A software tool is developed, given a new treatment plan, to predict treatment delivery time for radiation therapy (RT) treatments of patients on ViewRay magnetic resonance image‐guided radiation therapy (MR‐IGRT) delivery system. This tool is necessary for managing patient treatment scheduling in our clinic. The predicted treatment delivery time and the assessment of plan complexities could also be useful to aid treatment planning. A patient's total treatment delivery time, not including time required for localization, is modeled as the sum of four components: 1) the treatment initialization time; 2) the total beam‐on time; 3) the gantry rotation time; and 4) the multileaf collimator (MLC) motion time. Each of the four components is predicted separately. The total beam‐on time can be calculated using both the planned beam‐on time and the decay‐corrected dose rate. To predict the remain‐ing components, we retrospectively analyzed the patient treatment delivery record files. The initialization time is demonstrated to be random since it depends on the final gantry angle of the previous treatment. Based on modeling the relationships between the gantry rotation angles and the corresponding rotation time, linear regression is applied to predict the gantry rotation time. The MLC motion time is calculated using the leaves delay modeling method and the leaf motion speed. A quantitative analysis was performed to understand the correlation between the total treatment time and the plan complexity. The proposed algorithm is able to predict the ViewRay treatment delivery time with the average prediction error 0.22 min or 1.82%, and the maximal prediction error 0.89 min or 7.88%. The analysis has shown the correlation between the plan modulation (PM) factor and the total treatment delivery time, as well as the treatment delivery duty cycle. A possibility has been identified to significantly reduce MLC motion time by optimizing the positions of closed MLC pairs. The accuracy of the proposed prediction algorithm is sufficient to support patient treatment appointment scheduling. This developed software tool is currently applied in use on a daily basis in our clinic, and could also be used as an important indicator for treatment plan complexity.PACS number(s): 87.55.N
Background During clinical interactions, clinicians and people with aphasia (PWA) use humour and laughter for a range of purposes, most of which contribute to friendly interactions in which the participants appear to develop a positive regard for one another. Moreover, humour is a vital component of facework, or the processes interactants engage in to protect their own and one another's well‐respected, public personas. Aims To examine the ways in which speech–language pathology graduate student clinicians enlist humour during one‐on‐one therapy sessions for PWA. Methods & Procedures Three dyads composed of one graduate student clinician and one person with aphasia acted as participants. We recorded six routine individual aphasia therapy sessions that were each about 60 min in length. All sessions were orthographically transcribed by a trained research assistant. Transcriptions included verbal and non‐speech communication (e.g., facial expressions, gestures, writing). For analysis, we employed an ethnographic microanalysis framework. First, by focusing on laughter produced by the interactants, we identified segments in the data that involved clinician‐led humour. Next, we sought to understand patterns that represented potential functions of humour. We consciously sought out instances that did not appear consistent with our developing understanding of the functions of humour. Such negative cases were used to refine our description of how graduate student clinicians use humour. Other verification procedures included member checking and peer debriefing. Outcomes & Results The findings illustrate that graduate student clinicians use laughter and humour for a range of interactional purposes when interacting with clients with aphasia. Humour was used as a means of (1) softening exposure to client's errors, (2) equalizing interactional power, (3) mitigating errors made by graduate student clinicians, (4) supporting own narrative production and (5) demonstrating affiliation. Conclusions & Implications The current study demonstrates that graduate student clinicians we observed, like the clinicians studied in previous investigations of humour in therapeutic encounters, possess the humour and laughter‐related skills that help to foster positive interactions with PWA. Future investigations of the source of these skills should determine if students are adept because of natural abilities or if students can be taught to be better interactants via instruction. Findings emanating from these studies can be used to inform curriculum design, which will in turn help our field better meet the needs of clients.
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