Radiogenomic Associations Clear Cell Renal Cell Carcinoma: An Exploratory Study.

INTRODUCTION: This study investigates how quantitative texture analysis can be used to non-invasively identify novel radiogenomic correlations with clear cell renal cell carcinoma (ccRCC) biomarkers. METHODS: The Cancer Genome Atlas-Kidney Renal Clear Cell Carcinoma open-source database was used to identify 190 sets of patient genomic data that had corresponding multiphase contrast-enhanced CT images in The Cancer Imaging Archive. 2,824 radiomic features spanning fifteen texture families were extracted from CT images using a custom-built MATLAB software package. Robust radiomic features with strong inter-scanner reproducibility were selected. Random forest, AdaBoost, and elastic net machine learning (ML) algorithms evaluated the ability of the selected radiomic features to predict the presence of 12 clinically relevant molecular biomarkers identified from the literature. ML analysis was repeated with cases stratified by stage (I/II vs. III/IV) and grade (1/2 vs. 3/4). 10-fold cross validation was used to evaluate model performance. RESULTS: Before stratification by tumor grade and stage, radiomics predicted the presence of several biomarkers with weak discrimination (AUC 0.60-0.68). Once stratified, radiomics predicted KDM5C, SETD2, PBRM1, and mTOR mutation status with acceptable to excellent predictive discrimination (AUC ranges from 0.70 to 0.86). CONCLUSIONS: Radiomic texture analysis can potentially identify a variety of clinically relevant biomarkers in patients with ccRCC and may have a prognostic implication.

The impact of facility type and volume on treatment and overall survival in craniopharyngioma.

BACKGROUND: Craniopharyngiomas are uncommon benign sellar and parasellar tumors with high overall survival (OS) and recurrence rates. Treatment is often surgical but may include adjuvant therapies. The impact of adjuvant therapy and surgical approach have been evaluated, however, facility volume and type have not. The purpose of this study is to analyze the influence of facility volume and type on treatment modalities, extent of surgery and survival of craniopharyngioma. METHODS: The 2004-2016 National Cancer Database (NCDB) was queried for patients diagnosed with craniopharyngioma. Facilities were classified by type (academic vs. non-academic) and low-volume center (LVC) (Treating < 8 patients over the timeline) versus high-volume center (HVC), (Treating ≥ 8 patients over the timeline). Differences in treatment course, outcomes, and OS by facility type were assessed. RESULTS: 3730 patients (51.3% female) with mean age 41.2 ± 22.0 were included with a 5-year estimated OS of 94.8% (94.0-95.5%). 2564 (68.7%) patients were treated at HVC, of which 2142 (83.5%) were treated at academic facilities. Patients treated at HVC's were more likely to undergo both surgery and radiation. Surgical approach at HVC was more likely to be endoscopic. Patients treated at HVC demonstrated significantly higher 5-year OS compared to patients treated at LVC (96% [95% CI 95.6-97.1% versus 91.2% [95% CI 89-92.7%] with lower risk of mortality (Hazard ratio [95% CI] = 0.69 [0.56-0.84]). CONCLUSION: Treatment of craniopharyngioma at HVC compared to LVC is associated with improved OS, lower 30- and 90-day postoperative mortality risk, and more common use of both radiotherapy and endoscopic surgical approach.

CT-based radiomics stratification of tumor grade and TNM stage of clear cell renal cell carcinoma.

OBJECTIVES: To evaluate the utility of CT-based radiomics signatures in discriminating low-grade (grades 1-2) clear cell renal cell carcinomas (ccRCC) from high-grade (grades 3-4) and low TNM stage (stages I-II) ccRCC from high TNM stage (stages III-IV). METHODS: A total of 587 subjects (mean age 60.2 years ± 12.2; range 22-88.7 years) with ccRCC were included. A total of 255 tumors were high grade and 153 were high stage. For each subject, one dominant tumor was delineated as the region of interest (ROI). Our institutional radiomics pipeline was then used to extract 2824 radiomics features across 12 texture families from the manually segmented volumes of interest. Separate iterations of the machine learning models using all extracted features (full model) as well as only a subset of previously identified robust metrics (robust model) were developed. Variable of importance (VOI) analysis was performed using the out-of-bag Gini index to identify the top 10 radiomics metrics driving each classifier. Model performance was reported using area under the receiver operating curve (AUC). RESULTS: The highest AUC to distinguish between low- and high-grade ccRCC was 0.70 (95% CI 0.62-0.78) and the highest AUC to distinguish between low- and high-stage ccRCC was 0.80 (95% CI 0.74-0.86). Comparable AUCs of 0.73 (95% CI 0.65-0.8) and 0.77 (95% CI 0.7-0.84) were reported using the robust model for grade and stage classification, respectively. VOI analysis revealed the importance of neighborhood operation-based methods, including GLCM, GLDM, and GLRLM, in driving the performance of the robust models for both grade and stage classification. CONCLUSION: Post-validation, CT-based radiomics signatures may prove to be useful tools to assess ccRCC grade and stage and could potentially add to current prognostic models. Multiphase CT-based radiomics signatures have potential to serve as a non-invasive stratification schema for distinguishing between low- and high-grade as well as low- and high-stage ccRCC. KEY POINTS: • Radiomics signatures derived from clinical multiphase CT images were able to stratify low- from high-grade ccRCC, with an AUC of 0.70 (95% CI 0.62-0.78). • Radiomics signatures derived from multiphase CT images yielded discriminative power to stratify low from high TNM stage in ccRCC, with an AUC of 0.80 (95% CI 0.74-0.86). • Models created using only robust radiomics features achieved comparable AUCs of 0.73 (95% CI 0.65-0.80) and 0.77 (95% CI 0.70-0.84) to the model with all radiomics features in classifying ccRCC grade and stage, respectively.

Outcomes of Combined Antegrade-Retrograde Dilations for Radiation-Induced Esophageal Strictures in Head and Neck Cancer Patients.

The purpose of this study is to analyze outcomes of combined antegrade-retrograde dilations (CARD). This retrospective study was conducted on 14 patients with a history of head and neck cancer, treated with radiation therapy that was complicated by either complete or near-complete esophageal stenosis. All patients had minimal oral intake and depended on a gastrostomy tube for nutrition. Swallow function before and after CARD was assessed using the Functional Oral Intake Scale, originally developed for stroke patients and applied to head and neck cancer patients. Patients undergoing CARD demonstrated a quantifiable improvement in swallow function (p = 0.007) that persisted at last known follow-up (p = 0.015) but only a minority (23.1%) achieved oral intake sufficient to obviate the need for tube feeds. Complication rates were 24% per procedure or 36% per patient, almost all complications required procedural intervention, and all complications occurred in patients with complete stenosis. Our study suggests further caution when considering CARD, careful patient selection, and close post-operative monitoring.

Reliability of CT-based texture features: Phantom study.

OBJECTIVE: To determine the intra-, inter- and test-retest variability of CT-based texture analysis (CTTA) metrics. MATERIALS AND METHODS: In this study, we conducted a series of CT imaging experiments using a texture phantom to evaluate the performance of a CTTA panel on routine abdominal imaging protocols. The phantom comprises of three different regions with various textures found in tumors. The phantom was scanned on two CT scanners viz. the Philips Brilliance 64 CT and Toshiba Aquilion Prime 160 CT scanners. The intra-scanner variability of the CTTA metrics was evaluated across imaging parameters such as slice thickness, field of view, post-reconstruction filtering, tube voltage, and tube current. For each scanner and scanning parameter combination, we evaluated the performance of eight different types of texture quantification techniques on a predetermined region of interest (ROI) within the phantom image using 235 different texture metrics. We conducted the repeatability (test-retest) and robustness (intra-scanner) test on both the scanners and the reproducibility test was conducted by comparing the inter-scanner differences in the repeatability and robustness to identify reliable CTTA metrics. Reliable metrics are those metrics that are repeatable, reproducible and robust. RESULTS: As expected, the robustness, repeatability and reproducibility of CTTA metrics are variably sensitive to various scanner and scanning parameters. Entropy of Fast Fourier Transform-based texture metrics was overall most reliable across the two scanners and scanning conditions. Post-processing techniques that reduce image noise while preserving the underlying edges associated with true anatomy or pathology bring about significant differences in radiomic reliability compared to when they were not used. CONCLUSION: Following large-scale validation, identification of reliable CTTA metrics can aid in conducting large-scale multicenter CTTA analysis using sample sets acquired using different imaging protocols, scanners etc.

Optimization of an endovascular magnetic filter for maximized capture of magnetic nanoparticles.

To computationally optimize the design of an endovascular magnetic filtration device that binds iron oxide nanoparticles and to validate simulations with experimental results of prototype devices in physiologic flow testing. Three-dimensional computational models of different endovascular magnetic filter devices assessed magnetic particle capture. We simulated a series of cylindrical neodymium N52 magnets and capture of 1500 iron oxide nanoparticles infused in a simulated 14 mm-diameter vessel. Device parameters varied included: magnetization orientation (across the diameter, "D", along the length, "L", of the filter), magnet outer diameter (3, 4, 5 mm), magnet length (5, 10 mm), and spacing between magnets (1, 3 mm). Top designs were tested in vitro using 89Zr-radiolabeled iron oxide nanoparticles and gamma counting both in continuous and multiple pass flow model. Computationally, "D" magnetized devices had greater capture than "L" magnetized devices. Increasing outer diameter of magnets increased particle capture as follows: "D" designs, 3 mm: 12.8-13.6 %, 4 mm: 16.6-17.6 %, 5 mm: 21.8-24.6 %; "L" designs, 3 mm: 5.6-10 %, 4 mm: 9.4-15.8 %, 5 mm: 14.8-21.2 %. In vitro, while there was significant capture by all device designs, with most capturing 87-93 % within the first two minutes, compared to control non-magnetic devices, there was no significant difference in particle capture with the parameters varied. The computational study predicts that endovascular magnetic filters demonstrate maximum particle capture with "D" magnetization. In vitro flow testing demonstrated no difference in capture with varied parameters. Clinically, "D" magnetized devices would be most practical, sized as large as possible without causing intravascular flow obstruction.

In Vitro Capture of Small Ferrous Particles with a Magnetic Filtration Device Designed for Intravascular Use with Intraarterial Chemotherapy: Proof-of-Concept Study.

PURPOSE: To establish that a magnetic device designed for intravascular use can bind small iron particles in physiologic flow models. MATERIALS AND METHODS: Uncoated iron oxide particles 50-100 nm and 1-5 µm in size were tested in a water flow chamber over a period of 10 minutes without a magnet (ie, control) and with large and small prototype magnets. These same particles and 1-µm carboxylic acid-coated iron oxide beads were likewise tested in a serum flow chamber model without a magnet (ie, control) and with the small prototype magnet. RESULTS: Particles were successfully captured from solution. Particle concentrations in solution decreased in all experiments (P < .05 vs matched control runs). At 10 minutes, concentrations were 98% (50-100-nm particles in water with a large magnet), 97% (50-100-nm particles in water with a small magnet), 99% (1-5-µm particles in water with a large magnet), 99% (1-5-µm particles in water with a small magnet), 95% (50-100-nm particles in serum with a small magnet), 92% (1-5-µm particles in serum with a small magnet), and 75% (1-µm coated beads in serum with a small magnet) lower compared with matched control runs. CONCLUSIONS: This study demonstrates the concept of magnetic capture of small iron oxide particles in physiologic flow models by using a small wire-mounted magnetic filter designed for intravascular use.

Contrasting acute graft-versus-host disease effects of Tim-3/galectin-9 pathway blockade dependent upon the presence of donor regulatory T cells.

T-cell immunoglobulin mucin-3 (Tim-3) is expressed on pathogenic T cells, and its ligand galectin-9 (gal-9) is up-regulated in inflamed tissues. When Tim-3(+) T cells encounter high gal-9 levels, they are deleted. Tim-3 is up-regulated on activated T cells during GVHD. Inhibition of Tim-3/gal-9 binding by infusion of a Tim-3-Ig fusion protein or Tim-3(-/-) donor T cells increased T-cell proliferation and GVHD lethality. When the Tim-3/gal-9 pathway engagement was augmented using gal-9 transgenic recipients, GVHD lethality was slowed. Together, these data indicate a potential for modulating this pathway to reduce disease by increasing Tim-3 or gal-9 engagement. Paradoxically, when Tim-3/gal-9 was inhibited in the absence of donor T-regulatory cells (Tregs), GVHD was inhibited. GVHD reduction was associated with decreased colonic inflammatory cytokines as well as epithelial barrier destruction. CD25-depleted Tim-3(-/-) donor T cells underwent increased activation-induced cell death because of increased IFN-γ production. To our knowledge, these studies are the first to show that although the absence of Tim-3/gal-9 pathway interactions augments systemic GVHD, concurrent donor Treg depletion paradoxically and surprisingly inhibits GVHD. Thus, although donor Tregs typically inhibit GVHD, under some conditions, such Tregs actually may contribute to GVHD by reducing activation-induced T-cell death.

Prostate size, source configuration, and dosimetry dynamics of stranded 125I seed implants.

PURPOSE: To quantify changes in prostate size and seed movement over time after transperineal implantation of stranded 125I seeds, and to determine their impact on prostate dosimetry. METHODS: CT and MR (T2, balanced steady-state free precession) image triplets were acquired on days 0, 3, 10, and 30 for a cohort of 20 patients and registered automatically. Prostate contours were drawn on MR-T2 images; seeds were found and matched in successive CT images. Prostate volume and dimensions, seed movements, and prostate dose metrics V200, V150, V100 and D90 were calculated, and their dynamic behaviors quantified in an operationally defined prostate coordinate system. RESULTS: Cohort-averaged reductions in prostate A-P dimension (∼8%) and L-R dimension (∼5%) inferred from seed movements agreed with those obtained from contour measurements, whereas prostate volume and S-I dimension (implant direction) reductions inferred from seed movements were overestimated by about 30%. Average overall seed movement was 4.8 ± 3.0 mm, of which the only identifiable systematic component was resolution of prostate edema. Cohort-averaged ratios of prostate V200, V150, V100, and D90 on day 30 relative to day 0 were 1.67, 1.33, 1.02, and 1.08, respectively. CONCLUSIONS: Postimplant prostate size reduction in the SI (implant) direction cannot reliably be inferred from stranded seed movements. Apart from large-scale migration, residual seed movements relative to the prostate after accounting for edema resolution appear to be random. Prostate V100 and D90 changes 30 days post implant are modest, whereas those for V150 and V200 are substantial.

The Impact of Code Bundling on Medicare Volume and Reimbursements Within Endoscopic Sinus Surgery.

In 2018, Medicare introduced new codes to the Endoscopic Sinus Surgery (FESS) and balloon sinus dilation (BSD) families of Current Procedural Terminology (CPT) codes. Using the Medicare Part B National Summary Data File from 2010 to 2022, an interrupted time-series analysis examined trends in volume and reimbursements before and after 2018. Prior to 2018, volume and reimbursements for FESS grew at a mean rate of 2.5% ± 2.2% per year and 6.9% ± 6.6% per year, respectively, before reimbursements decreased significantly in 2018 by -13.9% (P = .014), leading to a stabilization of volume (growth of 0.72%, P = .602). Volume and reimbursements for BSD saw rapid growth from 2011 to 2015 which plateaued prior to the introduction of bundled codes and did not appear to change significantly in 2018 (-0.6%, P = .306 and 11.9%, P = .392, respectively). In addition to concurrent devaluation of FESS and BSD codes, bundling appears to have further contributed to falling reimbursements in rhinology.

Artificial intelligence and machine learning technologies in ulcerative colitis.

Interest in artificial intelligence (AI) applications for ulcerative colitis (UC) has grown tremendously in recent years. In the past 5 years, there have been over 80 studies focused on machine learning (ML) tools to address a wide range of clinical problems in UC, including diagnosis, prognosis, identification of new UC biomarkers, monitoring of disease activity, and prediction of complications. AI classifiers such as random forest, support vector machines, neural networks, and logistic regression models have been used to model UC clinical outcomes using molecular (transcriptomic) and clinical (electronic health record and laboratory) datasets with relatively high performance (accuracy, sensitivity, and specificity). Application of ML algorithms such as computer vision, guided image filtering, and convolutional neural networks have also been utilized to analyze large and high-dimensional imaging datasets such as endoscopic, histologic, and radiological images for UC diagnosis and prediction of complications (post-surgical complications, colorectal cancer). Incorporation of these ML tools to guide and optimize UC clinical practice is promising but will require large, high-quality validation studies that overcome the risk of bias as well as consider cost-effectiveness compared to standard of care.

Artificial intelligence in ulcerative colitis Ulcerative colitis (UC) is a chronic inflammatory disorder of the colon. The clinical care of patients with UC and research efforts to better understand the disease has inevitably produced a significant quantity of diverse and complex datasets ranging from electronic health records, laboratory values, images (endoscopy, radiology, histology) to gene expression. The size and complexity of datasets derived from UC poses a significant challenge to accurately and effectively predict clinically meaningful endpoints in order to ultimately improve UC outcomes. Artificial intelligence through the application of machine learning tools has the potential to improve the analysis of large, complex, high-dimensional datasets and reveal novel, deeper insights compared to traditional analytical tools. Here, we provide an updated and comprehensive summary of AI applications in UC.

Predictors of length of postoperative stay following endoscopic skull base surgery with intraoperative CSF leak.

OBJECTIVE: Establishing benchmarks for length of stay (LOS) may inform strategies to improve resource efficiency, decrease costs, and advance care quality. In this study, the authors characterize postoperative LOS in endoscopic skull base surgery (ESBS) and elucidate prolonging factors. METHODS: A retrospective chart review was conducted at a tertiary academic center including consecutive adult patients who underwent intradural ESBS with intraoperative CSF leak during primary repair between July 2018 and March 2024. LOS, calculated as the time between the end of anesthesia until discharge from the hospital, comprised the primary outcome. Categorical and continuous independent study variables were assessed for univariate LOS association via the Mann-Whitney U-test and Kendall's tau-b correlation, respectively, and those with significant associations were included as multiple linear regression inputs. RESULTS: One hundred sixty-three patients were included, with a median LOS of 4.0 (interquartile range [IQR] 2.8-5.8) days. LOS was significantly prolonged in high-flow (n = 82) compared with low-flow (n = 81) CSF leak cohorts (median 4.5 [IQR 3.9-6.5] vs 2.9 [IQR 2.1-4.7] days, p = 0.002). Defects involving the anterior cranial fossa (n = 16, median 4.6 [IQR 3.3-7.5)] days), suprasellar region (n = 94, median 4.4 [IQR 3.2-6.4] days), sella (n = 138, median 3.9 [IQR 2.8-5.8] days), or posterior cranial fossa (n = 17, median 4.5 [IQR 3.9-6.5] days) had variable LOSs. On multiple linear regression, after controlling for numerous patient, surgical, and postoperative factors, lesion diameter (B = 0.16, 95% CI 0.048-0.26), bone defect area (B = 0.008, 95% CI 0.001-0.014), anesthesia time (B = 0.015, 95% CI 0.004-0.026), bed rest length (B = 2.34, 95% CI 1.12-3.56), postoperative CSF leak (B = 11.06, 95% CI 4.11-18.01), postoperative meningitis (B = 11.79, 95% CI 4.83-18.74), postoperative stroke/hemorrhage (B = 25.25, 95% CI 18.43-32.06), and postoperative pneumonia (B = 5.59, 95% CI 0.79-10.38) independently predicted overall prolonged LOS. CONCLUSIONS: With healthcare utilization receiving increased attention, mitigating factors that extend LOS are important. Extent of surgery and certain postoperative complications may constitute key factors prolonging LOS following intradural ESBS with intraoperative CSF leak.

An evaluation of the Clarity 3D ultrasound system for prostate localization.

The purpose of this study is to evaluate the accuracy and precision of the Clarity 3D ultrasound system to track prostate gland positional variations due to setup error and organ motion. Seventeen patients (n = 17) undergoing radical external beam radiation therapy for localized prostate cancer were studied. Subsequent to initial reference ultrasound and planning CT scans, each patient underwent seven repeat weekly tracking CT and ultrasound (US) scans during the course of treatment. Variations in the location of the prostate between reference and tracking scans were measured. Differences reported by CT and ultrasound scans are compared. Ultrasound tracking was initially performed clinically by a group of trained general users. Retrospective prostate localization was then performed by a trained dedicated user upon the original raw data set and also a reduced data set derived from the original by an expert user from Resonant Medical. Correlation accuracy between ultrasound and CT shifts acquired and delineated by a pool of trained general users was deemed unacceptable for radiotherapy purposes. A mean discrepancy between CT and US localizations of greater than 10 mm, with a 5 mm or greater discrepancy rate of nearly 90%, was observed. Retrospective analysis by a dedicated user of both the original and Resonant Medical reduced data sets yielded mean CT-Us discrepancies of 8.7 mm and 7.4 mm, respectively. Unfortunately, the 5 mm or greater CT-US discord rate for these retrospective analyses failed to drop below 80%. The greatest disparity between CT and ultrasound was consistently observed in the superior-inferior direction, while greatest agreement was achieved in the lateral dimension. Despite an expert reanalysis of the original data, the Clarity ultrasound system failed to deliver an acceptable level of geometric accuracy required for modern radiotherapy purposes.

Pediatric chronic sinusitis: diagnosis and management.

PURPOSE OF REVIEW: Review the diagnosis and management of pediatric chronic sinusitis given recent advances in both surgical and medical management. RECENT FINDINGS: Balloon catheter dilation (BCD) of the sinuses has been used as an adjunct to adenoidectomy or in lieu of traditional endoscopic sinus surgery. BCD has been shown to be a safe technique in children although its efficacy compared to maxillary sinus irrigation or traditional sinus surgery cannot be determined based on current studies. SUMMARY: New advances in BCD and biologics may serve as useful adjuncts in surgical and medical therapy respectively with additional research needed to better delineate the optimal indications for each in the treatment continuum.

Association Between Insurance Type and Outcomes of Reconstructive Head and Neck Cancer Surgery.

OBJECTIVES/HYPOTHESIS: Although the benefits of expanding health insurance coverage are clear, there are limited studies comparing the different types of insurance. This study aims to determine the association between insurance type and outcomes in patients with head and neck cancer undergoing reconstructive surgery in the United States. METHODS: Population-based cross-sectional study of the 2012-2014 National Inpatient Sample. We identified 1,314 patients with head and neck cancers undergoing tumor ablative surgery followed by pedicled or free flap reconstruction of oncologic defects. Insurance type was classified as private, Medicare, Medicaid, self-pay, or other. The primary outcome was extended length of stay (LOS), defined as greater than 14 days, which represented the 75th percentile of the study sample. Secondary outcomes included acute medical complications, surgical complications, morbidities, and costs. Analyses were adjusted for gender, geographic location, and various medical comorbidities. RESULTS: In univariate analysis, insurance type was associated with extended LOS (P = .001), medical complications (P = <.001), and mortalities (P = .020). After controlling for other covariates in the multivariate analysis, compared to private insurance, Medicare and Medicaid were both associated with significantly higher odds of extended LOS (adjusted odds ratio [OR] [95% confidence interval (CI)] = 1.73 [1.09-2.76] and 2.22 [1.38-3.58], respectively). Medicare was associated with significantly higher odds of medical complications, but Medicaid was not (adjusted OR [95% CI] = 1.53 [1.02-2.31] and 1.64 [0.97-2.78], respectively). CONCLUSIONS: Medicaid and Medicare were independently associated with extended LOS after reconstructive head and neck cancer surgery. Medicare was associated with higher rates of medical complications. Efforts to address LOS should target care planning and coordination. LEVEL OF EVIDENCE: NA Laryngoscope, 132:1946-1952, 2022.

Geographic Distribution of Otolaryngology Advance Practice Providers and Physicians.

OBJECTIVES: Advanced practice providers (APPs), namely physician assistants (PAs) and nurse practitioners (NPs), play an increasing role in meeting growing demands for otolaryngologic services, particularly in rural communities. This study analyzes the geographic distribution of otolaryngology providers, which is essential to addressing future demands. STUDY DESIGN: Cross-sectional study. SETTING: Medicare Provider Utilization and Payment Data for 2017. METHODS: Current Procedural Terminology codes were used to identify APPs providing 10 common otolaryngologic services. Geographic distribution was evaluated by calculating densities of APPs and otolaryngologists per 100,000 persons in urban versus rural counties as defined by the National Center for Health Statistics Urban-Rural Classification Scheme. RESULTS: We identified cohorts of 8573 otolaryngologists, 1148 NPs, and 895 PAs. There were significantly higher population-controlled densities of otolaryngologists and APPs in urban counties as compared with rural counties. The majority of otolaryngologists (92.1%) and APPs (83.3%) were in urban counties. However, the proportion of APPs (16.7%) in rural counties was significantly higher than the proportion of otolaryngologists (7.9%) in rural counties (P < .01). A significant majority of rural counties (72.2%) had zero identified providers, and a greater proportion of rural counties (5.0%) were served exclusively by APPs as compared with urban counties (3.2%). CONCLUSIONS: Although otolaryngologists and APPs mostly practiced in urban counties, a relatively higher proportion of APPs practiced in rural counties when compared with otolaryngology physicians. The majority of rural counties did not have any otolaryngologic providers. Given the expected shortages of otolaryngology physicians, APPs may play a critical role in addressing these gaps in access.

Retained Dental Implant in the Maxillary Sinus.

Implant dentistry has become a popularized means of replacing damaged or missing teeth. Although it has become common practice, there are accounts of implants displacing into surrounding structures, commonly the maxillary sinus. We present the case of a 54-year-old man who presented with chronic left sided pain and pressure found to be secondary to a displaced implant obstructing the left maxillary outflow sinus tract. A systematic review was conducted to assess the current management and treatment options for dental implants displaced into the maxillary sinus. Functional endoscopic sinus surgery (FESS) and the lateral window approach were both found to be safe techniques with minimal postoperative complications.

The challenges facing deep learning-based catheter localization for ultrasound guided high-dose-rate prostate brachytherapy.

BACKGROUND: Automated catheter localization for ultrasound guided high-dose-rate prostate brachytherapy faces challenges relating to imaging noise and artifacts. To date, catheter reconstruction during the clinical procedure is performed manually. Deep learning has been successfully applied to a wide variety of complex tasks and has the potential to tackle the unique challenges associated with multiple catheter localization on ultrasound. Such a task is well suited for automation, with the potential to improve productivity and reliability. PURPOSE: We developed a deep learning model for automated catheter reconstruction and investigated potential factors influencing model performance. The model was designed to integrate into a clinical workflow, with a proposed reconstruction confidence metric to aid in planner verification. METHODS: Datasets from 242 patients treated from 2016 to 2020 were collected retrospectively. The anonymized dataset comprises 31,000 transverse images reconstructed from 3D sagittal ultrasound acquisitions and 3500 implanted catheters manually localized by the planner. Each catheter was retrospectively ranked based on the severity of imaging artifacts affecting reconstruction difficulty. The U-NET deep learning architecture was trained to localize implanted catheters on transverse images. A fivefold cross-validation method was used, allowing for evaluation over the entire dataset. The postprocessing software combined the predictions with patient-specific implant information to reconstructed catheters in 3D space, uniquely matched to the implanted grid positions. A reconstruction confidence metric was calculated based on the number and probability of localized predictions per catheter. For each patient, deep learning prediction and postprocessing reconstruction were completed in under 2 min on a nonperformance PC. RESULTS: Overall, 80% of catheter reconstructions were accurate, within 2 mm along 90% of the length. The catheter tip was often not detected and required extrapolation during reconstruction. The reconstruction accuracy was 89% for the easiest catheter ranking and decreased to 13% for the highest difficulty ranking, when the aid of live ultrasound would have been recommended. Even when limited to the easiest ranked catheters, the reconstruction accuracy decreased at distal grid positions, down to 50%. Individual implantation style was found to influence the frequency of severe artifacts, slightly impacting the model accuracy. A reconstruction confidence metric identified the difficult catheters, removed the observed individual variation, and increased the overall accuracy to 91% while excluding 27% of the reconstructions. CONCLUSIONS: The deep learning model localized implanted catheters over a large clinical dataset, with overall promising results. The model faced challenges due to ultrasound artifacts and image degradation distal to the probe, underlining the continued importance of maintaining image quality and minimizing artifacts. A potential workflow for integration into the clinical procedure was demonstrated, including the use of a confidence metric to predict low accuracy reconstructions. Comparison between models evaluated on different datasets should also consider underlying differences, such as the frequency and severity of imaging artifacts.

Vector of motion measurements in the living cochlea using a 3D OCT vibrometry system.

Optical coherence tomography (OCT) has become an important tool for measuring the vibratory response of the living cochlea. It stands alone in its capacity to measure the intricate motion of the hearing organ through the surrounding otic capsule bone. Nevertheless, as an extension of phase-sensitive OCT, it is only capable of measuring motion along the optical axis. Hence, measurements are 1-D. To overcome this limitation and provide a measure of the 3-D vector of motion in the cochlea, we developed an OCT system with three sample arms in a single interferometer. Taking advantage of the long coherence length of our swept laser, we depth (frequency) encode the three channels. An algorithm to depth decode and coregister the three channels is followed by a coordinate transformation that takes the vibrational data from the experimental coordinate system to Cartesian or spherical polar coordinates. The system was validated using a piezo as a known vibrating element that could be positioned at various angles. The angular measurement on the piezo was shown to have an RMSE of ≤ 0.30° (5.2 mrad) with a standard deviation of the amplitude of ≤ 120 pm. Finally, we demonstrate the system for in vivo imaging by measuring the vector of motion over a volume image in the apex of the mouse cochlea.

Feasibility of using CT radiomic signatures for predicting CD8-T cell infiltration and PD-L1 expression in renal cell carcinoma.

Objectives: To identify computed tomography (CT)-based radiomic signatures of cluster of differentiation 8 (CD8)-T cell infiltration and programmed cell death ligand 1 (PD-L1) expression levels in patients with clear-cell renal cell carcinoma (ccRCC). Methods: Seventy-eight patients with pathologically confirmed localized ccRCC, preoperative multiphase CT and tumor resection specimens were enrolled in this retrospective study. Regions of interest (ROI) of the ccRCC volume were manually segmented from the CT images and processed using a radiomics panel comprising of 1708 metrics. The extracted metrics were used as inputs to three machine learning classifiers: Random Forest, AdaBoost, and ElasticNet to create radiomic signatures for CD8-T cell infiltration and PD-L1 expression, respectively. Results: Using a cut-off of 80 lymphocytes per high power field, 59 % were classified to CD8 highly infiltrated tumors and 41 % were CD8 non highly infiltrated tumors, respectively. An ElasticNet classifier discriminated between these two groups of CD8-T cells with an AUC of 0.68 (95 % CI, 0.55-0.80). In addition, based on tumor proportion score with a cut-off of > 1 % tumor cells expressing PD-L1, 76 % were PD-L1 positive and 24 % were PD-L1 negative. An Adaboost classifier discriminated between PD-L1 positive and PD-L1 negative tumors with an AUC of 0.8 95 % CI: (0.66, 0.95). 3D radiomics metrics of graylevel co-occurrence matrix (GLCM) and graylevel run-length matrix (GLRLM) metrics drove the performance for CD8-Tcell and PD-L1 classification, respectively. Conclusions: CT-radiomic signatures can differentiate tumors with high CD8-T cell infiltration with moderate accuracy and positive PD-L1 expression with good accuracy in ccRCC.