ArticleNMR in biomedicine2019
VERDICT-AMICO: Ultrafast fitting algorithm for non-invasive prostate microstructure characterization.
Article in NMR in biomedicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Validating the biological origin of in vivo fractional intracellular volume from VERDICT-MRI in the prostate.European radiology experimental · 2026Observational
- Time-dependent diffusion MRI for differentiating non‑small cell lung‑cancer brain metastases from breast‑cancer brain metastases and gliomas.Neuroradiology · 2026Article
- Cluster Analysis of VERDICT MRI for Cancer Tissue Characterization in Neuroendocrine Tumors.NMR in biomedicine · 2025Article
- Joint estimation of relaxation and diffusion tissue parameters for prostate cancer with relaxation-VERDICT MRI.Scientific reports · 2023Article
- Improving MR cell size imaging by inclusion of transcytolemmal water exchange.NMR in biomedicine · 2022Article
- Differentiating False Positive Lesions from Clinically Significant Cancer and Normal Prostate Tissue Using VERDICT MRI and Other Diffusion Models.Diagnostics (Basel, Switzerland) · 2022Article
- MR cell size imaging with temporal diffusion spectroscopy.Magnetic resonance imaging · 2021Review
- New prostate MRI techniques and sequences.Abdominal radiology (New York) · 2020Review
- Challenges for biophysical modeling of microstructure.Journal of neuroscience methods · 2020Review
- Magnetic resonance imaging of mean cell size in human breast tumors.Magnetic resonance in medicine · 2020Article
- VERDICT MRI for Prostate Cancer: Intracellular Volume Fraction versus Apparent Diffusion Coefficient.Radiology · 2019Article
- VERDICT-AMICO: Ultrafast fitting algorithm for non-invasive prostate microstructure characterization.NMR in biomedicine · 2019Article
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Authors and funding
10 authors.
Funding
Abstract
VERDICT (vascular, extracellular and restricted diffusion for cytometry in tumours) estimates and maps microstructural features of cancerous tissue non-invasively using diffusion MRI. The main purpose of this study is to address the high computational time of microstructural model fitting for prostate diagnosis, while retaining utility in terms of tumour conspicuity and repeatability. In this work, we adapt the accelerated microstructure imaging via convex optimization (AMICO) framework to linearize the estimation of VERDICT parameters for the prostate gland. We compare the original non-linear fitting of VERDICT with the linear fitting, quantifying accuracy with synthetic data, and computational time and reliability (performance and precision) in eight patients. We also assess the repeatability (scan-rescan) of the parameters. Comparison of the original VERDICT fitting versus VERDICT-AMICO showed that the linearized fitting (1) is more accurate in simulation for a signal-to-noise ratio of 20 dB; (2) reduces the processing time by three orders of magnitude, from 6.55 seconds/voxel to 1.78 milliseconds/voxel; (3) estimates parameters more precisely; (4) produces similar parametric maps and (5) produces similar estimated parameters with a high Pearson correlation between implementations, r
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