Principles and applications of multienergy CT: Report of AAPM Task Group 291

Quantitative and qualitative image quality assessment in shoulder examinations with a first-generation photon-counting detector CT

Photon-counting detector (PCD) CT allows for ultra-high-resolution (UHR) examinations of the shoulder without requiring an additional post-patient comb filter to narrow the detector aperture. This study was designed to compare the PCD performance with a high-end energy-integrating detector (EID) CT. Sixteen cadaveric shoulders were examined with both scanners using dose-matched 120 kVp acquisition protocols (low-dose/full-dose: CTDI_vol = 5.0/10.0 mGy). Specimens were scanned in UHR mode with the PCD-CT, whereas EID-CT examinations were conducted in accordance with the clinical standard as "non-UHR". Reconstruction of EID data employed the sharpest kernel available for standard-resolution scans (ρ₅₀ = 12.3 lp/cm), while PCD data were reconstructed with both a comparable kernel (11.8 lp/cm) and a sharper dedicated bone kernel (16.5 lp/cm). Six radiologists with 2-9 years of experience in musculoskeletal imaging rated image quality subjectively. Interrater agreement was analyzed by calculation of the intraclass correlation coefficient in a two-way random effects model. Quantitative analyses comprised noise recording and calculating signal-to-noise ratios based on attenuation measurements in bone and soft tissue. Subjective image quality was higher in UHR-PCD-CT than in EID-CT and non-UHR-PCD-CT datasets (all p < 0.001). While low-dose UHR-PCD-CT was considered superior to full-dose non-UHR studies on either scanner (all p < 0.001), ratings of low-dose non-UHR-PCD-CT and full-dose EID-CT examinations did not differ (p > 0.99). Interrater reliability was moderate, indicated by a single measures intraclass correlation coefficient of 0.66 (95% confidence interval: 0.58-0.73; p < 0.001). Image noise was lowest and signal-to-noise ratios were highest in non-UHR-PCD-CT reconstructions at either dose level (p < 0.001). This investigation demonstrates that superior depiction of trabecular microstructure and considerable denoising can be realized without additional radiation dose by employing a PCD for shoulder CT imaging. Allowing for UHR scans without dose penalty, PCD-CT appears as a promising alternative to EID-CT for shoulder trauma assessment in clinical routine.

Ultrahigh-Resolution Photon-Counting CT in Cadaveric Fracture Models: Spatial Frequency Is Not Everything

In this study, the impact of reconstruction sharpness on the visualization of the appendicular skeleton in ultrahigh-resolution (UHR) photon-counting detector (PCD) CT was investigated. Sixteen cadaveric extremities (eight fractured) were examined with a standardized 120 kVp scan protocol (CTDI_vol 10 mGy). Images were reconstructed with the sharpest non-UHR kernel (Br76) and all available UHR kernels (Br80 to Br96). Seven radiologists evaluated image quality and fracture assessability. Interrater agreement was assessed with the intraclass correlation coefficient. For quantitative comparisons, signal-to-noise-ratios (SNRs) were calculated. Subjective image quality was best for Br84 (median 1, interquartile range 1-3; p ≤ 0.003). Regarding fracture assessability, no significant difference was ascertained between Br76, Br80 and Br84 (p > 0.999), with inferior ratings for all sharper kernels (p < 0.001). Interrater agreement for image quality (0.795, 0.732-0.848; p < 0.001) and fracture assessability (0.880; 0.842-0.911; p < 0.001) was good. SNR was highest for Br76 (3.4, 3.0-3.9) with no significant difference to Br80 and Br84 (p > 0.999). Br76 and Br80 produced higher SNRs than all kernels sharper than Br84 (p ≤ 0.026). In conclusion, PCD-CT reconstructions with a moderate UHR kernel offer superior image quality for visualizing the appendicular skeleton. Fracture assessability benefits from sharp non-UHR and moderate UHR kernels, while ultra-sharp reconstructions incur augmented image noise.

Impact of the automatic tube current modulation (ATCM) system on virtual monoenergetic image quality for dual-source CT: A phantom study

PURPOSE

To assess the impact of the automatic tube current modulation (ATCM) on virtual monoenergetic images (VMIs) quality in dual-source CT(DSCT).

MATERIALS AND METHODS

Acquisitions were performed on DSCT using the Mercury phantom. The acquisition parameters for an abdomen-pelvic examination with single-energy CT(SECT) and dual-energy CT(DECT) imaging were used. Acquisitions were performed for each imaging mode using fixed mAs and ATCM. The mAs value was set to obtain a volume CT dose index of 11 mGy in fixed mAs acquisitions. This value was used as the reference mAs in ATCM acquisitions. The noise power spectrum and task-based transfer function at 40,50,60 and 70 keV levels were computed on VMIs and SECT images. The detectability index (d') was calculated for a lesion with an iodine concentration of 10 mg/mL.

RESULTS

The noise magnitude on VMIs was higher with the ATCM system than with fixed mAs for all energy levels and section diameters of 21,26 and 31 cm. The noise texture and spatial resolution were similar between the fixed mAs and ATCM acquisitions for both imaging modes. The d' values were lower for all energy levels with ATCM than with fixed mAs acquisitions for 21 and 26 cm diameters by -39.82 ± 9.32%, similar at 31 cm diameter -4.13 ± 0.24% and higher at 36 cm diameter 10.40 ± 6.69%. It was higher on VMIs at all energy levels compared to SECT images.

CONCLUSIONS

The ATCM system could be used with DECT imaging to optimize patient exposure without changing the noise texture and spatial resolution of VMIs compared to fixed mAs and SECT.

Obesity-Related Pitfalls of Virtual versus True Non-Contrast Imaging-An Intraindividual Comparison in 253 Oncologic Patients

OBJECTIVES

Dual-source dual-energy CT (DECT) facilitates reconstruction of virtual non-contrast images from contrast-enhanced scans within a limited field of view. This study evaluates the replacement of true non-contrast acquisition with virtual non-contrast reconstructions and investigates the limitations of dual-source DECT in obese patients.

MATERIALS AND METHODS

A total of 253 oncologic patients (153 women; age 64.5 ± 16.2 years; BMI 26.6 ± 5.1 kg/m²) received both multi-phase single-energy CT (SECT) and DECT in sequential staging examinations with a third-generation dual-source scanner. Patients were allocated to one of three BMI clusters: non-obese: <25 kg/m² (n = 110), pre-obese: 25-29.9 kg/m² (n = 73), and obese: >30 kg/m² (n = 70). Radiation dose and image quality were compared for each scan. DECT examinations were evaluated regarding liver coverage within the dual-energy field of view.

RESULTS

While arterial contrast phases in DECT were associated with a higher CTDI_vol than in SECT (11.1 vs. 8.1 mGy; p < 0.001), replacement of true with virtual non-contrast imaging resulted in a considerably lower overall dose-length product (312.6 vs. 475.3 mGy·cm; p < 0.001). The proportion of DLP variance predictable from patient BMI was substantial in DECT (R² = 0.738) and SECT (R² = 0.620); however, DLP of SECT showed a stronger increase in obese patients (p < 0.001). Incomplete coverage of the liver within the dual-energy field of view was most common in the obese subgroup (17.1%) compared with non-obese (0%) and pre-obese patients (4.1%).

CONCLUSION

DECT facilitates a 30.8% dose reduction over SECT in abdominal oncologic staging examinations. Employing dual-source scanner architecture, the risk for incomplete liver coverage increases in obese patients.

Dual-energy CT-based stopping power prediction for dental materials in particle therapy

Radiotherapy with protons or light ions can offer accurate and precise treatment delivery. Accurate knowledge of the stopping power ratio (SPR) distribution of the tissues in the patient is crucial for improving dose prediction in patients during planning. However, materials of uncertain stoichiometric composition such as dental implant and restoration materials can substantially impair particle therapy treatment planning due to related SPR prediction uncertainties. This study investigated the impact of using dual-energy computed tomography (DECT) imaging for characterizing and compensating for commonly used dental implant and restoration materials during particle therapy treatment planning. Radiological material parameters of ten common dental materials were determined using two different DECT techniques: sequential acquisition CT (SACT) and dual-layer spectral CT (DLCT). DECT-based direct SPR predictions of dental materials via spectral image data were compared to conventional single-energy CT (SECT)-based SPR predictions obtained via indirect CT-number-to-SPR conversion. DECT techniques were found overall to reduce uncertainty in SPR predictions in dental implant and restoration materials compared to SECT, although DECT methods showed limitations for materials containing elements of a high atomic number. To assess the influence on treatment planning, an anthropomorphic head phantom with a removable tooth containing lithium disilicate as a dental material was used. The results indicated that both DECT techniques predicted similar ranges for beams unobstructed by dental material in the head phantom. When ion beams passed through the lithium disilicate restoration, DLCT-based SPR predictions using a projection-based method showed better agreement with measured reference SPR values (range deviation: 0.2 mm) compared to SECT-based predictions. DECT-based SPR prediction may improve the management of certain non-tissue dental implant and restoration materials and subsequently increase dose prediction accuracy.

Lung dual energy CT: Impact of different technological solutions on quantitative analysis

PURPOSE

To evaluated the accuracy of spectral parameters quantification of four different CT scanners in dual energy examinations of the lung using a dedicated phantom.

METHOD

Measurements were made with different technologies of the same vendor: one dual source CT scanner (DSCT), one TwinBeam (i.e. split filter) and two sequential acquisition single source scanners (SSCT). Angular separation of Calcium and Iodine signals were calculated from scatter plots of low-kVp versus high-kVp HUs. Electron density (ρe), effective atomic number (Zeff) and Iodine concentration (Iconc) were measured using Syngo.via software. Accuracy (A) of ρe, Zeff and Iconc was evaluated as the absolute percentage difference (D%) between reference values and measured ones, while precision (P) was evaluated as the variability σ obtained by repeating the measurement with different acquisition/reconstruction settings.

RESULTS

Angular separation was significantly larger for DSCT (α = 9.7°) and for sequential SSCT (α = 9.9°) systems. TwinBeam was less performing in material separation (α = 5.0°). The lowest average A was observed for TwinBeam (A_ρe = [4.7 ± 1.0], A_Z = [9.1 ± 3.1], A_Iconc = [19.4 ± 4.4]), while the best average A was obtained for Flash (A_ρe = [1.8 ± 0.4], A_Z = [3.5 ± 0.7], A_Iconc = [7.3 ± 1.8]). TwinBeam presented inferior average P (P_ρe = [0.6 ± 0.1], P_Z = [1.1 ± 0.2], P_Iconc = [10.9 ± 4.9]), while other technologies demonstrate a comparable average.

CONCLUSIONS

Different technologies performed material separation and spectral parameter quantification with different degrees of accuracy and precision. DSCT performed better while TwinBeam demonstrated not excellent performance. Iodine concentration measurements exhibited high variability due to low Iodine absolute content in lung nodules, thus limiting its clinical usefulness in pulmonary applications.

Assessment of epicardial adipose tissue on virtual non-contrast images derived from photon-counting detector coronary CTA datasets

OBJECTIVES

To assess epicardial adipose tissue (EAT) volume and attenuation of different virtual non-contrast (VNC) reconstructions derived from coronary CTA (CCTA) datasets of a photon-counting detector (PCD) CT-system to replace true non-contrast (TNC) series.

METHODS

Consecutive patients (n = 42) with clinically indicated CCTA and coronary TNC were included. Two VNC series were reconstructed, using a conventional (VNC_Conv) and a novel calcium-preserving (VNC_PC) algorithm. EAT was segmented on TNC, VNC_Conv, VNC_PC, and CCTA (CTA_-30) series using thresholds of -190 to -30 HU and an additional segmentation on the CCTA series with an upper threshold of 0 HU (CTA₀). EAT volumes and their histograms were assessed for each series. Linear regression was used to correlate EAT volumes and the Euclidian distance for histograms. The paired t-test and the Wilcoxon signed-rank test were used to assess differences for parametric and non-parametric data.

RESULTS

EAT volumes from VNC and CCTA series showed significant differences compared to TNC (all p < .05), but excellent correlation (all R² > 0.9). Measurements on the novel VNC_PC series showed the best correlation (R² = 0.99) and only minor absolute differences compared to TNC values. Mean volume differences were -12%, -3%, -13%, and +10% for VNC_Conv, VNC_PC, CTA_-30, and CTA₀ compared to TNC. Distribution of CT values on VNC_PC showed less difference to TNC than on VNC_Conv (mean attenuation difference +7% vs. +2%; Euclidean distance of histograms 0.029 vs. 0.016).

CONCLUSIONS

VNC_PC-reconstructions of PCD-CCTA datasets can be used to reliably assess EAT volume with a high accuracy and only minor differences in CT values compared to TNC. Substitution of TNC would significantly decrease patient's radiation dose.

KEY POINTS

• Measurement of epicardial adipose tissue (EAT) volume and attenuation are feasible on virtual non-contrast (VNC) series with excellent correlation to true non-contrast series (all R²>0.9). • Differences in VNC algorithms have a significant impact on EAT volume and CT attenuation values. • A novel VNC algorithm (VNC_PC) enables reliable assessment of EAT volume and attenuation with superior accuracy compared to measurements on conventional VNC- and CCTA-series.

Impact of CT Photon-Counting Virtual Monoenergetic Imaging on Visualization of Abdominal Arterial Vessels

PURPOSE

The novel photon-counting detector (PCD) technique acquires spectral data for virtual monoenergetic imaging (VMI) in every examination. The aim of this study was the evaluation of the impact of VMI of abdominal arterial vessels on quantitative and qualitative subjective image parameters.

METHODS

A total of 20 patients that underwent an arterial phase computed tomography (CT) scan of the abdomen with a novel PCD CT (Siemens NAEOTOM alpha) were analyzed regarding attenuation at different energy levels in virtual monoenergetic imaging. Contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR) were calculated and compared between the different virtual monoenergetic (VME) levels with correlation to vessel diameter. In addition, subjective image parameters (overall subjective image quality, subjective image noise and vessel contrast) were evaluated.

RESULTS

Our research showed decreasing attenuation levels with increasing energy levels in virtual monoenergetic imaging regardless of vessel diameter. CNR showed best overall results at 60 keV, and SNR at 70 keV with no significant difference to 60 keV (p = 0.294). Subjective image quality was rated best at 70 keV for overall image quality, vessel contrast and noise.

CONCLUSIONS

Our data suggest that VMI at 60-70 keV provides the best objective and subjective image quality concerning vessel contrast irrespective of vessel size.

Spectral CT in Emergency

Spectral CT technology is based on the acquisition of CT images with X-ray at 2 different energy levels which makes possible to distinguish between materials with different atomic numbers using their energy-dependent attenuation, even if those materials have similar density at conventional CT. This kind of technology has gained wide application due to the innumerable uses of their post-processing techniques, including virtual non-contrast images, iodine maps, virtual mono-chromatic images or mixed images without increasing radiation dose. There are several applications of spectral CT in Emergency Radiology that help in the detection, diagnosis and management of various pathologies such as differentiate haemorrhage from the underlaying causative lesion, diagnosis of pulmonary embolisms, demarcation of abscess, characterization of renal stones or reduction of artifacts. The purpose of this review is to provide the emergency radiologist a brief description of the main indications for spectral CT.

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.

Comparison of image quality of two versions of deep-learning image reconstruction algorithm on a rapid kV-switching CT: a phantom study

BACKGROUND

To assess the impact of the new version of a deep learning (DL) spectral reconstruction on image quality of virtual monoenergetic images (VMIs) for contrast-enhanced abdominal computed tomography in the rapid kV-switching platform.

METHODS

Two phantoms were scanned with a rapid kV-switching CT using abdomen-pelvic CT examination parameters at dose of 12.6 mGy. Images were reconstructed using two versions of DL spectral reconstruction algorithms (DLSR V1 and V2) for three reconstruction levels. The noise power spectrum (NSP) and task-based transfer function at 50% (TTF₅₀) were computed at 40/50/60/70 keV. A detectability index (d') was calculated for enhanced lesions at low iodine concentrations: 2, 1, and 0.5 mg/mL.

RESULTS

The noise magnitude was significantly lower with DLSR V2 compared to DLSR V1 for energy levels between 40 and 60 keV by -36.5% ± 1.4% (mean ± standard deviation) for the standard level. The average NPS frequencies increased significantly with DLSR V2 by 23.7% ± 4.2% for the standard level. The highest difference in TTF₅₀ was observed at the mild level with a significant increase of 61.7% ± 11.8% over 40-60 keV energy with DLSR V2. The d' values were significantly higher for DLSR V2 versus DLSR V1.

CONCLUSIONS

The DLSR V2 improves image quality and detectability of low iodine concentrations in VMIs compared to DLSR V1. This suggests a great potential of DLSR V2 to reduce iodined contrast doses.

Emerging Technology in Musculoskeletal MRI and CT

This article provides a focused overview of emerging technology in musculoskeletal MRI and CT. These technological advances have primarily focused on decreasing examination times, obtaining higher quality images, providing more convenient and economical imaging alternatives, and improving patient safety through lower radiation doses. New MRI acceleration methods using deep learning and novel reconstruction algorithms can reduce scanning times while maintaining high image quality. New synthetic techniques are now available that provide multiple tissue contrasts from a limited amount of MRI and CT data. Modern low-field-strength MRI scanners can provide a more convenient and economical imaging alternative in clinical practice, while clinical 7.0-T scanners have the potential to maximize image quality. Three-dimensional MRI curved planar reformation and cinematic rendering can provide improved methods for image representation. Photon-counting detector CT can provide lower radiation doses, higher spatial resolution, greater tissue contrast, and reduced noise in comparison with currently used energy-integrating detector CT scanners. Technological advances have also been made in challenging areas of musculoskeletal imaging, including MR neurography, imaging around metal, and dual-energy CT. While the preliminary results of these emerging technologies have been encouraging, whether they result in higher diagnostic performance requires further investigation.

A basic study for the molecular imaging of dual-energy CT in diagnosing anterior cruciate ligament injury of knee joint

Background

Anterior cruciate ligament (ACL) injury is a common disease in clinical practice that seriously affects the daily life of patients.

Purpose

To explore the molecular imaging basis of “diminution sign on dual-energy colour mapping” for the diagnosis of ACL injury by dual-energy computed tomography (DECT).

Material and Methods

The hydroxylysine and hydroxyproline reagents were prepared in different concentrations. The grouping was shown as follows: a simple concentration change group of an amino acid (group 1/2); a mixed solution group with the concentration increasing synchronously (group 3); a mixed solution group with the concentration reverse increasing and decreasing (group 4); and a mixed solution group that fix one amino acid with increasing concentration of the other (group 5/6). The samples were scanned by DECT. The solution CT value and image signal-to-noise ratio were analyzed.

Results

In group 1/2, the brightness of the dual-energy color mapping of each test tube solution and the CT value increased with increasing the concentration of amino acid. In group 6, there was no significant change in the brightness and brilliance of the dual-energy color mapping and the CT value. The remaining three groups showed an increase in the brightness and brilliance of the dual-energy color mapping and the CT value, and this increase was positively associated with the hydroxylysine concentration.

Conclusion

The dual-energy staining of the DECT imaging in “tendon” mode is related to hydroxylysine and hydroxyproline. Moreover, the degree of dual-energy color mapping is positively correlated with the change of CT value.

Contrast thresholds for detection of various iodine concentrations in subtraction CT and dual-energy CT systems

OBJECTIVE

To estimate the minimum iodine concentrations detectable in simulated vessels of various diameters for both subtraction computed tomography (CT) and dual-energy CT systems.

METHODS

Fillable tubes (diameters: 1, 3, and 5 mm) were filled with a variety of iodine concentrations (range: 0-20 mg/ml), placed in the center of 28-mm cylindrical rods and surrounded with water. Rods with and without fillable tubes were placed in a 20-cm cylindrical solid-water phantom to simulate administration of iodine in blood vessels. The phantom was scanned with clinical subtraction CT (SCT) and dual-energy CT (DECT) head protocols to assess the detection of minimum iodine concentrations in both systems. The SCT and DECT images were evaluated quantitatively with a MATLAB script to extract regions of interest (ROIs) of each simulated vessel. ROI measurements were used to calculate the limit of detectability (LOD) and signal-to-noise ratio of Rose criteria for the assessment of the contrast thresholds.

RESULTS

Both SNR_Rose and LOD methods agreed and determined the minimum detectable iodine concentration to be 0.4 mg/ml in the 5-mm diameter vessel for SCT. However, the minimum detectable concentration in the 5-mm vessel with DECT was 1 mg/ml. The 3-mm vessel had a minimum detectable concentration of 0.8 mg/ml for SCT and 2 mg/ml for DECT. Lastly, the minimum detectable iodine concentration for the 1-mm vessel was 10 mg/ml for SCT and 10 mg/ml for DECT.

CONCLUSION

In this phantom study, SCT showed the capability to detect lower iodine concentrations compared to DECT. Contrast thresholds varied for vessels of different diameters and the smaller vessels required a higher iodine concentration for detection. Based on this knowledge, radiologists can modify their protocols to increase contrast enhancement.

Early reduction in spectral dual-layer detector CT parameters as favorable imaging biomarkers in patients with metastatic renal cell carcinoma

OBJECTIVES

To associate the early change in DL-CT parameters and HU with survival outcomes and treatment response in patients with metastatic renal cell carcinoma (mRCC).

METHODS

DL-CT scans were performed at baseline and after 1 month of checkpoint immunotherapy or tyrosine kinase inhibitor therapy. Scans were reconstructed to conventional CT and DL-CT series, and used for assessment of HU, iodine concentration (IC), and the effective atomic number (Z_effective) in the combined RECISTv.1.1 target lesions. The relative changes, defined as ΔIC(combined), ΔZ_effective(combined), and ΔHU(combined), were associated with progression-free survival (PFS), overall survival (OS), and objective response rate (ORR). The reduction in the sum of diameters of target lesions ≥ 30% after 1 month was associated with OS, PFS, and ORR.

RESULTS

Overall, 115 and 104 mRCC patients were included at baseline and 1 month, respectively. Median IC(combined) decreased from 2.3 to 1.2 mg/ml (p < 0.001), Z_effective(combined) from 8.5 to 8.0 (p < 0.001), and HU(combined) from 86.0 to 64.00 HU (p < 0.001). After multivariate adjustments, the largest reductions in ΔIC(combined) (HR 0.47, 95% CI: 0.24-0.94, p = 0.033) and ΔZ_effective(combined) (HR = 0.43, 95% CI: 0.21-0.87, p = 0.019) were associated with favorable OS; the largest reduction in ΔZ_effective(combined) was associated with higher response (OR = 2.79, 95% CI: 1.12-6.94, p = 0.027). The largest reduction in ΔHU(combined) was solely associated with OS in univariate analysis (HR 0.45, 95% CI: 0.23-0.91). Reduction in SOD ≥ 30% at 1 month was not associated with outcomes (p > 0.075).

CONCLUSIONS

Early reductions at 1 month in ΔIC(combined) and ΔZ_effective(combined) are associated with favorable outcomes in patients with mRCC. This information may reassure physicians and patients about treatment strategy.

KEY POINTS

• Early reductions following 1 month of therapy in spectral dual-layer detector CT-derived iodine concentration and the effective atomic number (Z_effective) are independent biomarkers for better overall survival in patients with metastatic renal cell carcinoma. • Early reduction after 1 month of therapy in the effective atomic number (Z_effective) is an independent imaging biomarker for better treatment response metastatic renal cell carcinoma.

Spectral CT imaging: Technical principles of dual-energy CT and multi-energy photon-counting CT

Spectral computed tomography (CT) imaging encompasses a unique generation of CT systems based on a simple principle that makes use of the energy-dependent information present in CT images. Over the past two decades this principle has been expanded with the introduction of dual-energy CT systems. The first generation of spectral CT systems, represented either by dual-source or dual-layer technology, opened up a new imaging approach in the radiology community with their ability to overcome the limitations of tissue characterization encountered with conventional CT. Its expansion worldwide can also be considered as an important leverage for the recent groundbreaking technology based on a new chain of detection available on photon counting CT systems, which holds great promise for extending CT towards multi-energy CT imaging. The purpose of this article was to detail the basic principles and techniques of spectral CT with a particular emphasis on the newest technical developments of dual-energy and multi-energy CT systems.

Photon-counting detector CT improves quality of arterial phase abdominal scans: A head-to-head comparison with energy-integrating CT

PURPOSE

Photon-counting detector (PCD)-CT is expected to have a substantial impact on oncologic abdominal imaging. We compared subjective and objective image quality between PCD-CT and conventional energy-integrating detector (EID-)CT arterial phase abdominal scans.

METHODS

This study included 84 patients undergoing both types of abdominal CT. EID-CT scans were acquired with a tube voltage of 100 kVp. With PCD-CT, acquired with 120-kVp, we reconstructed polychromatic T3D images and virtual monoenergetic images (VMIs) in 10-keV intervals from 40 to 90 keV. Quantitative image analysis included noise and contrast-to-noise ratio (CNR) of hepatic vessels, kidney cortex, and hypervascular liver lesions to liver parenchyma. Three raters used a 5-point Likert scale for qualitative image analysis of image noise and contrast, lesion conspicuity, and overall image quality. Radiation dose exposure (CT dose index) was compared between the two CT types.

RESULTS

Mean CT dose index and effective dose were respectively 18 % and 26 % lower with PCD-CT versus EID-CT. Compared with EID-CT, CNRs of kidney cortex and vessel to liver parenchyma were significantly higher in PCD-CT VMIs at energies ≤ 60 keV and in polychromatic T3D images (p < 0.004). Overall image quality of PCD-CT VMIs at 50 and 60 keV was rated as significantly better (p < 0.01) than the EID-CT images (inter-reader agreement alpha = 0.80). Lesion conspicuity was significantly better in low-keV VMIs (p < 0.03) and worse in > 70-keV VMIs.

CONCLUSIONS

With low-keV VMI, PCD-CT yields significantly improved objective and subjective quality of arterial phase oncological imaging compared with EID-CT. This advantage may translate into higher diagnostic confidence and lower radiation dose protocols.

Deep learning-based virtual noncalcium imaging in multiple myeloma using dual-energy CT

BACKGROUND

Dual-energy CT with virtual noncalcium (VNCa) images allows the evaluation of focal intramedullary bone marrow involvement in patients with multiple myeloma. However, current commercial VNCa techniques suffer from excessive image noise and artifacts due to material decomposition used in synthesizing VNCa images.

OBJECTIVES

In this work, we aim to improve VNCa image quality for the assessment of focal multiple myeloma, using an Artificial intelligence based Generalizable Algorithm for mulTi-Energy CT (AGATE) method.

MATERIALS AND METHODS

AGATE method used a custom dual-task convolutional neural network (CNN) that concurrently carries out material classification and quantification. The material classification task provided an auxiliary regularization to the material quantification task. CNN parameters were optimized using custom loss functions that involved cross-entropy, physics-informed constraints, structural redundancy in spectral and material images, and texture information in spectral images. For training data, CT phantoms (diameters 30 to 45 cm) with tissue-mimicking inserts were scanned on a third generation dual-source CT system. Scans were performed at routine dose and half of the routine dose. Small image patches (i.e., 40 × 40 pixels) of tissue-mimicking inserts with known basis material densities were extracted for training samples. Numerically simulated insert materials with various shapes increased diversity of training samples. Generalizability of AGATE was evaluated using CT images from phantoms and patients. In phantoms, material decomposition accuracy was estimated using mean-absolute-percent-error (MAPE), using physical inserts that were not used during the training. Noise power spectrum (NPS) and modulation transfer function (MTF) were compared across phantom sizes and radiation dose levels. Five patients with multiple myeloma underwent dual-energy CT, with VNCa images generated using a commercial method and AGATE. Two fellowship-trained musculoskeletal radiologists reviewed the VNCa images (commercial and AGATE) side-by-side using a dual-monitor display, blinded to VNCa type, rating the image quality for focal multiple myeloma lesion visualization using a 5-level Likert comparison scale (-2 = worse visualization and diagnostic confidence, -1 = worse visualization but equivalent diagnostic confidence, 0 = equivalent visualization and diagnostic confidence, 1 = improved visualization but equivalent diagnostic confidence, 2 = improved visualization and diagnostic confidence). A post hoc assignment of comparison ratings was performed to rank AGATE images in comparison to commercial ones.

RESULTS

AGATE demonstrated consistent material quantification accuracy across phantom sizes and radiation dose levels, with MAPE ranging from 0.7% to 4.4% across all testing materials. Compared to commercial VNCa images, the AGATE-synthesized VNCa images yielded considerably lower image noise (50-77% noise reduction) without compromising noise texture or spatial resolution across different phantom sizes and two radiation doses. AGATE VNCa images had markedly reduced area under NPS curves and maintained NPS peak frequency (0.7 lp/cm to 1.0 lp/cm), with similar MTF curves (50% MTF at 3.0 lp/cm). In patients, AGATE demonstrated reduced image noise and artifacts with improved delineation of focal multiple myeloma lesions (all readers comparison scores indicating improved overall diagnostic image quality [scores 1 or 2]).

CONCLUSIONS

AGATE demonstrated reduced noise and artifacts in VNCa images and ability to improve visualization of bone marrow lesions for assessing multiple myeloma.

Dual-layer dual-energy CT for improving differential diagnosis of squamous cell carcinoma from adenocarcinoma at gastroesophageal junction

Objective

To examine the clinical values of dual-energy CT parameters derived from dual-layer spectral detector CT (SDCT) in the differential diagnosis of squamous cell carcinoma (SCC) and adenocarcinoma (AC) of the gastroesophageal junction (GEJ).

Methods

Totally 66 patients with SCC and AC of the GEJ confirmed by pathological analysis were retrospectively enrolled, and underwent dual-phase contrast-enhancement chest CT with SDCT. Plain CT value, CT attenuation enhancement (△CT), iodine concentration (IC), spectral slope (λHU), effective atomic number (Zeff) and 40keV CT value (CT40keV) of the lesion in the arterial phase (AP) and venous phase (VP) were assessed. Multivariate logistic regression analysis was performed to evaluate the diagnostic efficacies of different combinations of dual-energy CT parameters. Receiver operating characteristic (ROC) curves were used to analyze the accuracy of dual-energy CT parameters and Delong test was used to compare AUCs.

Results

IC, λHU, Zeff and CT40keV in AP and VP and △CT in VP were significantly higher in the AC group than those in the SCC group (all P&lt;0.05). ROC curve analysis showed that IC, λHU, Zeff and CT40keV in VP had high diagnostic performances, with AUCs of 0.74, 0.74, 0.79 and 0.78, respectively. Logistic regression showed the combination of ICVP, λHU VP, CT40keV VP and Zeff VP had the highest AUC (0.84), with a threshold of 0.40, sensitivity and specificity in distinguishing SCC and AC were 93.1% and 73.0%, respectively. Delong test showed that the AUC of △CTVP was lower than other AUCs of dual-energy CT parameters.

Conclusion

Dual-energy CT parameters derived from SDCT provide added value in the differential diagnosis of SCC and AC of the GEJ, especially the combination of IC, λHU, CT40keV and Zeff in VP.

Advances in knowledge

Dual-energy CT parameters derived from dual-layer spectral detector CT provide added value to differentiate AC from SCC at the GEJ, especially the combination of effective atomic number, spectral slope, iodine concentration and 40keV CT value in VP.

Reducing Visceral-Motion-Related Artifacts on the Liver with Dual-Energy CT: A Comparison of Four Different CT Scanner Techniques

Purpose: To assess the influence of different dual-energy CT (DECT) scanner techniques on the severity of visceral-motion-related artifacts on the liver. Methods: Two independent readers retrospectively evaluated visceral-motion-related artifacts on the liver on 120-kVp(-like), monoenergetic low- and high-keV, virtual non-contrast (VNC), and iodine images acquired on a dual-source, twin-beam, fast kV-switching, and dual-layer spectral detector scanner. Quantitative assessment: Depth of artifact extension into the liver, measurements of Hounsfield Units (HU) and iodine concentrations. Qualitative assessment: Five-point Likert scale (1 = none to 5 = severe). Artifact severity between image reconstructions were compared by Wilcoxon signed-rank and paired t-tests. Results: 615 contrast-enhanced routine clinical DECT scans of the abdomen were evaluated in 458 consecutive patients (mean age: 61 ± 14 years, 331 men). For dual-source and twin-beam scanners, depth of extension of artifacts into the liver was significantly shorter and artifact severity scores significantly lower for 120-kVp-like images compared with the other image reconstructions (p < 0.001, each). For fast kV-switching and spectral detector scanner images, depth of extension of artifacts was significantly shorter and artifact severity scores significantly lower for iodine images (p < 0.001, each). Dual-source 120-kVp-like and spectral detector iodine images reduced artifacts to an extent that no significant difference in HU or iodine concentrations between artifacts (dual-source: 97 HU, spectral detector: 1.9 mg/mL) and unaffected liver parenchyma (dual-source: 108 HU, spectral detector: 2.1 mg/mL) was measurable (dual-source: p = 0.32, spectral detector: p = 0.15). Conclusion: Visceral-motion-related artifacts on the liver can be markedly reduced by viewing 120-kVp-like images for dual-source and twin-beam DECT scanners and iodine images for fast kV-switching and dual-layer spectral detector DECT scanners.

Dual-energy CT: Technical considerations and clinical applications

Although dual-energy CT was initially described by Hounsfield in 1973, it remains underused in clinical practice. It is therefore important to emphasize the clinical benefits and limitations of this technique. Iodine mapping makes it possible to quantify the uptake of iodine, which is very important in characterizing tumors, lung perfusion, pulmonary nodules, and the tumor response to new treatments. Dual-energy CT also makes it possible to obtain virtual single-energy images and virtual images without iodinated contrast or without calcium, as well as to separate materials such as uric acid or fat and to elaborate hepatic iron overload maps. In this article, we review some of the clinical benefits and technical limitations to improve understanding of dual-energy CT and expand its use in clinical practice.

Introducing and Building a Dual-Energy CT Business

In recent years, there has been increased utilization of Dual-energy CT (DECT) in diagnostic imaging, mainly due to a reduction of effective radiation dose and lower intravenous contrast dose requirement in DECT imaging compared to conventional CT. A comprehensive imaging protocol and teamwork involving technologists and radiologists are needed to successfully implement DECT in clinical practice. At the same time, insight into the direct and indirect expenditures incurred is critical for rendering a cost-effective service to the patient and institution. This paper focuses on introducing the foundations of DECT to the readers and discusses the impediments encountered during the implementation of DECT in clinical practice. Potential solutions to these challenges are also proposed.

Impact of beam-hardening corrections on proton relative stopping power estimates from single- and dual-energy CT

A major contributing factor to proton range uncertainty is the conversion of computed tomography (CT) Hounsfield units (HU) to proton relative stopping power (RSP). This uncertainty is heightened in the presence of X-ray beam-hardening artifact (BHA), which has two manifestations: cupping and streaking, especially in and near bone tissue. This uncertainty can affect the accuracy of proton RSP calculation for treatment planning in proton radiotherapy. Dual-energy CT (DECT) and iterative beam-hardening correction (iBHC) both show promise in mitigating CT BHA. This present work attempts to analyze the relative robustness of iBHC and DECT techniques on both manifestations of BHA. The stoichiometric method for HU to RSP conversion was used for single-energy CT (SECT) and DECT-based monochromatic techniques using a tissue substitute phantom. Cupping BHA was simulated by measuring the HU of a bone substitute plug in wax/3D-printed phantoms of increasing size. Streaking BHA was simulated by placing a solid water plug between two bone plugs in a wax phantom. Finally, the effect of varying calibration phantom size on RSP was calculated in an anthropomorphic head phantom. The RSP decreased -0.002 cm^-1 as phantom size increased for SECT but remained largely constant when iBHC applied or with DECT techniques. The RSP varied a maximum of 2.60% in the presence of streaking BHA in SECT but was reduced to 1.40% with iBHC. For DECT techniques, the maximum difference was 2.40%, reduced to 0.6% with iBHC. Comparing calibration phantoms of 20- and 33-cm diameter, maximum voxel differences of 5 mm in the water-equivalent thickness were observed in the skull but reduced to 1.3 mm with iBHC. The DECT techniques excelled in mitigating cupping BHA, but streaking BHA still could be observed. The use of iBHC reduced RSP variation with BHA in both SECT and DECT techniques.

Potential of a Second-Generation Dual-Layer Spectral CT for Dose Calculation in Particle Therapy Treatment Planning

In particle therapy treatment planning, dose calculation is conducted using patient-specific maps of tissue ion stopping power ratio (SPR) to predict beam ranges. Improving patient-specific SPR prediction is therefore essential for accurate dose calculation. In this study, we investigated the use of the Spectral CT 7500, a second-generation dual-layer spectral computed tomography (DLCT) system, as an alternative to conventional single-energy CT (SECT) for patient-specific SPR prediction. This dual-energy CT (DECT)-based method allows for the direct prediction of SPR from quantitative measurements of relative electron density and effective atomic number using the Bethe equation, whereas the conventional SECT-based method consists of indirect image data-based prediction through the conversion of calibrated CT numbers to SPR. The performance of the Spectral CT 7500 in particle therapy treatment planning was characterized by conducting a thorough analysis of its SPR prediction accuracy for both tissue-equivalent materials and common non-tissue implant materials. In both instances, DLCT was found to reduce uncertainty in SPR predictions compared to SECT. Mean deviations of 0.7% and 1.6% from measured SPR values were found for DLCT- and SECT-based predictions, respectively, in tissue-equivalent materials. Furthermore, end-to-end analyses of DLCT-based treatment planning were performed for proton, helium, and carbon ion therapies with anthropomorphic head and pelvic phantoms. 3D gamma analysis was performed with ionization chamber array measurements as the reference. DLCT-predicted dose distributions revealed higher passing rates compared to SECT-predicted dose distributions. In the DLCT-based treatment plans, measured distal-edge evaluation layers were within 1 mm of their predicted positions, demonstrating the accuracy of DLCT-based particle range prediction. This study demonstrated that the use of the Spectral CT 7500 in particle therapy treatment planning may lead to better agreement between planned and delivered dose compared to current clinical SECT systems.

Deep Learning and Domain-Specific Knowledge to Segment the Liver from Synthetic Dual Energy CT Iodine Scans

We map single energy CT (SECT) scans to synthetic dual-energy CT (synth-DECT) material density iodine (MDI) scans using deep learning (DL) and demonstrate their value for liver segmentation. A 2D pix2pix (P2P) network was trained on 100 abdominal DECT scans to infer synth-DECT MDI scans from SECT scans. The source and target domain were paired with DECT monochromatic 70 keV and MDI scans. The trained P2P algorithm then transformed 140 public SECT scans to synth-DECT scans. We split 131 scans into 60% train, 20% tune, and 20% held-out test to train four existing liver segmentation frameworks. The remaining nine low-dose SECT scans tested system generalization. Segmentation accuracy was measured with the dice coefficient (DSC). The DSC per slice was computed to identify sources of error. With synth-DECT (and SECT) scans, an average DSC score of 0.93±0.06 (0.89±0.01) and 0.89±0.01 (0.81±0.02) was achieved on the held-out and generalization test sets. Synth-DECT-trained systems required less data to perform as well as SECT-trained systems. Low DSC scores were primarily observed around the scan margin or due to non-liver tissue or distortions within ground-truth annotations. In general, training with synth-DECT scans resulted in improved segmentation performance with less data.

Principles and Available Hardware in DECT

Computed tomography (CT) has undergone a phenomenal evolution since its introduction in 1971 and has revolutionized diagnostic radiology. It is now the cornerstone of diagnostic imaging and has become an inevitable part of the management of patients. Among all the advancements and breakthroughs witnessed over the years, the most recent and most advanced is the dual-energy CT (DECT), also known as spectral CT, introduced in 2006. In DECT, two datasets are obtained by scanning with two different energy spectra (low and high energy). The difference in attenuation can differentiate materials with different elemental compositions but similar attenuation in single-energy CT. Therefore, it has widespread clinical applications based on its potential for material decomposition and virtual monoenergetic imaging. In this review, the principle and hardware of DECT will be presented with an overview of its clinical applications.

Simultaneous Image Reconstruction and Element Decomposition for Iodine Contrast Agent Visualization in Multienergy Element-Resolved Cone Beam CT

Iodine contrast agent is widely used in liver cancer radiotherapy at CT simulation stage to enhance detectability of tumor. However, its application in cone beam CT (CBCT) for image guidance before treatment delivery is still limited because of poor image quality and excessive dose of contrast agent during multiple treatment fractions. We previously developed a multienergy element-resolved (MEER) CBCT framework that included x-ray projection data acquisition on a conventional CBCT platform in a kVp-switching model and a dictionary-based image reconstruction algorithm that simultaneously reconstructed x-ray attenuation images at each kilovoltage peak (kVp), an electron density image, and elemental composition images. In this study, we investigated feasibility using MEER-CBCT for low-concentration iodine contrast agent visualization. We performed simulation and experimental studies using a phantom with inserts containing water and different concentrations of iodine solution and the MEER-CBCT scan with 600 projections in a full gantry rotation, in which the kVp level sequentially changed among 80, 100, and 120 kVps. We included iodine material in the dictionary of the reconstruction algorithm. We analyzed iodine detectability as quantified by contrast-to-noise ratio (CNR) and compared results with those of CBCT images reconstructed by the standard filter back projection (FBP) method with 600 projections. MEER-CBCT achieved similar contrast enhancement as FBP method but significantly higher CNR. At 2.5% iodine solution concentration, FBP method achieved 170 HU enhancement and CNR of 2.0, considered the standard CNR for successful tumor visualization. MEER-CBCT achieved the same CNR but at ~6.3 times lower iodine concentration of 0.4%.

Impact Analysis of Different CT Configurations of Carotid Artery Plaque Calcifications on Cerebrovascular Events

BACKGROUND AND PURPOSE

CT is considered the standard reference both for quantification and characterization of carotid artery calcifications. Our aim was to investigate the relationship among different types of calcium configurations detected with CT within the plaque with a novel classification and to investigate the prevalence of cerebrovascular events.

MATERIALS AND METHODS

Seven hundred ninety patients (men = 332; mean age, 69.7 [SD, 13] years; 508 symptomatic for cerebrovascular symptoms and 282 asymptomatic) who underwent computed tomography of the carotid arteries were retrospectively included in this institutional review board-approved study. The plaque was classified into 6 types according to the different types of calcium configurations as the following: type 1, complete absence of calcification within the plaque; type 2, intimal or superficial calcifications; type 3, deep or bulky calcifications; type 4, adventitial calcifications with internal soft plaque of <2 mm thickness; type 5, mixed patterns with intimal and bulky calcifications; and type 6, positive rim sign.

RESULTS

The highest prevalence of cerebrovascular events was observed for type 6, for which 89 of the 99 cases were symptomatic. Type 6 plaque had the highest degree of correlation with TIA, stroke, symptoms, and ipsilateral infarct for both sides with a higher prevalence in younger patients. The frequency of symptoms observed by configuration type significantly differed between right and left plaques, with symptoms observed more frequently in type 6 calcification on the right side (50/53; 94%) than on the left side (39/46; 85%, P < .001).

CONCLUSIONS

We propose a novel carotid artery plaque configuration classification that is associated with the prevalence of cerebrovascular events. If confirmed in longitudinal analysis, this classification could be used to stratify the risk of occurrence of ischemic events.

Accuracy of virtual monochromatic images generated by the decomposition of photoelectric absorption and Compton scatter in dual-energy computed tomography

The decomposition of the linear attenuation coefficient into photoelectric absorption and Compton scattering provides virtual monochromatic images (VMIs). The accuracy of the computed tomography (CT) number of VMI, which is obtained by decomposing the linear attenuation coefficient into photoelectric absorption and Compton scattering, was verified in the energy range of 40-200 keV. The possibility of improving the accuracy of CT numbers by using pre-energy-calibrated images as input was also investigated. The VMIs were generated in two groups of images: (i) dual-energy scanned images and (ii) high- and low-energy images generated by two-material decomposition (i.e., pre-energy-calibrated images). The object for analysis was solid iodine rods inserted in the center of the multi-energy CT phantom. The VMIs were generated from the dual-energy scanned images and pre-energy-calibrated images, and the theoretical and measured CT numbers of solid iodine rods were compared. Furthermore, the absolute error (AE) and relative error (RE) were calculated. With both images, the accuracy of the CT numbers was extremely high for regions close to the high- and low-tube-voltage X-ray energy or the high and low energy of the input images. By using the pre-energy-calibrated images, the maximum AE was reduced from 133 to 96 HU at an energy of 40 keV. Similarly, the maximum RE was reduced from 325 to 50% at an energy of 200 keV. The pre-energy-calibrated images reduced the overall error of the CT numbers and controlled the energy region where accurate CT numbers could be obtained.

Virtual monoenergetic images from dual-energy CT: systematic assessment of task-based image quality performance

Background

To compare task-based image quality (TB-IQ) among virtual monoenergetic images (VMI) and linear-blended images (LBI) from dual-energy CT as a function of contrast task, radiation dose, size, and lesion diameter.

Methods

A TB-IQ phantom (Mercury Phantom 4.0, Sun Nuclear Corporation) was imaged on a third-generation dual-source dual-energy CT with 100/Sn150 kVp at three volume CT dose levels (5, 10, 15 mGy). Three size sections (diameters 16, 26, 36 cm) with subsections for image noise and spatial resolution analysis were used. High-contrast tasks (e.g., calcium-containing stone and vascular lesion) were emulated using bone and iodine inserts. A low-contrast task (e.g., low-contrast lesion or hematoma) was emulated using a polystyrene insert. VMI at 40-190 keV and LBI were reconstructed. Noise power spectrum (NPS) determined the noise magnitude and texture. Spatial resolution was assessed using the task-transfer function (TTF) of the three inserts. The detectability index (d') served as TB-IQ metric.

Results

Noise magnitude increased with increasing phantom size, decreasing dose, and decreasing VMI-energy. Overall, noise magnitude was higher for VMI at 40-60 keV compared to LBI (range of noise increase, 3-124%). Blotchier noise texture was found for low and high VMIs (40-60 keV, 130-190 keV) compared to LBI. No difference in spatial resolution was observed for high contrast tasks. d' increased with increasing dose level or lesion diameter and decreasing size. For high-contrast tasks, d' was higher at 40-80 keV and lower at high VMIs. For the low-contrast task, d' was higher for VMI at 70-90 keV and lower at 40-60 keV.

Conclusions

Task-based image quality differed among VMI-energy and LBI dependent on the contrast task, dose level, phantom size, and lesion diameter. Image quality could be optimized by tailoring VMI-energy to the contrast task. Considering the clinical relevance of iodine, VMIs at 50-60 keV could be proposed as an alternative to LBI.

Dual-layer spectral CT for proton, helium, and carbon ion beam therapy planning of brain tumors

Pretreatment computed tomography (CT) imaging is an essential component of the particle therapy treatment planning chain. Treatment planning and optimization with charged particles require accurate and precise estimations of ion beam range in tissues, characterized by the stopping power ratio (SPR). Reduction of range uncertainties arising from conventional CT-number-to-SPR conversion based on single-energy CT (SECT) imaging is of importance for improving clinical practice. Here, the application of a novel imaging and computational methodology using dual-layer spectral CT (DLCT) was performed toward refining patient-specific SPR estimates. A workflow for DLCT-based treatment planning was devised to evaluate SPR prediction for proton, helium, and carbon ion beam therapy planning in the brain. DLCT- and SECT-based SPR predictions were compared in homogeneous and heterogeneous anatomical regions. This study included eight patients scanned for diagnostic purposes with a DLCT scanner. For each patient, four different treatment plans were created, simulating tumors in different parts of the brain. For homogeneous anatomical regions, mean SPR differences of about 1% between the DLCT- and SECT-based approaches were found. In plans of heterogeneous anatomies, relative (absolute) proton range shifts of 0.6% (0.4 mm) in the mean and up to 4.4% (2.1 mm) at the distal fall-off were observed. In the investigated cohort, 12% of the evaluated organs-at-risk (OARs) presented differences in mean or maximum dose of more than 0.5 Gy (RBE) and up to 6.8 Gy (RBE) over the entire treatment. Range shifts and dose differences in OARs between DLCT and SECT in helium and carbon ion treatment plans were similar to protons. In the majority of investigated cases (75th percentile), SECT- and DLCT-based range estimations were within 0.6 mm. Nonetheless, the magnitude of patient-specific range deviations between SECT and DLCT was clinically relevant in heterogeneous anatomical sites, suggesting further study in larger, more diverse cohorts. Results indicate that patients with brain tumors may benefit from DLCT-based treatment planning.

Dual-energy CT in pulmonary vascular disease

Dual-energy CT (DECT) imaging is a technique that extends the capabilities of CT beyond that of established densitometric evaluations. CT pulmonary angiography (CTPA) performed with dual-energy technique benefits from both the availability of low kVp CT data and also the concurrent ability to quantify iodine enhancement in the lung parenchyma. Parenchymal enhancement, presented as pulmonary perfused blood volume maps, may be considered as a surrogate of pulmonary perfusion. These distinct capabilities have led to new opportunities in the evaluation of pulmonary vascular diseases. Dual-energy CTPA offers the potential for improvements in pulmonary emboli detection, diagnostic confidence, and most notably severity stratification. Furthermore, the appreciated insights of pulmonary vascular physiology conferred by DECT have resulted in increased use for the assessment of pulmonary hypertension, with particular utility in the subset of patients with chronic thromboembolic pulmonary hypertension. With the increasing availability of dual energy-capable CT systems, dual energy CTPA is becoming a standard-of-care protocol for CTPA acquisition in acute PE. Furthermore, qualitative and quantitative pulmonary vascular DECT data heralds promise for the technique as a "one-stop shop" for diagnosis and surveillance assessment in patients with pulmonary hypertension. This review explores the current application, clinical value, and limitations of DECT imaging in acute and chronic pulmonary vascular conditions. It should be noted that certain manufacturers and investigators prefer alternative terms, such as spectral or multi-energy CT imaging. In this review, the term dual energy is utilised, although readers can consider these terms synonymous for purposes of the principles explained.

DIRECT-Net: A unified mutual-domain material decomposition network for quantitative dual-energy CT imaging

PURPOSE

The purpose of this paper is to present an end-to-end deep convolutional neural network to improve the dual-energy CT (DECT) material decomposition performance.

METHODS

In this study, we proposes a unified mutual-domain (sinogram domain and CT domain) material decomposition network (DIRECT-Net) for DECT imaging. By design, the DIRECT-Net has immediate access to mutual-domain data, and utilizes stacked convolution neural network layers for noise reduction and material decomposition. The training data are numerically generated following the fundamental DECT imaging physics. Numerical simulation of the XCAT digital phantom, experiments of a biological specimen, a calcium chloride phantom and an iodine solution phantom are carried out to evaluate the performance of DIRECT-Net. Comparisons are performed with different DECT decomposition algorithms.

RESULTS

Results demonstrate that the proposed DIRECT-Net can generate water and bone basis images with less artifacts compared to the other decomposition methods. Additionally, the quantification errors of the calcium chloride (75-375 mg/cm³ ) and the iodine (2-20 mg/cm³ ) are less than 4%.

CONCLUSIONS

An end-to-end material decomposition network is proposed for quantitative DECT imaging. The qualitative and quantitative results demonstrate that this new DIRECT-Net has promising benefits in improving the DECT image quality.

Improving radiation physics, tumor visualisation, and treatment quantification in radiotherapy with spectral or dual-energy CT

Over the past decade, spectral or dual‐energy CT has gained relevancy, especially in oncological radiology. Nonetheless, its use in the radiotherapy (RT) clinic remains limited. This review article aims to give an overview of the current state of spectral CT and to explore opportunities for applications in RT.

In this article, three groups of benefits of spectral CT over conventional CT in RT are recognized. Firstly, spectral CT provides more information of physical properties of the body, which can improve dose calculation. Furthermore, it improves the visibility of tumors, for a wide variety of malignancies as well as organs‐at‐risk OARs, which could reduce treatment uncertainty. And finally, spectral CT provides quantitative physiological information, which can be used to personalize and quantify treatment.

Quantitative lung perfusion blood volume using dual energy CT-based effective atomic number (Zeff ) imaging

BACKGROUND

Iodine material images (aka iodine basis images) generated from dual energy computed tomography (DECT) have been used to assess potential perfusion defects in the pulmonary parenchyma. However, iodine material images do not provide the needed absolute quantification of the pulmonary blood pool, as materials with effective atomic numbers (Zeff ) different from those of basis materials may also contribute to iodine material images, thus confounding the quantification of perfusion defects.

PURPOSE

(i) To demonstrate the limitations of iodine material images in pulmonary perfusion defect quantification and (ii) to develop and validate a new quantitative biomarker using effective atomic numbers derived from DECT images.

METHODS

The quantitative relationship between the perfusion blood volume (PBV) in pulmonary parenchyma and the effective atomic number (Zeff ) spatial distribution was studied to show that the desired quantitative PBV maps are determined by the spatial maps of Zeff as PB V Z eff ( x ) = a Z eff β ( x ) + b , where a, b, and β are three constants. Namely, quantitative PB V Z eff is determined by Zeff images instead of the iodine basis images. Perfusion maps were generated for four human subjects to demonstrate the differences between conventional iodine material image-based PBV (PBViodine ) derived from two-material decompositions and the proposed PB V Z eff method.

RESULTS

Among patients with pulmonary emboli, the proposed PB V Z eff maps clearly show the perfusion defects while the PBViodine maps do not. Additionally, when there are no perfusion defects present in the derived PBV maps, no pulmonary emboli were diagnosed by an experienced thoracic radiologist.

CONCLUSION

Effective atomic number-based quantitative PBV maps provide the needed sensitive and specific biomarker to quantify pulmonary perfusion defects.

Can a ToF-PET photon attenuation reconstruction test stopping-power estimations in proton therapy? A phantom study

Objective. The aim of the phantom study was to validate and to improve the computed tomography (CT) images used for the dose computation in proton therapy. It was tested, if the joint reconstruction of activity and attenuation images of time-of-flight PET (ToF-PET) scans could improve the estimation of the proton stopping-power.Approach. The attenuation images, i.e. CT images with 511 keV gamma-rays (γCTs), were jointly reconstructed with activity maps from ToF-PET scans. Theβ⁺activity was produced with FDG and in a separate experiment with proton-induced radioactivation. The phantoms contained slabs of tissue substitutes. The use of theγCTs for the prediction of the beam stopping in proton therapy was based on a linear relationship between theγ-ray attenuation, the electron density, and the stopping-power of fast protons.Main results. The FDG based experiment showed sufficient linearity to detect a bias of bony tissue in the heuristic look-up table, which maps between x-ray CT images and proton stopping-power.γCTs can be used for dose computation, if the electron density of one type of tissue is provided as a scaling factor. A possible limitation is imposed by the spatial resolution, which is inferior by a factor of 2.5 compared to the one of the x-ray CT.γCTs can also be derived from off-line, ToF-PET scans subsequent to the application of a proton field with a hypofractionated dose level.Significance. γCTs are a viable tool to support the estimation of proton stopping with radiotracer-based ToF-PET data from diagnosis or staging. This could be of higher potential relevance in MRI-guided proton therapy.γCTs could form an alternative approach to make use of in-beam or off-line PET scans of proton-inducedβ⁺activity with possible clinical limitations due to the low number of coincidence counts.

Dual-energy computed tomography: Survey results on current uses and barriers to further implementation

OBJECTIVE

To gauge the current availability of dual-energy computed tomography (DECT) scanners in the UK, establish available technologies, look broadly at current clinical uses in adults and paediatrics, and identify barriers to implementation and potential ways to increase use.

METHODS

A survey was distributed amongst 10 radiology departments and shared on two national professional co-operation mail bases; the survey ran from 20th July to 9th December 2020. It explored current DECT utilisation in adults and paediatrics as well as barriers to use and suggestions to overcome those barriers.

RESULTS

The survey demonstrated DECT availability on 39 (40%) of the 98 CT scanners, but there was limited clinical use in adults and paediatrics. Eighteen (72%) of the 25 respondents had access to at least one DECT scanner, with 14 (56%) having adult DECT protocols in clinical use; <10% head examinations and <50% for other anatomical areas. Only two (8%) respondents had DECT paediatric protocols in clinical use; <10% examinations for all anatomical areas.The main barriers to implementation identified were lack of experience with DECT (8 (44%) users (adult) and 10 (56%) users (paediatric)) and no clinical protocols available (6 (33%) users (adult and paediatric)).Understanding DECT benefits and establishing suitable protocols were the most popular suggestions for increased implementation (10 (40%) of 25 respondents).

CONCLUSION

DECT scanners are available, but clinical use is limited for both adults and paediatrics. The main barriers identified were lack of experience with DECT and the availability of suitable protocols. Further work identified to help implementation included better education on the benefits of DECT, provision of clinical protocols and ensuring a multidisciplinary approach.

ADVANCES IN KNOWLEDGE

Barriers to implementation of clinical DECT protocols were identified, together with potential solutions to overcome these and enable further implementation.

Performance characterization of a prototype dual-layer cone-beam computed tomography system

PURPOSE

Conventional cone-beam computed tomography CT (CBCT) provides limited discrimination between low-contrast tissues. Furthermore, it is limited to full-spectrum energy integration. A dual-energy CBCT system could be used to separate photon energy spectra with the potential to increase the visibility of clinically relevant features and acquire additional information relevant in a multitude of clinical imaging applications. In this work, the performance of a novel dual-layer dual-energy CBCT (DL-DE-CBCT) C-arm system is characterized for the first time.

METHODS

A prototype dual-layer detector was fitted into a commercial interventional C-arm CBCT system to enable DL-DE-CBCT acquisitions. DL-DE reconstructions were derived from material-decomposed Compton scatter and photoelectric base functions. The modulation transfer function (MTF) of the prototype DL-DE-CBCT was compared to that of a commercial CBCT. Noise and uniformity characteristics were evaluated using a cylindrical water phantom. Effective atomic numbers and electron densities were estimated in clinically relevant tissue substitutes. Iodine quantification was performed (for 0.5-15 mg/ml concentrations) and virtual noncontrast (VNC) images were evaluated. Finally, contrast-to-noise ratios (CNR) and CT number accuracies were estimated.

RESULTS

The prototype and commercial CBCT showed similar spatial resolution, with a mean 10% MTF of 5.98 cycles/cm and 6.28 cycles/cm, respectively, using a commercial standard reconstruction. The lowest noise was seen in the 80 keV virtual monoenergetic images (VMI) (7.40 HU) and the most uniform images were seen at VMI 60 keV (4.74 HU) or VMI 80 keV (1.98 HU), depending on the uniformity measure used. For all the tissue substitutes measured, the mean accuracy in effective atomic number was 98.2% (SD 1.2%) and the mean accuracy in electron density was 100.3% (SD 0.9%). Iodine quantification images showed a mean difference of -0.1 (SD 0.5) mg/ml compared to the true iodine concentration for all blood and iodine-containing objects. For VNC images, all blood substitutes containing iodine averaged a CT number of 43.2 HU, whereas a blood-only substitute measured 44.8 HU. All water-containing iodine substitutes measured a mean CT number of 2.6 in the VNC images. A noise-suppressed dataset showed a CNR peak at VMI 40 keV and low at VMI 120 keV. In the same dataset without noise suppression applied, a peak in CNR was obtained at VMI 70 keV and a low at VMI 120 keV. The estimated CT numbers of various clinically relevant objects were generally very close to the calculated CT number.

CONCLUSIONS

The performance of a prototype dual-layer dual-energy C-arm CBCT system was characterized. Spatial resolution and noise were comparable with a commercially available C-arm CBCT system, while offering dual-energy capability. Iodine quantifications, effective atomic numbers, and electron densities were in good agreement with expected values, indicating that the system can be used to reliably evaluate the material composition of clinically relevant tissues. The VNC and monoenergetic images indicate a consistent ability to separate clinically relevant tissues. The results presented indicate that the system could find utility in diagnostic, interventional, and radiotherapy planning settings.

Optimization of image quality and accuracy of low iodine concentration quantification as function of dose level and reconstruction algorithm for abdominal imaging using dual-source CT: A phantom study

PURPOSE

The purpose of this study was to assess the impact of advanced modeled iterative reconstruction (ADMIRE) algorithm and dose levels on the accuracy of Hounsfield unit (HU) measurement, image noise and contrast-to-noise ratio (CNR) in virtual monochromatic images (VMIs) with low iodine concentrations, and the accuracy of iodine quantification.

MATERIALS AND METHODS

A CT phantom was scanned with dual-source CT using abdomen-pelvis examination parameters at four dose levels: 5, 8, 11 and 20 mGy. Images were reconstructed using filtered-back projection (FBP) and ADMIRE levels 3 and 5 (A3-A5). HU accuracy was assessed calculating the root-mean-square deviation (RMSD_HU). Image noise and CNR were computed on VMIs at 40/50/60/70 keV for 4 iodine inserts with 0.5, 1, 2 and 5 mg/mL concentrations. Accuracy of iodine quantification was assessed by the RMSD_iodine and iodine bias (IB).

RESULTS

The RMSD_HU decreased significantly as the dose levels increased compared to 5 mGy, except for 8 mGy with A3 (P = 0.380) and with A5 level (P = 0.945). Noise increased by 63.0 ± 3.0 (standard deviation [SD])% from 20 mGy to 5 mGy. Noise decreased significantly by -53.8 ± 0.9 (SD) % with A5 compared to FBP. The CNR decreased by -43.1 ± 6.5 (SD)% from 20 mGy to 5 mGy. It increased using ADMIRE, and as the ADMIRE levels increased. The RMSD_iodine and IB decreased as the dose level increased, and this was similar for all reconstruction types.

CONCLUSION

ADMIRE strongly improves image quality in VMIs and slightly improves HU accuracy but does not affect the accuracy of iodine quantification.

Principles and Applications of Dual Energy Computed Tomography in Neuroradiology

Dual-energy computed tomography (DE CT) is a promising tool with many current and evolving applications. Available DE CT scanners usually consist of one or two tubes, or use layered detectors for spectral separation. Most DE CT scanners can be used in single energy or dual-energy mode, except for the layered detector scanners that always acquire data in dual-energy mode. However, the layered detector scanners can retrospectively integrate the data from two layers to obtain conventional single energy images. DE CT mode enables generation of virtual monochromatic images, blended images, iodine quantification, improving conspicuity of iodinated contrast enhancement, and material decomposition maps or more sophisticated quantitative analysis not possible with conventional SE CT acquisition with an acceptable or even lower dose than the SE CT. This article reviews the basic principles of dual-energy CT and highlights many of its clinical applications in the evaluation of neurological conditions.

Design and implementation of a practical quality control program for dual-energy CT

A novel routine dual‐energy computed tomography (DECT) quality control (QC) program was developed to address the current deficiency of routine QC for this technology. The dual‐energy quality control (DEQC) program features (1) a practical phantom with clinically relevant materials and concentrations, (2) a clinically relevant acquisition, reconstruction, and postprocessing protocol, and (3) a fully automated analysis software to extract quantitative data for database storage and trend analysis. The phantom, designed for easy set up for standalone or adjacent imaging next to the ACR phantom, was made in collaboration with an industry partner and informed by clinical needs to have four iodine inserts (0.5, 1, 2, and 5 mg/ml) and one calcium insert (100 mg/ml) equally spaced in a cylindrical water‐equivalent background. The imaging protocol was based on a clinical DECT abdominal protocol capable of producing material specific concentration maps, virtual unenhanced images, and virtual monochromatic images. The QC automated analysis software uses open‐source technologies which integrates well with our current automated CT QC database. The QC program was tested on a GE 750 HD scanner and two Siemens SOMATOM FLASH scanners over a 3‐month period. The automated algorithm correctly identified the appropriate region of interest (ROI) locations and stores measured values in a database for monitoring and trend analysis. Slight variations in protocol settings were noted based on manufacturer. Overall, the project proved to provide a convenient and dependable clinical tool for routine oversight of DE CT imaging within the clinic.

Computed tomography recent history and future perspectives

Purpose: We provide a review of the key computed tomography (CT) technologies developed since the late 1980s and offer an overview of one of the future technologies under development. The focus of this review is mainly on the hardware and system development. The topics on the historical event linked to the early days of CT development and other innovations that contributed to the CT development, such as advanced image reconstruction techniques, are covered by companion papers in this special issue. Approach: The review is divided into five major sections, each linked to a key innovation in CT: helical spiral data acquisition, multi-slice CT, wide-cone CT, dual-source CT, and spectral CT. Given the limited scope of this review, only one of the future technologies, photon-counting CT, is discussed in detail. Whenever possible, both theory of operation and clinical examples are provided. Results: Theoretical analyses, phantom results, and clinical examples clearly demonstrate the efficacy and clinical relevancy of five historical technology developments and one future technology in CT. These technologies have improved and will continue to improve CT performance in terms of isotropic volume coverage, improved temporal resolution, and material differentiation and characterization capabilities. Conclusions: Over the past 30 years, technological developments of CT have contributed to the success of CT in many clinical applications such as trauma, oncology, cardiac imaging, and stroke. Advanced clinical applications have and will continue to demand more advanced technology development.

Synergistic multi-spectral CT reconstruction with directional total variation

This work considers synergistic multi-spectral CT reconstruction where information from all available energy channels is combined to improve the reconstruction of each individual channel. We propose to fuse these available data (represented by a single sinogram) to obtain a polyenergetic image which keeps structural information shared by the energy channels with increased signal-to-noise ratio. This new image is used as prior information during a channel-by-channel minimization process through the directional total variation. We analyse the use of directional total variation within variational regularization and iterative regularization. Our numerical results on simulated and experimental data show improvements in terms of image quality and in computational speed. This article is part of the theme issue 'Synergistic tomographic image reconstruction: part 2'.

A comparative study of effective atomic number calculations for dual-energy CT

PURPOSE

Several new formalisms of Effective Atomic Number ( Z eff ) have emerged recently, deviating from the widely accepted Mayneord's definition. This comparative study aims to reexamine their theories, reveal their connections, and apply them to material differentiation on dual-energy computed tomography (DECT).

METHODS

The first part of this paper is an in-depth review of several highly cited Z eff formalisms. This part includes (1) refuting the claim in Taylor's study that the classic Mayneord's formalism was inaccurate, (2) showing that Mayneord's, Rutherford's, and Bourque's formalisms were equivalent, and (3) explaining the fundamental difference between Taylor's and Bourque's formalisms. The second part of this paper explains how we translated the theories into software implementation and added an open-source Z eff calculation engine to our free research software 3D Quantitative Imaging (3DQI). The work includes developing an interpolation method based on radial basis function to make Taylor's formalism applicable to DECT, and devising a table lookup method to generate Z eff map with high efficiency for all appropriate formalisms.

RESULTS

Comparing Bourque's and Taylor's formalisms for six common materials over 40 ∼ 100 keV energy range, it was found that Bourque's Z eff values had a weak energy dependence by 0.18% ∼ 3.10%, but for Taylor's results this variation increased by a factor of 10. Further comparison showed that at 61 keV, different formalisms fall into two categories-Bourque, Mayneord, Van Abbema (a derivative of Rutherford) for the first category, and Taylor and Manohara for the second. Formalisms within each category produced similar Z eff values. For a material consisting of two elements, the two categories of formalisms tended to show a greater discrepancy if the constituent elements had larger difference in Z . The developed Z eff calculation engine was successfully applied to kidney stone classification and colon electronic cleansing.

CONCLUSIONS

We renewed the understanding of several popular Z eff formalisms: Contrary to the conclusion of Taylor's study, Mayneord's power-law formula is well grounded in theory; Bourque's formalism (based on the average electron microscopic cross-section) is considered numerically equivalent to Rutherford's, but with the advantage of being mathematically rigorous and physically meaningful; Taylor's formalism (based on the average atomic microscopic cross-section) is theoretically not suitable for DECT but a workaround still exists; Manohara's formalism should be used with caution due to a problem in its definition of electron cross-sections. The developed Z eff engine in the 3DQI software facilitated accurate and efficient Z eff estimate for various DECT applications.

Accuracy of proton stopping power estimation of silicone breast implants with single and dual-energy CT calibration techniques

A major contributing factor to proton range uncertainty is the conversion of computed tomography (CT) Hounsfield Units (HU) to proton relative stopping power (RSP). This uncertainty is elevated with implanted devices, such as silicone breast implants when computed with single energy CT (SECT). In recent years, manufacturers have introduced implants with variations in gel cohesivity. Deriving the RSP for these implants from dual-energy CT (DECT) can result in a marked reduction of the error associated with SECT. In this study, we investigate the validity of DECT calibration of HU to RSP on silicone breast implants of varying cohesivity levels. A DECT capable scanner was calibrated using the stoichiometric method of Bourque et al for SECT and DECT using a tissue substitute phantom. Three silicone breast implants of increasing gel cohesivity were measured in a proton beam of clinical energy to determine ground-truth RSP and water equivalent thickness (WET). These were compared to SECT-derived RSP at three CT spectrum energies and DECT with two energy pairs (80/140 kVp and 100/140 kVp) as obtained from scans with and without an anthropomorphic phantom. The RSP derived from parameters estimates from CT vendor-specific software (syngo.via) was compared. The WET estimates from SECT deviated from MLIC ground truth approximately +11%-19%, which would result in overpenetration if used clinically. Both the Bourque calibration and syngo.via WET estimates from DECT yielded error ≤0.5% from ground truth; no significant difference was found between models of varying gel cohesivity levels. WET estimates without the anthropomorphic phantom were significantly different than ground truth for the Bourque calibration. From these results, gel cohesivity had no effect on proton RSP. User-generated DECT calibration can yield comparably accurate RSP estimates for silicone breast implants to vendor software methods. However, care must be taken to account for beam hardening effects.