Intravoxel Incoherent Motion Combined With Dynamic Contrast-Enhanced Perfusion MRI of Early Cervical Carcinoma: Correlations Between Multimodal Parameters and HIF-1α Expression.


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:
09 2019
Historique:
received: 21 08 2018
revised: 28 11 2018
accepted: 29 11 2018
pubmed: 17 1 2019
medline: 22 10 2020
entrez: 17 1 2019
Statut: ppublish

Résumé

The identification of hypoxia inducible factor (HIF-1α) expression is helpful for the quantitative assessment of tumor hypoxia. The application of multimodal imaging techniques may play a part in the assessment of HIF-1α expression of cervical carcinoma. To investigate the correlations between multiple imaging parameters and HIF-1α expression of early cervical carcinoma and to determine whether tumor hypoxia can be predicted using multisequence imaging parameters. Prospective observational. One hundred patients with early cervical carcinoma. 3.0 T MRI including intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) and dynamic contrast-enhanced (DCE) perfusion MRI sequences. DCE-MRI and IVIM DWI were performed for all patients. The imaging parameters included volume transfer constant (K The comparisons of imaging parameters between two independent groups were performed using the Mann-Whitney U-test. Multiple linear regression analysis was performed to determine the correlation between multiple imaging parameters and HIF-1α expression. The diagnostic ability of DCE-MRI, IVIM DWI, and the combination of two techniques for discriminating high-expression and low-expression groups were analyzed. The high-expression group had a lower K The combination of DCE-MRI and IVIM DWI can improve the diagnostic ability of discriminating different HIF-1α expression levels for early cervical tumors. 1 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2019;50:918-929.

Sections du résumé

BACKGROUND
The identification of hypoxia inducible factor (HIF-1α) expression is helpful for the quantitative assessment of tumor hypoxia. The application of multimodal imaging techniques may play a part in the assessment of HIF-1α expression of cervical carcinoma.
PURPOSE
To investigate the correlations between multiple imaging parameters and HIF-1α expression of early cervical carcinoma and to determine whether tumor hypoxia can be predicted using multisequence imaging parameters.
STUDY TYPE
Prospective observational.
POPULATION
One hundred patients with early cervical carcinoma.
FIELD STRENGTH/SEQUENCES
3.0 T MRI including intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) and dynamic contrast-enhanced (DCE) perfusion MRI sequences.
ASSESSMENT
DCE-MRI and IVIM DWI were performed for all patients. The imaging parameters included volume transfer constant (K
STATISTICAL TESTS
The comparisons of imaging parameters between two independent groups were performed using the Mann-Whitney U-test. Multiple linear regression analysis was performed to determine the correlation between multiple imaging parameters and HIF-1α expression. The diagnostic ability of DCE-MRI, IVIM DWI, and the combination of two techniques for discriminating high-expression and low-expression groups were analyzed.
RESULTS
The high-expression group had a lower K
DATA CONCLUSION
The combination of DCE-MRI and IVIM DWI can improve the diagnostic ability of discriminating different HIF-1α expression levels for early cervical tumors.
LEVEL OF EVIDENCE
1 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2019;50:918-929.

Identifiants

pubmed: 30648775
doi: 10.1002/jmri.26604
doi:

Substances chimiques

Contrast Media 0
HIF1A protein, human 0
Hypoxia-Inducible Factor 1, alpha Subunit 0

Types de publication

Journal Article Observational Study

Langues

eng

Sous-ensembles de citation

IM

Pagination

918-929

Informations de copyright

© 2019 International Society for Magnetic Resonance in Medicine.

Auteurs

Xiangsheng Li (X)

Department of Radiology, Air Force General Hospital, People's Liberation Army, Beijing, China.

Shandong Wu (S)

Imaging Research Division Department of Radiology, Biomedical Informatics, and Bioengineering, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.

Dechang Li (D)

Department of Pathology, Air Force General Hospital, People's Liberation Army, Beijing, China.

Tao Yu (T)

Department of Medical Imaging, Cancer Hospital of China Medical University; Liaoning Cancer Hospital & Institute, Shenyang, Liaoning Province, China.

Hongxian Zhu (H)

Department of Radiology, Air Force General Hospital, People's Liberation Army, Beijing, China.

Yunlong Song (Y)

Department of Radiology, Air Force General Hospital, People's Liberation Army, Beijing, China.

Limin Meng (L)

Department of Radiology, Air Force General Hospital, People's Liberation Army, Beijing, China.

Hongxia Fan (H)

Department of Radiology, Air Force General Hospital, People's Liberation Army, Beijing, China.

Lizhi Xie (L)

Department of MR Research, GE Healthcare, Beijing, China.

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