Journal Article DKFZ-2020-02265

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png
Comprehensive Analysis of Tumour Sub-Volumes for Radiomic Risk Modelling in Locally Advanced HNSCC.

 ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;

2020
MDPI Basel

Cancers 12(10), 3047 () [10.3390/cancers12103047]
 GO

This record in other databases:  

Please use a persistent id in citations: doi:

Abstract: Imaging features for radiomic analyses are commonly calculated from the entire gross tumour volume (GTV entire). However, tumours are biologically complex and the consideration of different tumour regions in radiomic models may lead to an improved outcome prediction. Therefore, we investigated the prognostic value of radiomic analyses based on different tumour sub-volumes using computed tomography imaging of patients with locally advanced head and neck squamous cell carcinoma. The GTV entire was cropped by different margins to define the rim and the corresponding core sub-volumes of the tumour. Subsequently, the best performing tumour rim sub-volume was extended into surrounding tissue with different margins. Radiomic risk models were developed and validated using a retrospective cohort consisting of 291 patients in one of the six Partner Sites of the German Cancer Consortium Radiation Oncology Group treated between 2005 and 2013. The validation concordance index (C-index) averaged over all applied learning algorithms and feature selection methods using the GTVentire achieved a moderate prognostic performance for loco-regional tumour control (C-index: 0.61 ± 0.04 (mean ± std)). The models based on the 5 mm tumour rim and on the 3 mm extended rim sub-volume showed higher median performances (C-index: 0.65 ± 0.02 and 0.64 ± 0.05, respectively), while models based on the corresponding tumour core volumes performed less (C-index: 0.59 ± 0.01). The difference in C-index between the 5 mm tumour rim and the corresponding core volume showed a statistical trend (p = 0.10). After additional prospective validation, the consideration of tumour sub-volumes may be a promising way to improve prognostic radiomic risk models.

Classification:

Note: 2020 Oct 19;12(10):3047

Contributing Institute(s):
  1. DKTK BE zentral (BE01)
  2. DKTK ED ES zentral (ED01)
  3. DKTK FM zentral (FM01)
  4. DKTK DD zentral (DD01)
  5. DKTK HD zentral (HD01)
  6. DKTK MU LMU zentral (MU01)
  7. DKTK TU AG Krebs-Immuntherapie (TU03)
  8. E220 Radioonkologie/Radiobiologie (E220)
Research Program(s):
  1. 315 - Imaging and radiooncology (POF3-315) (POF3-315)

Appears in the scientific report 2020
Database coverage:
Medline ; Creative Commons Attribution CC BY (No Version) ; DOAJ ; Article Processing Charges ; BIOSIS Previews ; Biological Abstracts ; Clarivate Analytics Master Journal List ; DOAJ Seal ; Ebsco Academic Search ; Essential Science Indicators ; Fees ; IF >= 5 ; JCR ; NCBI Molecular Biology Database ; PubMed Central ; SCOPUS ; Science Citation Index Expanded ; Web of Science Core Collection
Click to display QR Code for this record

The record appears in these collections:
Document types > Articles > Journal Article
Public records
Publications database

 Record created 2020-10-26, last modified 2024-02-29



Rate this document:

Rate this document:
1
2
3
 
(Not yet reviewed)