Abstract
Image Based Data Mining (IBDM) is a novel analysis technique allowing the interrogation of large amounts of routine radiotherapy data. Using this technique, unexpected correlations have been identified between dose close to the prostate and biochemical relapse, and between dose to the base of the heart and survival in lung cancer. However, most analyses to date have considered only dose when identifying a region of interest, with confounding variables accounted for post-hoc, most often using a multivariate Cox regression. In this work, we introduce a novel method to account for confounding variables directly in the analysis, by performing a Cox regression in every voxel of the dose distribution, and apply it in the analysis of a large cohort of lung cancer patients. Our method produces three-dimensional maps of hazard for clinical variables, accounting for dose at each spatial location in the patient. Results confirm that a region of interest exists in the base of the heart where those patients with poor performance status (PS), PS > 1, have a stronger adverse reaction to incidental dose, but that the effect changes when considering other clinical variables, with patient age becoming dominant. Analyses such as this will help shape future clinical trials in which hypotheses generated by the analysis will be tested.
Highlights
Radiotherapy (RT) is a commonly used treatment for cancer in which radiation is used to destroy tumor cells
Non Small-cell Lung Cancer (NSCLC) patients treated with routine curative intent (55Gy in 20 fractions) between 2010 and 2013 at a single academic cancer center was collected without selection, including CT imaging used in treatment planning, and the planned radiotherapy dose distribution
This work has performed, for the first time, survival analysis per-voxel across a large patient population, producing hazard ratio maps showing that clinical variables have a spatially varying hazard when dose across anatomy is taken into account
Summary
Radiotherapy (RT) is a commonly used treatment for cancer in which radiation is used to destroy tumor cells. The most common RT treatment is delivered using a beam of high energy radiation generated outside the patient (External Beam Radiotherapy, or EBRT) and directed into the patient toward the tumor. Since EBRT delivers dose from outside the patient, dose to normal tissue close to the tumor is unavoidable. It is well-known that dose in normal tissue leads to treatment side effects, and limits are set on the incidental dose deposited in normal tissue. DVHs require delineations, finding dose sensitive regions relies on having delineated the correct anatomy before analysis, limiting analyses based on the assumptions made before analysis
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