Assessment of unintended shifts during frame-based stereotactic radiosurgery using cone beam computed tomography image guidance.

PURPOSE: To investigate the frequency, magnitude and possible causes of frame-shifts that may occur between treatment planning and treatment delivery when performing Gamma Knife radiosurgery with rigid frame-based immobilization. METHODS: Differences between computed tomography (CT) framed fiducial stereotactic coordinate reference and cone beam computed tomography stereotactic coordinates after image registration were recorded for 49 frame-based GK radiosurgery cases performed using the Gamma Knife Icon. Parameters recorded include rotational shifts, translational shifts, and the GK-computed Maximum Shot Displacement (MSD) between the two stereotactic coordinate spaces. Other patient-specific parameters were collected and linear regression analysis was performed to evaluate predictors of increased displacement. RESULTS: The median values of rotational shifts were: pitch 0.14°, yaw 0.17°, and roll 0.13°. The median absolute values of translational shifts were: left-right 0.39 mm, anteroposterior 0.14 mm, and superior-inferior 0. 22 mm. The median value of MSD was 0.71 mm. Twelve cases (24.5%) had a MSD of greater than 1.0 mm. Male gender was associated with increased MSD (p = 0.013) and translational shifts (root-mean-squared value, p = 0.017). Cases with large differences between right and left sided pin lengths were also associated with increased MSD (p = 0.011). CONCLUSIONS: The use of CBCT image guidance in frame-based GK radiosurgery allows unintended frame shifts to be identified and corrected. A significant fraction (24.5%) of patients had large enough shifts to result in a MSD of greater than 1.0 mm. Male gender and eccentrically placed frames were associated with increased MSD, and particular care should be taken in these cases.

Proton beam therapy utilization in adults with primary brain tumors in the United States.

The utilization of proton beam therapy (PBT) as the primary treatment of adults with primary brain tumors (APBT) was evaluated through query of the National Cancer Database (NCDB) between the years 2004 and 2015. International Classification of Diseases for Oncology code for each patient was stratified into six histology categories; high-grade gliomas, medulloblastomas, ependymomas, other gliomas, other malignant tumors, or other benign intracranial tumors. Demographics of the treatment population were also analyzed. A total of 1,296 patients received PBT during the 11-year interval for treatment of their primary brain tumor. High-grade glioma, medulloblastoma, ependymoma, other glioma, other malignant, and other benign intracranial histologies made up 39%, 20%, 13%, 12%, 13%, and 2% of the cohort, respectively. The number of patients treated per year increased from 34 to 300 in years 2004 to 2015. Histologies treated with PBT varied over the 11-year interval with high-grade gliomas comprising 75% and 45% at years 2004 and 2015, respectively. The majority of the patient population was 18-29 years of age (59%), Caucasian race (73%), had median reported income of over $63,000 (46%), were privately insured (68%), and were treated at an academic institution (70%). This study characterizes trends of malignant and benign APBT histologies treated with PBT. Our data from 2004 through 2015 illustrates a marked increase in the utilization of PBT in the treatment of APBT and shows variability in the tumor histology treated over this time.

Identifying the Most Costly Patients in Radiation Oncology and Predicting the Top Spenders.

PURPOSE: Quality payment programs aim to adjust payments on the basis of quality and cost; however, few quality metrics exist in radiation oncology. This study evaluates and predicts the top spenders (TS) after radiation therapy (RT). MATERIALS AND METHODS: Patient characteristics, cancer details, treatments, toxicity, and survival data were collected for patients treated with RT at Mayo Clinic from 2007 to 2016. Standardized costs were obtained and adjusted for inflation. TSs were identified as those with greater than 93rd percentile costs (≥ $120,812). Prediction models were developed to predict TSs using training and validation sets using information available at consultation, after RT, and at last follow-up. RESULTS: A total of 15,131 patients were included and 1,065 TSs identified. Mean cost overall was $55,290 (median, $39,996) for all patients. Prediction models 1, 2, and 3 had concordance statistics of 0.83 to 0.83, 0.85 to 0.85, and 0.87 to 0.88, respectively in training and validation, indicating excellent prediction of TSs. Factors that were most predictive of TSs included stage N/A and stage 4 (v stage 0; odds ratio [OR], 18.23 and 8.44, respectively; P < .001); hematologic, upper GI, skin and lung cancers (v breast; OR, 11.45, 7.69, 3.81, and 2.43, respectively; P < .01); immunotherapy, surgery, and chemotherapy use (OR, 4.36, 2.51, and 1.61, respectively; P < .01); hospitalizations within 90 days of RT (OR, 2.26; P < .01); or death during the episode (OR, 1.56; P < .01). CONCLUSION: This is the first study of its kind to predict with high accuracy the highest spenders in radiation oncology. These patients may benefit from pre-emptive management to mitigate costs, or may require exclusion or adjustment from quality payment programs.