# Reliability of PET/CT shape and heterogeneity features in functional and morphological components of Non-Small Cell Lung Cancer tumors: a repeatability analysis in a prospective multi-center cohort

arXiv: https://arxiv.org/abs/1610.01390 · HTML: https://mlsanity.com/paper/1610.01390/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 5 Oct 2016.

## Built on by (most cited first, 3 of 3)

- [Generative Models Improve Radiomics Reproducibility in Low Dose CTs: A Simulation Study](https://mlsanity.com/paper/2104.15050/) (2021)
- [Generative Models Improve Radiomics Performance in Different Tasks and Different Datasets: An Experimental Study](https://mlsanity.com/paper/2109.02252/) (2021)
- [Improving the U-Net Configuration for Automated Delineation of Head and Neck Cancer on MRI](https://mlsanity.com/paper/2501.05120/) (2025)

## Abstract (arXiv)

Purpose: The main purpose of this study was to assess the reliability of shape and heterogeneity features in both Positron Emission Tomography (PET) and low-dose Computed Tomography (CT) components of PET/CT. A secondary objective was to investigate the impact of image quantization.Material and methods: A Health Insurance Portability and Accountability Act -compliant secondary analysis of deidentified prospectively acquired PET/CT test-retest datasets of 74 patients from multi-center Merck and ACRIN trials was performed. Metabolically active volumes were automatically delineated on PET with Fuzzy Locally Adaptive Bayesian algorithm. 3DSlicerTM was used to semi-automatically delineate the anatomical volumes on low-dose CT components. Two quantization methods were considered: a quantization into a set number of bins (quantizationB) and an alternative quantization with bins of fixed width (quantizationW). Four shape descriptors, ten first-order metrics and 26 textural features were computed. Bland-Altman analysis was used to quantify repeatability. Features were subsequently categorized as very reliable, reliable, moderately reliable and poorly reliable with respect to the corresponding volume variability. Results: Repeatability was highly variable amongst features. Numerous metrics were identified as poorly or moderately reliable. Others were (very) reliable in both modalities, and in all categories (shape, 1st-, 2nd- and 3rd-order metrics). Image quantization played a major role in the features repeatability. Features were more reliable in PET with quantizationB, whereas quantizationW showed better results in CT.Conclusion: The test-retest repeatability of shape and heterogeneity features in PET and low-dose CT varied greatly amongst metrics. The level of repeatability also depended strongly on the quantization step, with different optimal choices for each modality. The repeatability of PET and low-dose CT features should be carefully taken into account when selecting metrics to build multiparametric models.