Differentiation of Hemorrhage from Iodine Using Spectral Detector CT: A Phantom Study.

BACKGROUND AND PURPOSE: Conventional CT often cannot distinguish hemorrhage from iodine extravasation following reperfusion therapy for acute ischemic stroke. We investigated the potential of spectral detector CT in differentiating these lesions. MATERIALS AND METHODS: Centrifuged blood with increasing hematocrit (5%-85%) was used to model hemorrhage. Pure blood, blood-iodine mixtures (75/25, 50/50, and 25/75 ratios), and iodine solutions (0-14 mg I/mL) were scanned in a phantom with attenuation ranging from 12 to 75 HU on conventional imaging. Conventional and virtual noncontrast attenuation was compared and investigated for correlation with calculation of relative virtual noncontrast attenuation. Values for all investigated categories were compared using the Mann-Whitney U test. Sensitivity and specificity of virtual noncontrast, relative virtual noncontrast, conventional CT attenuation, and iodine quantification for hemorrhage detection were determined with receiver operating characteristic analysis. RESULTS: Conventional image attenuation was not significantly different among all samples containing blood (P > .05), while virtual noncontrast attenuation showed a significant decrease with a decreasing blood component (P < .01) in all blood-iodine mixtures. Relative virtual noncontrast values were significantly different among all investigated categories (P < .01), with correct hemorrhagic component size estimation for all categories within a 95% confidence interval. Areas under the curve for hemorrhage detection were 0.97, 0.87, 0.29, and 0.16 for virtual noncontrast, relative virtual noncontrast, conventional CT attenuation, and iodine quantification, respectively. A ≥10-HU virtual noncontrast, ≥20-HU virtual noncontrast, ≥40% relative virtual noncontrast, and combined ≥10-HU virtual noncontrast and ≥40% relative virtual noncontrast attenuation threshold had a sensitivity/specificity for detecting hemorrhage of 100%/23%, 89%/95%, 100%/82%, and 100%/100%, respectively. CONCLUSIONS: Spectral detector CT can accurately differentiate blood from iodinated contrast in a phantom setting.

Improved visualization of hypodense liver lesions in virtual monoenergetic images from spectral detector CT: Proof of concept in a 3D-printed phantom and evaluation in 74 patients.

OBJECTIVES: The well-known boost of iodine associated-attenuation in low-keV virtual monoenergetic images (VMI_low) is frequently used to improve visualization of lesions and structures taking up contrast media. This study aimed to evaluate this concept in reverse. Hence to investigate if increased attenuation within the liver allows for improved visualization of little or not-enhancing lesions. METHODS: A 3D-printed phantom mimicking the shape of a human liver exhibiting a lesion in its center was designed and printed. Both, parenchyma- and lesion-mimic were filled with different solutions exhibiting 80/100/120HU and 0/15/40/60HU, respectively. Further, a total of 74 contrast-enhanced studies performed on a spectral detector CT scanner (SDCT) were included in this retrospective study. Patients had MRI or follow-up proven cysts and/or hypodense metastases. VMI of 40-200 keV as well as conventional images (CI) were reconstructed. ROI were placed in lesion and parenchyma(-mimics) on CI and transferred to VMI. Signal- and contrast-to-noise ratio were calculated (S-/CNR). Further, two radiologists independently evaluated image quality. Data was statistically assessed using ANOVA or Wilcoxon-test. RESULTS: In phantoms, S/CNR was significantly higher in VMI_low. The cyst-mimic in highly attenuating parenchyma-mimic on CI yielded a CNR of 6.4 ± 0.8; using VMI_40 keV, mildly hypodense lesion-mimic in poorly attenuating parenchyma-mimic exhibited a similar CNR (5.8 ± 0.9; p ≤ 0.05). The same tendency was observed in patients (cyst in CI/metastasis in VMI_40 keV: 4.4 ± 1.2/3.9 ± 1.8; p ≤ 0.05). Qualitative analysis indicated a benefit of VMI_40 keV (p ≤ 0.05). CONCLUSIONS: VMI_low from SDCT allow for an improved visualization of hypodense focal liver lesions exploiting the concept of contrast blooming in reverse.