Quantitative iodine-based material decomposition images with spectral CT imaging for differentiating prostatic carcinoma from benign prostatic hyperplasia

Dual-energy computed tomography for evaluating nodal staging in lung adenocarcinoma: correlation with surgical pathology

PURPOSE

To ascertain the performance of dual-energy CT (DECT) with iodine quantification in differentiating malignant mediastinal and hilar lymph nodes (LNs) from benign ones, focusing on patients with lung adenocarcinoma.

MATERIALS AND METHODS

In this study, patients with suspected lung cancer received a preoperative contrast-enhanced DECT scan from Jun 2018 to Dec 2020. Quantitative DECT parameters and the size were compared between metastatic and benign LNs. Their diagnostic performances were analyzed by the ROC curves and compared by using the two-sample t test.

RESULTS

72 patients (23 men, 49 women; mean age 62.5 ± 10.1 years) fulfilled the inclusion criteria. A total of 98 LNs (67 benign, 31 metastatic) were analyzed. The iodine concentration normalized by muscle (NICmuscle) was significantly higher (P < 0.001) in metastatic LNs (4.79 ± 1.70) than in benign ones (3.00 ± 1.45). The optimal threshold of NICmuscle was 3.44, which yielded AUC: 0.798, sensitivity: 83.9%, specificity: 73.1%, accuracy: 76.5%, respectively. Applying the established size parameters with 10 mm as the threshold yielded AUC: 0.600, sensitivity: 29.0%, specificity: 91.0%, accuracy: 71.4%, respectively. The diagnostic performance of NICmuscle was significantly better (P = 0.007) than the performance obtained using the established size parameters.

CONCLUSIONS

For lung adenocarcinoma, the quantitative measurement of NICmuscle derived from DECT is useful for differentiating benign and metastatic mediastinal and hilar LNs before surgical intervention.

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.

Application of contrast-enhanced dual-energy spectral CT for differentiating borderline from malignant epithelial ovarian tumours

AIM

To investigate the value of contrast-enhanced dual-energy spectral computed tomography (CT) in differentiating borderline epithelial ovarian tumours (BEOTs) from malignant epithelial ovarian tumours (MEOTs).

MATERIALS AND METHODS

Sixty patients who underwent pelvic contrast-enhanced spectral CT were divided into two groups for analysis based on the tumour types confirmed at histopathological examination (26 BEOTs and 34 MEOTs). The regions of interest (ROIs) were selected on solid tumour components to measure attenuation values on monochromatic image sets (40-140 keV) in all imaging phases and tumour iodine concentrations (IC) on material decomposition images. Differences in the attenuation value between the unenhanced and contrast-enhanced phases (enhancement degree) and between energy strengths (slope k, k = [attenuation at 40 keV- attenuation at 140 keV]/100) were calculated. All measurements between the two groups were compared with independent t-test. Receiver operating characteristic (ROC) curves were generated to calculate the sensitivity, specificity and area under the ROC curve (AUC). Logistic regression analysis was used to evaluate the diagnostic efficacy of using combined parameters in two-phase contrast-enhanced images.

RESULTS

In the arterial phase (AP) and venous phase (VP), the BEOTs had significantly lower enhancement than MEOTs from 40 to 100 keV (p<0.05). The k values and IC values both showed significant differences in the AP and VP (p<0.05). Combining parameters in two contrast-enhanced phases provided 80.8% sensitivity and 82.4% specificity in differentiating MEOTs from BEOTs with an AUC of 0.844.

CONCLUSION

Dual-energy spectral CT provides a multiparametric approach in differentiating BEOTs from MEOTs with the best diagnostic efficacy using combined parameters in the AP and VP images.

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

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

Impact of spectral body imaging in patients suspected for occult cancer: a prospective study of 503 patients

Objectives

To investigate the diagnostic impact and performance of spectral dual-layer detector CT in the detection and characterization of cancer compared to conventional CE-CT.

Methods

In a national workup program for occult cancer, 503 patients (286 females and 217 males) were prospectively enrolled for a contrast-enhanced spectral CT scan. The readings were performed with and without spectral data available. A minimum of 3 months between interpretations was implemented to minimize recall bias. The sequence of reads for the individual patient was randomized. Readers were blinded for patient identifiers and clinical outcome. Two radiologists with 9 and 33 years of experience performed the readings in consensus. If disagreement, a third radiologist with 11 years of experience determined the outcome of the reading

Results

Significantly more cancer findings were identified on the spectral reading. In 73 cases of proven cancer, we found a sensitivity of 89% vs 77% and a specificity of 77% vs 83% on spectral CT compared to conventional CT. A slight increase in reading time in spectral images of 82 s was found (382 vs 300, p < 0.001). For all cystic lesions, the perceived diagnostic certainty increased from 30% being completely certain to 96% most pronounced in the kidney, liver, thyroid, and ovaries. And adding the spectral information to the reading gave a decrease in follow-up examination for diagnostic certainty (0.25 vs 0.81 per reading, p < 0.001).

Conclusion

The use of contrast-enhanced spectral CT increases the confidence of the radiologists in correct characterization of various lesions and minimizes the need for supplementary examinations.

Key Points

• Spectral CT is associated with a higher sensitivity, but a slightly lower specificity compared to conventional CT.

• Spectral CT increases the confidence of the radiologists.

• The need for supplementary examinations is decreased, with only a slight increase in reading times.

Electronic supplementary material

The online version of this article (10.1007/s00330-020-06878-7) contains supplementary material, which is available to authorized users.

Dual-energy spectral CT quantitative parameters for the differentiation of Glioma recurrence from treatment-related changes: a preliminary study

Background

Differentiating glioma recurrence from treatment-related changes can be challenging on conventional imaging. We evaluated the efficacy of quantitative parameters measured by dual-energy spectral computed tomographic (CT) for this differentiation.

Methods

Twenty-eight patients were examined by dual-energy spectral CT. The effective and normalized atomic number (Z_eff and Z_eff-N, respectively); spectral Hounsfield unit curve (λ_HU) slope; and iodine and normalized iodine concentration (IC and IC_N, respectively) in the post-treatment enhanced areas were calculated. Pathological results or clinicoradiologic follow-up of ≥2 months were used for final diagnosis. Nonparametric and t-tests were used to compare quantitative parameters between glioma recurrence and treatment-related changes. Sensitivity, specificity, positive and negative predictive values (PPV and NPV, respectively), and accuracy were calculated using receiver operating characteristic (ROC) curves. Predictive probabilities were used to generate ROC curves to determine the diagnostic value.

Results

Examination of pre-contrast λ_HU, Z_eff, Z_eff-N, IC, IC_N, and venous phase IC_N showed no significant differences in quantitative parameters (P > 0.05). Venous phase λ_HU, Z_eff, Z_eff-N, and IC in glioma recurrence were higher than in treatment-related changes (P < 0.001). The optimal venous phase threshold was 1.03, 7.75, 1.04, and 2.85 mg/cm³, achieving 66.7, 91.7, 83.3, and 91.7% sensitivity; 100.0, 77.8, 88.9, and 77.8% specificity; 100.0, 73.3, 83.3, and 73.3% PPV; 81.8, 93.3, 88.9, and 93.3% NPV; and 86.7, 83.3, 86.7, and 83.3% accuracy, respectively. The respective areas under the curve (AUCs) were 0.912, 0.912, 0.931, and 0.910 in glioma recurrence and treatment-related changes.

Conclusions

Glioma recurrence could be potentially differentiated from treatment-related changes based on quantitative values measured by dual-energy spectral CT imaging.

Radiomics Analysis of Iodine-Based Material Decomposition Images With Dual-Energy Computed Tomography Imaging for Preoperatively Predicting Microsatellite Instability Status in Colorectal Cancer

Purpose: The aim of this study was to investigate the value of radiomics analysis of iodine-based material decomposition (MD) images with dual-energy computed tomography (DECT) imaging for preoperatively predicting microsatellite instability (MSI) status in colorectal cancer (CRC).

Methods: This study included 102 CRC patients proved by postoperative pathology, and their MSI status was confirmed by immunohistochemistry staining. All patients underwent preoperative DECT imaging scanned on either a Revolution CT or Discovery CT 750HD scanner, and the iodine-based MD images in the venous phase were reconstructed. The clinical, CT-reported, and radiomics features were obtained and analyzed. Data from the Revolution CT scanner were used to establish a radiomics model to predict MSI status (70% samples were randomly selected as the training set, and the remaining samples were used to validate); and data from the Discovery CT 750HD scanner were used to test the radiomics model. The stable radiomics features with both inter-user and intra-user stability were selected for the next analysis. The feature dimension reduction was performed by using Student's t-test or Mann–Whitney U-test, Spearman's rank correlation test, min–max standardization, one-hot encoding, and least absolute shrinkage and selection operator selection method. The multiparameter logistic regression model was established to predict MSI status. The model performances were evaluated: The discrimination performance was accessed by receiver operating characteristic (ROC) curve analysis; the calibration performance was tested by calibration curve accompanied by Hosmer–Lemeshow test; the clinical utility was assessed by decision curve analysis.

Results: Nine top-ranked features were finally selected to construct the radiomics model. In the training set, the area under the ROC curve (AUC) was 0.961 (accuracy: 0.875; sensitivity: 1.000; specificity: 0.812); in the validation set, the AUC was 0.918 (accuracy: 0.875; sensitivity: 0.875; specificity: 0.857). In the testing set, the diagnostic performance was slightly lower with AUC of 0.875 (accuracy: 0.788; sensitivity: 0.909; specificity: 0.727). A nomogram based on clinical factors and radiomics score was generated via the proposed logistic regression model. Good calibration and clinical utility were observed using the calibration and decision curve analyses, respectively.

Conclusion: Radiomics analysis of iodine-based MD images with DECT imaging holds great potential to predict MSI status in CRC patients.

Contribution of DECT in detecting serosal invasion of gastric cancer

Background/aim

This study aimed to investigate the relationship between the iodine concentration (IC) of perigastric fat tissue as assessed by dual-energy computed tomography (DECT) and serosal invasion of gastric cancer.

Materials and methods

A total of 41 patients underwent preoperative staging evaluation for gastric cancer using DECT between July 2015 and March 2018. Patients were divided into 2 groups based on pathology results: serosal invasion (stage T4a) and intact serosa (stages T1–T3). Cutoff values, the diagnostic efficacy of IC in the perigastric fat tissue, and the perigastric fat tissue/tumor (P/T) ratio were determined.

Results

Among the 41 patients, 22 had stage T4a gastric cancer and 19 patients had gastric cancer with a stage lower than T4a. The mean IC of perigastric fat tissue and the P/T ratio were significantly higher in patients with serosal invasion than in those with intact serosa (P < 0.001). During the arterial phase, the area under the curve (AUC) was 0.915 and 0.854 for the IC of perigastric fat tissue and the P/T ratio, respectively. During the venous phase, the AUC was 0.890 and 0.876 for the IC of perigastric fat tissue and the P/T ratio, respectively.

Conclusion

The IC in the perigastric fat tissue seems to be a reliable indicator for serosal invasion of gastric cancer.

Quantification of contrast agent materials using a new image- domain multi material decomposition algorithm based on dual energy CT

OBJECTIVE

Dual-Energy CT (DECT) is an imaging modality in which the objects are scanned by two different energy spectra. Using these two measurements, two type of materials can be separated and density image pairs can be generated as well. Decomposing more than two materials is necessary in both clinical and industrial CT applications.

METHODS

In our MMD, barycentric coordinates were chosen using an innovative local clustering method. Local clustering increases precision in the barycentric coordinates assignment by decreasing search domain. Therefore the algorithm can be run in parallel. For optimizing coordinates selection, a fast bi-directional Hausdorff distance measurement is used. To deal with the significant obstacle of noise, we used Doubly Local Wiener Filter Directional Window (DLWFDW) algorithm.

RESULTS

Briefly, the proposed algorithm separates blood and fat ROIs with errors of less than 2 and 9 % respectively on the clinical images. Also, the ability to decompose different materials with different concentrations is evaluated employing the phantom data. The highest accuracy obtained in separating different materials with different concentrations was 93 % (for calcium plaque) and 97.1 % (for iodine contrast agent) respectively. The obtained results discussed in detail in the following results section.

CONCLUSION

In this study, we propose a new material decomposition algorithm. It improves the MMD work flow by employing tools which are easy to implement. Furthermore, in this study, an effort has been made to turn the MMD algorithm into a semi-automatic algorithm by employing clustering concept in material coordinate's assignment. The performance of the proposed method is comparable to existing methods from qualitative and quantitative aspects.

ADVANCES IN KNOWLEDGE

All decomposition methods have their own specific problems. Image- domain decomposition also has barriers and problems, including the need for a predetermined table for the separation of different materials with specified coordinates. In the present study, it attempts to solve this problem by using clustering methods and relying on the intervals between different materials in the attenuation domain.

Axillary Sentinel Lymph Nodes in Breast Cancer: Quantitative Evaluation at Dual-Energy CT

Purpose To evaluate the diagnostic performance of quantitative parameters derived from dual-energy CT for the preoperative diagnosis of metastatic sentinel lymph nodes (SLNs) in participants with breast cancer. Materials and Methods For this prospective study, dual-phase contrast agent-enhanced CT was performed in female participants with breast cancer from June 2015 to December 2017. Quantitative dual-energy CT parameters and morphologic parameters were compared between metastatic and nonmetastatic SLNs. The quantitative parameters were fitted to univariable and multivariable logistic regression models. The diagnostic role of morphologic and quantitative parameters was analyzed by receiver operating characteristic curves and compared by using the McNemar test. Results This study included 193 female participants (mean age, 47.6 years ± 10.1; age range, 22-79 years). Quantitative dual-energy CT parameters including slope of the spectral Hounsfield unit curve (λ_Hu) measured at both arterial and venous phases, normalized iodine concentration at both arterial and venous phase, and normalized effective atomic number at the venous phase were higher in metastatic than in nonmetastatic SLNs (P value range, ≤.001 to .031). Univariable and multivariable logistic regression analyses showed that venous phase λ_Hu (in Hounsfield units per kiloelectron-volt) was the best single parameter for the detection of metastatic SLNs. The accuracy of the venous phase λ_Hu for detecting metastatic SLNs was 90.5% on a per-lymph node basis and 87.0% on a per-patient basis. The accuracy and specificity at venous phase λ_Hu was higher than their counterparts in the morphologic parameters (P < .001). Conclusion Dual-energy CT is a complementary means for the preoperative identification of sentinel lymph nodes metastases in participants with breast cancer. © RSNA, 2018 Online supplemental material is available for this article.

Quantitative assessment of the degree of differentiation in colon cancer with dual-energy spectral CT

OBJECTIVE

To evaluate dual-energy spectral CT imaging in evaluating the degree of differentiation in colon cancer.

METHODS

Forty-seven colon cancer patients underwent spectral CT during arterial phase (AP) and portal venous phase (PP), and were characterized pathologically differentiated to well-differentiated (A, n = 18) and poorly differentiated or undifferentiated carcinoma group (B, n = 29). Lesion iodine concentration (IC) was measured and normalized to that of aorta (NIC). CT numbers were measured and the slope (λ _HU) of the spectral HU curve was calculated. These parameters were statistically compared between the two groups. ROC curves were used to evaluate their diagnostic efficacies.

RESULTS

There were significant differences in IC (1.01 ± 0.20 vs. 1.59 ± 0.57 mg/ml), NIC (0.12 ± 0.03 vs. 0.19 ± 0.09), λ _HU (1.41 ± 0.29 vs. 2.03 ± 0.85), and CT number at 70 keV (48.61 ± 9.03HU vs. 63.97 ± 15.86HU) between groups A and B in AP (p < 0.05), but no difference in PP. Using IC = 1.13 mg/ml in AP as the threshold, one obtained a sensitivity of 81.8% and a specificity of 71.4% for differentiating well-differentiated from poorly differentiated or undifferentiated carcinoma. These values were statistically higher than those (64.7% and 62.3%) using CT number at 70 keV.

CONCLUSION

Spectral CT imaging parameters (IC, NIC, and λ _HU) in AP provide improved accuracy for evaluating the degrees of differentiation in colon cancer than CT number at 70 keV.

Iodine Concentration in Spectral CT: Assessment of Prognostic Determinants in Patients With Gastric Adenocarcinoma

OBJECTIVE

The purpose of this study was to use virtual monochromatic spectral CT to investigate the usefulness of iodine concentration (IC) and its correlation with clinicopathologically determined prognostic factors in gastric adenocarcinoma.

SUBJECTS AND METHODS

From June 2012 to March 2015, 34 patients with gastric adenocarcinoma underwent arterial and portal venous phase spectral CT. The ICs in the arterial and portal venous phases were calculated and then normalized with the aorta as normalized IC (NIC). The surgical specimen was evaluated with CD34 staining to determine microvessel density (MVD). The correlation between imaging results and clinicopathologic findings was investigated for histologic grading, lymph node metastasis, serosal involvement, distant metastasis, pathologic TNM stage, and MVD.

RESULTS

The mean arterial phase NIC value of tumors was 0.12 ± 0.03, portal venous phase NIC value was 0.39 ± 0.06, and MVD was 26.94 ± 7.87 vessels per high-power field (×400). Both arterial phase and portal venous phase NIC values were significantly higher in poorly differentiated gastric adenocarcinomas (p = 0.005) than in moderately differentiated tumors (p = 0.013). There was no significant correlation between NIC and serosal involvement or distant metastasis. There was significant correlation between the NIC and MVD in gastric adenocarcinoma (arterial phase NIC, p = 0.013; portal venous phase NIC, p = 0.001). However, neither the arterial nor the portal venous phase NIC of gastric adenocarcinoma had a significant relation to lymphatic metastasis or pathologic TNM stage. There was a significant difference between the high and low MVD groups with respect to portal venous phase NIC (p = 0.045).

CONCLUSION

NIC can serve as a useful predictor of angiogenesis and degree of differentiation of moderately and poorly differentiated gastric adenocarcinomas.

Spectral computed tomography in advanced gastric cancer: Can iodine concentration non-invasively assess angiogenesis?

AIM

To investigate the correlation of iodine concentration (IC) generated by spectral computed tomography (CT) with micro-vessel density (MVD) and vascular endothelial growth factor (VEGF) expression in patients with advanced gastric carcinoma (GC).

METHODS

Thirty-four advanced GC patients underwent abdominal enhanced CT in the gemstone spectral imaging mode. The IC of the primary lesion in the arterial phase (AP) and venous phase (VP) were measured, and were then normalized against that in the aorta to provide the normalized IC (nIC). MVD and VEGF were detected by immunohistochemical assays, using CD34 and VEGF-A antibodies, respectively. Correlations of nIC with MVD, VEGF, and clinical-pathological features were analyzed.

RESULTS

Both nICs correlated linearly with MVD and were higher in the primary lesion site than in the normal control site, but were not correlated with VEGF expression. After stratification by clinical-pathological subtypes, nIC-AP showed a statistically significant correlation with MVD, particularly in the group with tumors at stage T4, without nodular involvement, of a mixed Lauren type, where the tumor was located at the antrum site, and occurred in female individuals. nIC-VP showed a positive correlation with MVD in the group with the tumor at stage T4 and above, had nodular involvement, was poorly differentiated, was located at the pylorus site, of a mixed and diffused Lauren subtype, and occurred in male individuals. nIC-AP and nIC-VP showed significant differences in terms of histological differentiation and Lauren subtype.

CONCLUSION

The IC detected by spectral CT correlated with the MVD. nIC-AP and nIC-VP can reflect angiogenesis in different pathological subgroups of advanced GC.

[GSI Quantitative Parameters: Preoperative Diagnosis of Metastasis Lymph Nodes in Lung Cancer]

背景与目的

肺癌淋巴结转移是重要的生存预后因素，准确的纵隔淋巴结分期可以使患者最大程度地受益于手术。本研究旨在探讨宝石能谱计算机断层扫描（computed tomography, CT）定量参数在术前诊断非小细胞肺癌（non-small cell lung cancer, NSCLC）患者淋巴结转移的价值。

方法

收集48例NSCLC患者，连续进行宝石能谱CT成像（gemstone spectral imaging, GSI）模式肺增强扫描和手术治疗。重建GSI数据，测量淋巴结的大小、动脉期和静脉期的CT值、能谱曲线的斜率、标准化碘浓度以及水浓度。采用独立样本的t检验，并进行受试者工作特征曲线（receiver operating characteristic, ROC）分析，确定诊断的最佳阈值及效能。

结果

转移性淋巴结与非转移性淋巴结短轴直径、动脉期和静脉期的CT值、能谱曲线的斜率、标准化碘浓度均有统计学差异。当确定动脉期能谱曲线斜率的最佳临界值为2.75，其诊断的敏感性、特异性及总体的准确性分别为88.2%、88.4%、87.0%。

结论

能谱CT的GSI模式定量参数较传统CT在术前诊断转移性淋巴结方面有更高的诊断效能。

Small colorectal cancer liver metastases: Clinical value of quantitative iodine-based material decomposition images of spectral CT

AIM: To retrospectively assess the diagnostic value of quantitative iodine-based material decomposition images of spectral CT in evaluating small liver metastases (<3 cm) from colorectal cancer.

METHODS: Nine hundred and fifteen consecutive patients with liver lesions were recruited, and 140 of them were confirmed to have metastatic liver cancer. All the patients underwent double-phase [arterial phase (AP) and portal venous phase (PVP)] spectral CT scans and the best single energy images were obtained at the workstation. Fifteen different sources of small metastatic liver lesions (<3 cm) were analyzed, and the diagnosis rate was compared between the best single energy images and traditional images. The final study group included 41 patients with hepatic metastases from colorectal cancer. Iodine concentrations and CT values of normal liver parenchyma and metastatic lesions were derived from iodine-based material-decomposition CT or conventional CT images. The differences in iodine concentration and CT values between the AP and PVP were recorded and the lesion-to-normal liver parenchyma differences were calculated. The paired t-test was employed to compare CT value and iodine concentrations between AP and PVP. Two readers qualitatively assessed lesion types on the basis of conventional CT characteristics. The two-sample t-test was performed to compare the iodine concentrations and CT values changes between AP and PVP in normal liver parenchyma and metastatic lesions (central and marginal).

RESULTS: Compared with traditional CT hybrid energy images, the detection rate of small metastases was much higher by spectral CT images (Wilcoxon sighed-rank test Z = 3.306, P = 0.001). In the AP, comparing the marginal with the central parts of the lesions, the CT values increased by 37.65% while the iodine value increased by 65.95%, and there was a significant difference between them (P < 0.001). Comparing normal liver tissues with the marginal parts of the lesions, the CT values increased by 22.99% while the iodine value increased by 17.96%, and there was no significant difference between them (P = 0.225). In the PVP, comparing the marginal with the central parts of the lesions, the CT values increased by 32.13% while the iodine value increased by 40.01%, and the difference was significant (P < 0.001). Comparing normal liver tissues with the marginal parts of the lesions, the CT values increased by 34.47% while the iodine value increased by 40.92%, and the difference was significant (P = 0.033).

CONCLUSION: Quantitative CT iodine value analysis may be able to improve the detection rate of small lesions, and it can display the enhancement features of colorectal cancer liver metastases. This technique may help to improve the diagnostic accuracy of small metastatic lesions.

Application of spectral computed tomography dual-substance separation technology for diagnosing left ventricular thrombus

OBJECTIVE

To investigate the value of spectral computed tomography (CT) dual-substance separation technology for diagnosing left ventricular (LV) thrombus.

METHODS

In this observational case-control study, spectral CT scans were conducted in patients with and without LV thrombi. Densities in the regions of the LV cavity, papillary muscles and LV thrombus were observed on 140 kVp mixed-energy and 70 keV single-energy images. Iodine and blood were chosen as the base material pair, the densities were observed and the iodine and blood concentrations were quantitatively measured.

RESULTS

A total of 24 patients were enrolled in this study. On iodine-based density images, both the LV thrombus and papillary muscles showed low-attenuation shadows. On blood-based density images, comparable high-density attenuation was found in the LV thrombus and LV cavity, while relative hypodensity was noted in the papillary muscles. Iodine and blood densities were significantly lower in papillary muscles than in the LV cavity. Iodine densities were significantly lower in the LV thrombus than the LV cavity, whereas blood densities in the two areas did not differ significantly.

CONCLUSIONS

Spectral CT dual-substance separation technology and its derived images of iodine- and blood- based densities provide a new, simple, and feasible semiquantitative method to detect LV thrombus that warrants further investigation.

Clinical significance of dual-energy CT-derived iodine quantification in the diagnosis of metastatic LN in colorectal cancer

BACKGROUND

The purpose of this study was to evaluate the diagnostic value of dual-energy computed tomography (DECT) in detecting lymph node (LN) metastasis in patients with colorectal cancer.

METHODS

Data from 81 LNs from 28 patients with colorectal adenocarcinoma were retrospectively analyzed. All patients received DECT before surgery without any neoadjuvant therapy. The diagnostic value was assessed using the iodine concentration (IC).

RESULTS

In the pathological findings, 35 (43.2%) LNs from 13 patients were metastatic and 46 (56.8%) LNs from 17 patients were non-metastatic. The mean IC of metastatic LNs in the portal venous phase (PP) was 1.60 mg/ml, which was significantly lower compared with non-metastatic LNs (3.25 mg/ml, p < 0.001). Receiver operating characteristic (ROC) analysis revealed that the IC in PP had the highest ability to discriminate LN metastasis (area under the ROC curve [AUC] 0.932). The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of IC in PP (cutoff 2.1 mg/ml) were 87.0%, 88.6%, 85.3%, 90.0%, and 87.9%, respectively. When clinically obvious metastatic LNs in conventional CT findings were excluded, 50 LNs remained (5 metastatic and 45 non-metastatic LNs). In this subgroup analysis, the IC in PP remained the most powerful predictor of metastatic LNs (cutoff: 2.1 mg/ml, AUC 0.933).

CONCLUSIONS

The evaluation of IC in DECT may improve the diagnostic capabilities of discriminating metastatic LNs. This method may be particularly useful when conventional CT findings lead to equivocal results.

Assessment of Lipiodol Deposition and Residual Cancer for Hepatocellular Carcinoma After Transcatheter Arterial Chemoembolization via Iodine-Based Material Decomposition Images with Spectral Computed Tomography Imaging: A Preliminary Study

Background:

It is critical to follow up hepatocellular carcinoma (HCC) after transcatheter arterial chemoembolization (TACE) in clinical practice. Computed tomography (CT) is used to assess lipiodol deposition, whereas it is difficult to assess hypovascular residual cancer masked by lipiodol. In contrast, magnetic resonance imaging (MRI) is superior to CT in showing residual cancer, but cannot display lipiodol deposition.

Objectives:

The aim of this study was to investigate the value of spectral CT imaging in both lipiodol deposition and residual cancer for HCC patients after TACE.

Patients and Methods:

Ten HCC patients after treated with TACE underwent Discovery CT750 HD and MRI750 3T examination. Receiver operating characteristic (ROC) curves of iodine-based material decomposition images, monochromatic images and conventional CT images were generated.

Results:

Consequently, 30 residual lesions were detected in MRI of 10 patients. They were found in iodine-based images and monochromatic images versus 29 in conventional CT images. The area under ROC curves for the lesion-to-normal parenchyma ratio (LNR) on arterial phase (AP) in iodine-based material decomposition images, monochromatic images and conventional CT images were 0.933, 0.833 and 0.817, respectively.

Conclusion:

The study data highlighted good value of iodine-based material decomposition images of spectral CT in assessment of both lipiodol deposition and residual cancer for follow-up of HCC patients previously treated with TACE.

Spectral Imaging Technology-Based Evaluation of Radiation Treatment Planning to Remove Contrast Agent Artifacts

OBJECTIVE

This study employs dual-source computed tomography single-spectrum imaging to evaluate the effects of contrast agent artifact removal and the computational accuracy of radiotherapy treatment planning improvement.

METHOD

The phantom, including the contrast agent, was used in all experiments. The amounts of iodine in the contrast agent were 30, 15, 7.5, and 0.75 g/100 mL. Two images with different energy values were scanned and captured using dual-source computed tomography (80 and 140 kV). To obtain a fused image, 2 groups of images were processed using single-energy spectrum imaging technology. The Pinnacle planning system was used to measure the computed tomography values of the contrast agent and the surrounding phantom tissue. The difference between radiotherapy treatment planning based on 80 kV, 140 kV, and energy spectrum image was analyzed.

RESULTS

For the image with high iodine concentration, the quality of the energy spectrum-fused image was the highest, followed by that of the 140-kV image. That of the 80-kV image was the worst. The difference in the radiotherapy treatment results among the 3 models was significant. When the concentration of iodine was 30 g/100 mL and the distance from the contrast agent at the dose measurement point was 1 cm, the deviation values (P) were 5.95% and 2.20% when image treatment planning was based on 80 and 140 kV, respectively. When the concentration of iodine was 15 g/100 mL, deviation values (P) were -2.64% and -1.69%.

CONCLUSION

Dual-source computed tomography single-energy spectral imaging technology can remove contrast agent artifacts to improve the calculated dose accuracy in radiotherapy treatment planning.

Computer-aided diagnosis for preoperative invasion depth of gastric cancer with dual-energy spectral CT imaging

RATIONALE AND OBJECTIVES

This study evaluates the accuracy of dual-energy spectral computed tomography (DEsCT) imaging with the aid of computer-aided diagnosis (CAD) system in assessing serosal invasion in patients with gastric cancer.

MATERIALS AND METHODS

Thirty patients with gastric cancer were enrolled in this study. Two types of features (information) were collected with the use of DEsCT imaging: conventional features including patient's clinical information (eg, age, gender) and descriptive characteristics on the CT images (eg, location of the lesion, wall thickness at the gastric cardia) and additional spectral CT features extracted from monochromatic images (eg, 60 keV) and material-decomposition images (eg, iodine- and water-density images). The classification results of the CAD system were compared to pathologic findings. Important features can be found out using support vector machine classification method in combination with feature-selection technique thereby helping the radiologists diagnose better.

RESULTS

Statistical analysis showed that for the collected cases, the feature "long axis" was significantly different between group A (serosa negative) and group B (serosa positive) (P < .05). By adding quantitative spectral features from several regions of interest (ROIs), the total classification accuracy was improved from 83.33% to 90.00%. Two feature ranking algorithms were used in the CAD scheme to derive the top-ranked features. The results demonstrated that low single-energy (approximately 60 keV) CT values, tumor size (long axis and short axis), iodine (water) density, and Effective-Z values of ROIs were important for classification. These findings concurred with the experience of the radiologist.

CONCLUSIONS

The CAD system designed using machine-learning algorithms may be used to improve the identification accuracy in the assessment of serosal invasion in patients of gastric cancer with DEsCT imaging and provide some indicators which may be useful in predicting prognosis.

Imaging diagnosis for left ventricular thrombosis in idiopathic hypereosinophilic syndrome: two case reports

Idiopathic hypereosinophilic syndrome (IHES) is a rare disease that is frequently associated with cardiac thrombosis and endocardial wall thickness. This case report describes 2 patients who had IHES associated with left ventricular (LV) thrombi. The patients' symptoms are atypical. Peripheral blood and bone marrow tests showed markedly elevated eosinophils. Electrocardiography showed ischemic changes in both patients. Negative computed tomography (CT) angiography excluded coronary artery stenosis. Transthoracic echocardiography (TTE), conventional multislice spiral CT, gemstone spectral CT, and cardiac magnetic resonance imaging were used to identify the LV intraluminal thrombus and endocardial thickening, and the diagnostic values of each imaging method were analyzed and compared. These patients were clinically diagnosed as "IHES, LV thrombosis, NYHA heart function classification I." Both patients received oral prednisone and warfarin therapy. At 5 month follow-up, TTE rechecks showed that the size of the LV thrombotic lesion was reduced in the first case but substantially increased in the second case.

Differential diagnosis of pancreatic serous oligocystic adenoma and mucinous cystic neoplasm with spectral CT imaging: initial results

AIM

To investigate the imaging characteristics of pancreatic serous oligocystic adenoma (SOA) and mucinous cystic neoplasms (MCNs) using spectral computed tomography (CT) and to evaluate whether quantitative information derived from spectral imaging can improve the differential diagnosis of these diseases.

MATERIALS AND METHODS

From February 2010 to June 2013, 44 patients (24 SOAs and 20 MCNs) who underwent spectral CT imaging were included in the study. Conventional characteristics and quantitative parameters were compared between the two disease groups. Logistic regression was used for multiparametric analysis. The receiver-operating characteristic curve was used to evaluate the diagnostic performance of single parameter and multiparametric analysis. Two radiologists diagnosed the diseases blinded and independently, without and with the information of the statistical analysis.

RESULTS

Tumour location, contour, size, and monochromatic CT values at 40 keV to 70 keV, iodine concentration, and effective atomic number (effective-Z) in the late arterial phase were the independent factors correlated with category. Multiparametric analysis with logistic regression showed that tumour size, location, and contour were the most effective variations, and obtained an area under the ROC curve (AUC) of 0.934. With the knowledge of statistical analysis, the accuracy of the first reader increased from 70.5% to 86.4%, and the accuracy of the second reader increased from 81.8% to 90.9%.

CONCLUSIONS

Although CT spectral imaging provided additional information and multiparametric analysis obtained better performance than single-parameter analysis in differentiating MCNs from SOAs, multiparametric analysis with the combination of quantitative parameters derived from CT spectral imaging did not improve the diagnostic performance. Tumour size, location, and contour played an important role in differentiating MCNs from SOAs.