CT radiomics to predict Deauville score 4 positive and negative Hodgkin lymphoma manifestations.
Laura Jacqueline JensenJulian Manuel Michael RogaschDamon KimJuliana RießelmannChristian FurthHolger AmthauerBernd HammIngo G SteffenThomas ElgetiSebastian N NagelPublished in: Scientific reports (2022)
18F-FDG-PET/CT is standard to assess response in Hodgkin lymphoma by quantifying metabolic activity with the Deauville score. PET/CT, however, is time-consuming, cost-extensive, linked to high radiation and has a low availability. As an alternative, we investigated radiomics from non-contrast-enhanced computed tomography (NECT) scans. 75 PET/CT examinations of 43 patients on two different scanners were included. Target lesions were classified as Deauville score 4 positive (DS4+) or negative (DS4-) based on their SUVpeak and then segmented in NECT images. From these segmentations, 107 features were extracted with PyRadiomics. All further statistical analyses were then performed scanner-wise: differences between DS4+ and DS4- manifestations were assessed with the Mann-Whitney-U-test and single feature performances with the ROC-analysis. To further verify the reliability of the results, the number of features was reduced using different techniques. The feature median showed a high sensitivity for DS4+ manifestations on both scanners (scanner A: 0.91, scanner B: 0.85). It furthermore was the only feature that remained in both datasets after applying different feature reduction techniques. The feature median from NECT concordantly has a high sensitivity for DS4+ Hodgkin manifestations on two different scanners and thus could provide a surrogate for increased metabolic activity in PET/CT.
Keyphrases
- pet ct
- hodgkin lymphoma
- contrast enhanced
- computed tomography
- positron emission tomography
- deep learning
- magnetic resonance imaging
- diffusion weighted
- machine learning
- image quality
- magnetic resonance
- dual energy
- diffusion weighted imaging
- end stage renal disease
- ejection fraction
- newly diagnosed
- prognostic factors
- peritoneal dialysis
- lymph node metastasis
- high resolution