Analysis of the iodine distribution map in patients with diagnosis of pulmonary embolism: Initial results

Objectives: Analysing the iodine map distribution in patients with pulmonary embolism diagnosis by Dual Energy Computed Tomography. Materials and methods: Twenty-four images of pulmonary angiotomography by dual energy computed tomography were used to determinate the presence of pulmonary thrombi and identify the perfusion defects (PDs) in the Iodine Maps. Moreover, the iodine density (mg/ml) were measured in normal lung parenchyma and lung parenchyma with PDs areas. The documentary analysis was used thought the data collection sheet and the Likert scale questionnaire. The statistic software SPSS v.25 was used. Results: Thirty-four thrombi were found (21 occlusive and 13 partials occlusive) at monochromatic images. Forty-one perfusion defects (PD) were found at Iodine Maps, these have multiple origins: pulmonary thrombi (69.23%), artifacts (17.95%) and other alterations (12.82%). Furthermore, two new thrombi (5.56%) were identified, both were occlusive and segmental level. Mean Iodine density showed statistically significant differences among normal lung parenchyma (1.65 ± 0.66 mg/ml; [0.77-2.79 mg/ ml]) and parenchyma with PD areas (0.51 ± 0.26 mg/ml; [0.12-1.02 mg/ml])(p=0.000). Mean iodine density also had statistically significant differences between parenchyma with occlusive PD and partial occlusive PD (p=0.000). Iodine Map diagnostic quality was excellent (54.17%), good (33.33%), moderate (12.50%). Conclusion: The Iodine distribution Map offers a benefit greater than 5% in the diagnosis of pulmonary embolism by Dual-Energy Computed Tomography.

Efficiency of dual-energy computed tomography enterography in the diagnosis of Crohn’s disease

Background This retrospective study aimed to investigate the usefulness of the optimized kiloelectron volt (keV) for virtual monoenergetic imaging (VMI) combined with iodine map in dual-energy computed tomography enterography (DECTE) in the diagnosis of Crohn’s disease (CD). Methods Seventy-two patients (mean age: 41.89 ± 17.28 years) with negative computed tomography enterography (CTE) were enrolled for investigating the optimized VMI keV in DECTE by comparing subjective and objective parameters of VMIs that were reconstructed from 40 to 90 keV. Moreover, 68 patients (38.27 ± 15.10 years; 35 normal and 33 CD) were included for evaluating the diagnostic efficacy of DECTE iodine map at the optimized VMI energy level and routine CTE for CD and active CD. Statistical analysis for all data was conducted. Results Objective and subjective imaging evaluations showed the best results at 60 keV for VMIs. The CT values of the normal group, active subgroup, and CD group during the small intestinal phase at routine 120 kVp or 60 keV VMI had significant differences. The diagnostic efficacy of an iodine map was the best when NIC = 4% or fat value = 45.8% for CD, whereas NIC < 0.35 or the fat value < 0.38 for active CD. The combined routine CTE and optimized VMI improved the diagnostic efficacy (P < 0.001). Conclusions VMI at 60 keV provided the best imaging quality on DECTE. NIC and fat value provided important basis for active CD evaluation. Routine CTE combined with VMI at 60 keV improved the diagnostic efficiency for CD.

Therapy response assessment of non-small cell lung cancer using dual-energy computed tomography iodine map

OBJECTIVE: To investigate feasibility of the quantitative parameters of dual-energy computed tomography (DECT) to assess therapy response in advanced non-small cell lung cancer (NSCLC) compared with the traditional enhanced CT parameters based on the Response Evaluation Criteria in Solid Tumors (RECIST) guidelines. METHODS: Forty-five patients with unresectable locally advanced NSCLC who underwent DECT before and after chemotherapy or concurrent chemoradiotherapy (cCRT) were prospectively enrolled. By comparing baseline studies with follow-up, patients were divided into two groups according to RECIST guidelines as follows: disease control (DC, including partial response and stable disease) and progressive disease (PD). The diameter (D), attenuation, iodine concentration and normalized iodine concentration of arterial and venous phases (ICA, ICv, NICA, NICv) and the percentage of these changes pre- and post-therapy were measured and calculated. The Pearson correlation was used to analyze correlation between various quantitative parameters. The receiver operating characteristic (ROC) curves were used to evaluate accuracy of therapy response prediction. RESULTS: The change percentages of Attenuation (Δ-Attenuation-A and Δ-Attenuation-V), IC (ΔICA and ΔICV) and NIC (ΔNICA and ΔNICV) pre- and post-therapy correlate with the change percentage of D (ΔD). Among these, ΔICA strongly correlates with Δ D (r = 0.793, P < 0.001). The areas under ROC curves generated using Δ-Attenuation-A, ΔICA, and ΔNICA are 0.796, 0.900, and 0.880 with the corresponding cutoff value of 9.096, −15.692, and −4.7569, respectively, which are significantly different (P < 0.001). CONCLUSIONS: The quantitative parameters of DECT iodine map, especially iodine concentration, in arterial phase provides a new quantitative image marker to predict therapy response of patients diagnosed with advanced NSCLC.

Iodine Map Radiomics in Breast Cancer: Prediction of Metastatic Status

Dual-energy CT (DECT) iodine maps enable quantification of iodine concentrations as a marker for tissue vascularization. We investigated whether iodine map radiomic features derived from staging DECT enable prediction of breast cancer metastatic status, and whether textural differences exist between primary breast cancers and metastases. Seventy-seven treatment-naïve patients with biopsy-proven breast cancers were included retrospectively (41 non-metastatic, 36 metastatic). Radiomic features including first-, second-, and higher-order metrics as well as shape descriptors were extracted from volumes of interest on iodine maps. Following principal component analysis, a multilayer perceptron artificial neural network (MLP-NN) was used for classification (70% of cases for training, 30% validation). Histopathology served as reference standard. MLP-NN predicted metastatic status with AUCs of up to 0.94, and accuracies of up to 92.6 in the training and 82.6 in the validation datasets. The separation of primary tumor and metastatic tissue yielded AUCs of up to 0.87, with accuracies of up to 82.8 in the training, and 85.7 in the validation dataset. DECT iodine map-based radiomic signatures may therefore predict metastatic status in breast cancer patients. In addition, microstructural differences between primary and metastatic breast cancer tissue may be reflected by differences in DECT radiomic features.

Influence of beam hardening in dual-energy CT imaging: phantom study for iodine mapping, virtual monoenergetic imaging, and virtual non-contrast imaging

In this study, we investigated the influence of beam hardening on the dual-energy computed tomography (DECT) values of iodine maps, virtual monoenergetic (VME) images, and virtual non-contrast (VNC) images. 320-row DECT imaging was performed by changing the x-ray tube energy for the first and second rotations. DECT values of 5 mg/mL iodine of the multi-energy CT phantom were compared with and without a 2-mm-thick attenuation rubber layer (~700 HU) wound around the phantom. It was found that the CT density values UH, with/without the rubber layer had statistical differences in the iodine map (184 ± 0.7 versus 186 ± 1.8), VME images (125 ± 0.3 versus 110 ± 0.4), and VNC images (−58 ± 0.7 versus −76 ± 1.7) (p < 0.010 for all). This suggests that iodine mapping may be underestimated by DECT and overestimated by VME imaging because of x-ray beam hardening. The use of VNC images instead of plain CT images requires further investigation because of underestimation.

Prediction of Tumor Cellularity in Resectable PDAC from Preoperative Computed Tomography Imaging

Background: PDAC remains a tumor entity with poor prognosis and a 5-year survival rate below 10%. Recent research has revealed invasive biomarkers, such as distinct molecular subtypes, predictive for therapy response and patient survival. Non-invasive prediction of individual patient outcome however remains an unresolved task. Methods: Discrete cellularity regions of PDAC resection specimen (n = 43) were analyzed by routine histopathological work up. Regional tumor cellularity and CT-derived Hounsfield Units (HU, n = 66) as well as iodine concentrations were regionally matched. One-way ANOVA and pairwise t-tests were performed to assess the relationship between different cellularity level in conventional, virtual monoenergetic 40 keV (monoE 40 keV) and iodine map reconstructions. Results: A statistically significant negative correlation between regional tumor cellularity in histopathology and CT-derived HU from corresponding image regions was identified. Radiological differentiation was best possible in monoE 40 keV CT images. However, HU values differed significantly in conventional reconstructions as well, indicating the possibility of a broad clinical application of this finding. Conclusion: In this study we establish a novel method for CT-based prediction of tumor cellularity for in-vivo tumor characterization in PDAC patients.

Radiological differences between chronic thromboembolic pulmonary disease (CTEPD) and chronic thromboembolic pulmonary hypertension (CTEPH)

Objectives The aim of this study was to describe the radiological features of chronic thromboembolic pulmonary disease (CTEPD), not yet systematically described in the literature. Furthermore, we compared vascular scores between CTEPD and chronic thromboembolic pulmonary hypertension (CTEPH) patients, trying to explain why pulmonary hypertension does not develop at rest in CTEPD patients. Methods Eighty-five patients (40 CTEPD, 45 CTEPH) referred to our centre for pulmonary endarterectomy underwent dual-energy computed tomography pulmonary angiography (DE-CTPA) with iodine perfusion maps; other 6 CTEPD patients underwent single-source CTPA. CT scans were reviewed independently by an experienced cardiothoracic radiologist and a radiology resident to evaluate scores of vascular obstruction, hypoperfusion and mosaic attenuation, signs of pulmonary hypertension and other CT features typical of CTEPH. Results Vascular obstruction burden was similar in the two groups (p = 0.073), but CTEPD patients have a smaller extension of perfusion defects in the iodine map (p = 0.009) and a smaller number of these patients had mosaic attenuation (p < 0.001) than CTEPH patients, suggesting the absence of microvascular disease. Furthermore, as expected, the two groups were significantly different considering the indirect signs of pulmonary hypertension (p < 0.001). Conclusions CTEPD and CTEPH patients have significantly different radiological characteristics, in terms of signs of pulmonary hypertension, mosaic attenuation and iodine map perfusion extension. Importantly, our results suggest that the absence of peripheral microvascular disease, even in presence of an important thrombotic burden, might be the reason for the absence of pulmonary hypertension in CTEPD. Key Points • CTEPD and CTEPH patients have significantly different radiological characteristics. • The absence of peripheral microvascular disease might be the reason for the absence of pulmonary hypertension in CTEPD.

The Performance of a Dual-Energy CT Derived Radiomics Model in Differentiating Serosal Invasion for Advanced Gastric Cancer Patients After Neoadjuvant Chemotherapy: Iodine Map Combined With 120-kV Equivalent Mixed Images

ObjectivesThe aim was to determine whether the dual-energy CT radiomics model derived from an iodine map (IM) has incremental diagnostic value for the model based on 120-kV equivalent mixed images (120 kVp) in preoperative restaging of serosal invasion with locally advanced gastric cancer (LAGC) after neoadjuvant chemotherapy (NAC).MethodsA total of 155 patients (110 in the training cohort and 45 in the testing cohort) with LAGC who had standard NAC before surgery were retrospectively enrolled. All CT images were analyzed by two radiologists for manual classification. Volumes of interests (VOIs) were delineated semi-automatically, and 1,226 radiomics features were extracted from every segmented lesion in both IM and 120 kVp images, respectively. Spearman’s correlation analysis and the least absolute shrinkage and selection operator (LASSO) penalized logistic regression were implemented for filtering unstable and redundant features and screening out vital features. Two predictive models (120 kVp and IM-120 kVp) based on 120 kVp selected features only and 120 kVp combined with IM selected features were established by multivariate logistic regression analysis. We then build a combination model (ComModel) developed with IM-120 kVp signature and ycT. The performance of these three models and manual classification were evaluated and compared.ResultThree radiomics models showed great predictive accuracy and performance in both the training and testing cohorts (ComModel: AUC: training, 0.953, testing, 0.914; IM-120 kVp: AUC: training, 0.953, testing, 0.879; 120 kVp: AUC: training, 0.940, testing, 0.831). All these models showed higher diagnostic accuracy (ComModel: 88.9%, IM-120 kVp: 84.4%, 120 kVp: 80.0%) than manual classification (68.9%) in the testing group. ComModel and IM-120 kVp model had better performances than manual classification both in the training (both p&lt;0.001) and testing cohorts (p&lt;0.001 and p=0.034, respectively).ConclusionsDual-energy CT-based radiomics models demonstrated convincible diagnostic performance in differentiating serosal invasion in preoperative restaging for LAGC. The radiomics features derived from IM showed great potential for improving the diagnostic capability.