Iodine Maps Research Articles

Dual-energy CT late arterial phase iodine maps for the diagnosis of acute non-occlusive mesenteric ischemia.

To evaluate the diagnostic accuracy of dual-energy CT (DECT) iodine maps in comparison to conventional CT series for the assessment of non-occlusive mesenteric ischemia (NOMI). We evaluated data from 142 patients (72 men; 50.7%) who underwent DECT between 2018 and 2022, with surgically confirmed diagnosis of NOMI. One board-certified radiologist performed region of interest (ROI) measurements in bowel segments on late arterial (LA) and portal venous (PV) phase DECT iodine maps as well as LA conventional series, in both ischemic and non-ischemic bowel loops, using surgical reports as reference standard, and in a control group of 97 patients. Intra- and inter-reader agreement with a second board-certified radiologist was also evaluated. Receiver operating characteristic (ROC) curve analysis was performed to calculate the optimal threshold for discriminating ischemic from non-ischemic bowel segments. Subjective image rating of LA and PV iodine maps was performed. DECT-based iodine concentration (IC) measurements showed significant differences in LA phase iodine maps between ischemic (median:0.72; IQR 0.52-0.91mg/mL) and non-ischemic bowel loops (5.16; IQR 3.45-6.31mg/ml) (P <.0001). IC quantification on LA phase revealed an AUC of 0.966 for the assessment of acute bowel ischemia, significantly higher compared to both IC quantification based on PV phase (0.951) and attenuation values evaluated on LA conventional CT series (0.828). Excellent intra-observer and strong inter-observer agreements were observed for the quantification of iodine concentration. Conversely, weak inter-observer agreement was noted for conventional HU assessments. The optimal LA phase-based IC threshold for assessing bowel ischemia was 1.34mg/mL, yielding a sensitivity of 100% and specificity of 96.48%. Iodine maps based on LA phase significantly improve the diagnostic accuracy for the assessment of NOMI compared to conventional CT series and PV phase iodine maps.

Extracellular volume fraction of liver and pancreas using spectral CT in hypertensive patients: A comparative study

BACKGROUND: Besides the direct impact on the cardiovascular system, hypertension is closely associated with organ damage in the kidneys, liver, and pancreas. Chronic liver and pancreatic damage in hypertensive patients may be detectable via imaging. OBJECTIVE: To explore the correlation between hypertension-related indicators and extracellular volume fraction (ECV) of liver and pancreas measured by iodine maps, and to evaluate corresponding clinical value in chronic damage of liver and pancreas in hypertensive patients. METHODS: A prospective study from June to September 2023 included abdominal patients who underwent contrast-enhanced spectral CT. Normal and various grades of hypertensive blood pressure groups were compared. Upper abdominal iodine maps were constructed, and liver and pancreatic ECVs calculated. Kruskal-Wallis and Spearman analyses evaluated ECV differences and correlations with hypertension indicators. RESULTS: In 300 patients, hypertensive groups showed significantly higher liver and pancreatic ECV than the normotensive group, with ECV rising alongside hypertension severity. ECVliver displayed a stronger correlation with hypertension stages compared to ECVpancreas. Regression analysis identified hypertension severity as an independent predictor for increased ECV. CONCLUSIONS: ECVliver and ECVpancreas positively correlates with hypertension indicators and serves as a potential clinical marker for chronic organ damage due to hypertension, with ECVliver being more strongly associated than ECVpancreas.

Simultaneous high-pitch multi-energy CT pulmonary angiography using a dual-source photon-counting-detector CT: A phantom experiment.

A dual-source CT system can be operated in a high-pitch helical mode to provide a temporal resolution of 66ms, which reduces motion artifacts in CT pulmonary angiography (CTPA). It can also be operated in a multi-energy (ME) mode to provide iodine maps, beneficial in the evaluation of pulmonary embolism (PE). No energy-integrating detector (EID) CT can perform simultaneous ME and high-pitch acquisition. This phantom study aimed to evaluate the ability of a photon-counting-detector (PCD) CT to perform simultaneous high-pitch and ME imaging for CTPA. A motion phantom was used to mimic the respiratory motion. Two tubes filled with iodine with intravascular thrombus mimicked by injecting glue within the tubes were placed along with 5, 10, and 15mg/mL iodine samples, on a motion phantom at 20 and 30 revolutions per minute. Separate high-pitch and ME EID-CT scans and a single high-pitch ME PCD scan were acquired and virtual monoenergetic images and iodine maps reconstructed. Percent thrombus occlusion was measured and compared between static and moving images. When there was motion, EID-CT ME suffered from significant motion artifacts. The measured iodine concentrations with PCD-CT in high-pitch ME were more stable when there was a motion, with a lower standard deviation than EID-CT in ME mode. The estimated percent thrombus occlusion dropped significantly with applied motion on EID-CT, while PCD-CT high-pitch ME mode showed good agreement between measurements on static or moving images. PCD-CT with combined ME and high-pitch mode facilitates simultaneous accurate iodine quantification and assessment of intravascular occlusion.

Photon-counting detector CT (PCD-CT) generated iodine maps to characterize parenchymal lung disease: A feasibility study

BackgroundWith photon-counting CT, spectral imaging is always available, and iodine maps with high spatial and spectral resolution can be generated. ObjectivesThe aim of this study was to investigate whether iodine uptake in different parenchymal patterns can be used to characterise parenchymal disease with increased lung attenuation. Methods325 patients were scanned with a photon-counting CT using four scan protocols, all with lung parenchymal contrast. Lesions were classified into three basic patterns: consolidation, ground-glass opacities (GGO), and reticular pattern. Lesion classification was performed by 2 of 3 radiologists who were blinded to the diagnosis. Classification was performed twice using a 5-point Likert scale (with and without iodine maps). In case of disagreement, a third reader was consulted, and the decision was made by consensus. Results206 lesions were found with a confirmed diagnosis (83 consolidations, 72 GGO, and 51 reticular). Diagnostic confidence improved when iodine maps were included in the evaluation. The mean Likert score increased significantly for all three basic patterns (consolidations: 3.3 vs. 3.9, GGO: 3.4 vs. 4.1, and reticular: 3.6 vs. 4.4, p < 0.001). However, the score for GGO and reticular pattern was downgraded in three and one cases, respectively. The downgrading occurred for morphologically uncertain GGO findings (3) and atelectasis (1) with inhomogeneous iodine uptake. In 29 lesions, the classification was changed when the iodine maps were included in the evaluation. ConclusionIncluding iodine maps adds contrast uptake information and improves the diagnostic confidence of radiologists in the characterization of parenchymal pathologies. Clinical ImpactIodine maps have the potential to provide complementary information for the interpretation of lung opacities with overlapping morphology.

Optimal Spectral Performance on Pediatric Photon-Counting CT: Investigating Phantom-Based Size-Dependent kV Selection for Spectral Body Imaging.

The comprehensive evaluation of kV selection on photon-counting computed tomography (PCCT) has yet to be performed. The aim of the study is to evaluate and determine the optimal kV options for variable pediatric body sizes on the PCCT unit. In this study, 4 phantoms of variable sizes were utilized to represent abdomens of newborn, 5-year-old, 10-year-old, and adult-sized pediatric patients. One solid water and 4 solid iodine inserts with known concentrations (2, 5, 10, and 15 mg I/mL) were inserted into phantoms. Each phantom setting was scanned on a PCCT system (Siemens Alpha) with 4 kV options (70 and 90 kV under Quantum Mode, 120 and 140 kV under QuantumPlus Mode) and clinical dual-source (3.0 pitch) protocol. For each phantom setting, radiation dose (CTDIvol) was determined by clinical dose settings and matched for all kV acquisitions. Sixty percent clinical dose images were also acquired. Reconstruction was matched across all acquisitions using Qr40 kernel and QIR level 3. Virtual monoenergetic images (VMIs) between 40 and 80 keV with 10 keV interval were generated on the scanner. Low-energy and high-energy images were reconstructed from each scan and subsequently used to generate an iodine map (IM) using an image-based 2-material decomposition method. Image noise of VMIs from each kV acquisition was calculated and compared between kV options. Absolute percent error (APE) of iodine CT number accuracy in VMIs was calculated and compared. Root mean square error (RMSE) and bias of iodine quantification from IMs were compared across kV options. At the newborn size and 50 keV VMI, noise is lower at low kV acquisitions (70 kV: 10.5 HU, 90 kV: 10.4 HU), compared with high kV acquisitions (120 kV: 13.8 HU, 140 kV: 13.9 HU). At the newborn size and 70 keV VMI, the image noise from different kV options is comparable (9.4 HU for 70 kV, 8.9 HU for 90 kV, 9.7 HU for 120 kV, 10.2 HU for 140 kV). For APE of VMI, high kV (120 or 140 kV) performed overall better than low kV (70 or 90 kV). At the 5-year-old size, APE of 90 kV (median: 3.6%) is significantly higher (P < 0.001, Kruskal-Wallis rank sum test with Bonferroni correction) than 140 kV (median: 1.6%). At adult size, APE of 70 kV (median: 18.0%) is significantly higher (P < 0.0001, Kruskal-Wallis rank sum test with Bonferroni correction) than 120 kV (median: 1.4%) or 140 kV (median: 0.8%). The high kV also demonstrated lower RMSE and bias than the low kV across all controlled conditions. At 10-year-old size, RMSE and bias of 120 kV are 1.4 and 0.2 mg I/mL, whereas those from 70 kV are 1.9 and 0.8 mg I/mL. The high kV options (120 or 140 kV) on the PCCT unit demonstrated overall better performance than the low kV options (70 or 90 kV), in terms of image quality of VMIs and IMs. Our results recommend the use of high kV for general body imaging on the PCCT.

Impact of multi-parameter images obtained from dual-energy CT on radiomics to predict pathological grading of bladder urothelial carcinoma.

To investigate the effect of radiomics models obtained from dual-energy CT (DECT) material decomposition images and virtual monoenergetic images (VMIs) in predicting the pathological grading of bladder urothelial carcinoma (BUC). A retrospective analysis of preoperative DECT examination was conducted on 112 patients diagnosed with BUC. This cohort included 76 cases of high-grade urothelial carcinoma and 36 cases of low-grade urothelial carcinoma. DECT can provide material decomposition images of venous phase Iodine maps and Water maps based on the differences in attenuation of substances, as well as VMIs at 40 to 140keV (interval 10keV). A total of 13 image sets were obtained, and radiomics features were extracted and analyzed from each set to achieve preoperative prediction of BUC. The best features related to BUC were identified by recursive feature elimination (RFE), the Minimum Redundancy Maximum Relevance (mRMR), and the Least Absolute Shrinkage and Selection Operator (LASSO) in order. A five-fold cross-validation method was used to divide the samples into training and testing sets, and models for pathological prediction of BUC grading were constructed by a random forest (RF) classifier. Receiver operating curves (ROC) were plotted to evaluate the performance of 13 models obtained from each image set. Despite the notable differences in the best radiomics features chosen from each image set, all the features selected from 40 to 100keV VMIs included the Dependence Variance of the GLDM feature set. There were no statistically significant differences in the area under the curve (AUC) between the training set and the testing set for all 13 models. In the testing set, the AUCs of the models established through 40keV to 140keV (interval of 10keV) image sets were 0.895, 0.874, 0.855, 0.889, 0.841, 0.868, 0.852, 0.847, 0.889, 0.887 and 0.863 respectively. The AUCs for the models established using the Iodine maps and Water maps image sets were 0.873 and 0.852, respectively. Despite the differences in the selected radiomic features from DECT multi-parameter images, the performance of radiomics models in predicting the pathological grading of BUC was not affected by the variations in the types of images used for model training.

Differentiation of intrathoracic lymph node histopathology by volumetric dual energy CT radiomic analysis

PurposeTo determine the performance of volumetric dual energy low kV and iodine radiomic features for the differentiation of intrathoracic lymph node histopathology, and influence of contrast protocol. Materials and methodsIntrathoracic lymph nodes with histopathologic correlation (neoplastic, granulomatous sarcoid, benign) within 90 days of DECT chest imaging were volumetrically segmented. 1691 volumetric radiomic features were extracted from iodine maps and low-kV images, totaling 3382 features. Univariate analysis was performed using 2-sample t-test and filtered for false discoveries. Multivariable analysis was used to compute AUCs for lymph node classification tasks. Results129 lymph nodes from 72 individuals (mean age 61 ± 15 years) were included, 52 neoplastic, 51 benign, and 26 granulomatous-sarcoid. Among all contrast enhanced DECT protocol exams (routine, PE and CTA), univariable analysis demonstrated no significant differences in iodine and low kV features between neoplastic and non-neoplastic lymph nodes; in the subset of neoplastic versus benign lymph nodes with routine DECT protocol, 199 features differed (p = .01- < 0.05).Multivariable analysis using both iodine and low kV features yielded AUCs >0.8 for differentiating neoplastic from non-neoplastic lymph nodes (AUC 0.86), including subsets of neoplastic from granulomatous (AUC 0.86) and neoplastic from benign (AUC 0.9) lymph nodes, among all contrast protocols. ConclusionsVolumetric DECT radiomic features demonstrate strong collective performance in differentiation of neoplastic from non-neoplastic intrathoracic lymph nodes, and are influenced by contrast protocol.

Dual-Energy Computed Tomography Iodine Maps: Application in the Diagnosis of Periprosthetic Joint Infection in Total Hip Arthroplasty

BackgroundThe challenge of early and rapid diagnosis of periprosthetic joint infection (PJI) remains important. This study aimed to assess the efficacy of dual-energy computed tomography (DECT) iodine maps for diagnosing PJI in total hip arthroplasty. MethodsWe prospectively enrolled 68 patients who had postoperative joint pain after hip arthroplasty. All patients underwent preoperative DECT iodine imaging to quantify iodine concentration (IC) in periprosthetic tissues during arterial and venous phases. The diagnostic efficacy of DECT iodine maps was evaluated by constructing receiver operating characteristic curves according to the Musculoskeletal Infection Society criteria. ResultsCompared with erythrocyte sedimentation rate (area under the curve [AUC] = 0.837), polymorphonuclear cell percentage (AUC = 0.703), and C-reactive protein (AUC = 0.837), periprosthetic tissue venous-phase IC (AUC = 0.970) and arterial-phase IC (AUC = 0.964) exhibited outstanding discriminative capability between PJI and aseptic failure. The PJI cut-off point was venous IC = 1.225 mg/mL, with a sensitivity of 92.31% and specificity of 90.48%; for arterial IC = 1.065 mg/mL, the sensitivity was 96.15% and specificity was 90.70%. ConclusionsThis study demonstrates the great potential of DECT iodine maps for the diagnosis of PJI around hip arthroplasty, which helps to differentiate between periprosthetic infection and aseptic failure after hip arthroplasty.

Three-dimensional iodine mapping quantified by dual-energy CT for predicting programmed death-ligand 1 expression in invasive pulmonary adenocarcinoma

We examined the association between texture features using three-dimensional (3D) io-dine density histogram on delayed phase of dual-energy CT (DECT) and expression of programmed death-ligand 1 (PD-L1) using immunostaining methods in non-small cell lung cancer. Consecutive 37 patients were scanned by DECT. Unenhanced and enhanced (3 min delay) images were obtained. 3D texture analysis was performed for each nodule to obtain 7 features (max, min, median, mean, standard deviation, skewness, and kurtosis) from iodine density mapping and extracellular volume (ECV). A pathologist evaluated a tumor proportion score (TPS, %) using PD-L1 immunostaining: PD-L1 high (TPS ≥ 50%) and low or negative expression (TPS < 50%). Associations between PD-L1 expression and each 8 parameter were evaluated using logistic regression analysis. The multivariate logistic regression analysis revealed that skewness and ECV were independent indicators associated with high PD-L1 expression (skewness: odds ratio [OR] 7.1 [95% CI 1.1, 45.6], p = 0.039; ECV: OR 6.6 [95% CI 1.1, 38.4], p = 0.037). In the receiver-operating characteristic analysis, the area under the curve of the combination of skewness and ECV was 0.83 (95% CI 0.67, 0.93) with sensitivity of 64% and specificity of 96%. Skewness from 3D iodine density histogram and ECV on dual energy CT were significant factors for predicting PD-L1 expression.

Dual-Energy CTA Iodine Map Reconstructions Improve Visualization of Residual Cerebral Aneurysms following Endovascular Coiling.

Material-specific reconstructions of dual-energy CTA (DECTA) can highlight iodinated contrast, subtract predefined materials, and reduce metal artifact. We present a technique to improve detection of residual aneurysms after endovascular coiling by which iodine-map DECTA (IM-DECTA) reconstructions subtract platinum coil artifacts in MIP images (MIP IM-DECTA) and assess if IM-DECTA offers improved detection over conventional CTA (CCTA) or monoenergetic DECTA. We included consecutive patients who underwent endovascular aneurysm coiling with follow-up DECTA and DSA within 24 months. DECTA was performed at 80- and 150-kVp tube voltages on a rapid kV-switching single-source Revolution scanner. CCTA and IM-DECTA series were reconstructed. Reference-standard DSA was compared with CCTA, 50- and 70-keV virtual monochromatic DECTA, IM-DECTA, and MIP IM-DECTA. Blinded to DSA data, cross-section images were reviewed in consensus by 3 neurointerventionalists for residual aneurysms and assigned modified Raymond-Roy classifications (mRRC). Sensitivity, specificity, and accuracy of each series is reported relative to DSA, and single-factor ANOVA and pair-wise Spearman correlation coefficients compared the accuracy of each series. Readers provided ROI measurements of HU deviation adjacent to the aneurysm neck for quantitative noise assessment and qualitatively scored each series on a 3-point Likert-style scale ranging from uninterpretable to excellent image quality. Twenty-one patients with 25 coiled aneurysms were included. Mean time from DECTA to DSA was 286 ± 212 days. IM-DECTA and MIP IM-DECTA most sensitively (89% and 90%) and specifically (93% and 93%) detected residual aneurysms relative to CCTA (6% and 86%). Relative to DSA, IM-DECTA and MIP IM-DECTA most accurately detected (92% versus 28% for CCTA) and classified residual aneurysms by mRRC (ρC-CTA = -0.08; ρIM = 0.50; ρIM-MIP = 0.55; P < .001). Reader consensus reported the best image quality at the aneurysm neck with IM-DECTA and MIP IM-DECTA, with 56% of CCTAs considered uninterpretable versus 0% of IM-DECTAs, and image noise was significantly lower for IM-DECTA (27.9 ± 3.6 HU) or MIP IM-DECTA (26.8 ± 3.5 HU) than CCTA (103.2 ± 13.3 HU; P < .001). MIP IM-DECTA can subtract coil mass artifact and is more sensitive and specific than CCTA for the detection of residual aneurysms after endovascular coiling.

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.

Radiomics analysis of dual-layer spectral-detector CT-derived iodine maps for predicting tumor deposits in colorectal cancer.

To investigate the value of radiomics analysis of dual-layer spectral-detector computed tomography (DLSCT)-derived iodine maps for predicting tumor deposits (TDs) preoperatively in patients with colorectal cancer (CRC). A total of 264 pathologically confirmed CRC patients (TDs + (n = 80); TDs - (n = 184)) who underwent preoperative DLSCT from two hospitals were retrospectively enrolled, and divided into training (n = 124), testing (n = 54), and external validation cohort (n = 86). Conventional CT features and iodine concentration (IC) were analyzed and measured. Radiomics features were derived from venous phase iodine maps from DLSCT. The least absolute shrinkage and selection operator (LASSO) was performed for feature selection. Finally, a support vector machine (SVM) algorithm was employed to develop clinical, radiomics, and combined models based on the most valuable clinical parameters and radiomics features. Area under receiver operating characteristic curve (AUC), calibration curves, and decision curve analysis were used to evaluate the model's efficacy. The combined model incorporating the valuable clinical parameters and radiomics features demonstrated excellent performance in predicting TDs in CRC (AUCs of 0.926, 0.881, and 0.887 in the training, testing, and external validation cohorts, respectively), which outperformed the clinical model in the training cohort and external validation cohorts (AUC: 0.839 and 0.695; p: 0.003 and 0.014) and the radiomics model in two cohorts (AUC: 0.922 and 0.792; p: 0.014 and 0.035). Radiomics analysis of DLSCT-derived iodine maps showed excellent predictive efficiency for preoperatively diagnosing TDs in CRC, and could guide clinicians in making individualized treatment strategies. The radiomics model based on DLSCT iodine maps has the potential to aid in the accurate preoperative prediction of TDs in CRC patients, offering valuable guidance for clinical decision-making. Accurately predicting TDs in CRC patients preoperatively based on conventional CT features poses a challenge. The Radiomics model based on DLSCT iodine maps outperformed conventional CT in predicting TDs. The model combing DLSCT iodine maps radiomics features and conventional CT features performed excellently in predicting TDs.

Prediction of tumor regression grade in far-advanced gastric cancer after preoperative immuno-chemotherapy using dual-energy CT-derived extracellular volume fraction.

This study examines the effectiveness of dual-energy CT (DECT) delayed-phase extracellular volume (ECV) fraction in predicting tumor regression grade (TRG) in far-advanced gastric cancer (FAGC) patients receiving preoperative immuno-chemotherapy. A retrospective analysis was performed on far-advanced gastric adenocarcinoma patients treated with preoperative immuno-chemotherapy at our institution from August 2019 to March 2023. Patients were categorized based on their TRG into pathological complete response (pCR) and non-pCR groups. ECV was determined using the delayed-phase iodine maps. In addition, tumor iodine densities and standardized iodine ratios were meticulously analyzed using the triple-phase enhanced iodine maps. Univariate analysis with five-fold cross-validation and Spearman correlation determined DECT parameters and clinical indicators association with pCR. The predictive accuracy of these parameters for pCR was evaluated using a weighted logistic regression model with five-fold cross-validation. Of the 88 patients enrolled (mean age 60.8 ± 11.1 years, 63 males), 21 (23.9%) achieved pCR. Univariate analysis indicated ECV's significant role in differentiating between pCR and non-pCR groups (average p value = 0.021). In the logistic regression model, ECV independently predicted pCR with an average odds ratio of 0.911 (95% confidence interval, 0.798-0.994). The model, incorporating ECV, tumor area, and IDAV (the relative change rate of iodine density from venous phase to arterial phase), showed an average area under curves (AUCs) of 0.780 (0.770-0.791) and 0.766 (0.731-0.800) for the training and validation sets, respectively, in predicting pCR. DECT-derived ECV fraction is a valuable predictor of TRG in FAGC patients undergoing preoperative immuno-chemotherapy. This study demonstrates that DECT-derived extracellular volume fraction is a reliable predictor for pathological complete response in far-advanced gastric cancer patients receiving preoperative immuno-chemotherapy, offering a noninvasive tool for identifying potential treatment beneficiaries.

Use of the Spectral Iodine Map in the Assessment of Chronic Pulmonary Thromboembolism

Use of the Spectral Iodine Map in the Assessment of Chronic Pulmonary Thromboembolism

Deep learning image reconstruction generates thinner slice iodine maps with improved image quality to increase diagnostic acceptance and lesion conspicuity: a prospective study on abdominal dual-energy CT

BackgroundTo assess the improvement of image quality and diagnostic acceptance of thinner slice iodine maps enabled by deep learning image reconstruction (DLIR) in abdominal dual-energy CT (DECT).MethodsThis study prospectively included 104 participants with 136 lesions. Four series of iodine maps were generated based on portal-venous scans of contrast-enhanced abdominal DECT: 5-mm and 1.25-mm using adaptive statistical iterative reconstruction-V (Asir-V) with 50% blending (AV-50), and 1.25-mm using DLIR with medium (DLIR-M), and high strength (DLIR-H). The iodine concentrations (IC) and their standard deviations of nine anatomical sites were measured, and the corresponding coefficient of variations (CV) were calculated. Noise-power-spectrum (NPS) and edge-rise-slope (ERS) were measured. Five radiologists rated image quality in terms of image noise, contrast, sharpness, texture, and small structure visibility, and evaluated overall diagnostic acceptability of images and lesion conspicuity.ResultsThe four reconstructions maintained the IC values unchanged in nine anatomical sites (all p > 0.999). Compared to 1.25-mm AV-50, 1.25-mm DLIR-M and DLIR-H significantly reduced CV values (all p < 0.001) and presented lower noise and noise peak (both p < 0.001). Compared to 5-mm AV-50, 1.25-mm images had higher ERS (all p < 0.001). The difference of the peak and average spatial frequency among the four reconstructions was relatively small but statistically significant (both p < 0.001). The 1.25-mm DLIR-M images were rated higher than the 5-mm and 1.25-mm AV-50 images for diagnostic acceptability and lesion conspicuity (all P < 0.001).ConclusionsDLIR may facilitate the thinner slice thickness iodine maps in abdominal DECT for improvement of image quality, diagnostic acceptability, and lesion conspicuity.

An Image-Based Prior Knowledge-Free Approach for a Multi-Material Decomposition in Photon-Counting Computed Tomography.

Photon-counting CT systems generally allow for acquiring multiple spectral datasets and thus for decomposing CT images into multiple materials. We introduce a prior knowledge-free deterministic material decomposition approach for quantifying three material concentrations on a commercial photon-counting CT system based on a single CT scan. We acquired two phantom measurement series: one to calibrate and one to test the algorithm. For evaluation, we used an anthropomorphic abdominal phantom with inserts of either aqueous iodine solution, aqueous tungsten solution, or water. Material CT numbers were predicted based on a polynomial in the following parameters: Water-equivalent object diameter, object center-to-isocenter distance, voxel-to-isocenter distance, voxel-to-object center distance, and X-ray tube current. The material decomposition was performed as a generalized least-squares estimation. The algorithm provided material maps of iodine, tungsten, and water with average estimation errors of 4% in the contrast agent maps and 1% in the water map with respect to the material concentrations in the inserts. The contrast-to-noise ratio in the iodine and tungsten map was 36% and 16% compared to the noise-minimal threshold image. We were able to decompose four spectral images into iodine, tungsten, and water.

Preoperative prediction of lymphovascular invasion and T-staging of rectal cancer via a dual-energy computed tomography iodine map: a feasibility study.

To investigate the value of dual-energy computed tomography (DECT) in predicting lymphovascular invasion (LVI) and the accuracy of preoperative T-staging of rectal cancer (RC). Forty-nine patients with RC who had not received radiotherapy were enrolled to undergo a DECT scan. All patients underwent surgical tumor resection within 3-5 days after the DECT scan. Preoperative T-staging of RC based on images was performed by experienced radiologists. The normalized iodine concentrations (NIC) of the tumor and the perirectal adipose tissue (PAT) from the arterial phase (AP) and venous phase (VP) were measured using DECT. The tumor LVI and T-staging confirmed by pathology were used as the gold standard for grouping (group A, LVI-; group B, LVI+; group C, T1-2; and group D, T3-4a). The NIC values between two groups were compared using the Mann-Whitney U test, with P < 0.05 indicating a statistically significant difference. The accuracy of NIC in predicting LVI and distinguishing T1-2 RC from T3-4a RC were determined via receiver operating characteristic curve analysis, and the optimal cut-off of NIC was determined using the area under the curve. The tumor NIC values were significantly higher in the LV+ group than in the LVI- group in the VP (0.728 ± 0.031 vs. 0.669 ± 0.034, P < 0.001). The NIC values of PAT were significantly higher in the T3-4a group than in the T1-2 group in both the AP (4.034 ± 0.991 vs. 3.115 ± 0.581, P < 0.05) and the VP (5.481 ± 1.054 vs. 3.450 ± 0.980, P < 0.001). The accuracy of using NIC values to distinguish between the LVI+ group and the LVI- group and to diagnose the T3-4a group were 85.7% and 89.8%, respectively. However, there was no statistically significant difference between the NIC value in the LVI+ group and in the LVI- group in the AP. There was also no statistical difference in the tumor NIC value between the T1-2 group and the T3-4a group. The tumor and PAT NIC are valuable indicators in RC that can preoperatively predict LVI and improve the accuracy of preoperative RC T-staging. The use of DECT improves the T-staging and LVI prediction of RC, which is helpful in guiding the clinical selection of appropriate treatment modalities and improving prognostic outcomes.

Photon-Counting Detector CT Iodine Maps for Pituitary Adenoma in Cushing Disease.

Photon-Counting Detector CT Iodine Maps for Pituitary Adenoma in Cushing Disease.

Ultrahigh-Resolution K-Edge Imaging of Coronary Arteries With Prototype Deep-Silicon Photon-Counting CT: Initial Results in Phantoms.

Background Photon-counting CT (PCCT) represents a recent advancement in CT, offering improved spatial resolution and spectral separability. By using multiple adjustable energy bins, PCCT enables K-edge imaging, allowing mixed contrast agent distinction. Deep-silicon is a new type of photon-counting detector with different characteristics compared with cadmium photon-counting detectors. Purpose To evaluate the performance of a prototype deep-Si PCCT scanner and compare it with that of a state-of-the-art dual-energy energy-integrating detector (EID) scanner in imaging coronary artery plaques enhanced with iodine and K-edge contrast agents. Materials and Methods A series of 10 three-dimensional-printed inserts (diameter, 3.5 mm) was prepared, and materials mimicking soft and calcified plaques were added to simulate stenosed coronary arteries. Inserts filled with an iodine- or gadolinium-based contrast agent (GBCA) were scanned. Virtual monoenergetic images (VMIs) and iodine maps were generated using two- and eight-energy bin data from EID CT and PCCT, respectively. Gadolinium maps were calculated for PCCT. The CT numbers of VMIs and iodine maps were compared. Spatial resolution and blooming artifacts were compared on the 70-keV VMIs in plaque-free and calcified coronary arteries. Results No evidence of a significant difference in the CT number of 70-keV images was found except in inserts containing GBCAs. In the absence of a GBCA, excellent (r > 0.99) agreement for iodine was found. PCCT could quantify the GBCA within 0.2 mg Gd/mL ± 0.8 accuracy of the ground truth, whereas EID CT failed to detect the GBCA. Lumen measurements were more accurate for PCCT than for EID CT, with mean errors of 167 versus 442 µm (P < .001) compared with the 3.5-mm ground truth. Conclusion Deep-Si PCCT demonstrated good accuracy in iodine quantification and could accurately decompose mixtures of two contrast agents. Its improved spatial resolution resulted in sharper images with blooming artifacts reduced by 50% compared with a state-of-the-art dual-energy EID CT scanner. © RSNA, 2024.

Differentiation Between Abscesses and Unnecessary Intervention Fluid After Pancreas Surgery Using Dual-Energy Computed Tomography.

This study aimed to evaluate the potential of dual-energy computed tomography (CT) to distinguish postoperative ascites, pancreatic fistula, and abscesses. Patients who underwent biliary and pancreatic surgery performed at our institution between June 2021 and February 2022 were included in the study. Postoperative body fluid samples were collected through a drain or percutaneous drainage. These samples were set in a phantom, and imaging data were obtained using dual-energy CT. Image analysis was performed to obtain CT values at each energy in virtual monoenergetic images (VMIs), effective atomic number, iodine map, and virtual non-contrast (VNC) images. VMIs were calculated from 80 and 140 kVp tube data at 10 kV each from 40-140 kV. Additionally, the effective atomic number, iodine map, and VNC images were reconstructed from the material decomposition process using water and iodine as the base material pair. In this study, 25 patients (eight with abscess and 17 with ascites) were included. No significant association was observed between the presence or absence of abscess and malignancy or surgical procedure. The intervention was performed in six of the eight patients with abscesses. In contrast, five of the 17 patients with postoperative ascites required intervention. A significant relationship was observed between the intervention and the presence of an abscess. Significant differences in C-reactive protein values and the incidence of fever were observed between the groups. Only VNC showed a significant difference between the groups. VNC using dual-energy CT could differentiate abscesses from postoperative fluid.