SPECT Research Articles

Analisis Perbedaan Citra SPECT Non-AC dan CTAC pada Pemeriksaan Scintigrafi Perfusi Miokard

Background: Myocardial Perfusion Scan displays SPECT images, which is a non invasive imaging method for a quantitative view of myocardial ischemia which can’t be done with CT myocardial perfusion. The principle of myocardial perfusion scan is that the myocardial absorption of radiopharmaceuticals is proportional to coronary heart blood flow to the myocardium. The main problem with SPECT myocardial perfusion scan imaging is photon attenuation caused by soft tissue around the heart which causes inaccurate information and attenuation artifacts. One method to reduce attenuation artifacts is hybrid CT Scan imaging with SPECT tools. CT Scan images are used to correct attenuation in SPECT images. The purpose of this research is to analyze the differences between non-AC and CTAC SPECT images which will have an impact on myocardium perfusion values on myocardial perfusion scans.Methods: This research is a quantitative analysis with a direct observation approach. The research was undertaken at Nuclear Medicine and Molecular Theranostics Installation of Dr. Hasan Sadikin General Hospital in Bandung, starting November 2023 using a SPECT CT GE NM/CT 860 gamma camera. A total of 28 patients were examined for myocardial perfusion scans. Data processing is conducted by comparing the perfusion values of myocardium on non-AC and CTAC SPECT images for 28 samples by conducting hypothesis testing using paired test sample T-Test.Result: Based on the research results, non-AC, and CTAC SPECT image data showed a normal distribution using the Shapiro-Wilk test, allowing the analysis of differences using the Paired-Samples T-test. In general, the analysis results indicate a significant difference between non-AC and CTAC SPECT images, as the sig value is less than 0.05 in the RCA and LCx vascular segments, as well as in the septal, inferior, lateral, and apical wall segments. However, no significant differences were found in the LAD vascular segment and the anterior wall segment, as the sig value is greater than 0.05.Conclusions: There are differences between non-AC and CTAC SPECT images in the RCA and LCx blood vessel segments, as well as in the septal, inferior, lateral, and apical wall segments. However, no differences are observed in the LAD blood vessel segment and the anterior wall segment.

Determination of adequate bony resection margins in inflammatory jaw pathologies using SPECT-CT in primary mandibular reconstruction with virtually planned vascularized bone flaps

ObjectivesIn advanced stages of osteoradionecrosis, medication-related osteonecrosis of the jaw, and osteomyelitis, a resection of sections of the mandible may be unavoidable. The determination of adequate bony resection margins is a fundamental problem because bony resection margins cannot be secured intraoperatively. Single-photon emission computed tomography (SPECT-CT) is more accurate than conventional imaging techniques in detecting inflammatory jaw pathologies. The clinical benefit for virtual planning of mandibular resection and primary reconstruction with vascularized bone flaps has not yet been investigated. This study aimed to evaluate the determination of adequate bony resection margins using SPECT computed tomography (SPECT-CT) for primary microvascular reconstruction of the mandible in inflammatory jaw pathologies.Materials and methodsThe cases of 20 patients with inflammatory jaw pathologies who underwent primary microvascular mandibular reconstruction after the bony resection margins were determined with SPECT-CT were retrospectively analyzed. The bony resection margins determined by SPECT-CT were histologically validated. The sensitivity was calculated as the detection rate and the positive predictive value as the diagnostic precision. Radiological ossification of the vascularized bone flaps with the mandibular stumps was assessed at least 6 months after reconstruction. The clinical course was followed for 12 months.ResultsThe determination of adequate bony resection margins with SPECT-CT yielded a sensitivity of 100% and a positive predictive value of 94.7%. Of all the bony resection margins, 97.4% were radiologically sufficiently ossified with the vascularized bone flap and showed no complications in the clinical course.ConclusionsSPECT-CT could increase the probability of determining adequate bony resection margins.Clinical relevanceSPECT-CT could have a beneficial clinical impact in the context of primary microvascular bony reconstruction in inflammatory jaw pathologies.

Novel brain SPECT imaging unravels abnormal cerebral perfusion in patients with postural orthostatic tachycardia syndrome and cognitive dysfunction

Cognitive dysfunction is frequently reported in individuals with postural orthostatic tachycardia syndrome (POTS), possibly resulting from reduced cerebral blood flow (CBF). We used brain SPECT, an accessible imaging modality that has not been systematically evaluated in this patient group. Retrospective review of participants from our registry was undertaken to identify those who had a brain SPECT performed for investigation of cognitive dysfunction. Abnormal CBF was taken as z-score > 2 standard deviations of healthy control reference values. Patient reported outcome measures (PROMs) such as autonomic, gastric and quality of life symptom scores were analyzed. From a total of 56 participants (mean 34.8 ± 10.7 years, 88% females), PROMs indicate: moderate to severe autonomic dysfunction in 75%; at least mild to moderate gastroparesis in 23%; low global health rating and utility scores. Abnormal CBF was seen in 61% but did not differ by POTS triggers. The regions with the lowest mean z-scores were the lateral prefrontal and sensorimotor cortices. Hierarchal regression analyses found number of brain regions with abnormal CBF, autonomic and gastric symptoms to account for 51% of variances in health utility. Cerebral hypoperfusion is prevalent in those with POTS and cognitive dysfunction even whilst supine, contributing to reduced quality of life.

Combining Low-energy Images in Dual-energy Spectral CT With Deep Learning Image Reconstruction Algorithm to Improve Inferior Vena Cava Image Quality.

To explore the application of low-energy image in dual-energy spectral CT (DEsCT) combined with deep learning image reconstruction (DLIR) to improve inferior vena cava imaging. Thirty patients with inferior vena cava syndrome underwent contrast-enhanced upper abdominal CT with routine dose, and the 40, 50, 60, 70, and 80keV images in the delayed phase were first reconstructed with the ASiR-V40% algorithm. Image quality was evaluated both quantitatively [CT value, SD, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) for inferior vena cava] and qualitatively to select an optimal energy level with the best image quality. Then, the optimal-energy images were reconstructed again using deep learning image reconstruction medium strength (DLIR-M) and DLIR-H (high strength) algorithms and compared with that of ASiR-V40%. The objective CT value, SD, SNR, and CNR increased with the decrease in energy level, with statistically significant differences (all P<0.05). The 40keV images had the highest CT values, SNR, and CNR and good diagnostic acceptability, and 40keV was selected as the best energy level. Compared with ASiR-V40% and DLIR-M, DLIR-H had the lowest SD, highest SNR and CNR, and subjective score (all P<0.001) with good consistencies between the 2 physicians (all k ≥0.75). The 40keV images with DLIR-H had the highest overall image quality, showing sharper edges of inferior vena cava vessels and clearer lumen in patients with Budd-Chiari syndrome. Compared with the ASiR-V algorithm, DLIR-H significantly reduces image noise and provides the highest CNR and best diagnostic image quality for the 40keV DEsCT images in imaging inferior vena cava.

Assessing Pulmonary Embolisms on Unenhanced CT Images Using Electron Density Images Derived from Dual-Layer Spectral Detector CT: A Single-centre Prospective Study Conducted at the Emergency Department.

Aims To evaluate the utility of unenhanced spectral imaging, electron density (ED) and overlay electron density (OED) images for assessing pulmonary embolisms in patients with suspected or confirmed acute pulmonary embolism (APE). Background Multiple spectral images can be extrapolated from spectral detector CT (SDCT), ED and OED images. ED and OED images are highly sensitive to moisture-rich tissues. Potential use for detecting pulmonary artery thrombi in non-enhanced chest CT images. Objective To assess the sensitivity, specificity and accuracy of ED and OED images obtained using SDCT for the detection of pulmonary embolism on non-enhanced images. Method Seventy-nine patients who underwent unenhanced and CT pulmonary angiography using dual-layer spectral detector CT to evaluate APE between November 2021 and April 2022 were enrolled in this retrospective study. Based on unenhanced spectral and CTPA images, two radiologists identified areas of high density in the main, lobar, and segmental pulmonary arteries on ED and OED images and detected pulmonary embolism (PE) on enhanced images using a consultative approach. CTPA results were considered the gold standard. The diagnostic performance of ED and OED in detecting PE was analyzed. Results PE was detected in 40 patients (40/79), and 17, 69, and 20 PEs were detected in the main, lobar, and segmental arteries, respectively. The PE detection sensitivity on ED images was 69.7-94.7%, and the specificity was 58.5-98.2% for the individual, main, lobe, and segmental pulmonary arteries. The sensitivity and specificity for OED images were 94.1-95.2% and 80.0-98.1%, respectively. The positive predictive value (PPV) and negative predictive value (NPV) were 53.6-87.7% and 69.7-95.9% for ED images, and 48.5-88.9% and 94.1-98.9% for OED images, respectively. The accuracy was 76.0-98.9% and 87.3-96.2% when using ED and OED images, respectively. The research identified that whether main, lobar or segmental pulmonary arteries with blood clots, EDW values ranged from 108.1-108.8 %EDW, 3.9-4.2 %EDW higher than those of arteries without emboli. Pulmonary arteries with emboli standardised ED values were 103.6-104.3 %EDW. Conclusion ED and OED images using spectral CT without contrast media demonstrated high diagnostic performance and could improve the visualization of PE.

CT material decomposition with contrast agents: Single or multiple spectral photon-counting CT scans? A simulation study.

With the widespread introduction of dual energy computed tomography (DECT), applications utilizing the spectral information to perform material decomposition became available. Among these, a popular application is to decompose contrast-enhanced CT images into virtual non-contrast (VNC) or virtual non-iodine images and into iodine maps. In 2021, photon-counting CT (PCCT) was introduced, which is another spectral CT modality. It allows for scans with more than two different detected spectra. With these systems, it becomes possible to distinguish more than two materials. It is frequently proposed to administer more than one contrast agent, perform a single PCCT scan, and then calculate the VNC images and the contrast agent maps. This may not be optimal because the patient is injected with a material, only to have it computationally extracted again immediately afterwards by spectral CT. It may be better to do an unenhanced scan followed by one or more contrast-enhanced scans. The main argument for the spectral material decomposition is patient motion, which poses a significant challenge for approaches involving two or more temporally separated scans. In this work, we assume that we can correct for patient motion and thus are free to scan the patient more than once. Our goal is then to quantify the penalty for performing a single contrast-enhanced scan rather than a clever series of unenhanced and enhanced scans. In particular, we consider the impact on patient dose and imagequality. We simulate CT scans of three differently sized phantoms containing various contrast agents. We do this for a variety of tube voltage settings, a variety of patient-specific prefilter (PSP) thicknesses and a variety of threshold settings of the photon-counting detector with up to four energy bins. The reconstructed bin images give the expectation values of soft tissue and of the contrast agents. Error propagation of projection noise into the images yields the image noise. Dose is quantified using the total CT dose index (CTDI) value of the scans. When combining multiple scans, we further consider all possible tube current (or dose) ratios between the scans. Material decomposition is done image-based in a statistical optimal way. Error propagation into the material-specific images yields the signal-to-noise ratio at unit dose (SNRD). The winning scan strategy is the one with the highest total SNRD, which is related to the SNRD of the material that has the lowest signal-to-noise ratio (SNR) among the materials to decompose into. We consider scan strategies with up to three scans and up to three materials (water W, contrast agent X and contrast agent Y). In all cases, those scan strategies yield the best performance that combine differently enhanced scans, for example, W+WX, W+WXY, WX+WXY, W+WX+WY, with W denoting an unenhanced scan and WX, WY and WXY denoting X-, Y-, and X-Y-enhanced scans, respectively. The dose efficiency of scans with a single enhancement scheme, such as WX or WXY, is far lower. The dose penalty to pay for these single enhancement strategies is about two or greater. Our findings also apply to scans with a single energy bin and thus also to CT systems with conventional, energy-integrating detectors, that is, conventional DECT. Dual source CT (DSCT) scans are preferable over single source CT scans, also because one can use a PSP on the high Kilovolt spectrum to better separate the detected spectra. For the strategies and tasks considered here, it does not make sense to simultaneously scan with two different types of contrast agents. Iodine outperforms other high Z elements in nearly allcases. Given the significant dose penalty when performing only one contrast-enhanced scan rather than a series of unenhanced and enhanced scans, one should consider avoiding the single-scan strategies. This requires to invest in the development of accurate registration algorithms that can compensate for patient and contrast agent motion between separatescans.

Ultra-low dose dual-layer detector spectral CT for pulmonary nodule screening: image quality and diagnostic performance

ObjectivesTo investigate the image quality and diagnostic performance with ultra-low dose dual-layer detector spectral CT (DLSCT) by various reconstruction techniques for evaluation of pulmonary nodules.Materials and methodsBetween April 2023 and December 2023, patients with suspected pulmonary nodules were prospectively enrolled and underwent regular-dose chest CT (RDCT; 120 kVp/automatic tube current) and ultra-low dose CT (ULDCT; 100 kVp/10 mAs) on a DLSCT scanner. ULDCT was reconstructed with hybrid iterative reconstruction (HIR), electron density map (EDM), and virtual monoenergetic images at 40 keV and 70 keV. Quantitative and qualitative image analysis, nodule detectability, and Lung-RADS evaluation were compared using repeated one-way analysis of variance, Friedman test, and weighted kappa coefficient.ResultsA total of 249 participants (mean age ± standard deviation, 50.0 years ± 12.9; 126 male) with 637 lung nodules were included. ULDCT resulted in a significantly lower mean radiation dose than RDCT (0.3 mSv ± 0.0 vs. 3.6 mSv ± 0.8; p < 0.001). Compared with RDCT, ULDCT EDM showed significantly higher signal-noise-ratio (44.0 ± 77.2 vs. 4.6 ± 6.6; p < 0.001) and contrast-noise-ratio (26.7 ± 17.7 vs. 5.0 ± 4.4; p < 0.001) with qualitative scores ranked higher or equal to the average. Using the regular-dose images as a reference, ULDCT EDM images had a satisfactory nodule detection rate (84.6%) and good inter-observer agreements compared with RDCT (κw > 0.60).ConclusionUltra-low dose dual-layer detector CT with 91.2% radiation dose reduction achieves sufficient image quality and diagnostic performance of pulmonary nodules.Critical relevance statementDual-layer detector spectral CT enables substantial radiation dose reduction without impairing image quality for the follow-up of pulmonary nodules or lung cancer screening.Key PointsRadiation dose is a major concern for patients requiring pulmonary nodules CT screening.Ultra-low dose dual-layer detector spectral CT with 91.2% dose reduction demonstrated satisfactory performance.Dual-layer detector spectral CT has the potential for lung cancer screening and management.Graphical

Dual-energy CT in head and neck applications.

Dual-energy CT (DECT), also known as spectral CT, has advanced diagnostic capabilities in head and neck pathologies beyond those of conventional single-energy CT (SECT). By having images at two distinct energy levels, DECT generates virtual monoenergetic images (VMIs), iodine maps, and quantitative features such as iodine concentration (IC) and spectral Hounsfield unit attenuation curves (SHUAC), which leads to enhancing tissue characterization, reducing artifacts, and differentiating head and neck pathologies. This review highlights DECT's applications in evaluating head and neck squamous cell carcinoma (SCC), thyroid cartilage invasion, cervical lymph node metastasis, radiation therapy planning, post-treatment assessment, and role in other head and neck conditions, such as infection and sialolithiasis. Additionally, it explores emerging applications of DECT in radiomics and artificial intelligence. The review also discusses about integrating DECT into clinical practice requires overcoming workflow challenges and ensuring radiologist proficiency with its diverse image reconstructions. As DECT technology evolves, its integration promises to further enhance the efficacy of managing head and neck pathologies.

Enhancing photon-counting computed tomography reconstruction via subspace dictionary learning and spatial sparsity regularization.

Photon-counting computed tomography (CT) is an advanced imaging technique that enables multi-energy imaging from a single scan. However, the limited photon count assigned to narrow energy bins leads to increased quantum noise in the reconstructed spectral images. To address this issue, leveraging the prior information in the spectral images is essential. This study aimed to develop an efficient algorithm that enhances image reconstruction quality by reducing noise levels and preserving image details. To improve image reconstruction quality for photon-counting CT, we propose an algorithm based on the subspace-assisted multi-prior information, including global, nonlocal, and local priors, for spectral CT reconstruction. Specifically, the algorithm first maps spectral CT images, which exhibit global low-rank characteristics, to low-dimensional eigenimages using subspace decomposition. Then, similar image patches are extracted based on the manifold structure distance from highly correlated eigenimages in both spectral and spatial domains. These patches are stacked to form a nonlocal full-channel tensor group. Subsequently, non-convex structural sparsity is applied to this tensor group through adaptive dictionary learning, exploiting nonlocal similarity. Finally, the alternating direction method of multipliers (ADMM) is applied to solve the optimization model iteratively. The simulated walnut and real mouse data were applied to validate the effectiveness of the proposed method. In the simulation experiments, the proposed method reduced the root mean square error (RMSE) by 87.74%, 86.88%, 67.01%, 46.42%, and 13.51% compared to the respective state-of-the-art five comparison methods. The time taken for one iteration of the proposed algorithm was as low as 32.57 seconds, which was 92.07% less than framelet tensor nuclear norm [framelet tensor sparsity with block-matching method (FTNN)] method and 74.13% less than total variation regularization [tensor nonlocal similarity and local TV sparsity method (ITS_TV)] method, the other two tensor block-matching (BM)-based comparison methods. The material decomposition results in real mouse data further validated the accuracy of the proposed method for different materials. The experimental results indicate that the proposed algorithm effectively reduces computational costs while improving the accuracy of image reconstruction and material decomposition, showing promising advantages over the compared method.

Quantitative assessment of early changes in myocardial extracellular volume during postoperative adjuvant chemotherapy in patients with breast cancer via dual-layer spectral detector computed tomography: a cohort study.

The major of anticancer therapies induce a wide spectrum of cardiotoxic effects. Early identification of anticancer treatment-associated cardiotoxicity is critical to informing decisions on subsequent interventions. Myocardial extracellular volume (ECV) has been proposed as a useful parameter for quantifying the early cardiotoxicity of cancer-related treatment. This study used dual-layer spectral detector computed tomography (CT) technology to simultaneously assess cardiac function and myocardial ECV, characterizing the early changes in parameters during breast cancer therapy. A single-center cohort study was conducted that prospectively enrolled 40 women with breast cancer (mean age 47.5±10.8 years) who underwent postoperative adjuvant chemotherapy between January 12, 2022, and November 2, 2023, with available data from baseline to 3 months after chemotherapy of cardiac computed tomography (CCT), ultrasound cardiography (UCG), electrocardiography, and serum biomarkers. Midventricular and global ECVs of the left ventricle were measured based on an iodine map of the late enhancement phase of dual-layer spectral detector CT. Changes in cardiac function parameters, ECVs, and cardiac biomarkers from baseline to the 3-month follow-up were analyzed. Correlation coefficients between the changes in cardiac function parameters and ECVs were calculated. Between baseline and 3 months, there was no significant change in left ventricular ejection fraction (LVEF) on UCG (67.1%±3.8% vs. 66.3%±4.3%, P=0.29) or LVEF on CCT (65.4%±5.9% vs. 64.3%±7.4%, P=0.28). Heart rate increased over 3 months of follow-up (75.2±11.5 vs. 81.7±12.3 bpm; P<0.01). After normalization to body surface area (BSA), cardiac output on CCT/BSA ratio (CCT-CO indexed) (3.5±0.6 vs. 3.8±0.6 L/(min·m2); P=0.01) and left ventricular late (active) filling volume/BSA ratio (LVLFV indexed) (13.5±3.7 vs. 15.8±4.2 mL/m2; P<0.01) significantly increased, while there was a significant decrease at the 3-month follow-up in left ventricular early (passive) filling volume/BSA ratio (LVEFV indexed) (33.3±6.6 vs. 30.6±8.2 mL/m2; P=0.01) and LVEFV/LVLFV ratio (2.7±1.1 vs. 2.1±0.9; P<0.01). Midventricular and global ECVs were elevated at 3 months, significantly so for the midanterior ECV (24.0%±4.5% vs. 25.6%±3.1%; P=0.04), midaverage ECV (25.6%±2.5% vs. 27.0%±2.9%; P=0.01) and global ECV (25.4%±2.4% vs. 27.3%±2.7%; P<0.01). Although changes in ECVs were not associated with changes in LVEFs, global ECV changes were moderately correlated with changes in left ventricular end-diastolic volume/BSA ratio (CCT-LVEDV indexed) (r=0.52; P<0.001), left ventricular stroke volume/BSA ratio (CCT-LVSV indexed) (r=0.56; P<0.001), CCT-CO indexed (r=0.40; P=0.01), and LVEFV indexed (r=0.41; P=0.009). CCT-derived ECV was used to evaluate myocardial changes in the early stage of chemotherapy before LVEF significantly decreased. The increases in ECV were not correlated with LVEF. The changes in myocardial ECVs were moderately correlated with cardiac function parameters. ECV may be a useful biomarker for detecting cardiotoxicity in patients with breast cancer in the early stage of anticancer therapy.

A Nomogram Based on Laboratory Data, Inflammatory Bowel Disease Questionnaire and CT Enterography for Activity Evaluation in Crohn's Disease.

Accurately assessing the activity of Crohn's disease (CD) is crucial for determining prognosis and guiding treatment strategies for CD patients. This study aimed to develop and validate a nomogram for assessing CD activity. The semi-automatic segmentation method and PyRadiomics software were employed to segment and extract radiomics features from the spectral CT enterography images of lesions in 107 CD patients. The radiomic score (rad-score) was calculated using the radiomic signature formula. Multivariate logistic regression analysis identified the independent risk factors of erythrocyte sedimentation rate, fecal calprotectin, and Inflammatory Bowel Disease Questionnaire (IBDQ), and a nomogram was constructed in combination with rad-score. The nomogram underwent evaluation and testing in the training set (n = 84) and validation set (n = 23), respectively. The discrimination performance of the combined (AUC 0.877) was marginally superior to that of IBDQ + clinical (AUC 0.854). However, there was no significant difference in AUC between the two models in the validation set (P = 0.206). IBDQ + clinical outperformed clinical (AUC 0.808), clinical outperformed IBDQ (AUC 0.746), and IBDQ outperformed radiomic signature (AUC 0.688). Significant differences in AUC were observed between the two models (radiomic signature vs clinical, P = 0.026; radiomic signature vs IBDQ + clinical, P = 0.011; radiomic signature vs combined, P = 0.008; in the validation set). The nomogram, combined with laboratory data, IBDQ and rad-score, presents an accurate and reliable method for assessing CD activity. The nomogram enhances the potential for personalized treatment plans and better disease management, making it a valuable tool for clinical practice.

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

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). 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. 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). 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. 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.

Impact of image formation factors on material discrimination in spectral CT

Objective.The accuracy of material decomposition in spectral computed tomography (CT) depends on the information quality captured in image acquisition, a factor that cannot be adequately assessed using conventional image quality metrologies due to the multi-energy nature of spectral CT. This work used metrologies specific to spectral CT to evaluate the impact of acquisition conditions on the quality of spectral CT images and accuracy of material decomposition techniques.Approach.Computational phantoms were created with cylindrical shapes and variable sizes (20-40 cm), containing inserts of iodine and gadolinium (1-8 mg ml-1). The phantoms were imaged using a validated CT simulator modeling a clinical photon-counting CT scanner. The acquisitions were done at different detector energy thresholds (50-90 keV) and tube currents (25-250 mAs). The images were used to develop and train a data-driven material identification and quantification algorithm. Two spectral metrologies, multivariate contrast-to-noise ratio (CNR) and separability index, were used to characterize the impact of energy threshold, tube current, phantom size, and material concentration on signal quality. The results were interpreted in terms of figures of merit of accuracy for classification and mean absolute error (MAE) and root mean squared error (RMSE) for regression.Main results. Signal quality for iodine and gadolinium was maximized with a low energy threshold, high tube current, and small phantom size. While conventional CNR terms predicted variable image quality for two-thirds of all conditions, multivariate CNR was above 10 for half of those. Separability index showed that for a phantom size greater than 30 cm, a minimum of 75-110 mAs is required to separate 2 mg ml-1of iodine and gadolinium. For both classification and regression tasks, a random forest model with a local statistics dataset provided the best performance. Across conditions, classification performance was 0.66-0.99 for I accuracy, 0.72-0.99 for Gd accuracy. Regression performance was 0.02-0.91 mg ml-1I and 0.02-0.59 mg ml-1Gd for MAE and 0.11-1.08 mg ml-1I and 0.07-0.76 mg ml-1Gd for RMSE.Significance.Multivariate CNR and separability index metrologies can predict material decomposition performance. Theses metrics demonstrated that the decomposition of iodine and gadolinium have higher separability when the acquisition is done at a lower energy threshold, with a higher tube current, and when the imaged object has a smaller size. Object size had the largest impact on metrics and decomposition performance.

The clinical applications of dual-layer spectral detector CT in digestive system diseases.

Dual-layer spectral detector CT (DLCT) has several advantages in clinical practice, this study aims to reveal the clinical applications of DLCT in digestive system diseases. We searched PubMed and Cochrane Reviews for articles published from January 1, 2010 to May 31, 2024, using the terms "dual-layer spectral detector CT" or "dual-layer CT" combined with "hepatic fat" or "hepatic fibrosis" "hepatocellular carcinoma" or "pancreatic ductal adenocarcinoma" or "pancreatic neuroendocrine tumors" or "gastric cancer" or "colorectal cancer" or "Crohn's disease" or "bowel ischemia" or "acute abdominal conditions". DLCT consists of a top layer sensitive to lower-energy photons and a bottom layer sensitive to higher-energy photons. This configuration enables simultaneous acquisition of two energy spectra from a single X-ray beam ensuring consistent spatial alignment and temporal resolution. Spectral raw images allow image post-processing to improve image quality, reduce radiation doses and contrast media doses, and generate multiple quantitative parameters. It has broad potential for early detection, accurate staging, efficacy assessment, and prognosis prediction of liver, pancreatic, and gastrointestinal diseases, as well as for the assessment of digestive system vasculature. DLCT not only provides valuable information for the clinical diagnosis and therapeutic effect evaluation of digestive system diseases but also may play a more important role in the overall management of digestive diseases and in the decision-making of individualized medicine. Question What are the advantages of DLCT compared to traditional single-energy CT in the early detection, staging, and therapeutic evaluation of digestive system diseases? Findings DLCT enhances image quality, improves tissue characterization, and allows for multi-parametric analysis, making it superior in detecting and evaluating liver, pancreatic, and gastrointestinal diseases. Clinical relevance DLCT provides high-quality, multi-parametric imaging that improves the accuracy of diagnosing digestive diseases, facilitates more precise treatment planning, and enhances monitoring of treatment response, ultimately contributing to better patient management and prognosis.

In vivo temperature mapping during CT-guided thermal ablations: proof of feasibility using spectral CT.

In vivo temperature mapping during CT-guided thermal ablations: proof of feasibility using spectral CT.

Radiomics based on dual-layer spectral detector CT for predicting EGFR mutation status in non-small cell lung cancer.

To explore the value of dual-layer spectral computed tomography (DLCT)-based radiomics for predicting epidermal growth factor receptor (EGFR) mutation status in patients with non-small cell lung cancer (NSCLC). DLCT images and clinical information from 115 patients with NSCLC were collected retrospectively and randomly assigned to a training group (n=81) and a validation group (n=34). A radiomics model was constructed based on the DLCT radiomic features by least absolute shrinkage and selection operator (LASSO) dimensionality reduction. A clinical model based on clinical and CT features was established. A nomogram was built combining the radiomic scores (Radscores) and clinical factors. Receiver operating characteristic (ROC) analysis and decision curve analysis (DCA) were used for the efficacy and clinical value of the models assessment. A total of six radiomic features and two clinical features were screened for modeling. The AUCs of the radiomic model, clinical model, and nomogram were 0.909, 0.797, and 0.922, respectively, in the training group and 0.874, 0.691, and 0.881, respectively, in the validation group. The AUCs of the nomogram and the radiomics model were significantly higher than that of the clinical model, but no significant difference was found between them. DCA revealed that nomogram had the greatest clinical benefit at most threshold intervals. Nomogram integrating clinical factors and pretreatment DLCT radiomic features can help evaluate the EGFR mutation status of patients with NSCLC in a noninvasive way.

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

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). 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. 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). 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. 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 imagingand ultra-high spatial resolution, SPCCT enhances coronary artery assessment, potentially leading to more accurate diagnoses and better patient outcomes in cardiovascular imaging.

Nanoparticles with "K-edge" Metals Bring "Color" in Multiscale Spectral Photon Counting X-ray Imaging.

Preclinical and clinical diagnostics depend greatly on medical imaging, which enables the identification of physiological and pathological processes in living subjects. It is often necessary to use contrast agents to complement anatomical data with functional information or to describe the disease phenotypically. Nanomaterials are used as contrast agents in many advanced bioimaging techniques and applications because of their high payload, physicochemical properties, improved sensitivity, and multimodality. Metals with k-edge energy within the X-ray bandwidth respond to photon counting and spectral X-ray imaging. This Perspective examines the progress made in the emerging area of nanoparticle-based k-edge contrast agents. These nano "k-edge" particles have been explored with spectral photon counting CT (SPCCT) for multiplexed molecular imaging, pushing the boundaries of resolution and capabilities of CT imaging. Design considerations, contrast properties, and biological behavior are discussed in detail. The key applications are highlighted by categorizing these nanomaterials based on their X-ray, k-edge energy, and biological properties, as well as their synthesis, functionalization, and characterization processes. The article delves into the transformative impact of nano "k-edge" particles on early disease detection and other biomedical applications. The review provides further insights into how the "k-edge signatures" of these nanoparticles combined with photon counting technique can be leveraged for quantitative, multicontrast imaging of diseases. We also discuss the status quo of clinically approved nanoparticles for imaging and highlight the challenges such as toxicity and clearance as well as promising clinical perspectives, providing a balanced view of the potential and limitations of these nanomaterials. Furthermore, we discuss the necessary future research efforts required to clinically translate nano "k-edge" particles as SPCCT contrast agents for early disease diagnosis and tracking.

SOUL-Net: A Sparse and Low-Rank Unrolling Network for Spectral CT Image Reconstruction.

Spectral computed tomography (CT) is an emerging technology, that generates a multienergy attenuation map for the interior of an object and extends the traditional image volume into a 4-D form. Compared with traditional CT based on energy-integrating detectors, spectral CT can make full use of spectral information, resulting in high resolution and providing accurate material quantification. Numerous model-based iterative reconstruction methods have been proposed for spectral CT reconstruction. However, these methods usually suffer from difficulties such as laborious parameter selection and expensive computational costs. In addition, due to the image similarity of different energy bins, spectral CT usually implies a strong low-rank prior, which has been widely adopted in current iterative reconstruction models. Singular value thresholding (SVT) is an effective algorithm to solve the low-rank constrained model. However, the SVT method requires a manual selection of thresholds, which may lead to suboptimal results. To relieve these problems, in this article, we propose a sparse and low-rank unrolling network (SOUL-Net) for spectral CT image reconstruction, that learns the parameters and thresholds in a data-driven manner. Furthermore, a Taylor expansion-based neural network backpropagation method is introduced to improve the numerical stability. The qualitative and quantitative results demonstrate that the proposed method outperforms several representative state-of-the-art algorithms in terms of detail preservation and artifact reduction.

Therapeutic Efficacy of Persimmon Leaf Flavonoids Extract in Ischemic Cerebrovascular Disease

In this research, the effects of persimmon leaf extract in treating ischemic cerebrovascular disease (ICVD) were analyzed, and the therapeutic outcomes were evaluated using techniques such as computed tomography (CT) angiography. Firstly, the impact of extraction conditions on the yield of flavonoids from persimmon leaves was assessed, and their scavenging rates (SRs) against three types of free radicals (DPPH, hydroxyl, and superoxide anion) were measured. Subsequently, 80 patients with ICVD were enrolled. Before treatment, patients’ carotid artery atherosclerotic plaque composition was evaluated using gemstone spectral CT, and the effects of conventional therapy (Ctrl group) were compared with those of treatment using persimmon leaf extract (Test group) on the patients’ blood lipids (BLs), blood glucose (BG) levels, hemorheology, hemodynamics, and CT angiography/perfusion imaging characteristics. Additionally, the post-treatment recurrence rate was recorded. The results revealed that the solvent concentration, ultrasonic power, temperature, time, and solid-liquid ratio markedly influenced the yield of persimmon leaf extract. Furthermore, the persimmon leaf extract demonstrated remarkable efficacy in scavenging three types of free radicals, namely DPPH, hydroxyl, and superoxide anion. The clinical results demonstrated that the main components of carotid artery plaque in ICVD patients were lipids, fibrous matrix, and hemorrhage, and the spectral curve combined with CT values accurately differentiated these plaque components. Patients in Test group exhibited notable improvements versus Ctrl group (P &lt;0.05) in their serum lipid profiles (reduced total cholesterol (TC), triglyceride (TG), and high-density lipoprotein cholesterol (HDL-C) levels, increased low-density lipoprotein cholesterol (LDL-C) levels), BG levels (decreased fasting BG (FBG), glycosylated hemoglobin (HbA1c), and postprandial 2-hour BG (2h-PG) levels), hemorheological parameters (decreased low-shear whole blood viscosity (LSBV), high-shear whole blood viscosity (HSBV), blood viscosity (PV), packed cell volume (PCV), platelet adhesion rate (PAR), and fibrinogen (FIB) levels), transcranial Doppler ultrasound parameters (increased mean blood flow velocity (Vm), peak systolic velocity (PSV), and end-diastolic velocity (EDV) of middle cerebral artery (CA), anterior CA, and basilar artery), and CT angiography with perfusion imaging parameters (increased cerebral blood flow (rCBF) and region cerebral blood volume (rCBV), shortened time to peak (TTP)). Additionally, recurrence rates of transient ischemic attack and cerebral infarction were lower in Test group compared to Ctrl group. In summary, the findings suggest that persimmon leaf extract possesses potent antioxidant properties. Spectral CT can identify and distinguish carotid artery plaque components. Furthermore, persimmon leaf extract effectively improved blood lipids, blood pressure, hemorheology, hemodynamics, and cerebral perfusion status, thereby reducing the risk of recurrence in ICVD.