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Comparison of Early Contrast Enhancement Models in Ultrafast Dynamic Contrast-Enhanced Magnetic Resonance Imaging of Prostate Cancer

Comparison of Early Contrast Enhancement Models in Ultrafast Dynamic Contrast-Enhanced Magnetic Resonance Imaging of Prostate Cancer

Alfredo Clemente ¹, Guerino Selva ¹, Michael Berks ², Federica Morrone ³, Aniello Alessandro Morrone ³, Michele De Cristofaro Aulisa ⁴, Ekaterina Bliakharskaia ⁵, Andrea De Nicola ⁶, Armando Tartaro ^7,8, Paul E Summers ⁹

Alfredo Clemente ¹, Guerino Selva ¹, Michael Berks ²

¹Radiology Unit, Centro Medicina Nucleare N1, "Centro Morrone", 81100 Caserta, Italy.
²Quantitative Biomedical Imaging Laboratory, Division of Cancer Sciences, University of Manchester, Manchester M13 9PL, UK.
³Radiology Unit, Centro Radiologico Vega, "Centro Morrone", 81100 Caserta, Italy.
⁴Department of Biotechnological and Applied Clinical Sciences, University of L'Aquila, 67100 L'Aquila, Italy.
⁵Department of Neuroscience and Imaging, University G. d'Annunzio, 66100 Chieti, Italy.
⁶Radiology Unit, SS. Annunziata Hospital, ASL Lanciano Vasto Chieti, 66100 Chieti, Italy.
⁷Department of Clinical, Oral Sciences and Biotechnology, University "G. d'Annunzio", 66100 Chieti, Italy.
⁸MRI Unit, Santissima Trinità Hospital, ASL Pescara, 65026 Popoli, Italy.
⁹QMRI Tech, 65123 Pescara, Italy.

⁰Radiology Unit, Centro Medicina Nucleare N1, "Centro Morrone", 81100 Caserta, Italy.

Diagnostics (basel, Switzerland) +

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May 11, 2024

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View abstract on PubMed

Summary

This summary is machine-generated.

Ultrafast dynamic contrast-enhanced MRI (DCE-MRI) shows promise for prostate cancer detection. Early enhancement parameters, unlike Tofts models, may serve as reliable quantitative markers for prostate cancer grading and staging.

Area Of Science

Magnetic Resonance Imaging
Oncology
Biomedical Engineering

Background

Traditional Tofts models struggle to provide reliable quantitative markers for prostate cancer using DCE-MRI.
Prostate cancer diagnosis and grading rely on accurate imaging biomarkers.

Purpose Of The Study

To investigate differences in prostate zones and lesion PI-RADS categories and grade group (GG) using various DCE-MRI models.
To identify potential quantitative markers for prostate cancer from ultrafast DCE-MRI data.

Main Methods

Analysis of high temporal resolution (1.695 s) DCE-MRI data from 25 patients with 35 PI-RADS category 3 or higher tumors.
Application of two-compartment uptake (2CU), exponential, sigmoidal, and empirical mathematical models, alongside time to peak (TTP) analysis.
Region of interest analysis in tumor and normal-appearing prostate tissue.

Main Results

Plasma flow (Fp) and enhancement rate (α) differed between peripheral and transition zones.
Parameters including Fp, MTTp, Tc, E, α, A1 - T0, A2, and TTP correlated with PI-RADS categories and GG in the peripheral zone.
Permeability surface area product (PS) and transfer constant (Ktrans) showed no association with PI-RADS category or GG.

Conclusions

Early enhancement parameters from ultrafast DCE-MRI show potential as quantitative biomarkers for prostate cancer.
These parameters may aid in differentiating prostate cancer grades and localizing tumors within different prostate zones.

Keywords:

empirical mathematical model pharmacokinetic model prostate cancer ultrafast dynamic contrast enhanced MRI

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