Perfusion parameters as potential imaging biomarkers for the early prediction of radiotherapy response in a rat tumor model.

Purpose: We aimed to compare various tumor-related radiologic morphometric changes and computed tomography (CT) perfusion parameters before and after treatment, and to determine the optimal imaging assessment technique for the prediction of early response in a rat tumor model treated with radiotherapy.

Methods: Among paired tumors of FN13762 murine breast cancer cells implanted bilaterally in the necks of eight Fischer rats, tumors on the right side were treated with a single 20 Gy dose of radiotherapy. Perfusion CT studies were performed on day 0 before radiotherapy, and on days 1 and 5 after radiotherapy. Variables based on the size, including the longest diameter, tumor area, and volume, were measured. Quantitative perfusion analysis was performed for the whole tumor volume and permeabilities and blood volumes (BVs) were obtained. The area under the curve (AUC) difference in the histograms of perfusion parameters and texture analyses of uniformity and entropy were quantified. Apoptotic cell density was measured on pathology specimens immediately after perfusion imaging on day 5.

Results: On day 1 after radiotherapy, differences in size between the irradiated and nonirradiated tumors were not significant. In terms of percent changes in the uniformity of permeabilities between tumors before irradiation and on day 1 after radiotherapy, the changes were significantly higher in the irradiated tumors than in the nonirradiated tumors (0.085 [-0.417, 0.331] vs. -0.131 [-0.536, 0.261], respectively; P = 0.042). The differences in AUCs of the histogram of voxel-by-voxel vascular permeability and BV in tumors between day 0 and day 1 were significantly higher in treated tumors compared with the control group (permeability, 21.4 [-2.2, 37.5] vs. 9.5 [-8.9, 33.8], respectively, P = 0.030; BV, 52.9 [-6186.0, 419.2] vs. 11.9 [-198.3, 346.7], respectively, P = 0.049). Apoptotic cell density showed a significantly positive correlation with the AUC difference of BV, the percent change of uniformity in permeability and BV (r=0.202, r=0.644, and r=0.706, respectively).

Conclusion: By enabling earlier tumor response prediction than morphometric evaluation, the histogram analysis of CT perfusion parameters appears to have a potential in providing prognostic predictive information in an irradiated rat model.