Individual Image-based Normal Lung Radiosensitivity as Potential Biomarker to Individualize Reirradiation

Re-irradiation (reRT) is increasingly common but lacks clear guidance due to challenges in fitting traditional toxicity models. This pilot study investigates lung density changes on CT as a potential image-based lung radiosensitivity (iRS) biomarker to guide reRT.

We analyzed cancer patients treated with two thoracic radiotherapy (RT) courses. Planning and follow-up CTs were used to assess lung density changes. Normal lung receiving EQD2 (ᵅ/ᵦ =3) ≥10 Gy from one course (single-irradiated) or both courses (double-irradiated) were considered separately. iRS was quantified as the slope (HU/Gy₃) of normal lung HU change as a function of dose via dose-response curve fitting, and associations between iRS and clinical/treatment factors were tested using non-parametric statistics.

Fifty-one patients receiving 102 RT courses were included. iRS was conserved across RT courses within individual patients in single-irradiated lung subregions (r=0.34, p=0.047) but not in double-irradiated subregions (r=0.17, p=0.33). A shorter RT interval (<9 months) and hypofractionation at the first RT (RT1) were significantly associated with increased iRS at reRT in double-irradiated regions (ρ=0.53, p=0.001; ρ=0.37, p=0.028).

This pilot study employed an imaging biomarker of normal lung radiosensitivity to demonstrate a significant correlation of individual lung radiosensitivity between treatment courses. Radiosensitivity at reRT is shaped by treatment interval and dose overlap, with single-irradiated regions showing conserved iRS across courses, while double-irradiated regions exhibited stronger response at reRT with shorter treatment intervals. This illustrates the potential of using biomarkers of normal tissue radiation response observed at the first treatment to guide reirradiation.