Does Time to Retreatment Matter? A Normal Tissue Complication Probability Model to Predict Radionecrosis After Repeat...

Area of Science:

• Radiation Oncology
• Medical Physics
• Neuro-oncology

Background:

• Stereotactic radiosurgery (SRS) is a key treatment for brain metastases (BMs).
• Repeat SRS is increasingly used for recurrent BMs, necessitating accurate risk assessment for normal tissue complications.
• Normal tissue complication probability (NTCP) models are crucial for optimizing treatment plans and minimizing toxicity.

Purpose of the Study:

• To develop and compare NTCP models for recurrent BMs treated with repeat single-fraction SRS.
• To incorporate time-dependent discounted prior dose into NTCP modeling for recurrent BMs.
• To evaluate radionecrosis risk following initial and repeat SRS interventions.

Main Methods:

• Three NTCP models (M0, M1-retreat, M1-combo) were developed using GammaKnife-based SRS data.
• Doses were converted to equivalent dose in 2-Gy fractions (EQD2) using a linear-quadratic model.
• The M1-combo model uniquely accounted for time-dependent discounted prior SRS dose using a modified Gompertzian function.

Main Results:

• All developed models demonstrated good data fit.
• Fitted parameters indicated lower dose tolerance (EQD250 ~88 Gy) and a more gradual dose-response (γ50 ~0.6/Gy) for recurrent BMs treated with repeat SRS (M1-retreat model).
• The M1-combo model, incorporating prior dose, showed an even more gradual response (γ50 ~0.4/Gy) and higher tolerance (EQD250 ~165 Gy).

Conclusions:

• Recurrent BMs exhibit reduced dose tolerance and a shallower dose-response curve to repeat SRS compared to initial treatments.
• Considering cumulative prior SRS dose further accentuates the gradual dose-response for recurrent BMs.
• Tailoring SRS retreatment strategies using NTCP modeling can potentially improve therapeutic outcomes and reduce complications.