Paper Info
Title
Methodology And Technology For The Development Of A Prognostic Mri-Based Radiomic Model For The Outcome Of Head And Neck Cancer Patients
Abstract
The purpose of this study was to establish a methodology and technology for the development of an MRI-based radiomic signature for prognosis of overall survival (OS) in nasopharyngeal cancer from non-endemic areas. The signature was trained using 1072 features extracted from the main tumor in T1-weighted and T2-weighted images of 142 patients. A model with 2 radiomic features was obtained (RAD model). Tumor volume and a signature obtained by training the model on permuted survival data (RADperm model) were used as a reference. A 10-fold cross-validation was used to validate the signature. Harrel's C-index was used as performance metric. A statistical comparison of the RAD, RADperm and volume was performed using Wilcoxon signed rank tests. The C-index for the RAD model was higher compared to the one of the RADperm model (0.69 +/- 0.08 vs 0.47 +/- 0.05), which ensures absence of overfitting. Also, the signature obtained with the RAD model had an improved C-index compared to tumor volume alone (0.69 +/- 0.08 vs 0.65 +/- 0.06), suggesting that the radiomic signature provides additional prognostic information.
Year
DOI
Venue
2020
10.1109/EMBC44109.2020.9176565
42ND ANNUAL INTERNATIONAL CONFERENCES OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY: ENABLING INNOVATIVE TECHNOLOGIES FOR GLOBAL HEALTHCARE EMBC'20
DocType
Volume
ISSN
Conference
2020
1557-170X
Citations 
PageRank 
References 
0
0.34
0
Authors
16
Name
Order
Citations
PageRank
Marco Bologna101.35
Valentina D. A. Corino23012.91
Chiara Tenconi300.34
Nadia Facchinetti400.34
Giuseppina Calareso500.68
Nicola Iacovelli600.34
Anna Cavallo700.34
Salvatore Alfieri800.34
Stefano Cavalieri900.34
Carlo Fallai1000.34
Riccardo Valdagni1100.34
Tiziana Rancati1200.34
Annalisa Trama1300.68
Lisa Licitra1402.37
Ester Orlandi1500.34
Luca T. Mainardi1610626.02