Differentiation of small hepatic hemangioma from small hepatocellular carcinoma: recently introduced spectral CT method

Correlation of Spectral CT-Based Iodine Concentration Parameters with LI-RADS Classification of Suspected Hepatocellular Carcinoma Nodules in Cirrhotic Patients

Background: The LI-RADS classification is widely used for the hepatocellular carcinoma (HCC) risk stratification of liver nodules in cirrhotic patients. The evaluation of nodule enhancement, which is a major criterion, commonly relies on qualitative assessment. This study aims to investigate the potential role of material density (MD) parameters in the iodine maps of spectral computed tomography (SCT) to discriminate between LI-RADS (v2018 CORE) categories in cirrhotic patients. Methods: Dual-energy SCT scans of cirrhotic patients with suspected HCC, taken between March 1st, 2022 and September 30th, 2023, were retrospectively reviewed. All the images were reviewed by trained radiologists to classify nodules as LI-RADS 3, 4, or 5 by consensus. MD maps were generated in the hepatic arterial phase (HAP), portal venous phase (PVP), and equilibrium phase (EP). The iodine concentration density (ICD) values of nodules (ICDnodule) and the non-nodular liver parenchyma (ICDliver) were measured to calculate lesion-to-non-nodular liver ICD ratio (LNR), as well as their differences (ΔICD) and ratios (rLNR). Results were correlated with LI-RADS categories. Results: A total of 69 patients were included and 79 DECT exams were assessed. Overall, 197 nodules (size 24.67 ± 23.11 mm, mean ± SD) were categorized into different LI-RADS classes: 44 were classed as LI-RADS 3 (22.3%), 14 were classed as LI-RADS 4 (7.1%), and 139 were classed as LI-RADS 5 (70.6%). The arterial LNR, arterial ICDnodule, ΔICD, and rLNR between HAP and PVP discriminated between LI-RADS 3 and LI-RADS 4+5 nodules (p < 0.001). All the calculated MD parameters showed high diagnostic accuracy rates (all AUCs = 70-73%). Conclusions: MD parameters of liver nodules measured in SCT scans are viable diagnostic tools that may increase the radiologist's confidence in LI-RADS class allocation in cirrhotic patients. This preliminary and speculative study can serve as a baseline for the potential quantification of iodine concentrations of focal liver lesions to reduce subjectivity in hepatic nodule assessment and reporting. Future perspectives include the quantification of iodine concentration for prognostic stratification before locoregional and systemic treatments in HCC patients.

Spectral CT vs. diffusion-weighted imaging for the quantitative prediction of pathologic response to neoadjuvant chemotherapy in locally advanced gastric cancer

OBJECTIVES

To compare the performance of spectral CT and diffusion-weighted imaging (DWI) for predicting pathologic response after neoadjuvant chemotherapy (NAC) in locally advanced gastric cancer (LAGC).

MATERIALS AND METHODS

This was a retrospective analysis drawn from a prospective dataset. Sixty-five patients who underwent baseline concurrent triple-phase enhanced spectral CT and DWI-MRI and standard NAC plus radical gastrectomy were enrolled, and those with poor images were excluded. The tumor regression grade (TRG) was the reference standard, and patients were classified as responders (TRG 0 + 1) or non-responders (TRG 2 + 3). Quantitative iodine concentration (IC), normalized IC (nIC), and apparent diffusion coefficient (ADC) were measured by placing a freehand region of interest manually on the maximal two-dimensional plane. Their differences between responders and non-responders were compared. The performances of significant parameters were evaluated by the receiver operating characteristic analysis. The correlations between parameters and TRG status were explored through Spearman correlation coefficient test. Kaplan-Meier survival analysis was adopted to analyze their relationship with patient survival.

RESULTS

nICDP and ADC were associated with the TRG and yielded comparable performances for predicting TRG categories, with area under the curve (AUC) of 0.674 and 0.673, respectively. Their combination achieved a significantly increased AUC of 0.770 (p ; 0.05) and was associated with patient disease-free survival, with hazard ratio of 2.508 (1.043-6.029).

CONCLUSION

Spectral CT and DWI were equally useful imaging techniques for predicting pathologic response to NAC in LAGC. The combination of nICDP and ADC gained significant incremental benefits and was related to patient disease-free survival.

CLINICAL RELEVANCE STATEMENT

Spectral CT and DWI-based quantitative measurements are effective markers for predicting the pathologic regression outcomes of locally advanced gastric cancer patients after neoadjuvant chemotherapy.

KEY POINTS

• The pathologic tumor regression grade, the standard criteria for treatment response after neoadjuvant chemotherapy in gastric cancer patients, is difficult to predict early. • The quantitative parameters of normalized iodine concentration at delay phase and apparent diffusion coefficients were correlated with pathologic response; their combination demonstrated incremental benefits and was associated with patient disease-free survival. • Spectral CT and DWI are equally useful imaging modalities for predicting tumor regression grade after neoadjuvant chemotherapy in patients with locally advanced gastric cancer.

Spectral CT for preoperative diagnosis of N2 station lymph node metastasis in solid T1 non-small cell lung cancer

PURPOSE

To evaluate the diagnostic value of spectral CT for the preoperative diagnosis of N2 station lymph nodes metastasis in solid T1 non-small cell lung cancer (NSCLC).

METHOD

For this retrospective study, dual-phase contrast agent-enhanced CT was performed in patients with NSCLC from September 2019 to June 2023. Quantitative spectral CT parameters measurements were performed by 2 radiologists independently. Logistic regression analysis and Delong test were performed.

RESULTS

60 NSCLC patients (mean age, 62.85 years ± 8.49, 44men) were evaluated. A total of 121 lymph nodes (38 with metastasis) were enrolled. There was no significant difference in the slope of the spectral Hounsfield unit curve (λHu) on arterial phase (AP) or venous phase (VP) between primary lesions and metastatic lymph nodes (P > 0.05), but significant difference in VP λHu between primary lesions and non-metastatic lymph nodes (P < 0.001). The CT40KeV, λHu, normalized iodine concentration (nIC), normalized effective atomic number (nZeff) measured during both AP and VP were lower in metastatic lymph nodes than in non-metastatic lymph nodes (all P < 0.05). Short-axis diameter (S) of metastatic lymph nodes was higher than non-metastatic lymph nodes (P < 0.001). Area under the curve (AUC) for S performed the highest (0.788) in diagnosing metastatic lymph nodes. When combined with VP λHu, VP nZeff, AUC increased to 0.871.

CONCLUSION

Spectral CT is a complementary means for the preoperative diagnosis of N2 station lymph nodes metastasis in solid T1 NSCLC. The combined parameters have higher diagnostic efficiency.

A Deep Learning Image Reconstruction Algorithm for Improving Image Quality and Hepatic Lesion Detectability in Abdominal Dual-Energy Computed Tomography: Preliminary Results

This study aimed to compare the performance of deep learning image reconstruction (DLIR) and adaptive statistical iterative reconstruction-Veo (ASIR-V) in improving image quality and diagnostic performance using virtual monochromatic spectral images in abdominal dual-energy computed tomography (DECT). Sixty-two patients [mean age ± standard deviation (SD): 56 years ± 13; 30 men] who underwent abdominal DECT were prospectively included in this study. The 70-keV DECT images in the portal phase were reconstructed at 5-mm and 1.25-mm slice thicknesses with 40% ASIR-V (ASIR-V40%) and at 1.25-mm slice with deep learning image reconstruction at medium (DLIR-M) and high (DLIR-H) levels and then compared. Computed tomography (CT) attenuation, SD values, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were measured in the liver, spleen, erector spinae, and intramuscular fat. The lesions in each reconstruction group at 1.25-mm slice thickness were counted. The image quality and diagnostic confidence were subjectively evaluated by two radiologists using a 5-point scale. For the 1.25-mm images, DLIR-M and DLIR-H had lower SD, higher SNR and CNR, and better subjective image quality compared with ASIR-V40%; DLIR-H performed the best (all P values < 0.001). Furthermore, the 1.25-mm DLIR-H images had similar SD, SNR, and CNR values as the 5-mm ASIR-V40% images (all P > 0.05). Three image groups had similar lesion detection rates, but DLIR groups exhibited higher confidence in diagnosing lesions. Compared with ASIR-V40% at 70 keV, 70-keV DECT with DLIR-H further reduced image noise and improved image quality. Additionally, it improved diagnostic confidence while ensuring a consistent lesion detection rate of liver lesions.

Benefits of Dual-Layer Spectral CT Imaging in Staging and Preoperative Evaluation of Pancreatic Ductal Adenocarcinoma

Imaging of pancreatic malignancies is challenging but has a major impact on the patients therapeutic approach and outcome. In particular with pancreatic ductal adenocarcinoma (PDAC), usually a hypovascularized tumor, conventional CT imaging can be prone to errors in determining tumor extent and presence of metastatic disease. Dual-layer spectral detector CT (SDCT) is an emerging technique for acquiring spectral information without the need for prospective patient selection or specific protocols, with a detector capable of differentiating high- and low-energy photons to acquire full spectral images. In this review, we present the diagnostic benefits and capabilities of modern SDCT imaging with a focus on PDAC. We highlight the most useful virtual reconstructions in oncologic imaging and their benefits in staging and assessment of resectability in PDAC, including the assessment of tumor extent, vascular infiltration, and metastatic disease. We present imaging examples on a latest-generation SDCT scanner.

Differentiating invasive thymic epithelial tumors from mediastinal lung cancer using spectral CT parameters

PURPOSE

The purpose of the study was to explore the importance of quantitative characteristics of spectral CT between invasive thymic epithelial tumors (TETs) and mediastinal lung cancer.

METHODS

We analyzed 54 patients (28 with invasive TETs and 26 with mediastinal lung cancer) who underwent spectral CT. During the arterial and venous phase, we measured the CT70keV, effective atomic number (Zeff), iodine concentration (IC), and water concentration (WC) and calculated the slope of the spectral curve (K100keV). We compared the clinical findings and spectral CT parameters of both groups and performed receiver operating characteristic analysis to evaluate the diagnostic efficacy and the optimal cutoff values of the spectral CT parameters.

RESULTS

During the AP and VP, the CT70keV, Zeff, IC, and K100keV were significantly higher in patients with invasive TETs than those in patients with mediastinal lung cancer (p < 0.05). WC was not statistically significantly different between the two groups (p > 0.05). ROC curve analysis revealed that all quantitative parameters combined in the AP and VP provided the best diagnostic performance in identifying invasive TETs from mediastinal lung cancer (AUC = 0.88, p = 0.002, sensitivity = 0.89 and specificity = 0.77). The cutoff values in the AP for CT70keV, IC, Zeff, and K100keV to differentiate invasive TETs from mediastinal lung cancer were 75.55, 15.86, 8.45, and 1.71, respectively. The cutoff values in the VP for CT70keV, IC, Zeff, and K100keV to differentiate them were 67.06, 15.74, 8.50, and 1.81, respectively.

CONCLUSIONS

Spectral CT imaging has potential value in the differential diagnosis of invasive TETs and mediastinal lung cancer.

Development of a dual energy CT based model to assess response to treatment in patients with high grade serous ovarian cancer: a pilot cohort study

BACKGROUND

In patients with cancer, the current gold standard for assessing response to treatment involves measuring cancer lesions on computed tomography (CT) imaging. The percentage change in size of specific lesions determines whether patients have had a complete/partial response or progressive disease, according to RECIST criteria. Dual Energy CT (DECT) permits additional measurements of iodine concentration, a surrogate marker of vascularity. Here we explore the role of changes in iodine concentration within cancer tissue on CT scans to assess its suitability for determining treatment response in patients with high grade serous ovarian cancer (HGSOC).

METHODS

Suitable RECIST measurable lesions were identified from the CT images of HGSOC patients, taken at 2 different time points (pre and post treatment). Changes in size and iodine concentration were measured for each lesion. PR/SD were classified as responders, PD was classified as non-responder. Radiological responses were correlated with clinical and CA125 outcomes.

RESULTS

62 patients had appropriate imaging for assessment. 22 were excluded as they only had one DECT scan. 32/40 patients assessed (113 lesions) had received treatment for relapsed HGSOC. RECIST and GCIG (Gynaecologic Cancer Inter Group) CA125 criteria / clinical assessment of response for patients was correlated with changes in iodine concentration, before and after treatment. The prediction of median progression free survival was significantly better associated with changes in iodine concentration (p = 0.0001) and GCIG Ca125 / clinical assessment (p = 0.0028) in comparison to RECIST criteria (p = 0.43).

CONCLUSION

Changes in iodine concentration from dual energy CT imaging may be more suitable than RECIST in assessing response to treatment in patients with HGSOC.

TRIAL REGISTRATION

CICATRIx IRAS number 198179, 14 Dec 2015, https://www.myresearchproject.org.uk/ .

Use of dual-layer spectral detector computed tomography in the diagnosis of pancreatic neuroendocrine neoplasms

PURPOSE

To explore the optimal energy level of dual-layer spectral detector computed tomography (DLCT) images of pancreatic neuroendocrine neoplasms (pNENs) and investigate the value in their detection.

METHODS

This retrospective analysis included 134 pNEN patients with 136 lesions; they underwent contrast-enhanced DLCT scanning with histopathological confirmation of pNENs. Virtual monoenergetic images (VMI) of 40-100 keV, iodine concentration map (IC map), Z-effective atomic number map (Zeff map), and conventional images were analysed. The optimal energy level was obtained by comparing the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). The lesion detection rates of DLCT and conventional images were compared. Subjective image analysis was performed by two readers who assessed the image quality and lesion conspicuity on a 5-point scale.

RESULTS

The SNR of VMIs from 40 to 80 keV (arterial phase, P < 0.001; venous phase, P < 0.05) and CNR from 40 to 60 keV (arterial and venous phases, each P < 0.05) were higher than that of conventional images; VMI_40keV showed the highest SNR and CNR. There was a good inter-reader agreement between the two reviewers (Kappa values > 0.61); the scores of Zeff and IC maps were higher than those of conventional images and VMI_40keV (P < 0.05). The detection performance of DLCT images was better than conventional images.

CONCLUSIONS

The VMI_40keV demonstrated the best CNR and SNR of pNENs compared to other VMIs. Zeff and IC maps improve objective image quality and reader preference compared to conventional images. These findings could possess important clinical implications in formulating treatment strategies.

Spectral Computed Tomography-Derived Iodine Content and Tumor Response in the Follow-Up of Neuroendocrine Tumors-A Single-Center Experience

Spectral computed tomography (SCT) allows iodine content (IC) calculation for characterization of hypervascularized neoplasms and thus might help in the staging of neuroendocrine tumors (NETs). This single-center prospective study analyzed the association between SCT-derived IC and tumor response in the follow-up of metastasized NETs. Twenty-six patients with a median age of 70 years (range 51-85) with histologically proven NETs and a total of 78 lesions underwent SCT for staging. Because NETS are rare, no primary NET types were excluded. Lesions and intralesional hotspots were measured in virtual images and iodine maps. Tumor response was classified as progressive or nonprogressive at study endpoint. Generalized estimating equations served to estimate associations between IC and tumor response, additionally stratified by lesion location. Most commonly affected sites were the lymph nodes, liver, pancreas, and bones. Median time between SCT and endpoint was 64 weeks (range 5-260). Despite statistical imprecision in the estimate, patients with higher IC in lymphonodular metastases had lower odds for disease progression (adjusted OR = 0.21, 95% CI: 0.02-2.02). Opposite tendencies were observed in hepatic and pancreatic metastases in unadjusted analyses, which vanished after adjusting for therapy and primary tumor grade.

Value of CT spectral imaging in the differential diagnosis of sarcoidosis and Hodgkin's lymphoma based on mediastinal enlarged lymph node: A STARD compliant article

To investigate the imaging characteristics of sarcoidosis and Hodgkin's lymphoma based on mediastinal enlarged lymph node using spectral CT and evaluate whether the quantitative information can improve the differential diagnosis of these diseases. This retrospective study was approved by the institutional review board, and written informed consent was obtained from all patients. Overall, 21 patients with sarcoidosis and 39 patients with Hodgkin's lymphoma were examined with CT spectral imaging during the arterial phase (AP) and venous phase (VP). The CT values on 40 to 140 keV monochromatic images and iodine (water) concentrations of enlarged lymph nodes were obtained in AP and VP. Iodine concentrations (ICs) were normalized to the iodine concentration in the aorta. The differences in normalized iodine concentrations (NICs) and hounsfield units (HU) curve slop (λHU) were calculated. Anatomical distribution of mediastinal lymph nodes and morphologic features were also compared. Receiver operating characteristic curves were generated to help establish threshold values for the parameters required for the significant differentiation of sarcoidosis from lymphomas. The CT values on 40 to 100 keV monochromatic images in AP and 40 to 50 keV in VP were higher in sarcoidosis than those in Hodgkin's lymphoma, the differences were statistically significant (P < .05); NICs during the AP and λHU during the AP (VP) in patients with sarcoidosis differed significantly from those in patients with Hodgkin's lymphoma. Receiver operating characteristic curves analysis showed that the monochromatic CT value on 40 keV in AP had the highest sensitivity (71.4%) and specificity (100%) in differentiating sarcoidosis from Hodgkin's lymphoma. The anatomic distribution, coalescence, calcification, compression, enhancement pattern and enhancement degree of the mediastinal enlarged lymph node differed significantly between the groups (P < .05). The combination of monochromatic CT value, NICs and λHU had higher sensitivity and specificity than did those of conventional qualitative CT image analysis during the combined phases. CT spectral imaging has promising potential for the diagnostic differentiation of Hodgkin's lymphomas and sarcoidosis. The monochromatic CT value, iodine content and λHU could be valuable parameters for differentiating Hodgkin's lymphomas and sarcoidosis based on mediastinal enlarged lymph node.

Dual-energy CT based material decomposition to differentiate intrahepatic cholangiocarcinoma from hepatocellular carcinoma

PURPOSE

To assess the potential of material decomposition in dual-energy CT (DECT) to differentiate intrahepatic cholangiocarcinoma (iCCA) from hepatocellular carcinoma (HCC).

METHOD

In this retrospective study, we included 94 patients (26 female (27.7 %), median age 64.5 (interquartile range 55.5-74.5) years) with either iCCA or HCC who underwent abdominal contrast-enhanced DECT in arterial phase. To test for differences between iCCA (n = 47) and HCC (n = 47), we evaluated mean attenuation and DECT material density values including iodine density (ID), normalized iodine uptake (NIU), fat fraction, and lesion-to-liver parenchyma ratio. Histopathology served as reference standard for all lesions. We used univariate logistic regression models for the outcome iCCA versus HCC. ROC curve analysis was applied to assess discriminative ability of the model. Model accuracy was evaluated by calculating the Brier score. Youden index was applied to establish thresholds to differentiate between iCCA and HCC.

RESULTS

Comparison of quantitative image parameters revealed significant differences between iCCA and HCC for ID (1.6 ± 0.5 mg/ml vs 2.8 ± 0.8 mg/ml, p < 0.001), NIU (14.5 ± 4.8 vs 24.8 ± 10.3, p < 0.001), attenuation (41.9 ± 10.1 HU vs 47.9 ± 8.9 HU, p = 0.003), and fat fraction (12.0 ± 7.8 % vs 9.0 ± 6.4 %, p = 0.045). ROC curve analysis revealed highest ability to differentiate iCCA from HCC for ID (AUC = 0.93, 95 % CI 0.89-0.98). For ID, an optimal threshold of 2.33 mg/dl was determined to discriminate between iCCA and HCC (sensitivity 89.4 %, specificity 76.6 %).

CONCLUSIONS

DECT-based iodine quantification can serve as a tool for the differentiation of iCCA and HCC in contrast-enhanced CT. ID yielded the highest diagnostic performance and may assist in clinical routine CT diagnostics.

Pre-treatment spectral CT combined with CT perfusion can predict hemorrhagic transformation after thrombolysis in patients with acute ischemic stroke

OBJECTIVE

To investigate the value of pre-treatment spectral CT angiography (CTA) in predicting hemorrhagic transformation (HT) after intravenous thrombolysis (IVT) treatment in acute ischemic stroke (AIS) patients.

MATERIALS AND METHODS

AIS patients who underwent IVT with recombinant tissue plasminogen activator and pre-treatment head and neck spectral CTA and head CT perfusion (CTP) from January 2018 to June 2020 were reviewed retrospectively. Finally, 20 patients were included in the HT group and 22 age-matched patients were included in the non-HT group. Spectral and CTP parameters of the region of interest on pre-treatment CTA axial raw images and CTP images, including the infarct core (IC) and ischemic penumbral (IP) regions, were recorded. The differences in clinical variables, CTP, collateral scores and spectral parameters between the two groups were analyzed. Three multivariate logistic regression models were then developed, where model 1 included clinical and spectral parameters, model 2 included clinical and CTP parameters and a combined model included clinical, CTP, and spectral parameters. Receiver operating characteristic analysis was used to evaluate the performance of the multivariate model.

RESULTS

Patients with HT had higher Safe Implementation of Treatments in Stroke (SITS) score (p = 0.023), the volume of perfusion lesions (p = 0.005), the volume of IP (p = 0.003), the mean transit time (MIT) in the IC area (p = 0.012), as well as the TTP in IP area (p = 0.015) compared with patients without HT. The HT group showed significantly lower CBF in the IC area (p = 0.019), iodine concentration (p = 0.017) and the effective atomic number (p = 0.024) in the IP area than non-HT group. And the slope of the spectral curve of the HT group in the IP region was larger than that of the non-HT group (p = 0.023). Gender, age, SITS score, the volume of entire perfusion lesion, CBF and MIT in the IC area, TTP in the IP area, as well as iodine concentration in the IP area were included in the final multivariate model for predicting HT. And CBF in the IC area (OR = 0.779, 95 % CI:0.609-0.996, p = 0.046) as well as the iodine concentration of IP area (OR = 0.343, 95 % CI: 0.131-0.901, p = 0.030) were proved to be independent predictors for HT. The combined model including clinical, spectral, and CTP parameters, showed improved accuracy compared to the other two models, while the Delong test did not suggest a statistically significant difference (both p values > 0.05).

CONCLUSIONS

The iodine concentration of IP area derived from pre-treatment spectral CTA was an independent predictor of HT after IVT treatment for AIS patients. Moreover, multivariate models combined with clinical, spectral, and CTP parameters may be able to predict HT.

Quantitative Intracerebral Iodine Extravasation in Risk Stratification for Intracranial Hemorrhage in Patients with Acute Ischemic Stroke

BACKGROUND AND PURPOSE

Intracerebral hemorrhage poses a severe threat to the outcomes in patients with postthrombectomy acute stroke. We aimed to compare the absolute intracerebral iodine concentration and normalized iodine concentration ratio in predicting intracerebral hemorrhage in patients postthrombectomy.

MATERIALS AND METHODS

Patients with acute anterior circulation large-vessel occlusion who underwent mechanical thrombectomy and had successful recanalization were retrospectively included in the study. Dual-energy CT was performed within 1 hour after mechanical thrombectomy. Postprocessing was performed to measure the absolute intracerebral iodine concentration and the normalized iodine concentration ratio. The correlation between the absolute intracerebral iodine concentration and the normalized iodine concentration ratio was analyzed using the Spearman rank correlation coefficient. We compared the area under the receiver operating characteristic curve of the absolute intracerebral iodine concentration and the normalized iodine concentration ratio using the DeLong test.

RESULTS

We included 138 patients with successful recanalization. Of 43 patients who did not have parenchymal contrast staining on postthrombectomy dual-energy CT, 5 (11.6%) developed intracerebral hemorrhage. Among patients (95/138, 68.8%) with parenchymal contrast staining, 37 (38.9%, 37/95) developed intracerebral hemorrhage. The absolute intracerebral iodine concentration was significantly correlated with the normalized iodine concentration ratio (ρ = 0.807; 95% CI, 0.718-0.867; P < .001). The cutoffs of the normalized iodine concentration ratio and absolute intracerebral iodine concentration for identifying patients with intracerebral hemorrhage development were 222.8%, with a sensitivity of 67.6% and specificity of 76.4%, and 2.7 mg I/mL, with a sensitivity of 75.7% and specificity of 65.5%, respectively. No significant difference was found between the areas under the receiver operating characteristic curve for the absolute intracerebral iodine concentration and the normalized iodine concentration ratio (0.753 versus 0.738) (P = .694).

CONCLUSIONS

The hemorrhagic transformation predictive power of the normalized iodine concentration ratio is similar to that of the absolute intracerebral iodine concentration in patients with successful recanalization.

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.

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

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

Predicting axillary lymph node metastasis in breast cancer using the similarity of quantitative dual-energy CT parameters between the primary lesion and axillary lymph node

PURPOSE

To evaluate the similarity of quantitative dual-energy computed tomography (DECT) parameters between the primary breast cancer lesion and axillary lymph node (LN) for predicting LN metastasis.

MATERIALS AND METHODS

This retrospective study included patients with breast cancer who underwent contrast-enhanced DECT between July 2019 and April 2021. Relationships between LN metastasis and simple DECT parameters, similarity of DECT parameters, and pathological and morphological features were analyzed. ROC curve analysis was used to evaluate diagnostic ability.

RESULTS

Overall, 137 LNs (39 metastases and 98 non-metastases) were evaluated. Significant differences were observed in some pathological (nuclear grade, estrogen receptor status, and Ki67 index) and morphological characteristics (shortest and longest diameters of the LN, longest-to-shortest diameter ratio, and hilum), most simple DECT parameters, and all DECT similarity parameters between the LN metastasis and non-metastasis groups (all, P < 0.001-0.004). The shortest diameter of the LN (odds ratio 2.22; 95% confidence interval 1.47, 3.35; P < 0.001) and the similarity parameter of 40-keV attenuation (odds ratio, 2.00; 95% confidence interval 1.13, 3.53; P = 0.017) were independently associated with LN metastasis compared to simple DECT parameters of 40-keV attenuation (odds ratio 1.01; 95% confidence interval 0.99, 1.03; P =0.35). The AUC value of the similarity parameters for predicting metastatic LN was 0.78-0.81, even in cohorts with small LNs (shortest diameter < 5 mm) (AUC value 0.73-0.78).

CONCLUSION

The similarity of the delayed-phase DECT parameters could be a more useful tool for predicting LN metastasis than simple DECT parameters in breast cancer, regardless of LN size.

Radiomics Analysis on Noncontrast CT for Distinguishing Hepatic Hemangioma (HH) and Hepatocellular Carcinoma (HCC)

Background

To form a radiomic model on the basis of noncontrast computed tomography (CT) to distinguish hepatic hemangioma (HH) and hepatocellular carcinoma (HCC).

Methods

In this retrospective study, a total of 110 patients were reviewed, including 72 HCC and 38 HH. We accomplished feature selection with the least absolute shrinkage and operator (LASSO) and built a radiomics signature. Another improved model (radiomics index) was established using forward conditional multivariate logistic regression. Both models were tested in an internal validation group (38 HCC and 21 HH).

Results

The radiomic signature we built including 5 radiomic features demonstrated significant differences between the hepatic HH and HCC groups (P < 0.05). The improved model demonstrated a higher net benefit based on only 2 radiomic features. In the validation group, radiomics signature and radiomics index achieved great diagnostic performance with AUC values of 0.716 (95% confidence interval (CI): 0.581, 0.850) and 0.870 (95% CI: 0.782, 0.957), respectively.

Conclusions

Our developed radiomics-based model can successfully distinguish HH and HCC patients, which can help clinical decision-making with lower cost.

Dual-Energy CT of the Abdomen: Radiology In Training

A 61-year-old man with an esophageal cancer diagnosis underwent staging dual-energy CT of the chest and abdomen in the portal venous phase after contrast media administration. Aside from the primary tumor and suspicious local lymph nodes, CT revealed hypoattenuating ambiguous liver lesions, an incidental right adrenal nodule, and a right renal lesion with soft-tissue attenuation. In addition, advanced atherosclerosis of the abdominal aorta and its major branches was noted. This article provides a case-based review of dual-energy CT technologies and their applications in the abdomen. The clinical utility of virtual monoenergetic images, virtual unenhanced images, and iodine maps is discussed.

Radiomics nomogram based on dual-energy spectral CT imaging to diagnose low bone mineral density

Background

Osteoporosis is associated with a decrease of bone mineralized component as well as a increase of bone marrow fat. At present, there are few studies using radiomics nomogram based fat-water material decomposition (MD) images of dual-energy spectral CT as an evaluation method of abnormally low Bone Mineral Density (BMD). This study aims to establish and validate a radiomics nomogram based the fat-water imaging of dual-energy spectral CT in diagnosing low BMD.

Methods

Ninety-five patients who underwent dual-energy spectral CT included T11-L2 and dual x-ray absorptiometry (DXA) were collected. The patients were divided into two groups according to T-score, normal BMD(T ≥ -1) and abnormally low BMD (T < -1). Radiomic features were selected from fat-water imaging of the dual-energy spectral CT. Radscore was calculated by summing the selected features weighted by their coefficients. A nomogram combining the radiomics signature and significant clinical variables was built. The ROC curve was performed to evaluate the performance of the model. Finally, we used decision curve analysis (DCA) to evaluate the clinical usefulness of the model.

Results

Five radiomic features based on fat-water imaging of dual-energy spectral CT were constructed to distinguish abnormally low BMD from normal BMD, and its differential performance was high with an area under the curve (AUC) of 0.95 (95% CI, 0.89–1.00) in the training cohort and 0.97 (95% CI, 0.91–1.00) in the test cohort. The radiomics nomogram showed excellent differential ability with AUC of 0.96 (95%CI, 0.91–1.00) in the training cohort and 0.98 (95%CI, 0.93–1.00) in the test cohort, which performed better than the radiomics model and clinics model only. The DCA showed that the radiomics nomogram had a higher benefit in differentiating abnormally low BMD from normal BMD than the clinical model alone.

Conclusion

The radiomics nomogram incorporated radiomics features and clinical factor based the fat-water imaging of dual-energy spectral CT may serve as an efficient tool to identify abnormally low BMD from normal BMD well.

Dual-Energy Computed Tomography for Evaluation of Breast Cancer Follow-Ups: Comparison of Virtual Monoenergetic Images and Iodine-Map

Differentiating tumor tissue from dense breast tissue can be difficult. Dual-energy CT (DECT) could be suitable for making diagnoses at breast cancer follow-ups. This study investigated the contrast in DECT images and iodine maps for patients with breast cancer being followed-up. Chest CT images captured in 2019 were collected. Five cases of metastatic breast cancer in the lungs were analyzed; the contrast-to-noise ratio (for breast tissue and muscle: CNRb and CNRm, respectively), tumor-to-breast mammary gland ratio (T/B), and tumor-to-muscle ratio (T/M) were calculated. For 84 cases of no metastasis, monochromatic spectral and iodine maps were obtained to compare differences under various breast densities using the K-means algorithm. The optimal T/B, T/M, and CNRb (related to mammary glands) were achieved for the 40-keV image. Conversely, CNRm (related to lungs) was better for higher energy. The optimal balance was achieved at 80 keV. T/B, T/M, and CNR were excellent for iodine maps, particularly for density > 25%. In conclusion, energy of 80 keV is the parameter most suitable for observing the breast and lungs simultaneously by using monochromatic spectral images. Adding iodine mapping can be appropriate when a patient’s breast density is greater than 25%.

An assessment of liver lesions using a combination of CEUS LI-RADS and AFP

PURPOSE

To improve noninvasive diagnosis of HCC using a combination of CE US LI-RADS and alpha-fetoprotein (AFP).

METHODS

757 solitary liver nodules from 757 patients at risk of HCC with CE US and serum AFP test were categorized as LR-1 to LR-5 through LR-M according to CE US LI-RADS version 2017. In LR-3, LR-4, and LR-M nodules, those with AFP > 200 ng/ml were reclassified as mLR-5. Nodules with LR-5 and mLR-5 were reclassified as definitely HCC to modify CE US LI-RADS. Diagnostic performance was assessed with specificity, sensitivity, and PPV.

RESULTS

The sensitivity, specificity, and PPV of LR-5 as a predictor of HCC were 64.7%, 97.8%, and 98.9%, respectively. 32.1% patients with solitary liver nodule had AFP greater than 200 ng/ml, of which 98.8% were HCC (25.8%, 7.5%, 2.5% assigned to LR-M, LR-4, LR-3, respectively) and 1.2% were Combined Hepatocellular Cholangiocarcinoma. After modification, the sensitivity increased to 79.6% (P < 0.001), while specificity and PPV remained high (96.6% and 98.7%, P > 0.050).

CONCLUSION

The combination of CE US LI-RADS and AFP for diagnosing HCC improved diagnostic sensitivity significantly, while maintaining high PPV and specificity in patients with the solitary liver nodule.

A sonographic software program, Fluctuational Imaging, for diagnosis of hepatic hemangioma

Hepatic hemangioma is the most common benign solid lesion of the liver. Contrast-enhanced computed tomography or magnetic resonance imaging is recommended for definitive diagnosis of hepatic hemangioma. However, these modalities have drawbacks in terms of radiation exposure, invasiveness, and high cost for examination. “Fluttering sign” is one of the candidate findings considered specific for hepatic hemangioma that can be useful for diagnosis of hepatic hemangioma using grayscale US alone. However, the assessment is subjective and the findings are weak and likely to be overlooked in some cases. We developed a software program, Fluctuational Imaging, for objective detection and depiction of “fluttering sign”. Here, we evaluated the ability of Fluctuational Imaging software to depict “fluttering sign” in hepatic hemangioma. Presence or absence of “fluttering sign” was evaluated in the grayscale US videos and Fluctuational Imaging software analysis results of patients with hepatic hemangioma. The Cohen’s kappa test showed very good agreement (0.95). Fluctuational Imaging software can detect and depict the phenomenon of “fluttering sign” well and may be a useful tool for diagnosis of hepatic hemangioma.

Contrast-enhanced US diagnostic algorithm of hepatocellular carcinoma in patients with occult hepatitis B

PURPOSE

To assess the diagnostic performance of contrast-enhanced (CE) US Liver Imaging Reporting and Data System (LI-RADS) version 2017 and propose a diagnostic algorithm in diagnosing hepatocellular carcinoma (HCC) in patients with occult HBV infection (OBI).

METHODS

251 OBI patients with 251 newly diagnosed focal liver lesions were retrospectively enrolled. Each nodule was evaluated according to CEUS LI-RADS. The subgroup analyses were also performed in patients with alpha-fetoprotein (AFP) more than 20ug/L or not. Diagnostic performance of CEUS LI-RADS for diagnosing HCC was validated via sensitivity, specificity, accuracy, positive predictive value (PPV), and negative predictive value (NPV), respectively.

RESULTS

There were 90 HCCs (90 of 251, 35.9%), of which 2 (2.0%), 53 (53.5%), and 35 (35.4%) were classified as LR-4, LR-5, and LR-M, respectively. The sensitivity, specificity, accuracy, PPV, and NPV of CEUS LR-5 for HCC diagnosis were 58.9%, 88.8%, 78.1%, 74.6%, and 79.4%, respectively. AFP increased in 50.6% (45/89) HCCs. Using a proposed diagnostic algorithm (for OBI patients with AFP more than 20 ug/L, LR-5 nodules were diagnosed as definitely HCC), the sensitivity, specificity, accuracy, PPV, and NPV were 62.2%, 71.4%, 63.5%, 93.3%, and 22.7%, respectively. Therefore, 12.2% (30 of 246) nodules could be confirmed as HCC by CEUS without biopsy.

CONCLUSION

HCC diagnosis in patients with OBI is challenging. However, using LR-5 as a noninvasively diagnostic standard in OBI patients with AFP more than 20ug/L, HCC could be confirmed by CEUS without biopsy.

Utility of Dual-Energy CT in Abdominal Interventions

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

Dual-Energy Computed Tomography Imaging in Early-Stage Hepatocellular Carcinoma: A Preliminary Study

Background

This study aims to evaluate the application of dual-energy computed tomography (DECT) for multiparameter quantitative measurement in early-stage hepatocellular carcinoma (HCC).

Methods

The study retrospectively enrolled 30 patients with early-stage HCC and 43 patients with early-stage HCC who received radiofrequency ablation (RFA) and underwent abdomen enhanced CT scans in GSI mode. The GSI viewer was used for image display and data analysis. The regions of interest (ROIs) were delineated in the arterial phase and the venous phase. The optimal single energy value, CT values on different energy levels (40 keV, 70 keV, 100 keV, and 140 keV), the optimal energy level, the slope of the spectral attenuation curve, the effective atomic number (Z_eff), iodine concentration (IC), water concentration (WC), normalized iodine concentration (NIC), and normalized water concentration (NWC) are measured and quantitatively analyzed.

Results

The CT values of early-stage HCC at different single energy levels in dual phases were significantly different, and the single energy values were negatively correlated with the CT values. In the arterial phase and the venous phase, the optimal energy values for the best contrast-to-noise ratio were (68.34 ± 3.20) keV and (70.14 ± 2.01) keV, respectively. The slope of the spectral attenuation curve showed a downward trend at 40 keV, 70 keV, 100 keV, and 140 keV, but there was no statistically significant difference (P > 0.05). Z_eff was positively correlated with IC and standardized IC, but has no significant correlation with WC and NWC in dual phases.

Conclusion

DECT imaging contains multiparameter information and has different application values for early-stage HCC, and it is necessary to select the parameters reasonably for personalized and comprehensive evaluation.

Predicting Response to Systemic Chemotherapy for Advanced Gastric Cancer Using Pre-Treatment Dual-Energy CT Radiomics: A Pilot Study

Objective

To build and assess a pre-treatment dual-energy CT-based clinical-radiomics nomogram for the individualized prediction of clinical response to systemic chemotherapy in advanced gastric cancer (AGC).

Methods

A total of 69 pathologically confirmed AGC patients who underwent dual-energy CT before systemic chemotherapy were enrolled from two centers in this retrospective study. Treatment response was determined with follow-up CT according to the RECIST standard. Quantitative radiomics metrics of the primary lesion were extracted from three sets of monochromatic images (40, 70, and 100 keV) at venous phase. Univariate analysis and least absolute shrinkage and selection operator (LASSO) were used to select the most relevant radiomics features. Multivariable logistic regression was performed to establish a clinical model, three monochromatic radiomics models, and a combined multi-energy model. ROC analysis and DeLong test were used to evaluate and compare the predictive performance among models. A clinical-radiomics nomogram was developed; moreover, its discrimination, calibration, and clinical usefulness were assessed.

Result

Among the included patients, 24 responded to the systemic chemotherapy. Clinical stage and the iodine concentration (IC) of the tumor were significant clinical predictors of chemotherapy response (all p < 0.05). The multi-energy radiomics model showed a higher predictive capability (AUC = 0.914) than two monochromatic radiomics models and the clinical model (AUC: 40 keV = 0.747, 70 keV = 0.793, clinical = 0.775); however, the predictive accuracy of the 100-keV model (AUC: 0.881) was not statistically different (p = 0.221). The clinical-radiomics nomogram integrating the multi-energy radiomics signature with IC value and clinical stage showed good calibration and discrimination with an AUC of 0.934. Decision curve analysis proved the clinical usefulness of the nomogram and multi-energy radiomics model.

Conclusion

The pre-treatment DECT-based clinical-radiomics nomogram showed good performance in predicting clinical response to systemic chemotherapy in AGC, which may contribute to clinical decision-making and improving patient survival.

Multiparametric dual-energy CT to differentiate stage T1 nasopharyngeal carcinoma from benign hyperplasia

Background

Stage T1 nasopharyngeal carcinoma (NPC_T1) and benign hyperplasia (BH) are 2 common causes of nasopharyngeal mucosa/submucosa thickening without specific clinical symptoms. The treatment management of these 2 entities is significantly different. Reliable differentiation between the 2 entities is critical for the treatment decision and prognosis of patients. Therefore, our study aims to explore the optimal energy level of noise-optimized virtual monoenergetic images [VMI (+)] derived from dual-energy computed tomography (DECT) to display NPC_T1 and BH and to explore the clinical value of DECT for differentiating these 2 diseases.

Methods

A total of 91 patients (44 NPC_T1, 47 BH) were enrolled. The demarcation of the lesion margins and overall image quality, noise, contrast-to-noise ratio (CNR), and signal-to-noise ratio (SNR) were evaluated for 40-80 kiloelectron volts (keV) VMIs (+) and polyenergetic images in the contrast-enhanced phase. Image features were assessed in the contrast-enhanced images with optimal visualization of NPC_T1 and BH. The demarcation of NPC_T1 and BH in iodine-water maps was also assessed. The contrast-enhanced images were used to calculate the slope of the spectral Hounsfield unit curve (λ_HU) and normalized iodine concentration (NIC). The nonenhanced phase images were used to calculate the normalized effective atomic number (NZ_eff). The attenuation values on 40-80 keV VMIs (+) in the contrast-enhanced phase were recorded. The diagnostic performance was assessed using receiver operating characteristic (ROC) curve analysis.

Results

The 40 keV VMI (+) in the enhanced phase yielded higher demarcation of the lesion margins scores, overall image quality scores, noise, SNR, and CNR values than 50-80 keV VMIs (+) and polyenergetic images. NPC_T1 yielded higher attenuation values on VMI (+) at 40 keV (A₄₀), NIC, λ_HU, and NZ_eff values than BH. The multivariate logistic regression model combining image features (tumor symmetry) with quantitative parameters (A₄₀, NIC, λ_HU, and NZ_eff) yielded the best performance for differentiating the 2 diseases (AUC: 0.963, sensitivity: 89.4%, specificity: 93.2%).

Conclusions

The combination of DECT-derived image features and quantitative parameters contributed to the differentiation between NPC_T1 and BH.

A prospective study of dual-energy computed tomography for differentiating metastatic and non-metastatic lymph nodes of colorectal cancer

Background

Colorectal cancer (CRC) is the third most common malignancy worldwide, and lymph node metastasis is considered to be a risk factor for local recurrence and a poor prognosis in colorectal cancer. However, there remains a lack of reliable and non-invasive biomarkers to identify the lymph node status of CRC patients preoperatively. The purpose of this study was to explore the ability of dual-energy computed tomography (DECT) to differentiate metastatic from non-metastatic lymph nodes in colorectal cancer.

Methods

Seventy-one patients with primary colorectal cancer underwent contrast-enhanced dual-energy computed tomography imaging preoperatively. The colorectal specimen was scanned postoperatively, and lymph nodes were matched to the pathology report. The following dual-energy computed tomography quantitative parameters were analyzed: dual-energy curve slope value (λ_HU), standardized iodine concentration (n△HU), iodine water ratio (nIWR), electron density value (nρ_eff), and effective atom-number (nZ), based on metastatic and non-metastatic lymph node differentiation. Also, sensitivity and specificity analyses were performed using receiver operating characteristic curves.

Results

In all patients, one hundred and fifty lymph nodes, including 66 non-metastatic and 84 metastatic lymph nodes, were matched using the radiological-pathological correlation. Metastatic nodes had significantly greater λ_HU, n△HU, and nIWR values than non-metastatic nodes in both the arterial and venous phases (P<0.01). The area under curve (AUC), sensitivity, and specificity were 0.80, 80%, and 66% for λ_HU; 0.86, 70%, and 95% for n△HU; and 0.88, 71%, and 95% for nIWR in the arterial phase. There was no significant difference in electron density and effective Z values between metastatic and non-metastatic lymph nodes.

Conclusions

DECT quantitative parameters may help differentiate between metastatic and normal lymph nodes in patients with CRC.

Spectral detector CT applications in advanced liver imaging

OBJECTIVE

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

CONCLUSION

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

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

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

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

BACKGROUND AND AIMS

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Material decomposition using iodine quantification on spectral CT for characterising nodules in the cirrhotic liver: a retrospective study

Background

There is limited scientific evidence on the potential of spectral computed tomography (SCT) for differentiation of nodules in the cirrhotic liver. We aimed to assess SCT-generated material density (MD) parameters for nodule characterisation in cirrhosis.

Methods

Dynamic dual-energy SCT scans of cirrhotic patients performed over 3 years were retrospectively reviewed. They were classified as hepatocellular carcinoma (HCC), regenerative or indeterminate, according to the European Association for the Study of the Liver criteria. MD maps were generated to calculate the area under the curve (AUC) and cutoff values to discriminate these nodules in the hepatic arterial phase (HAP) and portal venous phase (PVP). MD maps included iodine concentration density (ICD) of the liver and nodule, lesion-to-normal liver ICD ratio (LNR) and difference in nodule ICD between HAP and PVP.

Results

Three hundred thirty nodules belonging to 300 patients (age 53.0 ± 12.7 years, mean ± standard deviation) were analysed at SCT (size 2.3 ± 0.8 cm, mean ± SD). One hundred thirty-three (40.3%) nodules were classified as HCC, 147 (44.5%) as regenerative and 50 (15.2%) as indeterminate. On histopathology, 136 (41.2%) nodules were classified as HCC, 183 (55.5%) as regenerative and 11 (3.3%) as dysplastic. All MD parameters on HAP and the nodule  difference in ICD could discriminate pathologically proven HCC or potentially malignant nodules from regenerative nodules (p < 0.001). The AUC was 82.4% with a cutoff > 15.5 mg/mL for nodule ICD, 81.3% > 1.8 for LNR-HAP and 81.3% for difference in ICD > 3.5 mg/mL.

Conclusion

SCT-generated MD parameters are viable diagnostic tools for differentiating malignant or potentially malignant from benign nodules in the cirrhotic liver.

Supplementary Information

The online version contains supplementary material available at 10.1186/s41747-021-00220-6.

Hepatic parenchyma and vascular blood flow changes after TIPS with spectral CT iodine density in HBV-related liver cirrhosis

To compare changes in spectral CT iodine densities of hepatic parenchyma and vessels before and after transjugular intrahepatic portosystemic shunt (TIPS) in hepatitis B virus (HBV)-related liver cirrhosis. Twenty-five patients with HBV-related liver cirrhosis who received TIPS for gastroesophageal varices bleeding were recruited. Each patient underwent three phases contrast CT before and after TIPS within 4 weeks, with the raw data reconstructed at 1.25-mm-thick slices. Iodine density (in milligrams per milliliter) was measured on iodine-based material decomposition image. Multiple regions of interest (ROIs) in liver parenchyma, aorta and portal vein were selected from three slices of images. Portal vein trunk was set as the central one, and mean liver parenchymal iodine densities from arterial phase (AP), venous phase (VP) and equilibrium phase (EP) were recorded. Quantitative indices of iodine density (ID), including normalized ID in liver parenchyma for arterial phase (NIDLAP), ID of liver parenchyma for venous phase (IDLVP), ID of portal vein in venous phase (IDPVP) and liver arterial iodine density fraction (AIF), were measured and compared before and after TIPS. Based on Child–Pugh stage, 4, 12 and 9 patients were classified as grade A, B, and C, respectively. Liver volume was comparable before and after TIPS (1110.5 ± 287.4 vs. 1092.0 ± 276.3, P = 0.28). After TIPS, ID was decreased in aorta (146.0 ± 34.5 vs. 120.9 ± 30.7, P < 0.01) whereas increased in liver parenchyma at arterial phase, as demonstrated by IDAP (9.3 ± 3.1 vs. 13.4 ± 4.4 mg/mL) and AIF (0.40 ± 0.11 vs. 0.58 ± 0.11, P < 0.01). For venous or equilibrium phase, quantitative indices remained stable (23.1 ± 4.5 vs. 23.0 ± 5.3, 19.8 ± 4.1 vs. 19.4 ± 4.6) mg/mL (Ps > 0.05). For portal vein, ID and NID were increased after TIPS (23.1 ± 11.7 vs. 36.5 ± 13.0, 16.4 ± 8.5 vs. 31.8 ± 12.8) (P < 0.01). No positive correlation between iodine density and preoperative Child–Pugh score was observed. Based on iodine density measurement, spectral CT as a noninvasive imaging modality may assess hepatic parenchyma and vascular blood flow changes before and after TIPS in HBV-related liver cirrhosis.

Clinical registration number: ChiCTR- DDC-16009986.

The value of a dual-energy spectral CT quantitative analysis technique in acute pancreatitis

AIM

To explore the value of dual-energy spectral computed tomography (DESCT) in evaluating the clinical severity of acute pancreatitis.

MATERIALS AND METHODS

Seventy patients with acute pancreatitis (AP) confirmed by clinical examination were included in this study. All patients underwent unenhanced/double-phase enhanced CT in spectral imaging mode. Iodine concentration and normalised iodine concentration (NIC) were measured retrospectively with a spectral imaging viewer (GSI Viewer). All data were analysed by analysis of variance. Receiver operating characteristic (ROC) curves were constructed to determine the optimal threshold for predicting the clinical severity of AP.

RESULTS

Seventy patients were included in the study comprising 30 mild, 22 moderate, and 18 severe cases of AP. The CT attenuation value, iodine concentration, and NIC were decreased with increasing clinical severity. Moreover, there were significant differences between the mild group and the severe group (p<0.05), as well as between the moderate group and the severe group (p<0.05). The area under the ROC curve AUC of each value was larger in arterial phase than in portal venous phase. The most sensitive value between the mild and severe groups in AP was the NIC (arterial phase: 0.19 ± 0.06; portal venous phase: 0.45 ± 0.09).

CONCLUSION

DESCT can provide multiple parameters to determine the severity of AP.

Spectral CT in clinical routine imaging of neuroendocrine neoplasms

AIM

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

MATERIAL AND METHODS

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

RESULTS

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

CONCLUSION

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

Rapid-kilovoltage-switching dual-energy computed tomography (CT) for differentiating spinal osteolytic metastases from spinal infections

Background

Rapid-kilovoltage-switching dual-energy computed tomography (RDECT) is a non-invasive, alternative technique for quantitative diagnosis. This study aimed to investigate the value of RDECT for differentiating spinal osteolytic metastases (SOM) from spinal infections (SIs).

Methods

RDECT was performed on 29 patients with SOM and 18 patients with SIs. Both iodine-based and water-based material decomposition images were generated from the spectral CT scan. The iodine/water densities of lesions on iodine/water material-decomposition images and the CT attenuation values on traditional CT images were measured three times at different image levels, and the averages were calculated. The lesion-to-muscle ratio (LMR) and lesion-to-artery ratio (LAR) for iodine density measurements were calculated. All parameters were compared between the two groups using the two-tailed Student's t-test. A P value <0.05 was considered statistically significant. The sensitivity and specificity for differentiating SOM from SIs were determined using receiver operating characteristic curves (ROC).

Results

Iodine density, LMR, and LAR during the arterial phase (AP) and venous phase (VP) were all significantly higher for SOM than for SIs (all P<0.05). The water densities and traditional CT attenuation values during the AP and VP were not significantly different between the two groups. For ROC analysis, LAR during the VP (LAR_VP) showed the best diagnostic performance, with an area under the ROC curve (AUC) value of 0.862. When the LARVP was 0.54, the sensitivity was 82.80% and the specificity was 77.80% for differentiating SOM from SIs.

Conclusions

RDECT can provide additional information that may be useful for differentiating atypical SOM from SIs.

Pancreatic Neuroendocrine Neoplasms: CT Spectral Imaging in Grading

RATIONALE AND OBJECTIVES

The purpose of this study was to define the CT spectral imaging characteristics of pancreatic neuroendocrine neoplasms (PNENs) and evaluate their potential for differential diagnosis of nonlow grade (non-LG) PNENs from low grade (LG) PNENs.

MATERIALS AND METHODS

CT spectral imaging data of 54 pathologically proven PNENs were retrospectively reviewed. Patients were divided into two groups: 40 cases with grade 1 in LG PNENs group and 14 cases with grade 2 and grade 3 in non-LG PNENs group.

RESULTS

Gender, calcification, inhomogeneity, invasiveness, PD dilatation, lymph node enlargement, size, normalized iodine (water) concentration in arterial phase (AP) (Iodine (ap)), normalized effective-Z (Z_ap), slope of normalized CT spectral curves in both AP, and portal venous phase were found to be significant variables for differentiating non-LG PNENs from LG PNENs (p < 0.05). Non-LG PNENs had larger size and lower Z_ap and Iodine (ap) than LG PNENs. The tumor size, Z_ap and Iodine (ap) had fair to good diagnostic performance with the area under receiver-operating-characteristic curve (AUC) 0.843, 0.733, and 0.728, respectively. Multivariate analysis with logistic regression had higher AUC (p<0.05) than all the single parameters except for size.

CONCLUSION

There were significant differences in CT spectral imaging parameters between non-LG and LG PNENs. Tumor size was the most promising independent parameter and the combination of quantitative parameters with qualitative parameters is the best predictor in differentiating of non-LG PNENs from LG PNENs. CT spectral imaging can help determine the malignancy of PNENs, which can better assist in surgical planning.

Quantitative spectral CT evaluation of kidney tumors with the stretched-exponential nonlinear regression analysis model

Background

This study aimed to use the stretched-exponential nonlinear regression analysis model to explore the value of the energy spectral curve in the differential diagnosis of clear cell renal cell carcinoma (ccRCC), minimal fat renal angiomyolipoma (RAML), and hypovascular renal cell carcinoma.

Methods

Sixty-five cases with renal tumors were enrolled retrospectively who had undergone a preoperative multiphase spectral CT scan of the kidney in pre-enhance and double-phase enhanced scanning. The normalized iodine concentrations (NIC) of these lesions, normal renal cortex, and psoas major were measured and calculated. The spectral curves of these lesions and normal tissues were analyzed to calculate the stretched-exponential index (α) and b value with the stretched-exponential nonlinear regression analysis model (y=-b·X^α). The differences between α, b value, and NIC of these lesions and normal tissues in pre-enhance and two enhanced phases were compared using one-way ANOVA. The correlation between α, b value, and NIC was evaluated using the Pearson coefficient test, with significance assigned at the 5% level.

Results

There was no significant difference in α value between the groups in pre-enhance scanning. In the Cortical phase (CP), there were no significant differences in NIC and α value between minimal fat RAML and hypovascular renal cell carcinoma, or between ccRCC and the normal renal cortex. However, in the nephrographic phase (NP), a significant difference in α value was found between minimal fat RAML and hypovascular renal cell carcinoma, but no difference in NIC between them. In NP, there were significant differences in NIC and α values between ccRCC and the normal renal cortex. In CP and NP, there were significant differences between the psoas major and other groups in all parameters. For b value, in pre-enhance scanning, there was a significant difference between the psoas major and other groups, and between ccRCC and the normal renal cortex. There was no significant difference between other groups. After enhancement, in CP and NP, significant differences were observed between the psoas major and other groups in b value, but no significant differences were observed between all renal tumors and the normal renal cortex. A linear correlation was found between α values and NIC in CP (r=0.780, P=0.00) and NP (r=0.693, P=0.00). The b values and NIC had a low correlation in CP, with no correlation in NP.

Conclusions

Quantitative spectral CT with the stretched-exponential nonlinear regression analysis model may enhance the differential diagnosis ability for renal tumors. Its clinical value remains to be further explored in other types of soft tissue lesions.

Comparison of spectral computed tomography imaging parameters between squamous cell carcinoma and adenocarcinoma at the gastroesophageal junction

OBJECTIVE

To compare the spectral computed tomography (CT) imaging parameters between squamous cell carcinoma (SCC) and adenocarcinoma (AC) at the gastroesophageal junction (GEJ).

METHODS

A total of 80 patients were enrolled in this retrospective study. Among them, 35 were diagnosed with SCC (SCC group) and 45 were diagnosed with AC (AC group). All patients underwent an enhanced scan with spectral CT. The following CT imaging parameters were evaluated: iodine concentration (IC), water content (WC), effective atomic number (Eff-Z) and slope of the spectral HU curve (λHU) of lesions. Receiver operating characteristic (ROC) curve was used to analyze the predictive value of spectral CT imaging parameters for diagnosis of SCC and AC.

RESULTS

Patients with SCC had lower IC, Eff-Z, and λHU in arterial phase and venous phase compared with AC (p< 0.05). There were no significant differences in WC between the two groups. ROC curve analyses revealed that IC, Eff-Z, and λHU in arterial phase and venous phase were predictors for diagnosis of SCC and AC (AUC > 0.5). Moreover, the IC, Eff-Z and λHU in venous phase had better differential diagnostic performances than that in arterial phase.

CONCLUSIONS

Spectral CT could be useful in the differential diagnosis of SCC and AC at the GEJ. Therefore, a routine spectral CT scan is recommended for patients with carcinoma of the GEJ.

Differential diagnosis of chromophobe renal cell carcinoma and papillary renal cell carcinoma with dual-energy spectral computed tomography

BACKGROUND

Computed tomography (CT) image features of chromophobe renal cell carcinoma (ChRCC) and papillary renal cell carcinoma (PRCC) are, occasionally, sometimes difficult to identify. However, spectral CT might provide quantitative parameters to differentiate them.

PURPOSE

To differentiate between ChRCC and PRCC with quantitative parameters using spectral CT.

MATERIAL AND METHODS

Forty cases of RCC confirmed with pathological tests were analyzed retrospectively (27 cases of PRCC and 13 cases of ChRCC). All patients underwent non-enhanced CT and dual-phase contrast-enhanced CT scans. For each lesion, the CT value of monochromatic images as well as iodine and water concentrations were measured, and the slope of spectrum curve was calculated. Data were analyzed using Student's t-test. Sensitivity and specificity of the quantitative parameters were analyzed using the receiver operating characteristic (ROC) curve.

RESULTS

During the cortex phase (CP) and parenchyma phase (PP), the CT value and slope of spectrum curve of ChRCC were higher than those of PRCC, and significant differences were observed at low energy levels (40-70 keV). Normalized iodine concentration of ChRCC and that of PRCC was significantly different during CP and PP (P < 0.05). The water (iodine) concentrations of ChRCC and PRCC in CP and PP were not statistically different (P > 0.05). All the ROCs for parameters were above the reference line.

CONCLUSION

Spectral CT may help increase the diagnostic accuracy of differentiating PRCC from ChRCC using a quantitative analysis.

Preoperative normalized iodine concentration derived from spectral CT is correlated with early recurrence of hepatocellular carcinoma after curative resection

OBJECTIVES

To investigate whether normalized iodine concentration (NIC) correlates with tumor microvessel density and early recurrence in patients with HCC.

MATERIALS AND METHODS

We included 71 patients with surgically resected single HCC in this prospective study who underwent preoperative spectral CT between November 2014 and June 2016. Two observers independently measured the NIC in the arterial phase (AP) and portal venous phase (PVP). The relationship between NIC and microvessel density was evaluated. Univariate and multivariate logistic regression was performed to evaluate independent predictors of early recurrence.

RESULTS

Early recurrence occurred in 28 of 71 patients (39.4%) during the 2-year follow-up. NIC-AP positively correlated with microvessel density for the two observers (r = 0.593 and 0.527). Based on multivariate analysis, independent risk factors for early HCC recurrence were tumor size (odds ratio, 1.200; p = 0.043) and NIC-AP (odds ratio, 2.522; p = 0.005). For the two observers, areas under the receiver operating characteristic curve for predicting early HCC recurrence were 0.719 and 0.677. Early recurrence rates were significantly higher among patients with NIC-AP values higher than the optimal cutoff than among those with values below the cutoff.

CONCLUSION

Normalized iodine concentration in the arterial phase from spectral CT reflects tumor-derived angiogenesis and is a potential predictive biomarker for early recurrence of hepatocellular carcinoma.

KEY POINTS

• Normalized iodine concentration in the arterial phase positively correlated with microvessel density of hepatocellular carcinoma. • In the patients with hepatocellular carcinoma, tumor size and normalized iodine concentration in the arterial phase were independent risk factors for early hepatocellular carcinoma recurrence. • Early hepatocellular carcinoma recurrence rates were significantly higher when normalized iodine concentration in the arterial phase values was above the optimal cutoff.

Diagnosis of multiple pulmonary cavernous hemangiomas via dual-layer spectral CT: A case report

RATIONALE

Cavernous hemangioma is a benign vascular tumor, which very rarely occurs in the lung. When appearing as multiple nodules on chest CT, this tumor can be misdiagnosed as metastatic malignancy.

PATIENT CONCERNS

A 72-year-old woman presented with incidentally found multiple lung nodules on chest radiograph.

DIAGNOSES

Based on information derived from dual-layer spectral CT images, the possibility of slow flow vascular tumor such as cavernous hemangioma was suggested. A pathologic diagnosis of pulmonary cavernous hemangioma was made via video-assisted thoracoscopic biopsy.

INTERVENTIONS

After tissue confirmation, the patient was discharged without further intervention.

OUTCOMES

The patient recovered without any event. Follow-up chest CT performed 6 months later showed no significant interval change in nodule size and distribution.

LESSONS

Material decomposition images obtained from dual energy CT can help physicians understand the character of tumor vascularity for an accurate diagnosis of pulmonary cavernous hemangioma.

Prediction of microvascular invasion of hepatocellular carcinoma: value of volumetric iodine quantification using preoperative dual-energy computed tomography

Background

To investigate the potential value of volumetric iodine quantification using preoperative dual-energy computed tomography (DECT) for predicting microvascular invasion (MVI) of hepatocellular carcinoma (HCC).

Methods

This retrospective study included patients with single HCC treated through surgical resection who underwent preoperative DECT. Quantitative DECT features, including normalized iodine concentration (NIC) to the aorta and mixed-energy CT attenuation value in the arterial phase, were three-dimensionally measured for peritumoral and intratumoral regions: (i) layer-by-layer analysis for peritumoral layers (outer layers 1 and 2; numbered in close order from the tumor boundary) and intratumoral layers (inner layers 1 and 2) with 2-mm layer thickness and (ii) volume of interest (VOI)-based analysis with different volume coverage (tumor itself; VOI_O1, tumor plus outer layer 1; VOI_O2, tumor plus outer layers 1 and 2; VOI_I1, tumor minus inner layer 1; VOI_I2, tumor minus inner layers 1 and 2). In addition, qualitative CT features, including peritumoral enhancement and tumor margin, were assessed. Qualitative and quantitative CT features were compared between HCC patients with and without MVI. Diagnostic performance of DECT parameters of layers and VOIs was assessed using receiver operating characteristic curve analysis.

Results

A total of 36 patients (24 men, mean age 59.9 ± 8.5 years) with MVI (n = 14) and without MVI (n = 22) were included. HCCs with MVI showed significantly higher NICs of outer layer 1, outer layer 2, VOI_O1, and VOI_O2 than those without MVI (P = 0.01, 0.04, 0.02, 0.02, respectively). Among the NICs of layers and VOIs, the highest area under the curve was obtained in outer layer 1 (0.747). Qualitative features, including peritumoral enhancement and tumor margin, and the mean CT attenuation of each layer and each VOI were not significantly different between HCCs with and without MVI (both P >  0.05).

Conclusions

Volumetric iodine quantification of peritumoral and intratumoral regions in arterial phase using DECT may help predict the MVI of HCC.

Atypical Appearance of Hepatocellular Carcinoma and Its Mimickers: How to Solve Challenging Cases Using Gadoxetic Acid-Enhanced Liver Magnetic Resonance Imaging

Hepatocellular carcinoma (HCC) can be diagnosed noninvasively with contrast-enhanced dynamic computed tomography, magnetic resonance imaging, or ultrasonography on the basis of its hallmark imaging features of arterial phase hyperenhancement and washout on portal or delayed phase images. However, approximately 40% of HCCs show atypical imaging features, posing a significant diagnostic challenge for radiologists. Another challenge for radiologists in clinical practice is the presentation of many HCC mimickers such as intrahepatic cholangiocarcinoma, combined HCC-cholangiocarcinoma, arterioportal shunt, and hemangioma in the cirrhotic liver. The differentiation of HCCs from these mimickers on preoperative imaging studies is of critical importance. Hence, we will review the typical and atypical imaging features of HCCs and the imaging features of its common mimickers. In addition, we will discuss how to solve these challenges in practice.

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.

Stepwise analysis of potential accuracy-influencing factors of iodine quantification on a fast kVp-switching second-generation dual-energy CT: from 3D-printed phantom to a simple solution in clinical routine use

Background

Measurement of iodine concentration from dual-energy or spectral computed tomography (CT) provides useful diagnostic information especially in patients suffering from malignant tumors of various origins.

Purpose

The purpose of this study was to systematically investigate the accuracy of the measurement of iodine concentration, focusing on potential influencing factors and assessing its suitability for routine clinical use.

Material and Methods

First, a 3D-printed cylindrical phantom was used to assess reliability of dual-energy CT-based iodine concentration measurement. Second, a semi-anthropomorphic phantom was used to evaluate the potential impact of positional variation of the target volume as typically seen in clinical scans. Finally, a reference vial was placed on the body surface of 38 patients undergoing abdominal dual-energy CT to analyze correlations between applied doses and patient diameters.

Results

The position of the target volume within the cylindrical phantom and the applied dose level significantly influenced the magnitude of measured iodine concentrations ( P < 0.001). We also found a significant difference in accuracy depending on target volume position in the semi-anthropomorphic phantom ( P = 0.028). In patient scans, we observed an error of 19.6 ± 5.6% in iodine concentration measurements of a reference and significant, moderate to strong, negative correlations between measured iodine concentration, maximum patient diameter, and applied dose (maximum sagittal diameter: r = −0.455, P = 0.004; maximum coronal diameter: r=−0.517, P = 0.001; CTDIvol: r = −0.385, P = 0.017)

Conclusion

Dual-energy CT-based iodine concentration measurement should be interpreted with caution. In clinical examinations, placement of a reference vial could be a potential solution to relativize errors.

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

BACKGROUND

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

PURPOSE

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

MATERIALS AND METHODS

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

RESULTS

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

CONCLUSION

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