samples—human plasma diluted in phosphate-buffered saline (#24-2), tomato juice (#24-5), grape juice (#24-8), and a surgical mask (#24-10). Notably, samples #24-10 may have contained live bacteria other than Y. pestis. A real-time polymerase chain reaction confirmed the presence of Y. pestis in all samples; however, whole-genome sequencing (WGS) coverage of the Y. pestis chromosome ranged from 0.46% to 97.1%, largely due to host DNA interference and low abundance. To address these limitations and enable strain-level identification, we designed a hybridization-based target enrichment approach focused on multilocus variable number tandem repeat analysis (MLVA). Next-generation sequencing (NGS) using whole-genome amplification revealed that the accuracy of the 25 MLVA profiles of Y. pestis for samples #24-2, #24-5, #24-8, and #24-10 was 4%, 100%, 52%, and 0%, respectively. However, all samples showed 100% accuracy with target-enriched NGS, confirming they all belong to the same strain. These findings demonstrate that a targeted enrichment strategy for MLVA loci can overcome common obstacles in microbial forensics, particularly when working with trace or degraded samples where conventional WGS proves challenging. Full article

Background: Acute appendicitis is the most common surgical emergency in children, yet timely and accurate diagnosis remains challenging due to nonspecific clinical presentations and limitations of imaging and blood tests. Saliva has emerged as a promising diagnostic medium because it is non-invasive, painless, inexpensive, and highly acceptable for pediatric patients. Salivary biomarkers may provide rapid and child-friendly adjuncts to existing diagnostic pathways. Methods: A systematic literature search was performed in Ovid/MEDLINE, Scopus, Web of Science, and the Cochrane Library to identify studies assessing salivary biomarkers in pediatric appendicitis. Eligible studies included children with suspected or confirmed appendicitis and evaluated the diagnostic accuracy of salivary markers compared to clinical, laboratory, or imaging standards. Results: To date, only three salivary biomarkers have been investigated. Leucine-rich α-2-glycoprotein 1 (LRG1) demonstrated high specificity of 100% but low sensitivity of 35–36%, with diagnostic accuracy ranging from AUC 0.77 to 0.85. C-reactive protein (CRP) showed excellent diagnostic performance with sensitivity of 91.3% and specificity of 95.4% (AUC 0.97), and strong correlation with serum CRP (ρ = 0.96). Irisin showed sensitivity of 90% and specificity of 60% with estimated AUC around 0.75, suggesting potential as an adjunct marker but limited as a standalone test. Conclusions: Salivary biomarkers in pediatric appendicitis are promising but remain underexplored, with evidence limited to small, single-center studies totalling fewer than 300 patients. Their advantages include feasibility, tolerability, and suitability for integration into point-of-care testing. Future research should focus on multicenter validation, development of multi-marker salivary panels, and application of biosensor technologies. With further evidence, salivary diagnostics could complement existing strategies and improve the accuracy and child-friendliness of appendicitis care. Full article

Background and Clinical Significance: Thoracic dorsal arachnoid web (DAW) is a rare intradural extramedullary condition characterized by a thin band of arachnoid tissue compressing the dorsal spinal cord. A hallmark imaging feature is the “scalpel sign”, which refers to anterior displacement of the thoracic spinal cord with dorsal cerebrospinal fluid (CSF) accumulation, producing a sagittal profile resembling a surgical scalpel. Although highly specific for DAW, this sign may also appear in other intradural conditions such as idiopathic ventral spinal cord herniation and arachnoid cysts. The clinical presentation is typically progressive and nonspecific, including lower limb weakness, sensory changes, gait disturbances, and, less frequently, sphincter dysfunction. Diagnosis is often delayed due to the subtle nature of the lesion and limited resolution of conventional Magnetic Resonance Imaging (MRI). High-resolution Three-Dimensional Constructive Interference in Steady State (3D-CISS) sequences improve diagnostic accuracy by highlighting indirect signs such as spinal cord deformation and dorsal CSF flow obstruction. Case Presentation: We report the case of a 57-year-old woman presenting with chronic cervico-dorsalgia, bilateral lower limb weakness, paresthesia, and progressive gait instability. Neurological examination revealed spastic paraparesis and hyperreflexia. Conventional MRI was inconclusive. However, sagittal T2-weighted and 3D-CISS sequences demonstrated the scalpel sign at the T4–T5 level, with anterior cord displacement and dorsal subarachnoid space enlargement. Surgical exploration confirmed the presence of a dorsal arachnoid web, which was resected. Postoperative follow-up showed clear improvement in motor function and gait. Conclusions: DAW should be considered in cases of unexplained thoracic myelopathy or cervico-dorsalgia with neurological signs. Early recognition of the scalpel sign using advanced MRI sequences is critical for timely diagnosis and surgical planning, which may lead to significant clinical improvement. Full article