A quantitative multiparametric MRI analysis platform for estimation of robust imaging biomarkers in clinical oncology Journal Article


Authors: LoCastro, E.; Paudyal, R.; Konar, A. S.; LaViolette, P. S.; Akin, O.; Hatzoglou, V.; Goh, A. C.; Bochner, B. H.; Rosenberg, J.; Wong, R. J.; Lee, N. Y.; Schwartz, L. H.; Shukla-Dave, A.
Article Title: A quantitative multiparametric MRI analysis platform for estimation of robust imaging biomarkers in clinical oncology
Abstract: There is a need to develop user-friendly imaging tools estimating robust quantitative biomarkers (QIBs) from multiparametric (mp)MRI for clinical applications in oncology. Quantitative metrics derived from (mp)MRI can monitor and predict early responses to treatment, often prior to anatomical changes. We have developed a vendor-agnostic, flexible, and user-friendly MATLAB-based toolkit, MRI-Quantitative Analysis and Multiparametric Evaluation Routines ("MRI-QAMPER", current release v3.0), for the estimation of quantitative metrics from dynamic contrast-enhanced (DCE) and multi-b value diffusion-weighted (DW) MR and MR relaxometry. MRI-QAMPER's functionality includes generating numerical parametric maps from these methods reflecting tumor permeability, cellularity, and tissue morphology. MRI-QAMPER routines were validated using digital reference objects (DROs) for DCE and DW MRI, serving as initial approval stages in the National Cancer Institute Quantitative Imaging Network (NCI/QIN) software benchmark. MRI-QAMPER has participated in DCE and DW MRI Collaborative Challenge Projects (CCPs), which are key technical stages in the NCI/QIN benchmark. In a DCE CCP, QAMPER presented the best repeatability coefficient (RC = 0.56) across test-retest brain metastasis data, out of ten participating DCE software packages. In a DW CCP, QAMPER ranked among the top five (out of fourteen) tools with the highest area under the curve (AUC) for prostate cancer detection. This platform can seamlessly process mpMRI data from brain, head and neck, thyroid, prostate, pancreas, and bladder cancer. MRI-QAMPER prospectively analyzes dose de-escalation trial data for oropharyngeal cancer, which has earned it advanced NCI/QIN approval for expanded usage and applications in wider clinical trials.
Keywords: biomarkers; biological marker; pathology; diagnostic imaging; oncology; prostatic neoplasms; prostate tumor; medical oncology; contrast medium; contrast media; dynamic contrast-enhanced mri; diffusion-weighted mri; multiparametric magnetic resonance imaging; cancer; humans; human; male; multiparametric mri; quantitative imaging biomarkers; optimal model mapping
Journal Title: Tomography
Volume: 9
Issue: 6
ISSN: 2379-1381
Publisher: MDPI  
Date Published: 2023-12-01
Start Page: 2052
End Page: 2066
Language: English
DOI: 10.3390/tomography9060161
PUBMED: 37987347
PROVIDER: scopus
PMCID: PMC10661267
DOI/URL:
Notes: The MSK Cancer Center Support Grant (P30 CA008748) is acknowledged in the PubMed record and PDF. Corresponding MSK author is Amita Shukla-Dave -- Source: Scopus
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MSK Authors
  1. Lawrence H Schwartz
    311 Schwartz
  2. Nancy Y. Lee
    884 Lee
  3. Richard J Wong
    419 Wong
  4. Bernard Bochner
    469 Bochner
  5. Amita Dave
    140 Dave
  6. Oguz Akin
    270 Akin
  7. Jonathan Eric Rosenberg
    518 Rosenberg
  8. Ramesh Paudyal
    39 Paudyal
  9. Alvin Chun chin Goh
    74 Goh