Comparative assessment of qualitative and quantitative perfusion with dual-energy CT and planar and SPECT-CT V/Q scanning in patients with chronic thromboembolic pulmonary hypertension

Background

The purpose of this study was to compare the qualitative and quantitative assessment of perfusion on dual-energy CT (DECT) and planar and single photon emission computed tomography (SPECT)-CT V/Q scanning in patients with chronic thromboembolic pulmonary hypertension (CTEPH).

Methods

Nineteen patients with known CTEPH underwent both DECT and SPECT-CT V/Q scanning. Sixteen of these patients underwent planar V/Q imaging concurrently. Two readers independently graded DECT-perfused blood volume (PBV) defects on a four-point scale (0= normal, 1= mild <25%, 2= moderate 25-50%, 3= severe >50%). A grade was given for each lung lobe and for each of 18 lung segments. One reader graded the SPECT-CT images similarly. Quantitative measurements of lung perfusion were calculated with DECT and planar V/Q scanning for 16 of these patients.

Results

The inter-reader agreement on DECT was strong with agreement in 85% (258/304) of segments (kappa =0.86) and 84% (80/95) of lobes (kappa =0.82). The inter-modality agreement between DECT and SPECT-CT was lower. Readers 1 and 3 agreed in only 34% (103/304) of segments (kappa =0.25) and 33% (31/94) of lobes (kappa =0.22). Agreement between readers 2 and 3 was similar. Correlation between quantitative measurements with DECT and planar V/Q imaging was poor and ranged from 0.01 to 0.45.

Conclusions

Inter-observer agreement in subjective grading of PBV maps is excellent. However, inter-modality agreement between DECT and SPECT-CT is modest. Automated quantification values of PBV maps correlate poorly with established tools like planar V/Q imaging. These differences need to be kept in mind during clinical decision making.

Early diagnosis and prediction of intracranial hemorrhage using dual-energy computed tomography after mechanical thrombectomy in patients with acute ischemic stroke

PURPOSE

This study assesses the clinical value of dual-energy computed tomography (DECT) in the early diagnosis of intracranial hemorrhage and evaluates the risk of hemorrhagic transformation in patients with acute ischemic stroke (AIS) after mechanical thrombectomy.

METHODS

Patients with AIS who have undergone thrombectomy with Solitaire stent and DECT within one hour after surgery were prospectively enrolled. Linear mixed energy images, virtual non-contrast (VNC) image, and iodine overlay map (IOM) were obtained. Routine CT scan was performed 24 h postoperatively. The sensitivity, specificity, positive and negative predictive values, and accuracy of DECT in the early diagnosis of intracranial hemorrhage was evaluated. The iodine concentration of intracranial lesions was measured by IOM with the follow-up results taken as reference. Receiver operating characteristic (ROC) analysis was performed to obtain the threshold of hemorrhagic transformation and increased bleeding.

RESULTS

Among the 44 patients enrolled in this study, 25 (56.8 %) were diagnosed with simple extravasation of iodinated contrast agent, and 19 (43.2 %) showed intracranial hemorrhage in DECT. Compared with the follow-up CT 24 h after surgery, early diagnosis of postoperative intracranial hemorrhage using DECT demonstrated a sensitivity of 90.5 %, specificity of 100 %, positive predictive rate of 100 %, negative predictive rate of 92.0 %, and accuracy of 95.5 %. Among the 86 intracranial lesions that underwent iodine concentration measurement, 19 were diagnosed with hemorrhagic transformation or increased bleeding, and 67 were diagnosed without the aforementioned conditions. The sensitivity and specificity for differentiating the two groups were 73.7 % and 92.5 %, respectively, with a cut-off value of 2.7 mg/mL.

CONCLUSION

DECT is clinically valuable in early diagnosis and prediction of intracranial hemorrhage after mechanical thrombectomy in AIS patients.

Ultrasound scans and dual energy CT identify tendons as preferred anatomical location of MSU crystal depositions in gouty joints

OBJECTIVE

The present study was performed to localize the articular deposition of monosodium urate (MSU) crystal in joints. We compare the detection efficiencies of dual-energy CT (DECT) and ultrasound scans.

METHODS

Analyses by DECT and ultrasound were performed with 184 bilateral joints of the lower limbs of 54 consecutive gout patients. All joints were categorized into (1) knee, (2) ankle, (3) MTP1, and (4) MTP2, and sorted into those with and those without detectable MSU deposition. The comparison of the positive rate between DECT and ultrasound and the agreement was performed using the McNemar test and the Cohen's κ coefficient, respectively. Next, we listed the MSU crystal deposition as assessed by ultrasound between the DECT-positive and -negative joints according to their interior structure. We included tendons, synovia, cartilage, subcutaneous tissue, etc. RESULTS: Among all joints, the percentages with MSU crystal deposition detected by DECT (99/184, 53.8%) and ultrasound (106/184, 57.6%) were comparable (P = 0.530 > 0.05). For MTP1 (21/34, 61.8%; 12/34, 35.3%; P < 0.05) and MTP2-5 (17/34, 50.0%; 10/34, 29.4%, P < 0.05), ultrasound and DECT were more efficient, respectively. The data concordance in 46 of 50 joints (92.00%; κ = 0.769, P < 0.05) for knee; and 27 of 34 joints (79.41%; κ = 0.588, P < 0.05) for MTP2-5 and suggested that tendons were the most frequent anatomical location of MSU crystal deposition.

CONCLUSIONS

The tendons are the most frequent anatomical location of MSU crystal depositions. The concordance rate of knee joints and MTP2-5 joints shows good agreement between DECT and ultrasound depending on the location.

One half-scan dual-energy CT imaging using the Dual-domain Dual-way Estimated Network (DoDa-Net) model

BACKGROUND

Compared with single-energy computed tomography (CT), dual-energy CT (DECT) can distinguish materials better. However, most DECT reconstruction theories require two full-scan projection datasets of different energies, and this requirement is hard to meet, especially for cases where a physical blockage disables a full circular rotation. Thus, it is critical to relax the requirements of data acquisition to promote the application of DECT.

METHODS

A flexible one half-scan DECT scheme is proposed, which acquires two projection datasets on two-quarter arcs (one for each energy). The limited-angle problem of the one half-scan DECT scheme can be solved by a reconstruction method. Thus, a dual-domain dual-way estimation network called DoDa-Net is proposed by utilizing the ability of deep learning in non-linear mapping. Specifically, the dual-way mapping Generative Adversarial Network (DM-GAN) was first designed to mine the relationship between two different energy projection data. Two half-scan projection datasets were obtained, the data of which was twice that of the original projection dataset. Furthermore, the data transformation from the projection domain to the image domain was realized by the total variation (TV)-based method. In addition, the image processing network (Im-Net) was employed to optimize the image domain data.

RESULTS

The proposed method was applied to a digital phantom and real anthropomorphic head phantom data to verify its effectiveness. The reconstruction results of the real data are encouraging and prove the proposed method's ability to suppress noise while preserving image details. Also, the experiments conducted on simulated data show that the proposed method obtains the closest results to the ground truth among the comparison methods. For low- and high-energy reconstruction, the peak signal-to-noise ratio (PSNR) of the proposed method is as high as 40.3899 and 40.5573 dB, while the PSNR of other methods is lower than 36.5200 dB. Compared with FBP, TV, and other GAN-based methods, the proposed method reduces root mean square error (RMSE) by, respectively, 0.0124, 0.0037, and 0.0016 for low-energy reconstruction, and 0.0102, 0.0028, and 0.0015 for high-energy reconstruction.

CONCLUSIONS

The developed DoDa-Net model for the proposed one half-scan DECT scheme consists of two stages. In stage one, DM-GAN is used to realize the dual map of projection data. In stage two, the TV-based method is employed to transform the data from the projection domain to the image domain. Furthermore, the reconstructed image is processed by the Im-Net. According to the experimental results of qualitative and quantitative evaluation, the proposed method has advantages in detail preservation, indicating the potential of the proposed method in one half-scan DECT reconstruction.

Establishment of a novel system for the preoperative prediction of adherent perinephric fat (APF) occurrence based on a multi-mode and multi-parameter analysis of dual-energy CT

Background

Adherent perinephric fat (APF) is evaluated preoperatively with the Mayo adhesive probability (MAP) scoring system using conventional single-form computed tomography (CT) images. An objective or quantitative indicator for predicting APF is urgently needed for clinical application.

Methods

A total of 150 patients with renal tumours who underwent laparoscopic partial nephrectomy (LPN) were retrospectively enrolled and divided into the APF group (n=100) and the non-APF group (n=50) according to surgical results. All patients underwent a renal contrast-enhanced dual-energy CT (DECT) scan. The obtained CT DICOM data were transmitted to the DECT post-processing workstation and adopted virtual non-contrast (VNC), Rho/Z Maps, and Monoenergetic Plus (mono+) modes separately to undergo a multi-parameter analysis. A logistic stepwise investigation was utilized to analyse the related risk factors. The cutoff value was determined by the Youden index. Fifty patients were prospectively enrolled to validate the constructed model. The area under the curve (AUC), sensitivity, specificity and accuracy of the model were calculated.

Results

The study demonstrated that age, sex, body mass index (BMI), smoking status, tumour diameter, exophytic status, degree of malignancy and posterior perinephric fat thickness were related to the occurrence of APF (P<0.05). Model 1 was selected with the contrast material (CM) parameter (cutoff point 0.5), model 2 was selected with the effective atomic number (Z_eff) parameter (cutoff point 6.5), and model 3 was selected with the slope K (K) parameter (cutoff point -0.95). The AUC, sensitivity, specificity and accuracy of model 1 were 0.94, 0.94, 0.93 and 0.94, respectively; for model 2, they were 0.94, 0.93, 0.93 and 0.96, respectively; and for model 3, they were 0.92, 0.92, 0.93 and 0.92, respectively.

Conclusions

Multi-mode and multi-parameter models of DECT can effectively be used to predict the occurrence of APF.

Diagnostic accuracy of dual-energy CT virtual non-calcium images with different related contrast material values for the detection of bone marrow edema in knee

PURPOSE

The purpose of this study was to evaluate the diagnostic accuracy of different related contrast material (Rel.CM) values in dual-energy computed tomography (DECT) virtual non-calcium (VNCa) images for the detection of bone marrow edema (BME) in knee.

METHOD

This prospective study was approved by the institutional research ethics board, and written informed consent was obtained from all participants. Twenty-three patients (24 knees) who underwent dual-energy CT and MRI within three weeks from July 2018 to June 2019 with a definite history of trauma were enrolled. Each knee was divided into 12 regions. First, MR images served as the reference standard, Receiver operating characteristic (ROC) curve was used and diagnostic accuracy of VNCa images corresponding to different Rel.CM values (1.25, 1.35, 1.45, 1.55, 1.65, 1.75) were analyzed, aimed to select an optimal Rel.CM value of VNCa images for detecting BME. Then, CT values of the normal areas and BME areas were measured on the VNCa images corresponding to the optimal Rel.CM value for preliminary quantitative analysis. The rank-sum test was used to compare the differences of CT values between BME areas and normal bone marrow areas on the VNCa images.

RESULTS

The 24 knees were divided into 288 areas. MR Imaging showed BME in 121 areas. The areas under the ROC curve with different Rel.CM values (1.25, 1.35, 1.45, 1.55, 1.65, and 1.75) were 0.633, 0.674, 0.882, 0.684, 0.651, and 0.649, respectively. On the VNCa images of Rel.CM = 1.45, the diagnostic accuracy was the highest (up to 89.2 %), the CT values of the BME area and the normal area were -67.9 (1.7∼-100.1) HU and -94.5 (-69.7∼-144.9) HU, respectively, with statistical significance (Z=-9.804, P < 0.05).

CONCLUSIONS

The VNCa images with a Rel.CM value of 1.45 is optimal for the detection of BME in knee.

Pediatric Applications of Dual-Energy Computed Tomography

There is renewed interest in novel pediatric dual-energy computed tomography (DECT) applications that can image awake patients faster and at low radiation doses. DECT enables the simultaneous acquisition of 2 data sets at different energy levels, allowing for better material characterization and unique image reconstructions that enhance image analysis and provide quantitative and qualitative information about tissue composition. Pediatric DECT reduces radiation doses further while accelerating image acquisition and improving motion robustness. Current applications include the improved evaluation of congenital and acquired cardiovascular anomalies, lung perfusion and ventilation, renal stone composition, tumor extension and treatment response, and gastrointestinal diseases.

CT in musculoskeletal imaging: still helpful and for what?

Computed tomography (CT) is a common modality employed for musculoskeletal imaging. Conventional CT techniques are useful for the assessment of trauma in detection, characterization and surgical planning of complex fractures. CT arthrography can depict internal derangement lesions and impact medical decision making of orthopedic providers. In oncology, CT can have a role in the characterization of bone tumors and may elucidate soft tissue mineralization patterns. Several advances in CT technology have led to a variety of acquisition techniques with distinct clinical applications. These include four-dimensional CT, which allows examination of joints during motion; cone-beam CT, which allows examination during physiological weight-bearing conditions; dual-energy CT, which allows material decomposition useful in musculoskeletal deposition disorders (e.g., gout) and bone marrow edema detection; and photon-counting CT, which provides increased spatial resolution, decreased radiation, and material decomposition compared to standard multi-detector CT systems due to its ability to directly translate X-ray photon energies into electrical signals. Advanced acquisition techniques provide higher spatial resolution scans capable of enhanced bony microarchitecture and bone mineral density assessment. Together, these CT acquisition techniques will continue to play a substantial role in the practices of orthopedics, rheumatology, metabolic bone, oncology, and interventional radiology.

Systematic Review on Learning-based Spectral CT

Spectral computed tomography (CT) has recently emerged as an advanced version of medical CT and significantly improves conventional (single-energy) CT. Spectral CT has two main forms: dual-energy computed tomography (DECT) and photon-counting computed tomography (PCCT), which offer image improvement, material decomposition, and feature quantification relative to conventional CT. However, the inherent challenges of spectral CT, evidenced by data and image artifacts, remain a bottleneck for clinical applications. To address these problems, machine learning techniques have been widely applied to spectral CT. In this review, we present the state-of-the-art data-driven techniques for spectral CT.

Concordance of Ultrasound and Dual-Energy CT in Diagnosing Gouty Arthritis in the Knee Joint: A Retrospective Observational Study

RATIONALE AND OBJECTIVES

To assess the consistency between ultrasound and dual-energy computed tomography (DECT) for the diagnosis of gout in the knee joint.

MATERIALS AND METHODS

The ultrasound and DECT images of 176 knee joints from 167 patients diagnosed with gout at the Gout Specialty Clinic of Qingdao University Affiliated Hospital from February 2022 to December 2023 were retrospectively analyzed. The knee joint was segmented into five anatomical regions: intra-articular, anterior, posterior, medial, and lateral. The location of monosodium urate (MSU) crystal deposition was recorded. Tophi were classified as hypoechogenic, isoechogenic, hyperechogenic, or strongly echogenic. The Kappa test was used to assess the consistency between the two examination methods in different regions of the knee joint. The McNemar chi-square test was utilized to conduct a differential analysis between the DECT and ultrasound results. The chi-square test was used to assess differences in the rate of tophi detection with different echogenicities by DECT. Pearson's correlation coefficient was used to assess the correlation between MSU crystal deposition volume and clinically relevant indicators.

RESULTS

Double contour (61.4%) was the most common intra-articular ultrasound sign. In the extra-articular region, MSU crystals were commonly deposited in and around the popliteal groove region (ultrasound: 52.3%; DECT: 60.0%). Corresponding MSU deposits on DECT were found in 7 of 54 joints with aggregates detected on ultrasound, and in 15 of 108 joints with DC. Tophi with hyperechogenicity or strong echogenicity were more likely to be detected on DECT than those with hypoechoic or isoechoic features (84.3% and 90.9% vs. 55.1% and 27.8%, respectively). For the assessment of MSU deposits, ultrasound showed an overall higher positive rate than DECT (81.1% vs. 72.2%), with poor consistency between the two examinations (κ = 0.177). In distinct anatomical regions, ultrasound and DECT showed high consistency in the medial (κ = 0.651) and lateral (κ = 0.705) views, with no significant difference. The intra-articular (κ = 0.316) and anterior (κ = 0.346) regions exhibited only fair consistency, with statistically significant diagnostic differences. When exclusively assessing cases with tophi, ultrasound and DECT demonstrated similar consistency in the medial, lateral and anterior views (κ = 0.633, 0.712, and 0.400, respectively), with statistically significant differences. In the intra-articular region, the consistency was reduced (κ = 0.237), and the differences were statistically significant.

CONCLUSION

Ultrasound and DECT are effective methods to detect MSU deposition in gout of the knee. However, the consistency between the two techniques varies in different anatomical locations. Clinical assessment should be tailored based on the specific anatomical position. DECT is advantageous for the evaluation of intra-articular MSU deposits, while ultrasound is more sensitive for the early detection of scattered MSU deposits.

Systematic Review on Learning-based Spectral CT

Spectral computed tomography (CT) has recently emerged as an advanced version of medical CT and significantly improves conventional (single-energy) CT. Spectral CT has two main forms: dual-energy computed tomography (DECT) and photon-counting computed tomography (PCCT), which offer image improvement, material decomposition, and feature quantification relative to conventional CT. However, the inherent challenges of spectral CT, evidenced by data and image artifacts, remain a bottleneck for clinical applications. To address these problems, machine learning techniques have been widely applied to spectral CT. In this review, we present the state-of-the-art data-driven techniques for spectral CT.

Imaging of Acute Pulmonary Embolism: An Update

Imaging is essential in the evaluation and management of acute pulmonary embolism. Advances in multi-energy CT including dual-energy CT and photon-counting CT have allowed faster scans with lower radiation dose and optimal quality. Artificial intelligence has a potential role in triaging potentially positive examinations and could serve as a second reader.

Flat-panel dual-energy head computed tomography in the angiography suite after thrombectomy for acute stroke: A clinical feasibility study

BACKGROUND

Management of large vessel occlusion (LVO) patients after thrombectomy is affected by the presence of intracranial hemorrhage (ICH) on post-procedure imaging. Differentiating contrast staining from hemorrhage on post-procedural imaging has been facilitated by dual-energy computed tomography (DECT), traditionally performed in dedicated computed tomography (CT) scanners with subsequent delays in treatment. We employed a novel method of DECT using the Siemens cone beam CT (DE-CBCT) in the angiography suite to evaluate for post-procedure ICH and contrast extravasation.

METHODS

After endovascular treatment for LVO was performed and before the patient was removed from the operating table, DE-CBCT was performed using the Siemens Q-biplane system, with two separate 20-second CBCT scans at two energy levels: 70 keV (standard) and 125 keV with tin filtration (nonstandard). Post-procedurally, patients also underwent a standard DECT using Siemens SOMATOM Force CT scanner. Two independent reviewers blindly evaluated the DE-CBCT and DECT for hemorrhage and contrast extravasation.

RESULTS

We successfully performed intra-procedural DE-CBCT in 10 subjects with no technical failure. The images were high-quality and subjectively useful to differentiate contrast from hemorrhage. The one hemorrhage seen on standard DECT was very small and clinically silent. The interrater reliability was 100% for both contrast and hemorrhage detection.

CONCLUSION

We demonstrate that intra-procedural DE-CBCT after thrombectomy is feasible and provides clinically meaningful images. There was close agreement between findings on DE-CBCT and standard DECT. Our findings suggest that DE-CBCT could be used in the future to improve stroke thrombectomy patient workflow and to more efficiently guide the postoperative management of these patients.

Real-time diagnosis of intracerebral hemorrhage by generating dual-energy CT from single-energy CT

Real-time diagnosis of intracerebral hemorrhage after thrombectomy is crucial for follow-up treatment. However, this is difficult to achieve with standard single-energy CT (SECT) due to similar CT values of blood and contrast agents under a single energy spectrum. In contrast, dual-energy CT (DECT) scanners employ two different energy spectra, which allows for real-time differentiation between hemorrhage and contrast extravasation based on energy-related attenuation characteristics. Unfortunately, DECT scanners are not as widely used as SECT scanners due to their high costs. To address this dilemma, in this paper, we generate pseudo DECT images from a SECT image for real-time diagnosis of hemorrhage. More specifically, we propose a SECT-to-DECT Transformer-based Generative Adversarial Network (SDTGAN), which is a 3D transformer-based multi-task learning framework equipped with a shared attention mechanism. In this way, SDTGAN can be guided to focus more on high-density areas (crucial for hemorrhage diagnosis) during the generation. Meanwhile, the introduced multi-task learning strategy and the shared attention mechanism also enable SDTGAN to model dependencies between interconnected generation tasks, improving generation performance while significantly reducing model parameters and computational complexity. In the experiments, we approximate real SECT images using mixed 120kV images from DECT data to address the issue of not being able to obtain the true paired DECT and SECT data. Extensive experiments demonstrate that SDTGAN can generate DECT images better than state-of-the-art methods. The code of our implementation is available at https://github.com/jiang-cw/SDTGAN.

Dual-energy Computed Tomography (DECT) predicts the efficacy of contrast medium extravasation and secondary cerebral hemorrhage after stent thrombectomy in acute ischemic cerebral infarction

 To prospective research the efficacy of dual-energy computed tomography (DECT) in predicting contrast medium extravasation and secondary cerebral hemorrhage after stent thrombectomy in acute ischemic cerebral infarction. Ninety-two patients with acute ischemic stroke who underwent intra-arterial thrombolysis in our hospital from December 2019 to January 2022 have opted as the study subjects. DECT was performed immediately after stent thrombectomy. Images were generated through the image workstation and routine diagnosis was performed 24 hours after the operation. To analyze the diagnostic value of To analyze the diagnostic value of DECT, and to explore the diagnostic status of lesions with hemorrhagic transformation or increased hemorrhage and their correlation with iodine concentration. (1) 68 situations were confirmed, 56 positive and 12 negative with detection rates of 10.71% for hemorrhage, 75.00% for contrast agent extravasation, and 14.29% for extravasation combined with hemorrhage; (2) DECT diagnosed 8 cases of postoperative bleeding and 44 cases of extravasation of contrast media and 4 cases of extravasation of contrast media with hemorrhage ; The accuracy of DECT in diagnosing postoperative hemorrhage was 96.43%. The accuracy of diagnosis of extravasation was 96.43%. (3) The mean iodine concentration of lesions with increased hemorrhage or hemorrhagic transformation was higher compared to those without; (4) There was a correlation between hemorrhagic transformation or increased hemorrhage and iodine concentration. Dual-energy CT (DECT) can accurately distinguish the extravasation of contrast agent and secondary cerebral hemorrhage, and can predict the increased bleeding and bleeding transformation, with good diagnostic value and good predictive efficacy.