Dark-field computed tomography reaches the human scale.

X-ray computed tomography (CT) is one of the most commonly used three-dimensional medical imaging modalities today. It has been refined over several decades, with the most recent innovations including dual-energy and spectral photon-counting technologies. Nevertheless, it has been discovered that wave-optical contrast mechanisms-beyond the presently used X-ray attenuation-offer the potential of complementary information, particularly on otherwise unresolved tissue microstructure. One such approach is dark-field imaging, which has recently been introduced and already demonstrated significantly improved radiological benefit in small-animal models, especially for lung diseases. Until now, however, dark-field CT could not yet be translated to the human scale and has been restricted to benchtop and small-animal systems, with scan durations of several minutes or more. This is mainly because the adaption and upscaling to the mechanical complexity, speed, and size of a human CT scanner so far remained an unsolved challenge. Here, we now report the successful integration of a Talbot-Lau interferometer into a clinical CT gantry and present dark-field CT results of a human-sized anthropomorphic body phantom, reconstructed from a single rotation scan performed in 1 s. Moreover, we present our key hardware and software solutions to the previously unsolved roadblocks, which so far have kept dark-field CT from being translated from the optical bench into a rapidly rotating CT gantry, with all its associated challenges like vibrations, continuous rotation, and large field of view. This development enables clinical dark-field CT studies with human patients in the near future.

X-ray dark-field chest radiography: a reader study to evaluate the diagnostic quality of attenuation chest X-rays from a dual-contrast scanning prototype.

OBJECTIVES: To compare the visibility of anatomical structures and overall quality of the attenuation images obtained with a dark-field X-ray radiography prototype with those from a commercial radiography system. METHODS: Each of the 65 patients recruited for this study obtained a thorax radiograph at the prototype and a reference radiograph at the commercial system. Five radiologists independently assessed the visibility of anatomical structures, the level of motion artifacts, and the overall image quality of all attenuation images on a five-point scale, with 5 points being the highest rating. The average scores were compared between the two image types. The differences were evaluated using an area under the curve (AUC) based z-test with a significance level of p ≤ 0.05. To assess the variability among the images, the distributions of the average scores per image were compared between the systems. RESULTS: The overall image quality was rated high for both devices, 4.2 for the prototype and 4.6 for the commercial system. The rating scores varied only slightly between both image types, especially for structures relevant to lung assessment, where the images from the commercial system were graded slightly higher. The differences were statistically significant for all criteria except for the bronchial structures, the cardiophrenic recess, and the carina. CONCLUSIONS: The attenuation images acquired with the prototype were assigned a high diagnostic quality despite a lower resolution and the presence of motion artifacts. Thus, the attenuation-based radiographs from the prototype can be used for diagnosis, eliminating the need for an additional conventional radiograph. KEY POINTS: • Despite a low tube voltage (70 kVp) and comparably long acquisition time, the attenuation images from the dark-field chest radiography system achieved diagnostic quality for lung assessment. • Commercial chest radiographs obtained a mean rating score regarding their diagnostic quality of 4.6 out of 5, and the grating-based images had a slightly lower mean rating score of 4.2 out of 5. • The difference in rating scores for anatomical structures relevant to lung assessment is below 5%.

[New definition and classification of pulmonary hypertension]. / Die neue Definition und Klassifikation der pulmonalen Hypertonie.

In the recent ESC/ERS guidelines on the diagnosis and management of pulmonary hypertension (PH) several important changes have been made in respect of the definition and classification of PH.The mPAP cut-off for defining PH was lowered. PH is now defined by an mPAP > 20 mmHg assessed by right heart catheterization. Moreover, the PVR threshold for defining precapillary PH was lowered. Precapillary PH is now defined by a PVR > 2 WU and a pulmonary arterial wedge pressure (PAWP) ≤ 15 mmHg. Furthermore, the increasing evidence for the clinical relevance of pulmonary exercise hemodynamics led to the reintroduction of exercise pulmonary hypertension (EPH) 1. EPH is characterized by a mPAP/CO-slope > 3 mmHg/L/min during exercise testing. In the classification of PH five groups are distinguished: Pulmonary arterial hypertension (group 1), PH associated with left heart disease (group 2), PH associated with lung diseases and/or hypoxia (Group 3), PH associated with pulmonary artery obstructions (group 4) and PH with unclear and/or multi-factorial mechanisms (group 5).In the following guideline-translation we focus on novel aspects regarding the definition and classification of PH and to provide additional background information.

Kinetic Regulation of the Mammalian Sterile 20-like Kinase 2 (MST2).

Canonically, MST1/2 functions as a core kinase of the Hippo pathway and noncanonically during both apoptotic signaling and with RASSFs in T-cells. Faithful signal transduction by MST1/2 relies on both appropriate activation and regulated substrate phosphorylation by the activated kinase. Considerable progress has been made in understanding the molecular mechanisms regulating the activation of MST1/2 and identifying downstream signaling events. Here, we investigated the ability of MST2 to phosphorylate a peptide substrate and how that activity is regulated. Using a steady-state kinetic system, we parse the contribution of different factors to substrate phosphorylation, including the domains of MST2, phosphorylation, caspase cleavage, and complex formation. We found that in the unphosphorylated state, the SARAH domain stabilizes interactions with a peptide substrate and promotes turnover. Phosphorylation drives the activity of MST2, and once activated, MST2 is not further regulated by complex formation with other Hippo pathway components (SAV1, MOB1A, and RASSF5). We also show that the phosphorylated, caspase-cleaved MST2 is as active as the full-length one, suggesting that caspase-stimulated activity arises through noncatalytic mechanisms. The kinetic analysis presented here establishes a framework for interpreting how signaling events and post-translational modifications contribute to the signaling of MST2 in vivo.

Qualitative and Quantitative Assessment of Emphysema Using Dark-Field Chest Radiography.

Background Dark-field chest radiography allows for assessment of lung alveolar structure by exploiting wave optical properties of x-rays. Purpose To evaluate the qualitative and quantitative features of dark-field chest radiography in participants with pulmonary emphysema as compared with those in healthy control subjects. Materials and Methods In this prospective study conducted from October 2018 to October 2020, participants aged at least 18 years who underwent clinically indicated chest CT were screened for participation. Inclusion criteria were an ability to consent to the procedure and stand upright without help. Exclusion criteria were pregnancy, serious medical conditions, and any lung condition besides emphysema that was visible on CT images. Participants were examined with a clinical dark-field chest radiography prototype that simultaneously acquired both attenuation-based radiographs and dark-field chest radiographs. Dark-field coefficients were tested for correlation with each participant's CT-based emphysema index using the Spearman correlation test. Dark-field coefficients of adjacent groups in the semiquantitative Fleischner Society emphysema grading system were compared using a Wilcoxon Mann-Whitney U test. The capability of the dark-field coefficient to enable detection of emphysema was evaluated with receiver operating characteristics curve analysis. Results A total of 83 participants (mean age, 65 years ± 12 [standard deviation]; 52 men) were studied. When compared with images from healthy participants, dark-field chest radiographs in participants with emphysema had a lower and inhomogeneous dark-field signal intensity. The locations of focal signal intensity loss on dark-field images corresponded well with emphysematous areas found on CT images. The dark-field coefficient was negatively correlated with the quantitative CT-based emphysema index (r = -0.54, P < .001). Participants with Fleischner Society grades of mild, moderate, confluent, or advanced destructive emphysema exhibited a lower dark-field coefficient than those without emphysema (eg, 1.3 m-1 ± 0.6 for participants with confluent or advanced destructive emphysema vs 2.6 m-1 ± 0.4 for participants without emphysema; P < .001). The area under the receiver operating characteristic curve for detection of mild emphysema was 0.79. Conclusion Pulmonary emphysema leads to reduced signal intensity on dark-field chest radiographs, showing the technique has potential as a diagnostic tool in the assessment of lung diseases. © RSNA, 2022 See also the editorial by Hatabu and Madore in this issue.

X-ray Dark-Field Chest Imaging: Qualitative and Quantitative Results in Healthy Humans.

Background X-ray dark-field radiography takes advantage of the wave properties of x-rays, with a relatively high signal in the lungs due to the many air-tissue interfaces in the alveoli. Purpose To describe the qualitative and quantitative characteristics of x-ray dark-field images in healthy human subjects. Materials and Methods Between October 2018 and January 2020, patients of legal age who underwent chest CT as part of their diagnostic work-up were screened for study participation. Inclusion criteria were a normal chest CT scan, the ability to consent, and the ability to stand upright without help. Exclusion criteria were pregnancy, serious medical conditions, and changes in the lung tissue, such as those due to cancer, pleural effusion, atelectasis, emphysema, infiltrates, ground-glass opacities, or pneumothorax. Images of study participants were obtained by using a clinical x-ray dark-field prototype, recently constructed and commissioned at the authors' institution, to simultaneously acquire both attenuation-based and dark-field thorax radiographs. Each subject's total dark-field signal was correlated with his or her lung volume, and the dark-field coefficient was correlated with age, sex, weight, and height. Results Overall, 40 subjects were included in this study (average age, 62 years ± 13 [standard deviation]; 26 men, 14 women). Normal human lungs have high signal, while the surrounding osseous structures and soft tissue have very low and no signal, respectively. The average dark-field signal was 2.5 m-1 ± 0.4 of examined lung tissue. There was a correlation between the total dark-field signal and the lung volume (r = 0.61, P < .001). No difference was found between men and women (P = .78). Also, age (r = -0.18, P = .26), weight (r = 0.24, P = .13), and height (r = 0.01, P = .96) did not influence dark-field signal. Conclusion This study introduces qualitative and quantitative values for x-ray dark-field imaging in healthy human subjects. The quantitative x-ray dark-field coefficient is independent from demographic subject parameters, emphasizing its potential in diagnostic assessment of the lung. ©RSNA, 2021 See also the editorial by Hatabu and Madore in this issue.

Correction to: Towards clinical grating-interferometry mammography.

The article Towards clinical grating-interferometry mammography, written by Carolina Arboleda, Zhentian Wang, Konstantins Jefimovs, Thomas Koehler, Udo Van Stevendaal, Norbert Kuhn, Bernd David, Sven Prevrhal, Kristina Lång, Serafino Forte, Rahel Antonia Kubik-Huch, Cornelia Leo.

Towards clinical grating-interferometry mammography.

OBJECTIVES: Grating-interferometry-based mammography (GIM) might facilitate breast cancer detection, as several research works have demonstrated in a pre-clinical setting, since it is able to provide attenuation, differential phase contrast, and scattering images simultaneously. In order to translate this technique to the clinics, it has to be adapted to cover a large field-of-view within a clinically acceptable exposure time and radiation dose. METHODS: We set up a grating interferometer that fits into a standard mammography system and fulfilled the aforementioned conditions. Here, we present the first mastectomy images acquired with this experimental device. RESULTS AND CONCLUSION: Our system performs at a mean glandular dose of 1.6 mGy for a 5-cm-thick, 18%-dense breast, and a field-of-view of 26 × 21 cm2. It seems to be well-suited as basis for a clinical-environment device. Further, dark-field signals seem to support an improved lesion visualization. Evidently, the effective impact of such indications must be evaluated and quantified within the context of a proper reader study. KEY POINTS: • Grating-interferometry-based mammography (GIM) might facilitate breast cancer detection, since it is sensitive to refraction and scattering and thus provides additional tissue information. • The most straightforward way to do grating-interferometry in the clinics is to modify a standard mammography device. • In a first approximation, the doses given with this technique seem to be similar to those of conventional mammography.

CT pulmonary angiography: dose reduction via a next generation iterative reconstruction algorithm.

BACKGROUND: Computed tomography pulmonary angiography (CTPA) is the standard imaging modality for detection or rule out of pulmonary embolism (PE); however, radiation exposure is a serious concern. With iterative reconstruction algorithms a distinct dose reduction could be achievable. PURPOSE: To evaluate a next generation iterative reconstruction algorithm for detection or rule-out of PE in simulated low-dose CTPA. MATERIAL AND METHODS: Low-dose CT datasets with 50%, 25%, and 12.5% of the original tube current were simulated based on CTPA examinations of 92 patients with suspected PE. All datasets were reconstructed with two reconstruction algorithms: standard filtered back-projection (FBP) and iterative model reconstruction (IMR). In total, 736 CTPA datasets were evaluated by three blinded radiologists regarding image quality, diagnostic confidence, and detectability of PE. Furthermore, contrast-to-noise ratio (CNR) was calculated. RESULTS: Images reconstructed with IMR showed better detectability of PE than images reconstructed with FBP, especially at lower dose levels. With IMR, sensitivity was over 95% for central and segmental PE down to a dose level of 25%. Significantly higher subjective image quality was shown at lower dose levels (25% and 12.5%) for IMR images whereas it was higher for FBP images at higher dose levels. FBP was rated as showing less artificial image appearance. CNR was significantly higher with IMR at all dose levels. CONCLUSION: By using IMR, a dose reduction of up to 50% while maintaining satisfactory image quality seems feasible in standard clinical situations, resulting in a mean effective dose of 1.38 mSv for CTPA.

Sensitivity-based optimization for the design of a grating interferometer for clinical X-ray phase contrast mammography.

An X-ray grating interferometer (GI) suitable for clinical mammography must comply with quite strict dose, scanning time and geometry limitations, while being able to detect tumors, microcalcifications and other abnormalities. Such a design task is not straightforward, since obtaining optimal phase-contrast and dark-field signals with clinically compatible doses and geometrical constraints is remarkably challenging. In this work, we present a wave propagation based optimization that uses the phase and dark-field sensitivities as figures of merit. This method was used to calculate the optimal interferometer designs for a commercial mammography setup. Its accuracy was validated by measuring the visibility of polycarbonate samples of different thicknesses on a Talbot-Lau interferometer installed on this device and considering some of the most common grating imperfections to be able to reproduce the experimental values. The optimization method outcomes indicate that small grating pitches are required to boost sensitivity in such a constrained setup and that there is a different optimal scenario for each signal type.

Feasibility of a Supraglottic Airway Device for Transbronchial Lung Cryobiopsy-A Retrospective Analysis.

OBJECTIVES: To determine the feasibility of a supraglottic airway device for transbronchial cryobiopsy in adults. DESIGN: Retrospective analysis of anesthetic and pulmonary records between March 2015 and August 2016. SETTING: Single university medical center. PARTICIPANTS: One hundred thirty-two patients who underwent transbronchial cryobiopsy procedures performed under general anesthesia. INTERVENTIONS: Not applicable. MEASUREMENTS AND MAIN RESULTS: Failure-free use of a supraglottic airway device was 96.8%. Failure of supraglottic airway device insertion was 3.1% because of impossible placement (n = 1), high oropharyngeal leakage (n = 1), massive bleeding requiring bronchial blocker (n = 1), and acute right heart failure with cardiac arrest requiring resuscitation (n = 1). No serious adverse events due to the supraglottic airway device were observed. CONCLUSION: The data demonstrated that transbronchial cryobiopsy under general anesthesia and airway management with a supraglottic airway device was a feasible technique.

Regularized iterative integration combined with non-linear diffusion filtering for phase-contrast x-ray computed tomography.

Phase-contrast x-ray computed tomography has a high potential to become clinically implemented because of its complementarity to conventional absorption-contrast.In this study, we investigate noise-reducing but resolution-preserving analytical reconstruction methods to improve differential phase-contrast imaging. We apply the non-linear Perona-Malik filter on phase-contrast data prior or post filtered backprojected reconstruction. Secondly, the Hilbert kernel is replaced by regularized iterative integration followed by ramp filtered backprojection as used for absorption-contrast imaging. Combining the Perona-Malik filter with this integration algorithm allows to successfully reveal relevant sample features, quantitatively confirmed by significantly increased structural similarity indices and contrast-to-noise ratios. With this concept, phase-contrast imaging can be performed at considerably lower dose.

Role of compressive sensing technique in dose reduction for chest computed tomography: a prospective blinded clinical study.

PURPOSE: The purpose of this study was to assess pulmonary lesion detection, diagnostic confidence, and noise reduction in sparse-sampled (SpS) computed tomographic (CT) data of submillisievert (SubmSv) chest CT reconstructed with iterative reconstruction technique (IRT). MATERIALS AND METHODS: This Human Insurance Portability and Accountability-compliant, institutional review board-approved prospective study was performed using SpS-SubmSv IRT chest CT in 10 non-obese patients (body-mass index, 21-35 kg/m; age range, 26-90 years). Written informed consent was obtained. The patients were scanned at standard-dose CT (mean [SD] volumetric CT dose index, 6 [0.9] mGy; mean [SD] dose-length product, 208 ± 44 mGy·cm; and mean [SD] effective dose, 3 [0.6] mSv) and at SubmSv dose (1.8 [0.2] mGy, 67 [2] mGy·cm, 0.9 [0.03] mSv, respectively) on a Philips 128-slice CT scanner with double z-sampling. Sparse angular sampling data were reconstructed using 25% of the angular projections from the SubmSv sinogram to reduce the number of views and radiation dose by approximately 4-fold. Hence, the patients were scanned and then, simulation-based sparse sampling was performed with a resultant dose hypothetical SpS scan estimated mathematically (0.2 mSv). From each patient data, 3 digital imaging and communications in medicine series were generated: SpS-SubmSv with IRT, fully sampled SubmSv filtered back projection (FBP), and fully sampled standard-dose FBP (SD-FBP). Two radiologists independently assessed these image series for detection of lung lesions, visibility of small structures, and diagnostic acceptability. Objective noise was measured in the thoracic aorta, and noise spectral density was obtained for SpS-SubmSv IRT, SubmSv-FBP, and SD-FBP. RESULTS: The SpS-SubmSv IRT resulted in 75% (0.2/0.9 mSv) and 92% (0.2/2.9 mSv) dose reduction, when compared with the fully sampled SubmSv-FBP and SD-FBP, respectively. Images of SpS-SubmSv displayed all 46 lesions (most <1 cm, 30 lung nodules, 7 ground glass opacities, 9 emphysema) seen on the SubmSv-FBP and SD-FBP data sets. Lesion margins with sparse-sampled data were deemed acceptable compared with both SubmSv-FBP and SD-FBP. Overall diagnostic confidence was maintained with SpS-SubmSv IRT despite the presence of minor pixilation artifacts in 3 of 10 cases. The SpS-SubmSv IRT showed 63% and 38% noise reduction when compared with SubmSv-FBP (P < 0.0001) and SD-FBP (P < 0.01), respectively, with no significant change in Hounsfield unit values (P > 0.05). Noise-spectral density showed that SpS-SubmSv IRT gives a linear decrease over frequency in the semilog plot and an exponential decrease of noise power over frequency compared with SubmSv-FBP and SD-FBP. CONCLUSIONS: More than 90% dose reduction could be achieved with one-fourth sparse-sampled and SubmSv chest CT examination when reconstructed with IRT. Chest CT dose at one fourth of a millisievert with SpS is possible with optimal lesion detection and diagnostic confidence for the evaluation of pulmonary findings.

Correction for X-Ray Scatter and Detector Crosstalk in Dark-Field Radiography.

Dark-field radiography, a new X-ray imaging method, has recently been applied to human chest imaging for the first time. It employs conventional X-ray devices in combination with a Talbot-Lau interferometer with a large field of view, providing both attenuation and dark-field radiographs. It is well known that sample scatter creates artifacts in both modalities. Here, we demonstrate that also X-ray scatter generated by the interferometer as well as detector crosstalk create artifacts in the dark-field radiographs, in addition to the expected loss of spatial resolution. We propose deconvolution-based correction methods for the induced artifacts. The kernel for detector crosstalk is measured and fitted to a model, while the kernel for scatter from the analyzer grating is calculated by a Monte-Carlo simulation. To correct for scatter from the sample, we adapt an algorithm used for scatter correction in conventional radiography. We validate the obtained corrections with a water phantom. Finally, we show the impact of detector crosstalk, scatter from the analyzer grating and scatter from the sample and their successful correction on dark-field images of a human thorax.

Streak artefact removal in x-ray dark-field computed tomography using a convolutional neural network.

BACKGROUND: Computed tomography (CT) relies on the attenuation of x-rays, and is, hence, of limited use for weakly attenuating organs of the body, such as the lung. X-ray dark-field (DF) imaging is a recently developed technology that utilizes x-ray optical gratings to enable small-angle scattering as an alternative contrast mechanism. The DF signal provides structural information about the micromorphology of an object, complementary to the conventional attenuation signal. A first human-scale x-ray DF CT has been developed by our group. Despite specialized processing algorithms, reconstructed images remain affected by streaking artifacts, which often hinder image interpretation. In recent years, convolutional neural networks have gained popularity in the field of CT reconstruction, amongst others for streak artefact removal. PURPOSE: Reducing streak artifacts is essential for the optimization of image quality in DF CT, and artefact free images are a prerequisite for potential future clinical application. The purpose of this paper is to demonstrate the feasibility of CNN post-processing for artefact reduction in x-ray DF CT and how multi-rotation scans can serve as a pathway for training data. METHODS: We employed a supervised deep-learning approach using a three-dimensional dual-frame UNet in order to remove streak artifacts. Required training data were obtained from the experimental x-ray DF CT prototype at our institute. Two different operating modes were used to generate input and corresponding ground truth data sets. Clinically relevant scans at dose-compatible radiation levels were used as input data, and extended scans with substantially fewer artifacts were used as ground truth data. The latter is neither dose-, nor time-compatible and, therefore, unfeasible for clinical imaging of patients. RESULTS: The trained CNN was able to greatly reduce streak artifacts in DF CT images. The network was tested against images with entirely different, previously unseen image characteristics. In all cases, CNN processing substantially increased the image quality, which was quantitatively confirmed by increased image quality metrics. Fine details are preserved during processing, despite the output images appearing smoother than the ground truth images. CONCLUSIONS: Our results showcase the potential of a neural network to reduce streak artifacts in x-ray DF CT. The image quality is successfully enhanced in dose-compatible x-ray DF CT, which plays an essential role for the adoption of x-ray DF CT into modern clinical radiology.

Robust Sample Information Retrieval in Dark-Field Computed Tomography with a Vibrating Talbot-Lau Interferometer.

X-ray computed tomography (CT) is a crucial tool for non-invasive medical diagnosis that uses differences in materials' attenuation coefficients to generate contrast and provide 3D information. Grating-based dark-field-contrast X-ray imaging is an innovative technique that utilizes small-angle scattering to generate additional co-registered images with additional microstructural information. While it is already possible to perform human chest dark-field radiography, it is assumed that its diagnostic value increases when performed in a tomographic setup. However, the susceptibility of Talbot-Lau interferometers to mechanical vibrations coupled with a need to minimize data acquisition times has hindered its application in clinical routines and the combination of X-ray dark-field imaging and large field-of-view (FOV) tomography in the past. In this work, we propose a processing pipeline to address this issue in a human-sized clinical dark-field CT prototype. We present the corrective measures that are applied in the employed processing and reconstruction algorithms to mitigate the effects of vibrations and deformations of the interferometer gratings. This is achieved by identifying spatially and temporally variable vibrations in air reference scans. By translating the found correlations to the sample scan, we can identify and mitigate relevant fluctuation modes for scans with arbitrary sample sizes. This approach effectively eliminates the requirement for sample-free detector area, while still distinctly separating fluctuation and sample information. As a result, samples of arbitrary dimensions can be reconstructed without being affected by vibration artifacts. To demonstrate the viability of the technique for human-scale objects, we present reconstructions of an anthropomorphic thorax phantom.

X-Ray Dark-Field Signal Reduction Due to Hardening of the Visibility Spectrum.

X-ray dark-field imaging enables a spatially-resolved visualization of ultra-small-angle X-ray scattering. Using phantom measurements, we demonstrate that a material's effective dark-field signal may be reduced by modification of the visibility spectrum by other dark-field-active objects in the beam. This is the dark-field equivalent of conventional beam-hardening, and is distinct from related, known effects, where the dark-field signal is modified by attenuation or phase shifts. We present a theoretical model for this group of effects and verify it by comparison to the measurements. These findings have significant implications for the interpretation of dark-field signal strength in polychromatic measurements.

Hybrid spectral CT system with clinical rapid kVp-switching x-ray tube and dual-layer detector for improved iodine quantification.

Spectral computed tomography (CT) is a powerful diagnostic tool offering quantitative material decomposition results that enhance clinical imaging by providing physiologic and functional insights. Iodine, a widely used contrast agent, improves visualization in various clinical contexts. However, accurately detecting low-concentration iodine presents challenges in spectral CT systems, particularly crucial for conditions like pancreatic cancer assessment. In this study, we present preliminary results from our hybrid spectral CT instrumentation which includes clinical-grade hardware (rapid kVp-switching x-ray tube, dual-layer detector). This combination expands spectral datasets from two to four channels, wherein we hypothesize improved quantification accuracy for low-dose and low-iodine concentration cases. We modulate the system duty cycle to evaluate its impact on quantification noise and bias. We evaluate iodine quantification performance by comparing two hybrid weighting strategies alongside rapid kVp-switching. This evaluation is performed with a polyamide phantom containing seven iodine inserts ranging from 0.5 to 20 mg/mL. In comparison to alternative methodologies, the maximum separation configuration, incorporating data from both the 80 kVp, low photon energy detector layer and the 140 kVp, high photon energy detector layer produces spectral images containing low quantitative noise and bias. This study presents initial evaluations on a hybrid spectral CT system, leveraging clinical hardware to demonstrate the potential for enhanced precision and sensitivity in spectral imaging. This research holds promise for advancing spectral CT imaging performance across diverse clinical scenarios.