Iodine quantification with dual-energy CT: phantom study and preliminary experience with VX2 residual tumour in rabbits after radiofrequency ablation

Evaluation of Radiation Dose Effect on Lung Function Using Iodine Maps Derived From Dual-Energy Computed Tomography

PURPOSE

There is interest in using dual-energy computed tomography (DECT) to evaluate organ function before and after radiation therapy (RT). The purpose of this study (trial identifier: NCT04863027) is to assess longitudinal changes in lung perfusion using iodine maps derived from DECT in patients with lung cancer treated with conventional or stereotactic RT.

METHODS AND MATERIALS

For 48 prospectively enrolled patients with lung cancer, a contrast-enhanced DECT using a dual-source CT simulator was acquired pretreatment and at 6 and 12 months posttreatment. Pulmonary functions tests (PFT) were obtained at baseline and at 6 and 12 months posttreatment. Iodine maps were extracted from the DECT images using a previously described 2-material decomposition framework. Longitudinal iodine maps were normalized using a reference region defined as all voxels with perfusion in the top 10% outside of the 5 Gy isodose volume. Normalized functional responses (NFR) were calculated for 3 dose ranges: <5, 5 to 20, and >20 Gy. Mixed model analysis was used to assess the correlation between dose metrics and NFR. Pearson correlation was used to assess if NFRs were correlated with PFT changes.

RESULTS

Out of the 48 patients, 21 (44%) were treated with stereotactic body RT and 27 (56%) were treated with conventionally fractionated intensity-modulated RT. Thirty-one out of these 48 patients were ultimately included in data analysis. It was found that NFR is linearly correlated with dose (P < .001) for both groups. The number of months elapsed post-RT was also found to correlate with NFR (P = .029), although this correlation was not observed for the stereotactic body RT subgroup. The NFR was not found to correlate with PFT changes.

CONCLUSIONS

DECT-derived iodine maps are a promising method for detailed anatomic evaluation of radiation effect on lung function, including potentially subclinical changes.

Advanced CT techniques for hepatic microwave ablation zone monitoring and follow-up

PURPOSE

To evaluate utility of advanced CT techniques including HighlY constrained back-projection and dual-energy CT for intra- and post-procedure hepatic microwave ablation zone monitoring.

METHODS

8 hepatic microwave ablations were performed in 4 adult swine (5 min/65 W). Low-dose routine CECT and dual-energy CT images were obtained every 1 min during ablation. Images were reconstructed ± HYPR. Image quality and dose metrics were collected. 21 MWA were performed in 4 adult swine. Immediate post-procedure CECT was performed in the arterial, portal venous, and delayed phases using both routine and DECT imaging with full-dose weight-based IV contrast dosing. An additional 16 MWA were subsequently performed in 2 adult swine. Immediate post-procedure CT was performed with half-dose IV contrast using routine and DECT. 12 patients (10 M/2F, mean age 62.4 yrs) with 14 hepatic tumors (4 HCC, 10 metastatic lesions) treated with MWA were prospectively imaged with DECT 1 month post-procedure. 120 kV equivalent images were compared to DECT [51 keV, iodine material density]. Image quality and dose metrics were collected.

RESULTS

Gas created during MWA led to high CNR in all intraprocedural CT datasets. Optimal CNRs were noted at 4 min with CNR 6.7, 15.5,15.9, and 21.5 on LD-CECT, LD-CECT + HYPR, DECT, and DECT + HYPR, respectively (p < 0.001). Image quality scores at 4 min were 1.8, 2.8, 2.4, and 3, respectively (p < 0.001). Mean radiation dose (CTDIvol) was eightfold higher for the DECT series. For swine, post-procedural DECT images (IMD/51 keV) showed improved CNR compared to routine CT at all time points with full and with reduced dose contrast (CNR 4.6, 3.2, and 1.5, respectively, at half-contrast dose, p < 0.001). For human subjects, the 51 keV and IMD images showed higher CNRs (5.8, 4.8 vs 4.0, p < 0.001) and SNRs (3.7, 5.9 vs 2.8). Ablation zone sharpness was improved with DECT (routine 3.0 ± 0.7, DECT 3.5 ± 0.5). Diagnostic confidence was higher with DECT (routine 2.3 ± 0.9, DECT 2.6 ± 0.8). Mean DLP for DECT was 905.7 ± 606 mGy-cm, CTDIvol 37.5 ± 21.2 mGy, and effective dose 13.6 ± 9.1 mSv, slightly higher than conventional CT series.

CONCLUSION

Advanced CT techniques can improve CT image quality in peri-procedural hepatic microwave ablation zone evaluation.

Effect of contrast material injection protocol on first-pass myocardial perfusion assessed by dual-energy dual-layer computed tomography

BACKGROUND

Dual-energy dual-layer computed tomography (CT) scanners can provide useful tools, such as iodine maps and virtual monochromatic images (VMI), for the evaluation of myocardial perfusion defects. Data about the influence of acquisition protocols and normal values are still lacking.

METHODS

Clinically indicated coronary CT-angiographies performed between January-October 2018 in a single university hospital with dual-energy dual-layer CT (DE-DLCT) and different injection protocols were retrospectively evaluated. The two protocols were: 35 mL in patients <80 kg and 0.5 mL/kg in patients >80 kg at 2.5 mL/s (group A) or double contrast dose at 5 mL/s (group B). Patients with coronary stenosis >50% were excluded. Regions of interest were manually drawn on 16 myocardial segments and iodine concentration was measured in mg/mL. Signal-to-noise, contrast-to-noise ratios (CNR) and image noise were measured on conventional images and VMI.

RESULTS

A total of 30 patients were included for each protocol. With iodine concentrations of 1.38±0.41 mg/mL for protocol A and 2.07±0.73 mg/mL for protocol B, the two groups were significantly different (P<0.001). No significant iodine concentration differences were found between the 16 segments (P=0.47 and P=0.09 for group A and B respectively), between basal, mid and apical segments for group A and B (P=0.28 and P=0.12 for group A and B respectively) and between wall regions for group A (P=0.06 on normalised data). In group B, iodine concentration was significantly different between three wall regions [highest values for the lateral wall, median =2.03 (1.06) mg/mL]. Post-hoc analysis showed highest contrast-to-noise and signal-to-noise in VMI at 40 eV (P<0.05).

CONCLUSIONS

Iodine concentration in left ventricular myocardium of patients without significant coronary artery stenosis varied depending on the injection protocol and appeared more heterogeneous in different wall regions at faster injection rate and greater iodine load. Signal-to-noise and contrast-to-noise gradually improved when decreasing VMI energy, although at the expenses of higher noise, demonstrating the potential of DE-DLCT to enhance objective image quality.

A Review of Imaging Methods to Assess Ultrasound-Mediated Ablation

Ultrasound ablation techniques are minimally invasive alternatives to surgical resection and have rapidly increased in use. The response of tissue to HIFU ablation differs based on the relative contributions of thermal and mechanical effects, which can be varied to achieve optimal ablation parameters for a given tissue type and location. In tumor ablation, similar to surgical resection, it is desirable to include a safety margin of ablated tissue around the entirety of the tumor. A factor in optimizing ablative techniques is minimizing the recurrence rate, which can be due to incomplete ablation of the target tissue. Further, combining focal ablation with immunotherapy is likely to be key for effective treatment of metastatic cancer, and therefore characterizing the impact of ablation on the tumor microenvironment will be important. Thus, visualization and quantification of the extent of ablation is an integral component of ablative procedures. The aim of this review article is to describe the radiological findings after ultrasound ablation across multiple imaging modalities. This review presents readers with a general overview of the current and emerging imaging methods to assess the efficacy of ultrasound ablative treatments.

Value of spectral detector computed tomography for the early assessment of technique efficacy after microwave ablation of hepatocellular carcinoma

OBJECTIVES

To investigate whether virtual monoenergetic images (VMI) and iodine maps derived from spectral detector computed tomography (SDCT) improve early assessment of technique efficacy in patients who underwent microwave ablation (MWA) for hepatocellular carcinoma (HCC) in liver cirrhosis.

METHODS

This retrospective study comprised 39 patients with 49 HCC lesions treated with MWA. Biphasic SDCT was performed 7.7±4.0 days after ablation. Conventional images (CI), VMI and IM were reconstructed. Signal- and contrast-to-noise ratio (SNR, CNR) in the ablation zone (AZ), hyperemic rim (HR) and liver parenchyma were calculated using regions-of-interest analysis and compared between CI and VMI between 40-100 keV. Iodine concentration and perfusion ratio of HR and residual tumor (RT) were measured. Two readers evaluated subjective contrast of AZ and HR, technique efficacy (complete vs. incomplete ablation) and diagnostic confidence at determining technique efficacy.

RESULTS

Attenuation of liver parenchyma, HR and RT, SNR of liver parenchyma and HR, CNR of AZ and HR were significantly higher in low-keV VMI compared to CI (all p<0.05). Iodine concentration and perfusion ratio differed significantly between HR and RT (all p<0.05; e.g. iodine concentration, 1.6±0.5 vs. 2.7±1.3 mg/ml). VMI50keV improved subjective AZ-to-liver contrast, HR-to-liver contrast, visualization of AZ margin and vessels adjacent to AZ compared to CI (all p<0.05). Diagnostic accuracy for detection of incomplete ablation was slightly higher in VMI50keV compared to CI (0.92 vs. 0.89), while diagnostic confidence was significantly higher in VMI50keV (p<0.05).

CONCLUSIONS

Spectral detector computed tomography derived low-keV virtual monoenergetic images and iodine maps provide superior early assessment of technique efficacy of MWA in HCC compared to CI.

Quantitative dual-energy CT material decomposition of holmium microspheres: local concentration determination evaluated in phantoms and a rabbit tumor model

Objectives

The purpose of this study was to assess the feasibility of dual-energy CT-based material decomposition using dual-X-ray spectra information to determine local concentrations of holmium microspheres in phantoms and in an animal model.

Materials and methods

A spectral calibration phantom with a solution containing 10 mg/mL holmium and various tube settings was scanned using a third-generation dual-energy CT scanner to depict an energy-dependent and material-dependent enhancement vectors. A serial dilution of holmium (microspheres) was quantified by spectral material decomposition and compared with known holmium concentrations. Subsequently, the feasibility of the spectral material decomposition was demonstrated in situ in three euthanized rabbits with injected (radioactive) holmium microspheres.

Results

The measured CT values of the holmium solutions scale linearly to all measured concentrations and tube settings (R² = 1.00). Material decomposition based on CT acquisitions using the tube voltage combinations of 80/150 Sn kV or 100/150 Sn kV allow the most accurate quantifications for concentrations down to 0.125 mg/mL holmium.

Conclusion

Dual-energy CT facilitates image-based material decomposition to detect and quantify holmium microspheres in phantoms and rabbits.

Key Points

• Quantification of holmium concentrations based on dual-energy CT is obtained with good accuracy.

• The optimal tube-voltage pairs for quantifying holmium were 80/150 Sn kV and 100/150 Sn kV using a third-generation dual-source CT system.

• Quantification of accumulated holmium facilitates the assessment of local dosimetry for radiation therapies.

DECT-MULTRA: Dual-Energy CT Image Decomposition With Learned Mixed Material Models and Efficient Clustering

Dual-energy computed tomography (DECT) imaging plays an important role in advanced imaging applications due to its material decomposition capability. Image-domain decomposition operates directly on CT images using linear matrix inversion, but the decomposed material images can be severely degraded by noise and artifacts. This paper proposes a new method dubbed DECT-MULTRA for image-domain DECT material decomposition that combines conventional penalized weighted-least squares (PWLS) estimation with regularization based on a mixed union of learned transforms (MULTRA) model. Our proposed approach pre-learns a union of common-material sparsifying transforms from patches extracted from all the basis materials, and a union of cross-material sparsifying transforms from multi-material patches. The common-material transforms capture the common properties among different material images, while the cross-material transforms capture the cross-dependencies. The proposed PWLS formulation is optimized efficiently by alternating between an image update step and a sparse coding and clustering step, with both of these steps having closed-form solutions. The effectiveness of our method is validated with both XCAT phantom and clinical head data. The results demonstrate that our proposed method provides superior material image quality and decomposition accuracy compared to other competing methods.

Dynamic Quantitative Iodine Myocardial Perfusion Imaging with Dual-Layer CT using a Porcine Model

Ischemic heart disease is the globally leading cause of death. When using coronary CT angiography, the functional hemodynamics within the myocardium remain uncertain. In this study myocardial CT perfusion imaging using iodine contrast agent demonstrated to strongly improve the assessment of myocardial disorders. However, a retrieval of such dynamics using Hounsfield units from conventional CT poses concerns with respect to beam-hardening effects and low contrast-to-noise ratio (CNR). Dual-energy CT offers novel approaches to overcome aforementioned limitations. Quantitative peak enhancement, perfusion, time to peak and iodine volume measurements inside the myocardium were determined resulting in 0.92 mg/ml, 0.085 mg/ml/s 17.12 s and 29.89 mg/ml*s, respectively. We report on the first extensive quantitative and iodine-based analysis of myocardial dynamics in a healthy porcine model using a dual-layer spectral CT. We further elucidate on the potential of reducing the radiation dose from 135 to 18 mGy and the contrast agent volume from 60 to 30 mL by presenting a two-shot acquisition approach and measuring iodine concentrations in the myocardium in-vivo down to 1 mg/ml, respectively. We believe that dynamic quantitative iodine perfusion imaging may be a highly sensitive tool for the precise functional assessment and monitoring of early myocardial ischemia.

Dose Optimization of Perfusion-derived Response Assessment in Hepatocellular Carcinoma Treated with Transarterial Chemoembolization: Comparison of Volume Perfusion CT and Iodine Concentration

RATIONALE AND OBJECTIVES

We assessed the value of iodine concentration (IC) as a perfusion-derived response marker for hepatocellular carcinoma (HCC) treated with transarterial chemoembolization (TACE) in comparison with volume perfusion computed tomography (VPCT) parameters.

MATERIALS AND METHODS

Forty-one HCC lesions in 32 patients examined before and after TACE were analyzed retrospectively. VPCT-parameters were calculated and lesion iodine-maps were computed using subtraction of the baseline and the scan 7 seconds after aortic peak enhancement from the corresponding 80 kVp-VPCT data set. Modified RECIST was used as standard response criteria. Comparisons were performed using Student's t test for normal distributed data and Mann-Whitney U test for non-normal distributed data. Additionally, correlation analysis, receiver operating characteristics (ROC) and interreader agreement were assessed.

RESULTS

In responding lesions, mean pre-TACE IC and blood flow (BF) were 131.2 mg/100 mL and 96.7 mL/100 mL/min, decreasing to IC 25.6 mg/100 mL (P < 0.001) and BF 28.5 mL/100 mL/min (P < 0.001) post-TACE. In nonresponding lesions, the values remained almost unchanged: pre-TACE: mean BF 79.3 mL/100 mL/min and mean IC 90.4 mg/100 mL; post-TACE: mean BF 71.3 mL/100 mL/min (n.s.) and mean IC 105.4 mg/100 mL (n.s.). Differences in IC-values revealed a high sensitivity/specificity of 96.7%/81.8%. IC and VPCT-parameters showed strong, positive correlations. Mean volume CT dose index for VPCT was 63.4 mGy and 4.9 mGy for iodine maps.

CONCLUSION

Thus, IC is a meaningful perfusion marker for local therapy response monitoring in HCC that can be acquired with low radiation dose. This information is important for further therapy response applications using dual and single energy CT.

How Well Does Dual-energy CT with Fast Kilovoltage Switching Quantify CT Number and Iodine and Calcium Concentrations?

RATIONALE AND OBJECTIVES

Because it is imperative for understanding the performance of dual-energy computed tomography scanner to determine clinical diagnosis, we aimed to assess the accuracy of quantitative measurements using dual-energy computed tomography with fast kilovoltage switching.

MATERIALS AND METHODS

Quantitative measurements were performed for 16 reference materials (physical density, 0.965-1.550 g/cm³; diameter of rod, 2.0-28.5 mm; iodine concentration, 2-15 mg/mL; and calcium concentration, 50-300 mg/mL) with varying scanning settings, and the measured values were compared to their theoretical values.

RESULTS

For high-density material, the maximum differences in Hounsfield unit values in the virtual monochromatic images at 50, 70, and 100 keV were -176.2, 61.0, and -35.2 HU, respectively, and the standard deviations over short- and long-term periods were 11.1, 6.1, and 3.5 HU at maximum. The accuracy of the Hounsfield unit measurement at 50 and 70 keV was significantly higher (P < 0.05) with higher radiation output and smaller phantom size. The difference in the iodine and calcium measurements in the large phantom were up to -2.6 and -60.4 mg/mL for iodine (5 mg/mL with 2-mm diameter) and calcium (300 mg/mL) materials, and the difference was improved with a small phantom. Metal artifact reduction software improved subjective image quality; however, the quantitative values were significantly underestimated (P < 0.05) (-49.5, -26.9, and -15.3 HU for 50, 70, and 100 keV, respectively; -1.0 and -17 mg/mL for iodine and calcium concentration, respectively) compared to that acquired without a metal material.

CONCLUSIONS

The accuracy of quantitative measurements can be affected by material density and the size of the object, radiation output, phantom size, and the presence of metal materials.

Quantification of Iodine Concentration Using Single-Source Dual-Energy Computed Tomography in a Calf Liver

OBJECTIVE

To evaluate the accuracy of single-source dual-energy computed tomography (ssDECT) in iodine quantification using various segmentation methods in an ex vivo model.

METHODS

Ten sausages, injected with variable quantities of iodinated contrast, were inserted into 2 livers and scanned with ssDECT. Material density iodine images were reconstructed. Three radiologists segmented each sausage. Iodine concentration, volume, and absolute quantity were measured. Agreement between the measured and injected iodine was assessed with the concordance correlation coefficient (CCC). Intrareader agreement was assessed using the intraclass correlation coefficient (ICC).

RESULTS

Air bubbles were observed in sausage (IX). Sausage (X) was within the same view as hyper-attenuating markers used for localization. With IX and X excluded, CCC and ICC were greater than 0.98 and greater than 0.88. When included, CCC and ICC were greater than 0.94 and greater than 0.79.

CONCLUSIONS

Iodine quantification was reproducible and precise. However, accuracy reduced in sausages consisting of air filled cavities and within the same view as hyperattenuating markers.

Dual-energy CT: a phantom comparison of different platforms for abdominal imaging

OBJECTIVES

Evaluation of imaging performance across dual-energy CT (DECT) platforms, including dual-layer CT (DLCT), rapid-kVp-switching CT (KVSCT) and dual-source CT (DSCT).

METHODS

A semi-anthropomorphic abdomen phantom was imaged on these DECT systems. Scans were repeated three times for CTDIvol levels of 10 mGy, 20 mGy, 30 mGy and different fat-simulating extension rings. Over the available range of virtual-monoenergetic images (VMI), noise as well as quantitative accuracy of hounsfield units (HU) and iodine concentrations were evaluated.

RESULTS

For all VMI levels, HU values could be determined with high accuracy compared to theoretical values. For KVSCT and DSCT, a noise increase was observed towards lower VMI levels. A patient-size dependent increase in the uncertainty of quantitative iodine concentrations is observed for all platforms. For a medium patient size the iodine concentration root-mean-square deviation at 20 mGy is 0.17 mg/ml (DLCT), 0.30 mg/ml (KVSCT) and 0.77mg/ml (DSCT).

CONCLUSION

Noticeable performance differences are observed between investigated DECT systems. Iodine concentrations and VMI HUs are accurately determined across all DECT systems. KVSCT and DLCT deliver slightly more accurate iodine concentration values than DSCT for investigated scenarios. In DLCT, low-noise and high-image contrast at low VMI levels may help to increase diagnostic information in abdominal CT.

KEY POINTS

• Current dual-energy CT platforms provide accurate, reliable quantitative information. • Dual-energy CT cross-platform evaluation revealed noticeable performance differences between different systems. • Dual-layer CT offers constant noise levels over the complete energy range.

Response assessment in pancreatic ductal adenocarcinoma: role of imaging

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive gastrointestinal (GI) malignancy with poor 5-year survival rate. Advances in surgical techniques and introduction of novel combination chemotherapy and radiation therapy regimens have necessitated the need for biomarkers for assessment of treatment response. Conventional imaging methods such as RECIST have been used for response evaluation in clinical trials particularly in patients with metastatic PDAC. However, the role of these approaches for assessing response to loco-regional and systemic therapies is limited due to complex morphological and histological nature of PDAC. Determination of tumor resectability after neoadjuvant therapy remains a challenge. This review article provides an overview of the challenges and limitations of response assessment in PDAC and reviews the current evidence for the utility of novel morphological and functional imaging tools in this disease.

Spectral performance of a whole-body research photon counting detector CT: quantitative accuracy in derived image sets

Photon-counting computed tomography (PCCT) uses a photon counting detector to count individual photons and allocate them to specific energy bins by comparing photon energy to preset thresholds. This enables simultaneous multi-energy CT with a single source and detector. Phantom studies were performed to assess the spectral performance of a research PCCT scanner by assessing the accuracy of derived images sets. Specifically, we assessed the accuracy of iodine quantification in iodine map images and of CT number accuracy in virtual monoenergetic images (VMI). Vials containing iodine with five known concentrations were scanned on the PCCT scanner after being placed in phantoms representing the attenuation of different size patients. For comparison, the same vials and phantoms were also scanned on 2nd and 3rd generation dual-source, dual-energy scanners. After material decomposition, iodine maps were generated, from which iodine concentration was measured for each vial and phantom size and compared with the known concentration. Additionally, VMIs were generated and CT number accuracy was compared to the reference standard, which was calculated based on known iodine concentration and attenuation coefficients at each keV obtained from the U.S. National Institute of Standards and Technology (NIST). Results showed accurate iodine quantification (root mean square error of 0.5 mgI/cc) and accurate CT number of VMIs (percentage error of 8.9%) using the PCCT scanner. The overall performance of the PCCT scanner, in terms of iodine quantification and VMI CT number accuracy, was comparable to that of EID-based dual-source, dual-energy scanners.

An effective noise reduction method for multi-energy CT images that exploit spatio-spectral features

PURPOSE

To develop and evaluate an image-domain noise reduction method for multi-energy CT (MECT) data.

METHODS

Multi-Energy Non-Local Means (MENLM) is a technique that uses the redundant information in MECT images to achieve noise reduction. In this method, spatio-spectral features are used to determine the similarity between pixels, making the similarity evaluation more robust to image noise. The performance of this MENLM filter was tested on images acquired on a whole-body research photon counting CT system. The impact of filtering on image quality was quantitatively evaluated in phantom studies in terms of image noise level (standard deviation of pixel values), noise power spectrum (NPS), in-plane and cross-plane spatial resolution, CT number accuracy, material decomposition performance, and subjective low-contrast spatial resolution using the American College of Radiology (ACR) CT accreditation phantom. Clinical feasibility was assessed by performing MENLM on contrast-enhanced swine images and unenhanced cadaver head images using clinically relevant doses and dose rates.

RESULTS

The phantom studies demonstrated that the MENLM filter reduced noise substantially and still preserved the shape and peak frequency of the NPS. With 80% noise reduction, MENLM filtering caused no degradation of high-contrast spatial resolution, as illustrated by the modulation transfer function (MTF) and slice sensitivity profile (SSP). CT number accuracy was also maintained for all energy channels, demonstrating that energy resolution was not affected by filtering. Material decomposition performance was improved with MENLM filtering. The subjective evaluation using the ACR phantom demonstrated an improvement in low-contrast performance. MENLM achieved effective noise reduction in both contrast-enhanced swine images and unenhanced cadaver head images, resulting in improved detection of subtle vascular structures and the differentiation of white/gray matter.

CONCLUSION

In MECT, MENLM achieved around 80% noise reduction and greatly improved material decomposition performance and the detection of subtle anatomical/low-contrast features while maintaining spatial and energy resolution. MENLM filtering may improve diagnostic or functional analysis accuracy and facilitate radiation dose and contrast media reduction for MECT.

Microscopic dual-energy CT (microDECT): a flexible tool for multichannel ex vivo 3D imaging of biological specimens

Dual-energy computed tomography (DECT) uses two different x-ray energy spectra in order to differentiate between tissues, materials or elements in a single sample or patient. DECT is becoming increasingly popular in clinical imaging and preclinical in vivo imaging of small animal models, but there have been only very few reports on ex vivo DECT of biological samples at microscopic resolutions. The present study has three main aims. First, we explore the potential of microscopic DECT (microDECT) for delivering isotropic multichannel 3D images of fixed biological samples with standard commercial laboratory-based microCT setups at spatial resolutions reaching below 10 μm. Second, we aim for retaining the maximum image resolution and quality during the material decomposition. Third, we want to test the suitability for microDECT imaging of different contrast agents currently used for ex vivo staining of biological samples. To address these aims, we used microCT scans of four different samples stained with x-ray dense contrast agents. MicroDECT scans were acquired with five different commercial microCT scanners from four companies. We present a detailed description of the microDECT workflow, including sample preparation, image acquisition, image processing and postreconstruction material decomposition, which may serve as practical guide for applying microDECT. The MATLAB script (The Mathworks Inc., Natick, MA, USA) used for material decomposition (including a graphical user interface) is provided as a supplement to this paper (https://github.com/microDECT/DECTDec). In general, the presented microDECT workflow yielded satisfactory results for all tested specimens. Original scan resolutions have been mostly retained in the separate material fractions after basis material decomposition. In addition to decomposition of mineralized tissues (inherent sample contrast) and stained soft tissues, we present a case of double labelling of different soft tissues with subsequent material decomposition. We conclude that, in contrast to in vivo DECT examinations, small ex vivo specimens offer some clear advantages regarding technical parameters of the microCT setup and the use of contrast agents. These include a higher flexibility in source peak voltages and x-ray filters, a lower degree of beam hardening due to small sample size, the lack of restriction to nontoxic contrast agents and the lack of a limit in exposure time and radiation dose. We argue that microDECT, because of its flexibility combined with already established contrast agents and the vast number of currently unexploited stains, will in future represent an important technique for various applications in biological research.

Noise suppression for dual-energy CT via penalized weighted least-square optimization with similarity-based regularization

PURPOSE

Dual-energy CT (DECT) expands applications of CT imaging in its capability to decompose CT images into material images. However, decomposition via direct matrix inversion leads to large noise amplification and limits quantitative use of DECT. Their group has previously developed a noise suppression algorithm via penalized weighted least-square optimization with edge-preservation regularization (PWLS-EPR). In this paper, the authors improve method performance using the same framework of penalized weighted least-square optimization but with similarity-based regularization (PWLS-SBR), which substantially enhances the quality of decomposed images by retaining a more uniform noise power spectrum (NPS).

METHODS

The design of PWLS-SBR is based on the fact that averaging pixels of similar materials gives a low-noise image. For each pixel, the authors calculate the similarity to other pixels in its neighborhood by comparing CT values. Using an empirical Gaussian model, the authors assign high/low similarity value to one neighboring pixel if its CT value is close/far to the CT value of the pixel of interest. These similarity values are organized in matrix form, such that multiplication of the similarity matrix to the image vector reduces image noise. The similarity matrices are calculated on both high- and low-energy CT images and averaged. In PWLS-SBR, the authors include a regularization term to minimize the L-2 norm of the difference between the images without and with noise suppression via similarity matrix multiplication. By using all pixel information of the initial CT images rather than just those lying on or near edges, PWLS-SBR is superior to the previously developed PWLS-EPR, as supported by comparison studies on phantoms and a head-and-neck patient.

RESULTS

On the line-pair slice of the Catphan(©)600 phantom, PWLS-SBR outperforms PWLS-EPR and retains spatial resolution of 8 lp/cm, comparable to the original CT images, even at 90% reduction in noise standard deviation (STD). Similar performance on spatial resolution is observed on an anthropomorphic head phantom. In addition, results of PWLS-SBR show substantially improved image quality due to preservation of image NPS. On the Catphan(©)600 phantom, NPS using PWLS-SBR has a correlation of 93% with that via direct matrix inversion, while the correlation drops to -52% for PWLS-EPR. Electron density measurement studies indicate high accuracy of PWLS-SBR. On seven different materials, the measured electron densities calculated from the decomposed material images using PWLS-SBR have a root-mean-square error (RMSE) of 1.20%, while the results of PWLS-EPR have a RMSE of 2.21%. In the study on a head-and-neck patient, PWLS-SBR is shown to reduce noise STD by a factor of 3 on material images with image qualities comparable to CT images, whereas fine structures are lost in the PWLS-EPR result. Additionally, PWLS-SBR better preserves low contrast on the tissue image.

CONCLUSIONS

The authors propose improvements to the regularization term of an optimization framework which performs iterative image-domain decomposition for DECT with noise suppression. The regularization term avoids calculation of image gradient and is based on pixel similarity. The proposed method not only achieves a high decomposition accuracy, but also improves over the previous algorithm on NPS as well as spatial resolution.

White Paper of the Society of Computed Body Tomography and Magnetic Resonance on Dual-Energy CT, Part 4: Abdominal and Pelvic Applications

This is the fourth of a series of 4 white papers that represent expert consensus documents developed by the Society of Computed Body Tomography and Magnetic Resonance through its task force on dual-energy computed tomography. This article, part 4, discusses DECT for abdominal and pelvic applications and, at the end of each, will offer our consensus opinions on the current clinical utility of the application and opportunities for further research.

Iodine concentration as a perfusion surrogate marker in oncology: Further elucidation of the underlying mechanisms using Volume Perfusion CT with 80 kVp

OBJECTIVES

To assess the value of iodine concentration (IC) in computed tomography data acquired with 80 kVp, as a surrogate for perfusion imaging in hepatocellular carcinoma (HCC) and lymphoma by comparing iodine related attenuation (IRA) with quantitative Volume Perfusion CT (VPCT)-parameters.

METHODS

VPCT-parameters were compared with intra-tumoral IC at 5 time points after the aortic peak enhancement (APE) with a temporal resolution of 3.5 sec in untreated 30 HCC and 30 lymphoma patients.

RESULTS

Intra-tumoral perfusion parameters for HCC showed a blood flow (BF) of 52.7 ± 17.0 mL/100 mL/min, blood volume (BV) 12.6 ± 4.3 mL/100 mL, arterial liver perfusion (ALP) 44.4 ± 12.8 mL/100 mL/min. Lesion IC 7 sec after APE was 133.4 ± 57.3 mg/100 mL. Lymphoma showed a BF of 36.8 ± 13.4 mL/100 mL/min, BV of 8.8 ± 2.8 mL/100 mL and IC of 118.2 ± 64.5 mg/100 mL 3.5 sec after APE. Strongest correlations exist for VPCT-derived BF and ALP with IC in HCC 7 sec after APE (r = 0.71 and r = 0.84) and 3.5 sec after APE in lymphoma lesions (r = 0.77). Significant correlations are also present for BV (r = 0.60 and r = 0.65 for HCC and lymphoma, respectively).

CONCLUSIONS

We identified a good, time-dependent agreement between VPCT-derived flow values and IC in HCC and lymphoma. Thus, CT-derived ICs 7 sec after APE in HCC and 3.5 sec in lymphoma may be used as surrogate imaging biomarkers for tumor perfusion with 80 kVp.

KEY POINTS

• Iodine concentration derived from low kVp CT is regarded as perfusion surrogate • Correlation with Perfusion CT was performed to elucidate timing and histology dependencies • Highest correlation was present 7 sec after aortic peak enhancement in hepatocellular carcinoma • In lymphoma, highest correlation was calculated 3.5 sec after aortic peak enhancement • With these results, further optimization of Dual energy CT protocols is possible.

Noise Suppression for Dual-Energy CT Through Entropy Minimization

In dual energy CT (DECT), noise amplification during signal decomposition significantly limits the utility of basis material images. Since clinically relevant objects typically contain a limited number of different materials, we propose an Image-domain Decomposition method through Entropy Minimization (IDEM) for noise suppression in DECT. Pixels of decomposed images are first linearly transformed into 2D clusters of data points, which are highly asymmetric due to strong signal correlation. An optimal axis is identified in the 2D space via numerical search such that the projection of data clusters onto the axis has minimum entropy. Noise suppression is performed on each image pixel by estimating the center-of-mass value of each data cluster along the direction perpendicular to the projection axis. The IDEM method is distinct from other noise suppression techniques in that it does not suppress pixel noise by reducing spatial variation between neighboring pixels. As supported by studies on Catphan©600 and anthropomorphic head phantoms, this feature endows our algorithm with a unique capability of reducing noise standard deviation on DECT decomposed images by approximately one order of magnitude while preserving spatial resolution and image noise power spectra (NPS). Compared with a filtering method and recently developed iterative method at the same level of noise suppression, the IDEM algorithm obtains high-resolution images with less artifacts. It also maintains accuracy of electron density measurements with less than 2% bias error. The IDEM method effectively suppresses noise of DECT for quantitative use, with appealing features on preservation of image spatial resolution and NPS.

Dual-energy CT after radiofrequency ablation of liver, kidney, and lung lesions: a review of features

Early detection of residual tumour and local tumour progression (LTP) after radiofrequency (RF) ablation is crucial in the decision whether or not to re-ablate. In general, standard contrast-enhanced computed tomography (CT) is used to evaluate the technique effectiveness; however, it is difficult to differentiate post-treatment changes from residual tumour. Dual-energy CT (DECT) is a relatively new technique that enables more specific tissue characterisation of iodine-enhanced structures because of the isolation of iodine in the imaging data. Necrotic post-ablation zones can be depicted as avascular regions by DECT on greyscale- and colour-coded iodine images. Synthesised monochromatic images from dual-energy CT with spectral analysis can be used to select the optimal keV to achieve the highest contrast-to-noise ratio between tissues. This facilitates outlining the interface between the ablation zone and surrounding tissue. Post-processing of DECT data can lead to an improved characterisation and delineation of benign post-ablation changes from LTP. Radiologists need to be familiar with typical post-ablation image interpretations when using DECT techniques. Here, we review the spectrum of changes after RF ablation of liver, kidney, and lung lesions using single-source DECT imaging, with the emphasis on the additional information obtained and pitfalls encountered with this relatively new technique.

Teaching Points

•Technical success of RF ablation means complete destruction of the tumour.

•Assessment of residual tumour on contrast-enhanced CT is hindered by post-ablative changes.

•DECT improves material differentiation and may improve focal lesion characterisation.

•Iodine maps delineate the treated area from the surrounding parenchyma well.

Iterative image-domain decomposition for dual-energy CT

PURPOSE

Dual energy CT (DECT) imaging plays an important role in advanced imaging applications due to its capability of material decomposition. Direct decomposition via matrix inversion suffers from significant degradation of image signal-to-noise ratios, which reduces clinical values of DECT. Existing denoising algorithms achieve suboptimal performance since they suppress image noise either before or after the decomposition and do not fully explore the noise statistical properties of the decomposition process. In this work, the authors propose an iterative image-domain decomposition method for noise suppression in DECT, using the full variance-covariance matrix of the decomposed images.

METHODS

The proposed algorithm is formulated in the form of least-square estimation with smoothness regularization. Based on the design principles of a best linear unbiased estimator, the authors include the inverse of the estimated variance-covariance matrix of the decomposed images as the penalty weight in the least-square term. The regularization term enforces the image smoothness by calculating the square sum of neighboring pixel value differences. To retain the boundary sharpness of the decomposed images, the authors detect the edges in the CT images before decomposition. These edge pixels have small weights in the calculation of the regularization term. Distinct from the existing denoising algorithms applied on the images before or after decomposition, the method has an iterative process for noise suppression, with decomposition performed in each iteration. The authors implement the proposed algorithm using a standard conjugate gradient algorithm. The method performance is evaluated using an evaluation phantom (Catphan©600) and an anthropomorphic head phantom. The results are compared with those generated using direct matrix inversion with no noise suppression, a denoising method applied on the decomposed images, and an existing algorithm with similar formulation as the proposed method but with an edge-preserving regularization term.

RESULTS

On the Catphan phantom, the method maintains the same spatial resolution on the decomposed images as that of the CT images before decomposition (8 pairs/cm) while significantly reducing their noise standard deviation. Compared to that obtained by the direct matrix inversion, the noise standard deviation in the images decomposed by the proposed algorithm is reduced by over 98%. Without considering the noise correlation properties in the formulation, the denoising scheme degrades the spatial resolution to 6 pairs/cm for the same level of noise suppression. Compared to the edge-preserving algorithm, the method achieves better low-contrast detectability. A quantitative study is performed on the contrast-rod slice of Catphan phantom. The proposed method achieves lower electron density measurement error as compared to that by the direct matrix inversion, and significantly reduces the error variation by over 97%. On the head phantom, the method reduces the noise standard deviation of decomposed images by over 97% without blurring the sinus structures.

CONCLUSIONS

The authors propose an iterative image-domain decomposition method for DECT. The method combines noise suppression and material decomposition into an iterative process and achieves both goals simultaneously. By exploring the full variance-covariance properties of the decomposed images and utilizing the edge predetection, the proposed algorithm shows superior performance on noise suppression with high image spatial resolution and low-contrast detectability.

Interdependencies of acquisition, detection, and reconstruction techniques on the accuracy of iodine quantification in varying patient sizes employing dual-energy CT

PURPOSE

To assess the impact of patient habitus, acquisition parameters, detector efficiencies, and reconstruction techniques on the accuracy of iodine quantification using dual-source dual-energy CT (DECT).

MATERIALS AND METHODS

Two phantoms simulating small and large patients contained 20 iodine solutions mimicking vascular and parenchymal enhancement from saline isodensity to 400 HU and 30 iodine solutions simulating enhancement of the urinary collecting system from 400 to 2,000 HU. DECT acquisition (80/140 kVp and 100/140 kVp) was performed using two DECT systems equipped with standard and integrated electronics detector technologies. DECT raw datasets were reconstructed using filtered backprojection (FBP), and iterative reconstruction (SAFIRE I/V).

RESULTS

Accuracy for iodine quantification was significantly higher for the small compared to the large phantoms (9.2 % ± 7.5 vs. 24.3 % ± 26.1, P = 0.0001), the integrated compared to the conventional detectors (14.8 % ± 20.6 vs. 18.8 % ± 20.4, respectively; P = 0.006), and SAFIRE V compared to SAFIRE I and FBP reconstructions (15.2 % ± 18.1 vs. 16.1 % ± 17.6 and 18.9 % ± 20.4, respectively; P ≤ 0.003). A significant synergism was observed when the most effective detector and reconstruction techniques were combined with habitus-adapted dual-energy pairs.

CONCLUSION

In a second-generation dual-source DECT system, the accuracy of iodine quantification can be substantially improved by an optimal choice and combination of acquisition parameters, detector, and reconstruction techniques.