3136 - Radiobiological Modeling of Dose Distributions over Time and Space to Predict Tumor Control and Normal Tissue Response in Spatially Fractionated (GRID) Therapy to Bulky Breast and Chest Wall Tumors
Presenter(s)
Y. R. Somnay1, H. Zhang2, C. Hyde3, and R. Boggula1; 1Wayne State University, Detroit, MI, 2Department of Radiation Oncology, University of Southern California, Los Angeles, CA, 3Wayne State University,, Detroit, MI
Purpose/Objective(s):
Spatially fractionated radiotherapy (GRID) enables therapeutic doses to bulky tumors otherwise limited by dose-volume constraints that risk exceeding organ-at-risk tolerances. In neglected, inoperable breast and chest wall tumors, GRID therapy provides a boost strategy that complements uniform radiotherapy and offers an alternative to palliative regimens. The radiobiological basis of spatial fractionation suggests normal tissue sparing due to interspersed high-dose peaks. This study investigates the impact of spatial dose fractionation on tumor control and normal tissue response using radiobiological modeling that accounts for dose heterogeneity.
Materials/Methods:
We analyzed dose distributions from 5 women treated with a 15Gy GRID boost to bulky breast/chest wall tumors, followed by a mean 45.7Gy EQD2 whole-breast radiotherapy regimen. Fractional GRID dose distributions were modeled via differential dose-volume histograms (dDVH) to reflect heterogeneity. A modified linear-quadratic model incorporating a dose-protraction factor G accounted for sublethal damage repair. Surviving fractions were computed per dose interval and summated to derive equivalent uniform doses (EUD) for breast tumors (a/ß=3.8-10) and normal tissues (a=0.366, ß=0.118; a=0.211, ß=0.068). Five test plans replicated uniform EUD-equivalent doses using opposed tangents with field-in-field modulation. To evaluate tumor control, we developed a tumor control probability (TCP) model using a modified linear-quadratic (MLQ) approach, performing serial surviving fraction (SF) product calculations per dose bin before dose-weighted integration to preserve spatial and temporal effects on predicted cell kill.
Results:
Mean follow-up was 17.2 months. All patients had a robust local response, resolution of mass effect symptoms, and minimal toxicity. Mean EUD for GRID plans ranged from 323.3-327.8cGy, with predicted tumor cell survival of 29.4-33.0%. Normal tissue survival was higher in GRID than uniform-dose plans in the boost [18.1-30.0% vs. 8.9-24.1%] & whole-breast [41.6-51.5% vs. 15.6-39.9%] (p<0.001). NTCP modeling predicted no increased risk for lung/skin toxicity, cardiac toxicity, or fibrosis.
Conclusion:
Radiobiological modeling supports GRID therapy’s feasibility, demonstrating equivalent tumor control with improved normal tissue sparing. Our TCP model used an MLQ approach with sequential SF products between fractions and the large field with boost plans. Discrete weighted integration was performed after SF product calculations between fractions and spatial dose contributions, ensuring accurate tumor control modeling. These findings support GRID’s integration into breast radiotherapy. Further studies with larger cohorts and long-term follow-up are needed to refine tumor control and NTCP estimates.