Development and Validation of Noninvasive MRI-Based Signature for Preoperative Prediction of Early Recurrence in Perihilar Cholangiocarcinoma.
early recurrence
magnetic resonance imaging
perihilar cholangiocarcinoma
radiomics
Journal
Journal of magnetic resonance imaging : JMRI
ISSN: 1522-2586
Titre abrégé: J Magn Reson Imaging
Pays: United States
ID NLM: 9105850
Informations de publication
Date de publication:
03 2022
03 2022
Historique:
revised:
08
07
2021
received:
15
04
2021
accepted:
09
07
2021
pubmed:
24
7
2021
medline:
4
5
2022
entrez:
23
7
2021
Statut:
ppublish
Résumé
Cholangiocarcinoma is a type of hepatobiliary tumor. For perihilar cholangiocarcinoma (pCCA), patients who experience early recurrence (ER) have a poor prognosis. Preoperative accurate prediction of postoperative ER can avoid unnecessary operation; however, prediction is challenging. To develop a novel signature based on clinical and/or MRI radiomics features of pCCA to preoperatively predict ER. Retrospective. One hundred eighty-four patients (median age, 61.0 years; interquartile range: 53.0-66.8 years) including 115 men and 69 women. A 1.5 T; volumetric interpolated breath-hold examination (VIBE) sequence. The models were developed from the training set (128 patients) and validated in a separate testing set (56 patients). The contrast-enhanced arterial and portal vein phase MR images of hepatobiliary system were used for extracting radiomics features. The correlation analysis, least absolute shrinkage and selection operator (LASSO) logistic regression (LR), backward stepwise LR were mainly used for radiomics feature selection and modeling (Model Chi-squared (χ Based on the comparison of area under the curves (AUC) using Delong test, Model A noninvasive model combining the MRI-based radiomics signature and clinical variables is potential to preoperatively predict ER for pCCA. 3 TECHNICAL EFFICACY STAGE: 4.
Sections du résumé
BACKGROUND
Cholangiocarcinoma is a type of hepatobiliary tumor. For perihilar cholangiocarcinoma (pCCA), patients who experience early recurrence (ER) have a poor prognosis. Preoperative accurate prediction of postoperative ER can avoid unnecessary operation; however, prediction is challenging.
PURPOSE
To develop a novel signature based on clinical and/or MRI radiomics features of pCCA to preoperatively predict ER.
STUDY TYPE
Retrospective.
POPULATION
One hundred eighty-four patients (median age, 61.0 years; interquartile range: 53.0-66.8 years) including 115 men and 69 women.
FIELD STRENGTH/SEQUENCE
A 1.5 T; volumetric interpolated breath-hold examination (VIBE) sequence.
ASSESSMENT
The models were developed from the training set (128 patients) and validated in a separate testing set (56 patients). The contrast-enhanced arterial and portal vein phase MR images of hepatobiliary system were used for extracting radiomics features. The correlation analysis, least absolute shrinkage and selection operator (LASSO) logistic regression (LR), backward stepwise LR were mainly used for radiomics feature selection and modeling (Model
STATISTICAL TESTS
Chi-squared (χ
RESULTS
Based on the comparison of area under the curves (AUC) using Delong test, Model
DATA CONCLUSION
A noninvasive model combining the MRI-based radiomics signature and clinical variables is potential to preoperatively predict ER for pCCA.
LEVEL OF EVIDENCE
3 TECHNICAL EFFICACY STAGE: 4.
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
787-802Informations de copyright
© 2021 International Society for Magnetic Resonance in Medicine.
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