Purpose/Objective(s):Dose volume histograms are a key and valuable tool when comparing treatment alternatives and as predictor of treatment outcomes in radiotherapy. The high number of region of interest and target volumens in actual radiotherapy makes necessary use specifics tools for reporting and analyze of DVH. In this work we show a tool to maintain a DVH database, to generate population based DVH and relevant statistics. Population based DVH will be used as reference in treatment planning process.Materials/Methods:We have used our DVH database with more than 8000 treatments to generate population DVH for several treatment sites. DVHs for regions of interest and PTVs were analyzed calculating mean histogram and 10% and 90% percentile histograms. Probability distribution of relevant evaluation parameters were calculated using these data (i.e V20, mean dose, NTCP⋯). Mean and percentile histograms are established as reference histograms in our reporting tool, allowing the interactive comparison of actual treatment DVH versus database. It is possible to incorporate DVH from several treatment planning systems.Results:Plotting database DVH allows to fast identify outliers, and observe variability in OARs and homogeneity in PTVs. Use of this tool warrants for high homogeneity clinical dosimetry, that is really important when participating in clinical trials. With these data it is possible to correlate treatment outcomes with planning data. Comparison of actual patient with reference DVH is straightforward using our application. Volume at a dose, dose at a volume, NTCP, EUD, mean dose are successfully calculated using DVH data. Comparison allows visual and numeric evaluation of DVH using per protocol standards. Treatment plans that deviate from population histograms will require specific and comprehensive quality assurance to identify reason of such differences.Conclusions:Population DVH comparison allows for a higher level of quality assurance of clinical dosimetry process and has proven to be a useful research tool for radiation therapy. Outlier treatments are easily identified. Study of population based DVHs allows identification of better predictive parameters to correlate with clinical outcomes.
Perez-Rozos, A,
Dose Volume Histograms Database, Reporting and Analyzing Software for Radiation Therapy. Radiological Society of North America 2014 Scientific Assembly and Annual Meeting, - ,Chicago IL.
http://archive.rsna.org/2014/14042059.html
