Purpose: To assess the value of 18F-Fluorodeoxyglucose (18F-FDG) PET Radiomic Features (RF) in predicting Distant Relapse Free Survival (DRFS) in patients with Locally Advanced Pancreatic Cancer (LAPC) treated with radio-chemotherapy. Materials & methods: One-hundred-ninety-eight RFs were extracted using IBSI (Image Biomarker Standardization Initiative) consistent software from pre-radiotherapy images of 176 LAPC patients treated with moderate hypo-fractionation (44.25 Gy, 2.95 Gy/fr). Tumors were segmented by applying a previously validated semi-automatic method. One-hundred-twenty-six RFs were excluded due to poor reproducibility and/or repeatability and/or inter-scanner variability. The original cohort was randomly split into a training (n = 116) and a validation (n = 60) group. Multi-variable Cox regression was applied to the training group, including only independent RFs in the model. The resulting radiomic index was tested in the validation cohort. The impact of selected clinical variables was also investigated. Results: The resulting Cox model included two first order RFs: Center of Mass Shift (COMshift) and 10th Intensity percentile (P10) (p = 0.0005, HR = 2.72, 95%CI = 1.54–4.80), showing worse outcomes for patients with lower COMshift and higher P10. Once stratified by quartile values (highest quartile vs the remaining), the index properly stratified patients according to their DRFS (p = 0.0024, log-rank test). Performances were confirmed in the validation cohort (p = 0.03, HR = 2.53, 95%CI = 0.96–6.65). The addition of clinical factors did not significantly improve the models’ performance. Conclusions: A radiomic-based index including only two robust PET-RFs predicted DRFS of LAPC patients after radio-chemotherapy. The current results could find relevant applications in the treatment personalization of LAPC. A multi-institution independent validation has been planned.

Training and validation of a robust PET radiomic-based index to predict distant-relapse-free-survival after radio-chemotherapy for locally advanced pancreatic cancer / M. Mori, P. Passoni, E. Incerti, V. Bettinardi, S. Broggi, M. Reni, P. Whybra, E. Spezi, E.G. Vanoli, L. Gianolli, M. Picchio, N.G. Di Muzio, C. Fiorino. - In: RADIOTHERAPY AND ONCOLOGY. - ISSN 0167-8140. - 153:(2020), pp. 258-264. [10.1016/j.radonc.2020.07.003]

Training and validation of a robust PET radiomic-based index to predict distant-relapse-free-survival after radio-chemotherapy for locally advanced pancreatic cancer

M. Mori
Primo
Formal Analysis
;
2020

Abstract

Purpose: To assess the value of 18F-Fluorodeoxyglucose (18F-FDG) PET Radiomic Features (RF) in predicting Distant Relapse Free Survival (DRFS) in patients with Locally Advanced Pancreatic Cancer (LAPC) treated with radio-chemotherapy. Materials & methods: One-hundred-ninety-eight RFs were extracted using IBSI (Image Biomarker Standardization Initiative) consistent software from pre-radiotherapy images of 176 LAPC patients treated with moderate hypo-fractionation (44.25 Gy, 2.95 Gy/fr). Tumors were segmented by applying a previously validated semi-automatic method. One-hundred-twenty-six RFs were excluded due to poor reproducibility and/or repeatability and/or inter-scanner variability. The original cohort was randomly split into a training (n = 116) and a validation (n = 60) group. Multi-variable Cox regression was applied to the training group, including only independent RFs in the model. The resulting radiomic index was tested in the validation cohort. The impact of selected clinical variables was also investigated. Results: The resulting Cox model included two first order RFs: Center of Mass Shift (COMshift) and 10th Intensity percentile (P10) (p = 0.0005, HR = 2.72, 95%CI = 1.54–4.80), showing worse outcomes for patients with lower COMshift and higher P10. Once stratified by quartile values (highest quartile vs the remaining), the index properly stratified patients according to their DRFS (p = 0.0024, log-rank test). Performances were confirmed in the validation cohort (p = 0.03, HR = 2.53, 95%CI = 0.96–6.65). The addition of clinical factors did not significantly improve the models’ performance. Conclusions: A radiomic-based index including only two robust PET-RFs predicted DRFS of LAPC patients after radio-chemotherapy. The current results could find relevant applications in the treatment personalization of LAPC. A multi-institution independent validation has been planned.
Distant relapses; Induction chemotherapy; Pancreatic cancer; Predictive models; Radiomic; Radiotherapy
Settore FIS/07 - Fisica Applicata(Beni Culturali, Ambientali, Biol.e Medicin)
2020
Article (author)
File in questo prodotto:
File Dimensione Formato  
1-s2.0-S0167814020303960-main.pdf

accesso riservato

Descrizione: Original Article
Tipologia: Publisher's version/PDF
Dimensione 840.62 kB
Formato Adobe PDF
840.62 kB Adobe PDF   Visualizza/Apri   Richiedi una copia
Spezi E - Training and validation of a robust PET ...-2-14.pdf

accesso aperto

Tipologia: Post-print, accepted manuscript ecc. (versione accettata dall'editore)
Dimensione 400 kB
Formato Adobe PDF
400 kB Adobe PDF Visualizza/Apri
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/1033254
Citazioni
  • ???jsp.display-item.citation.pmc??? 13
  • Scopus 21
  • ???jsp.display-item.citation.isi??? 24
social impact