Tumour texture features from preoperative CT predict high-risk disease in endometrial cancer.
Adult
Aged
Aged, 80 and over
Biopsy
Contrast Media
Endometrial Neoplasms
/ diagnostic imaging
Female
Humans
Magnetic Resonance Imaging
Middle Aged
Neoplasm Invasiveness
Predictive Value of Tests
Preoperative Period
Prognosis
Radiographic Image Interpretation, Computer-Assisted
Tomography, X-Ray Computed
/ methods
Journal
Clinical radiology
ISSN: 1365-229X
Titre abrégé: Clin Radiol
Pays: England
ID NLM: 1306016
Informations de publication
Date de publication:
01 2021
01 2021
Historique:
received:
29
08
2019
accepted:
15
07
2020
pubmed:
18
9
2020
medline:
4
6
2021
entrez:
17
9
2020
Statut:
ppublish
Résumé
To enable more individualised treatment of endometrial cancer, improved methods for preoperative tumour characterization are warranted. Texture analysis is a method for quantification of heterogeneity in images, increasingly reported as a promising diagnostic tool in oncological imaging, but largely unexplored in endometrial cancer AIM: To explore whether tumour texture features from preoperative computed tomography (CT) are related to known prognostic histopathological features and to outcome in endometrial cancer patients. Preoperative pelvic contrast-enhanced CT was performed in 155 patients with histologically confirmed endometrial cancer. Tumour ROIs were manually drawn on the section displaying the largest cross-sectional tumour area, using dedicated texture analysis software. Using the filtration-histogram technique, the following texture features were calculated: mean, standard deviation, entropy, mean of positive pixels (MPP), skewness, and kurtosis. These imaging markers were evaluated as predictors of histopathological high-risk features and recurrence- and progression-free survival using multivariable logistic regression and Cox regression analysis, including models adjusting for high-risk status based on preoperative biopsy, magnetic resonance imaging (MRI) findings, and age. High tumour entropy independently predicted deep myometrial invasion (odds ratio [OR] 3.7, p=0.008) and cervical stroma invasion (OR 3.9, p=0.02). High value of MPP (MPP5 >24.2) independently predicted high-risk histological subtype (OR 3.7, p=0.01). Furthermore, high tumour kurtosis tended to independently predict reduced recurrence- and progression-free survival (HR 1.1, p=0.06). CT texture analysis yields promising imaging markers in endometrial cancer and may supplement other imaging techniques in providing a more refined preoperative risk assessment that may ultimately enable better tailored treatment strategies.
Sections du résumé
BACKGROUND
To enable more individualised treatment of endometrial cancer, improved methods for preoperative tumour characterization are warranted. Texture analysis is a method for quantification of heterogeneity in images, increasingly reported as a promising diagnostic tool in oncological imaging, but largely unexplored in endometrial cancer AIM: To explore whether tumour texture features from preoperative computed tomography (CT) are related to known prognostic histopathological features and to outcome in endometrial cancer patients.
MATERIALS AND METHODS
Preoperative pelvic contrast-enhanced CT was performed in 155 patients with histologically confirmed endometrial cancer. Tumour ROIs were manually drawn on the section displaying the largest cross-sectional tumour area, using dedicated texture analysis software. Using the filtration-histogram technique, the following texture features were calculated: mean, standard deviation, entropy, mean of positive pixels (MPP), skewness, and kurtosis. These imaging markers were evaluated as predictors of histopathological high-risk features and recurrence- and progression-free survival using multivariable logistic regression and Cox regression analysis, including models adjusting for high-risk status based on preoperative biopsy, magnetic resonance imaging (MRI) findings, and age.
RESULTS
High tumour entropy independently predicted deep myometrial invasion (odds ratio [OR] 3.7, p=0.008) and cervical stroma invasion (OR 3.9, p=0.02). High value of MPP (MPP5 >24.2) independently predicted high-risk histological subtype (OR 3.7, p=0.01). Furthermore, high tumour kurtosis tended to independently predict reduced recurrence- and progression-free survival (HR 1.1, p=0.06).
CONCLUSION
CT texture analysis yields promising imaging markers in endometrial cancer and may supplement other imaging techniques in providing a more refined preoperative risk assessment that may ultimately enable better tailored treatment strategies.
Identifiants
pubmed: 32938538
pii: S0009-9260(20)30374-3
doi: 10.1016/j.crad.2020.07.037
pii:
doi:
Substances chimiques
Contrast Media
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
79.e13-79.e20Informations de copyright
Copyright © 2020 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.