Inverse versus convolution treatment planning algorithms for gamma knife radiosurgery

Abstract

Objective: To compare the convolution and inverse algorithm plans.
Method: The cross-sectional study was conducted from January to May 2022 at the Icon Gamma Knife Centre, Al-
Taj Hospital, Baghdad, Iraq, and comprised patients with malignant and benign brain tumours who underwent
gamma knife therapy. Each patient's brain was imaged using computed tomography and magnetic resonance
imaging. The neurosurgeon prescribed the dose depending on the tumour volume and type, while the medical
physicist generated the two plans based on inverse and convolution algorithms. The prescribed dose was delivered
to 50% of the isodose line of the tumour. Each plan was evaluated with respect to tumour conformity index,
coverage, gradient index, number of shots, and time of treatment.
Results: Of the 30 patients, 17(56.7%) were males and 13(43.3%) were females. The overall mean age was
46.29±15.20 years (range: 10-71 years). The mean dose delivered was 15.86±3.86Gy, and the mean number of
gamma radiation shots was 12.56±6.95. There was significant difference between the two algorithm plans for all
dosimetric parameters, with the inverse plan providing higher coverage and selectivity than convolution plan, but
taking longer time(p<0.05), while plan was inverse plan better than convolution plan in terms of gradient and
conformity (p<0.05).
Conclusion: With more extended treatment, the inverse plan was found to have superior selectivity, coverage,
gradient index and Paddick conformity index values compared to the convolution plan.
Key Words: Tumour, Algorithms, Brain, Magnetic, Tomography