Heterogeneity correction for intensity-modulated frameless SRS in pituitary and cavernous sinus tumors: a retrospective study.

BACKGROUND: Frameless immobilization allows for planning and quality assurance of intensity-modulated radiosurgery (IM-SRS) plans. We tested the hypothesis that IM-SRS planning with uniform tissue density corrections results in dose inaccuracy compared to heterogeneity-corrected algorithms. METHODS: Fifteen patients with tumors of the pituitary or cavernous sinus underwent frameless IM-SRS. Treatment planning CT and MRI scans were obtained and fused to delineate the tumor, optic nerves, chiasm, and brainstem. The plan was developed with static gantry IM-SRS fields using a pencil beam (PB), analytical anisotropic (AAA), and Acuros XB (AXB) algorithms. We evaluated measures of target coverage as well as doses to organs at risk (OAR) for each algorithm. We compared the results of each algorithm in the cases where PTV overlapped OAR (n = 10) to cases without overlapping OAR with PTV (n = 5). Utilizing film dosimetry, we measured the dose distribution for each algorithm through a uniform density target to a rando phantom with non-uniform density of air, tissue, and bone. RESULTS: There was no difference in target coverage measured by DMaxPTV, DMinPTV, D95%PTV, or the isodose surface (IDS) covering 95% of the PTV regardless of algorithm. However, there were differences in dose to OAR. PB predicted higher (p < 0.05) Dmax for the brainstem, chiasm, right optic nerve, and left optic nerve. In cases of PTV overlapping an optic nerve (n = 7), PB was unable to limit dose to 8 Gy while achieving PTV coverage (PB 855 cGy vs. AAA 769 cGy, p = 0.05 vs. AXB 658 cGy, p = 0.03). Within the rando phantom, the PB and AAA algorithms over-estimated the dose delivered in the bone-tissue-air interface of the sinus (+17%), while the AXB algorithm closely predicted the actual dose delivered through the inhomogeneous tissue (+/- 1 % max, p < 0.05). CONCLUSIONS: Patients undergoing frameless SRS benefit from heterogeneity corrected dose plans when the lesion lies in areas of widely varying tissue density and near critical normal structures such as the skull base. Film dosimetry confirms that the AXB dose calculation algorithm more accurately predicts actual dose delivered though tissues of varying densities than PB or AAA dose calculation algorithms.

Barriers and facilitators to learning and performing cardiopulmonary resuscitation in neighborhoods with low bystander cardiopulmonary resuscitation prevalence and high rates of cardiac arrest in Columbus, OH.

BACKGROUND: Residents who live in neighborhoods that are primarily black, Latino, or poor are more likely to have an out-of-hospital cardiac arrest, less likely to receive cardiopulmonary resuscitation (CPR), and less likely to survive. No prior studies have been conducted to understand the contributing factors that may decrease the likelihood of residents learning and performing CPR in these neighborhoods. The goal of this study was to identify barriers and facilitators to learning and performing CPR in 3 low-income, high-risk, and predominantly black neighborhoods in Columbus, OH. METHODS AND RESULTS: Community-Based Participatory Research approaches were used to develop and conduct 6 focus groups in conjunction with community partners in 3 target high-risk neighborhoods in Columbus, OH, in January to February 2011. Snowball and purposeful sampling, done by community liaisons, was used to recruit participants. Three reviewers analyzed the data in an iterative process to identify recurrent and unifying themes. Three major barriers to learning CPR were identified and included financial, informational, and motivational factors. Four major barriers were identified for performing CPR and included fear of legal consequences, emotional issues, knowledge, and situational concerns. Participants suggested that family/self-preservation, emotional, and economic factors may serve as potential facilitators in increasing the provision of bystander CPR. CONCLUSIONS: The financial cost of CPR training, lack of information, and the fear of risking one's own life must be addressed when designing a community-based CPR educational program. Using data from the community can facilitate improved design and implementation of CPR programs.