Dual energy imaging in cardiothoracic pathologies: A primer for radiologists and clinicians

Improving Image Quality of Chest Radiography with Artificial Intelligence-Supported Dual-Energy X-Ray Imaging System: An Observer Preference Study in Healthy Volunteers

Background/Objectives: To compare the image quality of chest radiography with a dual-energy X-ray imaging system using AI technology (DE-AI) to that of conventional chest radiography with a standard protocol. Methods: In this prospective study, 52 healthy volunteers underwent dual-energy chest radiography. Images were obtained using two exposures at 60 kVp and 120 kVp, separated by a 150 ms interval. Four images were generated for each participant: a conventional image, an enhanced standard image, a soft-tissue-selective image, and a bone-selective image. A machine learning model optimized the cancellation parameters for generating soft-tissue and bone-selective images. To enhance image quality, motion artifacts were minimized using Laplacian pyramid diffeomorphic registration, while a wavelet directional cycle-consistent adversarial network (WavCycleGAN) reduced image noise. Four radiologists independently evaluated the visibility of thirteen anatomical regions (eight soft-tissue regions and five bone regions) and the overall image with a five-point scale of preference. Pooled mean values were calculated for each anatomic region through meta-analysis using a random-effects model. Results: Radiologists preferred DE-AI images to conventional chest radiographs in various anatomic regions. The enhanced standard image showed superior quality in 9 of 13 anatomic regions. Preference for the soft-tissue-selective image was statistically significant for three of eight anatomic regions. Preference for the bone-selective image was statistically significant for four of five anatomic regions. Conclusions: Images produced by DE-AI provide better visualization of thoracic structures.

Multienergy cardiovascular CT imaging: current state and future

Multienergy cardiovascular CT imaging can be defined as data acquisition at 2 (dual-energy) or multiple X-ray energies. Multienergy cardiovascular CT imaging provides additional qualitative and quantitative information such as material maps or virtual monoenergetic images, which are supposed to further improve the quality and diagnostic yield of CT. Recently introduced photon-counting detector CT scanners further address some of the challenges and limitations of previous, conventional CT machines, hereby enhancing and extending the applications of CT for cardiovascular imaging. This review summarizes the technical principles of multienergy cardiovascular CT imaging and addresses the optimization of image quality and discusses the various dual-energy-based applications for coronary, valvular, and myocardial imaging. New developments in regard to k-edge imaging and new contrast media for multienergy cardiovascular CT imaging are being also discussed.

Dual-energy subtraction radiography (DESR): a systematic review and meta-analysis of pulmonary nodule detection

PURPOSE

This study examined the literature to compare the accuracy, sensitivity, and specificity of dual-energy subtraction radiography (DESR) with conventional radiography (CR) in the detection of pulmonary nodules. To our knowledge, no meta-analysis has been conducted to compare DESR with CR.

MATERIAL AND METHODS

The authors searched Pubmed using the terms "Dual-energy subtraction radiography," and "Dual-Energy Chest Radiography." Only studies comparing the detection of pulmonary nodules between DESR and CR were included. Studies utilizing artificial intelligence were excluded. The primary study outcomes analyzed were the mean difference of receiver operating characteristic area under the curve (ROC AUC), mean difference of sensitivity, and mean difference of specificity.

RESULTS

Twenty-three studies between 1994 and 2022 were included. Of these twenty-three, eighteen reported ROC AUC statistics. The difference between DESR ROC AUC (mean = 0.7702, SD = 0.1361) and CR ROC AUC (mean = 0.7106, SD = 0.1183) was 0.0597 (P<0.001). Sensitivity data was reported for thirteen of the twenty-three selected studies. The difference between DESR sensitivity (mean = 0.5753, SD = 0.1546) and CR sensitivity (mean = 0.4391, SD = 0.1007) was 0.136 (P<0.001). Specificity data were reported for ten of the twenty-three selected studies. The difference between DESR specificity (mean = 0.753, SD = 0.1575) and CR specificity (mean = 0.764, SD = 0.1168) was -0.011 (P=0.767). This was not statistically significant.

CONCLUSIONS

DESR showed superior sensitivity and ROC AUC values compared with CR in detecting pulmonary nodules. There was no difference in specificity.

An artificial intelligence algorithm for the detection of pulmonary ground-glass nodules on spectral detector CT: performance on virtual monochromatic images

BACKGROUND

This study aims to assess the performance of an established an AI algorithm trained on conventional polychromatic computed tomography (CT) images (CPIs) to detect pulmonary ground-glass nodules (GGNs) on virtual monochromatic images (VMIs), and to screen the optimal virtual monochromatic energy for the clinical evaluation of GGNs.

METHODS

Non-enhanced chest SDCT images of patients with pulmonary GGNs in our clinic from January 2022 to December 2022 were continuously collected: adenocarcinoma in situ (AIS, n = 40); minimally invasive adenocarcinoma (MIA, n = 44) and invasive adenocarcinoma (IAC, n = 46). A commercial CAD system based on deep convolutional neural networks (DL-CAD) was used to process the CPIs, 40, 50, 60, 70, and 80 keV monochromatic images of 130 spectral CT images. AI-based histogram parameters by logistic regression analysis. The diagnostic performance was evaluated by the receiver operating characteristic (ROC) curves, and Delong's test was used to compare the CPIs group with the VMIs group.

RESULTS

When distinguishing IAC from MIA, the diagnostic efficiency of total mass was obtained at 80 keV, which was superior to those of other energy levels (P < 0.05). And Delong's test indicated that the differences between the area-under-the-curve (AUC) values of the CPIs group and the VMIs group were not statistically significant (P > 0.05).

CONCLUSION

The AI algorithm trained on CPIs showed consistent diagnostic performance on VMIs. When pulmonary GGNs are encountered in clinical practice, 80 keV could be the optimal virtual monochromatic energy for the identification of preoperative IAC on a non-enhanced chest CT.

Applications of artificial intelligence in computed tomography imaging for phenotyping pulmonary hypertension

PURPOSE OF REVIEW

Pulmonary hypertension is a heterogeneous condition with significant morbidity and mortality. Computer tomography (CT) plays a central role in determining the phenotype of pulmonary hypertension, informing treatment strategies. Many artificial intelligence tools have been developed in this modality for the assessment of pulmonary hypertension. This article reviews the latest CT artificial intelligence applications in pulmonary hypertension and related diseases.

RECENT FINDINGS

Multistructure segmentation tools have been developed in both pulmonary hypertension and nonpulmonary hypertension cohorts using state-of-the-art UNet architecture. These segmentations correspond well with those of trained radiologists, giving clinically valuable metrics in significantly less time. Artificial intelligence lung parenchymal assessment accurately identifies and quantifies lung disease patterns by integrating multiple radiomic techniques such as texture analysis and classification. This gives valuable information on disease burden and prognosis. There are many accurate artificial intelligence tools to detect acute pulmonary embolism. Detection of chronic pulmonary embolism proves more challenging with further research required.

SUMMARY

There are numerous artificial intelligence tools being developed to identify and quantify many clinically relevant parameters in both pulmonary hypertension and related disease cohorts. These potentially provide accurate and efficient clinical information, impacting clinical decision-making.

Low KeV virtual monoenergetic images for detecting low dose iodine- or alternative Gd-based IV contrast agents

Background

The recent shortage of iodine-based intravenous contrast and its cost highlight the need for limiting dose and alterative agents.

Purpose

To quantify radiodensity (Hounsfield Units, HU) improvement and potential iodine dose reduction with low keV imaging compared to conventional polyenergetic reconstructions on dual source (DSCT) and dual layer (DLCT) CT and to assess potential utility of non-iodine gadolinium-alternatives with low keV imaging.

Materials and methods

This phantom study used dilutions of three commercially-available contrast agents scanned by DSCT and DLCT. Conventional polyenergetic and virtual monoenergetic images (VMI) were reconstructed of each of five dilutions at five keV levels. HU and signal-to-noise ratios were compared among iodine- and gadolinium-based contrast agents.

Results

Iodine- and gadolinium-based contrast agent HU increased inversely to keV for the same dilution in both scanners. At the lowest keV setting (40 keV), iodine-based contrast agent HU in VMIs with DLCT and DSCT were approximately 300 % and 400 % of conventional, respectively. Gd-based contrast agent HU in VMIs at low keV were similar to or better than conventional iodine HU. Comparing the dual energy CTs, although HU from iodine and gadolinium-based contrast agents for conventional polyenergetic reconstructions was similar, HU in VMIs of DSCT were right shifted compared to DLCT by ∼10 keV lower.

Conclusion

Depending on CT scanner type, 1/3 to 1/4 dose of iodinated contrast at 40 keV provides HU similar to full dose conventional acquisition, suggesting 1/3-1/4 dose may be adequate clinically at 40 keV. Depending on the Gd-based contrast and CT type, Gd-based contrast at 40 keV provides similar or greater HU compared to conventional acquisitions with iodinated contrast, suggesting Gd-based contrast at 40 keV may serve as an alternative to iodinated contrast. HU on VMI images is scanner dependent, suggesting scanner-dependent protocol optimization and potentially monoenergy HU calibration between scanners is needed.

Angle Dependence of Electrode Lead-Related Artifacts in Single- and Dual-Energy Cardiac ECG-Gated CT Scanning-A Phantom Study

Background: The electrodes of implantable cardiac devices (ICDs) may cause significant problems in cardiac computed tomography (CT) because they are a source of artifacts that obscure surrounding structures and possible pathology. There are a few million patients currently with ICDs, and some of these patients will require cardiac imaging due to coronary artery disease or problems with ICDs. Modern CT scanners can reduce some of the metal artifacts because of MAR software, but in some vendors, it does not work with ECG gating. Introduced in 2008, dual-energy CT scanners can generate virtual monoenergetic images (VMIs), which are much less susceptible to metal artifacts than standard CT images. Objective: This study aimed to evaluate if dual-energy CT can reduce metal artifacts caused by ICD leads by using VMIs. The second objective was to determine how the angle between the electrode and the plane of imaging affects the severity of the artifacts in three planes of imaging. Methods: A 3D-printed model was constructed to obtain a 0-90-degree field at 5-degree intervals between the electrode and each of the planes: axial, coronal, and sagittal. This electrode was scanned in dual-energy and single-energy protocols. VMIs with an energy of 40-140 keV with 10 keV intervals were reconstructed. The length of the two most extended artifacts originating from the tip of the electrode and 2 cm above it-at the point where the thick metallic defibrillating portion of the electrode begins-was measured. Results: For the sagittal plane, these observations were similar for both points of the ICDs that were used as the reference location. VMIs with an energy over 80 keV produce images with fewer artifacts than similar images obtained in the single-energy scanning mode. Conclusions: Virtual monoenergetic imaging techniques may reduce streak artifacts arising from ICD electrodes and improve the quality of the image. Increasing the angle of the electrode as well as the imaging plane can reduce artifacts. The angle between the electrode and the beam of X-rays can be increased by tilting the gantry of the scanner or lifting the upper body of the patient.

Roles of spectral dual-layer CT, D-dimer concentration, and COVID-19 pneumonia in diagnosis of pulmonary embolism

Purpose

To demonstrate advantages of spectral dual-layer computed tomography (CT) in diagnosing pulmonary embolism (PE). To compare D-dimer values in patients with PE and concomitant COVID-19 pneumonia to those in patients without PE and COVID-19 pneumonia. To compare D-dimer values in cases of minor versus extensive PE.

Methods

A monocentric retrospective study of 1500 CT pulmonary angiographies (CTPAs). Three groups of 500 consecutive examinations: 1) using conventional multidetector CT (CTC), 2) using spectral dual-layer CT (CTS), and 3) of COVID-19 pneumonia patients using spectral dual-layer CT (COV). Only patients with known D-dimer levels were enrolled in the study.

Results

Prevalence of inconclusive PE findings differed significantly between CTS and CTC (0.8 % vs. 5.4 %, p < 0.001). In all groups, D-dimer levels were significantly higher in PE positive patients than in patients without PE (CTC, 8.04 vs. 3.05 mg/L; CTS, 6.92 vs. 2.57 mg/L; COV, 10.26 vs. 2.72 mg/L, p < 0.001). There were also statistically significant differences in D-dimer values between minor and extensive PE in the groups negative for COVID-19 (CTC, 5.16 vs. 8.98 mg/L; CTS 3.52 vs. 9.27 mg/L, p < 0.001). The lowest recorded D-dimer value for proven PE in patients with COVID-19 pneumonia was 1.19 mg/L.

Conclusion

CTPAs using spectral dual-layer CT reduce the number of inconclusive PE findings. Plasma D-dimer concentration increases with extent of PE. Cut-off value of D-dimer with 100 % sensitivity for patients with COVID-19 pneumonia could be doubled to 1.0 mg/L. This threshold would have saved 110 (22 %) examinations in our cohort.

Photon-counting CT in Thoracic Imaging: Early Clinical Evidence and Incorporation Into Clinical Practice

Photon-counting CT (PCCT) is an emerging advanced CT technology that differs from conventional CT in its ability to directly convert incident x-ray photon energies into electrical signals. The detector design also permits substantial improvements in spatial resolution and radiation dose efficiency and allows for concurrent high-pitch and high-temporal-resolution multienergy imaging. This review summarizes (a) key differences in PCCT image acquisition and image reconstruction compared with conventional CT; (b) early evidence for the clinical benefit of PCCT for high-spatial-resolution diagnostic tasks in thoracic imaging, such as assessment of airway and parenchymal diseases, as well as benefits of high-pitch and multienergy scanning; (c) anticipated radiation dose reduction, depending on the diagnostic task, and increased utility for routine low-dose thoracic CT imaging; (d) adaptations for thoracic imaging in children; (e) potential for further quantitation of thoracic diseases; and (f) limitations and trade-offs. Moreover, important points for conducting and interpreting clinical studies examining the benefit of PCCT relative to conventional CT and integration of PCCT systems into multivendor, multispecialty radiology practices are discussed.

Editorial for the Special Issue "Cardiothoracic Imaging: Recent Techniques and Applications in Diagnostics"

Technology is making giant strides and is increasingly improving the diagnostic imaging of both frequent and rare acute and chronic diseases [...].

[Research progress on the identification of central lung cancer and atelectasis using multimodal imaging]

Central lung cancer is a common disease in clinic which usually occurs above the segmental bronchus. It is commonly accompanied by bronchial stenosis or obstruction, which can easily lead to atelectasis. Accurately distinguishing lung cancer from atelectasis is important for tumor staging, delineating the radiotherapy target area, and evaluating treatment efficacy. This article reviews domestic and foreign literatures on how to define the boundary between central lung cancer and atelectasis based on multimodal images, aiming to summarize the experiences and propose the prospects.

Portable Single-Exposure Dual-Energy X-ray Detector for Improved Point-of-Care Diagnostic Imaging

INTRODUCTION

Dual-energy subtraction (DES) imaging is well known to reduce anatomical noise and enable material classification. The current approaches to DES imaging have trade-offs, such as motion artifacts, low sensitivity because of losses in a mid-filter, and lack of portability. Recently, a portable triple-layer flat-panel detector (FPD) was proposed for use in single-shot DES imaging that can provide improved sensitivity and removal of motion artifacts in a point-of-care setting. The purpose of this study is to evaluate the feasibility of such a detector. Various image quality metrics and clinical images are provided.

MATERIALS AND METHODS

An FDA-cleared single-exposure DES FPD consisting of three stacked sensors was used for all measurements. This detector generates three images per exposure: A digital radiography (DR) image, i.e., as would be produced with a conventional detector, and two DES images, bone and soft tissue. To evaluate DR image quality, detective quantum efficiency (DQE) and modulation transfer function were measured for multiple radiation quality beams. Digital radiography and DES images obtained from this FPD were evaluated in previously reported fixed and portable clinical studies. Digital radiography and DES images from case studies are presented for qualitative assessment.

RESULTS

Modulation transfer function and DQE were measured across multiple radiation quality beams for the DR image. The DES images showed good tissue separation and uniformity with no visible motion or alignment artifacts. The DES images, when read in conjunction with the DR image, resulted in increased reader confidence and revealed abnormalities or details that were sometimes overlooked in the DR image.

CONCLUSIONS

The proposed panel produces high-quality DR images as indicated by the DQE and modulation transfer function. The DES images have been shown to improve sensitivity in clinical applications and increase reader confidence. This detector can enable DES in portable or otherwise difficult applications, opening new doors for improved patient care.

Advances for Pulmonary Functional Imaging: Dual-Energy Computed Tomography for Pulmonary Functional Imaging

Dual-energy computed tomography (DECT) can improve the differentiation of material by using two different X-ray energy spectra, and may provide new imaging techniques to diagnostic radiology to overcome the limitations of conventional CT in characterizing tissue. Some techniques have used dual-energy imaging, which mainly includes dual-sourced, rapid kVp switching, dual-layer detectors, and split-filter imaging. In iodine images, images of the lung's perfused blood volume (PBV) based on DECT have been applied in patients with pulmonary embolism to obtain both images of the PE occluding the pulmonary artery and the consequent perfusion defects in the lung's parenchyma. PBV images of the lung also have the potential to indicate the severity of PE, including chronic thromboembolic pulmonary hypertension. Virtual monochromatic imaging can improve the accuracy of diagnosing pulmonary vascular diseases by optimizing kiloelectronvolt settings for various purposes. Iodine images also could provide a new approach in the area of thoracic oncology, for example, for the characterization of pulmonary nodules and mediastinal lymph nodes. DECT-based lung ventilation imaging is also available with noble gases with high atomic numbers, such as xenon, which is similar to iodine. A ventilation map of the lung can be used to image various pulmonary diseases such as chronic obstructive pulmonary disease.

Dual-Energy CT in Cardiothoracic Imaging: Current Developments

This article describes the technical principles and clinical applications of dual-energy computed tomography (DECT) in the context of cardiothoracic imaging with a focus on current developments and techniques. Since the introduction of DECT, different vendors developed distinct hard and software approaches for generating multi-energy datasets and multiple DECT applications that were developed and clinically investigated for different fields of interest. Benefits for various clinical settings, such as oncology, trauma and emergency radiology, as well as musculoskeletal and cardiovascular imaging, were recently reported in the literature. State-of-the-art applications, such as virtual monoenergetic imaging (VMI), material decomposition, perfused blood volume imaging, virtual non-contrast imaging (VNC), plaque removal, and virtual non-calcium (VNCa) imaging, can significantly improve cardiothoracic CT image workflows and have a high potential for improvement of diagnostic accuracy and patient safety.

Characterizing incidental mass lesions in abdominal dual-energy CT compared to conventional contrast-enhanced CT

BACKGROUND

Incidental findings are common in abdominal computed tomography (CT) and often warrant further investigations with economic implications as well as implications for patients.

PURPOSE

To evaluate the potential of dual-energy CT (DECT) in the identification and/or characterization of abdominal incidental mass lesions compared to conventional contrast-enhanced CT.

MATERIAL AND METHODS

This retrospective study from a major tertiary hospital included 96 patients, who underwent contrast-enhanced abdominal DECT. Incidental lesions in adrenals, kidneys, liver, and pancreas were evaluated by two board-certified abdominal radiologists. Observer 1 only had access to standard CT reconstructions, while observer 2 had access to standard CT as well as DECT reconstructions. Disagreements were resolved by consensus review and used as a reference for observers using McNemar's test.

RESULTS

Observers 1 and 2 identified a total of 40 and 34 findings, respectively. Furthermore, observer 1 registered 13 lesions requiring follow-up, of which seven (two renal and five adrenal lesions) were resolved following consensus review using DECT (P = 0.008). The inter-observer agreement was near perfect (κ = 0.82).

CONCLUSION

DECT has the potential to improve the immediate characterization of incidental findings when compared to conventional CT for abdominal imaging.

Imaging Depiction of Hypoxic Pulmonary Vasoconstriction Using Dual-Energy CT

In this article, we aim to highlight the utility of dual-energy computed tomography (DECT) in demonstrating imaging changes due to hypoxic pulmonary vasoconstriction (HPV). DECT allows detailed image reconstructions that have been shown to better characterize cardiothoracic pathologies, as compared to conventional CT techniques. DECT simultaneously detects two different X-ray energies, which enables generation of iodine density maps, virtual monoenergetic images, and effective atomic number maps (Z_eff), among others. DECT has been shown to have utility in the assessment of benign versus malignant pulmonary nodules, pulmonary embolism, myocardial perfusion defects, and other conditions. Herein, we describe four cases of indeterminate pulmonary pathology when imaged with conventional CT in which subsequent use of DECT-derived image reconstructions demonstrated HPV as the underlying pathophysiological mechanism. The goal of this article is to understand the imaging appearance of HPV on DECT and discuss how HPV may mimic other causes of perfusion defects.

Coronary calcium scoring using virtual non-contrast reconstructions on a dual-layer spectral CT system: Feasibility in the clinical practice

PURPOSE

To evaluate the clinical applicability of a prototype virtual non-contrast (VNC) reconstruction algorithm based on coronary CT angiography (cCTA) to assess calcified coronary plaques by calcium scoring (CACS).

METHODS

Eighty consecutive patients suspected of coronary artery disease were retrospectively included. All patients underwent a cardiac CT using a dual-layer spectral-detector CT system. The standardized acquisition protocol included unenhanced CACS and cCTA. Datasets were acquired using 120 keV. VNC-reconstructions were calculated from the cCTA images at 2.5 mm (VNC group 1), 2.5 of 0.9 mm (group 2), and 0.9 mm (group 3) slice thickness. We compared the Agatston score and Coronary Artery Calcium Data and Reporting System (CAC-DRS) of all VNC reconstructions with the true non-contrast (TNC)-dataset as the gold standard.

RESULTS

In total, 73 patients were evaluated. Fifty patients (68.5 %) had a CACS > 0 based on TNC. We found a significant difference in the Agatston score comparing all VNC-reconstructions (1: 1.35, 2: 3.7, 3: 10.4) with the TNC dataset (3.8) (p < 0.001). Correlation analysis of the datasets showed an excellent correlation of the TNC results with the different VNC-reconstructions (r = 0.904-0.974, p < 0.001) with a slope of 1.89-2.53. Mean differences and limits of agreement by Bland-Altman analysis between TNC and group 1 were 83 and -196 to 362, respectively. By using the VNC-reconstructions, in group 1 23 patients (31.5 %), in group 2 10 (13.7 %), and in group 3 23 (31.5 %) were reclassified according to CAC-DRS compared to TNC. Classification according to CAC-DRS revealed a significant difference between TNC and group 1 (p = 0.024) and no significance compared to groups 2 and 3 (p = 0.670 and 0.273).

CONCLUSION

The investigated VNC reconstruction algorithm of routine cCTA allows the detection and evaluation of coronary calcium burden without the requirement for an additional acquisition of an unenhanced CT scan for CACS and, therefore, a reduction of radiation exposure.

Innovations in thoracic imaging: CT, radiomics, AI and x-ray velocimetry

In recent years, pulmonary imaging has seen enormous progress, with the introduction, validation and implementation of new hardware and software. There is a general trend from mere visual evaluation of radiological images to quantification of abnormalities and biomarkers, and assessment of ‘non visual’ markers that contribute to establishing diagnosis or prognosis. Important catalysts to these developments in thoracic imaging include new indications (like computed tomography [CT] lung cancer screening) and the COVID‐19 pandemic. This review focuses on developments in CT, radiomics, artificial intelligence (AI) and x‐ray velocimetry for imaging of the lungs. Recent developments in CT include the potential for ultra‐low‐dose CT imaging for lung nodules, and the advent of a new generation of CT systems based on photon‐counting detector technology. Radiomics has demonstrated potential towards predictive and prognostic tasks particularly in lung cancer, previously not achievable by visual inspection by radiologists, exploiting high dimensional patterns (mostly texture related) on medical imaging data. Deep learning technology has revolutionized the field of AI and as a result, performance of AI algorithms is approaching human performance for an increasing number of specific tasks. X‐ray velocimetry integrates x‐ray (fluoroscopic) imaging with unique image processing to produce quantitative four dimensional measurement of lung tissue motion, and accurate calculations of lung ventilation.

See relatedEditorial

Dual-Energy Imaging of the Chest

Dual-energy computed tomography (DECT) is a contemporary development by which the tissue can be characterized beyond conventional computed tomography. It improves tissue differentiation by exploiting the X-ray absorptive property of the tissues. Although still in its early stages, DECT utilization in pulmonary and cardiovascular pathologies is emerging. It includes applications such as pulmonary embolism, pulmonary hypertension, myocardial perfusion, and coronary artery assessment. This article discusses DECT principles and their current and emerging applications in thoracic imaging.

Differential Diagnosis of Preinvasive Lesions in Small Pulmonary Nodules by Dual Source Computed Tomography Imaging

This study was aimed to explore the differential diagnosis value of preinvasive lesions/minimally invasive adenocarcinoma and invasive adenocarcinoma manifesting as small pulmonary nodules under dual source computed tomography (DSCT) imaging. The patients with nodular manifestations of adenocarcinoma in situ (AIS)/microinfiltrating adenocarcinoma (MIA) were selected as group X, including 14 cases. A total of 31 cases with nodular infiltrating adenocarcinoma were selected as group Y. The enhanced dual-energy image obtained by DSCT dual-energy scan was transferred to the software to obtain the energy image and iodine distribution map. SPSS 18.0 was used for statistical analysis. P < 0.05 was considered statistically significant. All measurements were labeled as mean x͞±S standard deviation. In the CT findings of microinfiltrating adenocarcinoma and infiltrating adenocarcinoma, lobulation sign, burr sign, vacuole sign, and pleural depression sign can help the diagnosis of infiltrating adenocarcinoma. The results showed that lobulation sign, burr sign, vacuole sign, and pleural depression sign could be used as the distinguishing feature of preinvasive lesion/microinvasive adenocarcinoma and invasive adenocarcinoma. Receiver-operating characteristic (ROC) curve analysis showed that the critical value, sensitivity, and specificity of lesion diameter ≥1.4 cm and CT value ≥14.14HU for diagnosis of invasive lung adenocarcinoma were 1.32 and 14.14, 88.4% and 94.4%, and 67.3% and 75.8%, respectively. There were substantial differences in CT values between the two groups under low energy level (42-99 kev) (P < 0.05). DSCT dual-energy imaging can quantitatively identify preinvasive pulmonary nodules with multiple parameters.

Echocardiographic Assessment of Mitral Annular Disjunction With Cross-Correlation by Computed Tomography and Magnetic Resonance Imaging: A Case Series

Mitral valve (MV) pathology, along with its associated peripheral anatomy, is one of the most common categories of heart disease. Two-dimensional (2D) transthoracic echocardiography (TTE) plays a prominent role in the detection and management of various types MV disease, specifically mitral annular disjunction (MAD). MAD is defined as a structural abnormality of the mitral annulus fibrosus, causing a noticeable gap between the atrial wall-mitral valve junction and the basilar portion of the left ventricular free wall (LV). The integral role that cardiac sonographers play in identifying MAD cannot be underscored, as well as the risk of easily overlooking this unique abnormality. Often associated with mitral valve prolapse (MVP), accurate documentation of MAD amid an echocardiographic study can have positive implications on patient prognosis. This case series highlights the echocardiographic characteristics of MAD, to raise awareness of this often forgotten feature of myxomatous mitral valves, which can indeed cause adverse patient outcomes. It is important to demonstrate correlational features with additional imaging techniques such as magnetic resonance imaging (MRI) and computed tomography (CT).

Diagnostic performance of electron-density dual-energy CT in detection of cervical disc herniation in comparison with standard gray-scale CT and virtual non-calcium images

Objectives

To assess the diagnostic performance of dual-energy CT (DECT) with electron-density (ED) image reconstruction compared with standard CT (SC) and virtual non-calcium (VNCa) image CT reconstruction for detecting cervical disc herniation.

Methods

This cross-sectional study was approved by the IRB. We enrolled 64 patients (336 intervertebral discs from C2/3 to C7/T1; mean age, 55 years; 17 women and 47 men) who underwent DECT with spectral reconstruction and 3-T MRI within 2 weeks between January 2018 and June 2020. Four radiologists independently evaluated the first image set of randomized SC, VNCa, and ED images to detect cervical disc herniation. After 8 weeks, the readers re-evaluated the second and the last image sets with an 8-week interval. MRI evaluations performed by two other experienced served as the reference standard. Comparing diagnostic performance between each images set was evaluated by a generalized estimating equation.

Results

A total of 233 cervical disc herniations were noted on MRI. For detecting cervical disc herniation, electron-density images showed higher sensitivity (94% [219/233; 95% CI, 90–97] vs. 76% [177/233; 70–81] vs. 69% [160/233; 62–76]) (p < 0.001) and similar specificity (90% [93/103; 83–95] vs. 89% [92/103; 82–96] vs. 90% [93/103; 83–95]) (p > 0.05) as SC and VNCa images, respectively. Inter-reader agreement for cervical disc herniation calculated among the four readers was moderate for all image sets (κ = 0.558 for ED, κ = 0.422 for SC, and κ = 0.449 for VNCa).

Conclusion

DECT with ED reconstruction can improve cervical disc herniation detection and diagnostic confidence compared with SC and VNCa images.

Key Points

• Intervertebral discs with high material density are well visualized on electron-density images obtained from dual-energy CT.

• Electron-density images showed much higher sensitivity and diagnostic accuracy than standard CT and virtual non-calcium images for the detection of cervical disc herniation.

• Electron-density images can have false-negative results, especially for disc herniation with high signal intensity on T2W images and can show pseudo-disc extrusion at the lower cervical spine.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00330-021-08374-y.

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.

"Multimodality imaging of the extrapleural space lesions"

Extrapleural space (EPS) is a potential space between the outer layer of the parietal pleura and the inner layer of the chest wall and the diaphragm. Many different pathologies including chronic inflammatory conditions, infections, trauma, neoplastic disease (both benign and malignant) as well as many infiltrative disorders can involve the EPS. It is one of the frequently overlooked entity on imaging due to relative lack of understanding of the anatomy and the imaging appearances of the diseases localized to this space. The knowledge of the EPS is essential for the radiologists as the pathologies which involve the EPS may require different treatment approach compared to pleural or parenchymal lung disease. Additionally, the EPS involvement may influence the staging and treatment planning for chest malignancies. In this review, we give an overview of the anatomy and various pathologies involving EPS, utility of different imaging modalities in the evaluation of EPS lesions with emphasis on cross sectional imaging and emerging technologies like spectral CT and its role in recognizing the imaging features which enable specific diagnosis of various pathologies.

Mitral annular disjunction in patients with severe aortic stenosis: Extent and reproducibility of measurements with computed tomography

•

Mitral annulus disjunction (MAD) is frequent in patients with severe aortic stenosis.

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Computed tomography enables a highly reproducible assessment of MAD.

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MAD patients significantly more often have mitral valve prolapse.

Objectives

To determine with CT the prevalence and extent of mitral annular disjunction (MAD) in patients undergoing transcatheter aortic valve replacement (TAVR) and its association with mitral valve disease and arrhythmia.

Methods

We retrospectively evaluated 408 patients (median age, 82 years; 186 females) with severe aortic stenosis undergoing ECG-gated cardiac CT with end-systolic data acquisition. Baseline and follow-up data were collected in the context of a national registry. Two blinded, independent observers evaluated the presence of MAD on multi-planar reformations. Maximum MAD distance (left atrial wall-mitral leaflet junction to left ventricular myocardium) and circumferential extent of MAD were assessed on CT using dedicated post-processing software. Associated mitral valve disease was determined with echocardiography.

Results

7.8 % (32/408) of patients with severe aortic stenosis had MAD. The maximum MAD was 3.5 mm (interquartile range: 3.0–4.0 mm). The circumferential extent of MAD comprised 34 ± 15 % of the posterior and 26 ± 12 % of the entire mitral annulus. Intra- and interobserver agreement for the detection of MAD on CT were excellent (kappa: 0.90 ± 0.02 and 0.92 ± 0.02). Mitral regurgitation (p = 1.00) and severe mitral annular calcification (p = 0.29) were similarly prevalent in MAD and non-MAD patients. Significantly more patients with MAD (6/32; 19 %) had mitral valve prolapse compared to those without (6/376; 2 %; p < 0.001). MAD was not associated with arrhythmia before and after TAVR (p > 0.05).

Conclusions

Using CT, MAD was found in 7.8 % of patients with severe aortic stenosis, with a higher prevalence in patients with mitral valve prolapse. We found no association of MAD with arrhythmia before or after TAVR.