An exploratory assessment of early and delta PET radiomic features for outcome prediction in locally advanced cervical cancer.
Purpose: This study investigated whether radiomic features extracted from [18F]FDG-PET scans acquired before and two weeks after neoadjuvant treatment, and their variation, provided prognostic parameters in locally advanced cervical cancer (LACC) patients treated with neoadjuvant chemo-radiotherapy...
| Publicado en: | European Journal of Nuclear Medicine & Molecular Imaging Vol. 53; no. 1; pp. 251 - 263 |
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| Autores principales: | , , , , , , , , , , , , , , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Dec2025
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=189634250&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 189634250 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 16197070 NPC jtl: European Journal of Nuclear Medicine & Molecular Imaging issn: 16197070 maglogo: N pubinfo: dt: Dec2025 vid: 53 iid: 1 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 189634250 186010019 10.1007/s00259-025-07405-w 189634250 ppf: 251 ppct: 12 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: An exploratory assessment of early and delta PET radiomic features for outcome prediction in locally advanced cervical cancer. aug: au: Florit, Anita Noortman, Wyanne A. Bizzarri, Nicolò Pasciuto, Tina Feudo, Vanessa Annunziata, Salvatore de Geus-Oei, Lioe-Fee Pfaehler, Elisabeth Boellaard, Ronald Gambacorta, Maria Antonietta Zannoni, Gian Franco Ferrandina, Gabriella Sala, Evis Scambia, Giovanni Rufini, Vittoria van Velden, Floris H. P. Collarino, Angela affil: https://ror.org/00rg70c39 Nuclear Medicine Unit, Department of Diagnostic Imaging and Oncological Radiotherapy, Fondazione Policlinico Universitario A. Gemelli IRCCS, Largo A. Gemelli, 8, 00168, Rome, Italy sug: ab: Purpose: This study investigated whether radiomic features extracted from [18F]FDG-PET scans acquired before and two weeks after neoadjuvant treatment, and their variation, provided prognostic parameters in locally advanced cervical cancer (LACC) patients treated with neoadjuvant chemo-radiotherapy (CRT) followed by radical surgery. Methods: We retrospectively included LACC patients referred to our Institution from 2010 to 2016. [18F]FDG-PET/CT was performed before neoadjuvant CRT (baseline) and two weeks after the start of treatment (early). Radiomic features were extracted after semi-automatic delineation of the primary tumour, on baseline and early PET images. Delta radiomics were calculated as the relative differences between baseline and early features. We performed 5-fold cross-validation stratified for recurrence and cancer-specific death, integrating dimensionality reduction of the radiomic features and variable hunting with importance within the folds. After supervised feature selection, radiomic models with the best-performing features for each timepoint, as well as clinical models and combined clinico-radiomic models, were built. Model performances are presented as C-indices, for prediction of recurrence/progression (disease-free survival, DFS) and cancer-specific death (overall survival, OS). Results: 95 patients were included. With a median follow-up of 76.0 months (95% CI: 59.5–82.1), 31.6% of patients had recurrence/progression and 20.0% died of disease. None of the models could predict DFS (C-indices ≤ 0.72). Model performances for OS yielded slightly better results, with mean C-indices of 0.75 for both the radiomic and combined model based on early features, 0.79 and 0.78 for the radiomic and combined model derived from delta features, and 0.76 for the clinical models. Conclusion: [18F]FDG-PET early and delta radiomic features could not predict DFS in patients with LACC treated with neoadjuvant CRT followed by radical surgery. Although slightly improved performances for the radiomic and combined models were observed in the prediction of OS compared to the clinical model, the added value of these parameters and their inclusion in the clinical practice seems to be limited. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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