ArticleMedical physics2026
Gamma knife knowledge-based planning with isocenter selection.
Article in Medical physics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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3 authors.
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Abstract
backgroundIn Gamma Knife (GK) radiosurgery, effective treatment planning aims to achieve a desired dose distribution while minimizing the overall treatment duration. Clinically, plans are generated either manually through forward planning, or using inverse planning methods. To address the limitations presented by forward and inverse planning, a knowledge-based planning (KBP) pipeline was recently developed for GK, using 3D dose predictions in combination with inverse optimization. However, this approach still relied on manually selected isocenter locations, which may limit plan quality. PURPOSE: To develop a complete KBP pipeline for GK, combining dose prediction with the simultaneous optimization of isocenter locations and beam-on-times.
methodsData for 20 patients were obtained from a local care center. A previously trained deep learning model generated 3D dose predictions for each case. The primary treatment planning model was a mixed-integer model (GK-KBP-OptIso) that combined isocenter selection with beam-on-time optimization. Plans were generated under several different maximum allowable isocenter limits and compared against (1) plans generated using an existing KBP pipeline with fixed, manually selected isocenters (GK-KBP-FixIso) and (2) historical clinical plans. Plan quality was assessed using coverage, selectivity, Paddick conformity, and gradient indices, along with overall treatment time.
resultsUnder the same isocenter limits, GK-KBP-OptIso achieved comparable conformity to GK-KBP-FixIso (
conclusionsA KBP pipeline that integrates isocenter selection yields plans that are equal or superior to those generated using KBP with manually selected isocenters or manual clinical planning. The presented approach holds the potential to streamline the effort required to generate high-quality GK treatment plans.
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