Abstract
PurposeTo present the k‐means clustering algorithm as a tool to address treatment planning considerations characteristic of stereotactic radiosurgery using a single isocenter for multiple targets.MethodsFor 30 patients treated with stereotactic radiosurgery for multiple brain metastases, the geometric centroids and radii of each met were determined from the treatment planning system. In‐house software used this as well as weighted and unweighted versions of the k‐means clustering algorithm to group the targets to be treated with a single isocenter, and to position each isocenter. The algorithm results were evaluated using within‐cluster sum of squares as well as a minimum target coverage metric that considered the effect of target size. Both versions of the algorithm were applied to an example patient to demonstrate the prospective determination of the appropriate number and location of isocenters.ResultsBoth weighted and unweighted versions of the k‐means algorithm were applied successfully to determine the number and position of isocenters. Comparing the two, both the within‐cluster sum of squares metric and the minimum target coverage metric resulting from the unweighted version were less than those from the weighted version. The average magnitudes of the differences were small (−0.2 cm2 and 0.1% for the within cluster sum of squares and minimum target coverage, respectively) but statistically significant (Wilcoxon signed‐rank test, P < 0.01).ConclusionsThe differences between the versions of the k‐means clustering algorithm represented an advantage of the unweighted version for the within‐cluster sum of squares metric, and an advantage of the weighted version for the minimum target coverage metric. While additional treatment planning considerations have a large influence on the final treatment plan quality, both versions of the k‐means algorithm provide automatic, consistent, quantitative, and objective solutions to the tasks associated with SRS treatment planning using a single isocenter for multiple targets.
Highlights
Since its introduction over 60 yr ago, stereotactic radiosurgery (SRS) has been an effective method to treat both benign and malignant intracranial lesions.[1,2] Patients receiving SRS for the treatment of multiple brain metastases may be treated using one of several treatment machines or machine configurations
To demonstrate the application of the k-means clustering algorithm to SRS treatment planning, we retrospectively selected 30 patients that had been recently treated using the single isocenter for multiple targets technique (Varian TrueBeam 2.0, Varian Medical Systems, Palo Alto, CA, USA)
The within-cluster sum of squares resulting from the unweighted version of the algorithm was, on average, less than that from the weighted version
Summary
Since its introduction over 60 yr ago, stereotactic radiosurgery (SRS) has been an effective method to treat both benign and malignant intracranial lesions.[1,2] Patients receiving SRS for the treatment of multiple brain metastases (mets) may be treated using one of several treatment machines or machine configurations These include Gamma Knife (Elekta, Crawley, UK), CyberKnife (Accuray Inc., Sunnyvale, CA, USA), or a linear accelerator (linac) fit with a stereotactic cone or with a multileaf collimator (MLC). Several targets may be included within a larger jaw-defined field utilizing a single isocenter.[3] Additional blocking is provided by the MLCs to achieve conformity around the targets In this way, multiple brain mets can be irradiated simultaneously, improving the efficiency of treatment by reducing the amount of time the radiation beam is on and the amount of time the patient is on the table. Reducing the latter is beneficial as the observed magnitude of intrafractional motion of some techniques has been shown to increase with the treatment duration.[4,5]
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