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8 March 2024 Systematic evaluation of MRI-based characterization of tumor-associated vascular morphology and hemodynamics via a dynamic digital phantom
Chengyue Wu, David A. Hormuth II, Ty Easley, Federico Pineda, Gregory S. Karczmar, Thomas E. Yankeelov
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Journal of Medical Imaging, Vol. 11, Issue 2, 024002 (March 2024). https://doi.org/10.1117/1.JMI.11.2.024002
Abstract

Purpose

Validation of quantitative imaging biomarkers is a challenging task, due to the difficulty in measuring the ground truth of the target biological process. A digital phantom-based framework is established to systematically validate the quantitative characterization of tumor-associated vascular morphology and hemodynamics based on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI).

Approach

A digital phantom is employed to provide a ground-truth vascular system within which 45 synthetic tumors are simulated. Morphological analysis is performed on high-spatial resolution DCE-MRI data (spatial/temporal resolution = 30 to 300 μm/60 s) to determine the accuracy of locating the arterial inputs of tumor-associated vessels (TAVs). Hemodynamic analysis is then performed on the combination of high-spatial resolution and high-temporal resolution (spatial/temporal resolution = 60 to 300 μm/1 to 10 s) DCE-MRI data, determining the accuracy of estimating tumor-associated blood pressure, vascular extraction rate, interstitial pressure, and interstitial flow velocity.

Results

The observed effects of acquisition settings demonstrate that, when optimizing the DCE-MRI protocol for the morphological analysis, increasing the spatial resolution is helpful but not necessary, as the location and arterial input of TAVs can be recovered with high accuracy even with the lowest investigated spatial resolution. When optimizing the DCE-MRI protocol for hemodynamic analysis, increasing the spatial resolution of the images used for vessel segmentation is essential, and the spatial and temporal resolutions of the images used for the kinetic parameter fitting require simultaneous optimization.

Conclusion

An in silico validation framework was generated to systematically quantify the effects of image acquisition settings on the ability to accurately estimate tumor-associated characteristics.
© 2024 Society of Photo-Optical Instrumentation Engineers (SPIE)
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Chengyue Wu, David A. Hormuth II, Ty Easley, Federico Pineda, Gregory S. Karczmar, and Thomas E. Yankeelov "Systematic evaluation of MRI-based characterization of tumor-associated vascular morphology and hemodynamics via a dynamic digital phantom," Journal of Medical Imaging 11(2), 024002 (8 March 2024). https://doi.org/10.1117/1.JMI.11.2.024002
Received: 6 June 2023; Accepted: 19 February 2024; Published: 8 March 2024
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KEYWORDS
Tumors
Signal to noise ratio
Hemodynamics
Spatial resolution
Image segmentation
Image resolution
Temporal resolution
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