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Extension of a Clinical OIS/EMR/R&V System to Deliver Safe and Efficient Adaptive Plan-Of-The-Day Treatments Using a Fully Customizable Plan-Library-Based Workflow

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A Akhiat

A. Akhiat1,2*, A.P. Kanis1 , J.J. Penninkhof1 , N. Linton2 , A. Coleman2 , S. Sodjo1 , T. O'Neill1 , S. Quint1 , X. van Doorn1 , W. Schillemans1 , B. Heijmen1 , M. Hoogeman1 , (1) Erasmus MC Cancer Institute, Radiation Oncology, Rotterdam, The Netherlands , (2) Elekta, Sunnyvale, CA, United States


SU-E-J-73 (Sunday, July 12, 2015) 3:00 PM - 6:00 PM Room: Exhibit Hall

Purpose: To extend a clinical Record and Verify (R&V) system to enable a safe and fast workflow for Plan-of-the-Day (PotD) adaptive treatments based on patient-specific plan libraries.

Methods: Plan libraries for PotD adaptive treatments contain for each patient several pre-treatment generated treatment plans. They may be generated for various patient anatomies or CTV-PTV margins. For each fraction, a Cone Beam CT scan is acquired to support the selection of the plan that best fits the patient's anatomy-of-the-day. To date, there are no commercial R&V systems that support PotD delivery strategies. Consequently, the clinical workflow requires many manual interventions. Moreover, multiple scheduled plans have a high risk of excessive dose delivery. In this work we extended a commercial R&V system (MOSAIQ) to support PotD workflows using IQ-scripting. The PotD workflow was designed after extensive risk analysis of the manual procedure, and all identified risks were incorporated as logical checks.

Results: All manual PotD activities were automated. The workflow first identifies if the patient is scheduled for PotD, then performs safety checks, and continues to treatment plan selection only if no issues were found. The user selects the plan to deliver from a list of candidate plans. After plan selection, the workflow makes the treatment fields of the selected plan available for delivery by adding them to the treatment calendar. Finally, control is returned to the R&V system to commence treatment. Additional logic was added to incorporate off-line changes such as updating the plan library. After extensive testing including treatment fraction interrupts and plan-library updates during the treatment course, the workflow is running successfully in a clinical pilot, in which 35 patients have been treated since October 2014.

Conclusion: We have extended a commercial R&V system for improved safety and efficiency in library-based adaptive strategies enabling a wide-spread implementation of those strategies.

Funding Support, Disclosures, and Conflict of Interest: This work was in part funded by a research grant of Elekta AB, Stockholm, Sweden.

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