Accuracy of iodine quantification using dual energy CT in latest generation dual source and dual layer CT. Eur Radiol. 2017;27:3904-3912. [PMID: 28168368 PMCID: PMC5544802 DOI: 10.1007/s00330-017-4752-9]

Impact of patient habitus and acquisition protocol on iodine quantification in dual-source photon-counting computed tomography

Purpose

Evaluation of iodine quantification accuracy with varying iterative reconstruction level, patient habitus, and acquisition mode on a first-generation dual-source photon-counting computed tomography (PCCT) system.

Approach

A multi-energy CT phantom with and without its extension ring equipped with various iodine inserts (0.2 to 15.0 mg/ml) was scanned over a range of radiation dose levels (CTDI vol 0.5 to 15.0 mGy) using two tube voltages (120, 140 kVp) and two different source modes (single-, dual-source). To assess the agreement between nominal and measured iodine concentrations, iodine density maps at different iterative reconstruction levels were utilized to calculate root mean square error (RMSE) and generate Bland-Altman plots by grouping radiation dose levels (ultra-low: < 1.5 ; low: 1.5 to 5; medium: 5 to 15 mGy) and iodine concentrations (low: < 5 ; high: 5 to 15 mg/mL).

Results

Overall, quantification of iodine concentrations was accurate and reliable even at ultra-low radiation dose levels. RMSE ranged from 0.25 to 0.37, 0.20 to 0.38, and 0.25 to 0.37 mg/ml for ultra-low, low, and medium radiation dose levels, respectively. Similarly, RMSE was stable at 0.31, 0.28, 0.33, and 0.30 mg/ml for tube voltage and source mode combinations. Ultimately, the accuracy of iodine quantification was higher for the phantom without an extension ring (RMSE 0.21 mg/mL) and did not vary across different levels of iterative reconstruction.

Conclusions

The first-generation PCCT allows for accurate iodine quantification over a wide range of iodine concentrations and radiation dose levels. Stable accuracy across iterative reconstruction levels may allow further radiation exposure reductions without affecting quantitative results.

Performance evaluation of single- and dual-contrast spectral imaging on a photon-counting-detector CT

BACKGROUND

The first commercially available photon-counting-detector CT (PCD-CT) has been introduced for clinical use. However, its spectral performance on single- and dual-contrast imaging tasks has not been comprehensively assessed.

PURPOSE

To evaluate the spectral imaging performance of a clinical PCD-CT system for single-contrast material [iodine (I) or gadolinium (Gd)] and dual-contrast materials (I and Gd) in comparison with a dual-source dual-energy CT (DS-DECT).

METHODS

Iodine (5, 10, and 15 mg/mL) and gadolinium (3.3, 6.6, and 9.9 mg/mL) samples, and their mixtures (I/Gd: 5/3.3 and 10/6.6 mg/mL) were prepared and placed in two torso-shaped water phantoms (lateral dimensions: 30 and 40 cm). These phantoms were scanned on a PCD-CT (NAEOTOM Alpha, Siemens) at 90, 120, and 140 kV. The same phantoms were scanned on a DS-DECT (SOMATOM Force, Siemens) with 70/Sn150, 80/Sn150, 90/Sn150, and 100/Sn150 kV. The radiation dose levels were matched [volume CT dose index (CTDIvol): 10 mGy for the 30 cm phantom and 20 mGy for the 40 cm phantom] across all tube voltage settings and between scanners. Two-material decomposition (I/water or Gd/water) was performed on iodine or gadolinium samples, and three-material decomposition (I/Gd/water) on both individual samples and mixtures. On each decomposed image, mean mass concentration (± standard deviation) was measured in circular region-of-interests placed on the contrast samples. Root-mean-square-error (RMSE) values of iodine and gadolinium concentrations were reported based on the measurements across all contrast samples and repeated on 10 consecutive slices.

RESULTS

For all material decomposition tasks on the DS-DECT, the kV pairs with greater spectral separation (70/Sn150 kV and 80/Sn150 kV) yielded lower RMSE values than other DS-DECT and PCD-CT alternatives. Specifically, for the optimal 70/Sn150 kV, RMSE values were 1.2 ± 0.1 mg/mL (I) for I/water material decomposition, 1.0 ± 0.1 mg/mL (Gd) for Gd/water material decomposition, and 4.5 ± 0.2 mg/mL (I) and 3.7 ± 0.2 mg/mL (Gd), respectively, for I/Gd/water material decomposition. On the PCD-CT, the optimal tube voltages were 120 or 140 kV for I/water decomposition with RMSE values of 2.0 ± 0.1 mg/mL (I). For Gd/water decomposition on PCD-CT, the optimal tube voltage was 140 kV with gadolinium RMSE values of 1.5 ± 0.1 mg/mL (Gd), with the 90 kV setting on PCD-CT generating higher RMSE values for gadolinium concentration compared to all DS-DECT and PCD-CT alternatives. For three material decomposition, both imaging modalities demonstrated substantially higher RMSE values for iodine and gadolinium, with 90 kV being the optimal tube potential for Gd/I quantitation on PCD-CT [5.4 ± 0.3 mg/mL (I) and 3.9 ± 0.2 mg/mL (Gd)], and DS-DECT at 100/Sn150 kV having larger RMSE values for both materials compared to the alternatives for either modality.

CONCLUSION

Optimal tube voltage for material decomposition on the clinical PCD-CT is task-dependent but inferior to DS-DECT using 70/Sn150 kV or 80/Sn150 kV in two-material decomposition for single-contrast imaging (iodine/water or gadolinium/water). Three material decomposition (iodine/gadolinium/water) in dual-contrast imaging yields substantially higher RMSE for both imaging platforms.

Spectral CT in the evaluation of perineural invasion status in rectal cancer

PURPOSE

To investigate whether preoperative spectral CT quantitative parameters can assess perineural invasion (PNI) status in rectal cancer.

METHODS

Sixty-two patients diagnosed with rectal cancer who underwent preoperative spectral CT were retrospectively enrolled and divided into positive and negative PNI groups according to histopathologic results. The CT attenuation value (HU) of virtual monochromatic images (40-70 keV), spectral curve slope (K(HU)), effective atomic number (Zeff), and iodine concentration (IC) from spectral CT were compared between these two groups using t test or rank sum test. A nomogram was established by incorporating the independent predictors to assess the overall diagnostic efficacy. The area under the ROC curves (AUCs) were compared using the DeLong test.

RESULTS

The preoperative spectral CT parameters (40-70 keV attenuation, K(HU), Zeff, and IC) were significantly higher in the PNI-positive group compared to the PNI-negative group (all p < 0.05). The highest predictive efficiency of PNI was observed at 40 keV attenuation, with an area under the curve (AUC), sensitivity, specificity, and accuracy of 0.847, 81.8%, 72.5%, and 75.8%, respectively. Binary logistic regression demonstrated that the clinical feature (cN stage) and 40 keV attenuation were independent predictors of PNI status. The nomogram incorporating these two predictors (cN stage and 40 keV attenuation) exhibited the best evaluation efficacy, with an AUC, sensitivity, specificity, and accuracy of 0.885, 86.4%, 77.5%, and 80.6%.

CONCLUSION

Spectral CT quantitative parameters proved valuable in the preoperative assessment of PNI status in rectal cancer patients. The combination of spectral CT parameters and clinical features could further enhance the diagnostic efficiency.

Iodine concentration, HU accuracy, and metal artifacts evaluation on second-generation dual-layer spectral detector CT images with metal implants: a phantom study

BACKGROUND

Metal implants may affect the image quality, iodine concentration (IC), and CT Hounsfield unit (HU) quantification accuracy.

PURPOSE

To investigate the quantitative accuracy of IC and HU from dual-layer spectral detector (DLCT) in the presence of metal artifacts.

MATERIAL AND METHODS

An experimental cylindrical phantom containing eight iodine inserts and two metal inserts was designed. The phantom underwent scanning at three radiation dose levels and two tube voltage settings. A set of conventional images (CIs), virtual monoenergetic images (VMIs), and iodine concentration maps (ICMs) were generated and measured for all the eight iodine inserts. Quantitative indicators of mean absolute percentage error (MAPE), artifact index (AI), contrast-to-noise ratio (CNR), signal-to-noise ratio (SNR), and standard deviation (SD) on CIs and VMIs were calculated for IC and HU. Subjective score evaluation was also conducted.

RESULTS

The MAPEiodine values of all regions of interest across different scanning configurations were all <5%. Almost all APEiodine values were <5%, indicating that metal artifacts had little impact on IC measurements. When the tube voltage was fixed, the SD value of attenuation decreased with the increase of the tube current; this is also true when the tube current was fixed. The middle energy reconstructions seemed to give a good balance between reducing artifacts and improving contrast.

CONCLUSION

VMIs from DLCT can reduce metal artifacts, the accuracy of IC quantification is not sensitive to imaging parameters. In summary, metal implants exhibit minimal impact on image quality and IC quantification accuracy in reconstructed images from DLCT.

Stationary prospective cardiac gated computed tomography-dynamic study in phantoms andin vivo

Objective.This study explores the feasibility of a stationary gantry cardiac gated computed tomography (CT) with carbon nanotube (CNT) linear x-ray source arrays.Approach.We developed a stationary gantry CT system utilizing multipixel CNT x-ray sources. Given the advantages of straightforward x-ray pulse control with these sources, we investigated the potential for gated prospective imaging. We implemented prospective respiratory and cardiac gating control and evaluated the system through dynamic phantom imaging studies followed by imaging of a porcine model.Main Results.The findings revealed minimal anatomical motion artifacts in the heart and lungs, confirming successful physiologic gated acquisition in stationary gantry cardiac CT. This indicates the potential of this imaging approach for reducing artifacts and improving image quality.Significance.This study demonstrates the feasibility of prospective physiological gating with CNT x-ray sources in a stationary gantry setup for cardiac imaging. This approach could potentially alleviate the need for beta blocker administration during cardiac CT scans, thereby increasing the flexibility of the imaging system and enabling the imaging of a wider variety of patient cardiac conditions.

Intra-patient variability of iodine quantification across different dual-energy CT platforms: assessment of normalization techniques

OBJECTIVES

To investigate intra-patient variability of iodine concentration (IC) between three different dual-energy CT (DECT) platforms and to test different normalization approaches.

METHODS

Forty-four patients who underwent portal venous phase abdominal DECT on a dual-source (dsDECT), a rapid kVp switching (rsDECT), and a dual-layer detector platform (dlDECT) during cancer follow-up were retrospectively included. IC in the liver, pancreas, and kidneys and different normalized ICs (NICPV:portal vein; NICAA:abdominal aorta; NICALL:overall iodine load) were compared between the three DECT scanners for each patient. A longitudinal mixed effects analysis was conducted to elucidate the effect of the scanner type, scan order, inter-scan time, and contrast media amount on normalized iodine concentration.

RESULTS

Variability of IC was highest in the liver (dsDECT vs. dlDECT 28.96 (14.28-46.87) %, dsDECT vs. rsDECT 29.08 (16.59-62.55) %, rsDECT vs. dlDECT 22.85 (7.52-33.49) %), and lowest in the kidneys (dsDECT vs. dlDECT 15.76 (7.03-26.1) %, dsDECT vs. rsDECT 15.67 (8.86-25.56) %, rsDECT vs. dlDECT 10.92 (4.92-22.79) %). NICALL yielded the best reduction of IC variability throughout all tissues and inter-scanner comparisons, yet did not reduce the variability between dsDECT vs. dlDECT and rsDECT, respectively, in the liver. The scanner type remained a significant determinant for NICALL in the pancreas and the liver (F-values, 12.26 and 23.78; both, p < 0.0001).

CONCLUSIONS

We found tissue-specific intra-patient variability of IC across different DECT scanner types. Normalization mitigated variability by reducing physiological fluctuations in iodine distribution. After normalization, the scanner type still had a significant effect on iodine variability in the pancreas and liver.

CLINICAL RELEVANCE STATEMENT

Differences in iodine quantification between dual-energy CT scanners can partly be mitigated by normalization, yet remain relevant for specific tissues and inter-scanner comparisons, which should be taken into account at clinical routine imaging.

KEY POINTS

• Iodine concentration showed the least variability between scanner types in the kidneys (range 10.92-15.76%) and highest variability in the liver (range 22.85-29.08%). • Normalizing tissue-specific iodine concentrations against the overall iodine load yielded the greatest reduction of variability between scanner types for 2/3 inter-scanner comparisons in the liver and for all (3/3) inter-scanner comparisons in the kidneys and pancreas, respectively. • However, even after normalization, the dual-energy CT scanner type was found to be the factor significantly influencing variability of iodine concentration in the liver and pancreas.

Evaluating Treatment Response in GEJ Adenocarcinoma: The Role of Pretherapeutic and Posttherapeutic Iodine Mapping

BACKGROUND

Neoadjuvant therapy regimens have significantly improved the prognosis of GEJ (gastroesophageal junction) cancer; however, there are a significant percentage of patients who benefit from earlier resection or adapted therapy regimens, and the true response rate can only be determined histopathologically. Methods that allow preoperative assessment of response are lacking.

PURPOSE

The purpose of this retrospective study is to assess the potential of pretherapeutic and posttherapeutic spectral CT iodine density (IoD) in predicting histopathological response to neoadjuvant chemotherapy in patients diagnosed with adenocarcinoma of the GEJ.

METHODS

In this retrospective cohort study, a total of 62 patients with GEJ carcinoma were studied. Patients received a multiphasic CT scan at diagnosis and preoperatively. Iodine-density maps were generated based on spectral CT data. All tumors were histopathologically analyzed, and the tumor regression grade (TRG) according to Becker et al ( Cancer . 2003;98:1521-1530) was determined. Two experienced radiologists blindly placed 5 defined ROIs in the tumor region of highest density, and the maximum value was used for further analysis. Iodine density was normalized to the aortic iodine uptake. In addition, tumor response was assessed according to standard RECIST measurement. After assessing interrater reliability, the correlation of IoD values with treatment response and with histopathologic TRG was evaluated.

RESULTS

The normalized ΔIoD (IoD at diagnosis - IoD after neoadjuvant treatment) and the normalized IoD after neoadjuvant treatment correlated significantly with the TRG. For the detection of responders and nonresponders, the receiver operating characteristic (ROC) curve for normalized ΔIoD yielded the highest area under the curve of 0.95 and achieved a sensitivity and specificity of 92.3% and 92.1%, respectively. Iodine density after neoadjuvant treatment achieved an area under the curve of 0.88 and a sensitivity and specificity of 86.8% and 84.6%, respectively (cutoff, 0.266). Iodine density at diagnosis and RECIST did not provide information to distinguish responders from nonresponders. Using the cutoff value for IoD after neoadjuvant treatment, a reliable classification of responders and nonresponders was achieved for both readers in a test set of 11 patients. Intraclass correlation coefficient revealed excellent interrater reliability (intraclass correlation coefficient, >0.9). Lastly, using the cutoff value for normalized ΔIoD as a definition for treatment response, a significantly longer survival of responders was shown.

CONCLUSIONS

Changes in IoD after neoadjuvant treatment of GEJ cancer may be a potential surrogate for therapy response.

Improvement of Breast Cancer Detection Using Dual-Layer Spectral CT

This study aimed to investigate the diagnostic performance of breast mass detection on monoenergetic image data at 40 keV (MonoE40) and on iodine maps (IM) compared with conventional image data (CI). In this prospective single-center case-control study, 50 breast cancer patients were examined using contrast-enhanced dual-layer spectral CT. For qualitative and quantitative comparison of MonoE40 and IM with CI image data, four blinded, independent readers assessed 300 randomized single slices (two slices for each imaging type per case) with or without cancerous lesions for the presence of a breast mass. Detection sensitivity and specificity were calculated and readers rated their subjective diagnostic certainty. For statistical analysis of sensitivity and specificity, a paired t-test and ANOVA were used (significance level p = 0.05). A total of 50 female patients (median age 51 years, range 28-83 years) participated. IM had the highest overall scores in sensitivity and specificity for breast cancer detection, with 0.97 ± 0.06 and 0.95 ± 0.07, respectively, compared with 0.90 ± 0.04 and 0.92 ± 0.06 in CI. MonoE40 yielded a sensitivity of 0.96 ± 0.02 and specificity of 0.94 ± 0.08. All differences in sensitivity and specificity between MonoE or IM and CI were statistically significant (p < 0.001). The superiority of IM sensitivity and specificity was most pronounced in patients with dense breasts. Spectral CT improved the detection of breast cancer with higher sensitivity and specificity compared to conventional image data in our study.

Single photon emission computed tomography/computed tomography imaging of gouty arthritis: A new voice

Gouty arthritis, often referred to simply as gout, is a disorder of purine metabolism characterized by the deposition of monosodium urate monohydrate (MSU) crystals in multiple systems and organs, especially in joints and their surrounding soft tissue. Gout is a treatable chronic disease, and the main strategy for effective management is to reverse the deposition of MSU crystals by uric acid reduction, and to prevent gout attacks, tophi deposition and complications, and thereby improve the quality of life. However, the frequent association of gout with other conditions such as hypertension, obesity, cardiovascular disease, diabetes, dyslipidemia, chronic kidney disease (CKD) and kidney stones can complicate the treatment of gout and lead to premature death. Here, we review the use of medical imaging techniques for studying gouty arthritis with special interest in the potential role of single photon emission computed tomography (SPECT)/computed tomography (CT) in the clinical management of gout and complications (e.g., chronic kidney disease and cardiovascular disease).

Halved contrast medium dose coronary dual-layer CT-angiography - phantom study of tube current and patient characteristics

Virtual mono-energetic images (VMI) using dual-layer computed tomography (DLCT) enable substantial contrast medium (CM) reductions. However, the combined impact of patient size, tube voltage, and heart rate (HR) on VMI of coronary CT angiography (CCTA) remains unknown. This phantom study aimed to assess VMI levels achieving comparable contrast-to-noise ratio (CNR) in CCTA at 50% CM dose across varying tube voltages, patient sizes, and HR, compared to the reference protocol (100% CM dose, conventional at 120 kVp). A 5 mm artificial coronary artery with 100% (400 HU) and 50% (200 HU) iodine CM-dose was positioned centrally in an anthropomorphic thorax phantom. Horizontal coronary movement was matched to HR (at 0, < 60, 60-75, > 75 bpm), with varying patient sizes simulated using phantom extension rings. Raw data was acquired using a clinical CCTA protocol at 120 and 140 kVp (five repetitions). VMI images (40-70 keV, 5 keV steps) were then reconstructed; non-overlapping 95% CNR confidence intervals indicated significant differences from the reference. Higher CM-dose, reduced VMI, slower HR, higher tube voltage, and smaller patient sizes demonstrated a trend of higher CNR. Regardless of HR, patient size, and tube voltage, no significant CNR differences were found compared to the reference, with 100% CM dose at 60 keV, or 50% CM dose at 40 keV. DLCT reconstructions at 40 keV from 120 to 140 kVp acquisitions facilitate 50% CM dose reduction for various patient sizes and HR with equivalent CNR to conventional CCTA at 100% CM dose, although clinical validation is needed.

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.

Dual-Energy CT Iodine Uptake of Head and Neck: Definition of Reference Values in a Big Data Cohort

BACKGROUND

Despite a considerable amount of literature on dual-energy CT (DECT) iodine uptake of the head and neck, the physiologic iodine uptake of this region has not been defined yet. This study aims to establish reference values for the iodine uptake of healthy organs to facilitate clinical application.

METHODS

Consecutive venous DECT scans of the head and neck were reviewed, and unremarkable exams were included (n = 617). A total of 35 region of interest measurements were performed in 16 anatomical regions. Iodine uptake was compared among different organs/tissues and subgroup analysis was performed (male (n = 403) vs. female (n = 214); young (n = 207) vs. middle-aged (n = 206) vs. old (n = 204); and normal weight (n = 314) vs. overweight (n = 196) vs. obese (n = 107)).

RESULTS

Overall mean iodine uptake values ranged between 0.5 and 9.4 mg/mL. Women showed higher iodine concentrations in the cervical vessels and higher uptake for the parotid gland, masseter muscle, submandibular glands, sublingual glands, palatine tonsils, tongue body, thyroid gland, and the sternocleidomastoid muscle than men (p ≤ 0.04). With increasing age, intravascular iodine concentrations increased as well as iodine uptake for cerebellum and thyroid gland, while values for the tongue and palatine tonsils were lower compared to younger subjects (p ≤ 0.03). Iodine concentrations for parotid glands and sternocleidomastoid muscles decreased with a higher BMI (p ≤ 0.004), while normal-weighted patients showed higher iodine values inside the jugular veins, other cervical glands, and tonsils versus patients with a higher BMI (p ≤ 0.04).

CONCLUSION

physiologic iodine uptake values of cervical organs and tissues show gender-, age-, and BMI-related differences, which should be considered in the clinical routine of head and neck DECT.

Development and Validation of a Dual-Energy CT-Based Model for Predicting the Number of Central Lymph Node Metastases in Clinically Node-Negative Papillary Thyroid Carcinoma

RATIONALE AND OBJECTIVES

This study aimed to develop and validate a dual-energy CT (DECT)-based model for preoperative prediction of the number of central lymph node metastases (CLNMs) in clinically node-negative (cN0) papillary thyroid carcinoma (PTC) patients.

MATERIALS AND METHODS

Between January 2016 and January 2021, 490 patients who underwent lobectomy or thyroidectomy, CLN dissection, and preoperative DECT examinations were enrolled and randomly allocated into the training (N = 345) and validation cohorts (N = 145). The patients' clinical characteristics and quantitative DECT parameters obtained on primary tumors were collected. Independent predictors of> 5 CLNMs were identified and integrated to construct a DECT-based prediction model, for which the area under the curve (AUC), calibration, and clinical usefulness were assessed. Risk group stratification was performed to distinguish patients with different recurrence risks.

RESULTS

More than 5 CLNMs were found in 75 (15.3%) cN0 PTC patients. Age, tumor size, normalized iodine concentration (NIC), normalized effective atomic number (nZeff) and the slope of the spectral Hounsfield unit curve (λHu) in the arterial phase were independently associated with> 5 CLNMs. The DECT-based nomogram that incorporated predictors demonstrated favorable performance in both cohorts (AUC: 0.842 and 0.848) and significantly outperformed the clinical model (AUC: 0.688 and 0.694). The nomogram showed good calibration and added clinical benefit for predicting> 5 CLNMs. The KaplanMeier curves for recurrence-free survival showed that the high- and low-risk groups stratified by the nomogram were significantly different.

CONCLUSION

The nomogram based on DECT parameters and clinical factors could facilitate preoperative prediction of the number of CLNMs in cN0 PTC patients.

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

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

Nomogram Based on Dual-Layer Spectral Detector CTA Parameter for the Prediction of Infarct Core in Patients with Acute Ischemic Stroke

(1) Background: Acute ischemic stroke (AIS) is time-sensitive. The accurate identification of the infarct core and penumbra areas in AIS patients is an important basis for formulating treatment plans, and is the key to dual-layer spectral detector computed tomography angiography (DLCTA), a safer and more accurate diagnostic method for AIS that will replace computed tomography perfusion (CTP) in the future. Thus, this study aimed to investigate the value of DLCTA in differentiating infarct core from penumbra in patients with AIS to establish a nomogram combined with spectral computed tomography (CT) parameters for predicting the infarct core and performing multi-angle evaluation. (2) Methods: Data for 102 patients with AIS were retrospectively collected. All patients underwent DLCTA and CTP. The patients were divided into the non-infarct core group and the infarct core group, using CTP as the reference. Multivariate logistic regression analysis was used to screen predictors related to the infarct core and establish a nomogram model. The receiver operating characteristic (ROC) curve, the calibration curve, and decision curve analysis (DCA) were used to evaluate the predictive efficacy, accuracy, and clinical practicability of the model, respectively. (3) Results: Multivariate logistic analysis identified three independent predictors: iodine density (OR: 0.022, 95% CI: 0.003-0.170, p < 0.001), hypertension (OR: 7.179, 95% CI: 1.766-29.186, p = 0.006), and triglycerides (OR: 0.255, 95% CI: 0.109-0.594, p = 0.002). The AUC-ROC of the nomogram was 0.913. Calibration was good. Decision curve analysis was clinically useful. (4) Conclusions: The spectral CT parameters, specifically iodine density values, effectively differentiate between the infarct core and penumbra areas in patients with AIS. The nomogram, based on iodine density values, showed strong predictive power, discrimination, and clinical utility to accurately predict infarct core in AIS patients.

Quantitative Dual-Energy X-ray Imaging Based on K-Edge Absorption Difference

Conventional flat panel X-ray imaging (FPXI) employs a single scintillator for X-ray conversion, which lacks energy spectrum information. The recent innovation of employing multilayer scintillators offers a route for multispectral X-ray imaging. However, the principles guiding optimal multilayer scintillator configuration selection and quantitative analysis models remain largely unexplored. Here, we propose to adopt the K-edge absorption coefficient as a key parameter for selecting tandem scintillator combinations and to utilize the coefficient matrix to calculate the absorption efficiency spectrum of the sample. Through a dual scintillator example comprising C4H12NMnCl3 and Cs3Cu2I5, we establish a streamlined quantitative framework for deducing X-ray spectra from scintillation spectra, with an average relative error of 6.28% between the calculated and measured sample absorption spectrum. This insight forms the foundation for our quantitative method to distinguish the material densities. Leveraging this tandem scintillator configuration, in conjunction with our analytical tools, we successfully demonstrate the inherent merits of dual-energy X-ray imaging for discerning materials with varied densities and thicknesses.

Dual-Energy Computed Tomography in Cardiac Imaging

Dual-energy computed tomography (DECT) acquires images using two energy spectra and offers a variation of reconstruction techniques for improved cardiac imaging. Virtual monoenergetic images decrease artifacts improving coronary plaque and stent visualization. Further, contrast attenuation is increased allowing significant reduction of contrast dose. Virtual non-contrast reconstructions enable coronary artery calcium scoring from contrast-enhanced scans. DECT provides advanced plaque imaging with detailed analysis of plaque components, indicating plaque stability. Extracellular volume assessment using DECT offers noninvasive detection of myocardial fibrosis. This review aims to outline the current cardiac applications of DECT, summarize recent literature, and discuss their findings.

Establishing quality control action limits for CT number accuracy in spectral images using an American College of Radiology phantom

BACKGROUND

Computed tomography (CT) number accuracy is important for quality assurance in CT imaging. However, in dual-energy CT imaging, there are no widely used action limits for CT number accuracy in spectral images, information that is urgently needed.

PURPOSE

To establish action limits for spectral CT images using longitudinal spectral data and an American College of Radiology (ACR) phantom.

METHODS

An ACR accreditation phantom was scanned routinely as part of a quality control program in our institution. We selected and analyzed 57 continuous weekly scans. The CT numbers or the density values of conventional and spectral images, including virtual monoenergetic images (40, 50, 70, 120, and 200 keV), iodine maps, calcium suppressed, and virtual non-contrast images, were measured in the four inserts (solid water, bone, polyethylene, and acrylic) of the phantom. Longitudinal data were analyzed for correlation using Pearson's correlation coefficient (r) and standard deviation (SD). The SD ratios between spectral images and conventional images were calculated and the action limits for spectral images were established based on the action limits from the ACR.

RESULTS

Strong to very strong correlations (r > 0.70 or r < -0.70) were found among most spectral image types except the 200 keV images using solid water, polyethylene, and acrylic inserts (r = [-0.45, 0.64]). The SD ratio was highest for the 40 keV images, ranging from 2.8 to 6.5. The action limits of the bone insert were baseline ± 5.3 mg/mL for the iodine map and ranged from baseline ± 23.0 HU to baseline ± 391.9 HU for the other image types. The action limits for solid water ranged from baseline ± 4.1 HU to baseline ± 25.3 HU. The results for the polyethylene and the acrylic insert were close to those for solid water. Baselines can be established using the average of the initial 5∼10 measurements.

CONCLUSIONS

Using longitudinal data, we estimated the action limits for CT number accuracy in the spectral images. This paves the way for establishing a comprehensive quality control program for spectral CT imaging.

Quantitative performance of photon-counting CT at low dose: Virtual monochromatic imaging and iodine quantification

BACKGROUND

Quantitative imaging techniques, such as virtual monochromatic imaging (VMI) and iodine quantification (IQ), have proven valuable diagnostic methods in several specific clinical tasks such as tumor and tissue differentiation. Recently, a new generation of computed tomography (CT) scanners equipped with photon-counting detectors (PCD) has reached clinical status.

PURPOSE

This work aimed to investigate the performance of a new photon-counting CT (PC-CT) in low-dose quantitative imaging tasks, comparing it to an earlier generation CT scanner with an energy-integrating detector dual-energy CT (DE-CT). The accuracy and precision of the quantification across size, dose, material types (including low and high iodine concentrations), displacement from iso-center, and solvent (tissue background) composition were explored.

METHODS

Quantitative analysis was performed on two clinical scanners, Siemens SOMATOM Force and NAEOTOM Alpha using a multi-energy phantom with plastic inserts mimicking different iodine concentrations and tissue types. The tube configurations in the dual-energy scanner were 80/150Sn kVp and 100/150Sn kVp, while for PC-CT both tube voltages were set to either 120 or 140 kVp with photon-counting energy thresholds set at 20/65 or 20/70 keV. The statistical significance of patient-related parameters in quantitative measurements was examined using ANOVA and pairwise comparison with the posthoc Tukey honest significance test. Scanner bias was assessed in both quantitative tasks for relevant patient-specific parameters.

RESULTS

The accuracy of IQ and VMI in the PC-CT was comparable between standard and low radiation doses (p < 0.01). The patient size and tissue type significantly affect the accuracy of both quantitative imaging tasks in both scanners. The PC-CT scanner outperforms the DE-CT scanner in the IQ task in all cases. Iodine quantification bias in the PC-CT (-0.9 ± 0.15 mg/mL) at low doses in our study was comparable to that of DE-CT (range -2.6 to 1.5 mg/mL, published elsewhere) at a 1.7× higher dose, but the dose reduction severely biased DE-CT (4.72 ± 0.22 mg/mL). The accuracy in Hounsfield units (HU) estimation was comparable for 70 and 100 keV virtual imaging between scanners, but PC-CT was significantly underestimating virtual 40 keV HU values of dense materials in the phantom representing the extremely obese population.

CONCLUSIONS

The statistical analysis of our measurements reveals better IQ at lower radiation doses using new PC-CT. Although VMI performance was mostly comparable between the scanners, the DE-CT scanner quantitatively outperformed PC-CT when estimating HU values in the specific case of very large phantoms and dense materials, benefiting from increased X-ray tube potentials.

Effects of scan parameters on the accuracies of iodine quantification and hounsfield unit values in dual layer dual-energy head and neck computed tomography: A phantom study conducted in a hospital in Japan

INTRODUCTION

No study has investigated scan parameters in head and neck dual layer dual-energy computed tomography (DL-DECT). This study aimed to select the appropriate scan parameters in head and neck imaging by evaluating the scan parameter effects on the accuracies of CT numbers and conduct iodine quantification in DL-DECT.

METHODS

A multi-energy phantom was scanned using a dual layer CT (DLCT) scanner. Reference materials of iodine, blood, calcium, and adipose were used. A helical scan was performed by using reference and several protocols. Iodine density and virtual monochromatic images (VMIs) at the energy of 50, 70, and 100 keV were reconstructed. The iodine concentrations and CT numbers in each protocol were measured. Moreover, the absolute percentage errors (APEs) of iodine quantifications and CT numbers (reference vs. each protocol) were compared. Equivalence was observed when APEs between reference and each protocol was within 5%. Statistical analysis was performed using appropriate software.

RESULTS

The APEs between the high-tube-voltage and reference protocol were 23.7, 14.0, 8.8, and 8.1% for iodine reference materials with concentrations equal to 2, 5, 10, and 15 mg/ml, respectively. At 50 keV, APEs between the high-tube-voltage and reference protocols were greater than 5% except for calcium and adipose. At 100 keV, APEs between the high-tube-voltage and reference protocols were greater than 5% except for blood and calcium.

CONCLUSIONS

The high-tube-voltage protocol improved the accuracies of the measurement for iodine quantification and CT numbers. Additionally, the scanning parameters except for tube voltage had no effect on accuracies of iodine quantitation and CT numbers in the DLCT scanner.

IMPLICATIONS FOR PRACTICE

The use of the high-tube-voltage protocol will be recommended for more accurate material decomposition in head and neck DL-DECT.

Virtual monochromatic images of dual-energy CT as an alternative to single-energy CT: performance comparison using a detectability index for different acquisition techniques

OBJECTIVES

To investigate the performance of virtual monochromatic (VM) images with the same dose and iodine contrast as those for single-energy (SE) images using five dual-energy (DE) scanners with DE techniques: two generations of fast kV switching (FKS), two generations of dual source (DS), and one split filter (SF).

METHODS

A water-bath phantom with a diameter of 300 mm, which contains one rod-shaped phantom made of a material equivalent to soft-tissue and two rod-shaped phantoms made of diluted iodine (2 and 12 mg/mL), was scanned using both SE (120, 100, and 80 kV) and DE techniques with the same CT dose index in each scanner. The VM energy at which the CT number of the iodine rod is closest to that of each SE tube voltage was determined as the equivalent energy (Eeq). A detectability index (d') was calculated from the noise power spectrum, the task transfer functions, and a task function corresponding to each rod. The percentage of the d' value of the VM image to that of the corresponding SE image was calculated for performance comparison.

RESULTS

The average percentages of d' of FKS1, FKS2, DS1, DS2, and SF were 84.6%, 96.2%, 94.3%, 107%, and 104% for 120 kV-Eeq; 75.9%, 91.2%, 88.2%, 99.2%, and 82.6% for 100 kV-Eeq; 71.6%, 88.9%, 82.6%, 85.2%, and 62.3% for 80 kV-Eeq, respectively.

CONCLUSION

The performance of VM images was on the whole inferior to that of SE images especially at low equivalent energy levels, depending on the DE techniques and their generations.

KEY POINTS

• This study evaluated the performance of VM images with the same dose and iodine contrast as those for SE images using five DE scanners. • The performance of VM images varied with the DE techniques and their generations and was mostly inferior at low equivalent energy levels. • The results highlight the importance of distribution of available dose over the two energy levels and spectral separation for the performance improvement of VM images.

Physiological iodine uptake of the spine's bone marrow in dual-energy computed tomography - using artificial intelligence to define reference values based on 678 CT examinations of 189 individuals

Purpose

The bone marrow's iodine uptake in dual-energy CT (DECT) is elevated in malignant disease. We aimed to investigate the physiological range of bone marrow iodine uptake after intravenous contrast application, and examine its dependence on vBMD, iodine blood pool, patient age, and sex.

Method

Retrospective analysis of oncological patients without evidence of metastatic disease. DECT examinations were performed on a spectral detector CT scanner in portal venous contrast phase. The thoracic and lumbar spine were segmented by a pre-trained neural network, obtaining volumetric iodine concentration data [mg/ml]. vBMD was assessed using a phantomless, CE-certified software [mg/cm3]. The iodine blood pool was estimated by ROI-based measurements in the great abdominal vessels. A multivariate regression model was fit with the dependent variable "median bone marrow iodine uptake". Standardized regression coefficients (β) were calculated to assess the impact of each covariate.

Results

678 consecutive DECT exams of 189 individuals (93 female, age 61.4 ± 16.0 years) were evaluated. AI-based segmentation provided volumetric data of 97.9% of the included vertebrae (n=11,286). The 95^th percentile of bone marrow iodine uptake, as a surrogate for the upper margin of the physiological distribution, ranged between 4.7-6.4 mg/ml. vBMD (p <0.001, mean β=0.50) and portal vein iodine blood pool (p <0.001, mean β=0.43) mediated the strongest impact. Based thereon, adjusted reference values were calculated.

Conclusion

The bone marrow iodine uptake demonstrates a distinct profile depending on vBMD, iodine blood pool, patient age, and sex. This study is the first to provide the adjusted reference values.

Detection and size measurements of kidney stones on virtual non-contrast reconstructions derived from dual-layer computed tomography in an ex vivo phantom setup

OBJECTIVES

To systematically investigate the usability of virtual non-contrast reconstructions (VNC) derived from dual-layer CT (DLCT) for detection and size measurements of kidney stones with regards to different degrees of surrounding iodine-induced attenuation and radiation dose.

METHODS

Ninety-two kidney stones of varying size (3-14 mm) and composition were placed in a phantom filled with different contrast media/water mixtures exhibiting specific iodine-induced attenuation (0-1500 HU). DLCT-scans were acquired using CTDI_vol of 2 mGy and 10 mGy. Conventional images (CI) and VNC_0H-1500HU were reconstructed. Reference stone size was determined using a digital caliper (Man-M). Visibility and stone size were assessed. Statistical analysis was performed using the McNemar test, Wilcoxon test, and the coefficient of determination.

RESULTS

All stones were visible on CI_0HU and VNC_200HU. Starting at VNC_{400 HU}, the detection rate decreased with increasing HU and was significantly lower as compared to CI_0HU on VNC_{≥ 600HU} (100.0 vs. 94.0%, p < 0.05). The overall detection rate was higher using 10 mGy as compared to 2 mGy protocol (87.9 vs. 81.8%; p < 0.001). Stone size was significantly overestimated on all VNC compared to Man-M (7.0 ± 3.5 vs. 6.6 ± 2.8 mm, p < 0.001). Again, the 10 mGy protocol tended to show a better correlation with Man-M as compared to 2 mGy protocol (R² = 0.39-0.68 vs. R² = 0.31-0.57).

CONCLUSIONS

Detection and size measurements of kidney stones surrounded by contrast media on VNC are feasible. The detection rate of kidney stones decreases with increasing iodine-induced attenuation and with decreasing radiation dose as well as stone size, while remaining comparable to CI_0HU on VNC _{≤ 400 HU}.

KEY POINTS

• The detection rate of kidney stones on VNC depends on the surrounding iodine-induced attenuation, the used radiation dose, and the stone size. • The detection rate of kidney stones on VNC decreases with greater iodine-induced attenuation and with lower radiation dose, particularly in small stones. • The visibility of kidney stones on VNC _{≤ 400 HU} remains comparable to true-non-contrast scans even when using a low-dose technique.

Liver Iodine Quantification With Photon-Counting Detector CT: Accuracy in an Abdominal Phantom and Feasibility in Patients

RATIONALE AND OBJECTIVES

To compare the accuracy of iodine quantification in liver parenchyma and lesions between dual-source photon-counting detector CT (PCD-CT) and dual-source energy-integrating detector CT (EID-CT) in a phantom and to demonstrate the feasibility of iodine quantification with PCD-CT in liver parenchyma and lesions in patients.

MATERIALS AND METHODS

An anthropomorphic abdominal phantom with a liver insert containing parenchyma and lesions was imaged on a clinical PCD-CT at 120kV and in the dual-energy mode on an EID-CT with kV-combinations of 80/Sn150kV, 90/Sn150kV, and 100/Sn150kV. Three patient sizes were imaged at three different radiation doses (CTDI_vol: 5, 10, 15mGy). Thirty patients with liver cysts, hemangiomas or metastases imaged with PCD-CT were retrospectively included. Iodine maps were reconstructed and iodine concentrations were measured in liver parenchyma and lesions. For the phantom, iodine error was quantified as the absolute difference to the vendor's specifications as reference.

RESULTS

Overall iodine error was 0.33 ± 0.29, 0.34 ± 0.32, 0.39 ± 0.37, 0.35 ± 0.39 mgI/mL for 80/Sn150kV, 90/Sn150kV, 100/Sn150kV of EID-CT, and PCD-CT, respectively, without significant differences between PCD-CT and EID-CT (p > 0.05). Radiation dose did not significantly influence error of PCD-CT (p > 0.05) nor EID-CT (p > 0.05). For both scanners, smaller patient sizes were associated with lower errors (p < 0.05). Iodine concentration and base material attenuation significantly influenced quantification for EID-CT (p < 0.05) but not PCD-CT (p > 0.05). In patients, iodine quantification was feasible in liver parenchyma, cysts, hemangiomas, and metastases.

CONCLUSION

Iodine quantification with PCD-CT is accurate in simulated liver parenchyma and lesions irrespective of radiation dose, iodine concentration, and base attenuation and is feasible in common liver lesions in patients.

Phantom-based quantification of the spectral accuracy in dual-layer spectral CT for pediatric imaging at 100 kVp

Background

To determine the spectral accuracy in detector-based dual-energy CT (DECT) at 100 kVp and wide (8 cm) collimation width for dose levels and object sizes relevant to pediatric imaging.

Methods

A spectral CT phantom containing tissue-equivalent materials and iodine inserts of varying concentrations was scanned on the latest generation detector-based DECT system. Two 3D-printed extension rings were used to mimic varying pediatric patient sizes. Scans were performed at 100 and 120 kVp, 4 and 8 cm collimation widths, and progressively reduced radiation dose levels, down to 0.9 mGy CTDI_vol. Virtual mono-energetic, iodine density, effective atomic number, and electron density results were quantified and compared to their expected values for all acquisition settings and phantom sizes.

Results

DECT scans at 100 kVp provided highly accurate spectral results; however, a size dependence was observed for iodine quantification. For the medium phantom configuration (15 cm diameter), measurement errors in iodine density, effective atomic number, and electron density (ED) were below 0.3 mg/mL, 0.2 and 1.8 %ED_water, respectively. The average accuracy was slightly different from scans at 120 kVp; however, not statistically significant for all configurations. Collimation width had no substantial impact. Spectral results were accurate and reliable for radiation exposures down to 0.9 mGy CTDI_vol.

Conclusions

Detector-based DECT at 100 kVp can provide on-demand or retrospective spectral information with high accuracy even at extremely low doses, thereby making it an attractive solution for pediatric imaging.

Accurate Image Reconstruction in Dual-Energy CT with Limited-Angular-Range Data Using a Two-Step Method

Dual-energy CT (DECT) with scans over limited-angular ranges (LARs) may allow reductions in scan time and radiation dose and avoidance of possible collision between the moving parts of a scanner and the imaged object. The beam-hardening (BH) and LAR effects are two sources of image artifacts in DECT with LAR data. In this work, we investigate a two-step method to correct for both BH and LAR artifacts in order to yield accurate image reconstruction in DECT with LAR data. From low- and high-kVp LAR data in DECT, we first use a data-domain decomposition (DDD) algorithm to obtain LAR basis data with the non-linear BH effect corrected for. We then develop and tailor a directional-total-variation (DTV) algorithm to reconstruct from the LAR basis data obtained basis images with the LAR effect compensated for. Finally, using the basis images reconstructed, we create virtual monochromatic images (VMIs), and estimate physical quantities such as iodine concentrations and effective atomic numbers within the object imaged. We conduct numerical studies using two digital phantoms of different complexity levels and types of structures. LAR data of low- and high-kVp are generated from the phantoms over both single-arc (SA) and two-orthogonal-arc (TOA) LARs ranging from 14∘ to 180∘. Visual inspection and quantitative assessment of VMIs obtained reveal that the two-step method proposed can yield VMIs in which both BH and LAR artifacts are reduced, and estimation accuracy of physical quantities is improved. In addition, concerning SA and TOA scans with the same total LAR, the latter is shown to yield more accurate images and physical quantity estimations than the former. We investigate a two-step method that combines the DDD and DTV algorithms to correct for both BH and LAR artifacts in image reconstruction, yielding accurate VMIs and estimations of physical quantities, from low- and high-kVp LAR data in DECT. The results and knowledge acquired in the work on accurate image reconstruction in LAR DECT may give rise to further understanding and insights into the practical design of LAR scan configurations and reconstruction procedures for DECT applications.

Evaluation of myocardial viability in patients with myocardial ischemia reperfusion injury using the dual-energy CT myocardial blood pool imaging

OBJECTIVES

To evaluate myocardial viability in patients with myocardial ischemia reperfusion injury (MIRI) via dual-energy computed tomography myocardial blood pool imaging (DECT MBPI).

METHODS

Between September 2017 and January 2019, we prospectively recruited 59 patients with acute myocardial infarction (AMI) who developed MIRI after revascularization during invasive coronary angiography (ICA). Then, they received DECT MBPI, SPECT, and PET sequentially within 1 week after the onset of MIRI. A total of 1003 myocardial segments of 59 patients were recruited for this study. The iodine reduction areas and delayed enhancement areas were calculated by cardiac iodine map with SPECT rest myocardial perfusion imaging (MPI) + PET myocardial metabolism imaging (MMI) as reference criteria. The paired sample t-test was used to measure the difference of the myocardial iodine value. Cohen's Kappa analysis was used to test the consistency among different observers. ROC analysis was used to calculate the myocardial viability of DECT MBPI.

RESULTS

ROC showed the AUCs of DECT MBPI iodine value to identify a normal myocardium, an ischemic myocardium, and an infarcted myocardium were 0.957, 0.900, and 0.906 (p < 0.001). The sensitivity, specificity, and accuracy of DECT MBPI in identifying an ischemic myocardium were 87.6%, 89.3%, and 97.9% (p < 0.001). The sensitivity, specificity, and accuracy of DECT MBPI in identifying an infarcted myocardium were 88.9%, 92.2%, and 98.6% (p < 0.001). The cutoff value for DECT MBPI to differentiate between an ischemic and a normal myocardium was 0.84 mg I/mL. The cutoff value for DECT MBPI to differentiate between an infarct and a normal myocardium was 2.01 mg I/mL.

CONCLUSION

DECT MBPI can be used to assess myocardial viability in patients with MIRI with high sensitivity and specificity.

KEY POINTS

• Dual-energy computed tomography myocardial blood pool imaging (DECT MBPI) can evaluate myocardial viability of myocardial ischemia-reperfusion injury (MIRI). • DECT MBPI is a non-invasive and timesaving method for evaluation on myocardial ischemia-reperfusion injury in patients with acute myocardial infarction after coronary intervention.

Multivendor Comparison of Quantification Accuracy of Iodine Concentration and Attenuation Measurements by Dual-Energy CT: A Phantom Study

BACKGROUND. Studies comparing accuracy of quantification by dual-energy CT (DECT) scanners have been limited by small numbers of scanners evaluated and narrow ranges of scanning conditions. OBJECTIVE. The purpose of this study was to compare DECT scanners of varying vendors, technologies, and generations in terms of the accuracy of iodine concentration and attenuation measurements. METHODS. A DECT quality-control phantom was designed to contain seven inserts of varying iodine concentrations as well as soft-tissue and fat inserts. The phantom underwent DECT using 12 different scanner configurations based on seven different DECT scanners from three vendors, with additional variation in tube voltage settings. Technologies included rapid-switching, dual-source, and dual-layer detector DECT. Scans also used three radiation dose levels (10, 20, and 30 mGy) and multiple reconstruction algorithms (filtered back projection, medium and high iterative reconstruction, and deep learning image reconstruction [DLIR]). The mean absolute percentage error (MAPE, representing the absolute ratio of measured error to nominal values on average; lower values indicate better accuracy) was calculated for iodine concentration on iodine maps (MAPE_iodine) and attenuation on virtual monochromatic images (VMIs) using 40, 70, 100, and 140 keV (MAPE_HU). Linear mixed models were used to explore factors affecting quantification accuracy. RESULTS. MAPE_iodine and MAPE_HU ranged 4.62-28.55% and 10.21-26.33%, respectively, across scanner configurations. Accuracies of iodine concentration and attenuation measurements were higher for third-generation rapid-switching and dual-source scanners in comparison with respective earlier-generation scanners and the single evaluated dual-layer detector scanner. Among all configurations, the third-generation rapid-switching scanner using DLIR had the highest quantification accuracy for iodine concentration (MAPE_iodine, 4.62% ± 3.87%) and attenuation (MAPE_HU, 10.21% ± 11.43%). Overall, MAPE_iodine was significantly affected by scanner configuration (F = 450.0, p < .001) and iodine concentration (F = 211.0, p < .001). Overall, MAPE_HU was significantly affected by scanner configuration (F = 233.5, p < .001), radiation dose (F = 14.9, p < .001), VMI energy level (F = 1959.4, p < .001), and material density (F = 411.5, p < .001); radiation dose was significantly associated with MAPE_HU for five of 12 individual configurations. CONCLUSION. Quantification accuracy varied among DECT configurations of varying vendors, platforms, and generations and was affected by acquisition and reconstruction parameters. DLIR may improve quantification accuracy. CLINICAL IMPACT. The interscanner differences in DECT-based measurements should be recognized when quantitative evaluation is performed by DECT in clinical practice.

Value of Dual-Energy CT Perfusion Analysis in Patients with Acute Pancreatitis: Correlation and Discriminative Diagnostic Accuracy with Varying Disease Severity

Background: This study investigates the correlation and discriminative diagnostic accuracy of dual-energy CT (DECT)-derived imaging biomarkers in patients with acute pancreatitis of varying severity. Methods: In this retrospective study, we included 51 patients with acute pancreatitis who had undergone portal-venous phase DECT of the abdomen. Three blinded readers independently performed region-of-interest measurements on DECT images in the inflammatory pancreatic parenchyma. The correlation between modified CT severity index (CTSI) and quantitative imaging parameters was investigated using Pearson correlation coefficient. We performed receiver operator curve (ROC) analysis to assess diagnostic accuracy of the quantitative image parameters for the differentiation between mild/moderate versus severe acute pancreatitis. The optimal discriminative cut-off value to diagnose severe acute pancreatitis was determined using the Youden index. Results: Moderate correlations were found between CTSI scores and iodine density (Pearson’s correlation coefficient r = −0.65; p < 0.001), as well as attenuation (r = −0.55; p < 0.001) and normalized iodine uptake (r = −0.50; p < 0.001). ROC curve analysis revealed highest ability to differentiate mild/moderate from severe acute pancreatitis for iodine density (AUC = 0.86, 95% confidence interval 0.75 to 0.97). An optimal iodine density threshold of ≤1.63 mg/mL was found to indicate severe acute pancreatitis with a sensitivity of 81.3% and specificity of 77.1%. Conclusion: DECT-derived iodine density correlates with acute pancreatitis severity and may facilitate prediction of severe acute pancreatitis.

Utility of dual-layer spectral-detector CT imaging for predicting pathological tumor stages and histologic grades of colorectal adenocarcinoma

Objectives

To assess the utility of Dual-layer spectral-detector CT (DLCT) in predicting the pT stage and histologic grade for colorectal adenocarcinoma (CRAC).

Methods

A total of 131 patients (mean 62.7 ± 12.9 years; 72 female, 59 male) with pathologically confirmed CRAC (35 pT1-2, 61 pT3, and 35 pT4; 32 high grade and 99 low grade), who received dual-phase DLCT were enrolled in this retrospective study. Normalized iodine concentration (NIC), slope of the spectral HU curve (λHU), and effective atomic number (Eff-Z) were measured for each lesion by two radiologists independently. Intraobserver reliability and interobserver agreement were assessed. The above values were compared between three pT-stage and two histologic-grade groups. The correlation between the pT stages and above values were assessed. Receiver operating characteristic (ROC) curves were calculated to evaluate the diagnostic efficacy.

Results

Intra-class correlation coefficients were ranged from 0.856 to 0.983 for all measurements. Eff-Z [7.21(0.09) vs 7.31 (0.10) vs 7.35 (0.19)], NIC_AP [0.11 (0.05) vs 0.15 (0.08) vs 0.15 (0.08)], NIC_VP [0.27 (0.06) vs 0.34 (0.11) vs 0.35 (0.12)], λHU_AP [1.20 (0.45) vs 1.93 (1.18) vs 2.37 (0.91)], and λHU_VP [2.07 (0.68) vs 2.35 (0.62) vs 3.09 (1.07)] were significantly different among pT stage groups (all P<0.001) and exhibited a positive correlation with pT stages (r= 0.503, 0.455, 0.394, 0.512, 0.376, respectively, all P<0.001). Eff-Z [7.37 (0.10) vs 7.28 (0.08)], NIC_AP[0.20 (0.10) vs 0.13 (0.08)], NIC_VP[0.35 (0.07) vs 0.31 (0.11)], and λHU_AP [2.59 (1.11) vs 1.63 (0.75)] in the high-grade group were markedly higher than those in the low-grade group (all P<0.05). For discriminating the advanced- from early-stage CARC, the AUCs of Eff-Z, NIC_AP, NIC_VP, λHU_AP, and λHU_VP were 0.83, 0.80, 0.79, 0.86, and 0.68, respectively (all P<0.001). For discriminating the high- from low-grade CARC, the AUCs of Eff-Z, NIC_AP, NIC_VP, and λHU_AP were 0.81, 0.81, 0.64, and 0.81, respectively (all P<0.05).

Conclusions

The quantitative parameters derived from DLCT may provide new markers for assessing pT stages and histologic differentiation in patients with CRAC.

Application of spectral CT combined with perfusion scan in diagnosis of pancreatic neuroendocrine tumors

Background

Pancreatic neuroendocrine tumors (pNETs) are heterogeneous tumors from the pancreatic neuroendocrine system, and early diagnosis is important for tumor prognosis and treatment. In this study, we aimed to explore the diagnostic value of spectral CT combined with perfusion scanning in improving the detection rate of pNETs.

Methods

From December 2018 to December 2020, 58 patients with clinically suspected pNETs were prospectively enrolled in the study for one-stop spectral CT combined with perfusion scanning, 36 patients were confirmed with pNETs by histopathology. An independent cohort of 30 patients with pNETs who underwent routine pancreatic perfusion scanning in our hospital during the same period were retrospectively collected. The image characters of pNETs versus tumor-free pancreatic parenchymal were examined.

Results

The detection rate of spectral CT combined with perfusion was 83.1–96.2%. CT values of the pNETs lesions under each single energy in the arterial phase were statistically higher than those of the adjacent normal pancreatic parenchyma. IC, WC and NIC, in the arterial phase of pNETs lesion were all statistically higher than those of the adjacent normal pancreatic parenchyma. The perfusion parameters of pNETs including BF, BV and MSI were significantly higher than those in normal parenchyma. The average effective radiation dose during the perfusion combined energy spectrum enhanced scanning process was 17.51 ± 2.18 mSv.

Conclusion

The one-stop spectral CT combined with perfusion scan improves the detection of pNETs according to morphological features, perfusion parameters and energy spectrum characters with a relatively small radiation dose.

Attenuation values on virtual unenhanced images obtained with detector-based dual-energy computed tomography: observations on single- and split-bolus contrast protocols

PURPOSE

To compare virtual unenhanced (VUE) attenuation values and their agreement with true unenhanced (TUE) images in patients who underwent dual-layer detector-based dual-energy computed tomography (dlDECT) with single- vs. split-bolus contrast media protocol.

METHODS

In this HIPAA-compliant, IRB-approved retrospective analysis, a total of 105 patients who underwent nephrographic phase (NP) dlDECT between 07/2018 and 11/2019 were included: 55 patients received single bolus and 50 patients split-bolus examinations. Both scan protocols comprised a TUE and 120-kVp NP acquisition from which VUE images were reconstructed. A radiologist performed ROI-based attenuation measurements of liver parenchyma, main portal vein, aorta, spleen, renal parenchyma, and pelvis on TUE and VUE images. Agreement between TUE and VUE images was determined and compared for both protocols and each anatomic region.

RESULTS

VUE attenuation was significantly higher than TUE attenuation in both cohorts in the liver, portal vein, spleen, and renal parenchyma (p < 0.05), while it was similar in the abdominal aorta in both cohorts (p = 0.05, 0.7522, respectively). VUE attenuation was significantly higher than TUE attenuation in the renal pelvis of the split-bolus cohort (p < 0.05). When comparing VUE images between single- and split-bolus protocols, the renal parenchyma yielded a significantly higher VUE attenuation in the single-bolus cohort (single bolus: 38.8 ± 3.3 HU vs. split bolus: 36.8 ± 3.6 HU; p < 0.05), whereas the split-bolus cohort revealed markedly higher VUE attenuation in the renal pelvis (single bolus: 2.3 ± 10.8 HU vs. split bolus: 92.3 ± 76.8; p < 0.05). Mean intra-patient differences between TUE and VUE images were comparable between single- and split-bolus cohorts (p-range 0.09-0.35) except for the renal parenchyma and pelvis: in the first, the single-bolus cohort yielded a higher VUE attenuation, while in the second, attenuation was significantly higher in the split-bolus cohort (p < 0.05).

CONCLUSION

VUE attenuation overestimated TUE attenuation and differed between split- and single-bolus protocols for the renal parenchyma and pelvis, while all other tissues showed comparable VUE attenuation.

Dual-energy CT lung perfusion in systemic sclerosis: preliminary experience in 101 patients

OBJECTIVES

To investigate lung perfusion in systemic sclerosis (SSc).

METHODS

The study population included 101 patients who underwent dual-energy CT (DECT) in the follow-up of SSc with pulmonary function tests obtained within 2 months. Fifteen patients had right heart catheterization-proven PH.

RESULTS

Thirty-seven patients had no SSc-related lung involvement (Group A), 56 patients had SSc-related interstitial lung disease (Group B) of variable extent (Group B mild: ≤ 10% of lung parenchyma involved: n = 17; Group B moderate: between 11 and 50%: n = 31; Group B severe: > 50%: n = 8), and 8 patients had PVOD/PCH (Group C). Lung perfusion was abnormal in 8 patients in Group A (21.6%), 14 patients in Group B (25%), and 7 patients in Group C (87.5%). In Group A and Group B mild (n = 54), (a) patients with abnormal lung perfusion (n = 14; 26%) had a higher proportion of NYHA III/IV scores of dyspnea (7 [50%] vs 7 [17.5%]; p = 0.031) and a shorter mean walking distance at the 6MWT (397.0 [291.0; 466.0] vs 495.0 [381.0; 549.0]; p = 0.042) but no evidence of difference in the DLCO% predicted (61.0 [53.0; 67.0] vs 68.0 [61.0; 78.0]; p = 0.055) when compared to patients with normal lung perfusion (n = 40; 74%); (b) a negative correlation was found between the iodine concentration in both lungs and the DLCO% predicted but it did not reach statistical significance (r = -0.27; p = 0.059) and no correlation was found with the PAPs (r = 0.16; p = 0.29) and walking distance during the 6MWT (r = -0.029; p = 0.84).

CONCLUSIONS

DECT lung perfusion provides complementary information to standard HRCT scans, depicting perfusion changes in SSc patients with normal or minimally infiltrated lung parenchyma.

KEY POINTS

• In a retrospective observational study of 101 consecutive patients with SSc, dual-energy CT pulmonary angiography was obtained to evaluate lung perfusion. • Lung perfusion was abnormal in 14 out of 54 patients (26%) with no or mild SSc-related lung infiltration. • Patients with abnormal perfusion and no or mild SSc-related lung infiltration had more severe scores of dyspnea and shorter walking distance than patients with similar lung findings and normal perfusion, suggesting the presence of small vessel vasculopathy.

Iodine Images in Dual-energy CT: Detection of Hepatic Steatosis by Quantitative Iodine Concentration Values

Hepatic steatosis is a common condition and an early manifestation of a systemic metabolic syndrome. As of today, there is no broadly accepted method for the diagnosis of hepatic steatosis in contrast-enhanced CT images. This retrospective study evaluates the potential of quantitative iodine values in portal venous phase iodine images in dual-energy CT (DECT) by measuring iodine concentrations in regions of interest (ROI) and analyzing the absolute iodine concentration of the liver parenchyma as well as three different blood-normalized iodine concentrations in a study cohort of 251 patients. An independent two sample t-test (p < 0.05) was used to compare the iodine concentrations of healthy and fatty liver. Diagnostic performance was assessed by ROC (receiver operating characteristic) curve analysis. The results showed significant differences between the average iodine concentration of healthy and fatty liver parenchyma for the absolute and for the blood-normalized iodine concentrations. The study concludes that the iodine uptake of the liver parenchyma is impaired by hepatic steatosis, and that the measurement of iodine concentration can provide a suitable method for the detection of hepatic steatosis in quantitative iodine images. Suitable thresholds of quantitative iodine concentration values for the diagnosis of hepatic steatosis are provided.

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

Dual energy computed tomography (DECT) allows the quantification of specific materials such as iodine contrast agent in human body tissue, potentially providing additional diagnostic data. Yet full diagnostic value can only be achieved if physiological normal values for iodine concentrations are known. We retrospectively evaluated abdominal DECT scans of 105 patients with healthy liver between March and August 2018 (age 17 to 86 years, 43 female and 62 male). The iodine concentrations within ROIs of the liver parenchyma as well as of the abdominal aorta and main portal vein were obtained. We evaluated the absolute iodine concentration and blood-normalized iodine concentrations relating the measured iodine concentration of the liver parenchyma to those of the supplying vessels. The influence of age and gender on the iodine uptake was assessed. The absolute iodine concentration was significantly different for the male and female cohort, but the difference was eliminated by the blood-normalized values. The average blood-normalized iodine concentrations were 2.107 mg/ml (+/- 0.322 mg/ml), 2.125 mg/ml (+/- 0.426 mg/ml) and 2.103 mg/ml (+/- 0.317 mg/ml) for the portal vein normalized, aorta normalized and mixed blood normalized iodine concentrations, respectively. A significant negative correlation between the patients’ age and the iodine concentration was detected only for the blood-normalized values. A physiological range for iodine concentration in portal venous phase contrast enhanced DECT images can be defined for absolute and blood-normalized values. Deviations of blood-normalized iodine concentration values might be a robust biomarker for diagnostic evaluation. Patient age but not the gender influences the blood-normalized iodine concentrations in healthy liver parenchyma.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Significance of the spectral correction of photon counting detector response in material classification from spectral x-ray CT

Purpose: Photon counting imaging detectors (PCD) has paved the way for spectral x-ray computed tomography (spectral CT), which simultaneously measures a sample's linear attenuation coefficient (LAC) at multiple energies. However, cadmium telluride (CdTe)-based PCDs working under high flux suffer from detector effects, such as charge sharing and photon pileup. These effects result in the severe spectral distortions of the measured spectra and significant deviation of the extracted LACs from the reference attenuation curve. We analyze the influence of the spectral distortion correction on material classification performance. Approach: We employ a spectral correction algorithm to reduce the primary spectral distortions. We use a method for material classification that measures system-independent material properties, such as electron density, ρ e , and effective atomic number, Z eff . These parameters are extracted from the LACs using attenuation decomposition and are independent of the scanner specification. The classification performance with the raw and corrected data is tested on different numbers of energy bins and projections and different radiation dose levels. We use experimental data with a broad range of materials in the range of 6 ≤ Z eff ≤ 15 , acquired with a custom laboratory instrument for spectral CT. Results: We show that using the spectral correction leads to an accuracy increase of 1.6 and 3.8 times in estimating ρ e and Z eff , respectively, when the image reconstruction is performed from only 12 projections and the 15 energy bins approach is used. Conclusions: The correction algorithm accurately reconstructs the measured attenuation curve and thus gives better classification performance.

Accuracy of iodine quantification using dual-energy computed tomography with focus on low concentrations

BACKGROUND

Iodine quantification using dual-energy computed tomography (DECT) is helpful in characterizing, and follow-up after treatment of tumors. Some malignant masses, for instance papillary renal cell carcinomas (p-RCC), are hard to differentiate from benign lesions because of very low contrast enhancement. In these cases, iodine concentrations might be very low, and it is therefore important that iodine quantification is reliable even at low concentrations if this technique is used.

PURPOSE

To examine the accuracy of iodine quantification and to determine whether it is also accurate for low iodine concentrations.

MATERIAL AND METHODS

Twenty-six syringes with different iodine concentrations (0-30 mg I/mL) were scanned in a phantom model using a DECT scanner with two different kilovoltage and image reconstruction settings. Iodine concentrations were measured and compared to known concentration. Absolute and relative errors were calculated.

RESULTS

For concentrations of 1 mg I/mL or higher, there was an excellent correlation between true and measured iodine concentrations for all settings (R = 0.999-1.000; P < 0.001). For concentrations <1.0 mg I/mL, the relative error was greater. Absolute and relative errors were smaller using tube voltages of 80/Sn140 kV than 100/Sn140 kV (P < 0.01). Reconstructions using a 3.0-mm slice thickness had less variance between repeated acquisitions versus 0.6 mm (P < 0.001).

CONCLUSION

Iodine quantification using DECT was in general very accurate, but for concentrations < 1.0 mg I/mL the technique was less reliable. Using a tube voltage with larger spectral separation was more accurate and the result was more reproducible using thicker image reconstructions.

Spectral Photon-Counting Computed Tomography: A Review on Technical Principles and Clinical Applications

Photon-counting computed tomography (CT) is a technology that has attracted increasing interest in recent years since, thanks to new-generation detectors, it holds the promise to radically change the clinical use of CT imaging. Photon-counting detectors overcome the major limitations of conventional CT detectors by providing very high spatial resolution without electronic noise, providing a higher contrast-to-noise ratio, and optimizing spectral images. Additionally, photon-counting CT can lead to reduced radiation exposure, reconstruction of higher spatial resolution images, reduction of image artifacts, optimization of the use of contrast agents, and create new opportunities for quantitative imaging. The aim of this review is to briefly explain the technical principles of photon-counting CT and, more extensively, the potential clinical applications of this technology.

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.

Beyond Coronary CT Angiography: CT Fractional Flow Reserve and Perfusion

심장 전산화단층촬영은 비약적인 기술발전과 다양한 연구 결과를 바탕으로 심혈관위험 계층화와 치료 결정을 위한 관상동맥 질환의 진단과 예후 평가성능이 입증되었다. 전산화단층촬영 관상동맥조영술은 폐쇄성 관상동맥 질환에 대한 음성 예측도가 높아서 침습적 혈관조영술의 빈도를 줄일 수 있는 관상동맥 질환 관련 검사의 관문으로 부상했지만, 진단특이도가 상대적으로 낮다. 하지만 심장 전산화단층촬영을 이용한 분획혈류예비력과 심근관류를 분석하여 관상동맥 질환의 혈역학적 유의성을 확인하는 기능적 평가를 통해 그 한계를 극복할 수 있다. 최근에는 이를 보다 객관적이고 재현 가능하도록 인공지능을 접목하는 연구들이 활발히 진행되고 있다. 본 종설에서는 심장 전산화단층촬영의 기능적 영상화 기법들에 대해 알아보고자 한다.

Preoperative assessment of cervical lymph node metastases in patients with papillary thyroid carcinoma: Incremental diagnostic value of dual-energy CT combined with ultrasound

PURPOSE

To determine whether dual-energy CT (DECT) has incremental diagnostic value when combined with ultrasound (US) in the diagnosis of metastatic cervical lymph nodes (LNs) in patients with papillary thyroid carcinoma (PTC).

METHODS

This was a single-center retrospective cohort study of patients diagnosed with PTC between October 2019 and August 2020. US features of LNs to include hyperechogenicity, round shape, microcalcification, cystic component, and homogeneous/peripheral vascularity were considered suggestive of metastasis. The HU of arterial phase (HUarterial) and DECT-derived CT images [contrast media (CM) and areas under the 100 keV monoenergetic curve (AUC100keV)] were measured. Effective atomic numbers (Zeff), iodine concentration (mg/mL), and slope of the HU curve (λHU) were also obtained. The values for metastatic and benign LNs were compared using Student's t-test with false-discovery correction. Logistic regression with areas under the receiver operating characteristic curves (AUCs) were performed for predicting metastatic LNs.

RESULTS

A total of 102 patients were included (49 metastatic and 53 benign LNs; mean age, 46±15 years). Metastatic LNs showed significantly higher values for HUarterial, CM, Zeff, λHU, AUC100keV, and iodine concentration (all, P = 0.001). In logistic regression, the HUarterial demonstrated the highest AUC (0.824; 95% confidence interval [CI], 0.751-0.897), followed by CM HU (0.762; 95% CI, 0.679-0.846). Combination of DECT parameters with US features improved the AUC from 0.890 to 0.941.

CONCLUSION

Compared to US features alone, combination with DECT-derived quantitative parameters improved diagnostic performance in predicting metastatic cervical LNs in patients with PTC.

Value of spectral detector computed tomography to differentiate infected from noninfected thoracoabominal fluid collections

PURPOSE

To investigate the diagnostic value of spectral detector CT (SDCT)-derived virtual non-contrast (VNC), virtual monoenergetic images (VMI) and iodine overlays (IO) for distinguishing infected from noninfected fluid collections (FC) in the chest or abdomen.

METHOD

This retrospective study included 58 patients with venous phase SDCT with 77 FC. For all included FC, microbiological analysis of aspirated fluid served as reference. For quantitative analysis, wall thickness was measured, and (ROI)-based analysis performed within the fluid, the FC's wall (if any) and the aorta. Two radiologists qualitatively evaluated visibility of wall enhancement, diagnostic confidence regarding infection of fluid collection, confidence of CT-guided drainage catheter placement and visibility of anatomical landmarks in conventional images (CI) and VNC, VMI_40keV, IO.

RESULTS

Wall thickness significantly differed between infected (n = 46) and noninfected (n = 31) FC (3.5 ± 1.8 mm vs. 1.4 ± 1.8 mm, AUC = 0.81; p < 0.05). Fluid attenuation and wall enhancement was significantly higher in infected as compared to noninfected FC in all reconstructions (p < 0.05, respectively). Highest AUC regarding A) attenuation in fluid was yielded in CI and VMI_70,80keV (0.75); B) wall enhancement in CI (0.88) followed by iodine concentration (0.86). Contrast-to-noise ratio of wall vs. fluid was highest in VMI_40keV (p < 0.05). All assessed qualitative parameters received significantly higher ratings when using spectral reconstructions vs. CI (p for all <0.05), except for visibility of wall enhancement.

CONCLUSION

Spectral reconstructions improve the assessment of infected from noninfected thoracoabdominal fluid collections and depiction of wall enhancement. Diagnostic performance of the quantitative measurements in spectral reconstructions were comparable with measurements in conventional images.

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.

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.

Spectral CT using a fine grid structure and varying x-ray incidence angle

PURPOSE

Interest in spectral computed tomography (CT) for diagnostics and therapy evaluation has been growing. Data acquisitions with distinct spectral sensitivities provide the ability to discriminate multiple materials, quantitative density estimates, and reduced artifacts due to energy dependencies. We introduce a novel spectral CT concept that includes a fine-pitch grid structure for prefiltration of the x-ray beam.

METHODS

We develop physical models for grid designs and illustrate the basic operating principles wherein small angulations of the incident x rays results significant filtration and spectral shaping of the beam. We fabricate a prototype grid with tungsten lamellae. We compare x-ray spectra induced by this filter as a function of incidence angle in both simulation students and in physical measurements. The grid is also integrated onto a CT test bench where we scanned an iodinated phantom with clinically relevant concentrations (5, 10, 20, and 50 mgI/mL) to demonstrate the ability to perform spectral CT acquisitions and material decomposition.

RESULTS

X-ray spectrometer measurements reveal diverse and controllable spectral shaping with small angle changes that are in agreement with simulation studies. Critical angles where the characteristics of the induced spectrum changes dramatically are identified. Reconstructions of projection data for two angulations separated by 2° was reconstructed and material decomposition into iodine and water images shows good agreement with the known iodine concentrations.

CONCLUSIONS

This work demonstrates the feasibility of the grid-based approach to enable spectral CT data acquisitions and accurate material decompositions. On-going and future studies will investigate the potential of this novel concept as a relatively simple upgrade to standard energy-integrating CT.

High-resolution model-based material decomposition in dual-layer flat-panel CBCT

PURPOSE

Spectral CT uses energy-dependent measurements that enable material discrimination in addition to reconstruction of structural information. Flat-panel detectors (FPDs) have been widely used in dedicated and interventional systems to deliver high spatial resolution, volumetric cone-beam CT (CBCT) in compact and OR-friendly designs. In this work, we derive a model-based method that facilitates high-resolution material decomposition in a spectral CBCT system equipped with a prototype dual-layer FPD. Through high-fidelity modeling of multilayer detector, we seek to avoid resolution loss that is present in more traditional processing and decomposition approaches.

METHOD

A physical model for spectral measurements in dual-layer flat-panel CBCT is developed including layer-dependent differences in system geometry, spectral sensitivities, and detector blur (e.g., due to varied scintillator thicknesses). This forward model is integrated into a model-based material decomposition (MBMD) method based on minimization of a penalized weighted least-squared (PWLS) objective function. The noise and resolution performance of this approach was compared with traditional projection-domain decomposition (PDD) and image-domain decomposition (IDD) approaches as well as one-step MBMD with lower-fidelity models that use approximated geometry, projection interpolation, or an idealized system geometry without system blur model. Physical studies using high-resolution three-dimensional (3D)-printed water-iodine phantoms were conducted to demonstrate the high-resolution imaging performance of the compared decomposition methods in iodine basis images and synthetic monoenergetic images.

RESULTS

Physical experiments demonstrate that the MBMD methods incorporating an accurate geometry model can yield higher spatial resolution iodine basis images and synthetic monoenergetic images than PDD and IDD results at the same noise level. MBMD with blur modeling can further improve the spatial-resolution compared with the decomposition results obtained with IDD, PDD, and MBMD methods with lower-fidelity models. Using the MBMD without or with blur model can increase the absolute modulation at 1.75 lp/mm by 10% and 22% compared with IDD at the same noise level.

CONCLUSION

The proposed model-based material decomposition method for a dual-layer flat-panel CBCT system has demonstrated an ability to extend high-resolution performance through sophisticated detector modeling including the layer-dependent blur. The proposed work has the potential to not only facilitate high-resolution spectral CT in interventional and dedicated CBCT systems, but may also provide the opportunity to evaluate different flat-panel design trade-offs including multilayer FPDs with mismatched geometries, scintillator thicknesses, and spectral sensitivities.

CT Assessment of Myocardial Perfusion and Fractional Flow Reserve in Coronary Artery Disease: A Review of Current Clinical Evidence and Recent Developments

Coronary computed tomography angiography (CCTA) is routinely used for anatomical assessment of coronary artery disease (CAD). However, invasive measurement of fractional flow reserve (FFR) is the current gold standard for the diagnosis of hemodynamically significant CAD. CT-derived FFRCT and CT perfusion are two emerging techniques that can provide a functional assessment of CAD for risk stratification and clinical decision making. Several clinical studies have shown that the diagnostic performance of concomitant CCTA and functional CT assessment for detecting hemodynamically significant CAD is at least non-inferior to that of other routinely used imaging modalities. This article aims to review the current clinical evidence and recent developments in functional CT techniques.