Search

Purpose: To evaluate the clinical need for automated decision-support platforms for Adaptive Radiotherapy Therapy (ART) of Head & Neck cancer (HNC) patients. Methods: We tested RTapp (SegAna), a new decision-support software for ART, to investigate 22 HNC patients data retrospectively. For each fraction, RTapp estimated the daily and cumulative doses received by targets and OARs from daily 3D imaging in real-time. RTapp also included a prediction algorithm that analyzed dosimetric parameters (DP) trends against dosimetric endpoints (DE) to trigger adaptation up to 4 fractions ahead. Warning (V95DE10. The differences between predicted and calculated PTV V95 and parotids Dmean was up to 7.6% (mean: -2.9+/-4.6 %) and 5 Gy (mean: 0.2+/-1.6 Gy), respectively. The most accurate predictions were obtained closest to Fx. For parotids, Fx ranged between fractions 1 to 23, the lack of specific trend demonstrated the need to verify treatment adaptation for every fraction. Conclusion: Integrated in an ART clinical workflow, RTapp can predict whether specific treatment would require adaptation up to 4 fractions ahead of time., 20 pages, 7 figures, submitted to Frontiers in Oncology: Radiation Oncology