Integration of the M6 Cyberknife in the Moderato Monte Carlo platform and prediction of beam parameters using machine learning

Radiobiological evaluation considering the treatment time with stereotactic radiosurgery for brain metastases

Objective

We evaluated the radiobiological effect of the irradiation time with the interruption time of stereotactic radiosurgery (SRS) using CyberKnife® (CK) systemfor brain metastases.

Methods

We used the DICOM data and irradiation log file of the 10 patients with brain metastases from non-small-cell lung cancer (NSCLC) who underwent brain SRS. We defined the treatment time as the sum of the dose-delivery time and the interruption time during irradiations, and we used a microdosimetric kinetic model (MKM) to evaluate the radiobiological effects of the treatment time. The biological parameters, i.e. α0, β0, and the DNA repair constant rate (a + c), were acquired from NCI-H460 cell for the MKM. We calculated the radiobiological dose for the gross tumor volume (GTVbio) to evaluate the treatment time's effect compared with no treatment time as a reference. The D95 (%) and the Radiation Therapy Oncology Group conformity index (RCI) and Paddick conformity index (PCI) were calculated as dosimetric indices. We used several DNA repair constant rates (a + c) (0.46, 1.0, and 2.0) to assess the radiobiological effect by varying the DNA repair date (a + c) values.

Results

The mean values of D95 (%), RCI, and PCI for GTVbio were 98.8%, 0.90, and 0.80, respectively, and decreased with increasing treatment time. The mean values of D95 (%), RCI, and PCI of GTVbio at 2.0 (a+c) value were 94.9%, 0.71, and 0.49, respectively.

Conclusion

The radiobiological effect of the treatment time on tumors was accurately evaluated with brain SRS using CK.

Advances in knowledge

There has been no published investigation of the radiobiological impact of the longer treatment time with multiple interruptions of SRS using a CK on the target dose distribution in a comparison with the use of a linac. Radiobiological dose assessment that takes into account treatment time in the physical dose in this study may allow more accurate dose assessment in SRS for metastatic brain tumors using CK.

Validation of Monte Carlo dose calculation algorithm for CyberKnife multileaf collimator

PURPOSE

To commission and evaluate the Monte Carlo (MC) dose calculation algorithm for the CyberKnife equipped with a multileaf collimator (MLC).

METHODS

We created a MC model for the MLC using an integrated module of the CyberKnife treatment planning software (TPS). Two parameters could be optimized: the maximum energy and the source full width at half-maximum (FWHM). The optimization was performed by minimizing the differences between the measured and the MC calculated tissue phantom ratios and profiles. MLC plans were calculated in the TPS with the MC algorithm and irradiated on different phantoms. The dose was measured using an A1SL ionization chamber and EBT3 Gafchromic films, and then compared to the TPS dose to obtain dose differences (ΔD). Finally, patient-specific quality assurances (QA) were performed with global gamma index criteria of 3%/1 mm.

RESULTS

The maximum energy and source FWHM showing the best agreement with measurements were 6.4 MeV and 1.8 mm. The output factors calculated with these parameters gave an agreement within ±1% with measurements. The ΔD showed that MC model systematically underestimated the dose with an average of -1.5% over all configurations tested. For depths deeper than 12 cm, the ΔD increased, up to -3.0% (maximum at 15.5 cm depth).

CONCLUSIONS

The MC model for MLC of CyberKnife is clinically acceptable but underestimates the delivered dose by an average of -1.5%. Therefore, we recommend using the MC algorithm with the MLC only in heterogeneous regions and for shallow-seated tumors.