On the road to Gamma Knife Icon workflow automation in radiation oncology. Young Lee Department of Medical Physics

Transcription

1 On the road to Gamma Knife Icon workflow automation in radiation oncology Young Lee Department of Medical Physics

2 Outline - introduction to GK Icon and workflow - goals - processes for automation - on-going research - manufacturer - summary 2

3 What is a Gamma Knife Icon? GK Perfexion Unit with CBCT and intra-fractional monitoring system CBCT provides stereotactic coordinates (no frame) high dependence on image co-registration Detector X-ray tube Optical camera X-ray tube Detector 3

4 Real-time tracking HDMM system High Definition Motion Management enabling stereotactic Gamma Knife radiosurgery with non-rigid fixations. Elekta White Paper,

5 GK in oncology department traditionally operated in neurosurgery departments mainly to treat benign diseases when surgery was not an option. short plan-to-treat times. manually driven plan-to-treat processes - efficiency of workflow relies on personnel expertise. more recently, GK is being used to treat multiple brain metastases. increase in groups involved in RT patient pathway can lead to increased plan-to-treat times and treatment variability. 6

6 Sunnybrook workload first patient treated on Icon: June 13, 2017 total treated: 254 patients 52 frame 202 mask patients (including 27 hypo-fractionated cases) number of mask sessions: ~400 treatment indications: metastases (>80%) acoustic neuroma (10) AVM (6) meningioma (10) other (3, including 1 patient with OCD) 7

7 Goals Through automation - would like to streamline GK process - would like to increase planning and treatment consistency and efficiency 8

8 Identify processes for automation Frame Mask 9

9 Planning part 1 contouring issues treatment planning system does not allow margins to be added to volumes. volume manipulation such as subtracting volumes, donut shapes not allowed next version margin growing tool built into Gamma Plan (GK treatment planning system) 10 Manufacturer

10 Planning part 2 image fusion accuracy of image fusion process variable due to manual choosing of different VOI in current co-registration tool. automated image fusion auto-fusion, no manual intervention image fusion quantification Manufacturer 11

11 Planning part 3 planning methodology - manual forward planning (isocentre placement, choosing of sectors, weights) - heavy reliance on planner experience inverse planning 1) automatic isocentre placement using machine learning 2) dose optimization using DVH criteria (including previous treatment plan info) with penalties on time Researchers 12

12 inverse planning Planning part 3 machine learning development and implementation of inverse planning technique.lgp file Voxelized tumors, OARs + isocentres Isocentre location optimization Sector Duration Optimization (SDO) Optimized plan Point cloud-tosurface converter Machine learning Linear Quadratic Regularization Unconstrained Moment-based Work done by Azamat Berdyshev (MSc student) Work done by Mucahit Cevik (Post Doc) 13

13 Planning part 4 separation of complicated treatment plans multiple targets or hypo+srs to be treated over several days require daily plans to be created manually manual-intensive and intraand inter-observer variability is very high separation to daily plans automatically separate out targets to be treated each day using a dosimetric analyses calculate true composite dose and dose distributions for each day Manufacturer + Researchers 14

14 Recording data EPR data entry - requires manual entry of Rx, uploading of documents (dose distribution, plan details) - no R&V MOSAIQ compatibility true compatibility between GK and MOSAIQ (All Rx, document info automatically transferred) unit to be run through MOSAIQ 15 Manufacturer

15 Treatment visualization bony anatomy CBCT allows bony anatomy match between reference CBCT to daily CT high resolution CBCT tumour visualization using iterative reconstruction and dual energy imaging techniques 16 Researchers

16 Scheduling manual lists and MOSAIQ - multiple lists used to keep track of preplans, plans, documentation, QA etc. - MOSAIQ QCLs used for patient scheduling, documentation MOSAIQ dashboard utilizing QCL technology, check and track patient pathway Researchers 17

17 MOSAIQ Dashboard 18 -Potential for real-time refresh screen (currently only on backup server) 18

18 Frame Summary and Future work expect many of automated processes as described to be introduced into GK Icon workflow automated processes will allow a higher number of patients to be treated on GK without reducing quality and maintaining individualization. Mask 19

19 Sunnybrook Team Physics 20 Young Lee Mark Ruschin Arman Sarfehnia Collins Yeboah Brige Chugh Unit Therapy Jason Koskinen Teresa Cheng Ruby Bola Changsheng Yan Lori Holden MRI Therapy Sim Therapy Radiation Oncology Arjun Sahgal Hany Soliman Sten Myrehaug Eric Tseng Neurosurgery Todd Mainprize Mike Schwartz Nir Lipsman Leo DaCosta Victor Yang Research Azamat Berdyshev (MSc candidate) Dr. Mucahit Cevik Prof Dionne Aleman