Physiological imaging-defined, response-driven subvolumes of a tumor

To develop an image analysis framework to delineate the physiological imaging-defined subvolumes of a tumor in relating to treatment response and outcome.

Our proposed approach delineates the subvolumes of a tumor based on its heterogeneous distributions of physiological imaging parameters. The method assigns each voxel a probabilistic membership function belonging to the physiological parameter classes defined in a sample of tumors, and then calculates the related subvolumes in each tumor. We applied our approach to regional cerebral blood volume (rCBV) and Gd-DTPA transfer constant (K(trans)) images of patients who had brain metastases and were treated by whole-brain radiation therapy (WBRT). A total of 45 lesions were included in the analysis. Changes in the rCBV (or K(trans))-defined subvolumes of the tumors from pre-RT to 2 weeks after the start of WBRT (2W) were evaluated for differentiation of responsive, stable, and progressive tumors using the Mann-Whitney U test. Performance of the newly developed metrics for predicting tumor response to WBRT was evaluated by receiver operating characteristic (ROC) curve analysis.

The percentage decrease in the high-CBV-defined subvolumes of the tumors from pre-RT to 2W was significantly greater in the group of responsive tumors than in the group of stable and progressive tumors (P<.007). The change in the high-CBV-defined subvolumes of the tumors from pre-RT to 2W was a predictor for post-RT response significantly better than change in the gross tumor volume observed during the same time interval (P=.012), suggesting that the physiological change occurs before the volumetric change. Also, K(trans) did not add significant discriminatory information for assessing response with respect to rCBV.

The physiological imaging-defined subvolumes of the tumors delineated by our method could be candidates for boost target, for which further development and evaluation is warranted.