ABSTRACT
Background: Adaptive radiation therapy (ART) refers to redesigning of radiation therapy (RT) treatment plans with respect to dynamic changes in tumor size and location throughout the treatment course. In this study, we performed a comparative volumetric and dosimetric analysis to investigate the impact of ART for patients with limited-stage small cell lung cancer (LS-SCLC). Methods: Twenty-four patients with LS-SCLC receiving ART and concomitant chemotherapy were included in the study. ART was performed by replanning of patients based on a mid-treatment computed tomography (CT)-simulation which was routinely scheduled for all patients 20� days after the initial CT-simulation. While the first 15 RT fractions were planned using the initial CT-simulation images, the latter 15 RT fractions were planned using the mid-treatment CT-simulation images acquired 20� days after the initial CT-simulation. In order to document the impact of ART, target and critical organ dose-volume parameters acquired from this adaptive radiation treatment planning (RTP) were compared with the RTP based solely on the initial CT-simulation to deliver the whole RT dose of 60 Gy. Results: Statistically significant reduction was detected in gross tumor volume (GTV) and planning target volume (PTV) during the conventionally fractionated RT course along with statistically significant reduction in critical organ doses with incorporation of ART. Conclusion: One-third of the patients in our study who were otherwise ineligible for curative intent RT due to violation of critical organ dose constraints could be treat
ABSTRACT
Objective@#To explore the differences and correlation between the target volumes based on deformation registration (DIR) using preoperative prone diagnostic magnetic resonance (MR) imaging and postoperative prone computed tomography (CT) simulation imaging for patients undergoing breast-conserving surgery (BCS).@*Methods@#Eighteen breast cancer patients suitable for external-beam partial breast irradiation (EB-PBI) after BCS were enrolled. Preoperative prone diagnostic MR and postoperative prone CT scan sets were acquired during free breathing for all patients. The gross tumor volume (GTV) delineated on the preoperative diagnostic MR images was defined as GTVMRI, the clinical target volumes (CTVMRI+ 1 and CTVMRI+ 2)were defined as 10 and 20 mm margins around the GTVMRI, and the planning target volume (PTVMRI+ 1 and PTVMRI+ 2) were defined as 15 and 25 mm margins around the GTVMRI, respectively. Tumor bed (TB) delineated on the postoperative prone CT simulation images acquired during free breathing was defined as GTVTB, CTV and PTV were defined as 10 and 15 mm margins around the GTVTB, respectively. The target volume of the whole breast contoured on the MR and CT images were defined as CTVBreast-MRI and CTVBreast-CI, respectively. The MR and CT images were registered deformably in MIM software system.@*Results@#The GTVTB, CTVTB and PTVTB were significantly greater than GTVMRI, GTVMRI+ 1 and PTVMRI+ 1, respectively (Z=-3.593, -3.593, -2.983, P<0.05). Meanwhile, the CTVTB and PTVTB were significantly less than the CTVMRI+ 2 and PTVMRI+ 2, respectively(Z=-2.722, -2.853, P<0.05). The conformal index (CI) and degree of inclusion (DI) of GTVTB-GTVMRI, GTVTB-CTVMRI+ 1, CTVTB-GTVMRI and CTVTB-GTVMRI+ 1 based on center-coincidence of the compared targets were better than those based on DIR of the thorax(Z=-3.724、-3.724、-2.591、-3.593, P<0.05; Z=-3.724、-3.724、-3.201、-3.724, P<0.05).@*Conclusions@#For the patients enrolled for prone EB-PBI, target volumes delineated on the preoperative prone MR images were significantly smaller compared to that on the postoperative prone CT images, but a statistically significant positive correlation was found between the MR and CT target volumes. There were still relatively poor spatial overlap whether for the whole breast or the targets between the preoperative prone diagnostic MR images and the postoperative prone simulation CT images based on DIR. Therefore, it is infeasible to guide postoperative EB-PBI target delineation using the preoperative prone diagnostic MR images.