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2026 article

Radiomics on 177 Lu-DOTATATE Posttreatment Scans: Feasibility, Preprocessing Optimization, and Planar–SPECT Comparison

1Citations signalées, ce qui n’est pas une note de qualité
5Institutions déclarées
2Pays d’affiliation déclarés

Rattachement africain : it, fr. Niveau de preuve : code pays fourni par la source.

Le résumé fourni par la source

177Lu-DOTATATE peptide receptor radionuclide therapy (PRRT) is an established therapeutic option for patients with neuroendocrine tumors (NETs). Although radiomics has been increasingly applied in NET research, it was developed almost exclusively using 68Ga-DOTATOC PET imaging, whereas PRRT-related scintigraphic acquisitions remain largely unexplored. This study evaluates the feasibility of extracting hepatic radiomic features from posttreatment whole-body planar scintigraphic (WBS) and tomographic (SPECT) scans, enabling the optimization of preprocessing strategies and a direct comparison of radiomic profiles between imaging modalities. Methods: We conducted a retrospective analysis of data for 49 patients with well-differentiated, progressive metastatic gastroenteropancreatic NETs from 2 centers. All patients underwent posttreatment imaging within 2 d after each 177Lu-DOTATATE PRRT cycle, for a total of 183 WBS and 108 SPECT scans. Preprocessing operations included image-intensity normalization, dividing each image by the mean counts of a region of interest positioned on the spleen (S-norm) and the third lumbar vertebra (V-norm). Radiomic features were extracted with no spatial resampling, using 64-bin discretization and relative intensity rescaling. Results: Texture extraction was successfully performed on all planar and SPECT images from both centers. Correlations between intensity-based features measured using S-norm and V-norm images showed weak yet statistically significant r values. Conversely, there was a robust correlation between histogram-based and second-order features measured on S-norm and V-norm images, reflected in high r values. V-norm intensity-based features exhibited significantly higher values and lower SDs when compared with S-norm intensity-based variables. When comparing WBS and SPECT scans, a strong correlation was observed between intensity-based variables, whereas histogram-based and second-order features showed no significant correlation. Conclusion: Radiomic analysis on 177Lu-DOTATATE posttreatment scans was feasible, with proportional scaling to third-lumbar-vertebra activity resulting in the most effective intensity normalization approach, given the decreased variability compared with scaling to spleen activity. Correlations between features assessed using the 2 different scaling methods were weak for intensity-based features and strong for histogram-based and second-order features. Except for intensity-based features, radiomic features derived from WBS images were not comparable with those obtained from SPECT scans.

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Le contrôle bibliographique ouvert

DOI retrouvé dans Crossref DOI retrouvé, mais le titre doit être comparé manuellement.

Titre Crossref
Radiomics on <sup>177</sup> Lu-DOTATATE Posttreatment Scans: Feasibility, Preprocessing Optimization, and Planar–SPECT Comparison
Date Crossref
17/03/2026
Éditeur
Society of Nuclear Medicine
Type
journal-article

Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.

Les institutions déclarées

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Les sujets associés

Radiopharmaceutical Chemistry and ApplicationsRadiomics and Machine Learning in Medical ImagingMedical Imaging Techniques and Applications

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