Spectral CT imaging: Technical principles of dual-energy CT and multi-energy photon-counting CT

Ultra-high-resolution 40 keV virtual monoenergetic imaging using spectral photon-counting CT in high-risk patients for coronary stenoses

OBJECTIVES

To assess the image quality of ultra-high-resolution (UHR) virtual monoenergetic images (VMIs) at 40 keV compared to 70 keV, using spectral photon-counting CT (SPCCT) and dual-layer dual-energy CT (DECT) for coronary computed tomography angiography (CCTA).

METHODS AND MATERIALS

In this prospective IRB-approved study, 26 high-risk patients were included. CCTA was performed both with an SPCCT in UHR mode and with one of two DECT scanners (iQOn or CT7500) within 3 days. 40 keV and 70 keV VMIs were reconstructed for both modalities. Stenoses, blooming artefacts, and image quality were compared between all four reconstructions.

RESULTS

Twenty-six patients (4 women [15%]) and 28 coronary stenoses (mean stenosis of 56% ± 16%) were included. 40 keV SPCCT gave an overall higher quality score (5 [5, 5]) than 70 keV SPCCT (5 [4, 5], 40 keV DECT (4 [3, 4]) and 70 keV SPCCT (4 [4, 5]), p < 0.001). Less variability in stenosis measurement was found with SPCCT between 40 keV and 70 keV (bias: -1% ± 3%, LoA: 6%) compared with DECT (-6% ± 8%, LoA 16%). 40 keV SPCCT vs 40 keV DECT showed a -3% ± 6% bias, whereas 40 keV SPCCT vs 70 keV DECT showed a -8% ± 6% bias. From 70 keV to 40 keV, blooming artefacts did not increase with SPCCT (mean +2% ± 5%, p = 0.136) whereas they increased with DECT (mean +7% ± 6%, p = 0.005).

CONCLUSION

UHR 40 keV SPCCT VMIs outperformed 40 keV and 70 keV DECT VMIs for assessing coronary artery stenoses, with no impairment compared to 70 keV SPCCT VMIs.

KEY POINTS

Question Use of low virtual mono-energetic images at 40 keV using spectral dual-energy and photon-counting CT systems is not yet established for diagnosing coronary artery stenosis. Findings UHR 40 keV SPCCT enhances diagnostic accuracy in coronary artery assessment. Clinical relevance By combining spectral sensitivity with lower virtual mono-energetic imaging and ultra-high spatial resolution, SPCCT enhances coronary artery assessment, potentially leading to more accurate diagnoses and better patient outcomes in cardiovascular imaging.

Performance of novel multiparametric second-generation dual-layer spectral detector CT in gouty arthritis

OBJECTIVES

This study aimed to compare the performance of different dual-energy computed tomography (DECT) technologies in detecting monosodium urate (MSU) crystals and evaluate the potential clinical value of novel second-generation dual-layer spectral detector CT (dlDECT) in gouty arthritis.

METHODS

Using data collected from a tertiary hospital, we examined the diagnostic accuracy of different DECT technologies for the diagnosis of MSU. We used two standards: (1) demonstration of MSU crystals in synovial fluid (gold) and (2) 2015 ACR/EULAR gout classification criteria (silver). Furthermore, six novel spectral parameters derived from dlDECT were quantitatively calculated and analyzed for MSU diagnostic efficiency.

RESULTS

Of the 243 patients with 387 joints, 68 (27.98%) had synovial fluid analysis. Compared with the gold standard, MSU diagnostic accuracy statistics for dlDECT, dual-source DECT (dsDECT) and rapid kilovolt peak switching DECT (rsDECT) were as follows: area under the curve (AUC): 0.85, 0.80 and 0.75, respectively. Findings were replicated compared with the silver standard. Multiparametric analysis in dlDECT demonstrated the highest MSU detection rate (92.86%), significantly higher than rsDECT (42.08%) and dsDECT (85.80%). Among novel parameters in dlDECT, Calcium-suppressed index 25 (CaSupp-I 25) exhibited the best performance in distinguishing materials (MSU, muscle, and bone), with an AUC of 0.992. The differentiation was also aided by histograms, scatter plots, and attenuation curves.

CONCLUSION

The novel dlDECT is likely not inferior to other DECT technologies in MSU detection, especially its spectral parameter CaSupp-I 25. Multiparameter analysis showed the potential value for detecting MSU crystals in gouty arthritis, providing valuable clinical insights for gout diagnosis.

KEY POINTS

Question The performance of different DECT technologies in detecting monosodium urate (MSU), and the value of dual-layer spectral detector CT (dlDECT) in gouty arthritis remains unclear. Findings The dlDECT was likely not inferior to other DECT technologies in MSU detection, and its multiparametric analysis provided valuable information for MSU diagnosis. Clinical relevance Novel dlDECT may improve the accurate detection of MSU crystals in gouty arthritis compared to other DECT technologies, providing valuable clinical insights and potentially improving patient outcomes for more precise gout diagnosis.

Imaging in France: 2024 Update

Radiology in France has made major advances in recent years through innovations in research and clinical practice. French institutions have developed innovative imaging techniques and artificial intelligence applications in the field of diagnostic imaging and interventional radiology. These include, but are not limited to, a more precise diagnosis of cancer and other diseases, research in dual-energy and photon-counting computed tomography, new applications of artificial intelligence, and advanced treatments in the field of interventional radiology. This article aims to explore the major research initiatives and technological advances that are shaping the landscape of radiology in France. By highlighting key contributions in diagnostic imaging, artificial intelligence, and interventional radiology, we provide a comprehensive overview of how these innovations are improving patient outcomes, enhancing diagnostic accuracy, and expanding the possibilities for minimally invasive therapies. As the field continues to evolve, France's position at the forefront of radiological research ensures that these innovations will play a central role in addressing current healthcare challenges and improving patient care on a global scale.

Cardiovascular imaging techniques for electrophysiologists

Rapid technological advancements in noninvasive and invasive imaging including echocardiography, computed tomography, magnetic resonance imaging and positron emission tomography have allowed for improved anatomical visualization and precise measurement of cardiac structure and function. These imaging modalities allow for evaluation of how cardiac substrate changes, such as myocardial wall thickness, fibrosis, scarring and chamber enlargement and/or dilation, have an important role in arrhythmia initiation and perpetuation. Here, we review the various imaging techniques and modalities used by clinical and basic electrophysiologists to study cardiac arrhythmia mechanisms, periprocedural planning, risk stratification and precise delivery of ablation therapy. We also review the use of artificial intelligence and machine learning to improve identification of areas for triggered activity and isthmuses in reentrant arrhythmias, which may be favorable ablation targets.

Current and future role of CT and advanced CT applications in inflammatory arthritis in the clinic and trials

Computed tomography (CT) has traditionally been underutilized in the imaging of inflammatory arthritis due to its limitations in assessing soft tissue inflammation and concerns over radiation exposure. However, recent technological advancements have positioned CT as a more viable imaging modality for arthritis, offering high specificity and sensitivity in detecting structural bone changes. However, advances in ultra-low-dose CT protocols and AI-driven image reconstruction have significantly reduced radiation exposure while maintaining diagnostic quality. Dynamic CT and spectral CT techniques, including dual-energy CT (DECT), have broadened CT's application in assessing dynamic joint instabilities and visualizing inflammatory changes through material-specific imaging. Techniques such as CT subtraction imaging and iodine mapping have enhanced the detection of active soft-tissue inflammation, virtual non-calcium reconstructions, and the detection of bone marrow edema. Possible CT applications span various forms of arthritis, including gout, calcium pyrophosphate deposition disease (CPPD), psoriatic arthritis, and axial spondyloarthritis. Beyond its diagnostic capabilities, CT's ability to provide detailed structural assessment positions is a valuable tool for monitoring disease progression and therapeutic response, particularly in clinical trials. While MRI remains superior for soft tissue evaluation, CT's specificity for bone-related changes and its potential for integration into routine arthritis management warrant further exploration and research. This review explores the current and emerging roles of CT in arthritis diagnostics, with a focus on novel applications and future potential.

Penumbra-effect induced spectral mixing in x-ray computed tomography: a multi-ray spectrum estimation model and subsampled weighting algorithm

Objective.With the development of spectral CT, various spectral imaging technologies have been proposed. Among these, filter-based spectral imaging methods have been greatly advanced in recent years, such as split filters used in clinical diagnose, spectral modulators studied for spectral imaging and scatter correction. However, due to the finite size of the focal spot of x-ray source, spectral filters cause spectral mixing in the penumbra region. Traditional spectrum estimation methods fail to account for it, resulting in reduced spectral accuracy. To address this challenge, we develop a multi-ray spectrum estimation model and propose an Adaptive Subsampled WeIghting of Filter Thickness (A-SWIFT) method.Approach.First, we estimate the unfiltered spectrum using traditional methods. Next, we model the final spectra as a weighted summation of spectra attenuated by multiple filters. The weights and equivalent lengths are obtained by x-ray transmission measurements taken with altered spectra using different kVp or flat filters. Finally, the spectra are approximated by using the multi-ray model. To mimic the penumbra effect, we used a spectral modulator (0.2 mm Mo, 0.6 mm Mo), a split filter (0.07 mm Au, 0.7 mm Sn), and the abdominal images of an XCAT phantom in simulations; in experiments, we used spectral modulators made by molybdenum or copper along with a pure water phantom, a Gammex multi-energy CT phantom and a Kyoto chest phantom for validation.Main results.Simulation results show that the mean energy bias in the penumbra region decreased from 7.43 keV using the previous Spectral Compensation for Modulator (SCFM) method to 0.72 keV using the A-SWIFT method for the split filter, and from 1.98 keV to 0.61 keV for the spectral modulator. In physics experiments, for the pure water phantom with a molybdenum modulator, the average error of the mean values (ERMSE) in selected regions of interests decreased from 77 to 7 Hounsfield units (HU) using the A-SWIFT method compared with SCFM method; for the Gammex phantom,ERMSEin iodine images was 0.2 mg ml-1using A-SWIFT method, and 1.5 mg ml-1using SCFM method; for the chest phantom with an added 5 mg ml-1iodine cylinder, the estimated material density of the iodine inserts was 5.0 mg ml-1using A-SWIFT method, and 5.9 mg ml-1using SCFM method.Significance.Based on a multi-ray spectrum estimation model, the A-SWIFT method provides an accurate and robust spectrum estimation in the penumbra region, contributing to enhanced spectral imaging performance of CT systems utilizing spectral filters.

Spectral CT findings of bladder urothelial carcinoma with gastric metastasis: a case report

BACKGROUND

Bladder cancer is one of the most common cancers worldwide, and urothelial carcinoma is the most common form of bladder cancer. Gastric metastasis of urothelial carcinoma of the bladder is a rare condition. Cystoscopy plays an important role in the diagnosis of bladder cancer; however, it is an invasive procedure that may affect the patient's prognosis and does not allow for the observation of cancer infiltration and metastasis. Therefore, non-invasive imaging is increasingly becoming the most appropriate method for the diagnosis and follow-up of urothelial carcinoma.

CASE PRESENTATION

A 51-year-old female patient presented with pain in the lower abdomen and lower back for more than 2 months. This was a case of bladder urothelial carcinoma with gastric metastases, confirmed by pathology using dual-layer detector computed tomography (CT) spectral multiparametric imaging. The stage of the cancer was cT3N+M1b IVB, and the dimensions were 11.6 mm×42.2 mm×44.4 mm. The energy spectrum multiparameter image shows good consistency in the quantitative measurement of multiple nodules on the gastric wall and bladder wall masses (single energy 40 keV-CT value, iodine concentration, effective atomic number), and the spectral curve runs basically consistent. After 5 months of chemotherapy, the slope values of the spectral curve were 3.74 and 3.09 in the initial and follow-up spectral CT scans, respectively, reflecting the improvement of bladder wall lesions after treatment.

CONCLUSIONS

The present case is a very rare case of bladder urothelial carcinoma with gastric metastasis. We applied multi-parameter quantitative indicators of spectral CT to more accurately show the homology characteristics of gastric metastasis and bladder cancer, and also reflected the different sources of cystic lesions in the left adnexal region from bladder cancer and gastric metastasis. Spectral CT has a promising application prospect in detecting the homology of different lesions and diagnosing urothelial gastric metastasis carcinoma.

Updating the American Association of Physicists in Medicine (AAPM) Diagnostic Radiology Resident Physics Curriculum: Strategies, Content, and Dissemination

RATIONALE AND OBJECTIVES

The Diagnostic Radiology Resident Physics Curriculum (DRRPC), initiated in 2007 by the American Association of Physicists in Medicine (AAPM) and last updated in 2018, is an essential educational resource for those teaching physics to radiology residents. Regular updates are crucial to ensure the curriculum aligns with evolving technologies and clinical practices, maintaining its relevance and effectiveness in educating the next generation of radiologists. The paper aims to describe the update strategies of the DRRPC, focusing on the current iteration, its structure, and the newest updates.

MATERIALS AND METHODS

The update process, led by the Diagnostic Radiology Resident Physics Curriculum Working Group, commenced with a comprehensive survey targeting AAPM members who contribute to radiology physics teaching. The survey was conducted to assess the curriculum's current applicability and gather feedback for improvements. Subsequent updates were based on extensive stakeholder consultations and detailed analysis of survey data.

RESULTS

The revision process has led to significant enhancements in the curriculum, emphasizing practical clinical applications and the integration of cutting-edge technology. New modules on advanced image processing, artificial intelligence, informatics, and radiopharmaceutical therapy were developed, responding to the evolving needs of radiological education and practice.

CONCLUSION

The updated DRRPC supports educators in providing a dynamic and relevant training experience.

Assessment of small bowel ischemia in mechanical small bowel obstruction: Diagnostic value of bowel wall iodine concentration using dual-energy CT

PURPOSE

The purpose of this study was to determine whether dual-energy computed tomography (DECT), specifically by measuring bowel wall iodine concentration (BWIC), is superior to monoenergetic reconstructions (MR) for the diagnosis and staging of small bowel ischemia in patients with mechanical small bowel obstruction (SBO).

MATERIALS AND METHODS

From November 2021 to December 2023, all patients with mechanical SBO who underwent contrast-enhanced DECT of the abdomen and pelvis were evaluated for inclusion. Demographic, clinical and biochemical data were collected. Two abdominal radiologists, blinded to all patient information, reviewed all DECT examinations. Conventional CT features (including a closed loop mechanism, mesenteric haziness, decreased bowel wall enhancement (DBE), and increased unenhanced attenuation of the bowel wall) were first reviewed on 70-keV-MR and 40-keV-MR, followed by BWIC measurements in five regions of interest in the walls of both normal and abnormal small bowel loops. The diagnostic performance of a simple CT score, which included a closed loop mechanism, mesenteric haziness and DBE, was compared to that of BWIC measurements made on dilated and/or abnormal small bowel segments for the diagnosis of small bowel ischemia. The diagnostic capabilities were compared using areas under the receiver operating characteristic curves (AUCs).

RESULTS

A total of 142 patients were included (80 men, 62 women; mean age, 67 ± 17 [standard deviation (SD)] years). Fifty-six patients underwent surgery; 22 of them had confirmed small bowel ischemia, including 12 patients with small bowel necrosis requiring surgical resection. Significant differences in mean BWIC were found between patients without small bowel ischemia (1.73 ± 0.44 [SD] mg/mL), those with small bowel ischemia without necrosis (0.79 ± 0.37 [SD] mg/mL), and those with small bowel ischemia and necrosis (0.48 ± 0.32 [SD] mg/mL) (P < 0.001). The overall AUC of the BWIC measurement for diagnosing small bowel ischemia was 0.98 (95 % confidence interval [CI]: 0.97-1.00), similar to the AUC of the simple CT score (0.97; 95 % CI: 0.92-1.00). However, using a cut off-value of 1.16 mgI/mL, BWIC outperformed subjective assessment of DBE at 70-keV-MR and 40-keV-MR (Youden index, 0.90 vs. 0.54 and vs. 0.71, respectively) (P < 0.001 for both).

CONCLUSION

BWIC measurement outperforms subjective assessment of DBE for the diagnosis of small bowel ischemia in patients with SBO and can allow stratification of ischemia. However, BWIC does not outperfomr a global comprehensive analysis of conventional CT images.

A Generalizable Framework for Kidney Stone Composition Characterization Using Dual-Energy CT

RATIONALE AND OBJECTIVES

Classification of non-uric acid (NUA) renal stones in dual-energy CT (DECT) is difficult due to their similar CT number ratios (CTRs) and because the CTRs change with patient size and acquisition protocol. In this work, we developed a generalizable framework to estimate correct CTR threshold for different stone types, protocols, and patient sizes and validated the results on two DECT scanners.

MATERIALS AND METHODS

Our framework assumes generic x-ray spectra, estimates the added filtration to match half-value-layer (HVL) measurements, and predicts the CTR of each stone type from the chemical composition and patient size. The framework was validated for four calcium or iodine inserts in two solid water phantom sizes on two DECT scanners, and on 45 human urinary stones of five types (uric acid, cystine, calcium oxalate monohydrate, brushite, and hydroxyapatite) in three different water phantom sizes on a dual-source DECT. All scans were performed at high dose, using routine acquisition parameters. The predicted CTR was compared with the measured CTR.

RESULTS

The predicted CTRs for different stone types were consistent with experimentally measured values, with average absolute errors of 2.8% (range 1.3-4.3%), 1.8% (range 0.7-4.4%), and 1.8% (range 0.8-2.4%) for the 30, 40, and 50 cm phantom sizes. The predicted CTR errors of the four inserts were within 6.4%.

CONCLUSION

The developed framework uses easily obtained HVL measurements to predict renal stone CTRs of different compositions for varied patient sizes. With further refinement, it may help classify NUA subtypes in clinical scans.

Photon-counting versus energy-integrating CT of abdomen-pelvis: a phantom study on the potential for reducing iodine contrast media

BACKGROUND

To assess the potential of virtual monoenergetic images (VMIs) on a photon-counting computed tomography (PCCT) for reducing the amount of injected iodine contrast media compared to an energy-integrating CT (EICT).

METHODS

A multienergy phantom was scanned with a PCCT and EICT at 11 mGy with abdomen-pelvis examination parameters. VMIs were generated at 40 keV, 50 keV, 60 keV, and 70 keV. For all VMIs, the contrast-to-noise ratio (CNR) of iodine inserts with concentrations of 1 mg/mL, 2 mg/mL, 5 mg/mL, 10 mg/mL, and 15 mg/mL was calculated by dividing the signal difference between HU in iodine inserts versus solid water by the noise value assessed on solid water. The potential reduction in iodine media was calculated by the rate of reduction in iodine concentration with PCCT while maintaining the same CNR obtained with EICT for the reference concentration.

RESULTS

Significantly higher CNR values were found with PCCT at all VMI energy levels for iodine concentrations above 1 mg/mL. The highest reduction was observed at 40 keV, with a value of 48.9 ± 1.6% (mean ± standard deviation). It decreased as the energy level increased, by 38.5 ± 0.5%, and 30.8 ± 0.8% for 50 and 60 keV, respectively. For 70 keV, the potential reduction of 24.4 ± 1.1% was found for iodine concentrations above 1 mg/mL. This reduction reached 57 ± 2.3% at 40 keV with PCCT compared to 60 keV with EICT.

CONCLUSION

For abdomen-pelvis protocols, the use of VMIs with PCCT significantly improved the CNR of iodine, offering the potential to reduce the required contrast medium.

RELEVANCE STATEMENT

The use of VMIs with PCCT may reduce the quantity of iodine contrast medium to be injected compared with EICT, limiting costs, the risk of adverse effects, and the amount of contrast agent released into the wastewater.

KEY POINTS

PCCT improves the image quality of VMIs. PCCT offers the potential for reducing the amount of injected contrast medium. PCCT potential for reducing the injected contrast medium depends on energy level.

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.

Detectability of Iodine in Mediastinal Lesions on Photon Counting CT: A Phantom Study

Background/Objectives: To evaluate the detectability of iodine in mediastinal lesions with photon counting CT (PCCT) compared to conventional CT (CCT) in a phantom study. Methods: Mediastinal lesions were simulated by five cylindrical inserts with diameters from 1 to 12 mm within a 10 cm solid water phantom that was placed in the mediastinal area of an anthropomorphic chest phantom with fat ring (QRM-thorax, QRM L-ring, 30 cm × 40 cm cross-section). Inserts were filled with iodine contrast at concentrations of 0.238 to 27.5 mg/mL. A clinical chest protocol at 120 kV on a high-end CCT (Somatom Force, Siemens Healthineers) was compared to the same protocol on a PCCT (Naeotom Alpha, Siemens Healthineers). Images reconstructed with a soft tissue kernel at 1 mm thickness and a 512 matrix served as a reference. For PCCT, we studied the result of reconstructing virtual mono-energetic images (VMIs) at 40, 50, 60 and 70 keV, reducing exposure dose up by 66%, reducing slice thickness to 0.4 and 0.2 mm, and increasing matrix size from 512 to 768 and 1024. Two observers with similar experience independently determined the smallest insert size for which iodine enhancement could still be detected. Consensus was reached when detectability thresholds differed between observers. Results: CTDIvol on PCCT and CCT was 3.80 ± 0.12 and 3.60 ± 0.01 mGy, respectively. PCCT was substantially more sensitive than CCT for detection of iodine in small mediastinal lesions: to detect a 3 mm lesion, 11.2 mg/mL iodine was needed with CCT, while only 1.43 mg/mL was required at 40 keV and 50 keV with PCCT. Moreover, dose reduced by 66% resulted in a comparable detection of iodine between PCCT and CCT for all lesions, except 3 mm. Detection increased from 11.2 mg/mL on CCT to 4.54 mg/mL on PCCT. A matrix size of 1024 reduced this detection threshold further, to 0.238 mg/mL at 40 and 50 keV. For 5 mm lesions, this detection threshold of 0.238 mg/mL was already achieved with a 512 matrix. Very small, 1 mm lesions did not profit from PCCT except if reconstructed with a 1024 matrix, which reduced the detection threshold from 27.5 mg/mL to 11.2 mg/mL. Reduced slice thickness decreased iodine detection of 3-12 mm lesions but not for 1 mm lesions. Conclusions: Iodine detectability with PCCT is at least equal to CCT for simulated mediastinal lesions of 1-12 mm, even at a dose reduction of 66%. Iodine detectability further profits from virtual monoenergetic images of 40 and 50 keV and increased reconstruction matrix.

Nomogram combining dual-energy computed tomography features and radiomics for differentiating parotid warthin tumor from pleomorphic adenoma: a retrospective study

Introduction

Accurate differentiation between pleomorphic adenomas (PA) and Warthin tumors (WT) in the parotid gland is challenging owing to overlapping imaging features. This study aimed to evaluate a nomogram combining dual-energy computed tomography (DECT) quantitative parameters and radiomics to enhance diagnostic precision.

Methods

This retrospective study included 120 patients with pathologically confirmed PA or WT, randomly divided into training and test sets (7:3). DECT features, including tumor CT values from 70 keV virtual monochromatic images (VMIs), iodine concentration (IC), and normalized IC (NIC), were analyzed. Independent predictors were identified via logistic regression. Radiomic features were extracted from segmented regions of interest and filtered using the K-best and least absolute shrinkage and selection operator. Radiomic models based on 70 keV VMIs and material decomposition images were developed using logistic regression (LR), support vector machine (SVM), and random forest (RF). The best-performing radiomics model was combined with independent DECT predictors to construct a model and nomogram. Model performance was assessed using ROC curves, calibration curves, and decision curve analysis (DCA).

Results

IC (venous phase), NIC (arterial phase), and NIC (venous phase) were independent DECT predictors. The DECT feature model achieved AUCs of 0.842 and 0.853 in the training and test sets, respectively, outperforming the traditional radiomics model (AUCs 0.836 and 0.834, respectively). The DECT radiomics model using arterial phase water-based images with LR showed improved performance (AUCs 0.883 and 0.925). The combined model demonstrated the highest discrimination power, with AUCs of 0.910 and 0.947. The combined model outperformed the DECT features and conventional radiomics models, with AUCs of 0.910 and 0.947, respectively (P<0.05). While the difference in AUC between the combined model and the DECT radiomics model was not statistically significant (P>0.05), it showed higher specificity, accuracy, and precision. DCA found that the nomogram gave the greatest net therapeutic effect across a broad range of threshold probabilities.

Discussion

The nomogram combining DECT features and radiomics offers a promising non-invasive tool for differentiating PA and WT in clinical practice.

Photon-Counting Detector CT Applications in Musculoskeletal Radiology

ABSTRACT

Photon-counting detectors (PCDs) have emerged as one of the most influential technical developments for medical imaging in recent memory. Surpassing conventional systems with energy-integrating detector technology in many aspects, PCD-CT scanners provide superior spatial resolution and dose efficiency for all radiological subspecialities. Demanding detailed display of trabecular microarchitecture and extensive anatomical coverage frequently within the same scan, musculoskeletal (MSK) imaging in particular can be a beneficiary of PCD-CT's remarkable performance. Since PCD-CT provides users with a plethora of customization options for both image acquisition and reconstruction, however, MSK radiologists need to be familiar with the scanner to unlock its full potential. From filter-based spectral shaping for artifact reduction over full field-of-view ultra-high-resolution scans to postprocessing of single- or dual-source multienergy data, almost every imaging task can be met with an optimized approach in PCD-CT. The objectives of this review were to give an overview of the most promising applications of PCD-CT in MSK imaging to date, to state current limitations, and to highlight directions for future research and developments.

Effect of temporal resolution on calcium scoring: insights from photon-counting detector CT

To intra-individually investigate the variation of coronary artery calcium (CAC), aortic valve calcium (AVC), and mitral annular calcium (MAC) scores and the presence of blur artifacts as a function of temporal resolution in patients undergoing non-contrast cardiac CT on a dual-source photon counting detector (PCD) CT. This retrospective, IRB-approved study included 70 patients (30 women, 40 men, mean age 78 ± 9 years) who underwent ECG-gated cardiac non-contrast CT with PCD-CT (gantry rotation time 0.25 s) prior to transcatheter aortic valve replacement. Each scan was reconstructed at a temporal resolution of 66 ms using the dual-source information and at 125 ms using the single-source information. Average heart rate and heart rate variability were calculated from the recorded ECG. CAC, AVC, and MAC were quantified according to the Agatston method on images with both temporal resolutions. Two readers assessed blur artifacts using a 4-point visual grading scale. The influence of average heart rate and heart rate variability on calcium quantification and blur artifacts of the respective structures were analyzed by linear regression analysis. Mean heart rate and heart rate variability during data acquisition were 76 ± 17 beats per minute (bpm) and 4 ± 6 bpm, respectively. CAC scores were smaller on 66 ms (median, 511; interquartile range, 220-978) than on 125 ms reconstructions (538; 203-1050, p < 0.001). Median AVC scores [2809 (2009-3952) versus 3177 (2158-4273)] and median MAC scores [226 (0-1284) versus 251 (0-1574)] were also significantly smaller on 66ms than on 125ms reconstructions (p < 0.001). Reclassification of CAC and AVC risk categories occurred in 4% and 11% of cases, respectively, whereby the risk category was always overestimated on 125ms reconstructions. Image blur artifacts were significantly less on 66ms as opposed to 125 ms reconstructions (p < 0.001). Intra-individual analyses indicate that temporal resolution significantly impacts on calcium scoring with cardiac CT, with CAC, MAC, and AVC being overestimated at lower temporal resolution because of increased motion artifacts eventually leading to an overestimation of patient risk.

Editorial for the Special Issue "Imaging Diagnosis in the Abdomen"-A Step Forward in Diagnostic Precision

Abdominal imaging has undergone a significant transformation in recent years, driven by the rapid evolution of diagnostic technologies and their integration into clinical practice [...].

CT Imaging of the Pancreas: A Review of Current Developments and Applications

Pancreatic cancer continues to pose daily challenges to clinicians, radiologists, and researchers. These challenges are encountered at each stage of pancreatic cancer management, including early detection, definite characterization, accurate assessment of tumour burden, preoperative planning when surgical resection is possible, prediction of tumour aggressiveness, response to treatment, and detection of recurrence. CT imaging of the pancreas has made major advances in recent years through innovations in research and clinical practice. Technical advances in CT imaging, often in combination with imaging biomarkers, hold considerable promise in addressing such challenges. Ongoing research in dual-energy and spectral photon-counting computed tomography, new applications of artificial intelligence and image rendering have led to innovative implementations that allow now a more precise diagnosis of pancreatic cancer and other diseases affecting this organ. This article aims to explore the major research initiatives and technological advances that are shaping the landscape of CT imaging of the pancreas. By highlighting key contributions in diagnostic imaging, artificial intelligence, and image rendering, this article provides a comprehensive overview of how these innovations are enhancing diagnostic precision and improving outcome in patients with pancreatic diseases.

Spectral computed tomography in the assessment of metastatic lymph nodes in cervical cancer patients treated with definitive radiotherapy: a single-center, prospective study

Identifying metastatic lymph nodes (LNs) in patients with cervical cancer treated with definitive radiotherapy may inform treatment strategy and determine prognosis, but available methods have limitations, especially in developing regions. Herein, we aimed to evaluate the performance of quantitative parameters in spectral computed tomography (CT) scanning in this context, focusing on its complementary role alongside conventional diagnostic approaches like 18-fluorine-fuorodeoxyglucose positron emission tomography computed tomography (18 F FDG-PET/CT). Patients with cervical cancer, who underwent pretreatment spectral CT simulation scanning and planned radiotherapy, were enrolled in this prospective study. The LNs were categorized as "metastatic" and "non-metastatic", based on a procedure that included 18 F FDG-PET/CT as well as CT, magnetic resonance imaging, Node Reporting and Data System and follow-up results. Iodine concentrations (IC), normalized IC (NIC), effective atom number (effZ), and spectral curve slope (λHU) in the arterial (AP) and venous (VP) phases, were compared between metastatic and non-metastatic LNs. IC were derived from iodine-based material decomposition through manual delineation and normalized to the iodine concentration in the adjacent artery (NIC). effZ and λHU were calculated based on the effective atom number image and virtual monochromatic images. Univariate and multivariate logistic regression analyses were used to determine spectral CT factors independently associated with LNs metastasis, and their diagnostic efficacies were assessed using the area under the curve (AUC) analysis. The diagnostic efficiency of 18 F FDG-PET/CT and spectral CT was compared. A total of 115 metastatic and 97 non-metastatic LNs were detected, and spectral CT parameters (IC, NIC, effZ, λHU) significantly differed between the two groups. In univariate and multivariable logistic regression analysis, λHU in the AP and NIC in the VP were independent predictors for metastatic LNs and their combination improved AUC to 0.923, with a sensitivity of 84.4%, and a specificity of 85.6%. Spectral CT could achieve similar sensitivity as 18 FFDG-PET/CT in total LNs, and, more importantly, a higher sensitivity (95.5% vs. 59.1%) and diagnostic accuracy (92.9% vs. 67.9%) for para-aortic LNs. Quantitative spectral CT parameters can help distinguish metastatic from non-metastatic LNs in patients with cervical cancer treated with definitive radiotherapy. Combination of λHU in AP and NIC in VP further improves diagnostic performance. Spectral CT, while promising, complements rather than replaces PET/CT, especially for diagnosing para-aortic LNs, where PET/CT may have limitations. It could be a valuable adjunct to conventional imaging, particularly in settings with limited access to advanced tools.

Coronary artery disease detection using deep learning and ultrahigh-resolution photon-counting coronary CT angiography

PURPOSE

The purpose of this study was to evaluate the diagnostic performance of automated deep learning in the detection of coronary artery disease (CAD) on photon-counting coronary CT angiography (PC-CCTA).

MATERIALS AND METHODS

Consecutive patients with suspected CAD who underwent PC-CCTA between January 2022 and December 2023 were included in this retrospective, single-center study. Non-ultra-high resolution (UHR) PC-CCTA images were analyzed by artificial intelligence using two deep learning models (CorEx, Spimed-AI), and compared to human expert reader assessment using UHR PC-CCTA images. Diagnostic performance for global CAD assessment (at least one significant stenosis ≥ 50 %) was estimated at patient and vessel levels.

RESULTS

A total of 140 patients (96 men, 44 women) with a median age of 60 years (first quartile, 51; third quartile, 68) were evaluated. Significant CAD on UHR PC-CCTA was present in 36/140 patients (25.7 %). The sensitivity, specificity, accuracy, positive predictive value), and negative predictive value of deep learning-based CAD were 97.2 %, 81.7 %, 85.7 %, 64.8 %, and 98.9 %, respectively, at the patient level and 96.6 %, 86.7 %, 88.1 %, 53.8 %, and 99.4 %, respectively, at the vessel level. The area under the receiver operating characteristic curve was 0.90 (95 % CI: 0.83-0.94) at the patient level and 0.92 (95 % CI: 0.89-0.94) at the vessel level.

CONCLUSION

Automated deep learning shows remarkable performance for the diagnosis of significant CAD on non-UHR PC-CCTA images. AI pre-reading may be of supportive value to the human reader in daily clinical practice to target and validate coronary artery stenosis using UHR PC-CCTA.

Ultra-high resolution spectral photon-counting CT outperforms dual layer CT for lung imaging: Results of a phantom study

PURPOSE

The purpose of this study was to compare lung image quality obtained with ultra-high resolution (UHR) spectral photon-counting CT (SPCCT) with that of dual-layer CT (DLCT), at standard and low dose levels using an image quality phantom and an anthropomorphic lung phantom.

METHODS

An image quality phantom was scanned using a clinical SPCCT prototype and an 8 cm collimation DLCT from the same manufacturer at 10 mGy. Additional acquisitions at 6 mGy were performed with SPCCT only. Images were reconstructed with dedicated high-frequency reconstruction kernels, slice thickness between 0.58 and 0.67 mm, and matrix between 5122 and 10242 mm, using a hybrid iterative algorithm at level 6. Noise power spectrum (NPS), task-based transfer function (TTF) for iodine and air inserts, and detectability index (d') were assessed for ground-glass and solid nodules of 2 mm to simulate highly detailed lung lesions. Subjective analysis of an anthropomorphic lung phantom was performed by two radiologists using a five-point quality score.

RESULTS

At 10 mGy, noise magnitude was reduced by 29.1 % with SPCCT images compared to DLCT images for all parameters (27.1 ± 11.0 [standard deviation (SD)] HU vs. 38.2 ± 1.0 [SD] HU, respectively). At 6 mGy with SPCCT images, noise magnitude was reduced by 8.9 % compared to DLCT images at 10 mGy (34.8 ± 14.1 [SD] HU vs. 38.2 ± 1.0 [SD] HU, respectively). At 10 mGy and 6 mGy, average NPS spatial frequency (fav) was greater for SPCCT images (0.75 ± 0.17 [SD] mm-1) compared to DLCT images at 10 mGy (0.55 ± 0.04 [SD] mm-1) while remaining constant from 10 to 6 mGy. At 10 mGy, TTF at 50 % (f50) was greater for SPCCT images (0.92 ± 0.08 [SD] mm-1) compared to DLCT images (0.67 ± 0.06 [SD] mm-1) for both inserts. At 6 mGy, f50 decreased by 1.1 % for SPCCT images, while remaining greater compared to DLCT images at 10 mGy (0.91 ± 0.06 [SD] mm-1 vs. 0.67 ± 0.06 [SD] mm-1, respectively). At both dose levels, d' were greater for SPCCT images compared to DLCT for all clinical tasks. Subjective analysis performed by two radiologists revealed a greater median image quality for SPCCT (5; Q1, 4; Q3, 5) compared to DLCT images (3; Q1, 3; Q3, 3).

CONCLUSION

UHR SPCCT outperforms DLCT in terms of image quality for lung imaging. In addition, UHR SPCCT contributes to a 40 % reduction in radiation dose compared to DLCT.

Photon-counting CT systems: A technical review of current clinical possibilities

In recent years, computed tomography (CT) has undergone a number of developments to improve radiological care. The most recent major innovation has been the development of photon-counting detectors. By comparison with the energy-integrating detectors traditionally used in CT, these detectors offer better dose efficiency, eliminate electronic noise, improve spatial resolution and have intrinsic spectral sensitivity. These detectors also allow the energy of each photon to be counted, thus improving the sampling of the X-ray spectrum in multiple energy bins, to better distinguish between photoelectric and Compton attenuation coefficients, resulting in better spectral images and specific color K-edge images. The purpose of this article was to make the reader more familiar with the basic principles and techniques of new photon-counting CT systems equipped with photon-counting detectors and also to describe the currently available devices that could be used in clinical practice.

Stereotactic arrhythmia radioablation for ventricular tachycardia: a review of clinical trials and emerging roles of imaging

Ventricular tachycardia (VT) is a severe arrhythmia commonly treated with implantable cardioverter defibrillators, antiarrhythmic drugs and catheter ablation (CA). Although CA is effective in reducing recurrent VT, its impact on survival remains uncertain, especially in patients with extensive scarring. Stereotactic arrhythmia radioablation (STAR) has emerged as a novel treatment for VT in patients unresponsive to CA, leveraging techniques from stereotactic body radiation therapy used in cancer treatments. Recent clinical trials and case series have demonstrated the short-term efficacy and safety of STAR, although long-term outcomes remain unclear. Imaging techniques, such as electroanatomical mapping, contrast-enhanced magnetic resonance imaging and nuclear imaging, play a crucial role in treatment planning by identifying VT substrates and guiding target delineation. However, challenges persist owing to the complex anatomy and variability in target volume definitions. Advances in imaging and artificial intelligence are expected to improve the precision and efficacy of STAR. The exact mechanisms underlying the antiarrhythmic effects of STAR, including potential fibrosis and improvement in cardiac conduction, are still being explored. Despite its potential, STAR should be cautiously applied in prospective clinical trials, with a focus on optimizing dose delivery and understanding long-term outcomes. Collaborative efforts are necessary to standardize treatment strategies and enhance the quality of life for patients with refractory VT.

Diagnostic efficacy of dual-energy CT virtual non-calcium technique in the diagnosis of bone marrow edema of sacroiliac joints in ankylosing spondylitis

OBJECTIVE

In-depth investigation of the diagnostic performance of dual-energy CT (DECT) virtual non-calcium (VNCa) technique for sacroiliac joint bone marrow edema (BME) in patients with ankylosing spondylitis(AS).

METHODS

A total of 42 patients with AS)who underwent sacroiliac joint MRI and DECT scans on the same day at our Rheumatology and Immunology Department between August 2022 and June 2023 were selected. Using MRI as the reference standard, the presence of BME on the iliac and sacral surfaces was evaluated, resulting in the categorization of patients into BME-positive and BME-negative groups. Subsequently, the DECT scan data was processed using the "Bone Marrow" algorithm to generate VNCa color-coded images of the bone marrow. The diagnostic performance of DECT in detecting BME was assessed through visual qualitative evaluation and objective quantitative analysis.

RESULTS

Visual qualitative assessment analysis showed good agreement between the results of BME analysis on virtual non-calcium images and MRI images by both physicians (Kappa > 0.61). The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of visual qualitative assessment for BME by Physicians A and B were as follows: iliac facet [(92.5%, 88.6%, 88.1%, 92.9%, 90.5%), (90.0%, 90.9%, 90.0%, 90.9%, 90.5%)], sacral facet [(88.4%, 87.8%, 88.4%, 87.8%, 88.1%), (90.7%, 85.3%, 86.7%, 89.7%, 88.1%)].In terms of objective quantitative analysis, the CT values of the edematous areas on the iliac and sacral surfaces were (-41.4 ± 15.9) Hu and (-38.8 ± 19.7) Hu, respectively, while the CT values of normal bone marrow areas were (-79.6 ± 18.2) Hu and (-72.8 ± 14.8) Hu, respectively. The CT values of the edematous areas were higher than those of the non-edematous areas. Based on the receiver operating characteristic curve analysis, the area under the curve for the iliac and sacral surfaces were 0.90 and 0.89, respectively. The optimal CT cutoff values were - 57.4 Hu and - 56.8 Hu, with corresponding sensitivities of 92.5% and 86.4% and specificities of 90.7% and 87.8%.

CONCLUSION

The DECT VNCa technique has a high diagnostic efficacy in the diagnosis of BME in the sacroiliac joints in ankylosing spondylitis in terms of visual qualitative assessment and objective quantitative analysis.

Evaluation of Photon-Counting CT for Spectral Imaging in Cardiovascular Applications: Impact of Lumen Size, Dose, and Patient Habitus

Objectives

This study evaluates the performance of a clinical dual-source photon-counting computed tomography (PCCT) system in quantifying iodine within calcified vessels, using 3D- printed phantoms with vascular-like structures lined with calcium.

Methods

Parameters assessed include lumen diameters (4, 6, 8, 10, and 12 mm), phantom sizes (S: 20×20 cm, M: 25×25 cm, L: 30×40 cm, XL: 40×50 cm, representing the 99th percentile of US patient sizes), and iodine concentrations (2, 5, and 10 mg/mL). Scans were performed at radiation dose levels of 5, 10, 15, and 20 mGy to systematically evaluate iodine quantification accuracy and spectral imaging performance.

Results

The results indicate that for lumen diameters ≥6 mm, iodine quantification remains stable across all dose levels and phantom sizes, with deviations consistently below 0.6 mg/mL. Whereas, for 4 mm lumens, stability is observed primarily in smaller to medium phantoms, highlighting the influence of patient size and radiation dose on quantification accuracy. Virtual Monoenergetic Imaging (VMI) at 70 keV showed stable performance for larger lumens (≥6 mm) with variations of 13 ± 2 HU across all conditions, while smaller lumens remained stable in medium to small phantoms.

Conclusions

These findings highlight the influence of lumen diameter, patient size, and radiation dose in optimizing PCCT protocols for spectral imaging. Importantly, the study demonstrates that PCCT delivers stable and highly accurate imaging across nearly the entire range of patient sizes in the U.S..

Advances in knowledge

This study demonstrates PCCT's potential to enhance spectral imaging in vascular applications, surpassing conventional or Dual Energy CT.

Diagnostic value of dual-layer spectral detector CT parameters for differentiating high- from low-grade bladder cancer

OBJECTIVES

This study aimed to investigate the diagnostic value of spectral parameters of dual-layer spectral detector computed tomography (DLCT) in distinguishing between low- and high-grade bladder cancer (BCa).

METHODS

This single-center retrospective study included pathologically confirmed BCa patients who underwent preoperative contrast-enhanced DLCT. Patients were divided into low- and high-grade groups based on pathology. We measured and calculated the following spectral CT parameters: iodine density (ID), normalized ID (NID), arterial enhancement fraction (AEF), extracellular volume (ECV) fraction, virtual non-contrast (VNC), slope of the attenuation curve, and Z effective (Zeff). Univariate and multivariable logistic regression analyses were used to determine the best predictive factors in differentiating between low- and high-grade BCa. We used receiver operating characteristic curve analysis to assess diagnostic performance and decision curve analysis to determine the net benefit.

RESULTS

The study included 64 patients (mean age, 64 ± 11.0 years; 46 men), of whom 42 had high-grade BCa and 22 had low-grade BCa. Univariate analysis revealed that differences in ID and NID in the corticomedullary phase, AEF, ECV, VNC, and Zeff images were statistically significant (p = 0.001-0.048). Multivariable analysis found that AEF was the best predictor of high-grade tumors (p = 0.006). With AEF higher in high-grade BCa, AEF results were as follows: area under the curve (AUC), 0.924 (95% confidence interval, 0.861-0.988); sensitivity, 95.5%; specificity, 81.0%; and accuracy, 85.9%. The cutoff valve of AEF for predicting high-grade BCa was 67.7%.

CONCLUSION

Using DLCT AEF could help distinguish high-grade from low-grade BCa.

CRITICAL RELEVANCE STATEMENT

This research demonstrates that the arterial enhancement fraction (AEF), a parameter derived from dual-layer spectral detector CT (DLCT), effectively distinguishes between high- and low-grade bladder cancer, thereby aiding in the selection of appropriate clinical treatment strategies.

KEY POINTS

This study investigated the value of dual-layer spectral detector CT in the assessment of bladder cancer (BCa) histological grade. The spectral parameter arterial enhancement fraction could help determine BCa grade. Our results can help clinicians formulate initial treatment strategies and improve prognostications.

Quantitative multi-energy CT in oncology: State of the art and future directions

Multi-energy computed tomography (CT) involves acquisition of two or more CT measurements with distinct energy spectra. Using the differential attenuation of tissues and materials at different X-ray energies, multi-energy CT allows distinction of tissues and materials. Multi-energy technology encompasses different types of CT systems, such as dual-energy CT and photon-counting CT, that can use information from the energy and type of material present in acquired images to create multiple datasets. These scanners have overcome many of the limitations of conventional CT, making it possible to improve the diagnostic performance of CT and expand its use to new applications through better tissue characterization and multiple quantitative parameters. Quantitative imaging biomarkers based on multi-energy CT have enormous potential in oncologic imaging, from the diagnosis and characterization of tumor phenotypes to the evaluation of the response to treatment. Nevertheless, implementing these techniques in clinical practice remains challenging. This article reviews the basic principles underlying multi-energy CT and the most recent technical developments in these systems together with their advantages and limitations to establish the value of quantitative imaging derived from multi-energy CT in the field of oncology.

Spectral CT-based nomogram for evaluation of neoadjuvant chemotherapy response in esophageal squamous cell carcinoma

OBJECTIVES

To establish a spectral CT-based nomogram for predicting the response to neoadjuvant chemotherapy (NAC) in patients with locally advanced esophageal squamous cell carcinoma (ESCC).

METHODS

This retrospective study included 172 patients with ESCC who underwent spectral CT scans before NAC followed by resection. Based on postoperative tumor regression grades (TRG), 34% (58) of patients were responsive (TRG1) and 66% (114) were non-responsive (TRG2-3). The data was divided into a primary set of 120 and a validation set of 52, maintaining a 7:3 random ratio. Measurements included iodine concentration (IC), normalized iodine concentration (nIC), CT40kev, CT70kev, spectral attenuation curve slope (λHU), and effective atomic number (Zeff) during non-contrast and venous phases (VP). Clinicopathologic characteristics were collected. Univariable and multivariable logistic regressions identified independent predictors of NAC response. The model was visualized using nomograms, and its efficacy was assessed via receiver operating characteristic (ROC) curves.

RESULTS

Multivariable logistic regression analysis identified the neutrophil-to-lymphocyte ratio (NLR), clinical stage, ZeffVP, and nICVP as independent predictors of NAC response. The nomogram incorporating all four independent predictors, outperformed spectral CT and the clinical model with the highest AUCs of 0.825 (95% CI: 0.746-0.895) for the primary set and 0.794 (95% CI: 0.635-0.918) for the validation set (DeLong test: all p < 0.05).

CONCLUSIONS

The spectral CT and clinical models were useful in predicting NAC response in ESCC patients. Combining spectral CT imaging parameters and clinicopathologic characteristics in a nomogram improved predictive accuracy.

KEY POINTS

Question Developing a non-invasive, practical tool to predict ESCC's response to chemotherapy is crucial and has not yet been done. Findings This nomogram, incorporating clinicopathologic characteristics and spectral CT-derived parameters, predicted NAC response in ESCC patients. Clinical relevance This spectral CT-based nomogram is a non-invasive and easily obtainable tool for accurately predicting ESCC response to NAC, aiding clinicians in personalized treatment planning.

Photon-counting in dual-contrast-enhanced computed tomography: a proof-of-concept quantitative biomechanical assessment of articular cartilage

This proof-of-concept study explores quantitative imaging of articular cartilage using photon-counting detector computed tomography (PCD-CT) with a dual-contrast agent approach, comparing it to clinical dual-energy CT (DECT). The diffusion of cationic iodinated CA4 + and non-ionic gadolinium-based gadoteridol contrast agents into ex vivo bovine medial tibial plateau cartilage was tracked over 72 h. Continuous maps of the contrast agents' diffusion were created, and correlations with biomechanical indentation parameters (equilibrium and instantaneous moduli, and relaxation time constants) were examined at 28 specific locations. Cartilage at each location was analyzed as full-thickness to ensure a fair comparison, and calibration-based material decomposition was employed for concentration estimation. Both DECT and PCD-CT exhibit strong correlations between CA4 + content and biomechanical parameters, with PCD-CT showing superior significance, especially at later time points. DECT lacks significant correlations with gadoteridol-related parameters, while PCD-CT identifies noteworthy correlations between gadoteridol diffusion and biomechanical parameters. In summary, the experimental PCD-CT setup demonstrates superior accuracy and sensitivity in concentration estimation, suggesting its potential as a more effective tool for quantitatively assessing articular cartilage condition compared to a conventional clinical DECT scanner.

Image quality of virtual monochromatic and material density iodine images for evaluation of head and neck neoplasms using deep learning-based CT image reconstruction - A retrospective observational study

PURPOSE

To compare the quality of deep learning image reconstructed (DLIR) virtual monochromatic images (VMI) and material density (MD) iodine images from dual-energy computed tomography (DECT) for the evaluation of head and neck neoplasms with CT scans from a conventional single-energy protocol.

METHOD

A total of 294 head and neck CT scans (98 VMIs operated at 60 keV, 102 MD iodine images, and 94 images from a 120 kVp single-energy CT (SECT) protocol) were retrospectively evaluated. VMIs and MD iodine images were generated using the Gemstone Spectral Imaging (GSI) mode using DLIR and metal artifact reduction (MAR) algorithms. SECT images were generated using adaptive statistical iterative reconstruction (ASIR-V). Images were scored by two independent readers on a 6-point Likert-type scale for overall image quality, vessel contrast, soft tissue contrast, noise texture, noise intensity, artifact reduction, and sharpness.

RESULTS

Subjective overall image quality was rated as superior or excellent in 98 % of DLIR-based MD iodine images and VMIs, but only in 55 % of ASIR-V-based SECT images. For each individual quality criterion, image quality of VMIs and MD iodine images was rated as better than that of SECT images (p < 0.001 in each case). Noise texture and intensity were rated better in MD iodine images than in VMIs.

CONCLUSION

DECT using both DLIR and MAR for the generation of VMIs and MD iodine images resulted in higher subjective quality of oncologic head and neck images than ASIR-V-based SECT. Noise reduction and noise texture were best achieved with DLIR-based MD iodine images.

Recent Breakthroughs in PET-CT Multimodality Imaging: Innovations and Clinical Impact

This review presents a detailed examination of the most recent advancements in positron emission tomography-computed tomography (PET-CT) multimodal imaging over the past five years. The fusion of PET and CT technologies has revolutionized medical imaging, offering unprecedented insights into both anatomical structure and functional processes. The analysis delves into key technological innovations, including advancements in image reconstruction, data-driven gating, and time-of-flight capabilities, highlighting their impact on enhancing diagnostic accuracy and clinical outcomes. Illustrative case studies underscore the transformative role of PET-CT in lesion detection, disease characterization, and treatment response evaluation. Additionally, the review explores future prospects and challenges in PET-CT, advocating for the integration and evaluation of emerging technologies to improve patient care. This comprehensive synthesis aims to equip healthcare professionals, researchers, and industry stakeholders with the knowledge and tools necessary to navigate the evolving landscape of PET-CT multimodal imaging.

Creating a Foundation for the Visualization of Intracranial Cerebrospinal Fluid Using Photon-Counting Technology in Spectral Imaging for Cranial CT

BACKGROUND

Recent advancements in computed tomography (CT), notably in photon-counting CT (PCCT), are revolutionizing the medical imaging field. PCCT's spectral imaging can better visualize tissues based on their material properties. This research aims to establish a fundamental approach for the in vivo visualization of intracranial cerebrospinal fluid (CSF) using PCCT.

METHODS

PCCT was integrated to distinguish the CSF within the intracranial space with spectral imaging. In this study, we analyzed monoenergetic +67 keV reconstructions alongside virtual non-contrast and iodine phase images. This approach facilitated the assessment of the spectral characteristics of CSF in patients who did not present with intra-axial pathology or inflamation.

RESULTS

Our findings illustrate PCCT's effectiveness in providing distinct and clear visualizations of intracranial CSF structures, building a foundation. The signal-to-noise ratio was quantified across all measurements, to check in image quality.

CONCLUSIONS

PCCT serves as a robust, non-invasive platform for the detailed visualization of intracranial CSF. This technology is promising in enhancing diagnostic accuracy through different conditions.

Material decomposition approaches for monosodium urate (MSU) quantification in gouty arthritis: a (bio)phantom study

BACKGROUND

Dual-energy computed tomography (DECT) is a noninvasive diagnostic tool for gouty arthritis. This study aimed to compare two postprocessing techniques for monosodium urate (MSU) detection: conventional two-material decomposition and material map-based decomposition.

METHODS

A raster phantom and an ex vivo biophantom, embedded with four different MSU concentrations, were scanned in two high-end CT scanners. Scanner 1 used the conventional postprocessing method while scanner 2 employed the material map approach. Volumetric analysis was performed to determine MSU detection, and image quality parameters, such as signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR), were computed.

RESULTS

The material map-based method demonstrated superior MSU detection. Specifically, scanner 2 yielded total MSU volumes of 5.29 ± 0.28 mL and 4.52 ± 0.29 mL (mean ± standard deviation) in the raster and biophantom, respectively, versus 2.35 ± 0.23 mL and 1.15 ± 0.17 mL for scanner 1. Radiation dose correlated positively with detection for the conventional scanner, while there was no such correlation for the material map-based decomposition method in the biophantom. Despite its higher detection rate, material map-based decomposition was inferior in terms of SNR, CNR, and artifacts.

CONCLUSION

While material map-based decomposition resulted in superior MSU detection, it is limited by challenges such as increased artifacts. Our findings highlight the potential of this method for gout diagnosis while underscoring the need for further research to enhance its clinical reliability.

RELEVANCE STATEMENT

Advanced postprocessing such as material-map-based two-material decomposition might improve the sensitivity for gouty arthritis in clinical practice, thus, allowing for lower radiation doses or better sensitivity for gouty tophi.

KEY POINTS

Dual-energy CT showed limited sensitivity for tophi with low MSU concentrations. Materiel-map-based decomposition increased sensitivity compared to conventional two-material decomposition. The advantages of material-map-based decomposition outweigh lower image quality and increased artifact load.

Spectral computed tomography in abdominal and pelvic pathologies. A practical guide

Spectral computed tomography has represented a major breakthrough in radiology thanks to its multiple applications and potential to provide more information than conventional CT techniques. It is very useful for diagnosing and describing findings as well as the management of patients, thus avoiding further imaging or invasive procedures. The aim of this article is to explain basic concepts of spectral CT and highlight key practical features in a range of abdominal and pelvic pathologies, along with a brief description of different post-processing maps and their clinical applications including incidental, oncological and urgent findings.

Potential dose reduction and image quality improvement in chest CT with a photon-counting CT compared to a new dual-source CT

PURPOSE

To compare potential dose reduction and quality improvement in chest CT images with Photon-Counting CT (PCCT) versus a Dual-Source CT (DSCT).

METHODS

Acquisitions on phantoms were performed on a DSCT and a PCCT at 5 dose levels (9.5/7.5/6.0/2.5/0.4 mGy). Noise power spectrum (NPS) and task-based transfer function (TTF) were calculated to assess noise magnitude and noise texture (fav) and spatial resolution (f50), respectively. Computed detectability indexes (d') modelled the detection of 2 chest lesions: subsolid pulmonary nodules (SPN) and high-contrast pulmonary nodules (HCN). Two radiologists subjectively assessed the quality of chest images on an anthropomorphic phantom.

RESULTS

For all dose levels, noise magnitude was significantly lower with PCCT than with DSCT (-44.7 ± 3.0 %; p < 0.05). Identical outcomes were found for noise texture (fav; -6.2 ± 0.5 %; p < 0.05). f50 values were significantly higher with DSCT than with PCCT from 9.5 to 6 mGy for iodine insert (p < 0.05) and from 7.5 to 2.5 mGy for air insert (p < 0.05), but similar for both inserts at other dose levels. For all dose levels, d' values were significantly higher with PCCT than DSCT (71.9 ± 5.4 % for HCN and 65.6 ± 13.5 % for SPN). From 9.5 to 2.5 mGy, the potential dose reduction was -59.0 ± 3.9 % for both lesions with PCCT compared to DSCT. Chest images were rated satisfactory for clinical use by the radiologists with both CTs for all dose levels, except at 0.4 mGy.

CONCLUSION

Noise magnitude and detectability of chest lesions were better with PCCT than with the DSCT. PCCT may offer great potential for dose reduction in patients undergoing chest CT examinations.

Canadian radiology: 2024 update

Radiology in Canada is advancing through innovations in clinical practices and research methodologies. Recent developments focus on refining evidence-based practice guidelines, exploring innovative imaging techniques and enhancing diagnostic processes through artificial intelligence. Within the global radiology community, Canadian institutions play an important role by engaging in international collaborations, such as with the American College of Radiology to refine implementation of the Ovarian-Adnexal Reporting and Data System for ultrasound and magnetic resonance imaging. Additionally, researchers have participated in multidisciplinary collaborations to evaluate the performance of artificial intelligence-driven diagnostic tools for chronic liver disease and pediatric brain tumors. Beyond clinical radiology, efforts extend to addressing gender disparities in the field, improving educational practices, and enhancing the environmental sustainability of radiology departments. These advancements highlight Canada's role in the global radiology community, showcasing a commitment to improving patient outcomes and advancing the field through research and innovation. This update underscores the importance of continued collaboration and innovation to address emerging challenges and further enhance the quality and efficacy of radiology practices worldwide.

Imaging of Peritoneal Surface Malignancies

Management of peritoneal surface malignancies is currently entrusted to a multimodality approach. Computed tomography (CT) scan remains the first imaging method despite the limitations in identifying small implants in critical regions. Magnetic resonance imaging is usually recommended for its performance in small implants, mesentery, and small bowel assessment. Positron emission tomography/CT plays an important role only in pseudomyxoma peritonei. Thus, becoming aware of the imaging strengths and drawbacks and having a multimodality imaging approach might be the best option for the patients.

Multivendor comparison of quantification accuracy of effective atomic number by Dual-Energy CT: A phantom study

PURPOSE

Our study aimed to compare the accuracy of the effective atomic number (Zeff) of five dual-energy CT (DECT) from three vendors and different generations under different scanning parameters.

METHODS

Zeff accuracy of five DECT scanners with twelve tube voltage configurations was evaluated by using the TomoTherapy cheese phantom. The potential dose dependence of the Zeff was investigated using three radiation dose (5, 15, and 25 mGy), and the robustness of Zeff was simulated for different organs of the body by placing the inserts at different positional depths. Bias and mean absolute percentage error (MAPE) were used to characterize the accuracy of Zeff. Data underwent analysis using one-way ANOVA, followed by the Turky and LSD post hoc tests, simple linear regression, and linear mixed models.

RESULTS

All tube voltage configurations had a bias of less than 1. Dual layer detector DECT (dl-DECT) -140 kV has the lowest MAPE (1.79 %±1.93 %). The third generation dual source DECT (ds-DECT) and the second generation rapid switch DECT (rs-DECT) have higher MAPE than their predecessor DECT. The results of the linear mixed model showed that tube voltage configuration (F=16.92, p < 0.001) and insert type (F=53.26, p < 0.001) significantly affect the MAPE. In contrast, radiation dose only has a significant effect on the MAPE of rs-DECT. The inserts position does not affect the final MAPE.

CONCLUSION

When scanning different inserts, Zeff accuracy varies by vendor and DECT generation. Of all the scanners, dl-DECT had the highest Zeff accuracy. Upgrading DECT generation doesn't lead to higher accuracy, or even lower.

Differentiation of pathological subtypes and Ki-67 and TTF-1 expression by dual-energy CT (DECT) volumetric quantitative analysis in non-small cell lung cancer

BACKGROUND

To explore the value of dual-energy computed tomography (DECT) in differentiating pathological subtypes and the expression of immunohistochemical markers Ki-67 and thyroid transcription factor 1 (TTF-1) in patients with non-small cell lung cancer (NSCLC).

METHODS

Between July 2022 and May 2024, patients suspected of lung cancer who underwent two-phase contrast-enhanced DECT were prospectively recruited. Whole-tumor volumetric and conventional spectral analysis were utilized to measure DECT parameters in the arterial and venous phase. The DECT parameters model, clinical-CT radiological features model, and combined prediction model were developed to discriminate pathological subtypes and predict Ki-67 or TTF-1 expression. Multivariate logistic regression analysis was used to identify independent predictors. The diagnostic efficacy was assessed by the area under the receiver operating characteristic curve (AUC) and compared using DeLong's test.

RESULTS

This study included 119 patients (92 males and 27 females; mean age, 63.0 ± 9.4 years) who was diagnosed with NSCLC. When applying the DECT parameters model to differentiate between adenocarcinoma and squamous cell carcinoma, ROC curve analysis indicated superior diagnostic performance for conventional spectral analysis over volumetric spectral analysis (AUC, 0.801 vs. 0.709). Volumetric spectral analysis exhibited higher diagnostic efficacy in predicting immunohistochemical markers compared to conventional spectral analysis (both P < 0.05). For Ki-67 and TTF-1 expression, the combined prediction model demonstrated optimal diagnostic performance with AUC of 0.943 and 0.967, respectively.

CONCLUSIONS

The combined predictive model based on volumetric quantitative analysis in DECT offers valuable information to discriminate immunohistochemical expression status, facilitating clinical decision-making for patients with NSCLC.

Computed Tomography and Magnetic Resonance Imaging in Liver Iron Overload: From Precise Quantification to Prognosis Assessment

Liver iron overload is associated with conditions such as hereditary hemochromatosis, thalassemia major, and chronic liver diseases. The liver-related outcomes, patient outcomes, and treatment recommendations of these patients differ depending on the cause and extent of iron overload. Accurate quantification of the liver iron concentration (LIC) is critical for effective patient management. This review focuses on the application of computed tomography (CT) and magnetic resonance imaging (MRI) for the precise quantification and prognostic assessment of liver iron overload. In recent years, the use of dual-energy CT and the emergence of MRI-based sequences (such as UTE, QSM, Dixon, and CSE technologies) have significantly increased the potential for noninvasive liver iron quantification. However, the establishment of internationally standardized imaging parameters, postprocessing procedures, and reporting protocols is urgently needed for better management of patients with liver iron overload.

Whole-volume histogram analysis of spectral-computed tomography iodine maps characterizes HER2 expression in gastric cancer

BACKGROUND

Although surgery remains the primary treatment for gastric cancer (GC), the identification of effective alternative treatments for individuals for whom surgery is unsuitable holds significance. HER2 overexpression occurs in approximately 15%-20% of advanced GC cases, directly affecting treatment-related decisions. Spectral-computed tomography (sCT) enables the quantification of material compositions, and sCT iodine concentration parameters have been demonstrated to be useful for the diagnosis of GC and prediction of its invasion depth, angiogenesis, and response to systemic chemotherapy. No existing report describes the prediction of GC HER2 status through histogram analysis based on sCT iodine maps (IMs).

AIM

To investigate whether whole-volume histogram analysis of sCT IMs enables the prediction of the GC HER2 status.

METHODS

This study was performed with data from 101 patients with pathologically confirmed GC who underwent preoperative sCT examinations. Nineteen parameters were extracted via sCT IM histogram analysis: The minimum, maximum, mean, standard deviation, variance, coefficient of variation, skewness, kurtosis, entropy, percentiles (1st, 5th, 10th, 25th, 50th, 75th, 90th, 95th, and 99th), and lesion volume. Spearman correlations of the parameters with the HER2 status and clinicopathological parameters were assessed. Receiver operating characteristic curves were used to evaluate the parameters' diagnostic performance.

RESULTS

Values for the histogram parameters of the maximum, mean, standard deviation, variance, entropy, and percentiles were significantly lower in the HER2+ group than in the HER2- group (all P < 0.05). The GC differentiation and Lauren classification correlated significantly with the HER2 status of tumor tissue (P = 0.001 and 0.023, respectively). The 99th percentile had the largest area under the curve for GC HER2 status identification (0.740), with 76.2%, sensitivity, 65.0% specificity, and 67.3% accuracy. All sCT IM histogram parameters correlated positively with the GC HER2 status (r = 0.237-0.337, P = 0.001-0.017).

CONCLUSION

Whole-lesion histogram parameters derived from sCT IM analysis, and especially the 99th percentile, can serve as imaging biomarkers of HER2 overexpression in GC.

Using Dual-source Photon-counting Detector CT to Simultaneously Quantify Fat and Iron Content: A Phantom Study

RATIONALE AND OBJECTIVES

To evaluate the feasibility of using photon-counting detector computed tomography (PCD CT) to simultaneously quantify fat and iron content MATERIALS AND METHODS: Phantoms with pure fat, pure iron and fat-iron deposition were scanned by two tube voltages (120 and 140 kV) and two image quality (IQ) settings (80 and 145). Using an iron-specific three-material decomposition algorithm, virtual noniron (VNI) and virtual iron content (VIC) images were generated at quantum iterative reconstruction (QIR) strength levels 1-4.

RESULTS

Significant linear correlations were observed between known fat content (FC) and VNI for pure fat phantoms (r = 0.981-0.999, p < 0.001) and between known iron content (IC) and VIC for pure iron phantoms (r = 0.897-0.975, p < 0.001). In fat-iron phantoms, the measurement for fat content of 5-30% demonstrated good linearity between FC and VNI (r = 0.919-0.990, p < 0.001), and VNI were not affected by 75, 150, and 225 µmol/g iron overload (p = 0.174-0.519). The measurement for iron demonstrated a linear range of 75-225 µmol/g between IC and VIC (r = 0.961-0.994, p < 0.001) and VIC was not confounded by the coexisting 5%, 20%, and 30% fat deposition (p = 0.943-0.999). The Bland-Altman of fat and iron measurements were not significantly different at varying tube voltages and IQ settings (all p > 0.05). No significant difference in VNI and VIC at QIR 1-4.

CONCLUSION

PCD CT can accurately and simultaneously quantify fat and iron, including scan parameters with lower radiation dose.

Head and neck automatic multi-organ segmentation on Dual-Energy Computed Tomography

Background and purpose

Deep-learning-based automatic segmentation is widely used in radiation oncology to delineate organs-at-risk. Dual-energy CT (DECT) allows the reconstruction of enhanced contrast images that could help with manual and auto-delineation. This paper presents a performance evaluation of a commercial auto-segmentation software on image series generated by a DECT.

Material and methods

Different types of DECT images from seventy four head-and-neck (HN) patients were retrieved, including polyenergetic images at different voltages [80 kV reconstructed with a kernel corresponding to the commercial algorithm DirectDensity™ (PEI80-DD), 80 kV (PEI80), 120 kV-mixed (PEI120)] and a virtual-monoenergetic image at 40 keV (VMI40). Delineations used for treatment planning were considered as ground truth (GT) and were compared with the auto-segmentations performed on the 4 DECT images. A blinded qualitative evaluation of 3 structures (thyroid, left parotid, left nodes level II) was carried out. Performance metrics were calculated for thirteen HN structures to evaluate the auto-contours including dice similarity coefficient (DSC), 95th percentile Hausdorff distance (95HD) and mean surface distance (MSD).

Results

We observed a high rate of low scores for PEI80-DD and VMI40 auto-segmentations on the thyroid and for GT and VMI40 contours on the nodes level II. All images received excellent scores for the parotid glands. The metrics comparison between GT and auto-segmented contours revealed that PEI80-DD had the highest DSC scores, significantly outperforming other reconstructed images for all organs (p < 0.05).

Conclusions

The results indicate that the auto-contouring system cannot generalize to images derived from DECT acquisition. It is therefore crucial to identify which organs benefit from these acquisitions to adapt the training datasets accordingly.

Multi-energy CT and iodinated contrast

Spectral CT acquires images with the emission or detection of two separate energy spectra. This enables material decomposition due to the photoelectric effect (prevalent in low-energy photons) and Compton scattering (prevalent in high-energy photons). Iodine and other materials with high atomic numbers appear more hyperdense on low-energy monoenergetic images because of the direct relation between the photoelectric effect and the Z value. Given the way iodine behaves on spectral maps, radiologists can optimise the use of contrast media in these CTs, thus allowing lower doses of radiation and lower volumes of contrast media while achieving the same CT values and even enabling lower contrast flow rates, which is especially helpful in patients with poor vascular access. Moreover, in suboptimal diagnostic cases caused by poor contrast opacification, the resolution can be improved, thus avoiding the need to repeat the study.

Radiological properties of nano-hydroxyapatite compared to natural equine hydroxyapatite quantified using dual-energy CT and high-field MR

In equine medicine, assisted bone regeneration, including use of biomaterial substitutes like hydroxyapatite (HAP), is crucial for addressing bone defects. To follow-up on the outcome of HAP-based bone defect treatment, the advancement in quantified diagnostic imaging protocols is needed. This study aimed to quantify and compare the radiological properties of the HAP graft and natural equine bone using Magnetic Resonance (MR) and Computed Tomography (CT), both Single (SECT) and Dual Energy (DECT). SECT and DECT, allow for the differentiation of three HAP grain sizes, by progressive increase in relative density (RD). SECT, DECT, and MR enable the differentiation between natural cortical bone and synthetic HAP graft by augmentation in Effective Z and material density (MD) in HAP/Water, Calcium/Water, and Water/Calcium reconstructions, alongside the reduction in T2 relaxation time. The proposed quantification provided valuable radiological insights into the composition of HAP grafts, which may be useful in follow-up bone defect treatment.

Abdominal image quality and dose reduction with energy-integrating or photon-counting detectors dual-source CT: A phantom study

PURPOSE

The purpose of this study was to assess image-quality and dose reduction potential using a photon-counting computed tomography (PCCT) system by comparison with two different dual-source CT (DSCT) systems using two phantoms.

MATERIALS AND METHODS

Acquisitions on phantoms were performed using two DSCT systems (DSCT1 [Somatom Force] and DSCT2 [Somatom Pro.Pulse]) and one PCCT system (Naeotom Alpha) at four dose levels (13/6/3.4/1.8 mGy). Noise power spectrum (NPS) and task-based transfer function (TTF) were computed to assess noise magnitude and noise texture and spatial resolution (f50), respectively. Detectability indexes (d') were computed to model the detection of abdominal lesions: one unenhanced high-contrast task, one contrast-enhanced high-contrast task and one unenhanced low-contrast task. Image quality was subjectively assessed on an anthropomorphic phantom by two radiologists.

RESULTS

For all dose levels, noise magnitude values were lower with PCCT than with DSCTs. For all CT systems, similar noise texture values were found at 13 and 6 mGy, but the greatest noise texture values were found for DSCT2 and the lowest for PCCT at 3.4 and 1.8 mGy. For high-contrast inserts, similar or lower f50 values were found with PCCT than with DSCT1 and the opposite pattern was found for the low-contrast insert. For the three simulated lesions, d' values were greater with PCCT than with DSCTs. Abdominal images were rated satisfactory for clinical use by the radiologists for all dose levels with PCCT and for 13 and 6 mGy with DSCTs.

CONCLUSION

By comparison with DSCTs, PCCT reduces image-noise and improves detectability of simulated abdominal lesions without altering the spatial resolution and image texture. Image-quality obtained with PCCT seem to indicate greater potential for dose optimization than those obtained with DSCTs.