Background: The use of ultrasound guidance during knee arthrocentesis has proven to increase operator confidence and accuracy, particularly in novice healthcare providers. Realistic and practical means of teaching this procedure to medical trainees are needed. This study is intended to assess the feasibility and efficacy of using formalin-embalmed human cadavers in the instruction of ultrasound-guided knee arthrocentesis to medical trainees. Methods: Twenty participants received a 30-minute didactic orientation detailing the principles of ultrasound-guided knee arthrocentesis, followed by a training practicum performed on human cadavers. The practicum included a 25-minute training period, followed by a 15-minute assessment period. Participants were objectively assessed on their ability to independently aspirate synovial fluid from the suprapatellar bursa using ultrasound guidance. Digital pretraining and posttraining questionnaires were administered to evaluate each participant’s confidence in their ability to independently locate the site of optimal needle placement and successfully aspirate synovial fluid with the guidance of ultrasound imaging. Results: An analysis via the Wilcoxon rank sum testing revealed that participant self-confidence increased significantly after training across all assessment items (p < 0.0001). Fifteen participants (75%) successfully aspirated 1 mL of synovial fluid on their first attempt, whereas 3 participants (15%) were successful on their second attempt. Two participants (10%) failed to perform a successful aspiration within the 15-minute time limit. The average time required to aspirate 1 mL of synovial fluid was 41 seconds. Conclusions: Ultrasound images of the formalin-embalmed suprapatellar bursa are of sufficient quality to use in the instruction of arthrocentesis to medical trainees. Brief instruction using formalin-embalmed cadaver models significantly increases trainee confidence and prepares first-year medical students to successfully and independently perform ultrasound-guided knee arthrocentesis.

ObjectivesTo determine if five commonly used prognostic indices (PIs) – recursive partitioning analysis (RPA), Score Index for Radiosurgery (SIR), Basic Score for Brain Metastases (BSBM), graded prognostic assessment (GPA), and the diagnosis-specific GPA – are valid following delay between diagnosis and treatment of brain metastases.MethodsIn a single-institutional cohort, records of patients who underwent stereotactic radiosurgery (SRS) more than 30 days from diagnosis of brain metastases were collected, and five PI scores were calculated for each patient. For each PI, three score-based groupings were made to examine survival differences by means of adjusted log-rank analysis and area under the curve (AUC).ResultsOf 121 patients with sufficient PI information, 72 underwent SRS more than 30 days after diagnosis. Median age and Karnofsky performance status were 60 years and 80, respectively. Forty-three (60%) patients had lung primaries. Prior to SRS, 38 (52.8%) and 12 (16.7%) patients underwent whole brain radiation therapy (WBRT) and surgery, respectively. Two (2.8%) patients underwent both WBRT and surgery prior to SRS. A median of two lesions were treated per SRS course. Median survival of the cohort was 9.0 months. Using adjusted log-rank analysis for pairwise comparison, BSBM and GPA showed significance between two out of the three prognostic groups, while the other scores showed either one or no significant differences on comparison. AUC demonstrated good applicability for BSBM, RPA, and GPA, although SIR was statistically less prognostic than the other PIs.ConclusionThe PIs analyzed in this study were applicable in the setting of delayed SRS. Although these data are hypothesis generating, they serve to encourage further analyses to validate a PI that is most optimal for these patients.

Purpose/Objective(s): Conventional MRI is no longer sufficient to accurately identify tumor presence considering the widely documented infiltrative nature of gliomas. Diffusion Weighted Imaging (DWI) has lent further interpretation to available imaging, but data on the optimal combination of DWI sequences to be employed remains elusive. Our intent was to use a convolutional neural network approach to machine learning employing DWI sequences (apparent diffusion coefficient (ADC), relative cerebral blood volume (rCBV)) to identify an imaging biomarker for GBM. Materials/Methods: Ten histologically documented GBM cases with available detailed operative reports and gross tumor present on DWI prior to the administration of radiation therapy were selected. T1 post-gad images were used to manually delineate tumor which were then coregistered with DWI series. These 10 manually delineated tumors were used to train a convolutional neural network classifier (CNN). In testing, the trained CNN is employed to assign each pixel in the image a probability of belonging to tumor. Receiver Operating Characteristic (ROC) analysis was performed on the probability map to determine optimum thresholds for tumor grading and to obtain the sensitivity, specificity, and positive and negative predictive values for identifying high-grade gliomas. Results: Backtesting of the 10 GBM cases used for machine training achieved almost 100% probability concordance with the T1-gad manually delineated tumors. The trained CNN was then tested on 5 GBM patient datasets with T1-gad, ADC, rCBV images. A sensitivity of 75% and a specificity of 80% with positive and negative predictive values of 79% and 76% respectively were achieved. Optimum threshold for tumor was 0.47. Conclusion: The convolutional neural network approach to DWI analysis may be very useful in identifying a high grade glioma imaging biomarker. Further training with patient data will further improve the accuracy of this approach, enabling its use for recurrence pattern analysis in setting of radiation therapy and systemic treatment, with possible future applicability in tumor grading as well as radiation treatment field design.Purpose/Objective(s): SRS is an important tool in treating brain metastases and has made modern treatment options more sophisticated. Some patients may benefit from radiosurgery at the initial diagnosis of brain metastasis while others may benefit from delayed SRS after the use of whole brain radiation (WBRT) or surgery. Prognostic scoring systems help select patients who will benefit from SRS by estimating their survival.However, because these indices were validated to estimate survival only at the time of initial diagnosis of brain metastases, it is unclear whether or not they remain prognostic when used months after the discovery of brain metastases. In this study, we assess these prognostic indices in patients evaluated for SRS delayed from their initial diagnosis. Materials/Methods: We reviewed all patients treated at our institution with SRS for brain metastases ...