Spatial Analysis of Tumor Sub-Volume Using Multi-Modality Images for Rhabdomyosarcoma in Children

Abstract

To compare imaging of multi-modality for evaluating children patients with rhabdomyosacroma. To analyze the spatial relationship of tumor volumes between different imaging techniques. To identify the high risk sub-regions in tumor volumes. 16 pediatric patients with rhabdomyosarcoma underwent imaging with PET/CT, T2-MRI, ADC and spectral CT with iodine contrast. From the spectral CT, the volumetric iodine density and effective Z of patients’ images were extracted. Tumor/GTV contours were generated by clinical physicians on simulation CT. The images of different modalities were rigidly registered on the simulation CTs and the tumor contours were populated to other images in the same coordinate of simulation CTs. The tumor subvolumes of modalities were defined by isothreshold and fuzzy mean clustering. The spatial relations of these sub regions including similarity and incongruity were then evaluated with Dice’s coefficient and ANOVA. The modalities can be categorized with two groups. Group 1: ADC and T2-MRI; Group 2: iodine density, effective Z from spectral CT and PET. In the same patient of most cases, the sub-regions of ADC and T2 had high similarity. The sub-regions of iodine, effective Z and PET had high similarity. The sub-region of ADC showed a disjoint spatial relation with the sub-region of iodine density, e.g. the high iodine density signal of the sub region expressed a low ADC signal in the same region. The fuzzy mean clustering showed the better performance of sub volume determination. The average similarity of between and T2 images has Dice coefficient of 0.88±0.082. The average similarity of between iodine density, effective Z from spectral CT and PET images has Dice coefficient of 0.78±0.042. The average similarity of between ADC and iodine density images has Dice coefficient of 0.14±0.12. The sub-regions of tumor volumes were investigated between images of five modalities. Each modality provides different type of functional imaging based on physical properties of tumor tissues. The spatial correlation of sub-volumes in different modalities can help physicians identify the high risk sub-region of GTV for treatment planning.