Recent Advancements in Prostate Catheters and Stents for Management of Benign Prostatic Hyperplasia.

PURPOSE OF REVIEW: The prevalence of benign prostatic hyperplasia (BPH) is rising, however, current treatment options present severe complications and limit patient's quality of life. Accordingly, advancements in prostatic catheter and stent designs for use in treating lower urinary tract symptoms (LUTS) in BPH patients have largely expanded in the past five years and we aim to provide an exhaustive summary of recent outcomes. RECENT FINDINGS: The dual dilation and paxlitaxel eluting Optilume BPH Catheter System enhances promise in catheter-based treatments, providing the longest sustained increase in max urinary flow rate and decrease in post-void residual volume compared to alternative MISTs. Additionally, use of iTiND, along with recent advancements in temporary (EXIME, Prodeon Urocross) and permanent (Zenflow Spring, Butterfly, and ClearRing) stent designs, have demonstrated rapid, lasting, and low-cost LUTS relief with sustained sexual function. Minimally invasive solutions that offer in-office treatment, rapid symptom relief, shorter recovery times, and preservation of sexual function hold great promise in improving outcomes in managing BPH patients with LUTS.

AI for BPH Surgical Decision-Making: Cost Effectiveness and Outcomes.

PURPOSE OF REVIEW: Benign prostatic hyperplasia (BPH) is prevalent in nearly 70% of men over the age of 60, leading to significant clinical challenges due to varying symptom presentations and treatment responses. The decision to undergo surgical intervention is not straightforward; the American Urological Association recommends consideration of surgical treatment after inadequate or failed response to medical therapy. This review explores the role of artificial intelligence (AI), including machine learning and deep learning models, in enhancing the decision-making processes for BPH management. RECENT FINDINGS: AI applications in this space include analysis of non-invasive imaging modalities, such as multiparametric Magnetic Resonance Imaging (MRI) and Ultrasound, which enhance diagnostic precision. AI models also concatenate serum biomarkers and histopathological analysis to distinguish BPH from prostate cancer (PC), offering high accuracy rates. Furthermore, AI aids in predicting patient outcomes post-treatment, supporting personalized medicine, and optimizing therapeutic strategies. AI has demonstrated potential in differentiating BPH from PC through advanced imaging and predictive models, improving diagnostic accuracy, and reducing the need for invasive procedures. Despite promising advancements, challenges remain in integrating AI into clinical workflows, establishing standard evaluation metrics, and achieving cost-effectiveness. Here, we underscore the potential of AI to improve patient outcomes, streamline BPH management, and reduce healthcare costs, especially with continued research and development in this transformative field.

Increasing pitch count is associated with increasing elbow flexion angle at ball release in youth baseball pitchers.

BACKGROUND: Baseball is one of the most popular sports among youth athletes in the United States, and among these players, pitchers are at a particularly high risk of sustaining an injury. Overuse of the arm from repetitive pitching is a common mechanism for injury. Despite the attention that overuse injury has received, little is known regarding the mechanism that leads to elbow injury. This study aims to determine the effect of increasing pitch count on elbow flexion at ball release in a youth pitching cohort. The authors hypothesize that elbow flexion would increase as pitch count increases. METHODS: Study subjects included volunteers from youth baseball players from local teams and public advertisements. Retroreflective markers attached to bony landmarks were placed on the players according to International Shoulder Group recommendations. Pitchers threw an indoor simulated game. Three-dimensional marker trajectories were collected using a 12-camera optical motion capture system, and ball velocity was captured using a radar gun. Voluntary maximal isometric strength of the internal and external rotators was evaluated before and after pitching. Paired 2-tailed t tests were performed to determine if a significant change occurred between the fresh and fatigued sets. RESULTS: Twelve adolescent male pitchers were recruited. Eleven of 12 pitchers completed the prescribed 6 sets of 15 pitches, culminating in a 90-pitch simulated game. The ball speed in the second set was found to be the highest in all pitchers and was considered the "peak set" (P = .021), whereas ball speed was the slowest in the sixth set of pitches and was therefore considered the "fatigue set" (P = .001). There was a moderate but statistically significant inverse correlation between elbow flexion at ball release and maximum internal rotation velocity (P = .005). Elbow flexion at ball release was also significantly positively correlated with shoulder abduction at ball release (P = .004). Elbow flexion at ball release was not significantly correlated with ball velocity (P = .108). CONCLUSIONS: In a simulated game laboratory setting, increasing pitch count was associated with increasing elbow flexion angle at ball release in youth baseball pitchers. These findings demonstrate that pitching with fatigue may cause biomechanical changes that have been associated with increased rates of elbow injury in the adult throwing population. Further investigation on the association between elbow flexion angle and elbow injury in the youth baseball population is needed.

An additively manufactured model for preclinical testing of cervical devices.

Purpose: Composite models have become commonplace for the assessment of fixation and stability of total joint replacements; however, there are no comparable models for the cervical spine to evaluate fixation. The goal of this study was to create the framework for a tunable non-homogeneous model of cervical vertebral body by identifying the relationships between strength, in-fill density, and lattice structure and creating a final architectural framework for specific strengths to be applied to the model. Methods: The range of material properties for cervical spine were identified from literature. Using additive manufacturing software, rectangular prints with three lattice structures, gyroid, triangle, zig-zag, and a range of in-fill densities were 3D-printed. The compressive and shear strengths for all combinations were calculated in the axial and coronal planes. Eleven unique vertebral regions were selected to represent the distribution of density. Each bone density was converted to strength and subsequently correlated to the lattice structure and in-fill density with the desired material properties. Finally, a complete cervical vertebra model was 3D-printed to ensure sufficient print quality. Results: Materials testing identified a relationship between in-fill densities and strength for all lattice structures. The axial compressive strength of the gyroid specimens ranged from 1.5 MPa at 10% infill to 31.3 MPa at 100% infill and the triangle structure ranged from 2.7 MPa at 10% infill to 58.4 MPa at 100% infill. Based on these results, a cervical vertebra model was created utilizing cervical cancellous strength values and the corresponding in-fill density and lattice structure combination. This model was then printed with 11 different in-fill densities ranging from 33% gyroid to 84% triangle to ensure successful integration of the non-homogeneous in-fill densities and lattice structures. Conclusions: The findings from this study introduced a framework for using additive manufacturing to create a tunable, customizable biomimetic model of a cervical vertebra.