Advanced dual-energy CT applications for the evaluation of the soft tissues of the neck

Can virtual non-contrast imaging replace true non-contrast imaging in multiphase scanning of the neck region?

Background

Dual-energy computed tomography (DECT) is an advanced imaging method that enables reconstruction of virtual non-contrast (VNC) images from a contrast-enhanced acquisition. This has the potential to reduce radiation exposure by eliminating the need for a true non-contrast (TNC) phase.

Purpose

The purpose is to evaluate the feasibility of VNC images in the neck region.

Materials and methods

A total of 100 patients underwent a DECT scan as part of diagnostic workup of primary hyperparathyroidism. VNC images were reconstructed from 30 s (arterial) and 50 s (venous) post-contrast scans. Regions of interest (ROIs) were placed in thyroid tissue, lymph node, carotid artery, jugular vein, fat, and sternocleidomastoid muscle. Mean densities of all anatomical structures were compared between VNC and TNC images.

Results

For all anatomical structures except the thyroid gland, the difference in mean density between TNC and VNC images was less than 15 HU. The mean difference in density between TNC and VNC images of the thyroid was 53.2 HU (95% CI 46.8; 59.6, p = <0.001).

Conclusion

This study demonstrated an acceptable agreement in density between true non-contrast and virtual non-contrast images for most anatomical structures in the neck region. Therefore, VNC images may have the potential to replace TNC images in the neck. However, due to significant differences in CT density of thyroid tissue, true non-contrast imaging cannot be directly substituted by virtual non-contrast imaging when examining the thyroid and its surrounding tissue.

MRI of acute neck infections: evidence summary and pictorial review

Infection of the deep neck spaces is a life-threatening acute illness that requires prompt diagnosis and treatment. Magnetic resonance imaging (MRI) offers unsurpassed soft tissue discrimination and is therefore well suited for imaging neck infections. Recently, the feasibility, diagnostic accuracy, and clinical significance of this method have been documented in patients with acute neck infections. This review article summarizes the scientific evidence, provides a practical guide to image acquisition and interpretation, reviews the most common imaging findings, and discusses some difficult diagnoses and pitfalls in acute neck infections, to help both radiologists and clinicians in managing these critically ill patients.

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.

Diagnostic accuracy of contrast-enhanced CT for neck abscesses: A systematic review and meta-analysis of positive predictive value

OBJECTIVES

To review the diagnostic accuracy of contrast-enhanced computed tomography (CT) in differentiating abscesses from cellulitis in patients with neck infections, using surgical findings as the reference standard.

MATERIALS AND METHODS

Previous studies in the last 32 years were searched from PubMed and Embase. Because of partial verification bias (only positive abscess findings are usually verified surgically), sensitivity and specificity estimates are unreliable, and we focused on positive predictive value (PPV). For all studies, PPV was calculated as the proportion of true positives out of all positives on imaging. To estimate pooled PPV, we used both the median with an interquartile range and a model-based estimate. For narrative purposes, we reviewed the utility of common morphological CT criteria for abscesses, such as central hypodensity, the size of the collection, bulging, rim enhancement, and presence of air, as well as sensitivity and specificity values reported by the original reports.

RESULTS

23 studies were found reporting 1453 patients, 14 studies in children (771 patients), two in adults (137 patients), and seven including all ages (545 patients). PPV ranged from 0.67 to 0.97 in individual studies, had a median of 0.84 (0.79-0.87), and a model-based pooled estimate of 0.83 (95% confidence interval 0.80-0.85). Most morphological CT criteria had considerable overlap between abscesses and cellulitis.

CONCLUSIONS

The pooled estimate of PPV is 0.83 for diagnosing neck abscesses with CT. False positives may be due to limited soft tissue contrast resolution. Overall, none of the morphological criteria seem to be highly accurate for differentiation between abscess and cellulitis.

State-of-the-art imaging in oesophago-gastric cancer

Radiological investigations are essential in the management of oesophageal and gastro-oesophageal junction cancers. The current multimodal combination of CT, 18F-fluorodeoxyglucose positron emission tomography combined with CT (PET/CT) and endoscopic ultrasound (EUS) has limitations, which hinders the prognostic and predictive information that can be used to guide optimum treatment decisions. Therefore, the development of improved imaging techniques is vital to improve patient management. This review describes the current evidence for state-of-the-art imaging techniques in oesophago-gastric cancer including high resolution MRI, diffusion-weighted MRI, dynamic contrast-enhanced MRI, whole-body MRI, perfusion CT, novel PET tracers, and integrated PET/MRI. These novel imaging techniques may help clinicians improve the diagnosis, staging, treatment planning, and response assessment of oesophago-gastric cancer.

Clinical applications of dual-energy computed tomography in neuroradiology

Dual-energy computed tomography (DECT) has developed into a robust set of techniques with increasingly validated clinical applications in neuroradiology. We review some of the most common applications in neuroimaging along with demonstrative case examples that showcase the use of this technology in intracranial hemorrhage, stroke imaging, trauma imaging, artifact reduction, and tumor characterization.

Multi-channel convolutional analysis operator learning for dual-energy CT reconstruction

Objective. Dual-energy computed tomography (DECT) has the potential to improve contrast and reduce artifacts and the ability to perform material decomposition in advanced imaging applications. The increased number of measurements results in a higher radiation dose, and it is therefore essential to reduce either the number of projections for each energy or the source x-ray intensity, but this makes tomographic reconstruction more ill-posed. Approach. We developed the multi-channel convolutional analysis operator learning (MCAOL) method to exploit common spatial features within attenuation images at different energies and we propose an optimization method which jointly reconstructs the attenuation images at low and high energies with mixed norm regularization on the sparse features obtained by pre-trained convolutional filters through the convolutional analysis operator learning (CAOL) algorithm. Main results. Extensive experiments with simulated and real computed tomography data were performed to validate the effectiveness of the proposed methods, and we report increased reconstruction accuracy compared with CAOL and iterative methods with single and joint total variation regularization. Significance. Qualitative and quantitative results on sparse views and low-dose DECT demonstrate that the proposed MCAOL method outperforms both CAOL applied on each energy independently and several existing state-of-the-art model-based iterative reconstruction techniques, thus paving the way for dose reduction.

Parathyroid Imaging: Past, Present, and Future

The goal of parathyroid imaging is to identify all sources of excess parathyroid hormone secretion pre-operatively. A variety of imaging approaches have been evaluated and utilized over the years for this purpose. Ultrasound relies solely on structural features and is without radiation, however is limited to superficial evaluation. 4DCT and 4DMRI provide enhancement characteristics in addition to structural features and dynamic enhancement has been investigated as a way to better distinguish parathyroid from adjacent structures. It is important to recognize that 4DCT provides valuable information however results in much higher radiation dose to the thyroid gland than the other available examinations, and therefore the optimal number of phases is an area of controversy. Single-photon scintigraphy with 99mTc-Sestamibi, or dual tracer 99mTc-pertechnetate and 99mTc-sestamibi with or without SPECT or SPECT/CT is part of the standard of care in many centers with availability and expertise in nuclear medicine. This molecular imaging approach detects cellular physiology such as mitochondria content found in parathyroid adenomas. Combining structural imaging such as CT or MRI with molecular imaging in a hybrid approach allows the ability to obtain robust structural and functional information in one examination. Hybrid PET/CT is widely available and provides improved imaging and quantification over SPECT or SPECT/CT. Emerging PET imaging techniques, such as 18F-Fluorocholine, have the exciting potential to reinvent parathyroid imaging. PET/MRI may be particularly well suited to parathyroid imaging, where available, because of the ability to perform dynamic contrast-enhanced imaging and co-registered 18F-Fluorocholine PET imaging simultaneously with low radiation dose to the thyroid. A targeted agent specific for a parathyroid tissue biomarker remains to be identified.

Image quality comparison of single-energy and dual-energy computed tomography for head and neck patients: a prospective randomized study

OBJECTIVES

The aim of this study was to compare the quality of images obtained using single-energy computed tomography (SECT) performed with automated tube voltage adaptation (TVA) with dual-energy CT (DECT) weighted average images.

METHODS

Eighty patients were prospectively randomized to undergo either SECT with TVA (n = 40, ref. mAs 200) or radiation dose-matched DECT (n = 40, 80/Sn150 kV, ref. mAs tube A 91/tube B 61) on a dual-source CT scanner. Objective image quality was evaluated as dose-normalized contrast-to-noise ratio (CNRD) for the jugular veins relative to fatty tissue and muscle tissue and for muscle tissue relative to fatty issue. For subjective image quality, reproduction of anatomical structures, image artifacts, image noise, spatial resolution, and overall diagnostic acceptability were evaluated at sixteen anatomical substructures using Likert-type scales.

RESULTS

Effective radiation dose (ED) was comparable between SECT and DECT study groups (2.9 ± 0.6 mSv/3.1 ± 0.7 mSv, p = 0.5). All examinations were rated as excellent or good for clinical diagnosis. Compared to the CNRD in the SECT group, the CNRD in the DECT group was significantly higher for the jugular veins relative to fatty tissue (7.51/6.08, p < 0.001) and for muscle tissue relative to fatty tissue (4.18/2.90, p < 0.001). The CNRD for the jugular veins relative to muscle tissue (3.33/3.18, p = 0.51) was comparable between groups. Image artifacts were less pronounced and overall diagnostic acceptability was higher in the DECT group (all p = 0.01).

CONCLUSIONS

DECT weighted average images deliver higher objective and subjective image quality than SECT performed with TVA in head and neck imaging.

KEY POINTS

• Weighted average images derived from dual-energy CT deliver higher objective and subjective image quality than single-energy CT using automated tube voltage adaptation in head and neck imaging. • If available, dual-energy CT acquisition may be preferred over automated low tube voltage adopted single-energy CT for both malignant and non-malignant conditions.

The application of dual-layer spectral detector computed tomography in solitary pulmonary nodule identification

Background

Differentiating between malignant solitary pulmonary nodules (SPNs) and other lung diseases remains a substantial challenge. The latest generation of dual-energy computed tomography (CT), which realizes dual-energy technology at the detector level, has clinical potential for distinguishing lung cancer from other benign SPNs. This study aimed to evaluate the performance of dual-layer spectral detector CT (SDCT) for the differentiation of SPNs.

Methods

Spectral images of 135 SPNs confirmed by pathology were retrospectively analyzed in both the arterial phase (AP) and the venous phase (VP). Patients were classified into two groups [the malignant group (n=93) and the benign group (n=42)], with the malignant group further divided into small cell lung cancer (SCLC, n=30) and non-small cell lung cancer (NSCLC, n=63) subtypes. The slope of the spectral Hounsfield Unit (HU) curve (λ_HU), normalized iodine concentration (NIC), CT values of 40 keV monochromatic images (CT_40keV), and normalized arterial enhancement fraction (NAEF) in contrast-enhanced images were calculated and compared between the benign and malignant groups, as well as between the SCLC and NSCLC subgroups. ROC curve analysis was performed to assess the diagnostic performance of the above parameters. Seventy cases were randomly selected and independently measured by two radiologists, and intraclass correlation coefficient (ICC) and Bland-Altman analyses were performed to calculate the reliability of the measurements.

Results

Except for NAEF (P=0.23), the values of the parameters were higher in the malignant group than in the benign group (all P<0.05). NIC, λ_HU, and CT_40keV performed better in the VP (NIC_VP, λ_VPHU, and CT_VP40keV) (P<0.001), with an area under the ROC curve (AUC) of 0.93, 0.89, and 0.89 respectively. With respective cutoffs of 0.31, 1.83, and 141.00 HU, the accuracy of NIC_VP, λ_VPHU, and CT_VP40keV was 91.11%, 85.19%, and 88.15%, respectively. In the subgroup differentiating NSCLC and SCLC, the diagnostic performances of NIC_AP (AUC =0.89) were greater than other parameters. NIC_AP had an accuracy of 86.02% when the cutoff was 0.14. ICC and Bland-Altman analyses indicated that the measurement of SDCT has great reproducibility.

Conclusions

Quantitative measures from SDCT can help to differentiate benign from malignant SPNs and may help with the further subclassification of malignant cancer into SCLC and NSCLC.

Comparison of tumor delineation using dual energy computed tomography versus magnetic resonance imaging in head and neck cancer re-irradiation cases

•

GTVs on the 60 kV and 140 kV from DECT, and the T1c and T2 from MRI were compared.

•

Delineation was the most consistent using T1c (no interobserver difference in DSC).

•

T1c MRI provided higher interobserver agreement for skull base tumors.

•

60 kV DECT provided higher interobserver agreement for non-skull base tumors.

In treatment planning, multiple imaging modalities can be employed to improve the accuracy of tumor delineation but this can be costly. This study aimed to compare the interobserver consistency of using dual energy computed tomography (DECT) versus magnetic resonance imaging (MRI) for delineating tumors in the head and neck cancer (HNC) re-irradiation scenario. Twenty-three patients with recurrent HNC and had planning DECT and MRI were identified. Contoured tumor volumes by seven radiation oncologists were compared. Overall, T1c MRI performed the best with median DSC of 0.58 (0–0.91) for T1c. T1c MRI provided higher interobserver agreement for skull base sites and 60 kV DECT provided higher interobserver agreement for non-skull base sites.

Technical Principles of Dual-Energy Cone Beam Computed Tomography and Clinical Applications for Radiation Therapy

PURPOSE

Medical imaging is an indispensable tool in radiotherapy for dose planning, image guidance and treatment monitoring. Cone beam CT (CBCT) is a low dose imaging technique with high spatial resolution capability as a direct by-product of using flat-panel detectors. However, certain issues such as x-ray scatter, beam hardening and other artifacts limit its utility to the verification of patient positioning using image-guided radiotherapy.

METHODS AND MATERIALS

Dual-energy (DE)-CBCT has recently demonstrated promise as an improved tool for tumor visualization in benchtop applications. It has the potential to improve soft-tissue contrast and reduce artifacts caused by beam hardening and metal. In this review, the practical aspects of developing a DE-CBCT based clinical and technical workflow are presented based on existing DE-CBCT literature and concepts adapted from the well-established library of work in DE-CT. Furthermore, the potential applications of DE-CBCT on its future role in radiotherapy are discussed.

RESULTS AND CONCLUSIONS

Based on current literature and an investigation of future applications, there is a clear potential for DE-CBCT technologies to be incorporated into radiotherapy. The applications of DE-CBCT include (but are not limited to): adaptive radiotherapy, brachytherapy, proton therapy, radiomics and theranostics.

An update on advanced dual-energy CT for head and neck cancer imaging

Introduction: Dual-energy-computed tomography (DECT) is an advanced form of computed tomography (CT) that enables spectral tissue characterization beyond what is possible with conventional CT scans. DECT can improve non-invasive diagnostic evaluation of the neck, especially for the evaluation of head and neck cancer. Areas covered: This article is a review of current applications of DECT for the evaluation of head and neck cancer, focusing largely on squamous cell carcinoma (HNSCC). The article will begin with a brief overview of principles and different approaches for DECT scanning. This will be followed by a review of different DECT applications in diagnostic imaging and radiation oncology, practical and workflow considerations, and various emerging advanced applications for tumor analysis, including the use of DECT datasets for radiomics and machine learning applications. Expert opinion: Using a multi-parametric approach, different DECT reconstructions can be used to improve diagnostic evaluation and surveillance of head and neck cancer, including improving visibility of HNSCC, determination of tumor boundaries and extent, and invasion of critical organs such as the thyroid cartilage. In the future, the large amount of quantitative information on DECT scans may be leveraged for improving radiomic and machine learning models for tumor characterization.

How to Incorporate Dual-Energy Computed Tomography Into Your Neuroradiology Practice: Questions and Answers

Dual-energy computed tomography (DECT) has many current and evolving applications in neuroradiology including material decomposition, improving conspicuity of iodinated contrast enhancement, and artifact reduction. However, there are multiple challenges in incorporating DECT into practice including hardware selection, postprocessing software requirements, technologist and physician training, and numerous workflow issues. This article reviews in a question-and-answer format common issues that arise when incorporating DECT into a busy neuroradiology practice.

Experimental feasibility of dual-energy computed tomography based on the Thomson scattering X-ray source

Unlike large-scale and expensive synchrotron radiation facilities, the Thomson scattering X-ray source can provide quasi-monochromatic, energy-tunable and high-brightness X-ray pulses with a small footprint and moderate cost, making it an excellent candidate for dual-energy and multi-energy imaging at laboratories and hospitals. Here, the first feasibility study on dual-energy computed tomography (CT) based on this type of light source is reported, and the effective atomic number and electron-density distribution of a standard phantom consisting of polytetrafluoroethylene, water and aluminium is derived. The experiment was carried out at the Tsinghua Thomson scattering X-ray source with peak energies of 29 keV and 68 keV. Both the reconstructed effective atomic numbers and the retrieved electron densities of the three materials were compared with their theoretical values. It was found that these values were in agreement by 0.68% and 2.60% on average for effective atomic number and electron density, respectively. These results have verified the feasibility of dual-energy CT based on the Thomson scattering X-ray source and will further expand the scope of X-ray imaging using this type of light source.

Spectral multi-energy CT texture analysis with machine learning for tissue classification: an investigation using classification of benign parotid tumours as a testing paradigm

OBJECTIVE

There is a rich amount of quantitative information in spectral datasets generated from dual-energy CT (DECT). In this study, we compare the performance of texture analysis performed on multi-energy datasets to that of virtual monochromatic images (VMIs) at 65 keV only, using classification of the two most common benign parotid neoplasms as a testing paradigm.

METHODS

Forty-two patients with pathologically proven Warthin tumour (n = 25) or pleomorphic adenoma (n = 17) were evaluated. Texture analysis was performed on VMIs ranging from 40 to 140 keV in 5-keV increments (multi-energy analysis) or 65-keV VMIs only, which is typically considered equivalent to single-energy CT. Random forest (RF) models were constructed for outcome prediction using separate randomly selected training and testing sets or the entire patient set.

RESULTS

Using multi-energy texture analysis, tumour classification in the independent testing set had accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of 92%, 86%, 100%, 100%, and 83%, compared to 75%, 57%, 100%, 100%, and 63%, respectively, for single-energy analysis.

CONCLUSIONS

Multi-energy texture analysis demonstrates superior performance compared to single-energy texture analysis of VMIs at 65 keV for classification of benign parotid tumours.

KEY POINTS

• We present and validate a paradigm for texture analysis of DECT scans. • Multi-energy dataset texture analysis is superior to single-energy dataset texture analysis. • DECT texture analysis has high accura\cy for diagnosis of benign parotid tumours. • DECT texture analysis with machine learning can enhance non-invasive diagnostic tumour evaluation.