Intermanufacturer Comparison of Dual-Energy CT Iodine Quantification and Monochromatic Attenuation: A Phantom Study.

Purpose To determine the accuracy of dual-energy computed tomographic (CT) quantitation in a phantom system comparing fast kilovolt peak-switching, dual-source, split-filter, sequential-scanning, and dual-layer detector systems. Materials and Methods A large elliptical phantom containing iodine (2, 5, and 15 mg/mL), simulated contrast material-enhanced blood, and soft-tissue inserts with known elemental compositions was scanned three to five times with seven dual-energy CT systems and a total of 10 kilovolt peak settings. Monochromatic images (50, 70, and 140 keV) and iodine concentration images were created. Mean iodine concentration and monochromatic attenuation for each insert and reconstruction energy level were recorded. Measurement bias was assessed by using the sum of the mean signed errors measured across relevant inserts for each monochromatic energy level and iodine concentration. Iodine and monochromatic errors were assessed by using the root sum of the squared error of all measurements. Results At least one acquisition paradigm per scanner had iodine biases (range, -2.6 to 1.5 mg/mL) with significant differences from zero. There were no significant differences in iodine error (range, 0.44-1.70 mg/mL) among the top five acquisition paradigms (one fast kilovolt peak switching, three dual source, and one sequential scanning). Monochromatic bias was smallest for 70 keV (-12.7 to 15.8 HU) and largest for 50 keV (-80.6 to 35.2 HU). There were no significant differences in monochromatic error (range, 11.4-52.0 HU) among the top three acquisition paradigms (one dual source and two fast kilovolt peak switching). The lowest accuracy for both measures was with a split-filter system. Conclusion Iodine and monochromatic accuracy varies among systems, but dual-source and fast kilovolt-switching generally provided the most accurate results in a large phantom. © RSNA, 2017 Online supplemental material is available for this article.

Clinically translatable quantitative molecular photoacoustic imaging with liposome-encapsulated ICG J-aggregates.

Photoacoustic (PA) imaging is a functional and molecular imaging technique capable of high sensitivity and spatiotemporal resolution at depth. Widespread use of PA imaging, however, is limited by currently available contrast agents, which either lack PA-signal-generation ability for deep imaging or their absorbance spectra overlap with hemoglobin, reducing sensitivity. Here we report on a PA contrast agent based on targeted liposomes loaded with J-aggregated indocyanine green (ICG) dye (i.e., PAtrace) that we synthesized, bioconjugated, and characterized to addresses these limitations. We then validated PAtrace in phantom, in vitro, and in vivo PA imaging environments for both spectral unmixing accuracy and targeting efficacy in a folate receptor alpha-positive ovarian cancer model. These study results show that PAtrace concurrently provides significantly improved contrast-agent quantification/sensitivity and SO2 estimation accuracy compared to monomeric ICG. PAtrace's performance attributes and composition of FDA-approved components make it a promising agent for future clinical molecular PA imaging.

Improved Photoacoustic-Based Oxygen Saturation Estimation With SNR-Regularized Local Fluence Correction.

As photoacoustic (PA) imaging makes its way into the clinic, the accuracy of PA-based metrics becomes increasingly important. To address this need, a method combining finite-element-based local fluence correction (LFC) with signal-to-noise-ratio (SNR) regularization was developed and validated to accurately estimate oxygen saturation (SO2) in tissue. With data from a Vevo LAZR system, performance of our LFC approach was assessed in ex vivo blood targets (37.6%-99.6% SO2) and in vivo rat arteries. Estimation error of absolute SO2 and change in SO2 reduced from 10.1% and 6.4%, respectively, without LFC to 2.8% and 2.0%, respectively, with LFC, while the accuracy of the LFC method was correlated with the number of wavelengths acquired. This paper demonstrates the need for an SNR-regularized LFC to accurately quantify SO2 with PA imaging.