Quantitative investigation of the edge enhancement in in-line phase contrast projections and tomosynthesis provided by distributing microbubbles on the interface between two tissues : a phantom study

The objective of this study was to quantitatively investigate the ability to distribute microbubbles along the interface between two tissues, in an effort to improve the edge and/or boundary features in phase contrast imaging. The experiments were conducted by employing a custom designed tissue simulating phantom, which also simulated a clinical condition where the ligand-targeted microbubbles are self-aggregated on the endothelium of blood vessels surrounding malignant cells. Four different concentrations of microbubble suspensions were injected into the phantom: 0%, 0.1%, 0.2%, and 0.4%. A time delay of 5 min was implemented before image acquisition to allow the microbubbles to become distributed at the interface between the acrylic and the cavity simulating a blood vessel segment. For comparison purposes, images were acquired using three system configurations for both projection and tomosynthesis imaging with a fixed radiation dose delivery: conventional low-energy contact mode, low-energy in-line phase contrast and high-energy in-line phase contrast. The resultant images illustrate the edge feature enhancements in the in-line phase contrast imaging mode when the microbubble concentration is extremely low. The quantitative edge-enhancement-to-noise ratio calculations not only agree with the direct image observations, but also indicate that the edge feature enhancement can be improved by increasing the microbubble concentration. In addition, high-energy in-line phase contrast imaging provided better performance in detecting low-concentration microbubble distributions.

Medienart:

E-Artikel

Erscheinungsjahr:

2017

Erschienen:

2017

Enthalten in:

Zur Gesamtaufnahme - volume:62

Enthalten in:

Physics in medicine and biology - 62(2017), 24 vom: 21. Nov., Seite 9357-9376

Sprache:

Englisch

Beteiligte Personen:

Wu, Di [VerfasserIn]
Wong, Molly Donovan [VerfasserIn]
Li, Yuhua [VerfasserIn]
Fajardo, Laurie [VerfasserIn]
Zheng, Bin [VerfasserIn]
Wu, Xizeng [VerfasserIn]
Liu, Hong [VerfasserIn]

Links:

Volltext

Themen:

Contrast Media
Journal Article

Anmerkungen:

Date Completed 12.04.2018

Date Revised 27.03.2024

published: Electronic

Citation Status MEDLINE

doi:

10.1088/1361-6560/aa9548

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM278273513