ABSTRACT
Purpose: The purpose of this study was to evaluate the doses delivered to the brachytherapy (BT) target volume and organs at risk from two-dimensional X-ray-based plans on magnetic resonance imaging (MRI) and to compare these doses with the corresponding doses from the image-based optimized plans. Materials and Methods: Twenty patients with cervical cancer treated with chemoradiation and BT were included in this study. All patients had two sets of treatment plans generated for the first fraction of BT. Volume doses resulting from MRI-based optimized plans were compared with the corresponding doses from standard “Point A” prescription plans. Results: There was statistically significant difference between the two planning modalities for the mean high-risk clinical target volume (HRCTV) D90 doses (P = 0.0014) although mean D2cc of bladder (P = 0.1667) and rectum (P = 0.051) was not different. Standard plans with a prescription dose of 7 Gy to Point A delivered a mean HRCTV D90 of 10.07 Gy in patients with no gross residual disease at the time of BT, which was very similar to the mean dose from MR-based plans (MRI 10.02 Gy and standard 10.07 Gy). The only factor seen affecting dose distribution in this group was the applicator geometry. Standard plans failed to deliver HRCTV D90 doses of >8.5 Gy in all patients with gross residual disease. The doses were <7.00 Gy to the HRCTV in three patients who had maximum residual diseases at the time of BT. Conclusion: Conventional X-ray-based plans with moderate Point A doses deliver HRCTV D90 comparable to MRI-based plans in patients with no residual disease, and centrally placed residual disease, provided proper applicator placement and ideal geometry can be ensured. Soft-tissue image-based BT dose optimization ought to be considered in all patients with gross residual disease at the time of brachytherapy.
ABSTRACT
The association between an exposure of interest (risk factor) and a disease may be confounded by the action of other separate factors as well as by interactions between risk factors exerting an impact. Crude measures of effect may be misleading in such situations. Levels of the potential confounding factor could be estimated using stratified analysis. Uniformity of the stratum-specific effect estimates can be assessed by performing chi-square tests for heterogeneity. If the effect is uniform across strata, we can calculate a pooled adjusted summary estimate of the effect using the Mantel-Haenzel (M-H) method. Confidence intervals for the adjusted estimate and the M-H chi-square test are calculated to assess the significance. If the effect is not uniform (presence of interaction), we report stratum-specific estimates, confidence intervals and chi-square for each estimate. In the present paper, assessment of the level of confounding and interaction between risk factors are illustrated using a case-control study of lung cancer conducted at the Regional Cancer Centre, Trivandrum.