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Surface-Guided Radiotherapy Systems as Source of Big Data: Using SGRT Data to Derive Patient-Specific Treatment Margins

D Jacqmin1*, (1) University of Wisconsin, Madison, WI


(Sunday, 7/14/2019) 4:30 PM - 5:00 PM

Room: Exhibit Hall | Forum 6

Purpose: We investigated a hypothetical treatment paradigm in which breast radiotherapy patients are adaptively re-planned after the first few fractions using smaller treatment margins derived by surface-guided radiotherapy system data. We explore the feasibility of this approach and the effect on treatment efficiency.

Methods: A custom Python library called alignrt-tools was written to convert the raw data from three AlignRT systems to a format that can be used for data mining. The alignrt-tools library was used to calculate custom margins for 127 previously-treated breast radiotherapy patients. We used AlignRT positional data from the first one, three and five fractions of treatment to calculate margins such that the patient would remain in tolerance 90% of the time during those fractions. We evaluated the effect that the new margins would have on the duty cycle of remaining treatments by determining the fraction of the time the patient would be in tolerance. To improve the duty cycle, we investigated the effect of increasing the derived margins by 0.5 mm in each direction.

Results: The average SGRT-derived margins calculated after one, three and five fractions were 1.8 mm, 2.2 mm and 2.3 mm, respectively. These margins produced average duty cycles of 52.1%, 65.8% and 70.0%, respectively, for the remaining fractions. Increasing the margins by an additional 0.5 mm improved the duty cycles to 77.3%, 84.1% and 86.2% for margins derived after one, three and five fractions, respectively. Overall, 85.3%, 77.1% and 81.1% of patients have margins less than 3 mm when derived after one, three and five fractions, respectively.

Conclusion: Compared to a standard margin of 5-mm typically used for breast IMRT/VMAT, the margins calculated in this study show that most patients would benefit from adaptive planning using SGRT-derived margins determined early during treatment. Reducing margins can be done without seriously compromising treatment efficiency.


Optical Imaging, Image-guided Therapy, Target Localization


TH- RT Interfraction motion management : setup errors, immobilization, localization

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