Optimal Radiation Therapy Fractionation Regimens for Early-Stage Non-Small Cell Lung Cancer

Realistic closed-form TCP model including cell sensitivity dependence

Objective.To develop a mechanistic extension of the Poisonnian linear quadratic (LQ) tumor control probability (TCP) formulation by incorporating tumor volume and cell sensitivity inter-patient variations which can be applied to a cohort of patients.Approach.A novel closed-form expression for TCP was derived from first principles, incorporating inter-individual variations in tumor volume and cell sensitivity within the LQ model of tumor control. Furthermore, an exponential time dependence of local control (LC) in terms of TCP was introduced. The proposed model was fitted to 22 datasets of early-stage non-small cell lung cancer (NSCLC), encompassing various dose regimes, tumor volumes, treatment duration and outcome values over different follow-up periods. A log-likelihood algorithm was employed for the fitting process.Main results.The fit of the population TCP model, which adopts tumor volume and cell radiosensitivities uniformly distributed, resulted in a cell sensitivity value ofα¯U=0.37 [0.13-0.47]Gy-1, its corresponding bandwidthΔα= 0.37 [0.04-0.42] Gy-1,β =0. 015 [0.009-0.039] Gy-2, the characteristic time at which LC reaches TCP,t1/2= 19.6 [7.3-90.8] months, and the cell population doubling timeTd= 2.0 [0.2 4.9] days. The parametersα¯U,Δα andβwere found to be significant (p< 0.05), whilet1/2andTdproved non-statistically significant for the model under Wald test. This model describes data from 1675 lesions and offers a better fit compared to alternative approaches incorporating Gaussian or log-normal radiosensitivity distributions.Significance.A closed form of TCP population model was derived by including cell sensitivity and tumor size heterogeneities. A relation between TCP and LC was established by modeling LC as an exponential function of follow-up time. The derived TCP population model facilitates direct application to clinical datasets and was tested against NSCLC clinical data. Individual TCP can be estimated from the radiobiological parameters of the population.

Comparing the Robustness of Intensity-modulated Proton Therapy and Proton-arc Therapy Against Interplay Effects of 4D Robust-optimised Plans for Lung Stereotactic Body Radiotherapy

AIMS

To assess the robustness of 4D-optimised IMPT and PAT plans against interplay effects in non-small cell lung cancer (NSCLC) patients with respiratory motion over 10 mm, and to provide insights into the use of proton-based stereotactic body radiotherapy (SBRT) for lung cancer with significant tumour movement.

MATERIALS AND METHODS

Fourteen patients with early-stage NSCLC and tumour motion >10 mm were selected. Three hypofraction regimens were generated using 4D robust optimisation with the IMPT and PAT techniques. The nominal plan qualities for both techniques were compared, and their robustness against setup and range uncertainties was evaluated. 4D dynamic dose and the 4D static dose were generated to calculate ΔIMR(%) for interplay effects.

RESULTS

PAT plans demonstrated superior target metrics such as D95 and D2, and offered enhanced protection for organs at risk (OARs), particularly in lung metrics, across multiple fractionation schemes (p < 0.05). The robustness of target coverage against setup and range uncertainties was better in PAT plans than IMPT, with average pass rates of 97.8% and 95.4%, respectively (p < 0.01). The interplay effect significantly affected target metrics in single-fraction plans, decreasing with more fractions, while its effect on OAR metrics was minimal. Median values for single-fraction plans were: ΔID98GTV was -3% for IMPT and -0.7% for PAT (p < 0.01); ΔID95GTV was -2.4% for IMPT and -0.6% for PAT (p < 0.01); ΔID2GTV was 3.2% for IMPT and 0.9% for PAT (p < 0.05). The interplay effects resulted in median homogeneity index deviations of 9.1% and 2% for the IMPT and PAT plans, respectively (p < 0.01). Different starting phases affected IMPT more significantly than PAT.

CONCLUSION

PAT demonstrated greater robustness to interplay effects than IMPT for hypofractionated treatments of early-stage NSCLC, particularly in single-fraction schemes. Additionally, PAT showed good resilience to variations in different starting phases.

Histology-driven hypofractionated radiation therapy schemes for early-stage lung adenocarcinoma and squamous cell carcinoma

BACKGROUND AND PURPOSE

Histology was found to be an important prognostic factor for local tumor control probability (TCP) after stereotactic body radiotherapy (SBRT) of early-stage non-small-cell lung cancer (NSCLC). A histology-driven SBRT approach has not been explored in routine clinical practice and histology-dependent fractionation schemes remain unknown. Here, we analyzed pooled histologic TCP data as a function of biologically effective dose (BED) to determine histology-driven fractionation schemes for SBRT and hypofractionated radiotherapy of two predominant early-stage NSCLC histologic subtypes adenocarcinoma (ADC) and squamous cell carcinoma (SCC).

MATERIAL AND METHODS

The least-χ2 method was used to fit the collected histologic TCP data of 8510 early-stage NSCLC patients to determine parameters for a well-developed radiobiological model per the Hypofractionated Treatment Effects in the Clinic (HyTEC) initiative.

RESULTS

A fit to the histologic TCP data yielded independent radiobiological parameter sets for radiotherapy of early-stage lung ADC and SCC. TCP increases steeply with BED and reaches an asymptotic maximal plateau, allowing us to determine model-independent optimal fractionation schemes of least doses in 1-30 fractions to achieve maximal tumor control for early-stage lung ADC and SCC, e.g., 30, 44, 48, and 51 Gy for ADC, and 32, 48, 54, and 58 Gy for SCC in 1, 3, 4, and 5 fractions, respectively.

CONCLUSION

We presented the first determination of histology-dependent radiobiological parameters and model-independent histology-driven optimal SBRT and hypofractionated radiation therapy schemes for early-stage lung ADC and SCC. SCC requires substantially higher radiation doses to maximize tumor control than ADC, plausibly attributed to tumor genetic diversity and microenvironment. The determined optimal SBRT schemes agree well with clinical practice for early-stage lung ADC. These proposed optimal fractionation schemes provide first insights for histology-based personalized radiotherapy of two predominant early-stage NSCLC subtypes ADC and SCC, which require further validation with large-scale histologic TCP data.

Optimal hypofractionated radiation therapy schemes for early-stage hepatocellular carcinoma

PURPOSE

Stereotactic body radiation therapy (SBRT) has been emerging as an efficacious and safe treatment modality for early-stage hepatocellular carcinoma (HCC), but optimal fractionation regimens are unknown. This study aims to analyze published clinical tumor control probability (TCP) data as a function of biologically effective dose (BED) and to determine radiobiological parameters and optimal fractionation schemes for SBRT and hypofractionated radiation therapy of early-stage HCC.

MATERIAL AND METHODS

Clinical 1- to 5-year TCP data of 4313 patients from 41 published papers were collected for hypofractionated radiation therapy at 2.5-4.5 Gy/fraction and SBRT of early-stage HCC. BED was calculated at isocenter using three representative radiobiological models developed per the Hypofractionated Treatment Effects in the Clinic (HyTEC) initiative. Radiobiological parameters were determined from a fit to the TCP data using the least χ2 method with one set of model parameters regardless of tumor stages or Child-Pugh scores A and B.

RESULTS

The fits to the clinical TCP data for SBRT of early-stage HCC found consistent α/β ratios of about 14 Gy for all three radiobiological models. TCP increases sharply with BED and reaches an asymptotic maximal plateau, which results in optimal fractionation schemes of least doses to achieve asymptotic maximal tumor control for SBRT and hypofractionated radiation therapy of early-stage HCC that are found to be model-independent.

CONCLUSION

From the fits to the clinical TCP data, we presented the first determination of radiobiological parameters and model-independent optimal fractionation regimens in 1-20 fractions to achieve maximal tumor control whenever safe for SBRT and hypofractionated radiation therapy of early-stage HCC. The determined optimal fractionation schemes agree well with clinical practice for SBRT of early-stage HCC. However, most existing hypofractionated radiation therapy schemes of 3-5 Gy/fraction are not optimal, higher doses are required to maximize tumor control, further validation of these findings is essential with clinical TCP data.