Background:
Significant tumour volume regression (TVR) during radiotherapy (RT) for non-small cell lung cancer (NSCLC) can occur during treatment. Advances in imaging faciliate on-treatment assessment of anatomical changes, offering an opportunity to identify when tumours shrink and adaptive RT (ART) strategies could be implemented to adjust the plan and better conform to the reduced target volume. Current clinical practice continues with the initial RT plan, but ART can potentially spare healthy lung tissue. However, the biological and geometric nature of TVR remains poorly understood, particularly regarding whether regression occurs through elastic or dissolving mechanisms and these factors should be elucidated prior to routinely adapting RT.
Aims and Hypotheses:
This project aims to characterise the pattern of TVR in NSCLC and determine its implications for adaptive radiotherapy decision-making. We hypothesise that elastic regression, where the surrounding lung tissue and tumour boundaries move cohesively, is associated with a lower risk of geographic miss and may represent a safer trigger for adaptive replanning. In contrast, dissolving regression, where tumour boundaries recede without concurrent movement of normal anatomy, may indicate residual microscopic disease and a higher risk of local recurrence.
Objectives:
Quantify and classify patterns of TVR in a cohort of eight NSCLC patients using weekly 4DCT imaging and gross tumour volume (GTV) delineations.
Differentiate elastic from dissolving regression using image registration and deformation field analysis.
Correlate regression patterns with peritumour density changes to identify potential indicators of microscopic residual disease.
Expected Outcomes:
This work will establish a systematic framework for identifying and characterising TVR patterns during lung RT. By distinguishing between elastic and dissolving regression, the study aims to inform evidence-based adaptive RT strategies, ensuring that plan adaptations occur under biologically safe conditions. Ultimately, these findings will contribute to optimising adaptive treatment protocols, improving local control, and reducing toxicity in patients with NSCLC.