Quantitative transport mapping (QTM) for differentiating benign and malignant breast lesion: Comparison with traditional kinetics modeling and semi-quantitative enhancement curve characteristics.

TitleQuantitative transport mapping (QTM) for differentiating benign and malignant breast lesion: Comparison with traditional kinetics modeling and semi-quantitative enhancement curve characteristics.
Publication TypeJournal Article
Year of Publication2022
AuthorsZhang Q, Spincemaille P, Drotman M, Chen C, Eskreis-Winkler S, Huang W, Zhou L, Morgan J, Nguyen TD, Prince MR, Wang Y
JournalMagn Reson Imaging
Volume86
Pagination86-93
Date Published2022 02
ISSN1873-5894
KeywordsBreast, Breast Neoplasms, Contrast Media, Diagnosis, Differential, Diffusion Magnetic Resonance Imaging, Female, Humans, Kinetics, Magnetic Resonance Imaging, Retrospective Studies, ROC Curve
Abstract

PURPOSE: To test the feasibility of using quantitative transport mapping (QTM) method, which is based on the inversion of transport equation using spatial deconvolution without any arterial input function, for automatically postprocessing dynamic contrast enhanced MRI (DCE-MRI) to differentiate malignant and benign breast tumors.

MATERIALS AND METHODS: Breast DCE-MRI data with biopsy confirmed malignant (n = 13) and benign tumors (n = 13) was used to assess QTM velocity (|u|) and diffusion coefficient (D), volume transfer constant (K), volume fraction of extravascular extracellular space (V) from kinetics method, and traditional enhancement curve characteristics (ECC: amplitude A, wash-in rate α, wash-out rate β). A Mann-Whitney U test and receiver operating characteristic curve (ROC) analysis were performed to assess the diagnostic performance of these parameters for distinguishing between benign and malignant tumors.

RESULTS: Between malignant and benign tumors, there was a significant difference in |u| and K, (p = 0.0066, 0.0274, respectively), but not in D, V, A, α and β (p = 0.1119, 0.2382, 0.4418,0.2592 and 0.9591, respectively). ROC area-under-the-curve was 0.82, 0.75 (95% confidence level 0.60-0.95, 0.51-0.90) for |u| and K, respectively.

CONCLUSION: QTM postprocesses DCE-MRI automatically through deconvolution in space and time to solve the inverse problem of the transport equation. Comparing with traditional kinetics method and ECC, QTM method showed better diagnostic accuracy in differentiating benign from malignant breast tumors in this study.

DOI10.1016/j.mri.2021.10.039
Alternate JournalMagn Reson Imaging
PubMed ID34748928
PubMed Central IDPMC8726426
Grant ListS10 OD021782 / OD / NIH HHS / United States
Related Institute: 
MRI Research Institute (MRIRI)

Weill Cornell Medicine
Department of Radiology
525 East 68th Street New York, NY 10065