Quantitative analysis of the dual-energy CT virtual spectral curve for focal liver lesions characterization

Dual-energy CT for differentiation of hypodense liver lesions in pancreatic adenocarcinoma

OBJECTIVE

To assess the accuracy of CT spectral HU curve assessment of hypodense liver lesions.

METHODS

In this retrospective HIPAA-compliant study (January 2016 through May 2023), patients with biopsy-proven pancreatic adenocarcinoma and a biopsied indeterminate liver lesion underwent a DECT abdominal CT scan. Spectral HU curves were provided for each hypodense liver lesion, and slopes were calculated. Lesion Hounsfield units, iodine concentration and virtual enhancement were recorded. The Wilcoxon rank sum test was used to compare malignant and benign lesions. Optimal cutoff points were estimated using ROC curves and Youden's Index.

RESULTS

Thirty-six patients (19 men, 17 women) with a mean age of 63 years ± 9 (standard deviation), a mean height of 170.9 cm ± 9.5, a mean weight of 69.8 kg ± 14.5, and a body mass index of 23.9 kg/m2 ± 3.5. Reference standard assessment identified 92 liver lesions (50 metastases, 24 cysts, 13 abscesses, 3 regions of inflammation, 2 hemangiomas) with a mean size of 1.1 cm ± 0.5. The mean interval between the CT and liver lesion biopsy was 24 days. A diagnosis of benign versus malignant was determined based on optimal cutoffs: spectral curve slope of 1.36, iodine concentration of 6.47 (100 µg/cm3), and enhancement of 10.25. The receiver operating curves (ROC) for diagnosis using spectral curve slope, iodine concentration, and virtual enhancement resulted in an area under the curve (AUC) of 0.948, 0.946, and 0.937, respectively.

CONCLUSION

Spectral HU curves and iodine concentration of well-defined hypodense liver lesions are highly accurate in the diagnosis of benign versus malignant lesions.

KEY POINTS

Question Limited evidence exists for spectral imaging diagnosis of liver lesions-can DECT accurately differentiate between benign and metastatic hypodense liver lesions? Findings Ninety-two hypodense liver lesions evaluated using HU keV curve slope, iodine concentration, and virtual enhancement resulted in accurate benign versus metastatic differentiation. Clinical relevance Hypodense liver lesions are a challenging issue at staging, often requiring further imaging, follow-up, and/or biopsy. The additional information from multi-energy CT can be useful to differentiate between benign and malignant lesions, thereby reducing the need for costly additional evaluation.

Single-Energy, Dual-Energy, and Photon-Counting Computed Tomography of the Liver: Current Development and Clinical Utility for the Assessment of Focal Liver Lesions

ABSTRACT

Advancements in computed tomography (CT) technology, particularly the emergence of dual-energy CT (DE-CT) and photon-counting detector CT (PCD-CT), can improve detection, characterization, and treatment monitoring of focal liver lesions. DE-CT, through its ability to differentiate tissues with similar densities and produce diverse datasets, has enhanced lesion visibility and diagnostic precision. PCD-CT further advances imaging with superior spatial resolution and material decomposition capabilities, offering potential for complex diagnostic scenarios. This review aimed to highlight the role of CT in hepatic imaging and its application to focal liver lesions.DE-CT improves lesion detectability using low-energy virtual monochromatic images, which enhance iodine contrast and reduce radiation and contrast agent doses. It also facilitates treatment response evaluation after locoregional therapies for hepatocellular carcinoma by quantifying biomarkers, such as the extracellular volume fraction. This review underscores the transformative impact of DE-CT and PCD-CT on liver imaging, emphasizing their complementary roles alongside magnetic resonance imaging. These innovations have paved the way for more precise diagnostics, improved treatment planning, and enhanced patient outcomes in the management of liver diseases.

Image quality and dose reduction with photon counting detector CT: Comparison between ultra-high resolution mode and standard mode using a phantom study

PURPOSE

The purpose of this study was to assess the image quality and dose reduction potential of ultra-high resolution (UHR) mode compared with standard mode, both available on a commercial photon-counting detector computed tomography (PCCT) scanner.

MATERIALS AND METHODS

Images were acquired on a PCCT with a phantom using UHR and standard modes at three dose levels (3/6/12 mGy). Raw data were reconstructed using soft tissue (Br36) and bone (Br68) reconstruction kernels and 0.4-mm slice thickness. Noise power spectrum (NPS) and task-based transfer function (TTF) were calculated to assess noise magnitude, noise texture (fav), and spatial resolution (f50), respectively. Detectability indexes (d') were calculated to model the detection of two abdominal lesions for a Br36 soft tissue reconstruction kernel and three bone lesions for a Br68 bone reconstruction kernel.

RESULTS

At all dose levels, noise magnitude values were lower with UHR than with standard mode (mean difference, -18.0 ± 2.6 [standard deviation (SD)] % for Br36 and -33.9 ± 2.3 [SD] % for Br68). Noise texture was lower with UHR than with standard mode (mean difference, -4.2 ± 0.9 [SD] % for Br36 and -16.0 ± 1.8 [SD] % for Br68). For the solid water insert and Br36, f50 values were similar for both UHR (0.34 ± [SD] 0.04 mm-1) and standard (0.33 ± [SD] 0.04 mm-1) modes. For Br68, f50 values were greater with UHR than with standard for iodine (mean difference, 18.5 ± 1.9 [SD] %) and bone (11.7 ± 5.7 [SD] %) inserts. For all simulated lesions, d' values were greater with UHR than with standard and, compared to standard, the dose reduction potential with UHR was -32.9 ± 0.0 (SD) % for abdominal lesions and -68.7 ± 3.2 (SD) % for bone lesions.

CONCLUSION

Compared to the standard mode, the UHR mode offers lower noise levels and better detectability of abdominal and bone lesions, paving the way for potential dose reduction with PCCT in clinical applications.

Impact of deep learning reconstructions on image quality and liver lesion detectability in dual-energy CT: An anthropomorphic phantom study

BACKGROUND

Deep learning image reconstruction (DLIR) algorithms allow strong noise reduction while preserving noise texture, which may potentially improve hypervascular focal liver lesions.

PURPOSE

To assess the impact of DLIR on image quality (IQ) and detectability of simulated hypervascular hepatocellular carcinoma (HCC) in fast kV-switching dual-energy CT (DECT).

METHODS

An anthropomorphic phantom of a standard patient morphology (body mass index of 23 kg m-2) with customized liver, including mimickers of hypervascular lesions in both late arterial phase (AP) and portal venous phase (PVP) enhancement, was scanned on a DECT. Virtual monoenergetic images were reconstructed from raw data at four energy levels (40/50/60/70 keV) using filtered back-projection (FBP), adaptive statistical iterative reconstruction-V 50% and 100% (ASIRV-50 and ASIRV-100), DLIR low (DLIR-L), medium (DLIR-M), and high (DLIR-H). The contrast between the lesion and the liver parenchyma, the noise magnitude, the average and peak frequencies (favg and fpeak) of the noise power spectrum (NPS) reflecting noise texture, and the task-based measure of the modulation transfer function (MTFtask) were measured to evaluate spatial resolution. A detectability index (d') was computed to model the detection of hypervascular lesions in both AP and PVP. Metrics were compared between reconstructions and between energy levels using a Friedman test with follow-up post-hoc multiple comparison.

RESULTS

Lesion-to-liver contrast significantly increased with decreasing energy level in both AP and PVP (p ≤ 0.042) but was not affected by reconstruction algorithm (p ≥ 0.57). Overall, noise magnitude increased with decreasing energy levels and was the lowest with ASIRV-100 at all energy levels in both AP and PVP (p ≤ 0.01) and significantly lower with DLIR-M and DLIR-H reconstructions compared to ASIRV-50 and DLIR-L (p < 0.001). For all reconstructions, noise texture within the liver tended to get smoother with decreasing energy; favg significantly shifted towards lower frequencies from 70 to 40 keV (p ≤ 0.01). Noise texture was the smoothest with ASIRV-100 (p < 0.001) while DLIR-L had the noise texture closer to the one of FBP. The spatial resolution was not significantly affected by the energy level, but it was degraded when increasing the level of ASIRV and DLIR. For all reconstructions, the detectability indices increased with decreasing energy levels and peaked at 40 and 50 keV in AP and PVP, respectively. In both AP and PVP, the highest d' values were observed with ASIRV-100 and DLIR-H, whatever the energy level studied (p ≤ 0.01) without statistical significance between those two reconstructions.

CONCLUSIONS

Compared to the routinely used level of iterative reconstruction, DLIR reduces noise without consequential noise texture modification, and may improve the detectability of hypervascular liver lesions while enabling the use of lower energy virtual monoenergetic images. The optimal energy level and DLIR level may depend on the lesion enhancement.

Vascular Plugs Improve Pulmonary Arteriovenous Malformation Occlusion over Coil Embolization Alone: A Proof-of-Concept Study Using Dual-Energy CT

PURPOSE

To evaluate effectiveness of pulmonary arteriovenous malformation (PAVM) embolization using dual-energy computed tomography (CT) and spectral curve analysis by characterizing contrast enhancement and vascular perfusion as a surrogate of the degree of vascular occlusion after embolotherapy.

MATERIALS AND METHODS

Nine consecutive adult patients underwent embolization for 21 PAVMs (size range, 0.4-2.0 cm; 15/21 simple angioarchitecture) and subsequent postembolization chest dual-energy CT angiography. Twelve PAVMs were treated with vascular plugs with or without coils, whereas 9 PAVMs were treated with coils alone. Virtual spectral curves were generated using dual-energy image postprocessing in order to measure embolization effectiveness.

RESULTS

Complete occlusion of target PAVM was achieved in all cases on digital subtraction angiography (DSA) at the end of the embolization procedure. With a median follow-up of 12.7 months, the vascular plug group demonstrated significantly less vascular opacification compared with the coils-only group, as measured by opacification between upstream feeding artery and different downstream vasculature locations (Δslope1: median 79.1 vs 28.6; P = .003; Δslope2: 76.4 vs 28.6; P = .0197; Δslope3: 78.9 vs 28.6; P = .004). Persistence occurred in 3 PAVMs based on size criteria, which demonstrated higher vascular opacification by dual-energy CT (Δslope1: 72 vs 28.6; P = .253; Δslope2: 65.1 vs 32.7; P = .326; Δslope3: 72.9 vs 53.5; P = .733), although statistical significance was not reached.

CONCLUSIONS

Similar to emerging literature, dual-energy CT showed improved occlusion in PAVMs treated with vascular plugs compared with those treated with coils alone.

Comparison of low-energy virtual monoenergetic images between photon-counting CT and energy-integrating detectors CT: A phantom study

PURPOSE

The purpose of this study was to assess image quality and dose level using a photon-counting CT (PCCT) scanner by comparison with a dual-source CT (DSCT) scanner on virtual monoenergetic images (VMIs) at low energy levels.

MATERIALS AND METHODS

A phantom was scanned using a DSCT and a PCCT with a volume CT dose index of 11 mGy, and additionally at 6 mGy and 1.8 mGy for PCCT. Noise power spectrum and task-based transfer function were evaluated from 40 to 70 keV on VMIs to assess noise magnitude and noise texture (fav) and spatial resolution on two iodine inserts (f50), respectively. A detectability index (d') was computed to assess the detection of two contrast-enhanced lesions according to the energy level used.

RESULTS

For all energy levels, noise magnitude values were lower with PCCT than with DSCT at 11 and 6 mGy, but greater at 1.8 mGy. fav values were higher with PCCT than with DSCT at 11 mGy (8.6 ± 1.5 [standard deviation [SD]%), similar at 6 mGy (1.6 ± 1.5 [SD]%) and lower at 1.8 mGy (-17.8 ± 2.2 [SD]%). For both inserts, f50 values were higher with PCCT than DSCT at 11- and 6 mGy for all keV levels, except at 6 mGy and 40 keV. d' values were higher with PCCT than with DSCT at 11- and 6 mGy for all keV and both simulated lesions. Similar d' values to those of the DSCT at 11 mGy, were obtained at 2.25 mGy for iodine insert at 2 mg/mL and at 0.96 mGy for iodine insert at 4 mg/mL at 40 keV.

CONCLUSION

Compared to DSCT, PCCT reduces noise magnitude and improves noise texture, spatial resolution and detectability on VMIs for all low-keV levels.

Comparison of the spectral performance between two dual-source CT systems on low-energy virtual monoenergetic images: A phantom study

PURPOSE

To compare the spectral performance of two different DSCT (DSCT-Pulse and DSCT-Force) on virtual monoenergetic images (VMIs) at low energy levels.

METHODS

An image quality phantom was scanned on the two DSCTs at three dose levels: 11/6/1.8 mGy. Level 3 of an advanced modeled iterative reconstruction algorithm was used. Noise power spectrum and task-based transfer function were computed on VMIs from 40 to 70 keV to assess noise magnitude and noise texture (fav) and spatial resolution (f50). A detectability index (d') was computed to assess the detection of one contrast-enhanced abdominal lesion as a function of the keV level used.

RESULTS

For all dose levels and all energy levels, noise magnitude was significantly higher (p < 0.05) with DSCT-Pulse than with DSCT-Force (12.6 ± 2.7 % at 1.8 mGy, 9.1 ± 2.9 % at 6 mGy and 4.0 ± 2.7 % at 11 mGy). For all energy levels, fav values were significantly higher (p < 0.05) with DSCT-Pulse than with DSCT-Force at 1.8 mGy (4.8 ± 3.9 %) and at 6 mGy (5.5 ± 2.5 %) but similar at 11 mGy (0.2 ± 3.6 %; p = 0.518). For all energy levels, f50 values were significantly higher with DSCT-Pulse than with DSCT-Force (12.7 ± 5.6 % at 1.8 mGy, 17.9 ± 4.5 % at 6 mGy and 13.1 ± 2.6 % at 11 mGy). For all keV, similar d' values were found with both DSCT-Force and DSCT-Pulse at 11 mGy (-1.0 ± 3.1 %; p = 0.084). For other dose levels, d' values were significantly lower with DSCT-Pulse than with DSCT-Force (9.1 ± 3.2 % at 1.8 mGy and -6.3 ± 3.9 % at 6 mGy).

CONCLUSION

Compared with the DSCT-Force, the DSCT-Pulse improved noise texture and spatial resolution, but noise magnitude was slightly higher and detectability slightly lower, particularly when the dose level was reduced.

Feasibility of dose calculation for treatment plans using electron density maps from a novel dual-layer detector spectral CT simulator

BACKGROUND

Conventional single-energy CT can only provide a raw estimation of electron density (ED) for dose calculation by developing a calibration curve that simply maps the HU values to ED values through their correlations. Spectral CT, also known as dual-energy CT (DECT) or multi-energy CT, can generate a series of quantitative maps, such as ED maps. Using spectral CT for radiotherapy simulations can directly acquire ED information without developing specific calibration curves. The purpose of this study is to assess the feasibility of utilizing electron density (ED) maps generated by a novel dual-layer detector spectral CT simulator for dose calculation in radiotherapy treatment plans.

METHODS

30 patients from head&neck, chest, and pelvic treatment sites were selected retrospectively, and all of them underwent spectral CT simulation. Treatment plans based on conventional CT images were transplanted to ED maps with the same structure set, including planning target volume (PTV) and organs at risk (OARs), and the dose distributions were then recalculated. The differences in dose and volume histogram (DVH) parameters of the PTV and OARs between the two types of plans were analyzed and compared. Besides, gamma analysis between these plans was performed by using MEPHYSTO Navigator software.

RESULTS

In terms of PTV, the homogeneity index (HI), gradient index (GI), D2%, D98%, and Dmean showed no significant difference between conventional plans and ED plans. For OARs, statistically significant differences were observed in parotids D50%, brainstem in head&neck plans, spinal cord in chest plans and rectum D50% in pelvic plans, whereas the variance remained minor. For the rest, the DVH parameters exhibited no significant difference between conventional plans and ED plans. All of the mean gamma passing rates (GPRs) of gamma analysis were higher than 90%.

CONCLUSION

Compared to conventional treatment plans relying on CT images, plans utilizing ED maps demonstrated similar dosimetric quality. However, the latter approach enables direct utilization in dose calculation without the requirements of establishing and selecting a specific Hounsfield unit (HU) to ED calibration curve, providing an advantage in clinical applications.

Spectral performance evaluation of a second-generation spectral detector CT

PURPOSE

The aim of this study was to characterize a second-generation wide-detector dual-layer spectral computed tomography (CT) system for material quantification accuracy, acquisition parameter and patient size dependencies, and tissue characterization capabilities.

METHODS

A phantom with multiple tissue-mimicking and material-specific inserts was scanned with a dual-layer spectral detector CT using different tube voltages, collimation widths, radiation dose levels, and size configurations. Accuracy of iodine density maps and virtual monoenergetic images (MonoE) were investigated. Additionally, differences between conventional and MonoE 70 keV images were calculated to evaluate acquisition parameter and patient size dependencies. To demonstrate material quantification and differentiation, liver-mimicking inserts with adipose and iron were analyzed with a two-base decomposition utilizing MonoE 50 and 150 keV, and root mean square error (RMSE) for adipose and iron content was reported.

RESULTS

Measured inserts exhibited quantitative accuracy across a wide range of MonoE levels. MonoE 70 keV images demonstrated reduced dependence compared to conventional images for phantom size (1 vs. 27 HU) and acquisition parameters, particularly tube voltage (4 vs. 37 HU). Iodine density quantification was successful with errors ranging from -0.58 to 0.44 mg/mL. Similarly, inserts with different amounts of adipose and iron were differentiated, and the small deviation in values within inserts corresponded to a RMSE of 3.49 ± 1.76% and 1.67 ± 0.84 mg/mL for adipose and iron content, respectively.

CONCLUSION

The second-generation dual-layer CT enables acquisition of quantitatively accurate spectral data without compromises from differences in patient size and acquisition parameters.

Advancing Differentiation of Hepatic Metastases in Malignant Melanoma through Dual-Energy Computed Tomography Rho/Z Maps

OBJECTIVES

The aim of this study is to evaluate the diagnostic accuracy of dual-energy computed tomography (DECT)-based Rho/Z maps in differentiating between metastases and benign liver lesions in patients diagnosed with malignant melanoma compared to conventional CT value measurements.

METHODS

This retrospective study included 73 patients (mean age, 70 ± 13 years; 43 m/30 w) suffering from malignant melanoma who had undergone third-generation DECT as part of tumor staging between December 2017 and December 2021. For this study, we measured Rho (electron density) and Z (effective atomic number) values as well as Hounsfield units (HUs) in hypodense liver lesions. Values were compared, and diagnostic accuracy for differentiation was computed using receiver operating characteristic (ROC) curve analyses. Additional performed MRI or biopsies served as a standard of reference.

RESULTS

A total of 136 lesions (51 metastases, 71 cysts, and 14 hemangiomas) in contrast-enhanced DECT images were evaluated. The most notable discrepancy (p < 0.001) between measured values and the highest diagnostic accuracy for distinguishing melanoma metastases from benign cysts was observed for the Z (0.992; 95% CI, 0.956-1) parameters, followed by Rho (0.908; 95% CI, 0.842-0.953) and finally HU120kV (0.829; 95% CI, 0.751-0.891). Conversely, when discriminating between liver metastases and hemangiomas, the HU120kV parameters showed the most significant difference (p < 0.001) and yielded the highest values for diagnostic accuracy (0.859; 95% CI, 0.740-0.937), followed by the Z parameters (0.790; 95% CI, 0.681-0.876) and finally the Rho values (0.621; 95% CI, 0.501-0.730).

CONCLUSIONS

Rho and Z measurements derived from DECT allow for improved differentiation of liver metastases and benign liver cysts in patients with malignant melanoma compared to conventional CT value measurements. In contrast, in differentiation between liver hemangiomas and metastases, Rho/Z maps show inferior diagnostic accuracy. Therefore, differentiation between these two lesions remains a challenge for CT imaging.

Differentiation of Hamartomas and Malignant Lung Tumors in Single-Phased Dual-Energy Computed Tomography

This study investigated the efficacy of single-phase dual-energy CT (DECT) in differentiating pulmonary hamartomas from malignant lung lesions using virtual non-contrast (VNC), iodine, and fat quantification. Forty-six patients with 47 pulmonary lesions (mean age: 65.2 ± 12.1 years; hamartomas-to-malignant lesions = 22:25; male: 67%) underwent portal venous DECT using histology, PET-CT and follow-up CTs as a reference. Quantitative parameters such as VNC, fat fraction, iodine density and CT mixed values were statistically analyzed. Significant differences were found in fat fractions (hamartomas: 48.9%; malignancies: 22.9%; p ≤ 0.0001) and VNC HU values (hamartomas: -20.5 HU; malignancies: 17.8 HU; p ≤ 0.0001), with hamartomas having higher fat content and lower VNC HU values than malignancies. CT mixed values also differed significantly (p ≤ 0.0001), but iodine density showed no significant differences. ROC analysis favored the fat fraction (AUC = 96.4%; sensitivity: 100%) over the VNC, CT mixed value and iodine density for differentiation. The study concludes that the DECT-based fat fraction is superior to the single-energy CT in differentiating between incidental pulmonary hamartomas and malignant lesions, while post-contrast iodine density is ineffective for differentiation.

Accuracy of liver metastasis detection and characterization: Dual-energy CT versus single-energy CT with deep learning reconstruction

PURPOSE

To assess whether image quality differences between SECT (single-energy CT) and DECT (dual-energy CT 70 keV) with equivalent radiation doses result in altered detection and characterization accuracy of liver metastases when using deep learning image reconstruction (DLIR), and whether DECT spectral curve usage improves accuracy of indeterminate lesion characterization.

METHODS

In this prospective Health Insurance Portability and Accountability Act-compliant study (March through August 2022), adult men and non-pregnant adult women with biopsy-proven colorectal cancer and liver metastases underwent SECT (120 kVp) and a DECT (70 keV) portovenous abdominal CT scan using DLIR in the same breath-hold (Revolution CT ES; GE Healthcare). Participants were excluded if consent could not be obtained, if there were nonequivalent radiation doses between the two scans, or if the examination was cancelled/rescheduled. Three radiologists independently performed lesion detection and characterization during two separate sessions (SECT DLIRmedium and DECT DLIRhigh) as well as reported lesion confidence and overall image quality. Hounsfield units were measured. Spectral HU curves were provided for any lesions rated as indeterminate. McNemar's test was used to test the marginal homogeneity in terms of diagnostic sensitivity, accuracy and lesion detection. A generalized estimating equation method was used for categorical outcomes.

RESULTS

30 participants (mean age, 58 years ± 11, 21 men) were evaluated. Mean CTDIvol was 34 mGy for both scans. 141 lesions (124 metastases, 17 benign) with a mean size of 0.8 cm ± 0.3 cm were identified. High scores for image quality (scores of 4 or 5) were not significantly different between DECT (N = 71 out of 90 total scores from the three readers) and SECT (N = 62) (OR, 2.01; 95% CI:0.89, 4.57; P = 0.093). Equivalent image noise to SECT DLIRmed (HU SD 10 ± 2) was obtained with DECT DLIRhigh (HU SD 10 ± 3) (P = 1). There was no significant difference in lesion detection between DECT and SECT (140/141 lesions) (99.3%; 95% CI:96.1%, 100%).The mean lesion confidence scores by each reader were 4.2 ± 1.3, 3.9 ± 1.0, and 4.8 ± 0.8 for SECT and 4.1 ± 1.4, 4.0 ± 1.0, and 4.7 ± 0.8 for DECT (odds ratio [OR], 0.83; 95% CI: 0.62, 1.11; P = 0.21). Small lesion (≤5mm) characterization accuracy on SECT and DECT was 89.1% (95% CI:76.4%, 96.4%; 41/46) and 84.8% (71.1%, 93.7%; 39/46), respectively (P = 0.41). Use of spectral HU lesion curves resulted in 34 correct changes in characterizations and no mischaracterizations.

CONCLUSION

DECT required a higher strength of DLIR to obtain equivalent noise compared to SECT DLIR. At equivalent radiation doses and image noise, there was no significant difference in subjective image quality or observer lesion performance between DECT (70 keV) and SECT. However, DECT spectral HU curves of indeterminate lesions improved characterization.

Spectral performance of two split-filter dual-energy CT systems: A phantom study

BACKGROUND

Recently, a second generation of split filter dual-energy CT (SFCT) platform has been developed. The thicknesses of the gold and tin filters used to obtain both low- and high-energy spectra have been changed. These differences in filter thickness may affect the spectral separation between the two spectra and thus the quality of spectral images.

PURPOSE

To compare the spectral performance of two Split-Filter Dual-Energy CT systems (SFCT-1st and SFCT-2nd ) on virtual monoenergetic images (VMIs) and iodine map.

METHODS

A Multi-Energy CT phantom was scanned on two SFCT with a tube voltage of 120 kVp for both systems (SFCT-1st -120 and SFCT-2nd -120) and 140 kVp only for the second generation (SFCT-2nd -140). Acquisitions were performed on the phantom with a CTDIvol close to 11 mGy. Noise power spectrum (NPS) and task-based transfer function (TTF) were evaluated on VMIs from 40 to 70 keV. A detectability index (d') was computed to assess the detection of two contrast-enhanced lesions on VMIs. Hounsfield Unit (HU) accuracy was assessed on VMIs and the accuracy of iodine concentration was assessed on iodine maps.

RESULTS

For all keV, noise magnitude values were lower with the SFCT-2nd -120 than with the SFCT-1st -120 (on average: -22.5 ± 2.9%) and higher with the SFCT-2nd -140 than with the SFCT-2nd -120 (on average: 25.0 ± 6.2%). Average NPS spatial frequencies (fav ) were lower with the SFCT-1st -120 than with the SFCT-2nd -120 (-6.0 ± 0.5%) and the SFCT-2nd -140 (-3.6 ± 1.6%). Similar TTF50% values were found for both systems and both kVp for blood and iodine inserts at 2 mg/mL (0.29 ± 0.01 mm-1 ) and at 4 mg/mL (0.31 ± 0.01 mm-1 ). d' values peaked at 40 keV for the SFCT-2nd and at 70 keV for the SFCT-1st . Highest d' values were found for the SFCT-2nd -120 for both simulated lesions. Accuracy of HU values and iodine concentration was higher with the SFCT-2nd than with the SFCT 1st .

CONCLUSION

Compared to the SFCT-1st , with similar spatial resolution and noise texture values, the SFCT-2nd -120 exhibited the lowest values for noise magnitude, the highest detectability index values, and more accurate HU values and iodine concentrations.

Impact of Phantom Size on Low-Energy Virtual Monoenergetic Images of Three Dual-Energy CT Platforms

The purpose of this study was to compare the quality of low-energy virtual monoenergetic images (VMIs) obtained with three Dual-Energy CT (DECT) platforms according to the phantom diameter. Three sections of the Mercury Phantom 4.0 were scanned on two generations of split-filter CTs (SFCT-1st and SFCT-2nd) and on one Dual-source CT (DSCT). The noise power spectrum (NPS), task-based transfer function (TTF), and detectability index (d') were assessed on VMIs from 40 to 70 keV. The highest noise magnitude values were found with SFCT-1st and noise magnitude was higher with DSCT than with SFCT-2nd for 26 cm (10.2% ± 1.3%) and 31 cm (7.0% ± 2.5%), and the opposite for 36 cm (-4.2% ± 2.5%). The highest average NPS spatial frequencies and TTF values at 50% (f50) values were found with DSCT. For all energy levels, the f50 values were higher with SFCT-2nd than SFCT-1st for 26 cm (3.2% ± 0.4%) and the opposite for 31 cm (-6.9% ± 0.5%) and 36 cm (-5.6% ± 0.7%). The lowest d' values were found with SFCT-1st. For all energy levels, the d' values were lower with DSCT than with SFCT-2nd for 26 cm (-6.2% ± 0.7%), similar for 31 cm (-0.3% ± 1.9%) and higher for 36 cm (5.4% ± 2.7%). In conclusion, compared to SFCT-1st, SFCT-2nd exhibited a lower noise magnitude and higher detectability values. Compared with DSCT, SFCT-2nd had a lower noise magnitude and higher detectability for the 26 cm, but the opposite was true for the 36 cm.

Consistency of spectral results in cardiac dual-source photon-counting CT

We evaluate stability of spectral results at different heart rates, acquisition modes, and cardiac phases in first-generation clinical dual-source photon-counting CT (PCCT). A cardiac motion simulator with a coronary stenosis mimicking a 50% eccentric calcium plaque was scanned at five different heart rates (0, 60-100 bpm) with the three available cardiac scan modes (high pitch prospectively ECG-triggered spiral, prospectively ECG-triggered axial, retrospectively ECG-gated spiral). Subsequently, full width half max (FWHM) of the stenosis, Dice score (DSC) for the stenosed region, and eccentricity of the non-stenosed region were calculated for virtual monoenergetic images (VMI) at 50, 70, and 150 keV and iodine density maps at both diastole and systole. FWHM averaged differences of - 0.20, - 0.28, and - 0.15 mm relative to static FWHM at VMI 150 keV across acquisition parameters for high pitch prospectively ECG-triggered spiral, prospectively ECG-triggered axial, and retrospectively ECG-gated spiral scans, respectively. Additionally, there was no effect of heart rate and acquisition mode on FWHM at diastole (p-values < 0.001). DSC demonstrated similarity among parameters with standard deviations of 0.08, 0.09, 0.11, and 0.08 for VMI 50, 70, and 150 keV, and iodine density maps, respectively, with insignificant differences at diastole (p-values < 0.01). Similarly, eccentricity illustrated small differences across heart rate and acquisition mode for each spectral result. Consistency of spectral results at different heart rates and acquisition modes for different cardiac phase demonstrates the added benefit of spectral results from PCCT to dual-source CT to further increase confidence in quantification and advance cardiovascular diagnostics.

Spectral CT: Current Liver Applications

Using two different energy levels, dual-energy computed tomography (DECT) allows for material differentiation, improves image quality and iodine conspicuity, and allows researchers the opportunity to determine iodine contrast and radiation dose reduction. Several commercialized platforms with different acquisition techniques are constantly being improved. Furthermore, DECT clinical applications and advantages are continually being reported in a wide range of diseases. We aimed to review the current applications of and challenges in using DECT in the treatment of liver diseases. The greater contrast provided by low-energy reconstructed images and the capability of iodine quantification have been mostly valuable for lesion detection and characterization, accurate staging, treatment response assessment, and thrombi characterization. Material decomposition techniques allow for the non-invasive quantification of fat/iron deposition and fibrosis. Reduced image quality with larger body sizes, cross-vendor and scanner variability, and long reconstruction time are among the limitations of DECT. Promising techniques for improving image quality with lower radiation dose include the deep learning imaging reconstruction method and novel spectral photon-counting computed tomography.

Virtual monochromatic spectral attenuation curve analysis for evaluation of incidentally detected small renal lesions using rapid kilovoltage-switching dual-energy computed tomography

PURPOSE

To determine whether the spectral attenuation curve on a rapid kilovoltage-switching dual-energy computed tomography (DECT) scan can distinguish enhancing from nonenhancing incidental small (1-4 cm) renal lesions compared with conventional single-energy attenuation changes.

METHODS

This retrospective study enrolled 46 patients with 78 renal lesions (24 enhancing; 54 nonenhancing) who underwent DECT with DE mode performed during the portovenous or nephrographic phase. Final diagnosis of enhancing and nonenhancing masses was confirmed by pathology or imaging following the established criteria. Virtual monochromatic images (VMI) were reconstructed, and the slopes between the VMI dataset at 40-70 keV (Slope HU_40-70), 40-100 keV (Slope HU_40-100), and 40-140 keV (Slope HU_40-140) were measured. Visual assessment of the curve pattern was recorded. Diagnostic accuracies were calculated with a cross-validated Mann-Whitney U test, and correlations of quantitative spectral parameters and intraclass correlation coefficient (ICC) were calculated using Spearman's rho correlation.

RESULTS

All quantitative and qualitative spectral analysis parameters significantly differentiated the enhancing and nonenhancing lesions (P < 0.001). The optimal slope thresholds calculated by cross-validation for Slope HU_40-70, Slope HU_40-100, and Slope HU_40-140 were 3.0, 1.8 and 1.2, respectively for reader 1 and 3.0, 1.9 and 1.15, respectively for reader 2. Using a slope threshold at all datasets yielded a high diagnostic accuracy of 96 for reader 1 and 95 for reader 2. Using a ∆HU threshold of 20 HU yielded an accuracy of 100. Visual analysis of the curve pattern also yielded high accuracy of 94.

CONCLUSIONS

The spectral attenuation curve on rapid kilovoltage-switching DECT gives excellent diagnostic accuracy differentiating between incidental enhancing and nonenhancing renal lesions. This benefit of DECT will be most helpful when the true unenhanced phase is not performed.

Accuracy of virtual non-contrast images with different algorithms in dual-energy computed tomography

We investigated the accuracy of the computed tomography (CT) numbers of virtual non-contrast (VNC) images for two different material decomposition algorithms using the same image data for different diluted contrast agent concentrations. A container filled with contrast agents was inserted into a cylindrical phantom and scanned with dual-energy protocols (80/Sn140 kV, 100/Sn140 kV) using a dual-source CT. VNC images were generated by the 2-material decomposition (MD) algorithm using the energy of each tube voltage and the linear attenuation coefficient, calculated from the theoretical spectral curve of the agent and the CT number of the image, respectively. Furthermore, VNC images using 3-material decomposition (3-MD) algorithm were produced by applying LiverVNC, an analysis parameter implemented in the scanner. The robustness of both the algorithms was verified by investigating the CT numbers of the agents in the VNC. The closer the CT number is to 0 HU, the more robust the algorithm. Without beam-hardening correction, the CT numbers increased with an increase in concentration in both the algorithms, maximal at 50 mg/ml concentration, with CT numbers of 38 HU for 2-MD, 86 HU for 3-MD. With correction, CT numbers were ± 10 HU or less for both the algorithms up to 30 mg/ml concentration, whereas, for concentrations above 40 mg/ml, the maximal averaged CT number was 12 HU for 2-MD, 22 HU for 3-MD. For both the algorithms, the accuracy of the CT numbers was maintained in the low-concentration range; parameter adjustment was necessary to maintain the accuracy at concentrations higher than clinically expected.

Economics of Dual-Energy CT: Workflow, Costs, and Benefits

Dual-energy CT is an emerging technology which is progressively becoming more available for routine clinical applications. As practices and institutions evaluate the business case for purchase of these high-end scanners, the clinical utility and downstream costs must be determined. This article will provide an overview of the technology and will review direct and indirect costs associated with the implementation of dual-energy CT programs.

Lu3+-based nanoprobe for virtual non-contrast CT imaging of hepatocellular carcinoma

Transcatheter arterial chemoembolization (TACE), the mainstream treatment for hepatocellular carcinoma (HCC), is a method of blocking tumor blood vessels with a mixture of lipiodol and chemotherapeutics. And the contrast-enhanced computed tomography (CT) is the commonly used way for follow-up of HCC after TACE. However, it is noteworthy that when lipiodol deposition plays an embolic effect, it also produces high-density artifacts in CT images. These artifacts usually conceal the enhancement effect of iodine contrast agents. As a result, the residual region is difficult to be visualized. To overcome this obstacle, we developed one kind of Lu³⁺/Gd³⁺ doped fluoride nanoprobe modified with Dp-PEG2000 to realize CT/MRI dual-modality imaging of HCC. Compared with lipiodol or ioversol, the obtained PEGylated product LG-PEG demonstrated a greater density value in high keV CT images. In vitro experiments showed the lipiodol artifacts can be removed in virtual non-contrast (VNC) imaging, but the density of ioversol was also removed at the same time. However, the LG-PEG synthesized in this work can still maintain a high density in VNC imaging, which indicates that LG-PEG can exploit its advantages to the full in VNC imaging. Furthermore, LG-PEG successfully exerted tumor enhancement effects in the in vivo VNC images of HCC with lipiodol deposition. In addition, LG-PEG exhibited a strong T₂ enhancement effect with low biological toxicity and less side-effect on the main organ and blood. Thus, the LG-PEG reported in this research can serve as an effective and safe VNC contrast agent for HCC imaging after TACE.

The clinical value of dual-energy computed tomography and diffusion-weighted imaging in the context of liver cancer: A narrative review

The dual-energy computed tomography (DECT) and diffusion-weighted magnetic resonance imaging (DWI-MRI) are used to diagnose liver cancer. The clinical value of these two examination methods needs to be further summarized. We collected and summarized relevant literature published from 2011 to 2021. The diagnostic performance of DECT was assessed between conventional computed tomography and DWI-MRI. DWI-MRI had a 69% sensitivity for detecting small hepatocellular carcinoma (HCC) lesions and a 60% diagnostic specificity for differentiating between types of HCC lesions. DECT had a sensitivity to small liver lesions (<1 cm) of 69%, and the diagnostic specificity for HCC and metastasis was about 60%. DWI was more sensitive (90.3% vs. 74.9%) and accurate (91.9% vs. 76.9%) in diagnosing HCC compared with conventional MRI sequencing. With the aid of contrast media, DWI-MRI had 90.0% specificity for detecting small HCCs (smaller than 1 cm). Furthermore, DWI-MRI not only provided physicians with valuable diagnostic information but also delivered histological grading information, with 78% accuracy for all benign lesions and 71% for solid lesions. DECT had relatively high sensitivity and required a lower contrast medium dose. With standardized quantitative parameters, it can be an extremely useful tool for HCC surveillance. DWI-MRI is the preferred imaging process as it produces high-contrast images for supporting an early diagnosis (high sensitivity and specificity) and provides histological information using non-ionizing radiation.

A Computed Tomography Nomogram for Assessing the Malignancy Risk of Focal Liver Lesions in Patients With Cirrhosis: A Preliminary Study

Purpose

The detection and characterization of focal liver lesions (FLLs) in patients with cirrhosis is challenging. Accurate information about FLLs is key to their management, which can range from conservative methods to surgical excision. We sought to develop a nomogram that incorporates clinical risk factors, blood indicators, and enhanced computed tomography (CT) imaging findings to predict the nature of FLLs in cirrhotic livers.

Method

A total of 348 surgically confirmed FLLs were included. CT findings and clinical data were assessed. All factors with P < 0.05 in univariate analysis were included in multivariate analysis. ROC analysis was performed, and a nomogram was constructed based on the multivariate logistic regression analysis results.

Results

The FLLs were either benign (n = 79) or malignant (n = 269). Logistic regression evaluated independent factors that positively affected malignancy. AFP (OR = 10.547), arterial phase hyperenhancement (APHE) (OR = 740.876), washout (OR = 0.028), satellite lesions (OR = 15.164), ascites (OR = 156.241), and nodule-in-nodule architecture (OR =27.401) were independent predictors of malignancy. The combined predictors had excellent performance in differentiating benign and malignant lesions, with an AUC of 0.959, a sensitivity of 95.24%, and a specificity of 87.5% in the training cohort and AUC of 0.981, sensitivity of 94.74%, and specificity of 93.33% in the test cohort. The C-index was 96.80%, and calibration curves showed good agreement between the nomogram predictions and the actual data.

Conclusions

The nomogram showed excellent discrimination and calibration for malignancy risk prediction, and it may aid in making FLLs treatment decisions.

Dual-Energy Computed Tomography in Diffuse Liver Diseases

Dual-energy computed tomography (DECT) is an advancement in the field of CT, where images are acquired at two energies. Materials are identified and quantified based on their attenuation pattern at two different energy beams using various material decomposition algorithms. With its ability to identify and quantify materials such as fat, calcium, iron, and iodine, DECT adds great value to conventional CT and has innumerable applications in body imaging. Continuous technological advances in CT scanner hardware, material decomposition algorithms, and image reconstruction software have led to considerable growth of these applications. Among all organs, the liver is the most widely investigated by DECT, and DECT has shown promising results in most liver applications. In this article, we aim to provide an overview of the role of DECT in the assessment of diffuse liver diseases, mainly the deposition of fat, fibrosis, and iron and review the most relevant literature.

Comparison of virtual monoenergetic imaging between a rapid kilovoltage switching dual-energy computed tomography with deep-learning and four dual-energy CTs with iterative reconstruction

Background

To assess the spectral performance of rapid kV switching dual-energy CT (KVSCT-Canon) equipped with a Deep-Learning spectral reconstruction algorithm on virtual-monoenergetic images at low-energy levels and to compare its performances with four other dual-energy CT (DECT) platforms equipped with iterative reconstruction algorithms.

Methods

Two CT phantoms were scanned on five DECT platforms: KVSCT-Canon, fast kV-switching CT (KVSCT-GE), split filter CT, dual-source CT (DSCT), and dual-layer CT (DLCT). The classical parameters of abdomen-pelvic examinations were used for all phantom acquisitions, and a CTDI_vol close to 10 mGy. For KVSCT-Canon, virtual-monoenergetic images were reconstructed with a clinical slice thickness of 0.5 and 1.5 mm to be close to other platforms. Noise power spectrum (NPS) and task-based transfer function (TTF) were evaluated from 40 to 80 keV of virtual-monoenergetic images. A detectability index (d') was computed to model the detection task of two contrast-enhanced lesions as function of keV.

Results

For KVSCT-Canon, the noise magnitude and average NPS spatial frequency (f_av) decreased from 40 to 70 keV and increased thereafter. Similar noise magnitude outcomes were found for KVSCT-GE but the opposite for f_av. For the other DECT platforms, the noise magnitude decreased as the keV increased. For split filter CT, DSCT and DLCT, the f_av values increased from 40 to 80 keV. For all DECT platforms, TTF at 50% (f₅₀) decreased as the keV increased, decreasing spatial resolution. For KVSCT-Canon, d' values peaked at 60 and 70 keV for both simulated lesions and from 50 to 70 keV for KVSCT-GE. d' decreased between 40 and 70 keV for DSCT, DLCT and split filter CT. For KVSCT-Canon, the increase in slice thickness decreases noise magnitude, f_av and f₅₀ and increases d' values. The highest d' values were found for DLCT at 40 and 50 keV and for KVSCT-Canon at 1.5 mm for other keV.

Conclusions

For KVSCT-Canon, the detectability of contrast-enhanced lesions was highest at 60 keV. The highest d' values were found for DLCT at 40 and 50 keV and for KVSCT-Canon at 1.5 mm for other keV.

Utility of Dual-Energy CT in Abdominal Interventions

Dual-energy computed tomography (DECT) is an emerging CT technique based on data acquisition at two different settings. Various postprocessing techniques generate different sets of images, each with unique advantages. With DECT, it is possible to obtain virtual unenhanced images from monochromatic reconstructions and attenuation maps of different elements, thereby improving the detection and characterization of a variety of lesions. Presently, DECT is widely used to evaluate pulmonary embolism, characterize abdominal masses, determine the composition of urinary calculi, and detect tophi in gout. CT angiography is an essential prerequisite for endovascular intervention. DECT allows a better quality of angiographic images with a lesser dose of contrast. Various postprocessing techniques in DECT also help in a better evaluation of response to locoregional therapy. Virtual noncontrast images and iodine map differentiate residual or recurrent tumors from intrinsically hyperdense materials. Superior metallic artifact reduction allows better evaluation of vascular injuries adjacent to bony fractured fragments or previously deployed embolization coils. In addition to metal artifacts reduction, virtual monochromatic spectral imaging could further mitigate metal artifacts during CT-guided biopsy, providing an improved depiction of lesions and safe and versatile access for long puncture pathways. This article reviews and illustrates the different applications of DECT in various abdominal interventions. Familiarity with the capabilities of DECT may help interventional radiologists to improve their practice and ameliorate patient care.

Evaluating image quality and optimal parameters for non-linear blending dual-energy computed tomography images of hepatic portal veins by blending-property-map

BACKGROUND

Blending technology is usually used to improve quality of dual-energy computed (DECT) images.

OBJECTIVES

To evaluate the blended DECT image qualities by employing the Blending-Property-Map (BP-Map) and elucidating the optimal parameters with the highest signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR).

METHODS

Sixty pairs of 80 kV and 140 kV CT images are blended non-linearly by four methods. Protocol A uses the fixed values of blending width (BW) and blending center (BC); Protocol B uses the values of BW =  (CThepatic portal vein - CThepatic parenchymal) / 2 and BC =  (CThepatic portal vein + CThepatic parenchymal) / 2; Protocol C uses a BW ranging from 10 to 100 HU at an interval of 10 HU and BC = (CThepatic portal vein + CThepatic parenchymal) / 2; Protocol D uses the BP-Map that covers all possible values of BW and BC.

RESULTS

When using CT value of adipose tissue as noise, the calculated SNR and CNR of optimal blending width and blending center were 123.22±41.73 and 9.00±3.52, respectively, by the BP-Map in the protocol D. By employing the CT value of back muscle as noise, the SNR and CNR of the best-blended images were 75.90±14.52 and 6.39±2.37, respectively. The subjective score of protocol D was 4.88±0.12.

CONCLUSIONS

Compared to traditional blending methods, the BP-Map technique can determine the optimal blending parameter and provide the best-blended images with the highest SNR and CNR.

Spectral CT Hybrid Images in the Diagnostic Evaluation of Hypervascular Abdominal Tumors-Potential Advantages in Clinical Routine

Background: This study aimed to investigate the use of spectral computed tomography (SCT) hybrid images combining virtual monoenergetic images (VMIs) and iodine maps (IMs) as a potentially efficient search series for routine clinical imaging in patients with hypervascular abdominal tumors. Methods: A total of 69 patients with hypervascular abdominal tumors including neuroendocrine neoplasms (NENs, n = 48), renal cell carcinoma (RCC, n = 10), and primary hepatocellular carcinoma (HCC, n = 11) were analyzed retrospectively. Two radiological readers (blinded to clinical data) read three CT image sets (1st a reference set with 70 keV; 2nd a 50:50 hybrid 140 keV/40 keV set; 3rd a 50:50 hybrid 140 keV/IM set). They assessed images subjectively by rating several parameters including image contrast, visibility of suspicious lesions, and diagnostic confidence on five-point Likert scales. In addition, reading time was estimated. Results: Median subjective Likert scores were highest for the 1st set, except for image contrast, for which the 2nd set was rated highest. Scores for diagnostic confidence, artifacts, noise, and visibility of suspicious lesions or small structures were significantly higher for the 1st set than for the 2nd or 3rd set (p < 0.001). Regarding image contrast, the 2nd set was rated significantly higher than the 3rd set (p < 0.001), while the median did not differ significantly compared with the 1st set. Agreement between the two readers was high for all sets. Estimated potential reading time was the same for hybrid and reference sets. Conclusions: Hybrid images have the potential to efficiently exploit the additional information provided by SCT in patients with hypervascular abdominal tumors. However, the use of rigid weighting did not significantly improve diagnostic performance in this study.

Impact of four kVp combinations available in a dual-source CT on the spectral performance of abdominal imaging: A task-based image quality assessment on phantom data

Purpose

To compare the spectral performance of four combinations of kVp available in a third generation dual‐source CT (DSCT) on abdominal imaging.

Methods

An image‐quality phantom was scanned with a DSCT using four kVp pairs (tube “A” voltage/tube “B” voltage): 100/Sn150 kVp, 90/Sn150 kVp, 80/Sn150 kVp, and 70/Sn150 kVp, classic parameters and dose level for abdomen examination (CTDI_vol: 11 mGy). The noise power spectrum (NPS) and the task‐based transfer function (TTF) of two inserts were computed on virtual monochromatic images (VMIs) at 40/50/60/70 keV and for mixed, low‐, and high‐kVp images. Detectability index (d’) was computed on VMIs and mixed images to model the detection task of liver metastasis (LM) and hepatocellular carcinoma (HCC). Iodine quantification accuracy was assessed using the Root Mean Square Deviation (RMSD_iodine) and the iodine bias (IB).

Results

Noise magnitude decreased by −55%± 0% between 40 and 70 keV for all kVp pairs. Compared to 70/Sn150 kVp, noise magnitude was increased by 9% ± 0% with 80/Sn150 kVp, by 16% ± 1% with 90/Sn150 kVp and by 24%± 1% with 100/Sn150 kVp. The average NPS spatial frequency (f_av) shifted toward higher frequencies as energy level increased for all kVp pairs. Lowest f_av values were found for 70/Sn150 kVp and highest for 100/Sn150 kVp. The value of TTF at 50% (f₅₀) shifted toward lower frequencies with increasing energy level. The highest f₅₀ values occurred for 100/Sn150 kVp and the lowest for 80/Sn150 kVp. For both lesions, d’ was highest for 70/Sn150 kVp and lowest for 100/Sn150 kVp. Compared to 70/Sn150 kVp, d’ decreased by −6% ± 3% with 80/Sn150 kVp, by −11% ± 2% with 90/Sn150 kVp and by −13%± 2% with 100/Sn150 kVp. For all acquisitions, the RSMD_iodine and IB were the lowest for 100/Sn150 kVp (0.29 ± 0.10 mg/ml and 0.88 ± 0.30 mg/ml, respectively) and increased when the tube “A” voltage decreased (2.34 ± 0.29 mg/ml for 70/Sn150 kVp and 7.42 ± 0.51 mg/ml respectively).

Conclusion

70/Sn150 kVp presented the lowest image noise and highest detectability in VMIs of two small focal liver lesions. 100/Sn150 kVp presented the lowest image noise on mixed images and highest accuracy of iodine quantification in iodine images.

Spectral detector CT applications in advanced liver imaging

OBJECTIVE

Spectral detector CT (SDCT) has many applications in advanced liver imaging. If appropriately utilized, this technology has the potential to improve image quality, provide new diagnostic information, and allow for decreased radiation dose. The purpose of this review is to familiarize radiologists with the uses of SDCT in liver imaging.

CONCLUSION

SDCT has a variety of post-processing techniques, which can be used in advanced liver imaging and can significantly add value in clinical practice.

Image-domain Material Decomposition for Spectral CT using a Generalized Dictionary Learning

The spectral computed tomography (CT) has huge advantages by providing accurate material information. Unfortunately, due to the instability or overdetermination of material decomposition model, the accuracy of material decomposition can be compromised in practice. Very recently, the dictionary learning based image-domain material decomposition (DLIMD) can obtain high accuracy for material decompositions from reconstructed spectral CT images. This method can explore the correlation of material components to some extent by training a unified dictionary from all material images. In addition, the dictionary learning based prior as a penalty is applied on material components independently, and many parameters would be carefully elaborated in practice. Because the concentration of contrast agent in clinical applications is low, it can result in data inconsistency for dictionary based representation during the iteration process. To avoid the aforementioned limitations and further improve the accuracy of materials, we first construct a generalized dictionary learning based image-domain material decomposition (GDLIMD) model. Then, the material tensor image is unfolded along the mode-1 to enhance the correlation of different materials. Finally, to avoid the data inconsistency of low iodine contrast, a normalization strategy is employed. Both physical phantom and tissue-synthetic phantom experiments demonstrate the proposed GDLIMD method outperforms the DLIMD and direct inversion (DI) methods.

Differentiation of Hepatocellular Carcinoma from Hepatic Hemangioma and Focal Nodular Hyperplasia using Computed Tomographic Spectral Imaging

BACKGROUND AND AIMS

Hepatocellular carcinoma (HCC) is the most common primary hepatic malignancy. This study was designed to investigate the value of computed tomography (CT) spectral imaging in differentiating HCC from hepatic hemangioma (HH) and focal nodular hyperplasia (FNH).

METHODS

This was a retrospective study of 51 patients who underwent spectral multiple-phase CT at 40-140 keV during the arterial phase (AP) and portal venous phase (PP). Slopes of the spectral curves, iodine density, water density derived from iodine- and water-based material decomposition images, iodine uptake ratio (IUR), normalized iodine concentration, and the ratio of iodine concentration in liver lesions between AP and PP were measured or calculated.

RESULTS

As energy level decreased, the CT values of HCC (n=31), HH (n=17), and FNH (n=7) increased in both AP and PP. There were significant differences in IUR in the AP, IUR in the PP, normalized iodine concentration in the AP, slope in the AP, and slope in the PP among HCC, HH, and FNH. The CT values in AP, IUR in the AP and PP, normalized iodine concentration in the AP, slope in the AP and PP had high sensitivity and specificity in differentiating HH and HCC from FNH. Quantitative CT spectral data had higher sensitivity and specificity than conventional qualitative CT image analysis during the combined phases.

CONCLUSIONS

Mean CT values at low energy (40-90 keV) and quantitative analysis of CT spectral data (IUR in the AP) could be helpful in the differentiation of HCC, HH, and FNH.

Quantitative benchmarking of iodine imaging for two CT spectral imaging technologies: a phantom study

BACKGROUND

The aim of this study was to quantitatively benchmark iodine imaging across specific virtual monoenergetic energy levels, iodine maps and virtual non-contrast images with different phantom sizes and iodine concentrations, using a rapid switching dual-energy CT (DECT) and a dual source DECT, in order to investigate accuracy and potential differences between the technologies.

METHODS

Solutions of iodine contrast (10, 20, 30, 50, and 100 mg/mL), sterile water and saline were scanned in a phantom on a rapid switching single-source and dual-source DECT scanners from two different vendors. The phantom was equipped with polyurethane rings simulating three body sizes. The datasets were reconstructed in virtual monoenergetic energy levels (70, 80, 90, 100, 110, 120, 130, and 140 keV), virtual non-contrast images and iodine maps. HU and iodine concentrations were measured by placing ROIs in the iodine solutions.

RESULTS

The iodine concentrations were reproduced with a high degree of accuracy for the single-source DECT (1.8-9.0%), showing a slight dependence on phantom size. The dual source DECT technique showed deviant values (error -33.8 to 12.0%) for high concentrations. In relation to the virtual non-contrast measurements, the images from both vendors were affected by the iodine concentration and phantom size (-127.8 to 539.1 HU). Phantom size did not affect the calculated monoenergetic attenuation values, but the attenuation values varied between the scanners.

CONCLUSIONS

Quantitative measurements of post-processed images are dependent on the concentration of iodine, the phantom size and different technologies. However, our study indicates that the iodine maps are reliable for quantification of iodine.

Added value of spectral parameters for the assessment of lymph node metastasis of lung cancer with dual-layer spectral detector computed tomography

BACKGROUND

Lymph node (LN) metastasis is an important factor affecting the treatment of lung cancer. The purpose of this article was to investigate the benefits of dual-layer spectral detector computed tomography (SDCT) for the evaluation of metastatic LNs in lung cancer.

METHODS

Data from 93 patients with lung cancer who underwent dual-phase enhanced scanning with SDCT were retrospectively analyzed. According to the pathological findings, 166 LNs were grouped as metastatic (n=80) or non-metastatic (n=86). LNs in station 4 (n=80) and station 7 (n=35) accounted for the majority of the LNs (approximately 69.23%). The short-axis diameter of the LN, arterial enhancement fraction (AEF), normalized iodine concentration (NIC), and the slope of the spectral Hounsfield unit curve (λHU) during the arterial phase (AP) and venous phase (VP) were measured. The Mann-Whitney U test was used to statistically compare these quantitative parameters. Receiver operating characteristic (ROC) curves were plotted to identify the cutoff values, and decision curve analysis (DCA) was performed to determine the net benefit of each parameter. The diagnostic performance, obtained by combining the short-axis diameter with each of the above parameters, was also studied.

RESULTS

The short-axis LN diameter, AEF, NIC, and λHU during the AP and VP all showed significant differences between the metastatic and non-metastatic groups (P<0.05). Of the parameters, the AEF had the greatest diagnostic efficiency for metastatic LNs [area under the ROC curve (AUC)AEF =0.885] with a threshold of 86.40%. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and 95% confidence interval were 90.00%, 89.53%, 88.89%, 90.59%, and 0.830-0.944, respectively. When the quantitative parameters were combined with the short-axis diameter, the AUCs of the parameters, except the AEF, were significantly improved (P<0.05).

CONCLUSIONS

The iodine quantitative parameters from SDCT, such as the AEF, demonstrated high diagnostic performances in the differentiation of metastatic and non-metastatic LNs.

Spectral CT quantification stability and accuracy for pediatric patients: A phantom study

BACKGROUND

Spectral computed tomography (spectral CT) provides access to clinically relevant measures of endogenous and exogenous materials in patients. For pediatric patients, current spectral CT applications include lesion characterization, quantitative vascular imaging, assessments of tumor response to treatment, and more.

OBJECTIVE

The aim of this study is a comprehensive investigation of the accuracy and stability of spectral quantifications from a spectral detector-based CT system with respect to different patient sizes and radiation dose levels relevant for the pediatric population.

MATERIALS AND METHODS

A spectral CT phantom with tissue-mimicking materials and iodine concentrations relevant for pediatric imaging was scanned on a spectral detector CT system using a standard pediatric abdominal protocol at 100%, 67%, 33% and 10% of the nominal radiation dose level. Different pediatric patient sizes were simulated using supplemental 3D-printed extension rings. Virtual mono-energetic, iodine density, effective atomic number, and electron density results were analyzed for stability with respect to radiation dose and patient size.

RESULTS

Compared to conventional CT imaging, a pronounced improvement in the stability of attenuation measurements across patient size was observed when using virtual mono-energetic images. Iodine densities were within 0.1 mg/ml, effective atomic numbers were within 0.26 atomic numbers and electron density quantifications were within ±1.0% of their respective nominal values. Relative to the nominal dose clinical protocol, differences in attenuation of all tissue-mimicking materials were maintained below 1.6 HU for a 33% dose reduction, below 2.7 HU for a 67% dose reduction and below 3.7 HU for a 90% dose reduction, for all virtual mono-energetic energies equal to or greater than 50 keV. Iodine, and effective atomic number quantifications were stable to within 0.1 mg/ml and 0.06 atomic numbers, respectively, across all measured dose levels.

CONCLUSION

Spectral CT provides accurate and stable material quantification with respect to radiation dose reduction (up to 90%) and differing pediatric patient size. The observed consistency is an important step towards quantitative pediatric imaging at low radiation exposure levels.

Spectral CT in clinical routine imaging of neuroendocrine neoplasms

AIM

To evaluate the potential of new spectral computed tomography (SCT)-based tools in patients with neuroendocrine neoplasms (NEN).

MATERIAL AND METHODS

Eighty-eight consecutive patients with NENs were included prospectively. The patients underwent multiphase CT with spectral and standard mode. The signal-to-noise ratio (SNR)/contrast-to-noise-ratio (CNR)_{tumour-to-liver}, iodine concentrations (ICs, total tumour/hotspot) and attenuation slopes in virtual monochromatic images (VMIs) were used to assess NEN-specific SCT values in primary tumours and metastatic lesions and investigate a possible lesion contrast improvement as well as possible correlations of SCT parameters to primary tumour location and tumour grade. Furthermore, the usability of SCT parameters to differentiate between the primary tumour and metastatic lesions, and to predict tumour response after 6-months follow-up was analyzed. The applied dose of spectral and standard mode was compared intra-individually.

RESULTS

SNR/CNR_{tumour-to-liver} significantly increased in low-energy VMIs. NENs showed significant differences in ICs between primary and metastatic lesions for both absolute and normalised values (p<0.001) regardless of whether the total tumour or the hotspot was measured. There was also a significant difference in the attenuation slope (p<0.001). No significant correlations were found between SCT and tumour grade. A tumour response prediction by SCT parameters was not possible. The applied dose was comparable between the scan modes.

CONCLUSION

SCT was comparable regarding applied dose, improved tumour contrast, and contributed to differentiation between primary NEN and metastasis.

Performance of four dual-energy CT platforms for abdominal imaging: a task-based image quality assessment based on phantom data

OBJECTIVES

To compare the spectral performance of dual-energy CT (DECT) platforms using task-based image quality assessment based on phantom data.

MATERIALS AND METHODS

Two CT phantoms were scanned on four DECT platforms: fast kV-switching CT (KVSCT), split filter CT (SFCT), dual-source CT (DSCT), and dual-layer CT (DLCT). Acquisitions on each phantom were performed using classical parameters of abdomen-pelvic examination and a CTDI_vol at 10 mGy. Noise power spectrum (NPS) and task-based transfer function (TTF) were evaluated from 40 to 140 keV of virtual monoenergetic images. A detectability index (d') was computed to model the detection task of two contrast-enhanced lesions as function of keV.

RESULTS

The noise magnitude decreased from 40 to 70 keV for all DECT platforms, and the highest noise magnitude values were found for KVSCT and SFCT and the lowest for DSCT and DLCT. The average NPS spatial frequency shifted towards lower frequencies as the energy level increased for all DECT platforms, smoothing the image texture. TTF values decreased with the increase of keV deteriorating the spatial resolution. For both simulated lesions, higher detectability (d' value) was obtained at 40 keV for DLCT, DSCT, and SFCT but at 70 keV for KVSCT. The detectability of both simulated lesions was highest for DLCT and DSCT.

CONCLUSION

Highest detectability was found for DLCT for the lowest energy levels. The task-based image quality assessment used for the first time for DECT acquisitions showed the benefit of using low keV for the detection of contrast-enhanced lesions.

KEY POINTS

• Detectability of both simulated contrast-enhanced lesions was higher for dual-layer CT for the lowest energy levels. • The image noise increased and the image texture changed for the lowest energy levels. • The detectability of both simulated contrast-enhanced lesions was highest at 40 keV for all dual-energy CT platforms except for fast kV-switching platform.

Noninvasive Staging of Liver Fibrosis Using 5-Minute Delayed Dual-Energy CT: Comparison with US Elastography and Correlation with Histologic Findings

Background Normalized iodine concentration (NIC) (ratio of iodine concentration of liver to that of aorta) of liver at delayed dual-energy CT (DECT) may reflect the amount of fibrosis based on the extent of iodine uptake. Purpose To stage liver fibrosis by using 5-minute delayed DECT and compare findings with those of transient elastography (TE), shear-wave elastography (SWE), and histologic examination. Materials and Methods This prospective study included patients with chronic liver disease who were scheduled to undergo multiphase abdominal CT and liver biopsy from January 2017 to September 2018. Fifty individuals being screened as renal donors comprised the control group. Study participants underwent TE, SWE, multiphasic DECT (including 5-minute delayed dual-energy scanning), and liver biopsy. Multiphasic DECT and SWE were performed in the control group. The NIC of the right lobe of the liver (RNIC) was compared with liver stiffness (LS) as measured with TE and SWE and with the METAVIR fibrosis stage (ranging from F0 to F4). Diagnostic performance was assessed by using areas under the receiver operating characteristic curve (AUCs). Results A total of 107 participants (mean age, 35 years ± 12 [standard deviation]; 57 men) and 50 control subjects (mean age, 47 years ± 11; 29 women) were evaluated. The RNIC showed strong correlation with METAVIR stage (Spearman ρ = 0.81, P < .001). The AUC for RNIC with each METAVIR stage ranged between 0.86 (95% CI: 0.76, 0.97) and 0.96 (95% CI: 0.92, 0.99). The cut-off value of RNIC was 0.24 (sensitivity: 85% [86 of 101 participants; 95% CI: 77%, 91%]; specificity: 83% [84 of 101 participants; 95% CI: 42%, 98%]) for stage F1 fibrosis and 0.29 (sensitivity: 84% [67 of 80 participants; 95% CI: 74%, 90%]; specificity: 81% [65 of 80 participants; 95% CI: 63%, 92%]) for stage F2 fibrosis. RNIC correlated well with LS as measured with TE and SWE (Spearman ρ = 0.60 and 0.64, respectively; P < .001). Conclusion Normalized iodine concentration of liver at 5-minute delayed dual-energy CT showed strong correlation with the histologic stages of liver fibrosis and good diagnostic performance in estimating liver fibrosis. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Chandarana and Shanbhogue in this issue.

Dual-energy CT for differentiating early glottic squamous cell carcinoma from chronic inflammation and leucoplakia of vocal cord: comparison with simulated conventional 120 kVp CT

AIM

To evaluate the value of dual-energy (DE) computed tomography (CT) in discriminating early glottic squamous cell carcinoma (eGSCC) from chronic inflammation and leucoplakia of the vocal cord, and to compare the diagnostic efficiency of DECT with that of simulated conventional 120 kVp CT.

MATERIALS AND METHODS

Seventy patients with glottic lesions confirmed by histopathology (38 cases with eGSCC, 11 cases with chronic inflammation, 21 cases with leucoplakia) were enrolled in this prospective study. The DECT-derived parameters were measured and compared using independent sample t-test. Receiver operating characteristic (ROC) curve was performed to evaluate the diagnostic performance, and comparison of the area under the ROC curve (AUC) was made using the Z test to further select the best diagnostic parameters.

RESULTS

Significantly higher iodine concentration (IC), normalised IC (NIC), effective atomic number (Z_eff), 40-100 keV (20 keV-interval), slope(k), and Mix-0.3 values were found in eGSCC than those in chronic inflammation, leucoplakia, and inflammation + leucoplakia (all p<0.05). Compared with attenuation measurement of simulated conventional 120 kVp CT, the NIC, 60 keV values derived from DECT showed significantly higher AUC in discriminating these glottic lesions (p<0.05).

CONCLUSIONS

DECT is more accurate for differentiating eGSCC from chronic inflammation and leucoplakia when compared with simulated conventional 120 kVp CT.

Quantitative positron emission tomography imaging in the presence of iodinated contrast media using electron density quantifications from dual-energy computed tomography

PURPOSE

As preparation for future positron emission tomography (PET)/dual-energy computed tomography (DECT)T imaging modality and new possible clinical applications, the study aimed to evaluate the utility of clinically available spectral results from a DECT system for improving attenuation corrections of PET acquisitions in the presence of iodinated contrast media. The dependence of the accuracy of PET quantification values, reconstructed with conventional and spectral-based attenuation corrections, was examined as a function of the amount of iodine content and x-ray radiation exposure.

METHODS

Measurements were performed on commercial PET/CT and DECT systems, using a semi-anthropomorphic phantom with seven centrifuge tubes in its bore. Five different configurations of tube contents were scanned by both PET/CT and DECT. With the aim of mimicking clinically observed concentrations, in all phantom configurations the center tube contained a high concentration of radionuclide while the peripheral tubes contained a lower concentration of radionuclide. Iodine content was incrementally increased between phantom configurations by replacing iodine-free tubes with tubes that contained the original radionuclide concentration within a 10 mg/ml iodine dilution. DECT-based attenuation correction maps were generated by scaling electron density spectral results into corresponding 511 keV photon linear attenuation coefficients.

RESULTS

Mean SUV values obtained from the nominal PET reconstruction, using conventional CT images as input for the attenuation correction, demonstrate a monotonic increase of 8.6% when the water and radionuclide mixtures were replaced by iodine, water, and radionuclide (same level of activity) mixture. Mean SUV values obtained from the DECT-based reconstruction, in which the attenuation correction utilizes electron density values as input, demonstrate different, more stable behavior across all iodine insert configurations, with a standard deviation to mean ratio of less than 1%. This observed behavior was independent of the area size used for measurement. A minor radiation dose dependency of the electron density values (below 0.5%) was observed. This resulted in consistent (iodine independent) PET quantification behavior, which persisted even at the lowest radiation dose levels tested in our experiment, that is, 25% of the radiation dose utilized for CT acquisition in the clinical PET/CT protocol.

CONCLUSIONS

Utilization of DECT-generated electron density estimations for attenuation correction benefit PET quantification consistency in the presence of iodine and at nominal and low DECT radiation exposure levels. The ability to correctly account for iodinated contrast media in PET acquisitions will allow the development of new clinical applications that rely on the quantitative capabilities of spectral CT technologies and modern PET systems.

Semiautomatic Segmentation and Radiomics for Dual-Energy CT: A Pilot Study to Differentiate Benign and Malignant Hepatic Lesions

OBJECTIVE. This study assessed a machine learning-based dual-energy CT (DECT) tumor analysis prototype for semiautomatic segmentation and radiomic analysis of benign and malignant liver lesions seen on contrast-enhanced DECT. MATERIALS AND METHODS. This institutional review board-approved study included 103 adult patients (mean age, 65 ± 15 [SD] years; 53 men, 50 women) with benign (60/103) or malignant (43/103) hepatic lesions on contrast-enhanced dual-source DECT. Most malignant lesions were histologically proven; benign lesions were either stable on follow-up CT or had characteristic benign features on MRI. Low- and high-kilovoltage datasets were deidentified, exported offline, and processed with the DECT tumor analysis for semiautomatic segmentation of the volume and rim of each liver lesion. For each segmentation, contrast enhancement and iodine concentrations as well as radiomic features were derived for different DECT image series. Statistical analyses were performed to determine if DECT tumor analysis and radiomics can differentiate benign from malignant liver lesions. RESULTS. Normalized iodine concentration and mean iodine concentration in the benign and malignant lesions were significantly different (p < 0.0001-0.0084; AUC, 0.695-0.856). Iodine quantification and radiomic features from lesion rims (AUC, ≤ 0.877) had higher accuracy for differentiating liver lesions compared with the values from lesion volumes (AUC, ≤ 0.856). There was no difference in the accuracies of DECT iodine quantification (AUC, 0.91) and radiomics (AUC, 0.90) for characterizing liver lesions. CONCLUSION. DECT radiomics were more accurate than iodine quantification for differentiating solid benign and malignant hepatic lesions.

Follow-up Recommendation Rates Associated With Spectral Detector Dual-Energy CT of the Abdomen and Pelvis: A Retrospective Comparison to Single-Energy CT

BACKGROUND

Dual-energy CT image sets have many applications in abdominopelvic imaging but no demonstrated clinical effect.

PURPOSE

To determine the effect of dual-energy CT iodine maps on abdominopelvic imaging follow-up recommendation rates.

MATERIALS AND METHODS

Retrospective study of abdominopelvic CTs acquired from April 2017 through June 2018. CT reports were analyzed for radiologic follow-up recommendation and follow-up recommendation reason. Follow-up MRI reports were analyzed for benign or nonbenign diagnosis. CT scans with iodine maps (CTIMs) and conventional CT scans (CCTs) subgroups were compared using χ² testing.

RESULTS

In all, 3,221 abdominopelvic CT scans of 2,401 patients (1,326 men, 1,075 women, mean age 54.1 years) were analyzed; 1,423 were CTIMs and 1,798 were CCTs. Follow-up recommendation rates were not significantly different for CTIMs and CCTs (19.5% and 21.4%, respectively, P = .19). Follow-up recommendations because of incomplete diagnosis were significantly lower in CTIMs (9.1%) than in CCTs (11.9%, P = .01). Follow-up recommendations for MRI and PET/CT were significantly lower in CTIMs (9.6%) than CCTs (13.0%, P = .003). Follow-up MRI outcomes (n = 111) were not different between CTIMs (61.2% benign) and CCTs (59.6%, P = .87).

CONCLUSION

Dual-energy CT iodine maps are associated with decreased follow-up examinations because of incomplete diagnosis and decreased recommendations for follow-up MRI, suggesting that abdominopelvic iodine maps may benefit patient care and decrease institutional cost.

Image-domain multimaterial decomposition for dual-energy computed tomography with nonconvex sparsity regularization

Dual-energy computed tomography (CT) has the potential to decompose tissues into different materials. However, the classic direct inversion (DI) method for multimaterial decomposition (MMD) cannot accurately separate more than two basis materials due to the ill-posed problem and amplified image noise. We propose an integrated MMD method that addresses the piecewise smoothness and intrinsic sparsity property of the decomposition image. The proposed MMD was formulated as an optimization problem including a quadratic data fidelity term, an isotropic total variation term that encourages image smoothness, and a nonconvex penalty function that promotes decomposition image sparseness. The mass and volume conservation rule was formulated as the probability simplex constraint. An accelerated primal-dual splitting approach with line search was applied to solve the optimization problem. The proposed method with different penalty functions was compared against DI on a digital phantom, a Catphan^® 600 phantom, a quantitative imaging phantom, and a pelvis patient. The proposed framework distinctly separated the CT image up to 12 basis materials plus air with high decomposition accuracy. The cross talks between two different materials are substantially reduced, as shown by the decreased nondiagonal elements of the normalized cross correlation (NCC) matrix. The mean square error of the measured electron densities was reduced by 72.6%. Across all datasets, the proposed method improved the average volume fraction accuracy from 61.2% to 99.9% and increased the diagonality of the NCC matrix from 0.73 to 0.96. Compared with DI, the proposed MMD framework improved decomposition accuracy and material separation.

Renal cystic lesions characterization using spectral detector CT (SDCT): Added value of spectral results

OBJECTIVES

To evaluate the added value of spectral results derived from Spectral Detector CT (SDCT) to the characterization of renal cystic lesions (RCL).

METHODS

This retrospective study was approved by the local Institutional review board. 70 consecutive patients who underwent abdominopelvic SDCT and had at least one RCL were included. 84 RCL were categorized as simple, complex or neoplastic based on attenuation values on single-phase post-contrast images. Attenuation values were measured in each lesion on standard conventional CT images (stCI) and virtual monoenergetic images of 40keV and 100keV. A spectral curve slope was calculated and intra lesional iodine concentration (IC) was measured using iodine-density maps. Reference standard was established using histopathologic correlation, prior and follow-up imaging. Analysis of variance (ANOVA) was used to compare between the groups.

RESULTS

Mean attenuation values for benign simple and complex RCL differed significantly (42 ± 16 vs 8 ± 3 HU; p < 0.001). IC was almost identical in benign simple and complex RCL (0.23 ± 0.04 mg ml^-1 vs 0.24 ± 0.04 mg ml^-1), while IC in neoplastic RCL was significantly higher (2.10 ± 0.08 mg ml^-1 ; p < 0.001). The mean spectral curve slope did not differ significantly between simple and complex RCL (0.30 ± 0.03 vs 0.33 ± 0.05) but was significantly higher in neoplastic RCL (2.60 ± 0.10; p < 0.001).

CONCLUSIONS

Spectral results of SDCT are highly promising in distinguishing benign complex RCL from enhancing neoplastic RCL based on single-phase post-contrast imaging only.

ADVANCES IN KNOWLEDGE

SDCT can assist in differentiating between benign complex and neoplastic renal cystic lesions.

Spectral CT and its specific values in the staging of patients with non-small cell lung cancer: technical possibilities and clinical impact

AIM

To investigate how spectral computed tomography (SCT) values impact the staging of non-small cell lung cancer (NSCLC) patients.

MATERIALS AND METHODS

One hundred and thirteen patients with confirmed NSCLC were included in a prospective cohort study. All patients underwent single-phase contrast-enhanced SCT (using the fast tube voltage switching technique, 80-140 kV). SCT values (iodine content [IC], spectral slope pitch, and radiodensity increase) of malignant tissue (primary and metastases) and lymph nodes (LNs) were measured. Adrenal masses were evaluated in a virtual non-contrast series (VNS). If pulmonary embolism was present, pulmonary perfusion was analysed as an additional finding.

RESULTS

Fifty-two untreated primary NSCLC lesions were evaluable. Lung adenocarcinoma had significantly higher normalised IC (NIC: 19.37) than squamous cell carcinoma (NIC: 12.03; p=0.035). Pulmonary metastases were not significantly different from benign lung nodules. A total of 126 LNs were analysed and histologically proven metastatic LNs (2.08 mg/ml) had significantly lower IC than benign LNs (2.58 mg/ml; p=0.023). Among 34 adrenal masses, VNS identified adenomas with high sensitivity (91%) and specificity (100%). In two patients, a perfusion defect due to pulmonary embolism was detected in the iodine images.

CONCLUSION

SCT may contribute to the differentiation of histological NSCLC subtypes and improve the identification of LN metastases. VNS differentiates adrenal adenoma from metastasis. In case of pulmonary embolism, iodine imaging can visualise associated pulmonary perfusion defects.