Radiation Physics

PV QA 3 - Poster Viewing Q&A 3

TU_12_3231 - Dosimetric Evaluation of Knowledge - Based Therapy Planning for Complex Craniospinal Irradiation

Tuesday, October 23
1:00 PM - 2:30 PM
Location: Innovation Hub, Exhibit Hall 3

Dosimetric Evaluation of Knowledge – Based Therapy Planning for Complex Craniospinal Irradiation
P. Anchineyan1, J. Amal2, D. Arulin1, R. Amutham1, K. Gurunath1, P. S. Sridhar3, and B. ajai Kumar4; 1Helath Care Global Ent., Bangalore, India, 2HCG Cancer Center, Bengaluru, India, 3Health Care Global Enterprises Ltd, Bangalore, India, 4Healthcare Global Enterprises, Bangalore, India

Purpose/Objective(s): Craniospinal irradiation (CSI) remains technically demanding, with potential for treatment filed overlap or gaps to yield unacceptable dosimetric target heterogeneity and time consuming for planning. Knowledge-based therapy planning (KBTP) model for CSI were created using dosimetric inputs from helical tomotherapy (HT) planning to guide optimization and to generate plans with Volumetric Modulated Arc Therapy (VMAT) technique in a different planning system and then to test the performance of this model against user plans.

Materials/Methods: Thirty six CSI patients treated with HT were chosen to create KBTP model. All image set had organ at risks (OAR) such as Heart, bilateral Kidneys, Lungs, Eyes, Rectum, Bladder contoured and deliverable plans were created using a tomotherapy planning system. The Radiotherapy dose dicom file were then transferred to another planning system to train KBTP models. For the purpose of training KBTP model, we considered five OARs say Heart, bilateral Kidneys, Lungs to extract dosimetric data. The published model was then used to guide VMAT Optimization and to generate deliverable plans on an independent set of 20 adult patients using three isocentre. Resultant model plans were then compared and analyzed against user plans using VMAT and HT. The planning target volume (PTV) coverage were compared using the Uniformity Index (UI). Four dose-volume points such as V5, V10, V20 and mean doses were used to compare the OARs doses.

Results: Out of 36 patient dosimetric data extracted, 27 dataset were used to train KBTP model excluding potential poor outliers from data set. R-square values of trained model as goodness of fit for OARs were Heart 0.623,Left Kidney 0.761 , Right Kidney 0.887 , Left Lung 0.965 and Right Lung 0.903. UI for PTV were 1.03 ± 0.02 and 1.06 ± 0.01 for KBTP model plan and user VMAT plan respectively. Mean dose to Heart, Right and left Lungs, Right and left kidneys were 400 cGy ± 59, 462.1cGy ± 53, 406.8 cGy ± 40, 431.7cGy ± 30, 406.6 cGy ± 31 for KBTP plans and 383.2 cGy ± 29, 423.8 cGy ± 17, 393.1 cGy ± 44, 557.6 cGy ± 20, 557.2 cGy ± 19 for user plans respectively. There is no significant improvement in OAR dose volume values between plans. The targets heterogeneity and global maximum dose were found to be high in VMAT user’s plan by 2 - 3 % and closely fit to HT user’s plans when compared with model plans.

Conclusion: KBTP CSI models are suitable for generating clinically acceptable VMAT plans and planning time is greatly reduced. Overall results promotes KBTP as effective CSI planning solution.

Author Disclosure: P. Anchineyan: None. J. Amal: None. D. Arulin: None. R. Amutham: None. K. Gurunath: None.

Pichandi Anchineyan, PhD

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