Citations

Abstract PURPOSE Brain tumor related epilepsy (BTE) is a major co-morbidity in patients with glioma. It is difficult to determine whether the use of anti-epileptic drugs is necessary. We attempted to build a machine-learning model to predict the probability of seizure presentation (SP) with glioma. METHODS We trained a random forest classifier using the following variables: volumetric data of pre-treatment MR images (T1Gd and T2-FLAIR sequences), patient demographics (age; sex), and measurements of tumor proliferation (log(ρ)), invasiveness (log(D)) and their relative ratio (log(ρ/D)). Our cohort consisted of 221 patients total. Using an 80-20 ratio, we used 176 patients (76 SP, 100 nSP) for training and the remaining 45 patients (19 SP, 26 nSP) were used for testing. We also trained on male-only and female-only cohorts to evaluate any sex differences in prediction. For training, 108 males (53 SP, 55 nSP) were used and 28 for testing (14 SP, 14 nSP). We used 72 females (21 SP, 49 nSP) for training and 15 (7 SP, 8 nSP) for testing. We corrected for class imbalance in the female cohort before training. Using 10-fold cross-validation and a separate testing set, we measured performance by ROC curve (AUC), accuracy, sensitivity, and specificity of predictions (average of folds in cross validation). RESULTS The female model achieved the highest AUC (0.853) followed by the mixed model (0.726) and the male model (0.651). In the validation set, the accuracy/sensitivity/specificity of the three cohorts were as follows: mixed (0.726/0.696/0.750), female (0.853/0.830/0.875), and male (0.651/0.577/0.722). The performance of the testing set, in terms of accuracy/sensitivity/specificity were: mixed (0.733/0.74/0.73), female (0.8/0.57/1), and male (0.714/0.64/0.79). CONCLUSION We found a negative correlation between seizure probability and size and invasiveness of tumors. Our model shows promising performance on testing set data. Further cohort studies and training is warranted.

Abstract Sex differences in brain tumor related epilepsy (BTE) as an initial symptom of glioma are rarely investigated. Sex differences are being explored with increased interest more recently. Epidemiological studies have generally indicated overall incidence of epilepsy to be slightly higher in males than females, but a higher incidence of idiopathic generalized epilepsy has been seen in females in some studies. Clinicians regularly face the challenge of anti-epileptic drug prescription determination in patients with newly identified brain mass and would greatly benefit from knowing clinical characteristics in BTE. We analyzed clinical characteristics in patients with pathologically-determined glioma with known seizure status at clinical presentation using non-parametric and Fisher’s Exact tests with the entire cohort and male and female separately. From our clinical data repository, we identified 223 patients (females, n=86 (39%); males, n=137 (61%)) divided by those that presented with seizure (SP, n=96, 43%; F, n= 28; M, n= 68) and those that presented without seizure (nSP, n=127, 57%, F n=58, M n=69). In sex-specific analysis males had a significantly (x2=6.28, p=0.01) higher proportion of SP (49.6%) than females (32.6%). There was a dependence between seizure presentation status and tumor grade in males (x2=5.94, p=0.015). Tumor kinetics in the female cohort showed significantly (p< 0.0001) more diffuse tumors in SP compared to nSP. Right-sided tumors were predominantly nSP, while left-sided tumors were split more evenly between SP and nSP. The predominance of nSP among right-sided tumors seems to be driven by females (74%), male right-sided tumors were split more evenly between SP and nSP. Seizure status is dependent on tumor location for the combined cohort, however not for males (x2=5.23, p=0.16) or females (x2=4.34, p=0.23). Clearly there are sex differences and similarities in clinical characteristics at glioma presentation. Further characterization could lead to improved adherence of national standards for AED prescription.

Certain medical schools have begun teaching courses in health systems science (HSS) to train medical students in skills aimed to improve health care in the United States. Although substantial research has been done on the potential benefit of HSS courses, reactions from students have not been reported. In this Invited Commentary, five medical students who have completed the first year of a longitudinal HSS course at the Arizona campus of the Mayo Clinic School of Medicine offer their observations of how early exposure to HSS affected their reactions to subsequent course work and current events in health care. The authors describe the HSS course and outline three benefits they have observed from their experience so far: (1) thinking more critically about health care delivery during all educational experiences, (2) gaining a better understanding of the complexity of the health care system, and (3) having a greater consideration for the many facets of health care delivery. The HSS course helped the authors identify health systems problems, develop solutions that incorporated diverse domains of health care delivery, and recognize the role and responsibility of the physician as an agent of change in a health care system.

Arteriovenous malformations (AVMs) are a subset of congenital vascular malformations (CVMs). They comprise abnormal connections between arterial and venous circulation; treatment approaches are dependent on the angioarchitecture of the AVM, specifically the number and arrangement of the feeder arteries and outflow veins. Various imaging modalities can be used to diagnose and plan treatment. Here we will review the use of transarterial approaches to treat AVMs.

Nutcracker syndrome (NS) refers to symptomatic compression of the left renal vein (LRV) between the abdominal aorta and superior mesenteric artery with potential symptoms including hematuria, proteinuria, left flank pain, and renal venous hypertension. No consensus diagnostic criteria exist to guide endovascular treatment. We aimed to evaluate the specificity of LRV compression to NS symptoms through a retrospective study including 33 NS and 103 control patients. The size of the patent lumen at point of compression and normal portions of the LRV were measured for all patients. Multiple logistic regression analyses (MLR) assessing impact of compression, body mass index (BMI), age, and gender on the likelihood of each symptom with NS were obtained. NS patients presented most commonly with abdominal pain (72.7%), followed by hematuria (57.6%), proteinuria (39.4%), and left flank pain (30.3%). These symptoms were more commonly seen than in the control group at 10.6, 11.7, 6.8, and 1.9%, respectively. The degree of LRV compression for NS was 74.5% and 25.2% for controls (p < 0.0001). Higher compression led to more hematuria (p < 0.0013), abdominal pain (p < 0.006), and more proteinuria (p < 0.002). Furthermore, the average BMI of NS patients was 21.4 and 27.2 for controls (p < 0.001) and a low BMI led to more abdominal pain (p < 0.005). These results demonstrate a strong correlation between the degree of LRV compression on imaging in diagnosing NS.