Spectral detector CT applications in advanced liver imaging

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

CLINICAL RELEVANCE STATEMENT

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

KEY POINTS

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

Noninvasive diagnosis of liver cirrhosis: qualitative and quantitative imaging biomarkers

A diagnosis of cirrhosis initiates a shift in the management of chronic liver disease and affects the diagnostic workflow and treatment decision of primary liver cancer. Liver biopsy remains the gold standard for cirrhosis diagnosis, but it is invasive and susceptible to sampling bias and observer variability. Various qualitative and quantitative imaging biomarkers based on ultrasound, CT and MRI have been proposed for noninvasive diagnosis of cirrhosis. Qualitative imaging features are easy to apply but have moderate diagnostic sensitivity. Elastography techniques allow quantitative assessment of liver stiffness and are highly accurate for cirrhosis diagnosis. Ultrasound elastography are widely used in clinical practice, while MR elastography has narrower availability. Although not applicable in clinical practice yet, other quantitative imaging features, including liver surface nodularity, linear and volumetric measurement, extracellular volume fraction, liver enhancement on hepatobiliary phase, and parameters derived from diffusion-weighted imaging, can provide additional information of liver morphology, perfusion, and function, thus may increase diagnosis performance. The introduction of radiomics and deep learning has further improved diagnostic accuracy while reducing subjectivity. Several imaging features may also help to assess liver function and outcomes in patients with cirrhosis. In this review, we summarize the qualitative and quantitative imaging biomarkers for noninvasive cirrhosis diagnosis, and the assessment of liver function and outcomes, and discuss the challenges and future directions in this field.

Computed-Tomography-Guided Lung Biopsy: A Practice-Oriented Document on Techniques and Principles and a Review of the Literature

Computed tomography (CT)-guided lung biopsy is one of the oldest and most widely known minimally invasive percutaneous procedures. Despite being conceptually simple, this procedure needs to be performed rapidly and can be subject to meaningful complications that need to be managed properly. Therefore, knowledge of principles and techniques is required by every general or interventional radiologist who performs the procedure. This review aims to contain all the information that the operator needs to know before performing the procedure. The paper starts with the description of indications, devices, and types of percutaneous CT-guided lung biopsies, along with their reported results in the literature. Then, pre-procedural evaluation and the practical aspects to be considered during procedure (i.e., patient positioning and breathing) are discussed. The subsequent section is dedicated to complications, with their incidence, risk factors, and the evidence-based measures necessary to both prevent or manage them; special attention is given to pneumothorax and hemorrhage. After conventional CT, this review describes other available CT modalities, including CT fluoroscopy and cone-beam CT. At the end, more advanced techniques, which are already used in clinical practice, like fusion imaging, are included.

Application of Dual-Layer Spectral-Detector Computed Tomography Angiography in Identifying Symptomatic Carotid Atherosclerosis: A Prospective Observational Study

BACKGROUND

Dual-layer spectral-detector dual-energy computed tomography angiography (DLCTA) can distinguish components of carotid plaques. Data on identifying symptomatic carotid plaques in patients using DLCTA are not available.

METHODS AND RESULTS

In this prospective observational study, patients with carotid plaques were enrolled and received DLCTA. The attenuation for both polyenergetic image and virtual monoenergetic images (40, 70, 100, and 140 keV), as well as Z-effective value, were recorded in the noncalcified regions of plaques. Logistic regression models were used to assess the association between attenuations of DLCTA and the presence of symptomatic carotid plaques. In total, 100 participants (mean±SD age, 64.37±8.31 years; 82.0% were men) were included, and 36% of the cases were identified with the symptomatic group. DLCTA parameters were different between 2 groups (symptomatic versus asymptomatic: computed tomography [CT] 40 keV, 152.63 [interquartile range (IQR), 70.22-259.78] versus 256.78 [IQR, 150.34-408.13]; CT 70 keV, 81.28 [IQR, 50.13-119.33] versus 108.87 [IQR, 77.01-165.88]; slope40-140 keV, 0.91 [IQR, 0.35-1.87] versus 1.92 [IQR, 0.96-3.00]; Z-effective value, 7.92 [IQR, 7.53-8.46] versus 8.41 [IQR, 7.94-8.92]), whereas no difference was found in conventional polyenergetic images. The risk of symptomatic plaque was lower in the highest tertiles of attenuations in CT 40 keV (adjusted odds ratio [OR], 0.243 [95% CI, 0.078-0.754]), CT 70 keV (adjusted OR, 0.313 [95% CI, 0.104-0.940]), Z-effective values (adjusted OR, 0.138 [95% CI, 0.039-0.490]), and slope40-140 keV (adjusted OR, 0.157 [95% CI, 0.046-0.539]), with all P values and P trends <0.05. The areas under the curve for CT 40 keV, CT 70 keV, slope 40 to 140 keV, and Z-effective values were 0.64, 0.61, 0.64, and 0.63, respectively.

CONCLUSIONS

Parameters of DLCTA might help assist in distinguishing symptomatic carotid plaques. Further studies with a larger sample size may address the overlap and improve the diagnostic accuracy.

Ablation margin quantification after thermal ablation of malignant liver tumors: How to optimize the procedure? A systematic review of the available evidence

Introduction

To minimize the risk of local tumor progression after thermal ablation of liver malignancies, complete tumor ablation with sufficient ablation margins is a prerequisite. This has resulted in ablation margin quantification to become a rapidly evolving field. The aim of this systematic review is to give an overview of the available literature with respect to clinical studies and technical aspects potentially influencing the interpretation and evaluation of ablation margins.

Methods

The Medline database was reviewed for studies on radiofrequency and microwave ablation of liver cancer, ablation margins, image processing and tissue shrinkage. Studies included in this systematic review were analyzed for qualitative and quantitative assessment methods of ablation margins, segmentation and co-registration methods, and the potential influence of tissue shrinkage occurring during thermal ablation.

Results

75 articles were included of which 58 were clinical studies. In most clinical studies the aimed minimal ablation margin (MAM) was ≥ 5 mm. In 10/31 studies, MAM quantification was performed in 3D rather than in three orthogonal image planes. Segmentations were performed either semi-automatically or manually. Rigid and non-rigid co-registration algorithms were used about as often. Tissue shrinkage rates ranged from 7% to 74%.

Conclusions

There is a high variability in ablation margin quantification methods. Prospectively obtained data and a validated robust workflow are needed to better understand the clinical value. Interpretation of quantified ablation margins may be influenced by tissue shrinkage, as this may cause underestimation.

Early evaluation of liver metastasis using spectral CT to predict outcome in patients with colorectal cancer treated with FOLFOXIRI and bevacizumab

PURPOSE

Early evaluation of the efficacy of first-line chemotherapy combined with bevacizumab in patients with colorectal cancer liver metastasis (CRLM) remains challenging. This study used 2-month post-chemotherapy spectral computed tomography (CT) to predict the overall survival (OS) and response of CRLM patients with bevacizumab-containing therapy.

METHOD

This retrospective analysis was performed in 104 patients with pathologically confirmed CRLM between April 2017 and October 2021. Patients were treated with 5-fluorouracil, leucovorin, oxaliplatin or irinotecan with bevacizumab. Portal venous phase spectral CT was performed on the target liver lesion within 2 months of commencing chemotherapy to demonstrate the iodine concentration (IoD) of the target liver lesion. The patients were classified as responders (R +) or non-responders (R -) according to the Response Evaluation Criteria in Solid Tumors (RECIST) v1.1 at 6 months. Multivariate analysis was performed to determine the relationships of the spectral CT parameters, tumor markers, morphology of target lesions with OS and response. The differences in portal venous phase spectral CT parameters between the R + and R - groups were analyzed. Receiver operating characteristic (ROC) curves were used to evaluate the predictive power of spectral CT parameters.

RESULTS

Of the 104 patients (mean age ± standard deviation: 57.73 years ± 12.56; 60 men) evaluated, 28 (26.9%) were classified as R + . Cox multivariate analysis identified the iodine concentration (hazard ratio [HR]: 1.238; 95% confidence interval [95% CI]: 1.089-1.408; P < 0.001), baseline tumor longest diameter (BLD) (HR: 1.022; 95% CI: 1.005-1.038, P = 0.010), higher baseline CEA (HR: 1.670; 95% CI: 1.016-2.745, P = 0.043), K-RAS mutation (HR: 2.027; 95% CI: 1.192-3.449; P = 0.009), and metachronous liver metastasis (HR: 1.877; 95% CI: 1.179-2.988; P = 0.008) as independent risk factors for patient OS. Logistic multivariate analysis identified the IoD (Odds Ratio [OR]: 2.243; 95% CI: 1.405-4.098; P = 0.002) and clinical N stage of the primary tumor (OR: 4.998; 95% CI: 1.210-25.345; P = 0.035) as independent predictor of R + . Using IoD cutoff values of 4.75 (100ug/cm³) the area under the ROC curve was 0.916, sensitivity and specificity were 80.3% and 96.4%, respectively.

CONCLUSIONS

Spectral CT IoD can predict the OS and response of patients with CRLM after 2 months of treatment with bevacizumab-containing therapy.

The diagnostic value of quantitative parameters on dual-layer detector-based spectral CT in identifying ischaemic stroke

Objective

To investigate the diagnostic value of quantitative parameters of spectral computed tomography (CT) in ischaemic stroke areas.

Methods

The medical records of 57 patients with acute ischaemic stroke (AIS) who underwent plain computed tomography (CT) head scans, CT angiography (CTA), and CT perfusion (CTP) were retrospectively reviewed. The ischaemic areas (including the core infarct area and penumbra) and non-ischaemic areas in each patient were quantitatively analyzed using F-STROKE software. Two independent readers measured the corresponding values of the spectroscopic quantitative parameters (effective atomic number [Zeff value], iodine density value, and iodine-no-water value) in the ischaemic area and contralateral normal area alone. The differences in spectroscopic quantitative parameters between the two groups were compared, and their diagnostic efficacy was obtained.

Results

The Zeff, iodine-no-water value, and iodine density value of the ischaemic area all showed significant lower than those of non-ischaemic tissue (P < 0.001). For differentiating the ischaemic area from non-ischaemic tissue, the area under the curve (AUC) of the Zeff value reached 0.869 (cut-off value: 7.385; sensitivity: 93.0%; specificity: 70.2%), the AUC of the iodine density value reached 0.932 (cut-off value: 0.235; sensitivity: 91.2%; specificity: 82.5%), and the AUC of the iodine-no-water value reached 0.922 (cut-off value: 0.205; sensitivity: 96.5%; specificity: 78.9%).

Conclusion

The study showed the spectral CT would be a potential novel rapid method for identifying AIS. The spectral CT quantitative parameters (Zeff, iodine density values, and iodine-no-water values) can effectively differentiate the ischaemic area from non-ischaemic tissue in stroke patients.

Detection of axillary lymph node metastasis in breast cancer using dual-layer spectral computed tomography

PURPOSE

To investigate the value of contrast-enhanced dual-layer spectral computed tomography (DLCT) in the detection of axillary lymph node (ALN) metastasis in breast cancer.

MATERIALS AND METHODS

In this prospective study, 31 females with breast cancer underwent contrast-enhanced DLCT from August 2019 to June 2020. All ALNs were confirmed by postoperative histology. Spectral quantitative parameters, including λ _HU (in Hounsfield units per kiloelectron-volt), nIC (normalized iodine concentration), and Z_eff (Z-effective value) in both arterial and delay phases, were calculated and contrasted between metastatic and nonmetastatic ALNs using the McNemar test. Discriminating performance from metastatic and nonmetastatic ALNs was analyzed using receiver operating characteristic curves.

RESULTS

In total, 132 ALNs (52 metastatic and 80 nonmetastatic) were successfully matched between surgical labels and preoperative labels on DLCT images. All spectral quantitative parameters (λ_Hu , nIC, and Z_eff) derived from both arterial and delayed phases were greater in metastatic ALNs than in nonmetastatic SLNs (all p < 0.001). Logistic regression analyses showed that λ_Hu in the delayed phase was the best single parameter for the detection of metastatic ALNs on a per-lymph node basis, with an area under the curve of 0.93, accuracy of 86.4% (114/132), sensitivity of 92.3% (48/52), and specificity of 87.5% (70/80).

CONCLUSION

The spectral quantitative parameters derived from contrast-enhanced DLCT, such as λ_Hu , can be applied for the preoperative detection of ALN metastasis in breast cancer.

Dual-layer spectral CT fusion imaging for lung biopsies: more accurate targets, diagnostic samplings, and biomarker information?

The increasingly widespread use of computed tomography (CT) has increased the number of detected lung lesions, which are then subjected to needle biopsy to obtain histopathological diagnosis. Obtaining high-quality biopsy specimens is fundamental for diagnosis and biomolecular characterisation that guide therapy decision-making. In order to obtain samples with high diagnostic potential, fusion imaging techniques, such as fusion between positron emission tomography and CT, have been introduced to target the biopsy where there more viable neoplastic cells can be sampled. Nowadays, dual-layer spectral CT represents a novel technology enabling an increased tissue characterisation. In particular, Z-effective images, i.e., colour-coded images based on the effective atomic number of tissue components, provide a higher level of discrimination than usual imaged based on x-ray attenuation in Hounsfield units and offer the potential of a better tissue characterisation. Our hypothesis is based on the future use of data provided by spectral CT, in particular by Z-effective images, as a guide for appropriate biopsy sampling for histopathological and biomolecular characterisation in the era of patient tailored-therapy.

Utility of Dual-Layer Spectral-Detector CTA to Characterize Carotid Atherosclerotic Plaque Components: An Imaging-Histopathology Comparison in Patients Undergoing Endarterectomy

Background: The composition of non-calcified portions of carotid atherosclerotic plaque represents an important marker of plaque vulnerability and ischemia risk. Objective: To assess the utility of dual-layer spectral-detector CTA (DLCTA) parameters for carotid plaque component characterization, using histologic results from carotid endarterectomy (CEA) as reference. Methods: Seven patients (5 male, 2 female; 61.6±8.5 years old) with carotid plaque awaiting CEA were prospectively enrolled and underwent preoperative supra-aortic DLCTA. A neuroradiologist and pathologist performed joint slice-by-slice review of histologic slices of resected plaques and CTA images. ROIs were placed on non-calcified components [lipid-rich necrotic core (LRNC), intraplaque hemorrhage (IPH), fibrous tissue, loose matrix (LM)] on CTA images in comparison with corresponding histologic slices using anatomic landmarks. For each ROI, attenuation was recorded for polyenergetic images (CTPI) and virtual monoenergetic images with keV ranging from 40-140 (CT40-140keV); attenuation spectrum curve slope was calculated; and Z-effective value (representing effective atomic number) was recorded. DLCTA parameters were compared among plaque components. Results: Seven plaques with a total of 65 slices and 364 ROIs (159 fibrous tissue, 96 LRNC, 86 loose matrix, 23 IPH) were analyzed. All parameters (CTPI, CT40-140keV, slope from 40 to 140 keV, Z-effective value) showed significant differences between LRNC and the other components (all p<.001). For example, mean CTPI was 37.1±15.1 HU for LRNC, 58.4±21.6 HU for IPH, 69.7±20.5 HU for fibrous tissue, and 69.6±19.6 HU for loose matrix; mean CT40keV was 28.1±36.7 HU for LRNC, 87.5±48.9 HU for IPH, 106.3±47.5 HU for fibrous tissue, and 102.6±48.0 HU for loose matrix. AUC for differentiating LRNC from other components was highest (0.945) for CT40kev and decreased with higher keV; AUC for CTPI was 0.908. CT40kev also had highest accuracy (90.4%); at cutoff of 55.7 HU, CT40kev had 88.5% sensitivity and 90.9% specificity. For differentiating IPH from fibrous tissue and loose matrix, AUC was highest at 0.652 for CTPI and 0.645 for CT40kev. Conclusion: DLCTA showed strong performance in differentiating LRNC from other non-calcified plaque components; CT40kev had highest accuracy, outperforming conventional polyenergetic images. Clinical Impact: DLCTA parameters may help characterize carotid plaque composition as a marker of vulnerable plaque and ischemia risk.