学术文献库

Adaptive Radiotherapy (ART) is an emerging technique for treating cancer patients which facilitates higher delivery accuracy and has the potential to reduce toxicity. However, ART is also resource-intensive, requiring extra human and machine time compared to standard treatment methods. In this analysis, we sought to predict the subset of node-negative cervical cancer patients who benefit the most from ART. CT images, initial plan data, and on-treatment Cone-Beam CT (CBCT) images for 20 retrospective cervical cancer patients were used to simulate doses from daily non-adaptive and adaptive techniques. We evaluated the correlation (R$^2$) between dose and volume metrics from initial treatment plans and the dosimetric benefits to the Bowel V$_{40Gy}$, Bowel V$_{45Gy}$, Bladder D$_{mean}$, and Rectum D$_{mean}$ from adaptive radiotherapy using reduced 3mm or 5mm CTV-to-PTV margins. The LASSO technique was used to identify the most predictive metrics for Bowel V$_{40Gy}$. The three highest performing metrics were used to build multivariate models with leave-one-out validation for Bowel V$_{40Gy}$. Patients with higher initial bowel doses were correlated with the largest decreases in Bowel V$_{40Gy}$ from daily adaptation (linear best fit R$^2$=0.77 for a 3mm PTV margin and R$^2$=0.8 for a 5mm PTV margin). Other metrics had intermediate or no correlation. Selected covariates for the multivariate model were differences in the initial Bowel V$_{40Gy}$. and Bladder D$_{mean}$ using standard versus reduced margins and the initial bladder volume. Leave-one-out validation had an R$^2$ of 0.66 between the predicted and true adaptive Bowel V$_{40Gy}$ benefits for both margins. This work could be used to prospectively triage cervical cancer patients, and presents a critical foundation for predicting benefits from daily adaptation that can be extended to other patient cohorts.