Iodine images in dual energy CT: A monocentric study benchmarking quantitative iodine concentration values of the healthy liver

Photon-Counting Computed Tomography-Based Hepatic iron Quantification Using a Tungsten-Based Contrast Agent

OBJECTIVES

This study explores the potential of quantifying hepatic iron in computed tomography (CT) scans in the presence of iodine (I)- or tungsten (W)-based contrast media (CM).

MATERIALS AND METHODS

Experimental work was performed on a commercial photon-counting CT system able to simultaneously acquire up to 4 spectral data sets in a single scan. We examined 2 anthropomorphic abdominal phantoms with material samples of liquid liver tissue surrogate, fat, iron, and I- or W-based CM to mimic different liver compositions in an enhanced CT scan. Iron was quantified by material decomposition of reconstructed spectral CT images.

RESULTS

Two-material decomposition based on 2 spectral data sets provided material images of iron and liver with an accuracy of 1.4 mg/mL in the iron image of CM-free samples. The presence of W affected the iron quantification: For 2 and 4 mgW/mL in the material samples, the iron concentration was overestimated (P < 0.05) with accuracies of 2.7 and 4.7 mg/mL, respectively. Three-material decomposition based on 4 spectral data sets provided material images of iron, liver, and W, with an accuracy of 1.4 mg/mL in the images without W and 1.5 (nonsignificant difference, P > 0.07) and 1.6 mg/mL (overestimation, P > 0.03) in the iron image at 2 and 4 mgW/mL, respectively. The presence of I affected the iron quantification more than W in both 2- and 3-material decomposition: For 2 and 4 mgI/mL in the material samples, the measured iron concentration was even higher (P < 0.05), with accuracies >18 and >37 mg/mL, respectively.

CONCLUSIONS

The accuracy of iron quantification from a 3-material decomposition suggested clinically feasible detection and quantification of critical hepatic iron levels in enhanced CT scans with suitable CM. In a 2-material decomposition, severe pathology is required to detect an iron liver. W-based CM was superior to I-based CM.

A practical approach to the spatial-domain calculation of nonprewhitening model observers in computed tomography

BACKGROUND

Modern reconstruction algorithms for computed tomography (CT) can exhibit nonlinear properties, including non-stationarity of noise and contrast dependence of both noise and spatial resolution. Model observers have been recommended as a tool for the task-based assessment of image quality (Samei E et al., Med Phys. 2019; 46(11): e735-e756), but the common Fourier domain approach to their calculation assumes quasi-stationarity.

PURPOSE

A practical spatial-domain approach is proposed for the calculation of the nonprewhitening (NPW) family of model observers in CT, avoiding the disadvantages of the Fourier domain. The methodology avoids explicit estimation of a noise covariance matrix. A formula is also provided for the uncertainty on estimates of detectability index, for a given number of slices and repeat scans. The purpose of this work is to demonstrate the method and provide comparisons to the conventional Fourier approach for both iterative reconstruction (IR) and a deep Learning-based reconstruction (DLR) algorithm.

MATERIALS AND METHODS

Acquisitions were made on a Revolution CT scanner (GE Healthcare, Waukesha, Wisconsin, USA) and reconstructed using the vendor's IR and DLR algorithms (ASiR-V and TrueFidelity). Several reconstruction kernels were investigated (Standard, Lung, and Bone for IR and Standard for DLR). An in-house developed phantom with two flat contrast levels (2 and 8 mgI/mL) and varying feature size (1-10 mm diameter) was used. Two single-energy protocols (80 and 120 kV) were investigated with two dose levels (CTDIvol = 5 and 13 mGy). The spatial domain calculations relied on repeated scanning, region-of-interest placement and simple operations with image matrices. No more repeat scans were utilized than required for Fourier domain estimations. Fourier domain calculations were made using techniques described in a previous publication (Thor D et al., Med Phys. 2023;50(5):2775-2786). Differences between the calculations in the two domains were assessed using the normalized root-mean-square discrepancy (NMRSD).

RESULTS

Fourier domain calculations agreed closely with those in the spatial domain for all zero-strength IR reconstructions, which most closely resemble traditional filtered backprojection. The Fourier-based calculations, however, displayed higher detectability compared to those in the spatial domain for IR with strong iterative strength and for the DLR algorithm. The NRMSD remained within 10% for the NPW model observer without eye filter, but reached larger values when an eye filter was included. The formula for the uncertainty on the detectability index was validated by bootstrap estimates.

CONCLUSION

A practical methodology was demonstrated for calculating NPW observers in the spatial domain. In addition to being a valuable tool for verifying the applicability of typical Fourier-based methodologies, it lends itself to routine calculations for features embedded in a phantom. Higher estimates of detectability were observed when adopting the Fourier domain methodology for IR and for a DLR algorithm, demonstrating that use of the Fourier domain can indicate greater benefit to noise suppression than suggested by spatial domain calculations. This is consistent with the results of previous authors for the Fourier domain, who have compared to human and other model observers, but not, as in this study, to the NPW model observer calculated in the spatial domain.

Performance of iodine quantification through high-pitch dual-source photon-counting CT: a phantom study

PURPOSE

To investigate the feasibility and accuracy of iodine quantification using PCD-CT in standard-pitch and high-pitch scanning at different scan parameters in a phantom model.

MATERIALS AND METHODS

Four inserts with known iodine concentrations (2, 5, 10, and 15 mg/mL) were placed in the removable CT phantom and scanned using high-pitch (3.2) and standard-pitch (0.8) modes on PCD-CT. Two tube voltages (120 and 140 kVp) and four radiation doses (1, 3, 5, and 10 mGy) were alternated. Each scan setting was repeated three times. Mean iodine concentration for each insert across three consecutive slices was recorded. Percentage absolute bias (PAB) was assessed for iodine quantification.

RESULTS

A total of 96 acquisitions were conducted. In small phantom, the average for PAB was 2.96% (range: 1.75% ~ 4.56%) and 1.67% (range: 1.00% ~ 3.42%) for high-pitch and standard-pitch acquisitions, respectively. In large phantom, it was 3.72% (range: 1.75% ~ 5.97%) and 2.94% (range: 1.75% ~ 4.70%). Linear regression analysis revealed that only phantom size significantly influenced (P < 0.001) the accuracy of iodine quantification.

CONCLUSION

The high-pitch scan mode in PCD-CT can be used to quantify iodine density with similar accuracy compared with standard pitch.

Standardization of Dual-Energy CT Iodine Uptake of the Abdomen and Pelvis: Defining Reference Values in a Big Data Cohort

Background: To establish dual-energy-derived iodine density reference values in abdominopelvic organs in a large cohort of healthy subjects. Methods: 597 patients who underwent portal venous phase dual-energy CT scans of the abdomen were retrospectively enrolled. Iodine distribution maps were reconstructed, and regions of interest measurements were placed in abdominal and pelvic structures to obtain absolute iodine values. Subsequently, normalization of the abdominal aorta was conducted to obtain normalized iodine ratios. The values obtained were subsequently analyzed and differences were investigated in subgroups defined by sex, age and BMI. Results: Overall mean iodine uptake values and normalized iodine ratios ranged between 0.31 and 6.08 mg/mL and 0.06 and 1.20, respectively. Women exhibited higher absolute iodine concentration across all organs. With increasing age, normalized iodine ratios mostly tend to decrease, being most significant in the uterus, prostate, and kidneys (p < 0.015). BMI was the parameter less responsible for variations in iodine concentrations; normal weighted patients demonstrated higher values of both absolute and normalized iodine. Conclusions: Iodine concentration values and normalized iodine ratios of abdominal and pelvic organs reveal significant gender-, age-, and BMI-related differences, underscoring the necessity to integrate these variables into clinical practice.

Quantifying iodine concentration in the normal bowel wall using dual-energy CT: influence of patient and contrast characteristics

This study aimed to establish quantitative references of the normal bowel wall iodine concentration (BWIC) using dual energy CT (DECT). This single-center retrospective study included 248 patients with no history of gastrointestinal disease who underwent abdominal contrast-enhanced DECT between January and April 2022. The BWIC was normalized by the iodine concentration of upper abdominal organs (BWICorgan,) and the iodine concentration (IC) of the aorta (BWICaorta). BWIC decreased from the stomach to the rectum (mean 2.16 ± 0.63 vs. 2.19 ± 0.63 vs. 2.1 ± 0.58 vs. 1.67 ± 0.47 vs. 1.31 ± 0.4 vs. 1.18 ± 0.34 vs. 0.94 ± 0.26 mgI/mL for the stomach, duodenum, jejunum, ileum, right colon, left colon and rectum, respectively; P < 0.001). By multivariate analysis, BWIC was associated with a higher BMI (OR:1.01, 95% CI 1.00-1.02, P < 0.001) and with a higher injected contrast dose (OR: 1.51; 95% CI 1.36-1.66, P < 0.001 and 2.06; 95% CI 1.88-2.26, P < 0.001 for 500 mgI/kg and 600 mgI/kg doses taking 400 mgI/kg dose as reference). The BWICorgan was shown independent from patients and contrast-related variables while the BWICaorta was not. BWIC varies according to bowel segments and is dependent on the total iodine dose injected. It shall be normalized with the IC of the upper abdominal organs.

Spatial resolution, noise properties, and detectability index of a deep learning reconstruction algorithm for dual-energy CT of the abdomen

BACKGROUND

Iterative reconstruction (IR) has increasingly replaced traditional reconstruction methods in computed tomography (CT). The next paradigm shift in image reconstruction is likely to come from artificial intelligence, with deep learning reconstruction (DLR) solutions already entering the clinic. An enduring disadvantage to IR has been a change in noise texture, which can affect diagnostic confidence. DLR has demonstrated the potential to overcome this issue and has recently become available for dual-energy CT.

PURPOSE

To evaluate the spatial resolution, noise properties, and detectability index of a commercially available DLR algorithm for dual-energy CT of the abdomen and compare it to single-energy (SE) CT.

METHODS

An oval 25 cm x 35 cm custom-made phantom was scanned on a GE Revolution CT scanner (GE Healthcare, Waukesha, WI) at two dose levels (13 and 5 mGy) and two iodine concentrations (8 and 2 mg/mL), using three typical abdominal scan protocols: dual-energy (DE), SE 80 kV (SE-80 kV) and SE 120 kV (SE-120 kV). Reconstructions were performed with three strengths of IR (ASiR-V: AR0%, AR50%, AR100%) and three strengths of DLR (TrueFidelity: low, medium, high). The DE acquisitions were reconstructed as mono-energetic images between 40 and 80 keV. The noise power spectrum (NPS), task transfer function (TTF), and detectability index (d') were determined for the reconstructions following the recommendations of AAPM Task Group 233.

RESULTS

Noise magnitude reductions (relative to AR0%) for the SE protocols were on average (-29%, -21%) for (AR50%, TF-M), while for DE-70 keV were (-28%, -43%). There was less reduction in mean frequency (f_av ) for DLR than for IR, with similar results for SE and DE imaging. There was, however, a substantial change in the NPS shape when using DE with DLR, quantifiable by a marked reduction in the peak frequency (f_peak ) that was absent in SE mode. All protocols and reconstructions (including AR0%) exhibited slight to moderate shifts towards lower spatial frequencies at the lower dose (<12% in f_av ). Spatial resolution was consistently superior for DLR compared to IR for SE but not for DE. All protocols and reconstructions (including AR0%) showed decreased resolution with reduced dose and iodine concentration, with less decrease for DLR compared to IR. DLR displayed a higher d' than IR. The effect of energy was large: d' increased with lower keV, and SE-80 kV had higher d' than SE-120 kV. Using DE with DLR could provide higher d' than SE-80 kV at the higher dose but not at lower dose.

CONCLUSIONS

DE imaging with DLR maintained spatial resolution and reduced noise magnitude while displaying less change in noise texture than IR. The d' was also higher with DLR than IR, suggesting superiority in detectability of iodinated contrast. Despite these trends being consistent with those previously established for SE imaging, there were some noteworthy differences. For DE imaging there was no improvement in resolution compared to IR and a change in noise texture. DE imaging with low keV and DLR had superior detectability to SE DLR at the high dose but was not better than SE-80 kV at low dose.