Value of Dynamic Contrast-Enhanced (DCE) MRI in Predicting Response to Foam Sclerotherapy of Venous Malformations.


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:
10 2021
Historique:
revised: 06 04 2021
received: 19 02 2021
accepted: 07 04 2021
pubmed: 16 5 2021
medline: 30 9 2021
entrez: 15 5 2021
Statut: ppublish

Résumé

Preoperative imaging assessment of venous malformations (VMs) and prediction of foam sclerotherapy efficacy might be achievable by DCE-MRI but elaborate quantitive analysis was absent. To evaluate the value of DCE-MRI in predicting the effectiveness of foam sclerotherapy in VMs. Retrospective. Fifty-five patients (M:F = 17:38; mean age ± SD, 15.4 ± 13.0 years) with VMs. Three Tesla MRI with 3D T Patients who underwent pretreatment DCE-MRI were divided into "effective" and "ineffective" groups according to the response to foam sclerotherapy. Clinical characteristics and morphologic features were assessed. The semiquantitative parameters, such as maximum intensity time ratio (MITR), enhancement ratio (ER), and Slope, were obtained from ROI and volume of interest (VOI). The quartile and mean values of these parameters were acquired from VOI, while mean values denoted as Mean Mann-Whitney U-test, Cohen's kappa, multivariate logistic regression analysis (backward stepwise), and ROC analyses. The lesion classification, presence of phlebolith, semiquantitative parameters of VOI (quartile and mean of MITR), and semiquantitative parameters of ROI (Slope DCE-MRI is promising in predicting the response to foam sclerotherapy for VMs. The whole lesion VOI-based model showed better performance and could instruct surgical approach in the future. 3 TECHNICAL EFFICACY: Stage 4.

Sections du résumé

BACKGROUND
Preoperative imaging assessment of venous malformations (VMs) and prediction of foam sclerotherapy efficacy might be achievable by DCE-MRI but elaborate quantitive analysis was absent.
PURPOSE
To evaluate the value of DCE-MRI in predicting the effectiveness of foam sclerotherapy in VMs.
STUDY TYPE
Retrospective.
POPULATION
Fifty-five patients (M:F = 17:38; mean age ± SD, 15.4 ± 13.0 years) with VMs.
FIELD STRENGTH/SEQUENCE
Three Tesla MRI with 3D T
ASSESSMENT
Patients who underwent pretreatment DCE-MRI were divided into "effective" and "ineffective" groups according to the response to foam sclerotherapy. Clinical characteristics and morphologic features were assessed. The semiquantitative parameters, such as maximum intensity time ratio (MITR), enhancement ratio (ER), and Slope, were obtained from ROI and volume of interest (VOI). The quartile and mean values of these parameters were acquired from VOI, while mean values denoted as Mean
STATISTICAL ANALYSIS
Mann-Whitney U-test, Cohen's kappa, multivariate logistic regression analysis (backward stepwise), and ROC analyses.
RESULTS
The lesion classification, presence of phlebolith, semiquantitative parameters of VOI (quartile and mean of MITR), and semiquantitative parameters of ROI (Slope
DATA CONCLUSION
DCE-MRI is promising in predicting the response to foam sclerotherapy for VMs. The whole lesion VOI-based model showed better performance and could instruct surgical approach in the future.
EVIDENCE LEVEL
3 TECHNICAL EFFICACY: Stage 4.

Identifiants

pubmed: 33991357
doi: 10.1002/jmri.27657
doi:

Substances chimiques

Contrast Media 0

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

1108-1116

Informations de copyright

© 2021 International Society for Magnetic Resonance in Medicine.

Références

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Auteurs

Zhipeng Xia (Z)

Department of Radiology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, PR China.

Hao Gu (H)

Department of Plastic and Reconstructive Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, PR China.

Ying Yuan (Y)

Department of Radiology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, PR China.

Shiyu Xiang (S)

Department of Radiology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, PR China.

Zimin Zhang (Z)

Department of Radiology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, PR China.

Xiaofeng Tao (X)

Department of Radiology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, PR China.

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