Haralick texture feature analysis for Monte Carlo dose distributions of permanent implant prostate brachytherapy

TL;DR

This study applies Haralick texture analysis to 3D dose distributions in prostate brachytherapy, revealing how spatial dose variations relate to tissue calcifications and simulation conditions, providing insights into dose characterization.

Contribution

It introduces a quantitative method using Haralick features to analyze patient-specific dose distributions and interprets these measures in the context of physics and dosimetry.

Findings

Haralick features effectively quantify spatial dose differences.

Textural measures correlate with calcification levels and simulation conditions.

D90 dose metric shows weak correlation with spatial texture features.

Abstract

Purpose: Demonstrate quantitative characterization of 3D patient-specific absorbed dose distributions using Haralick texture analysis and interpret measures in terms of underlying physics and radiation dosimetry. Methods: Retrospective analysis is performed for 137 patients who underwent permanent implant prostate brachytherapy using two simulation conditions: ``TG186'' (realistic tissues including 0-3.8% intraprostatic calcifications; interseed attenuation) and ``TG43'' (water-model; no interseed attenuation). Haralick features (homogeneity, contrast, correlation, local homogeneity, entropy) are calculated using the original Haralick formalism, and a modified approach designed to reduce grey-level quantization sensitivity. Trends in textural features are compared to clinical dosimetric measures (D90; minimum absorbed dose to the hottest 90% of a volume) and changes in patient target volume % intraprostatic calcifications by volume (%IC). Results: Both original and modified measures quantify the spatial differences in absorbed dose distributions. Strong correlations between differences in textural measures calculated under TG43 and TG186 conditions and %IC are observed for all measures. For example, differences between measures of contrast and correlation increase and decrease respectively as patients with higher levels of %IC are evaluated, reflecting the large differences across adjacent voxels (higher dose in voxels with calcification) when calculated under TG186 conditions. Conversely, the D90 metric is relatively weakly correlated with textural measures, as it generally does not characterize the spatial distribution of absorbed dose. Conclusion: patient-specific 3D dose distributions may be quantified using Haralick analysis, and trends may be interpreted in terms of fundamental physics.