Clinical Applications of Dual-Energy CT

Low-dose tin-filtered computed tomography (CT) with iterative metal artifact reduction algorithm versus dual-energy CT for patients with lumbar metal implants

PURPOSE

This study aimed to evaluate a low-dose tin-filtered (LD Sn) CT protocol with iterative metal artifact reduction (iMAR) to reduce metal artifacts and radiation dose compared to dual-energy CT (DECT) with iMAR in patients with lumbar metal implants.

METHODS

The study included 70 patients, comprising 35 patients in the prospective LD Sn CT cohort and 35 matched patients in the retrospective DECT cohort, utilizing a hybrid design. Evaluations included DECT Mixed images, noise-optimized virtual monoenergetic imaging at 130 keV (DE Mono+), and LD Sn CT with and without iMAR. Objective assessments included the signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and figure of merit (FOM). A 5-point scoring system was used for subjective evaluations of image quality, including overall image quality, soft tissue visualization, bone architecture, and the degree of metal artifacts. Radiation dose metrics, including CT dose index (CTDIvol), dose length product (DLP), and effective dose (ED), were recorded.

RESULTS

The LD Sn CT protocol achieved a 26 % lower effective dose than the DECT protocol (7.34 ± 1.45 mSv vs. 9.93 ± 2.00 mSv, P < 0.05). No significant differences were observed in SNR, CNR, or FOM between LD Sn and DE Mono+ (P = 0.238-0.310). Subjective assessments, including overall image quality, soft tissue visualization, bone architecture, and the degree of metal artifact, showed slight differences without statistical significance. LD Sn iMAR scores ranged from 2.00 to 2.11, while DE Mono+ iMAR scores ranged from 1.83 to 2.00 (P = 0.120-0.763).

CONCLUSIONS

The LD Sn iMAR protocol achieved the optimal balance between image quality and radiation dose. It is recommended for routine follow-up in patients with lumbar implants.

Diagnostic performance of dual-energy computed tomography in detecting anterior cruciate ligament injuries: a systematic review and meta-analysis

OBJECTIVE

Anterior cruciate ligament (ACL) injuries are common and lead to significant physical limitations. While MRI is the diagnostic gold standard, its use is restricted in acute trauma cases due to contraindications and longer imaging times. Dual-energy computed tomography (DECT) has emerged as a potential alternative. This meta-analysis evaluates the diagnostic accuracy of DECT for ACL injuries.

MATERIALS AND METHODS

Following PRISMA guidelines, a comprehensive literature search was conducted using PubMed, Web of Science, Scopus, and Embase for studies published up to June 2024. Studies that provided diagnostic accuracy data for DECT in ACL ruptures were included. Metrics of diagnostic accuracy were aggregated using a bivariate random effects model.

RESULTS

The meta-analysis, which included five studies with a total of 191 patients, found that DECT had a pooled sensitivity of 88.1% (95% CI, 78.0-93.9%) and a specificity of 82.0% (95% CI, 62.0-92.7%) for diagnosing ACL ruptures, with an AUC of 0.92 (95% CI, 0.72-0.96). For complete ruptures, sensitivity was 83.2% (95% CI, 68.2-92.0%), and specificity was 94.9% (95% CI, 92.2-96.7%), with an AUC of 0.96 (95% CI, 0.81-0.98). In acute/subacute settings, sensitivity was 89.4% (95% CI, 76.8-95.6%), and specificity was 82.1% (95% CI, 56.2-94.2%), with an AUC of 0.93 (95% CI, 0.71-0.97).

CONCLUSION

Our findings suggest that DECT is a valuable diagnostic tool for ACL injuries, particularly as an adjunct or alternative when MRI is unavailable or contraindicated, enabling timely and accurate diagnosis.

Technique selection and technical developments for 2D dual-energy subtraction angiography on an interventional C-arm

BACKGROUND

Dual-energy (DE) x-ray image acquisition has the potential to provide material-specific angiographic images in the interventional suite. This approach can be implemented with novel detector technologies, such as dual-layer and photon-counting detectors. Alternatively, DE imaging can be implemented on existing systems using fast kV-switching. Currently, there are no commercially available DE options for interventional platforms.

PURPOSE

This study reports on the development of a prototype fast kV-switching DE subtraction angiography system. In contrast to alternative approaches to DE imaging in the interventional suite, this prototype uses a clinically available interventional C-arm equipped with special x-ray tube control software. An automatic exposure control algorithm and technical features needed for such a system in the interventional setting are developed and validated in phantom studies.

METHODS

Fast kV-switching was implemented on an interventional C-arm platform using software that enables frame-by-frame specification of x-ray tube techniques (e.g., tube voltage/kV, pulse width/ms, tube current/mA). A real-time image display was developed on a portable workstation to display DE subtraction images in real-time (nominal 15 frame/s). An empirical CNR-driven automatic exposure control (AEC) algorithm was created to guide DE tube technique selection (kV pair, ms pair, mA). The AEC model contained a look-up table which related DE tube technique parameters and air kerma to iodine CNR, which was measured in acrylic phantom models containing an iodine-equivalent reference object. For a given iodine CNR request, the AEC algorithm estimated patient thickness and then selected the DE tube technique expected to deliver the requested CNR at the minimum air kerma. The AEC algorithm was developed for DE imaging performed without and with the application of anti-correlated noise reduction (ACNR). Validation of the AEC model was performed by comparing the AEC-predicted iodine CNR values with directly measured values in a separate phantom study. Both dose efficiency (CNR2/kerma) and maximum achievable iodine CNR (within tube technique constraints) were quantified. Finally, improvements in DE iodine CNR were quantified using a novel variant to the ACNR approach, which used machine-learning image denoising (ACNR-ML).

RESULTS

The prototype system provided a continuous display of DE subtraction images. For standard DE imaging, the AEC-predicted iodine CNR values agreed with directly measured values to within 3.5% ± 1.6% (mean ± standard deviation). When ACNR was applied, predicted iodine CNR agreed with measurement to within 2.1% ± 3.3%. AEC-generated DE techniques were typically (low/high energy): 63/125 kV, 10/3.2 ms, with varying mA values. When ACNR was applied, dose efficiency was increased by a factor of 9.37 ± 2.08 and maximum CNR was increased by a factor of 3.29 ± 0.21 relative to DE without denoising. Application of ACNR-ML yielded a greater increase in both the dose efficiency (16.11 ± 2.99) and maximum CNR (4.46 ± 0.31) compared to DE without denoising.

CONCLUSION

A prototype DE subtraction angiography system using fast kV-switching was implemented on a clinically available interventional C-arm platform without modification of system hardware. The technical features presented in this work include a real-time image display, noise-reduction strategies, and a CNR-driven AEC algorithm. This prototype system demonstrates the feasibility of 2D dual-energy imaging for image-guided interventions.

Dual-Energy Computed Tomography Applications in Rheumatology

Dual-energy computed tomography (DECT) has emerged as a transformative tool in the past decade. Initially employed in gout within the field of rheumatology to distinguish and quantify monosodium urate crystals through its dual-material discrimination capability, DECT has since broadened its clinical applications. It now encompasses various rheumatic diseases, employing advanced techniques such as bone marrow edema assessment, iodine mapping, and collagen-specific imaging. This review article aims to examine the unique characteristics of DECT, discuss its strengths and limitations, illustrate its applications for accurately evaluating various rheumatic diseases in clinical practice, and propose future directions for DECT in rheumatology.

Implications and pathophysiology of neuroinflammation in pediatric patients with traumatic brain injury: an updated review

Traumatic Brain Injury (TBI) in children is a profound public health issue with the potential to disrupt cognitive, behavioral, and psychosocial development significantly. This review provides an updated examination of the role of neuroinflammation in pediatric TBI, emphasizing its dual impact on injury progression and recovery. Highlighted is the complex interplay of primary and secondary injury mechanisms, including the critical contributions of neuroinflammatory responses mediated by central and peripheral immune cells. Advances in biomarker identification and imaging techniques are discussed, showcasing how tools like diffusion tensor imaging (DTI) and positron emission tomography (PET) enhance our understanding of neuroinflammatory processes. The review also explores current therapeutic strategies targeting neuroinflammation, underscoring emerging treatments such as pharmacologic agents that modulate immune responses and novel therapies like stem cell interventions. This comprehensive review seeks to deepen the understanding of neuroinflammation's pathophysiological roles in pediatric TBI and propose directions for future clinical and research efforts.

Predicting complications and morbidities in PAD patients through lower extremity compositions with dual-energy CT and material decomposition: a 2-year follow-up observational study

BACKGROUND

Peripheral artery disease (PAD) is associated with various morbidities. This study aims to investigate the correlation between different lower extremity compositions and development of morbidities in PAD patients.

METHODS

Between January 2018 and December 2020, 108 subjects diagnosed of PAD were enrolled (mean age of 64.1 ± 13.5 years) and utilized dual-energy computed tomography (DECT) with material decomposition to measure the vessel volume, muscle volume, fat volume, and cortical-bone volume in lower extremity respectively. The association between each leg composition and developing complications or morbidities in PAD patients was analyzed over a two-year follow-up.

RESULTS

Fontaine stage 3 and 4 had lower muscle mass compared to stages 1 and 2. More severe vascular stenosis was associated with lower muscle, fat, and cortical-bone volume. Patients with severe Fontaine stages (3 and 4) and lower-leg vascular stenosis had a higher risk of developing infection or inflammation (OR 45.5, 95% CI: 13.5-166.7, and OR 11.7, 95% CI: 2.8-50, P < 0.05) and amputation (OR 18.2, 95% CI: 2.2-142.8, and OR 10.7, 95% CI: 1.11-100, P < 0.05). Lower thigh cortical-bone volume was associated with an increased risk of falls resulting in fractures (OR: 1.39, 95% CI: 1.13-2.19, P < 0.01). Thigh cortical-bone volume below 64.5 cm3 was identified as the cut-off value to predict fall-related fractures, with a sensitivity of 100% and specificity of 92%.

CONCLUSIONS

This study demonstrates the potential of DECT with material decomposition to assess lower extremity composition and its relevance in predicting complications and morbidities in PAD patients. Severe vascular stenosis may contribute to muscle wasting and subsequent complications, while lower thigh cortical-bone mass may serve as a predictor of fall-related fractures.

The role of dual-energy computed tomography (DECT) in emergency radiology: a visual guide to advanced diagnostics

Dual-energy computed tomography (DECT) has become an essential tool in emergency radiology, significantly enhancing diagnostic capabilities for a variety of acute conditions. By utilising two distinct X-ray energy spectra, DECT differentiates materials based on their attenuation properties, providing detailed insights into tissue composition and pathology. In emergency settings, DECT is used in thoracic imaging for the detection of pulmonary embolism, in abdominal imaging to enhance the diagnosis and characterisation of conditions such as pancreatitis, appendicitis, gastrointestinal bleeding, and bowel ischaemia and in the genitourinary system for identifying kidney stones, pyelonephritis, and urinary bleeding. In neuroimaging, DECT enables image optimisation through virtual monochromatic images and the reduction of metal artifacts. It helps in the differential diagnosis of haemorrhage versus tumour-related haemorrhage, haemorrhage versus contrast extravasation, and in the dating of vertebral collapse. DECT offers several advantages, including enhanced visualisation, the potential to reduce radiation exposure and contrast medium, and improved diagnostic accuracy across a wide range of conditions. However, its routine clinical adoption is still evolving due to challenges such as limited availability, cost, and the need for specialised training. This pictorial essay aims to encourage the broader integration of DECT into emergency imaging protocols by showcasing its clinical applications and benefits.

Innovative Approaches for the Treatment of Spinal Disorders: A Comprehensive Review

This comprehensive review explores the latest advancements in the management of spinal disorders, including minimally invasive surgical techniques, treatment of complex deformities, disc replacement technologies, and non-surgical approaches. The review highlights the potential of innovations such as robotic-assisted surgeries, regenerative medicine, and artificial intelligence to enhance precision, reduce recovery times, and improve patient outcomes. It also discusses the integration of wearable technologies and personalized medicine in tailoring treatments. Challenges such as high costs, accessibility issues, and limited long-term data are critically analyzed, alongside gaps in research, including a lack of diversity in study populations and insufficient economic evaluations. Future directions emphasize the need for multidisciplinary collaboration to develop durable, accessible, and personalized solutions to address the global burden of spinal disorders.

Comparing two deep learning spectral reconstruction levels for abdominal evaluation using a rapid-kVp-switching dual-energy CT scanner

PURPOSE

Deep Learning Spectral Reconstruction (DLSR) potentially improves dual-energy CT (DECT) image quality, but there is a paucity of research involving human abdominal DECT scans. The purpose of this study was to comprehensively evaluate image quality by quantitatively and qualitatively comparing strong and standard levels of a DLSR algorithm. Optimal virtual monochromatic image (VMI) energy levels were also evaluated.

METHODS

DECT scans of the abdomen/pelvis from 51 patients were retrospectively evaluated. VMIs were reconstructed at energy levels ranging from 35 to 200 keV using both standard and strong DLSR levels. For quantitative analysis, various abdominal structures were assessed using regions of interest, and mean signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) values were calculated. This was supplemented with a qualitative evaluation of VMIs reconstructed at 35, 45, 55, and 65 keV.

RESULTS

The strong-level DLSR demonstrated significantly better SNR and CNR values (p < 0.0001) compared to standard-level DLSR across all structures. The optimal SNR was observed at 70 keV (p < 0.0001), while the optimal CNR was found at 65 keV (p < 0.0001). The average qualitative scores between standard and strong DLSR were significantly different at 45, 55, and 65 keV (p < 0.0001). There was a moderate level of agreement between observers (ICC = 0.427, p < 0.0001).

CONCLUSION

A DLSR set to a strong level significantly improves image quality compared to standard-level DLSR, potentially enhancing the diagnostic evaluation of abdominal DECT scans. In addition to achieving a very high SNR, 65 keV VMIs had the highest CNR, which differs from what is typically observed with traditional DECT using non-deep learning reconstruction approaches.

The optimal energy level of virtual monochromatic imaging in dual-energy CT arthrography of the wrist

OBJECTIVES

To suggest an optimal energy level of virtual monochromatic images (VMIs) in dual-energy CT (DECT) arthrography of the wrist.

METHODS

This retrospective study included 53 patients with wrist CT arthrography. Conventional polychromatic images and VMIs at 4 energy levels (40-70 keV at 10 keV intervals) were obtained. Image noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were measured, and qualitative analysis of image quality and diagnostic confidence was performed. For each patient, an energy level with the best image quality was chosen by consensus. Comparisons of quantitative and qualitative parameters between VMI sets were performed.

RESULTS

The image noise of bone and muscle were increased with decreasing energy level (P < .001). The noise of contrast was highest on 60 keV VMI. SNR and CNR (between contrast and muscle) were increased with decreasing energy level and were markedly increased between 60 and 50 keV (P < .001). The 60 keV VMI demonstrated the highest image quality and diagnostic confidence, chosen as the best diagnostic image (n = 31/53). Given that the attenuation of the contrast material was low on the conventional image, the optimal energy level of the best VMI tended to be low.

CONCLUSIONS

Wrist DECT arthrography with VMIs at 60 keV or less could improve image quality and diagnostic performance by increasing SNR and CNR in cases with low contrast attenuation.

ADVANCES IN KNOWLEDGE

Wrist DECT arthrography with VMIs at variable keV could be utilized to enhance SNR and CNR, thereby achieving diagnostic images of high quality.

The Impact of Weighting Factors on Dual-Energy Computed Tomography Image Quality in Non-Contrast Head Examinations: Phantom and Patient Study

Background: This study aims to evaluate the impact of various weighting factors (WFs) on the quality of weighted average (WA) dual-energy computed tomography (DECT) non-contrast brain images and to determine the optimal WF value. Because they simulate standard CT images, 0.4-WA reconstructions are routinely used. Methods: In the initial phase of the research, quantitative and qualitative analyses of WA DECT images of an anthropomorphic head phantom, utilizing WFs ranging from 0 to 1 in 0.1 increments, were conducted. Based on the phantom study findings, WFs of 0.4, 0.6, and 0.8 were chosen for patient analyses, which were identically carried out on 85 patients who underwent non-contrast head DECT. Three radiologists performed subjective phantom and patient analyses. Results: Quantitative phantom image analysis revealed the best gray-to-white matter contrast-to-noise ratio (CNR) at the highest WFs and minimal noise artifacts at the lowest WF values. However, the WA reconstructions were deemed non-diagnostic by all three readers. Two readers found 0.6-WA patient reconstructions significantly superior to 0.4-WA images (p < 0.001), while reader 1 found them to be equally good (p = 0.871). All readers agreed that 0.8-WA images exhibited the lowest image quality. Conclusions: In conclusion, 0.6-WA reconstructions demonstrated superior image quality over 0.4-WA and are recommended for routine non-contrast brain DECT.

Dual-energy CT applications on liver imaging: what radiologists and radiographers should know? A systematic review

PURPOSE

This review aims to provide a comprehensive summary of DECT techniques, acquisition workflows, and post-processing methods. By doing so, we aim to elucidate the advantages and disadvantages of DECT compared to conventional single-energy CT imaging.

METHODS

A systematic search was conducted on MEDLINE/EMBASE for DECT studies in liver imaging published between 1980 and 2024. Information regarding study design and endpoints, patient characteristics, DECT technical parameters, radiation dose, iodinated contrast agent (ICA) administration and postprocessing methods were extracted. Technical parameters, including DECT phase, field of view, pitch, collimation, rotation time, arterial phase timing (from injection), and venous timing (from injection) from the included studies were reported, along with formal narrative synthesis of main DECT applications for liver imaging.

RESULTS

Out of the initially identified 234 articles, 153 met the inclusion criteria. Extensive variability in acquisition parameters was observed, except for tube voltage (80/140 kVp combination reported in 50% of articles) and ICA administration (1.5 mL/kg at 3-4 mL/s, reported in 91% of articles). Radiation dose information was provided in only 40% of articles (range: 6-80 mGy), and virtual non-contrast imaging (VNC) emerged as a common strategy to reduce the radiation dose. The primary application of DECT post-processed images was in detecting focal liver lesions (47% of articles), with predominance of study focusing on hepatocellular carcinoma (HCC) (27%). Furthermore, a significant proportion of the articles (16%) focused on enhancing DECT protocols, while 15% explored metastasis detection.

CONCLUSION

Our review recommends using 80/140 kVp tube voltage with 1.5 mL/kg ICA at 3-4 mL/s flow rate. Post-processing should include low keV-VMI for enhanced lesion detection, IMs for tumor iodine content evaluation, and VNC for dose reduction. However, heterogeneous literature hinders protocol standardization.

Computed tomography numbers obtained for varying iodine contrast concentrations by different-generation dual-energy computed tomography scanners

We compared the computed tomography (CT) numbers from monochromatic images obtained using the first-generation (Discovery CT750 HD: GE Healthcare, Milwaukee, WI) and second-generation (Revolution CT: GE HealthCare) dual-energy CT (first and second DECT) scanners in phantom and clinical studies. In a polypropylene phantom, eight polypropylene tubes containing iodine at various concentrations (0.5, 1, 2, 5, 10, 12, 20, 30 mg I per ml) were arranged in an outer circle. The iodine densities and CT numbers obtained after imaging with different-generation DECT scanners were analyzed. The CT numbers from images obtained from 61 consecutive patients with aortic disease who underwent CT with different-generation DECT scanners were compared during the arterial and delayed phases. The iodine concentration obtained from second DECT was more accurate than that from the first DECT in the phantom study. A significantly higher contrast enhancement was observed with the second DECT compared with the first DECT during the arterial phase in the clinical study. Contrast enhancement was higher with the second DECT than with the first DECT, and the second DECT was effective in minimizing the use of contrast materials.

Potential of Dual-Energy CT-Based Collagen Maps for the Assessment of Disk Degeneration in the Lumbar Spine

RATIONALE AND OBJECTIVES

Lumbar disk degeneration is a common condition contributing significantly to back pain. The objective of the study was to evaluate the potential of dual-energy CT (DECT)-derived collagen maps for the assessment of lumbar disk degeneration.

PATIENTS AND METHODS

We conducted a retrospective analysis of 127 patients who underwent dual-source DECT and MRI of the lumbar spine between 07/2019 and 10/2022. The level of lumbar disk degeneration was categorized by three radiologists as follows: no/mild (Pfirrmann 1&2), moderate (Pfirrmann 3&4), and severe (Pfirrmann 5). Recall (sensitivity) and accuracy of DECT collagen maps were calculated. Intraclass correlation coefficient (ICC) was used to evaluate inter-reader reliability. Subjective evaluations were performed using 5-point Likert scales for diagnostic confidence and image quality.

RESULTS

We evaluated a total of 762 intervertebral disks from 127 patients (median age, 69.7 (range, 23.0-93.7), female, 56). MRI identified 230 non/mildly degenerated disks (30.2%), 484 moderately degenerated disks (63.5%), and 48 severely degenerated disks (6.3%). DECT collagen maps yielded an overall accuracy of 85.5% (1955/2286). Recall (sensitivity) was 79.3% (547/690) for the detection of no/mild lumbar disk degeneration, 88.7% (1288/1452) for the detection of moderate disk degeneration, and 83.3% (120/144) for the detection of severe disk degeneration (ICC=0.9). Subjective evaluations of DECT collagen maps showed high diagnostic confidence (median 4) and good image quality (median 4).

CONCLUSION

The use of DECT collagen maps to distinguish different stages of lumbar disk degeneration may have clinical significance in the early diagnosis of disk-related pathologies in patients with contraindications for MRI or in cases of unavailability of MRI.

Dual-Energy Computed Tomography Applications in Rheumatology

Dual-energy computed tomography (DECT) has emerged as a transformative tool in the past decade. Initially employed in gout within the field of rheumatology to distinguish and quantify monosodium urate crystals through its dual-material discrimination capability, DECT has since broadened its clinical applications. It now encompasses various rheumatic diseases, employing advanced techniques such as bone marrow edema assessment, iodine mapping, and collagen-specific imaging. This review article aims to examine the unique characteristics of DECT, discuss its strengths and limitations, illustrate its applications for accurately evaluating various rheumatic diseases in clinical practice, and propose future directions for DECT in rheumatology.

Assessment of thoracic disc degeneration using dual-energy CT-based collagen maps

BACKGROUND

We evaluated the role of dual-energy computed tomography (DECT)-based collagen maps in assessing thoracic disc degeneration.

METHODS

We performed a retrospective analysis of patients who underwent DECT and magnetic resonance imaging (MRI) of the thoracic spine within a 2-week period from July 2019 to October 2022. Thoracic disc degeneration was classified by three blinded radiologists into three Pfirrmann categories: no/mild (grade 1-2), moderate (grade 3-4), and severe (grade 5). The DECT performance was determined using MRI as a reference standard. Interreader reliability was assessed using intraclass correlation coefficient (ICC). Five-point Likert scales were used to assess diagnostic confidence and image quality.

RESULTS

In total, 612 intervertebral discs across 51 patients aged 68 ± 16 years (mean ± standard deviation), 28 males and 23 females, were assessed. MRI revealed 135 no/mildly degenerated discs (22.1%), 470 moderately degenerated discs (76.8%), and 7 severely degenerated discs (1.1%). DECT collagen maps achieved an overall accuracy of 1,483/1,838 (80.8%) for thoracic disc degeneration. Overall recall (sensitivity) was 331/405 (81.7%) for detecting no/mild degeneration, 1,134/1,410 (80.4%) for moderate degeneration, and 18/21 (85.7%) for severe degeneration. Interrater agreement was good (ICC = 0.89). Assessment of DECT-based collagen maps demonstrated high diagnostic confidence (median 4; interquartile range 3-4) and good image quality (median 4; interquartile range 4-4).

CONCLUSION

DECT showed an overall 81% accuracy for disc degeneration by visualizing differences in the collagen content of thoracic discs.

RELEVANCE STATEMENT

Utilizing DECT-based collagen maps to distinguish various stages of thoracic disc degeneration could be clinically relevant for early detection of disc-related conditions. This approach may be particularly beneficial when MRI is contraindicated.

KEY POINTS

A total of 612 intervertebral discs across 51 patients were retrospectively assessed with DECT, using MRI as a reference standard. DECT-based collagen maps allowed thoracic disc degeneration assessment achieving an overall 81% accuracy with good interrater agreement (ICC = 0.89). DECT-based collagen maps could be a good alternative in the case of contraindications to MRI.

Recent advances in imaging and artificial intelligence (AI) for quantitative assessment of multiple myeloma

Multiple myeloma (MM) is a malignant blood disease, but there have been significant improvements in the prognosis due to advancements in quantitative assessment and targeted therapy in recent years. The quantitative assessment of MM bone marrow infiltration and prognosis prediction is influenced by imaging and artificial intelligence (AI) quantitative parameters. At present, the primary imaging methods include computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET). These methods are now crucial for diagnosing MM and evaluating myeloma cell infiltration, extramedullary disease, treatment effectiveness, and prognosis. Furthermore, the utilization of AI, specifically incorporating machine learning and radiomics, shows great potential in the field of diagnosing MM and distinguishing between MM and lytic metastases. This review discusses the advancements in imaging methods, including CT, MRI, and PET/CT, as well as AI for quantitatively assessing MM. We have summarized the key concepts, advantages, limitations, and diagnostic performance of each technology. Finally, we discussed the challenges related to clinical implementation and presented our views on advancing this field, with the aim of providing guidance for future research.

Dual-layer spectral-detector CT for detecting liver steatosis by using proton density fat fraction as reference

OBJECTIVES

To evaluate the diagnostic accuracy of liver dual-layer spectral-detector CT (SDCT) derived parameters of liver parenchyma for grading steatosis with reference to magnetic resonance imaging-based proton density fat fraction (MRI-PDFF).

METHODS

Altogether, 320 consecutive subjects who underwent MRI-PDFF and liver SDCT examinations were recruited and prospectively enrolled from four Chinese hospital centers. Participants were classified into normal (n = 152), mild steatosis (n = 110), and moderate/severe(mod/sev) steatosis (n = 58) groups based on MRI-PDFF. SDCT liver parameters were evaluated using conventional polychromatic CT images (CTpoly), virtual mono-energetic images at 40 keV (CT40kev), the slope of the spectral attenuation curve (λ), the effective atomic number (Zeff), and liver to spleen attenuation ratio (L/S ratio). Linearity between SDCT liver parameters and MRI-PDFF was examined using Spearman correlation. Cutoff values for SDCT liver parameters in determining steatosis grades were identified using the area under the receiver-operating characteristic curve analyses.

RESULTS

SDCT liver parameters demonstrated a strong correlation with PDFF, particularly Zeff (rs = -0.856; p < 0.001). Zeff achieved an area under the curve (AUC) of 0.930 for detecting the presence of steatosis with a sensitivity of 89.4%, a specificity of 82.4%, and an AUC of 0.983 for detecting mod/sev steatosis with a sensitivity of 93.1%, a specificity of 93.5%, the corresponding cutoff values were 7.12 and 6.94, respectively. Zeff also exhibited good diagnostic performance for liver steatosis grading in subgroups, independent of body mass index.

CONCLUSION

SDCT liver parameters, particularly Zeff, exhibit excellent diagnostic accuracy for grading steatosis.

CRITICAL RELEVANCE STATEMENT

Dual-layer SDCT parameter, Zeff, as a more convenient and accurate imaging biomarker may serve as an alternative indicator for MRI-based proton density fat fraction, exploring the stage and prognosis of liver steatosis, and even metabolic risk assessment.

KEY POINTS

Liver biopsy is the standard for grading liver steatosis, but is limited by its invasive nature. The diagnostic performance of liver steatosis using SDCT-Zeff outperforms conventional CT parameters. SDCT-Zeff accurately and noninvasively assessed the grade of liver steatosis.

CT-based synthetic contrast-enhanced dual-energy CT generation using conditional denoising diffusion probabilistic model

Objective.The study aimed to generate synthetic contrast-enhanced Dual-energy CT (CE-DECT) images from non-contrast single-energy CT (SECT) scans, addressing the limitations posed by the scarcity of DECT scanners and the health risks associated with iodinated contrast agents, particularly for high-risk patients.Approach.A conditional denoising diffusion probabilistic model (C-DDPM) was utilized to create synthetic images. Imaging data were collected from 130 head-and-neck (HN) cancer patients who had undergone both non-contrast SECT and CE-DECT scans.Main Results.The performance of the C-DDPM was evaluated using Mean Absolute Error (MAE), Structural Similarity Index (SSIM), and Peak Signal-to-Noise Ratio (PSNR). The results showed MAE values of 27.37±3.35 Hounsfield Units (HU) for high-energy CT (H-CT) and 24.57±3.35HU for low-energy CT (L-CT), SSIM values of 0.74±0.22 for H-CT and 0.78±0.22 for L-CT, and PSNR values of 18.51±4.55 decibels (dB) for H-CT and 18.91±4.55 dB for L-CT.Significance.The study demonstrates the efficacy of the deep learning model in producing high-quality synthetic CE-DECT images, which significantly benefits radiation therapy planning. This approach provides a valuable alternative imaging solution for facilities lacking DECT scanners and for patients who are unsuitable for iodine contrast imaging, thereby enhancing the reach and effectiveness of advanced imaging in cancer treatment planning.

Differentiation of benign and malignant lesions in Bethesda III and IV thyroid nodules via dual-energy computed tomography quantitative parameters and morphologic features

Background

Thyroid nodules (TNs) cytologically defined as category Bethesda III and IV pose a major diagnostic challenge before surgery, demanding new methods to reduce unnecessary diagnostic thyroid lobectomies for patients with benign TNs. This study aimed to assess whether a model combining dual-energy computed tomography (DECT) quantitative parameters with morphologic features could reliably differentiate between benign and malignant lesions in Bethesda III and IV TNs.

Methods

Data from 77 patients scheduled for thyroid surgery for Bethesda III and IV TNs (malignant =48; benign =29) who underwent DECT scans were reviewed. DECT quantitative parameters including normalized iodine concentration (NIC), attenuation on the slope of spectral Hounsfield unit (HU) curve, and normalized effective atomic number (Zeff) were measured in the arterial phase (AP) and venous phase (VP). DECT quantitative parameters and morphologic features were compared between the malignant and benign cohorts. The receiver operating characteristic curve was performed to compare the performances of significant DECT quantitative parameters, morphologic features, or the models combining the DECT parameters, respectively, with morphologic features. A nomogram was constructed from the optimal performance model, and the performance was evaluated via the calibration curve and decision curve analysis.

Results

The areas under the receiver operating characteristic curve with 95% confidence interval (CI) of the NIC in the AP (AP-NIC), slope of spectral HU curve in the AP, and NZeff in the AP were 0.749 (95% CI: 0.641-0.857), 0.654 (95% CI: 0.530-0.778), and 0.722 (95% CI: 0.602-0.842), respectively. The model combining AP-NIC with enhanced blurring showed the highest diagnostic performance, with an area under the receiver operating characteristic curve (AUC), sensitivity, and specificity of 0.808, 0.854, and 0.655, respectively; it was then used to construct a nomogram. The calibration curve showed that the discrepancy between the prediction of the nomogram and actual observations was less than 5%. The decision curve analysis indicated the nomogram had a positive net benefit in threshold risk ranges of 14% to 58% or 60% to 91% for malignant Bethesda III and IV TNs.

Conclusions

The model combining AP-NIC with enhanced blurring could reliably differentiate between benign and malignant lesions in Bethesda III and IV TNs.

Generation of virtual monoenergetic images at 40 keV of the upper abdomen and image quality evaluation based on generative adversarial networks

BACKGROUND

Abdominal CT scans are vital for diagnosing abdominal diseases but have limitations in tissue analysis and soft tissue detection. Dual-energy CT (DECT) can improve these issues by offering low keV virtual monoenergetic images (VMI), enhancing lesion detection and tissue characterization. However, its cost limits widespread use.

PURPOSE

To develop a model that converts conventional images (CI) into generative virtual monoenergetic images at 40 keV (Gen-VMI40keV) of the upper abdomen CT scan.

METHODS

Totally 444 patients who underwent upper abdominal spectral contrast-enhanced CT were enrolled and assigned to the training and validation datasets (7:3). Then, 40-keV portal-vein virtual monoenergetic (VMI40keV) and CI, generated from spectral CT scans, served as target and source images. These images were employed to build and train a CI-VMI40keV model. Indexes such as Mean Absolute Error (MAE), Peak Signal-to-Noise Ratio (PSNR), and Structural Similarity (SSIM) were utilized to determine the best generator mode. An additional 198 cases were divided into three test groups, including Group 1 (58 cases with visible abnormalities), Group 2 (40 cases with hepatocellular carcinoma [HCC]) and Group 3 (100 cases from a publicly available HCC dataset). Both subjective and objective evaluations were performed. Comparisons, correlation analyses and Bland-Altman plot analyses were performed.

RESULTS

The 192nd iteration produced the best generator mode (lower MAE and highest PSNR and SSIM). In the Test groups (1 and 2), both VMI40keV and Gen-VMI40keV significantly improved CT values, as well as SNR and CNR, for all organs compared to CI. Significant positive correlations for objective indexes were found between Gen-VMI40keV and VMI40keV in various organs and lesions. Bland-Altman analysis showed that the differences between both imaging types mostly fell within the 95% confidence interval. Pearson's and Spearman's correlation coefficients for objective scores between Gen-VMI40keV and VMI40keV in Groups 1 and 2 ranged from 0.645 to 0.980. In Group 3, Gen-VMI40keV yielded significantly higher CT values for HCC (220.5HU vs. 109.1HU) and liver (220.0HU vs. 112.8HU) compared to CI (p < 0.01). The CNR for HCC/liver was also significantly higher in Gen-VMI40keV (2.0 vs. 1.2) than in CI (p < 0.01). Additionally, Gen-VMI40keV was subjectively evaluated to have a higher image quality compared to CI.

CONCLUSION

CI-VMI40keV model can generate Gen-VMI40keV from conventional CT scan, closely resembling VMI40keV.

Hepatic fat quantification in dual-layer computed tomography using a three-material decomposition algorithm

OBJECTIVES

The purpose of this study was to evaluate a three-material decomposition algorithm for hepatic fat quantification using a dual-layer computed tomography (DL-CT) and MRI as reference standard on a large patient cohort.

METHOD

A total of 104 patients were retrospectively included in our study, i.e., each patient had an MRI exam and a DL-CT exam in our institution within a maximum of 31 days. Four regions of interest (ROIs) were positioned blindly and similarly in the liver, by two independent readers on DL-CT and MRI images. For DL-CT exams, all imaging phases were included. Fat fraction agreement between CT and MRI was performed using intraclass correlation coefficients (ICC), determination coefficients R2, and Bland-Altman plots. Diagnostic performance was determined using sensitivity, specificity, and positive and negative predictive values. The cutoff for steatosis was 5%.

RESULTS

Correlation between MRI and CT data was excellent for all perfusion phases with ICC calculated at 0.99 for each phase. Determination coefficients R2 were also good for all perfusion phases (about 0.95 for all phases). Performance of DL-CT in the diagnosis of hepatic steatosis was good with sensitivity between 89 and 91% and specificity ranging from 75 to 80%, depending on the perfusion phase. The positive predictive value was ranging from 78 to 93% and the negative predictive value from 82 to 86%.

CONCLUSION

Multi-material decomposition in DL-CT allows quantification of hepatic fat fraction with a good correlation to MRI data.

CLINICAL RELEVANCE STATEMENT

The use of DL-CT allows for detection of hepatic steatosis. This is especially interesting as an opportunistic finding CT performed for other reasons, as early detection can help prevent or slowdown the development of liver metabolic disease.

KEY POINTS

• Hepatic fat fractions provided by the dual-layer CT algorithm is strongly correlated with that measured on MRI. • Dual-layer CT is accurate to detect hepatic steatosis ≥ 5%. • Dual-layer CT allows opportunistic detection of steatosis, on CT scan performed for various indications.

Does dual-layer spectral detector CT provide added value in predicting spread through air spaces in lung adenocarcinoma? A preliminary study

OBJECTIVES

To examine the predictive value of dual-layer spectral detector CT (DLCT) for spread through air spaces (STAS) in clinical lung adenocarcinoma.

METHODS

A total of 225 lung adenocarcinoma cases were retrospectively reviewed for demographic, clinical, pathological, traditional CT, and spectral parameters. Multivariable logistic regression analysis was carried out based on three logistic models, including a model using traditional CT features (traditional model), a model using spectral parameters (spectral model), and an integrated model combining traditional CT and spectral parameters (integrated model). Receiver operating characteristic (ROC) curve analysis and decision curve analysis (DCA) were performed to assess these models.

RESULTS

Univariable analysis showed significant differences between the STAS and non-STAS groups in traditional CT features, including nodule density (p < 0.001), pleural indentation types (p = 0.006), air-bronchogram sign (p = 0.031), the presence of spiculation (p < 0.001), long-axis diameter of the entire nodule (LD) (p < 0.001), and consolidation/tumor ratio (CTR) (p < 0.001). Multivariable analysis revealed that LD > 20 mm (odds ratio [OR] = 2.271, p = 0.025) and CTR (OR = 24.208, p < 0.001) were independent predictors in the traditional model, while electronic density (ED) in the venous phase was an independent predictor in the spectral (OR = 1.062, p < 0.001) and integrated (OR = 1.055, p < 0.001) models. The area under the curve (AUC) for the integrated model (0.84) was the highest (spectral model, 0.83; traditional model, 0.80), and the difference between the integrated and traditional models was statistically significant (p = 0.015). DCA showed that the integrated model had superior clinical value versus the traditional model.

CONCLUSIONS

DLCT has added value for STAS prediction in lung adenocarcinoma.

CLINICAL RELEVANCE STATEMENT

Spectral CT has added value for spread through air spaces prediction in lung adenocarcinoma so may impact treatment planning in the future.

KEY POINTS

• Electronic density may be a potential spectral index for predicting spread through air spaces in lung adenocarcinoma. • A combination of spectral and traditional CT features enhances the performance of traditional CT for predicting spread through air spaces.

Detection of malignant lesions in cytologically indeterminate thyroid nodules using a dual-layer spectral detector CT-clinical nomogram

Purpose

To evaluate the capability of dual-layer detector spectral CT (DLCT) quantitative parameters in conjunction with clinical variables to detect malignant lesions in cytologically indeterminate thyroid nodules (TNs).

Materials and methods

Data from 107 patients with cytologically indeterminate TNs who underwent DLCT scans were retrospectively reviewed and randomly divided into training and validation sets (7:3 ratio). DLCT quantitative parameters (iodine concentration (IC), NICP (IC nodule/IC thyroid parenchyma), NICA (IC nodule/IC ipsilateral carotid artery), attenuation on the slope of spectral HU curve and effective atomic number), along with clinical variables, were compared between benign and malignant cohorts through univariate analysis. Multivariable logistic regression analysis was employed to identify independent predictors which were used to construct the clinical model, DLCT model, and combined model. A nomogram was formulated based on optimal performing model, and its performance was assessed using receiver operating characteristic curve, calibration curve, and decision curve analysis. The nomogram was subsequently tested in the validation set.

Results

Independent predictors associated with malignant TNs with indeterminate cytology included NICP in the arterial phase, Hashimoto's Thyroiditis (HT), and BRAF V600E (all p < 0.05). The DLCT-clinical nomogram, incorporating the aforementioned variables, exhibited superior performance than the clinical model or DLCT model in both training set (AUC: 0.875 vs 0.792 vs 0.824) and validation set (AUC: 0.874 vs 0.792 vs 0.779). The DLCT-clinical nomogram demonstrated satisfactory calibration and clinical utility in both training set and validation set.

Conclusion

The DLCT-clinical nomogram emerges as an effective tool to detect malignant lesions in cytologically indeterminate TNs.

The novel imaging methods in diagnosis and assessment of cerebrovascular diseases: an overview

Cerebrovascular diseases, including ischemic strokes, hemorrhagic strokes, and vascular malformations, are major causes of morbidity and mortality worldwide. The advancements in neuroimaging techniques have revolutionized the field of cerebrovascular disease diagnosis and assessment. This comprehensive review aims to provide a detailed analysis of the novel imaging methods used in the diagnosis and assessment of cerebrovascular diseases. We discuss the applications of various imaging modalities, such as computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET), and angiography, highlighting their strengths and limitations. Furthermore, we delve into the emerging imaging techniques, including perfusion imaging, diffusion tensor imaging (DTI), and molecular imaging, exploring their potential contributions to the field. Understanding these novel imaging methods is necessary for accurate diagnosis, effective treatment planning, and monitoring the progression of cerebrovascular diseases.

Utility of Dual-Energy Computed Tomography in Clinical Conundra

Advancing medical technology revolutionizes our ability to diagnose various disease processes. Conventional Single-Energy Computed Tomography (SECT) has multiple inherent limitations for providing definite diagnoses in certain clinical contexts. Dual-Energy Computed Tomography (DECT) has been in use since 2006 and has constantly evolved providing various applications to assist radiologists in reaching certain diagnoses SECT is rather unable to identify. DECT may also complement the role of SECT by supporting radiologists to confidently make diagnoses in certain clinically challenging scenarios. In this review article, we briefly describe the principles of X-ray attenuation. We detail principles for DECT and describe multiple systems associated with this technology. We describe various DECT techniques and algorithms including virtual monoenergetic imaging (VMI), virtual non-contrast (VNC) imaging, Iodine quantification techniques including Iodine overlay map (IOM), and two- and three-material decomposition algorithms that can be utilized to demonstrate a multitude of pathologies. Lastly, we provide our readers commentary on examples pertaining to the practical implementation of DECT's diverse techniques in the Gastrointestinal, Genitourinary, Biliary, Musculoskeletal, and Neuroradiology systems.

Low-dose versus conventional CT urography using dual-source CT with different time-current product values and the same tube voltage: image quality and diagnostic performance in various diagnoses

OBJECTIVES

To compare the image quality and diagnostic performance of low-dose CT urography to that of concurrently acquired conventional CT using dual-source CT.

METHODS

This retrospective study included 357 consecutive CT urograms performed by third-generation dual-source CT in a single institution between April 2020 and August 2021. Two-phase CT images (unenhanced phase, excretory phase with split bolus) were obtained with two different tube current-time products (280 mAs for the conventional-dose protocol and 70 mAs for the low-dose protocol) and the same tube voltage (90 kVp) for the two X-ray tubes. Iterative reconstruction was applied for both protocols. Two radiologists independently performed quantitative and qualitative image quality analysis and made diagnoses. The correlation between the noise level or the effective radiation dose and the patients' body weight was evaluated.

RESULTS

Significantly higher noise levels resulting in a significantly lower liver signal-to-noise ratio and contrast-to-noise ratio were noted in low-dose images compared to conventional images (P < .001). Qualitative analysis by both radiologists showed significantly lower image quality in low-dose CT than in conventional CT images (P < .001). Patient's body weight was positively correlated with noise and effective radiation dose (P < .001). Diagnostic performance for various diseases, including urolithiasis, inflammation, and mass, was not different between the two protocols.

CONCLUSIONS

Despite inferior image quality, low-dose CT urography with 70 mAs and 90 kVp and iterative reconstruction demonstrated diagnostic performance equivalent to that of conventional CT for identifying various diseases of the urinary tract.

ADVANCES IN KNOWLEDGE

Low-dose CT (25% radiation dose) with low tube current demonstrated diagnostic performance comparable to that of conventional CT for a variety of urinary tract diseases.

Vertebral Venous Congestion That May Mimic Vertebral Metastasis on Contrast-Enhanced Chest Computed Tomography in Chemoport Inserted Patients

OBJECTIVE

This study aimed to determine the prevalence of vertebral venous congestion (VVC) in patients with chemoport insertion, evaluate the imaging characteristics of nodular VVC, and identify the factors associated with VVC.

MATERIALS AND METHODS

This retrospective single-center study was based on follow-up contrast-enhanced chest computed tomography (CT) of 1412 adult patients who underwent chemoport insertion between January 2016 and December 2016. The prevalence of venous stenosis, reflux, and VVC were evaluated. The imaging features of nodular VVC, including specific locations within the vertebral body, were analyzed. To identify the factors associated with VVC, patients with VVC were compared with a subset of patients without VVC who had been followed up for > 3 years without developing VVC after chemoport insertion. Toward this, a multivariable logistic regression analysis was performed.

RESULTS

After excluding 333 patients, 1079 were analyzed (mean age ± standard deviation, 62.3 ± 11.6 years; 540 females). The prevalence of VVC was 5.8% (63/1079), with all patients (63/63) demonstrating vertebral venous reflux and 67% (42/63) with innominate vein stenosis. The median interval between chemoport insertion and VVC was 515 days (interquartile range, 204-881 days). The prevalence of nodular VVC was 1.5% (16/1079), with a mean size of 5.9 ± 3.1 mm and attenuation of 784 ± 162 HU. Nodular VVC tended to be located subcortically. Forty-four patients with VVC underwent CT examinations with contrast injections in both arms; the VVC disappeared in 70% (31/44) when the contrast was injected in the arm contralateral to the chemoport site. Bevacizumab use was independently associated with VVC (odds ratio, 3.45; P < 0.001).

CONCLUSION

The prevalence of VVC and nodular VVC was low in patients who underwent chemoport insertion. Nodular VVC was always accompanied by vertebral venous reflux and tended to be located subcortically. To avoid VVC, contrast injection in the arm contralateral to the chemoport site is preferred.

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.

Dual-Energy Computed Tomography to Photon Counting Computed Tomography: Emerging Technological Innovations

Computed tomography (CT) has seen remarkable developments in the past several decades, radically transforming the role of imaging in day-to-day clinical practice. Dual-energy CT (DECT), an exciting innovation introduced in the early part of this century, has widened the scope of CT, opening new opportunities due to its ability to provide superior tissue characterization. The introduction of photon-counting CT (PCCT) heralds a paradigm shift in CT scanner technology representing another significant milestone in CT innovation. PCCT offers several advantages over DECT, such as improved spectral resolution, enhanced tissue characterization, reduced image artifacts, and improved image quality.

Dual-Energy Computed Tomography Applications in Lung Cancer

This article examines the intrathoracic applications for dual-energy computed tomography (DECT), focusing on lung cancer. The topics covered include the image data sets, methods for iodine quantification, and clinical applications. The applications of DECT are to differentiate benign and malignant lung nodules, determining the grade of lung cancer and expression of ki-67 expression. Iodine quantification has role in assessment of treatment response in both the primary tumor and nodal metastases.

Optimal combination periprosthetic vasculature visualization and metal artifact reduction by spectral computed tomography using virtual monoenergetic images in total hip arthroplasty

OBJECTIVES

To investigate the optimal parameters of spectral CT for preferably visualizing the periprosthetic vasculature and metal artifact reduction (MAR) in total hip arthroplasty (THA).

METHODS

A total of 34 THA of 30 patients were retrospectively included. Image reconstructions included conventional image (CI), CI combined with MAR (CIMAR), and virtual monoenergetic images (VMI) combined with MAR (VMIMAR) at 50-120 keV. The attenuation and standard deviation of the vessel and artifact, and the width of artifact were measured. Qualitative scoring was evaluated including the vascular contour, the extent of artifact, and overall diagnostic evaluation.

RESULTS

The attenuation, noise of the vessel and artifact, and the width of artifact decreased as the energy level increased (p < 0.001). The downtrend was relatively flat at 80-120 keV, and the vascular attenuation dropped to 200 HU at 90 keV. The qualitative rating of vascular contour was significantly higher at CIMAR (3.47) and VMIMAR 60-80 keV (2.82-3.65) compared with CI (2.03) (p ≤ 0.029), and the highest score occurred at 70 and 80 keV (3.65 and 3.56). The score of the extent of artifact was higher at VMIMAR 80 keV than CIMAR (3.53 VS 3.12, p = 0.003). The score of the overall diagnostic evaluation was higher at VMIMAR 70 and 80 keV (3.32 and 3.53, respectively) than CIMAR (3.12) (p ≤ 0.035).

CONCLUSION

Eighty kiloelectron volts on VMIMAR, providing satisfactorily reduced metal artifacts and improved vascular visualization, can be an optimal recommended parameter of spectrum CT for the assessment of periprosthetic vasculature in THA patients.

CRITICAL RELEVANCE STATEMENT

The metal artifact is gradually reducing with increasing energy level; however, the vascular visualization is worsening. The vascular visualization is terrible above 100 keV, while the vessel is disturbed by artifacts below 70 keV. The best performance is found at 80 keV.

KEY POINTS

• VMIMAR can provide both reduced metal artifacts and improved vascular visualization. • Eighty kiloelectron volts on VMIMAR performs best in vascular visualization of total hip arthroplasty patients. • Energy spectrum CT is recommended for routine use in patients with total hip arthroplasty.

The value of dual-energy computed tomography (DECT) in the diagnosis of urinary calculi: a systematic review and meta-analysis of retrospective studies

Objective

Dual-energy computed tomography (DECT) imaging technology opens a new idea and method for analyzing stone composition, which can obtain several quantitative parameters reflecting tissue-related information and energy images different from traditional images. However, the application of DECT in diagnosing urinary calculi remains unknown. This study aims to evaluate the value of DECT in diagnosing urinary calculi by meta-analysis.

Methods

PubMed, EMBASE, Web of Science, and the Cochrane Library were searched to articles published from the establishment of the databases to April 18, 2023. We reviewed the articles on the diagnosis of urinary calculi detected by DECT, established standards, screened the articles, and extracted data. Two researchers carried out data extraction and the Cohen's unweighted kappa was estimated for inter-investigator reliability. The quality of the literature was evaluated by the diagnostic test accuracy quality evaluation tool (QUADAS-2). The heterogeneity and threshold effects were analyzed by Meta-Disc 1.4 software, and the combined sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic ratio were calculated. The combined receiver-operating characteristic (ROC) curve was drawn, and the value of DECT in the diagnosis of urinary calculi was evaluated by the area under the curve (AUC). The meta-analysis was registered at PROSPERO (CRD42023418204).

Results

One thousand and twenty-seven stones were detected in 1,223 samples from 10 diagnostic tests. The analyzed kappa alternated between 0.78-0.85 for the document's retrieval and detection procedure. The sensitivity of DECT in the diagnosis of urinary calculi was 0.94 (95% CI [0.92-0.96]). The positive likelihood ratio (PLR) of DECT in the diagnosis of urinary stones was 0.91 (95% CI [0.88-0.94]), and the negative likelihood ratio (NLR) was 0.08 (95% CI [0.05-0.11]). The specificity of DECT for detecting urinary calculi was 0.91 (95% CI [0.88-0.94]). The area under the curve of the summary receiver operator characteristic (SROC) was 0.9875. The sensitivity of dual-energy CT in the diagnosis of urinary calculi diameter <3 mm was 0.94 (95% CI [0.91-0.96]). The PLR of DECT in the diagnosis of urinary stones diameter <3 mm was 10.79 (95% CI [5.25 to 22.17]), and the NLR was 0.08 (95% CI [0.05-0.13]). The specificity of DECT for detecting urinary calculi <3 mm was 0.91 (95% CI [0.87-0.94]). The SROC was 0.9772.

Conclusion

The DECT has noble application value in detecting urinary calculi.

The evolution and current situation in the application of dual-energy computed tomography: a bibliometric study

Background

Dual-energy computed tomography (DECT) has received extensive attention in clinical practice; however, a quantitative assessment of published literature in this domain is presently lacking. This study thus aimed to characterize the application conditions, developmental trends, and research hot spots of DECT using bibliometric analysis.

Methods

All literature on DECT was retrieved from the Web of Science Core Collection (WoSCC) on January 22, 2023. The co-occurrence, cooperation network, and co-citation of countries, institutions, references, authors, journals, and keywords were analyzed using CiteSpace, VOSviewer, and R-bibliometrix software.

Results

In total, 4,720 original articles and reviews were included. The number of publications related to DECT has rapidly increased since 2006. The USA (n=1,662) and Mayo Clinic (n=178) were found to be the most productive country and institution, respectively. The most cited article was published by Johnson TRC et al., while the article published by McCollough CH et al. in 2015 had the most co-citations. Schoepf UJ ranked first with most articles among 16,838 authors. The journal with the most published articles was European Radiology, with 411 publications. The timeline analysis indicated that material decomposition was the most recent topic, followed by gout, radiomics, proton therapy, and bone marrow edema.

Conclusions

An increasing number of researchers are committed to researching DECT, with the USA making the most significant contributions in this area. Prior studies have primarily concentrated on cardiovascular diseases, and contemporary hot spots include expansion into to other fields, such as iodine quantification, deep learning, and bone marrow edema.

[Progress in Image-planned and Real-time Image-guided Lung Cancer Biopsy in the Detection of Biomarkers]

With the progress of targeted therapy and immunotherapy for lung cancer, the clinical demand for lung biopsy is increasing. An ideal biopsy specimen can be used not only for histopathological diagnosis, but also for biomarker detection. The ideal biopsy specimen should meet two requirements, including more than 60 mm2 of tumor tissue and containing more than 20% of tumor cells. In order to obtain ideal lung cancer biopsy specimens, advanced imaging techniques are needed to help. In this article, we reviewed the requirements for biopsy specimens based on biomarker detection, as well as the current status and research progress of using imaging techniques for preoperative planning and intraoperative real time guidance of lung cancer biopsy.
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Dual-Energy CT Arthrography: Advanced Muscolo-Skelatal Applications in Clinical Practice

This paper provides a comprehensive overview of the potential applications of dual-energy CT (DECT) in improving image quality and the diagnostic capabilities of CT arthrography (CTA) in clinical practice. The paper covers the use of virtual non-contrast (VNC) images, in which the injected contrast medium is subtracted from the articular cavity in order to better analyze 2D and 3D images of the bone. Moreover, virtual monoenergetic imaging (VMI) applications and their potential use for the reduction of metal artifacts and improving image contrast are reviewed. The role of virtual non-calcium (VNCa) in detecting bone marrow edema surrounding the imaged joint will be discussed. Furthermore, the role of iodine maps in enhancing the contrast between soft tissues, optimizing the visualization of contrast material, and distinguishing contrast material from calcifications is described. Finally, a case series including different joints is provided to underline the additional advantages of high-spatial-resolution dual-energy CT reconstructed images.

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.

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/ .

Comparison between Dual-Energy CT and Quantitative Susceptibility Mapping in Assessing Brain Iron Deposition in Parkinson Disease

BACKGROUND AND PURPOSE

Both dual-energy CT and quantitative susceptibility mapping can evaluate iron depositions in the brain. The purpose of this study was to compare these 2 techniques in evaluating brain iron depositions in Parkinson disease.

MATERIALS AND METHODS

Forty-one patients with Parkinson disease (Parkinson disease group) and 31 age- and sex-matched healthy controls (healthy control group) were included. All participants underwent brain dual-energy CT and quantitative susceptibility mapping. ROIs were set bilaterally in the globus pallidus, substantia nigra, red nucleus, caudate nucleus, and putamen. CT values and magnetic susceptibility values were obtained in each ROI. Differences in CT values and magnetic susceptibility values between the Parkinson disease and healthy control groups were compared, followed by analysis of receiver operating characteristic curves. Correlations between CT values and magnetic susceptibility values were then evaluated.

RESULTS

The CT values of the bilateral globus pallidus, substantia nigra, and red nucleus were higher in the Parkinson disease group (P < .05). The magnetic susceptibility values of the bilateral globus pallidus and substantia nigra were higher in the Parkinson disease group (P < .05). The CT value of the right globus pallidus in linear fusion images had the highest diagnostic performance (0.912). Magnetic susceptibility values of the bilateral globus pallidus in the Parkinson disease group were positively correlated with CT values at the level of 80 kV(peak), linear fusion images, and SN150 kV(p) (r = 0.466∼0.617; all, P < .05).

CONCLUSIONS

Both dual-energy CT and quantitative susceptibility mapping could assess excessive brain iron depositions in Parkinson disease, and we found a positive correlation between CT values and magnetic susceptibility values in the bilateral globus pallidus.

Pros and Cons of Dual-Energy CT Systems: "One Does Not Fit All"

Dual-energy computed tomography (DECT) uses different energy spectrum x-ray beams for differentiating materials with similar attenuation at a certain energy. Compared with single-energy CT, it provides images with better diagnostic performance and a potential reduction of contrast agent and radiation doses. There are different commercially available DECT technologies, with machines that may display two x-ray sources and two detectors, a single source capable of fast switching between two energy levels, a specialized detector capable of acquiring high- and low-energy data sets, and a filter splitting the beam into high- and low-energy beams at the output. Sequential acquisition at different tube voltages is an alternative approach. This narrative review describes the DECT technique using a Q&A format and visual representations. Physical concepts, parameters influencing image quality, postprocessing methods, applicability in daily routine workflow, and radiation considerations are discussed. Differences between scanners are described, regarding design, image quality variabilities, and their advantages and limitations. Additionally, current clinical applications are listed, and future perspectives for spectral CT imaging are addressed. Acknowledging the strengths and weaknesses of different DECT scanners is important, as these could be adapted to each patient, clinical scenario, and financial capability. This technology is undoubtedly valuable and will certainly keep improving.

Comparative study of true and virtual non-contrast imaging generated from dual-layer spectral CT in patients with upper aerodigestive tract cancer

Purpose

Dual-layer spectral computed tomography (DLSCT) is a novel CT platform of dual-energy CT. Virtual non-contrast (VNC) imaging theoretically resembles true non-contrast (TNC) imaging by subtracting iodine attenuation from post-contrast data. We aimed to compare qualitative and quantitative datasets between TNC and VNC in patients with upper aerodigestive tract cancer (UATC) and to evaluate the potential radiation dose reduction obtained by omitting the TNC phase.

Material and methods

The study included 61 patients with UATC who underwent DLSCT. The CT protocol included TNC and post-contrast phases. The VNC images were reconstructed from the post-contrast phase. The differences of mean CT attenuation values, imaging noise, and image quality for TNC and VNC images were compared. The effective radiation doses of a biphasic TNC and post-contrast CT protocol were compared with a single-phase protocol (post-contrast CT with VNC reconstruction).

Results

There were a total of 732 ROIs from TNC and VNC. There was no statistical difference in the mean CT attenuation values between TNC and VNC images for all tissue types (p = 0.09-0.44), except for the buccal fat pad. Overall, 85.3% of cases revealed a difference of less than 10 HU. There was no significant difference in mean imaging noise (p = 0.5455) and image quality (p = 0.3214) between 2 acquisitions. All VNC images had acceptable quality for diagnostic purposes. The potential dose reduction by omitting the TNC was 49.5 ± 3.5%.

Conclusion

VNC could replace TNC images in patients with UATC, with good image quality and the advantage of radiation dose reduction.

The value of dual-energy spectral CT in differentiating solitary pulmonary tuberculosis and solitary lung adenocarcinoma

BACKGROUND

To explore the value of dual-energy spectral CT in distinguishing solitary pulmonary tuberculosis (SP-TB) from solitary lung adenocarcinoma (S-LUAD).

METHODS

A total of 246 patients confirmed SP-TB (n = 86) or S-LUAD (n = 160) were retrospectively included. Spectral CT parameters include CT40keV value, CT70keV value, iodine concentration (IC), water concentration (WC), effective atomic number (Zeff), and spectral curve slope (λ70keV). Data were measured during the arterial phase (AP) and venous phase (VP). Chi-square test was used to compare categorical variables, Wilcoxon rank-sum test was used to compare continuous variables, and a two-sample t-test was used to compare spectral CT parameters. ROC curves were used to calculate diagnostic efficiency.

RESULTS

There were significant differences in spectral CT quantitative parameters (including CT40keV value [all P< 0.001] , CT70keV value [all P< 0.001], λ70keV [P< 0.001, and P = 0.027], Zeff [P =0.015, and P = 0.001], and IC [P =0.002, and P = 0.028]) between the two groups during the AP and VP. However, WC (P = 0.930, and P = 0.823) was not statistically different between the two groups. The ROC curve analysis showed that the AUC in the AP and VP was 90.9% (95% CI, 0.873-0.945) and 83.4% (95% CI, 0.780-0.887), respectively. The highest diagnostic performance (AUC, 97.6%; 95% CI, 0.961-0.991) was achieved when all spectral CT parameters were combined with clinical variables.

CONCLUSION

Dual-energy spectral CT has a significant value in distinguishing SP-TB from S-LUAD.

Improving the Accuracy of the Effective Atomic Number (EAN) and Relative Electron Density (RED) with Stoichiometric Calibration on PCD-CT Images

The photon counting detector (PCD) in computed tomography (CT) can count the number of incoming photons in order to obtain energy information for photons corresponding to user-defined thresholds. Research on the extraction of effective atomic number (EAN) and relative electron density (RED) using dual-energy CT (DECT) is currently underway. This study proposes a method for improving EAN and RED accuracy of tissue-equivalent materials by using PCD-CT-based stoichiometric calibration. After obtaining DECT images in energy bin (EB) and full spectrum (FS) modes for eight tissue-equivalent materials, the EAN was calculated with stoichiometric calibration. Using the EAN image, the RED image was acquired to evaluate the accuracy. The errors of both EAN and RED obtained with EB were within 4%. In particular, the accuracy of RED was higher than that of the FS method. Study results indicate that PCD-CT contributes to improving EAN and RED accuracy. Further studies will be aimed at reducing ring artifacts by pixel-correcting PCD images and improving stopping power ratio (SPR) measurements for dose calculation in particle therapy.

Radiation Dose Reduction Opportunities in Vascular Imaging

Computed tomography angiography (CTA) has been the gold standard imaging modality for vascular imaging due to a variety of factors, including the widespread availability of computed tomography (CT) scanners, the ease and speed of image acquisition, and the high sensitivity of CTA for vascular pathology. However, the radiation dose experienced by the patient during imaging has long been a concern of this image acquisition method. Advancements in CT image acquisition techniques in combination with advancements in non-ionizing radiation imaging techniques including magnetic resonance angiography (MRA) and contrast-enhanced ultrasound (CEUS) present growing opportunities to reduce total radiation dose to patients. This review provides an overview of advancements in imaging technology and acquisition techniques that are helping to minimize radiation dose associated with vascular imaging.

Quantitative parameters of enhanced dual-energy computed tomography for differentiating lung cancers from benign lesions in solid pulmonary nodules

Objectives

This study aimed to investigate the ability of quantitative parameters of dual-energy computed tomography (DECT) and nodule size for differentiation between lung cancers and benign lesions in solid pulmonary nodules.

Materials and Methods

A total of 151 pathologically confirmed solid pulmonary nodules including 78 lung cancers and 73 benign lesions from 147 patients were consecutively and retrospectively enrolled who underwent dual-phase contrast-enhanced DECT. The following features were analyzed: diameter, volume, Lung CT Screening Reporting and Data System (Lung-RADS) categorization, and DECT-derived quantitative parameters including effective atomic number (Zeff), iodine concentration (IC), and normalized iodine concentration (NIC) in arterial and venous phases. Multivariable logistic regression analysis was used to build a combined model. The diagnostic performance was assessed by area under curve (AUC) of receiver operating characteristic curve, sensitivity, and specificity.

Results

The independent factors for differentiating lung cancers from benign solid pulmonary nodules included diameter, Lung-RADS categorization of diameter, volume, Zeff in arterial phase (Zeff_A), IC in arterial phase (IC_A), NIC in arterial phase (NIC_A), Zeff in venous phase (Zeff_V), IC in venous phase (IC_V), and NIC in venous phase (NIC_V) (all P < 0.05). The IC_V, NIC_V, and combined model consisting of diameter and NIC_V showed good diagnostic performance with AUCs of 0.891, 0.888, and 0.893, which were superior to the diameter, Lung-RADS categorization of diameter, volume, Zeff_A, and Zeff_V (all P < 0.001). The sensitivities of IC_V, NIC_V, and combined model were higher than those of IC_A and NIC_A (all P < 0.001). The combined model did not increase the AUCs compared with IC_V (P = 0.869) or NIC_V (P = 0.633).

Conclusion

The DECT-derived IC_V and NIC_V may be useful in differentiating lung cancers from benign lesions in solid pulmonary nodules.

Spectral computed tomography with inorganic nanomaterials: State-of-the-art

Recently, spectral computed tomography (CT) technology has received great interest in the field of radiology. Spectral CT imaging utilizes the distinct, energy-dependent X-ray absorption properties of substances in order to provide additional imaging information. Dual-energy CT and multi-energy CT (Spectral CT) are capable of constructing monochromatic energy images, material separation images, energy spectrum curves, constructing effective atomic number maps, and more. However, poor contrast, due to neighboring X-ray attenuation of organs and tissues, is still a challenge to spectral CT. Hence, contrast agents (CAs) are applied for better differentiation of a given region of interest (ROI). Currently, many different kinds of inorganic nanoparticulate CAs for spectral CT have been developed due to the limitations of clinical iodine (I)-based contrast media, leading to the conclusion that inorganic nanomedicine applied to spectral CT will be a powerful collaboration both in basic research and in clinics. In this review, the underlying principles and types of spectral CT techniques are discussed, and some evolving clinical diagnosis applications of spectral CT techniques are introduced. In particular, recent developments in inorganic CAs used for spectral CT are summarized. Finally, the challenges and future developments of inorganic nanomedicine in spectral CT are briefly discussed.

Lumbar Spine Posttherapeutic Imaging

Management of patients after lumbar spine surgery or interventional radiology can be complex, and postoperative imaging patterns are often poorly understood by nonspecialized radiologists. This article focuses on postoperative imaging features of the lumbar spine in five clinical settings (with corresponding interventions): vertebral osteoporotic fractures (percutaneous vertebroplasty and vertebral augmentation), lumbar disk herniation (surgical diskectomy and percutaneous interventional radiology), lumbar spinal stenosis (surgical decompression), lumbar spondylolisthesis (surgical decompression and fusion), and degenerative scoliosis (techniques of osteotomies).For each intervention, we discuss imaging indications, depending if the patient is asymptomatic or if there are suspected complications, describe normal and pathologic imaging features, and present key points.

Dual energy CT angiography for lower extremity trauma: comparison with conventional CT

PURPOSE

To determine if rapid switching dual-energy CT (rsDECT) provides improvements in vascular attenuation, subjective diagnostic quality, and detection of vascular injuries compared to conventional CT in trauma patients undergoing lower extremity CT angiography.

MATERIALS AND METHODS

The IRB approved this HIPAA-compliant retrospective study. Informed consent was waived. Thirty-nine patients with acute lower extremity trauma including gunshot wounds (19 patients), falls (6 patients), motor vehicle accidents (5 patients), stab wounds (4 patients), pedestrian struck (2 patients), and unspecified trauma (3 patients) who underwent IV contrast-enhanced rsDECT angiography of the lower extremities on a rapid-kilovoltage-switching dual-energy CT scanner (Revolution CT, GE Healthcare) from 6/4/2019 to 1/14/2021 were studied. 7 patients were initially positive for vascular injury on conventional CT, while 32 patients were negative. Blended CT reconstructions simulating conventional 120 kVp single-energy CT, and rsDECT reconstructions (50 keV monoenergetic and iodine density maps) were reviewed. Region of interest contrast density measurements were recorded on conventional and 50 keV reconstructions at multiple levels from the distal aorta to the ankles and compared using Wilcoxon signed-rank tests. Vascular contrast density of 150 HU was used as a minimum cutoff for diagnostically adequate opacification. Images were interpreted by consensus for subjective image quality and presence of injury on both conventional and DECT reconstructions by two fellowship-trained abdominal radiologists blinded to clinical data, and compared using the paired McNemar test.

RESULTS

Density measurement differences between conventional and rsDECT at every level of the bilateral lower extremities were statistically significant, with the average difference ranging from 304 Hounsfield units (HU) in the distal aorta to 121 HU at the ankles (p < 0.0001). Using a cutoff of 150 HU, 9.5% (93/976) and 3.1% of vascular segments (30/976) were considered non-diagnostic in the conventional and rsDECT groups, respectively, a reduction of 67.7% (p < 0.0001). Subjective image quality between conventional and rsDECT was not statistically significant, but there were 7 vascular segments out of a total of 976 segments across 3 different patients out of a total of 39 patients in which diagnostic quality was upgraded from non-diagnostic on conventional CT to diagnostic on rsDECT, all of which showed suboptimal bolus quality on conventional CT (unmeasurable in 4/7 and ranging from 56-146 HU in the remaining 3). Similarly, rate of injury detection was identical between conventional CT (15/39 patients) and DECT (15/39 patients).

CONCLUSIONS

Vascular contrast density is statistically significantly higher with rsDECT compared to conventional CT, and subjective image quality was upgraded from non-diagnostic on conventional CT to diagnostic on rsDECT in 7 vascular segments across 3 patients.

CLINICAL RELEVANCE

rsDECT provides greater vascular contrast density than conventional CT, with potential to salvage suboptimal examinations caused by poor contrast opacification.