Semi-automated volumetric analysis of artificial lymph nodes in a phantom study

Purpose: Quantification of tumour burden in oncology requires accurate and reproducible image evaluation. The current standard is one-dimensional measurement (e.g. RECIST) with inherent disadvantages. Volumetric analysis is discussed as an alternative for therapy monitoring of lung and liver metastases. The aim of this study was to investigate the accuracy of semi-automated volumetric analysis of artificial lymph node metastases in a phantom study.

Materials and methods: Fifty artificial lymph nodes were produced in a size range from 10 to 55mm; some of them enhanced using iodine contrast media. All nodules were placed in an artificial chest phantom (artiCHEST®) within different surrounding tissues. MDCT was performed using different collimations (1-5 mm) at varying reconstruction kernels (B20f, B40f, B60f). Volume and RECIST measurements were performed using Oncology Software (Siemens Healthcare, Forchheim, Germany) and were compared to reference volume and diameter by calculating absolute percentage errors.

Results: The software performance allowed a robust volumetric analysis in a phantom setting. Unsatisfying segmentation results were frequently found for native nodules within surrounding muscle. The absolute percentage error (APE) for volumetric analysis varied between 0.01 and 225%. No significant differences were seen between different reconstruction kernels. The most unsatisfactory segmentation results occurred in higher slice thickness (4 and 5 mm). Contrast enhanced lymph nodes showed better segmentation results by trend.

Conclusion: The semi-automated 3D-volumetric analysis software tool allows a reliable and convenient segmentation of artificial lymph nodes in a phantom setting. Lymph nodes adjacent to tissue of similar density cause segmentation problems. For volumetric analysis of lymph node metastases in clinical routine a slice thickness of ≤3mm and a medium soft reconstruction kernel (e.g. B40f for Siemens scan systems) may be a suitable compromise for semi-automated volumetric analysis.