Technical note: Personalized treatment gating thresholds in frameless stereotactic radiosurgery using predictions of dosimetric fidelity and treatment interruption

• Published in: Medical physics (Lancaster) 2021-12, Vol.48 (12), p.8045-8051
• Main Authors: MacDonald, R. Lee, Lee, Young, Schasfoort, Jannie, Soliman, Hany, Sahgal, Arjun, Ruschin, Mark
• Format: Article
• Language: English
• Subjects: dose reconstruction; Humans; motion management; Precision Medicine; Radiometry; Radiosurgery; Radiotherapy Dosage; Radiotherapy Planning, Computer-Assisted; Retrospective Studies; stereotactic radiosurgery
• ISSN: 0094-2405; 2473-4209
• DOI: 10.1002/mp.15331

Purpose Gamma Knife Icon (GKI) enables a user‐defined gating threshold for intrafraction motion during stereotactic radiosurgery (SRS). An optimal threshold would ensure dosimetric fidelity of the planned distribution and minimize treatment time extension by gating. A prediction of motion characteristics for a patient based on a retrospective database of motion traces could be beneficial to evaluating the choice of gating threshold. A short acquisition of motion may help to define a personalized threshold that balances dosimetric accuracy and treatment length. This study aims to evaluate the performance of a prediction of motion and the resultant dosimetric consequences for a range of motion gating thresholds. Methods A database of 2552 motion traces (776 patients) was analyzed using previously published methods to characterize patient intrafraction motion on the GKI. For a selection of six fractionated SRS patient cases (two patients with single brain metastasis, four vestibular schwannomas), a 10‐min sample of motion was used to classify motion and identify traces in the database with similar metrics. The similar motion traces were used to perform a predictive reconstruction of the selected patient's delivered dose for a range of motion thresholds. The remaining fractions were reconstructed and compared to that predicted. From the six cases, 26 fractions were used to predict the number of interruptions (n = 26), change in target coverage (n = 26), and change in brainstem maximum dose (vestibular cases only, n = 20). The difference between mean predicted and reconstructed values was compared for accuracy. Results The difference between mean prediction and reconstructed values was 0.32 ± 0.38% in target coverage, 2.36 ± 5.06 interruptions, and 0.15 ± 0.24 Gy for the brainstem maximum dose. Sixty‐seven of the 72 predictions (26 coverage, 26 interruptions, and 20 brainstem maximum dose) were within one standard deviation of the predicted mean. Conclusions Large databases of motion traces were used to characterize patient performance and predict motion performance. Dosimetric deterioration due to motion and extension of treatment duration can be predicted in some cases using only a short acquisition of motion and the treatment plan. This reconstruction may provide benefit in generating a patient‐specific motion threshold.