Persistent Inequities in Intravenous Thrombolysis for Acute Ischemic Stroke in the United States: Results From the Nationwide Inpatient Sample

BACKGROUND

Despite its approval for acute ischemic stroke >25 years ago, intravenous thrombolysis (IVT) remains underused, with inequities by age, sex, race, ethnicity, and geography. Little is known about IVT rates by insurance status.

METHODS AND RESULTS

We assessed temporal trends from 2002 to 2015 in IVT for acute ischemic stroke in the Nationwide Inpatient Sample using adjusted, survey-weighted logistic regression. We calculated odds ratios for IVT for each category in 2002 to 2008 (period 1) and 2009 to 2015 (period 2). IVT use for acute ischemic stroke increased from 1.0% in 2002 to 6.8% in 2015 (adjusted annual relative ratio, 1.15). Individuals aged ≥85 years had the most pronounced increase during 2002 to 2015 (adjusted annual relative ratio, 1.18) but were less likely to receive IVT compared with 18- to 44-year-olds in period 1 (adjusted odds ratio [aOR], 0.23) and period 2 (aOR, 0.36). Women were less likely than men to receive IVT, but the disparity narrowed over time (period 1: aOR, 0.81; period 2: aOR, 0.94). Inequities in IVT resolved for Hispanic individuals in period 2 (aOR, 0.96) but not for Black individuals (period 2: aOR, 0.81). The disparity in IVT for Medicare patients, compared with privately insured patients, lessened over time (period 1: aOR, 0.59; period 2: aOR, 0.75). Patients treated in rural hospitals remained less likely to receive IVT than in urban hospitals; a more dramatic increase in urbanity widened the inequity (period 2, urban nonteaching versus rural: aOR, 2.58, period 2, urban teaching versus rural: aOR, 3.90).

CONCLUSIONS

IVT for acute ischemic stroke increased among adults. Despite some encouraging trends, the remaining disparities highlight the need for intensified efforts at addressing inequities.

An Objective Computer-Assisted Measurement of Sonographic Renal Cortical Echogenicity: The Splenorenal Index

ABSTRACT

Renal cortical echogenicity represents a marker of renal function. However, evaluation of the renal echotexture is subjective and thus disposed to error and interrater variability. Computer-aided image analysis may be used to objectively assess renal cortical echogenicity by comparing the echogenicity of the left kidney to that of the spleen; the resultant ratio is referred to as the splenorenal index (SRI). We performed a retrospective review of all adult patients who received a renal ultrasound over a 45-day period at our institution. Demographic data and kidney function laboratory values were documented for each patient. Regions of interest (ROIs) were selected in the left renal cortex and spleen using ImageJ software. The SRI was calculated as a ratio of the mean pixel brightness of the left kidney cortex ROI to the mean pixel brightness of the spleen ROI. The SRI was then correlated with serum creatinine, blood urea nitrogen, and estimated glomerular filtration rate. We found that among the 94 patients included in the study, the SRI had a significant positive correlation with serum creatinine ( r = 0.43, P < 0.001) and serum blood urea nitrogen ( r = 0.45, P < 0.001) and negative correlation with estimated glomerular filtration rate ( r = -0.47, P < 0.001). Our data indicate that SRI may serve as a valuable tool for sonographic evaluation of renal parenchymal disease.

Competency in Robotic Surgery: Standard Setting for Robotic Suturing Using Objective Assessment and Expert Evaluation

OBJECTIVE

Surgical skill assessment tools such as the End-to-End Assessment of Suturing Expertise (EASE) can differentiate a surgeon's experience level. In this simulation-based study, we define a competency benchmark for intraoperative robotic suturing using EASE as a validated measure of performance.

DESIGN

Participants conducted a dry-lab vesicourethral anastomosis (VUA) exercise. Videos were each independently scored by 2 trained, blinded reviewers using EASE. Inter-rater reliability was measured with prevalence-adjusted bias-adjusted Kappa (PABAK) using 2 example videos. All videos were reviewed by an expert surgeon, who determined if the suturing skills exhibited were at a competency level expected for residency graduation (pass or fail). The Contrasting Group (CG) method was then used to set a pass/fail score at the intercept of the pass and fail cohorts' EASE score distributions.

SETTING

Keck School of Medicine, University of Southern California.

PARTICIPANTS

Twenty-six participants: 8 medical students, 8 junior residents (PGY 1-2), 7 senior residents (PGY 3-5) and 3 attending urologists.

RESULTS

After 1 round of consensus-building, average PABAK across EASE subskills was 0.90 (Range 0.67-1.0). The CG method produced a competency benchmark EASE score of >35/39, with a pass rate of 10/26 (38%); 27% were deemed competent by expert evaluation. False positives and negatives were defined as medical students who passed and attendings who failed the assessment, respectively. This pass/fail score produced no false positives or negatives, and fewer JR than SR were considered competent by both the expert and CG benchmark.

CONCLUSIONS

Using an absolute standard setting method, competency scores were set to identify trainees who could competently execute a standardized dry-lab robotic suturing exercise. This standard can be used for high stakes decisions regarding a trainee's technical readiness for independent practice. Future work includes validation of this standard in the clinical environment through correlation with clinical outcomes.

Artificial Intelligence-Based Video Feedback to Improve Novice Performance on Robotic Suturing Skills: A Pilot Study

Introduction: Automated skills assessment can provide surgical trainees with objective, personalized feedback during training. Here, we measure the efficacy of artificial intelligence (AI)-based feedback on a robotic suturing task. Materials and Methods: Forty-two participants with no robotic surgical experience were randomized to a control or feedback group and video-recorded while completing two rounds (R1 and R2) of suturing tasks on a da Vinci surgical robot. Participants were assessed on needle handling and needle driving, and feedback was provided via a visual interface after R1. For feedback group, participants were informed of their AI-based skill assessment and presented with specific video clips from R1. For control group, participants were presented with randomly selected video clips from R1 as a placebo. Participants from each group were further labeled as underperformers or innate-performers based on a median split of their technical skill scores from R1. Results: Demographic features were similar between the control (n = 20) and feedback group (n = 22) (p > 0.05). Observing the improvement from R1 to R2, the feedback group had a significantly larger improvement in needle handling score (0.30 vs -0.02, p = 0.018) when compared with the control group, although the improvement of needle driving score was not significant when compared with the control group (0.17 vs -0.40, p = 0.074). All innate-performers exhibited similar improvements across rounds, regardless of feedback (p > 0.05). In contrast, underperformers in the feedback group improved more than the control group in needle handling (p = 0.02). Conclusion: AI-based feedback facilitates surgical trainees' acquisition of robotic technical skills, especially underperformers. Future research will extend AI-based feedback to additional suturing skills, surgical tasks, and experience groups.

Age-Related Decline in BBB Function is More Pronounced in Males than Females

The blood-brain barrier (BBB) plays a pivotal role in protecting the central nervous system (CNS), shielding it from potential harmful entities. A natural decline of BBB function with aging has been reported in both animal and human studies, which may contribute to cognitive decline and neurodegenerative disorders. Limited data also suggest that being female may be associated with protective effects on BBB function. Here we investigated age and sex-dependent trajectories of perfusion and BBB water exchange rate (kw) across the lifespan in 186 cognitively normal participants spanning the ages of 8 to 92 years old, using a novel non-invasive diffusion prepared pseudo-continuous arterial spin labeling (DP-pCASL) MRI technique. We found that the pattern of BBB kw decline with aging varies across brain regions. Moreover, results from our novel DP-pCASL technique revealed a remarkable decline in BBB kw beginning in the early 60s, which was more pronounced in males. In addition, we observed sex differences in parietotemporal and hippocampal regions. Our findings provide in vivo results demonstrating sex differences in the decline of BBB function with aging, which may serve as a foundation for future investigations into perfusion and BBB function in neurodegenerative and other brain disorders.

A Multi-institution Study on the Association of Virtual Reality Skills with Continence Recovery after Robot-assisted Radical Prostatectomy

BACKGROUND

Virtual reality (VR) simulators are increasingly being used for surgical skills training. It is unclear what skills are best improved via VR, translate to live surgical skills, and influence patient outcomes.

OBJECTIVE

To assess surgeons in VR and live surgery using a suturing assessment tool and evaluate the association between technical skills and a clinical outcome.

DESIGN, SETTING, AND PARTICIPANTS

This prospective five-center study enrolled participants who completed VR suturing exercises and provided live surgical video. Graders provided skill assessments using the validated End-To-End Assessment of Suturing Expertise (EASE) suturing evaluation tool.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

A hierarchical Poisson model was used to compare skill scores among cohorts and evaluate the association of scores with clinical outcomes. Spearman's method was used to assess correlation between VR and live skills.

RESULTS AND LIMITATIONS

Ten novices, ten surgeons with intermediate expertise (median 64 cases, interquartile range [IQR] 6-80), and 26 expert surgeons (median 850 cases, IQR 375-3000) participated in this study. Intermediate and expert surgeons were significantly more likely to have ideal scores in comparison to novices for the subskills needle hold angle, wrist rotation, and wrist rotation needle withdrawal (p < 0.01). For both intermediate and expert surgeons, there was positive correlation between VR and live skills for needle hold angle (p < 0.05). For expert surgeons, there was a positive association between ideal scores for VR needle hold angle and driving smoothness subskills and 3-mo continence recovery (p < 0.05). Limitations include the size of the intermediate surgeon sample and clinical data limited to expert surgeons.

CONCLUSIONS

EASE can be used in VR to identify skills to improve for trainee surgeons. Technical skills that influence postoperative outcomes may be assessable in VR.

PATIENT SUMMARY

This study provides insights into surgical skills that translate from virtual simulation to live surgery and that have an impact on urinary continence after robot-assisted removal of the prostate. We also highlight the usefulness of virtual reality in surgical education.

Persistent Inequities in Intravenous Thrombolysis for Acute Ischemic Stroke in the United States: Results from the Nationwide Inpatient Sample

Background

Despite its approval for use in acute ischemic stroke (AIS) >25 years ago, intravenous thrombolysis (IVT) remains underutilized, with inequities by age, sex, race/ethnicity, and geography. Little is known about IVT rates by insurance status. We aimed to assess temporal trends in the inequities in IVT use.

Methods

We assessed trends from 2002 to 2015 in IVT for AIS in the Nationwide Inpatient Sample by sex, age, race/ethnicity, hospital location/teaching status, and insurance, using survey-weighted logistic regression, adjusting for sociodemographics, comorbidities, and hospital characteristics. We calculated odds ratios for IVT for each category in 2002-2008 (Period 1) and 2009-2015 (Period 2).

Results

Among AIS patients (weighted N=6,694,081), IVT increased from 1.0% in 2002 to 6.8% in 2015 (adjusted annual relative ratio (AARR) 1.15, 95% CI 1.14-1.16). Individuals ≥85 years had the most pronounced increase from 2002 to 2015 (AARR 1.18, 1.17-1.19), but were less likely to receive IVT compared to those aged 18-44 years in both Period 1 (adjusted odds ratio (aOR) 0.23, 0.21-0.26) and Period 2 (aOR 0.36, 0.34-0.38). Women were less likely than men to receive IVT, but the disparity narrowed over time (Period 1 aOR 0.81, 0.78-0.84, Period 2 aOR 0.94, 0.92-0.97). Inequities in IVT by race/ethnicity resolved for Hispanic individuals in Period 2 but not for Black individuals (Period 2 aOR 0.81, 0.78-0.85). The disparity in IVT for Medicare patients, compared to privately insured patients, lessened over time (Period 1 aOR 0.59, 0.56-0.52, Period 2 aOR 0.75, 0.72-0.77). Patients treated in rural hospitals were less likely to receive IVT than those treated in urban hospitals; a more dramatic increase in urban areas widened the inequity (Period 2 urban non-teaching vs. rural aOR 2.58, 2.33-2.85, urban teaching vs. rural aOR 3.90, 3.55-4.28).

Conclusion

From 2002 through 2015, IVT for AIS increased among adults. Despite encouraging trends, only 1 in 15 AIS patients received IVT and persistent inequities remained for Black individuals, women, government-insured, and those treated in rural areas, highlighting the need for intensified efforts at addressing inequities.

Toward precision medicine using a "digital twin" approach: modeling the onset of disease-specific brain atrophy in individuals with multiple sclerosis

Digital Twin (DT) is a novel concept that may bring a paradigm shift for precision medicine. In this study we demonstrate a DT application for estimating the age of onset of disease-specific brain atrophy in individuals with multiple sclerosis (MS) using brain MRI. We first augmented longitudinal data from a well-fitted spline model derived from a large cross-sectional normal aging data. Then we compared different mixed spline models through both simulated and real-life data and identified the mixed spline model with the best fit. Using the appropriate covariate structure selected from 52 different candidate structures, we augmented the thalamic atrophy trajectory over the lifespan for each individual MS patient and a corresponding hypothetical twin with normal aging. Theoretically, the age at which the brain atrophy trajectory of an MS patient deviates from the trajectory of their hypothetical healthy twin can be considered as the onset of progressive brain tissue loss. With a tenfold cross validation procedure through 1000 bootstrapping samples, we found the onset age of progressive brain tissue loss was, on average, 5-6 years prior to clinical symptom onset. Our novel approach also discovered two clear patterns of patient clusters: earlier onset versus simultaneous onset of brain atrophy.

Technical surgical skill assessment of neurovascular bundle dissection and urinary continence recovery after robotic-assisted radical prostatectomy

Purpose

To examine the association between the quality of neurovascular bundle dissection and urinary continence recovery after robotic-assisted radical prostatectomy.

Materials and Methods

Patients who underwent RARPs from 2016 to 2018 in two institutions with ≥1-year postoperative follow-up were included. The primary outcomes were time to urinary continence recovery. Surgical videos were independently assessed by 3 blinded raters using the validated Dissection Assessment for Robotic Technique (DART) tool after standardized training. Cox regression was used to test the association between DART scores and urinary continence recovery while adjusting for relevant patient features.

Results

121 RARP performed by 23 surgeons with various experience levels were included. The median follow-up was 24 months (95% CI 20 - 28 months). The median time to continence recovery was 7.3 months (95% CI 4.7 - 9.8 months). After adjusting for patient age, higher scores of certain DART domains, specifically tissue retraction and efficiency, were significantly associated with increased odds of continence recovery (p<0.05).

Conclusions

Technical skill scores of neurovascular bundle dissection vary among surgeons and correlate with urinary continence recovery. Unveiling the specific robotic dissection skillsets which impact patient outcomes has the potential to focus surgical training.

Toward Precision Medicine Using a "Digital Twin" Approach: Modeling the Onset of Disease-Specific Brain Atrophy in Individuals with Multiple Sclerosis

Digital Twin (DT) is a novel concept that may bring a paradigm shift for precision medicine. In this study we demonstrate a DT application for estimating the age of onset of disease-specific brain atrophy in individuals with multiple sclerosis (MS) using brain MRI. We first augmented longitudinal data from a well-fitted spline model derived from a large cross-sectional normal aging data. Then we compared different mixed spline models through both simulated and real-life data and identified the mixed spline model with the best fit. Using the appropriate covariate structure selected from 52 different candidate structures, we augmented the thalamic atrophy trajectory over the lifespan for each individual MS patient and a corresponding hypothetical twin with normal aging. Theoretically, the age at which the brain atrophy trajectory of an MS patient deviates from the trajectory of their hypothetical healthy twin can be considered as the onset of progressive brain tissue loss. With a 10-fold cross validation procedure through 1000 bootstrapping samples, we found the onset age of progressive brain tissue loss was, on average, 5-6 years prior to clinical symptom onset. Our novel approach also discovered two clear patterns of patient clusters: earlier onset vs. simultaneous onset of brain atrophy.

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.

Characterizing breast masses using an integrative framework of machine learning and CEUS-based radiomics

AIMS

We evaluated the performance of contrast-enhanced ultrasound (CEUS) based on radiomics analysis to distinguish benign from malignant breast masses.

METHODS

131 women with suspicious breast masses (BI-RADS 4a, 4b, or 4c) who underwent CEUS examinations (using intravenous injection of perflutren lipid microsphere or sulfur hexafluoride lipid-type A microspheres) prior to ultrasound-guided biopsies were retrospectively identified. Post biopsy pathology showed 115 benign and 16 malignant masses. From the cine clip of the CEUS exams obtained using the built-in GE scanner software, breast masses and adjacent normal tissue were then manually segmented using the ImageJ software. One frame representing each of the four phases: precontrast, early, peak, and delay enhancement were selected post segmentation from each CEUS clip. 112 radiomic metrics were extracted from each segmented tissue normalized breast mass using custom Matlab® code. Linear and nonlinear machine learning (ML) methods were used to build the prediction model to distinguish benign from malignant masses. tenfold cross-validation evaluated model performance. Area under the curve (AUC) was used to quantify prediction accuracy.

RESULTS

Univariate analysis found 35 (38.5%) radiomic variables with p < 0.05 in differentiating between benign from malignant masses. No feature selection was performed. Predictive models based on AdaBoost reported an AUC = 0.72 95% CI (0.56, 0.89), followed by Random Forest with an AUC = 0.71 95% CI (0.56, 0.87).

CONCLUSIONS

CEUS based texture metrics can distinguish between benign and malignant breast masses, which can, in turn, lead to reduced unnecessary breast biopsies.

Machine Learning to Delineate Surgeon and Clinical Factors That Anticipate Positive Surgical Margins After Robot-Assisted Radical Prostatectomy

Purpose: Automated performance metrics (APMs), derived from instrument kinematic and systems events data during robotic surgery, are validated objective measures of surgeon performance. Our previous studies showed that APMs are strong outcome predictors of urinary continence after robot-assisted radical prostatectomy (RARP). We now use machine learning to investigate how surgeon performance (i.e., APMs) and clinical factors can predict positive surgical margins (PSMs) after RARP. Methods: We prospectively collected data of patients undergoing RARP at our institution from 2016 to 2019. Random Forest model predicted PSMs based on 15 clinical factors and 38 APMs from 11 standardized RARP steps. Out-of-bag Gini impurity index determined the top 10 variables of importance (VOI). APMs in the top 10 VOI were assessed for confounding effects by extracapsular extension (ECE) and pathologic T (pT) through Poisson regression with Generalized Estimating Equation. Results: 55/236 (23.3%) cases had PSMs. Of the 55 cases with PSMs, 9 (16.4%) were pT2 and 46 (83.6%), pT3. The full model, including clinical factors and APMs, achieved area under the curve (AUC) 0.74. When assessing clinical factors or APMs alone, the model achieved AUC 0.72 and 0.64, respectively. The strongest PSM predictors were ECE and pT stage, followed by APMs in specific steps. After adjusting for ECE and pT stage, most APMs remained as independent predictors of PSM. Conclusion: Using machine learning methods, we found that the strongest predictors of PSMs after RARP are nonmodifiable, disease-driven factors (ECE and pT). While APMs provide minimal additional insight into when PSMs may occur, they are nonetheless capable of independently predicting PSMs based on objective measures of surgeon performance.

Educational, psychosocial, and clinical impact of SARS-CoV-2 (COVID-19) pandemic on medical students in the United States

BACKGROUND

The coronavirus disease 2019 (COVID-19) pandemic altered education, exams, and residency applications for United States medical students.

AIM

To determine the specific impact of the pandemic on US medical students and its correlation to their anxiety levels.

METHODS

An 81-question survey was distributed via email, Facebook and social media groups using REDCap^TM. To investigate risk factors associated with elevated anxiety level, we dichotomized the 1-10 anxiety score into low (≤ 5) and high (≥ 6). This cut point represents the 25^th percentile. There were 90 (29%) shown as low anxiety and 219 (71%) as high anxiety. For descriptive analyses, we used contingency tables by anxiety categories for categorical measurements with chi square test, or mean ± STD for continuous measurements followed by t-test or Wilcoxson rank sum test depending on data normality. Least Absolute Shrinkage and Selection Operator was used to select important predictors for the final multivariate model. Hierarchical Poisson regression model was used to fit the final multivariate model by considering the nested data structure of students clustered within State.

RESULTS

397 medical students from 29 states were analyzed. Approximately half of respondents reported feeling depressed since the pandemic onset. 62% of participants rated 7 or higher out of 10 when asked about anxiety levels. Stressors correlated with higher anxiety scores included “concern about being unable to complete exams or rotations if contracting COVID-19” (RR 1.34; 95%CI: 1.05-1.72, P = 0.02) and the use of mental health services such as a “psychiatrist” (RR 1.18; 95%CI: 1.01-1.3, P = 0.04). However, those students living in cities that limited restaurant operations to exclusively takeout or delivery as the only measure of implementing social distancing (RR 0.64; 95%CI: 0.49-0.82, P < 0.01) and those who selected “does not apply” for financial assistance available if needed (RR 0.83; 95%CI: 0.66-0.98, P = 0.03) were less likely to have a high anxiety.

CONCLUSION

COVID-19 significantly impacted medical students in numerous ways. Medical student education and clinical readiness were reduced, and anxiety levels increased. It is vital that medical students receive support as they become physicians. Further research should be conducted on training medical students in telemedicine to better prepare students in the future for pandemic planning and virtual healthcare.

Minocycline decreases blood-brain barrier permeability following aneurysmal subarachnoid hemorrhage: a randomized, double-blind, controlled trial

OBJECTIVE

Aneurysmal subarachnoid hemorrhage (aSAH)-induced vasospasm is linked to increased inflammatory cell trafficking across a permeable blood-brain barrier (BBB). Elevations in serum levels of matrix metalloprotease 9 (MMP9), a BBB structural protein, have been implicated in the pathogenesis of vasospasm onset. Minocycline is a potent inhibitor of MMP9. The authors sought to detect an effect of minocycline on BBB permeability following aSAH.

METHODS

Patients presenting within 24 hours of symptom onset with imaging confirmed aSAH (Fisher grade 3 or 4) were randomized to high-dose (10 mg/kg) minocycline or placebo. The primary outcome of interest was BBB permeability as quantitated by contrast signal intensity ratios in vascular regions of interest on postbleed day (PBD) 5 magnetic resonance permeability imaging. Secondary outcomes included serum MMP9 levels and radiographic and clinical evidence of vasospasm.

RESULTS

A total of 11 patients were randomized to minocycline (n = 6) or control (n = 5) groups. No adverse events or complications attributable to minocycline were reported. High-dose minocycline administration was associated with significantly lower permeability indices on imaging analysis (p < 0.01). There was no significant difference with respect to serum MMP9 levels between groups, although concentrations trended upward in both cohorts. Radiographic vasospasm was noted in 6 patients (minocycline = 3, control = 3), with only 1 patient developing symptoms of clinical vasospasm in the minocycline cohort. There was no difference between cohorts with respect to Lindegaard ratios, transcranial Doppler values, or onset of vasospasm.

CONCLUSIONS

Minocycline at high doses is well tolerated in the ruptured cerebral aneurysm population. Minocycline curtails breakdown of the BBB following aSAH as evidenced by lower permeability indices, though minocycline did not significantly alter serum MMP9 levels. Larger randomized clinical trials are needed to assess minocycline as a neuroprotectant against aSAH-induced vasospasm. Clinical trial registration no.: NCT04876638 (clinicaltrials.gov).

Technical Skill Impacts the Success of Sequential Robotic Suturing Substeps

Introduction: Robotic surgical performance, in particular suturing, has been associated with postoperative clinical outcomes. Suturing can be deconstructed into substep components (needle positioning, needle entry angle, needle driving, and needle withdrawal) allowing for the provision of more specific feedback while teaching suturing and more precision when evaluating suturing technical skill and prediction of clinical outcomes. This study evaluates if the technical skill required for particular substeps of the suturing process is associated with the execution of subsequent substeps in terms of technical skill, accuracy, and efficiency. Materials and Methods: Training and expert surgeons completed standardized sutures on the Mimic™ Flex virtual reality robotic simulator. Video recordings were deidentified, time annotated, and provided technical skill scores for each of the four suturing substeps. Hierarchical Poisson regression with generalized estimating equation was used to examine the association of technical skill rating categories between substeps. Results: Twenty-two surgeons completed 428 suturing attempts with 1669 individual technical skill assessments made. Technical skill scores between substeps of the suturing process were found to be significantly associated. When needle positioning was ideal, needle entry angle was associated with a significantly greater chance of being ideal (risk ratio [RR] = 1.12, p = 0.05). In addition, ideal needle entry angle and needle driving technical skill scores were each significantly associated with ideal needle withdrawal technical skill scores (RR = 1.27, p = 0.03; RR = 1.3, p = 0.03, respectively). Our study determined that ideal technical skill was associated with increased accuracy and efficiency of select substeps. Conclusions: Our study found significant associations in the technical skill required for completing substeps of suturing, demonstrating inter-relationships within the suturing process. Together with the known association between technical skill and clinical outcomes, training surgeons should focus on mastering not just the overall suturing process, but also each substep involved. Future machine learning efforts can better evaluate suturing, knowing that these inter-relationships exist.

Fever as a predictor of adverse outcomes in COVID-19

BACKGROUND/INTRODUCTION

There are little data on outcomes of COVID-19 patients with the presence of fever compared to the presence of symptoms.

AIM

We examined the associations between symptomology, presence of fever and outcomes of a COVID-19 cohort.

DESIGN AND METHODS

Between 23 January and 30 April 2020, 554 COVID-19 patients were admitted to a tertiary hospital in Singapore. They were allocated into four groups based on symptomology and fever-Group 1: asymptomatic and afebrile, Group 2: symptomatic but afebrile, Group 3: febrile but asymptomatic and Group 4: symptomatic and febrile. The primary outcomes were intensive care unit (ICU) admissions and mortality. The composite end-point included ICU admissions, mortality or any COVID-19 related end-organ involvement.

RESULTS

There were differences in ferritin (P=0.003), C-reactive protein (CRP) levels (P<0.001) and lymphopenia (P=0.033) across all groups, with the most favourable biochemical profile in Group 1, and the least in Group 4. Symptomatic groups (Groups 2 and 4) had higher ICU admissions (1.9% and 6.0%, respectively, P=0.003) than asymptomatic groups (Groups 1 and 3). Composite end-point was highest in Group 4 (24.0%), followed by Group 3 (8.6%), Group 2 (4.8%) and Group 1 (2.4%) (P<0.001). The presence of fever (OR 4.096, 95% CI 1.737-9.656, P=0.001) was associated with the composite end-point after adjusting for age, pulse rate, comorbidities, lymphocyte, ferritin and CRP. Presence of symptoms was not associated with the composite end-point.

DISCUSSION/CONCLUSION

In this COVID-19 cohort, presence of fever was a predictor of adverse outcomes. This has implications on the management of febrile but asymptomatic COVID-19 patients.

Benchmarking Various Radiomic Toolkit Features While Applying the Image Biomarker Standardization Initiative toward Clinical Translation of Radiomic Analysis

The image biomarkers standardization initiative (IBSI) was formed to address the standardization of extraction of quantifiable imaging metrics. Despite its effort, there remains a lack of consensus or established guidelines regarding radiomic feature terminology, the underlying mathematics and their implementation across various software programs. This creates a scenario where features extracted using different toolboxes cannot be used to build or validate the same model leading to a non-generalization of radiomic results. In this study, IBSI-established phantom and benchmark values were used to compare the variation of the radiomic features while using 6 publicly available software programs and 1 in-house radiomics pipeline. All IBSI-standardized features (11 classes, 173 in total) were extracted. The relative differences between the extracted feature values from the different software programs and the IBSI benchmark values were calculated to measure the inter-software agreement. To better understand the variations, features are further grouped into 3 categories according to their properties: 1) morphology, 2) statistic/histogram and 3)texture features. While a good agreement was observed for a majority of radiomics features across the various tested programs, relatively poor agreement was observed for morphology features. Significant differences were also found in programs that use different gray-level discretization approaches. Since these software programs do not include all IBSI features, the level of quantitative assessment for each category was analyzed using Venn and UpSet diagrams and quantified using two ad hoc metrics. Morphology features earned lowest scores for both metrics, indicating that morphological features are not consistently evaluated among software programs. We conclude that radiomic features calculated using different software programs may not be interchangeable. Further studies are needed to standardize the workflow of radiomic feature extraction.

Predicting clinical outcomes in COVID-19 using radiomics on chest radiographs

Objectives

For optimal utilization of healthcare resources, there is a critical need for early identification of COVID-19 patients at risk of poor prognosis as defined by the need for intensive unit care and mechanical ventilation. We tested the feasibility of chest X-ray (CXR)-based radiomics metrics to develop machine-learning algorithms for predicting patients with poor outcomes.

Methods

In this Institutional Review Board (IRB) approved, Health Insurance Portability and Accountability Act (HIPAA) compliant, retrospective study, we evaluated CXRs performed around the time of admission from 167 COVID-19 patients. Of the 167 patients, 68 (40.72%) required intensive care during their stay, 45 (26.95%) required intubation, and 25 (14.97%) died. Lung opacities were manually segmented using ITK-SNAP (open-source software). CaPTk (open-source software) was used to perform 2D radiomics analysis.

Results

Of all the algorithms considered, the AdaBoost classifier performed the best with AUC = 0.72 to predict the need for intubation, AUC = 0.71 to predict death, and AUC = 0.61 to predict the need for admission to the intensive care unit (ICU). AdaBoost had similar performance with ElasticNet in predicting the need for admission to ICU. Analysis of the key radiomic metrics that drive model prediction and performance showed the importance of first-order texture metrics compared to other radiomics panel metrics. Using a Venn-diagram analysis, two first-order texture metrics and one second-order texture metric that consistently played an important role in driving model performance in all three outcome predictions were identified.

Conclusions:

Considering the quantitative nature and reliability of radiomic metrics, they can be used prospectively as prognostic markers to individualize treatment plans for COVID-19 patients and also assist with healthcare resource management.

Advances in knowledge

We report on the performance of CXR-based imaging metrics extracted from RT-PCR positive COVID-19 patients at admission to develop machine-learning algorithms for predicting the need for ICU, the need for intubation, and mortality, respectively.

Accuracy of contrast-enhanced spectral mammography compared with MRI for invasive breast cancers: Prospective study in population of predominantly underrepresented minorities

OBJECTIVES

This prospective study compares contrast-enhanced spectral mammography (CESM) with contrast-enhanced breast MRI in assessing the extent of newly diagnosed breast cancer in a multiethnic cohort.

METHODS

This study includes 41 patients with invasive breast cancer detected by mammography or conventional ultrasound imaging from May 2017 to March 2020. CESM and MRI scans were performed prior to any treatment. Results are compared with each other and to histopathology. Detection of the malignant lesion was assessed by sensitivity, specificity, PPV, NPV. Consistency of malignant tumor size measurement was compared between modalities using Intraclass Correlation Coefficient (ICC).

RESULTS

In a multiethnic cohort with over 65% Hispanic and African-American women, the sensitivity of detecting malignant lesions for CESM is 93.1% (77.23%, 99.15%) and MRI is 96.55% (82.24%, 99.91%). The PPV for CESM 96.43% (81.65%, 99.91%) is better compared to MRI 82.35% (65.47%, 93.24%). CESM is as effective as MRI in evaluating index cancers and multifocal/multicentric/contralateral disease. CESM has greater specificity and PPV since MRI tends to overcall benign lesions. There is a good agreement of tumor size between CESM to surgery and MRI to surgery with ICC of 0.85 (95% CI 0.69, 0.93) and 0.87 (95% CI 0.74, 0.94), respectively. There is good agreement of malignancy detection between CESM and MRI with Kappa of 0.74 (95% CI 0.52, 0.95).

CONCLUSIONS

CESM is an effective imaging modality for evaluating the extent of disease in newly diagnosed invasive breast cancers and a good alternative to MRI in a multiethnic population.

Surgeon Automated Performance Metrics as Predictors of Early Urinary Continence Recovery After Robotic Radical Prostatectomy-A Prospective Bi-institutional Study

Background

During robotic surgeries, kinematic metrics objectively quantify surgeon performance.

Objective

To determine whether clinical factors confound the ability of surgeon performance metrics to anticipate urinary continence recovery after robot-assisted radical prostatectomies (RARPs).

Design, setting, and participants

Clinical data (patient characteristics, continence recovery, and treatment factors) and surgeon data from RARPs performed between July 2016 and November 2018 were prospectively collected. Surgeon data included 40 automated performance metrics (APMs) derived from robot systems (instrument kinematics and events) and summarized over each standardized RARP step. The data were collected from two high-volume robotic centers in the USA and Germany. Surgeons from both institutions performed RARPs. The inclusion criteria were consecutive RARPs having both clinical and surgeon data.

Intervention

RARP with curative intent to treat prostate cancer.

Outcome measurements and statistical analysis

The outcome was 3- and 6-mo urinary continence recovery status. Continence was defined as the use of zero or one safety pad per day. Random forest (SAS HPFOREST) was utilized.

Results and limitations

A total of 193 RARPs performed by 20 surgeons were included. Of the patients, 56.7% (102/180) and 73.3% (129/176) achieved urinary continence by 3 and 6 mo after RARP, respectively. The model anticipated continence recovery (area under the curve = 0.74, 95% confidence interval [CI] 0.66–0.81 for 3-mo, and area under the curve = 0.67, 95% CI 0.58–0.76 for 6 mo). Clinical factors, including pT stage, confounded APMs during prediction of continence recovery at 3 mo after RARP (Δβ median –13.3%, interquartile range [–28.2% to –6.5%]). After adjusting for clinical factors, 11/20 (55%) top-ranking APMs remained significant and independent predictors (ie, velocity and wrist articulation during the vesicourethral anastomosis). Limitations included heterogeneity of surgeon/patient data between institutions, although it was accounted for during multivariate analysis.

Conclusions

Clinical factors confound surgeon performance metrics during the prediction of urinary continence recovery after RARP. Nonetheless, many surgeon factors are still independent predictors of early continence recovery.

Patient summary

Both patient factors and surgeon kinematic metrics, recorded during robotic prostatectomies, impact early urinary continence recovery after robot-assisted radical prostatectomy.

Abstract P872: Persistent Inequities in Intravenous Thrombolysis for Acute Ischemic Stroke in the United States: Results From the Nationwide Inpatient Sample

Background: Intravenous thrombolysis (IVT) was approved for acute ischemic stroke (AIS) 25 yrs ago, yet few AIS patients receive it, with inequities by race/ethnicity, sex, and geography. With expanding evidence-based programs, we hypothesized increases in IVT utilization and reduction in inequities.

Methods: Using the Nationwide Inpatient Sample (NIS), we assessed temporal trends from 2002 to 2015 in IVT for AIS (weighted N=6,694,081) by sex, race/ethnicity, age, insurance, and hospital location/teaching status strata using survey - weighted logistic regression. Covariates included socio-demographics, comorbidities, and hospital characteristics. We calculated odds ratios for IVT by each category in 2002-2008 and 2009-2015.

Results: IVT for AIS increased from 1.0% in 2002 to 6.8% in 2015, with an overall adjusted annual relative ratio (AARR) of 1.15 (CI 1.14-1.16). Individuals 18-44 yrs had the highest rate of IVT in 2015. The very elderly (≥85 yrs) had the most pronounced increase in IVT (AARR 1.18, CI 1.17-1.19). The sex disparity in IVT improved, but in 2009-2015, women were still 6% less likely to receive IVT than men (Fig 1). Individuals 18-44 yrs were ~3-fold more likely to receive IVT than the very elderly. IVT inequities for black and Hispanic stroke survivors lessened, but blacks remained ~20% less likely than whites to receive IVT. Government-insured patients were ~25% less likely to receive IVT compared to privately insured. Urban AIS patients were up to 4-fold more likely to receive IVT than rural dwellers.

Conclusion: From 2002 through 2015, IVT for AIS in the U.S. increased regardless of race/ethnicity, sex, and age among ≥18 yrs, with the most pronounced increase among the very elderly. Despite encouraging trends, only 1 in 15 AIS patients received IVT and persistent inequities remain for blacks, women, government-insured, and rural stroke survivors, highlighting the need for intensifying stroke literacy and preparedness and enhancing systems of care.

Evaluation of Knee Cartilage Diurnal, Activity, and BMI-Related Variations Using Quantitative T2 Mapping MRI and Fitbit Activity Tracking

The aim of this study is to evaluate diurnal variation in knee cartilage 3 Tesla magnetic resonance imaging (MRI) T2 mapping relaxation times, as well as activity- and body mass index (BMI)-dependent variability, using quantitative analysis of T2 values from segmented regions of the weight-bearing articular surfaces of the medial and lateral femoral condyles and tibial plateaus. Ten healthy volunteers' daily activity (steps) were tracked with Fitbit pedometers. Sagittal MRI T2 maps were obtained in the morning and afternoon on days 2 and 3. Mean T2 values were analyzed for variation related to the number of steps taken (activity), time of day (diurnal variation), and BMI using mixed effect model. Significant (albeit small) differences in the medial femoral and medial tibial cartilage regions were identified between morning and afternoon scans (diurnal variation). Daily activity did not result in significant changes and increasing BMI only demonstrated a slight increase in T2 values for the lateral tibial plateau. These findings suggest that it may be necessary to control diurnal variation when using quantitative MRI T2 mapping to assess articular cartilage longitudinally in healthy participants. Further investigation is needed to confirm these findings and determine if they also apply to symptomatic patients.

The Children's Health and Maintenance Program (CHAMP): An innovative community outreach oral health promotion program: A randomized trial

OBJECTIVE

To describe CHAMP (Children's Oral Health Promotion Program) evaluating the impact of two motivational methods in increasing dental care access.

METHODS

CHAMP is a multi-dimensional oral health promotion programme that recruited and screened underprivileged children/families from community sites in Los Angeles County between 2012 and 2018. A randomized clinical trial (RCT) enrolled children/families into one or more motivational interventions (intra-oral camera and/or social work consultation) designed to impact subsequent scheduling of dental appointments.

RESULTS

CHAMP served 24 535 families. RCT had 418 families with 68.5% scheduling appointments by second follow-up (P < .001). Excluding children with scheduled appointments by first follow-up, children experiencing both interventions were 4.1 (95% CI 1.5-11.2) times more likely to schedule appointments by second follow-up than were the controls (P=<.01). When experiencing both interventions and had never previously been to the dentist, 68.3% scheduled dental appointments; this was significantly higher than the controls (46.7%) (P = .04). The best predictor for families to have scheduled appointments was a dental visit within the last six months [OR = 3.8 (95% CI 2.2-6.6), P < .001].

CONCLUSIONS

Outreach health promotion programmes are important and should consider utilizing various motivational techniques to encourage enrolment and treatment at dental homes.

Daily Ultrasound Imaging for Patients Undergoing Postprostatectomy Radiation Therapy Predicts and Ensures Dosimetric Endpoints

Purpose

Patients who receive radiation therapy (RT) for prostate cancer are routinely positioned through radiographic means. We set out to establish a data-driven process that defines bladder volume required to meet V40/65 constraints using daily bladder ultrasound (US) and comparative cone beam CT (CBCT) before placing a patient on the treatment table.

Methods and Materials

This was a single institution retrospective study of 20 patients (390 CBCT scans) who received postprostatectomy RT. Each patient received a daily US before treatment. CBCT alignment was performed 3 times a week. The bladder and rectum were contoured on each CBCT and a session dose was recorded. A mixed-effect model was used to estimate trajectory slopes of radiation exposure with organs-at-risk volume increase. Slope differences by V40/65 for prostate fossa (PF) and pelvic lymph nodes (PF/pLN) were tested using a 3-way-interaction term with Bonferroni correction.

Results

For the 20 patients, 10 received treatment to PF and 10 received RT to the PF/pLN. Predefined bladder constraints were V65 < 50%, V40 < 70%, and rectal constraints were V65 < 35%, V40 < 55%. The CBCT bladder volume (76-578 cm³) was greater than the pretreatment bladder US (87-466 cm³) due to volume filling between measurements (r = 0.8 ± 0.05). Mixed model detected a statistically significant 3-way interaction (P < .01) for bladder volume and V40/65. Both PF and PF/pLN patients showed improvement in V40/65 with an increase in bladder volume. For PF patients, bladder constraints were met when the US volume was >108 cm³ and for PF/pLN patients when the US bladder volume was >200 cm³. Rectal filling showed no association with CBCT volume.

Conclusions

Daily US of the bladder before postprostatectomy RT allows for dosimetric predictions before daily treatment. This should translate into fewer CBCT for the patient and improved machine throughput. This technique is easy to institute and ensures organs-at-risk volumetric constraints are met based on daily US measurements.

Abstract 5379: Non-invasive profiling of advanced prostate cancer via multi-parametric liquid biopsy and radiomics

Introduction: Biomarkers of treatment response in advanced prostate cancer (PC) are urgently needed. Liquid biopsy profiling and radiomic imaging enable non-invasive, repeatable tumor profiling, and combining these modalities could yield powerful new predictive tools. We tested the feasibility of concurrent, multi-parametric molecular analysis of circulating tumor cells (CTCs) and matched plasma cell-free DNA (cfDNA), combined with radiomic analysis of CT scans from the same patients.

Methods: Under IRB-approved informed consent, blood was collected from 23 patients with metastatic castrate resistant PC (mCRPC). CTCs were enumerated using the RareCyte and CellSearch platforms, and individual single CTCs and white blood cells (WBCs) were retrieved using RareCyte's integrated robotic micropipette. DNA was extracted from single cells (scDNA), as well as from matched cfDNA and buffy coats (bcDNA), then sequenced using Ampliseq HD Pan-cancer panel. Concurrent radiomic analysis was performed on bone metastatic lesions identified on CT scans from the same patients, and manually segmented regions of interest were queried for a variety of texture metrics.

Results: Of 19 patients with both CellSearch and RareCyte enumeration, CTCs were detected in 12 by CellSearch (63%; median: 3/7.5 mL; range 1-343/ 7.5 mL) and in 14 by RareCyte (74%; median: 1/7.5 mL; range 1-363/7.5 mL). Using matched bcDNA as a gold standard, sensitivity and positive predictive value of germline SNP detection were 74% and 93% for scDNA, and 98% and 99% for cfDNA. A total of 48 and 18 somatic alterations were identified across the cohort in CTCs and cfDNA, respectively, including mutations in AR, TP53, CCND3, FGFR1, ALK, and ROS1. Of 14 patients whose single CTCs were recovered by RareCyte, 12 (86%) had detectable somatic mutations in scDNA, and 7 (50%) had detectable somatic mutations in matched cfDNA. While some mutations were concordant between matched scDNA and cfDNA, most were distinct. Radiomic entropy in CT scans was associated with CellSearch CTC-counts (AUC of 0.74) using the FDA-cleared prognostic threshold of &lt;5 vs. ≥5 CTCs/7.5ml.

Conclusion: We successfully piloted an integrated, multi-parametric analysis of matched single CTCs, WBCs, plasma cfDNA, and buffy coats, along with matched radiomic analysis of CT scans in patients with mCRPC. Germline variants were detected more readily in cfDNA, whereas somatic mutations in commonly altered genes were detected more frequently in CTCs. CellSearch CTC count, an FDA cleared prognostic biomarker, correlated with radiomic entropy, the first such association to our knowledge between liquid biopsy and radiographic readouts. The results demonstrate the feasibility of this approach and its potential to generate comprehensive molecular data and new biomarker profiles. Prospective validation in a large PC cohort is underway.

Citation Format: Gareth J. Morrison, Jonathan Buckley, D. Gigi Ostrow, Bino Varghese, Nolan Ericson, Steven Cen, Alexander Cunha, Yi-Tsung Lu, Tad George, Jeffrey Smith, David Quinn, Vinay Duddalwar, Timothy Triche, Amir Goldkorn. Non-invasive profiling of advanced prostate cancer via multi-parametric liquid biopsy and radiomics [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 5379.

Deep learning based classification of solid lipid-poor contrast enhancing renal masses using contrast enhanced CT

OBJECTIVE

Establish a workflow that utilizes convolutional neural nets (CNN) to classify solid, lipid-poor, contrast enhancing renal masses using multiphase contrast enhanced CT (CECT) images and to assess the performance of the resulting network.

METHODS

In this institutional review board approved study of 143 patients with predominantly solid, lipid-poor, contrast enhancing renal lesions (46 benign and 97 malignant), patients with a pre-operative multiphase CECT of the abdomen and pelvis obtained between June 2009 and June 2015 were retrospectively queried. Benign renal masses included oncocytoma and lipid-poor angiomyolipoma and the malignant group included clear cell, papillary, and chromophobe carcinomas.Region of interests of whole tumor volumes were manually segmented, and CT phase images with the largest cross-section of the segmented tumor in the axial plane were used for assessment. Post-surgical pathological evaluation was used to establish diagnosis.The segmented images of renal masses were used as input to a CNN. The data were augmented and split into training (83.9%) and validation sets (16.1%) to determine the hyperparameters of the CNN. Thereafter. the performance of the resulting CNN was quantified using eightfold cross-validation.

RESULTS

The CNN-based classifier demonstrated an overall accuracy of 78% (95% confidence interval: 76-80%), sensitivity of 70% (95% confidence interval: 66-74%), specificity of 81% (79-83%) and an area under the curve of 0.82.

CONCLUSION

A CNN-based classifier to diagnose solid enhancing malignant renal masses based on multiphase CECT images was developed.

ADVANCES IN KNOWLEDGE

It was established that a CNN-based classifier could be trained to accurately distinguish malignant renal lesions.

Abstract TP405: IV TPA Utilization and Outcomes in Young Stroke Patients

Objective: Cerebrovascular disorders are among the top ten causes of death in the pediatric population. The incidence is felt to be 1-2 per 100,000, although this number could be higher due to poor recognition. Our objective is to describe the incidence, tPA utilization, inpatient mortality, length of stay, and cost associated with stroke in pediatric population.

Methods: Ischemic stroke cases between the ages of 1 and 17 years were obtained from the Nationwide Inpatient Sample (NIS) for the period from January 1, 2000 through December 31, 2014. The primary outcome was inpatient mortality. The secondary outcome was LOS and total cost per day. National trend estimate followed HCUP methodical standard which adopted the design change at 2012 with appropriate trend weight. Weighted estimates were made via SURVEYMEAN procedure and presented as national estimate ± standard error from sampling. SAS9.4 was used for the analysis.

Results: From January 2000 through December 2014, there were an estimated 12908±1087 pediatric cases with ischemic stroke, 157±28 (1.2%±0.2%) had TPA. Pediatric ischemic stroke patients were predominantly discharged from urban, large-bed-size, teaching hospitals (40.7%±3.9%), more likely to be white (39.3%±1.8%) and male (52.5%±1.2%), most prevalent among those aged 16 years old (10.3%±0.8%). Overall inpatient mortality was 3.0±0.3 per 100 discharges. Median LOS was 4.0±0.1 days. Median total charge per day was $ 8162±348. Majority of pediatric ischemic stroke patients discharged routinely to home or self-care (75.8%±1.2%).

Conclusion: This study highlights that during the prespecified time frame of four years there was an estimated 12908±1087 ischemic strokes in the pediatric population and less than 2% of children received alteplase. Hospital mortality was 3.0% ± 0.3%. The average length of stay was 4 days with an estimated cost of $8162+/- 348 per day. The majority of pediatric patients were discharged home.

Feasibility of coronary endothelial function assessment using arterial spin labeled CMR

Coronary endothelial dysfunction (CED) is an independent predictor of cardiovascular disease, but its assessment has been limited to invasive coronary angiography. Myocardial perfusion imaging using arterial spin labeled (ASL) cardiac magnetic resonance (CMR) may be an effective non-invasive alternative for detection of CED. Thirty-four patients were recruited: 10 healthy volunteers, 13 at high-risk for coronary artery disease (CAD), and 11 with established CAD. ASL-CMR was performed continuously in a single mid-short axis slice during rest, stress, and recovery. Stress was induced with sustained isometric handgrip exercise, an endothelial dependent stressor. Myocardial perfusion (MP) during rest, peak stress, and recovery were calculated and compared. After excluding subjects unable to complete the protocol or who exhibited poor data quality, 6 healthy, 10 high-risk, and 7 CAD patients were included in the analysis. Average MP (ml/g/min) was 1.31 ± 1.23, 1.61 ± 1.12, and 1.40 ± 0.97 at rest, and 1.64 ± 1.49, 2.31 ± 1.61, and 2.84 ± 1.77 during stress, for the CAD, high-risk and healthy group, respectively. The average MP response (MP_stress - MP_rest , ml/g/min) was 0.32 ± 1.93, 0.69 ± 1.34, and 1.44 ± 1.46 for CAD, high-risk and healthy group, respectively. MP during handgrip stress was significantly lower for both the CAD (p = 0.0005) and high-risk groups (p = 0.05) compared to the healthy volunteers. In only the healthy subjects, MP was significantly higher in stress compared to rest (p = 0.0002). Participants with CAD had significantly lower MP response compared to healthy volunteers, as detected by ASL-CMR. These findings support the feasibility of ASL-CMR for non-invasive assessment of CED.

Compressed Sensing MR Imaging (CS-MRI) of the Knee: Assessment of Quality, Inter-reader Agreement, and Acquisition Time

We compared 3 Tesla (3T) compressed sensing (CS)-MRI of different pulse sequences with various acceleration factors to standard fast spin-echo (FSE) sequences in terms of time, quality, and inter-reader agreement. Each sequence was qualitatively ranked and then qualitatively scored for blurring, artifact, low contrast detection, noise pattern, signal-to-noise ratio, and overall quality. The CS-MRI sequences demonstrated very good overall quality compared with routine FSE sequences with overall good inter-reader agreement.

Signal Hyperintensity on Unenhanced T1-Weighted Brain and Cervical Spinal Cord MR Images after Multiple Doses of Linear Gadolinium-Based Contrast Agent

BACKGROUND AND PURPOSE

The clinical implications of gadolinium deposition in the CNS are not fully understood, and it is still not known whether gadolinium tends to be retained more in the brain compared with the spinal cord. In this study, we assessed the effects of linear gadolinium-based contrast agents on the T1 signal intensity of 3 cerebral areas (dentate nucleus, globus pallidus, and the less studied substantia nigra) and the cervical spinal cord in a population of patients with MS.

MATERIALS AND METHODS

A single-center population of 100 patients with MS was analyzed. Patients underwent 2-16 contrast-enhanced MRIs. Fifty patients received ≤5 linear gadolinium injections, and 50 patients had ≥6 injections: Fifty-two patients had both Gd-DTPA and gadobenate dimeglumine injections, and 48 patients received only gadobenate dimeglumine. A quantitative analysis of signal intensity changes was independently performed by 2 readers on the first and last MR imaging scan. The globus pallidus-to-thalamus, substantia nigra-to-midbrain, dentate nucleus-to-middle cerebellar peduncle, and the cervical spinal cord-to-pons signal intensity ratios were calculated.

RESULTS

An increase of globus pallidus-to-thalamus (mean, +0.0251 ± 0.0432; P < .001), dentate nucleus-to-middle cerebellar peduncle (mean, +0.0266 ± 0.0841; P = .002), and substantia nigra-to-midbrain (mean, +0.0262 ± 0.0673; P < .001) signal intensity ratios after multiple administrations of linear gadolinium-based contrast agents was observed. These changes were significantly higher in patients who received ≥6 injections (P < .001) and positively correlated with the number of injections and the accumulated dose of contrast. No significant changes were detected in the spinal cord (mean, +0.0008 ± 0.0089; P = .400).

CONCLUSIONS

Patients with MS receiving ≥6 linear gadolinium-based contrast agent injections showed a significant increase in the signal intensity of the globus pallidus, dentate nucleus, and substantia nigra; no detectable changes were observed in the cervical spinal cord.

Shoulder measurements on MRI: Statistical analysis of patients without and with rotator cuff tears and predictive modeling

This study aims to determine significant differences between various measurements of shoulder structures and relationships in patients with and without rotator cuff tears and identify a subset of these measurements that may merit further investigation. Shoulder MRIs of 120 patients with rotator cuff tears (RCT group) and 80 patients with normal examinations (No RCT group) were retrospectively identified. Numerous measurements of shoulder anatomy and relationships and pathology characterization were performed for each study. The mean and ranges of measurements for each group were identified, and P-values were calculated to assess differences between the two groups. Classification and Regression Tree (CART) identified prediction models for separating the two groups based on these shoulder MRI measurements. Statistically significant differences were observed for 9 of 18 of the shoulder measurements between the two groups (P < 0.05). Using long head of biceps tendon tear, tendinosis, and subacromial-subdeltoid bursal fluid, the prediction model from CART demonstrated 99.5% accuracy in separating the two groups. Subacromial distance, subacromial spur size, and acromioclavicular osteophyte could also separate the two groups with 97.5% accuracy. Other measures less commonly associated with impingement and rotator cuff tears could also be used to separate the two groups with up to 81.5% accuracy. This study introduces new measures and clarifies ranges for existing measurements on shoulder MRI. Abnormalities of some of these measurements may be associated with subacromial impingement, and combinations of these parameters may be useful for separating patients with or without rotator cuff tears. Clin. Anat. 33:173-186, 2020. © 2019 Wiley Periodicals, Inc.

Abstract TP3: Mechanical Thrombectomy for Cerebral Venous Thrombosis is Associated With Increased Inpatient Mortality: Outcomes From the Nationwide Inpatient Sample

Introduction: Cerebral venous thrombosis (CVT) is a rare form of stroke which can lead to both ischemic or hemorrhagic infarcts. The mainstay of treatment is therapeutic anticoagulation. Endovascular treatments, specifically, mechanical thrombectomy (MT) has been increasingly utilized, likely owing to the increasing concomitant use of MT in acute ischemic stroke patients. However, despite some small series and case reports demonstrating success, endovascular treatment, consisting of thrombolysis with or without MT, has not been shown to be superior to anticoagulation. Likely owing to its rarity, however, the use of MT alone has not been widely evaluated in large studies. Here, we utilize the Nationwide Inpatient Sample (NIS) to determine national rates of MT among patients with CVT over a 5-year epoch and characterize their outcomes.

Methods: Cases with CVT were retrospectively obtained from the NIS for the period from January 1, 2006 through December 31, 2011. The primary outcome is inpatient mortality. Demographic and sample characteristics were compared using a chi-squared test between MT group and no MT group for categorical variables and using two-sample t-test for continuous variables. Poisson regression was performed to examine the mortality rate difference between MT vs. no MT groups, stratified by patients’ likelihood of dying at admission (major/extreme vs. minor/moderate).

Results: 3605 cases of CVT were identified, with 64 patients (1.8%) undergoing MT. Patients who underwent MT were on average younger, more likely to be admitted to a large teaching hospital, had extreme likelihood of dying at admission, and had longer length of stay (LOS). The MT group had higher inpatient mortality (22% vs 4%) and was more likely to be discharged to institutional care (38% vs 16%) than no MT group (p < 0.01). Among high risk patients with either major or extreme likelihood of dying at admission, the MT group showed statistically significantly higher inpatient mortality than the no MT group (31.2%±3.2% vs. 15.9%±0.7%, p<0.01).

Conclusions: Patients with CVT undergoing MT were rare, with an extremely high acuity at presentation. Overall, these patients did poorly, with high inpatient mortality, longer LOS and high rates of discharge to institutional care.

A Decision-Support Tool for Renal Mass Classification

We investigate the viability of statistical relational machine learning algorithms for the task of identifying malignancy of renal masses using radiomics-based imaging features. Features characterizing the texture, signal intensity, and other relevant metrics of the renal mass were extracted from multiphase contrast-enhanced computed tomography images. The recently developed formalism of relational functional gradient boosting (RFGB) was used to learn human-interpretable models for classification. Experimental results demonstrate that RFGB outperforms many standard machine learning approaches as well as the current diagnostic gold standard of visual qualification by radiologists.

Acetabular labral tear description and measures of pincer and cam-type femoroacetabular impingement and interobserver variability on 3 T MR arthrograms

PURPOSE

To evaluate the inter-rater agreement for description of labral tears and measures of femoroacetabular impingement (FAI) on 3 T hip MR arthrography.

MATERIALS AND METHODS

53 hip MR arthrograms were reviewed by three musculoskeletal radiologists. Labral tears were described (Czerny classification) with extents recorded. Cam- and pincer-type FAI measures were performed. Intraclass correlation (ICC) and kappa statistic (κ) assessed inter-observer agreement.

RESULTS

There was fair agreement for labral tear description (κ = 0.25-0.39) and for alpha angles (ICC = 0.54), and fair to excellent agreement for other measures of FAI (ICC = 0.51-0.90).

CONCLUSION

There is moderate inter-observer variability reporting labral tears and measures of FAI.

Abstract WP181: CNS Vasculitis in the United States: Demographics and Complications

Introduction: Primary and secondary CNS vasculitis encompass a range of disorders that are notoriously challenging to diagnose. While rare, their protean clinical presentations make them frequent considerations in the differential diagnosis of various clinical scenarios. This study investigates the scope of primary and secondary CNS vasculitis in the US inpatient population and identifies risk factors for mortality and non-routine discharge.

Methods: A subset of adult patients (age ≥18 years) with a discharge diagnosis of “cerebral arteritis” (ICD-9-CM 437.4) were identified in the HCUP National Inpatient Sample database for years 2000-2011. We report patient characteristics and outcomes as well as complications and comorbidities. Logistic regression analysis was performed to identify factors associated with in-hospital death and non-routine discharge.

Results: A total of 6,269 discharges were identified, including 1,561 with cerebral arteritis as the primary discharge diagnosis. Mean age was 53.6 years (SD 16.7); sex was 67% female (n=6264). Mean Charlson Comorbidity Index was 1.2 (SD 1.5) indicating low comorbidity burden. The most common complications or comorbidities included disorders of cognition (15%, n=6269), ischemic stroke (12.2%, n=6269), any late effect of stroke (12%, n=6269), any intracranial hemorrhage (8.6%, n=6269), TIA (7.6%, n=6269), seizures/epilepsy (6.3%, n=6269), headache (4%, n=6269) and hydrocephalus (1.8%, n=6269). Combined, a range of inflammatory disorders were common (22.4%, n=6269) but individual diagnoses were not highly represented except SLE (9.2%) and RA (3.5%). In-hospital mortality was 5.1% (n=6269); discharges were routine for 48.9% (n=6269). Major complications associated with in-hospital mortality were hydrocephalus (OR 2.4, CI 1.2-4.8) and intracranial hemorrhage (OR 1.8, CI 1.3-2.7). Conditions associated with non-routine discharge were weakness (OR 2.2, CI 1.8-2.7), cognitive diagnoses (OR 1.9, CI 1.6-2.4) and ischemic stroke (OR 1.3, CI 1.1-1.6).

Conclusions: Cognitive disorders, in addition to various stroke subtypes, are the most prominent complications of CNS vasculitis in the US. In-hospital mortality in CNS vasculitis is linked with hydrocephalus and intracranial hemorrhage.

Digital image analysis agrees with visual estimates of adult bone marrow trephine biopsy cellularity

INTRODUCTION

Evaluation of cellularity is an essential component of bone marrow trephine biopsy examination. The standard practice is to report the results as visual estimates (VE). Digital image analysis (DIA) offers the promise of more objective measurements of cellularity.

METHODS

Adult bone marrow trephine biopsy sections were assessed for cellularity by VE. Sections were scanned using an Aperio AT2 Scanscope and analyzed using a Cytonuclear (version 1.4) algorithm on halo software. Intraclass correlation (ICC) was used to assess relatedness between VE and DIA, and between MRI and DIA for a separate subset of patients. Trephine biopsy sections from a subset of patients with bone marrow biopsies uninvolved by malignancy were assessed for age-related changes.

RESULTS

Interobserver VE agreement was good to excellent. The ICC value was 0.81 for VE and DIA, and 0.50 for MRI and DIA. Linearity studies showed no statistically significant trend for age-related changes in cellularity in our cohort (r = -.29, P = .06).

CONCLUSIONS

Agreement was good between VE and DIA. It may be possible to use DIA or VE to measure cellularity in the appropriate clinical scenario. The limited sample size precludes similar determinations for MRI calculations. Further studies examining healthy donors are necessary before making definitive conclusions regarding age and cellularity.

Particulate Air Pollutants, Brain Structure, and Neurocognitive Disorders in Older Women

Introduction

An increasing number of studies have suggested that exposure to particulate matter (PM) may represent a novel - and potentially amendable - environmental determinant of brain aging. The current longitudinal environmental epidemiological study addressed some important knowledge gaps in this emerging field, which combines the study of air pollution and neuroepidemiology. The investigators hypothesized that long-term PM exposure adversely influences global brain volume and brain regions (e.g., frontal lobe or hippocampus) that are critical to memory and complex cognitive processing or that are affected by neuropathological changes in dementia. It was also hypothesized that long-term PM exposure results in neurovascular damage and may increase the risk of mild cognitive impairment (MCI) and -dementia.

Methods

The investigators selected a well-characterized and geographically diverse population of older women (N = 7,479; average age = 71.0 ± 3.8 years at baseline) in the Women's Health Initiative (WHI) Memory Study (WHIMS) cohort (1996-2007), which included a subcohort (n = 1,403) enrolled in the WHIMS-Magnetic Resonance Imaging (WHIMS-MRI) study (2005-2006). Residence-specific yearly exposures to PM ≤ 2.5 µm in aerodynamic diameter (PM₂.₅) were estimated using a Bayesian maximum entropy spatiotemporal model of annual monitoring data (1999-2007) recorded in the U.S. Environmental Protection Agency (U.S. EPA) Air Quality System (AQS). Annual exposures (1996-2005) to diesel PM (DPM) were assigned to each residential census tract in a nationwide spatiotemporal mapping, based on a generalized additive model (GAM), to conduct census tract-specific temporal interpolation of DPM on-road estimates given by the U.S. EPA National-Scale Air Toxics Assessment Program. Multiple linear regression and multicovariate-adjusted Cox models were used to examine the associations, with statistical adjustment for multiple potential confounders.

Results

The investigators found that participants had smaller brain volumes, especially in the normal-appearing white matter (WM), if they lived in locations with higher levels of cumulative exposure (1999-2006) to PM ₂.₅ before the brain MRI scans were performed. The associations were not explained by sociodemographic factors, socioeconomic status, lifestyle factors, or other clinical characteristics. Analyses showed that the adverse effect on brain structure in the participants was driven primarily by the smaller WM volumes associated with cumulative PM₂.₅ exposures, which were present in the WM divisions of the association brain area (frontal, parietal, and temporal lobes) and corpus callosum. Increased DPM exposures were associated with larger ventricular volume, suggesting an overall atrophic effect on the aging brains. The participants tended to have smaller gray matter (GM) volumes if they lived in areas with the highest (i.e., fourth quartile) estimated cumulative DPM exposure in the 10 years before the brain MRI scans, compared with women in the first to third quartiles. This observed association was present in the total brain GM and in the association brain cortices. The associations with normal-appearing WM varied by DPM exposure range. For women with estimated cumulative exposure below that of the fourth quartile, increased DPM estimates were associated with smaller WM volumes. However, for women with increased cumulative DPM exposures estimates in the fourth quartile, WM volumes were larger. This pattern of association was found consistently in the association brain area; no measurable difference was found in the volume of the corpus callosum. These observed adverse effects of cumulative exposure to PM₂.₅ (linking exposure with smaller WM volumes) and to DPM (linking exposure in the highest quartile with smaller GM volumes) were not significantly modified by existing cardiovascular diseases, diabetes mellitus, obesity, or measured white blood cell (WBC) count. MRI measurements of the structural brain showed no differences in small-vessel ischemic diseases (SVID) in participants with varying levels of cumulative exposure to PM₂.₅ (1999-2006) or DPM (1996-2005), and no associations between PM exposures and SVID volumes were noted for total brain, association brain area, GM, or WM. For neurocognitive outcomes followed until 2007, the investigators found no evidence for increased risk of MCI/dementia associated with long-term PM exposures. Although exploratory secondary analyses showed different patterns of associations linking PM exposures separately with MCI and dementia, none of the -results was statistically significant. A similar lack of associations between PM exposures and MCI/dementia was found across the subgroups, with no strong indications for effect modification by cardiovascular diseases, diabetes mellitus, obesity, or WBC count.

Conclusions

The investigators concluded that their study findings support the hypothesized brain-structure neurotoxicity associated with PM exposures, a result that is in line with emerging neurotoxicological data. However, the investigators found no evidence of increased risk of MCI/dementia associated with long-term PM exposures.

To better test the neurovascular effect hypothesis in PM-associated neurotoxic effects on the aging brain, the investigators recommend that future studies pay greater attention to selecting optimal populations with repeated measurements of cerebrovascular damage and address the possibility of selection biases accordingly. To further investigate the long-term consequence of brain-structure neurotoxicity on pathological brain aging, future researchers should take the pathobiologically heterogeneous neurocognitive outcomes into account and design adequately powered prospective cohort studies with improved exposure estimation and valid outcome ascertainment to assess whether PM-associated neurotoxicity increases the risks of pathological brain aging, including MCI and dementia.

Application of Prostate Imaging Reporting and Data System Version 2 (PI-RADS v2): Interobserver Agreement and Positive Predictive Value for Localization of Intermediate- and High-Grade Prostate Cancers on Multiparametric Magnetic Resonance Imaging

RATIONALE AND OBJECTIVES

To evaluate interobserver agreement with the use of and the positive predictive value (PPV) of Prostate Imaging Reporting and Data System version 2 (PI-RADS v2) for the localization of intermediate- and high-grade prostate cancers on multiparametric magnetic resonance imaging (mpMRI).

MATERIALS AND METHODS

In this retrospective, institutional review board-approved study, 131 consecutive patients who had mpMRI followed by transrectal ultrasound-MR imaging fusion-guided biopsy of the prostate were included. Two readers who were blinded to initial mpMRI reports, clinical data, and pathologic outcomes reviewed the MR images, identified all prostate lesions, and scored each lesion based on the PI-RADS v2. Interobserver agreement was assessed by intraclass correlation coefficient (ICC), and PPV was calculated for each PI-RADS category.

RESULTS

PI-RADS v2 was found to have a moderate level of interobserver agreement between two readers of varying experience, with ICC of 0.74, 0.72, and 0.67 for all lesions, peripheral zone lesions, and transitional zone lesions, respectively. Despite only moderate interobserver agreement, the calculated PPV in the detection of intermediate- and high-grade prostate cancers for each PI-RADS category was very similar between the two readers, with approximate PPV of 0%, 12%, 64%, and 87% for PI-RADS categories 2, 3, 4, and 5, respectively.

CONCLUSIONS

In our study, PI-RADS v2 has only moderate interobserver agreement, a similar finding in studies of the original PI-RADS and in initial studies of PI-RADS v2. Despite this, PI-RADS v2 appears to be a useful system to predict significant prostate cancer, with PI-RADS scores correlating well with the likelihood of intermediate- and high-grade cancers.