Edge-illumination spectral phase-contrast tomography

Following the rapid, but independent, diffusion of x-ray spectral and phase-contrast systems, this work demonstrates the first combination of spectral and phase-contrast computed tomography (CT) obtained by using the edge-illumination technique and a CdTe small-pixel (62μm) spectral detector. A theoretical model is introduced, starting from a standard attenuation-based spectral decomposition and leading to spectral phase-contrast material decomposition. Each step of the model is followed by quantification of accuracy and sensitivity on experimental data of a test phantom containing different solutions with known concentrations. An example of a micro CT application (20μm voxel size) on an iodine-perfusedex vivomurine model is reported. The work demonstrates that spectral-phase contrast combines the advantages of spectral imaging, i.e. high-Zmaterial discrimination capability, and phase-contrast imaging, i.e. soft tissue sensitivity, yielding simultaneously mass density maps of water, calcium, and iodine with an accuracy of 1.1%, 3.5%, and 1.9% (root mean square errors), respectively. Results also show a 9-fold increase in the signal-to-noise ratio of the water channel when compared to standard spectral decomposition. The application to the murine model revealed the potential of the technique in the simultaneous 3D visualization of soft tissue, bone, and vasculature. While being implemented by using a broad spectrum (pink beam) at a synchrotron radiation facility (Elettra, Trieste, Italy), the proposed experimental setup can be readily translated to compact laboratory systems including conventional x-ray tubes.

Technical note: TIGRE-DE for the creation of virtual monoenergetic images from dual-energy cone-beam CT

BACKGROUND

Dual-energy (DE)-CBCT represents a promising imaging modality that can produce virtual monoenergetic (VM) CBCT images. VM images, which provide enhanced contrast and reduced imaging artifacts, can be used to assist in soft-tissue visualization during image-guided radiotherapy.

PURPOSE

This work reports the development of TIGRE-DE, a module in the open-source TIGRE toolkit for the performance of DE-CBCT and the production of VM CBCT images. This module is created to make DE-CBCT tools accessible in a wider range of clinical and research settings.

METHODS

We developed an add-on (TIGRE-DE) to the TIGRE toolkit that performs DE material decomposition. To verify its performance, sequential CBCT scans at 80 and 140 kV of a Catphan 604 phantom were decomposed into equivalent thicknesses of aluminum (Al) and polymethyl-methylacrylate (PMMA) basis materials. These basis material projections were used to synthesize VM projections for a range of x-ray energies, which were then reconstructed using the Feldkamp-Davis-Kress (FDK) algorithm. Image quality was assessed by computing Hounsfield units (HU) and contrast-to-noise ratios (CNR) for the material inserts of the phantom and comparing with the constituent 80 and 140 kV images.

RESULTS

All VM images generated using TIGRE-DE showed good general agreement with the theoretical HU values of the material inserts of the phantom. Apart from the highest-density inserts imaged at the extremes of the energy range, the measured HU values agree with theoretical HUs within the clinical tolerance of ±50 HU. CNR measurements for the various inserts showed that, of the energies selected, 60 keV provided the highest CNR values. Moreover, 60 keV VM images showed average CNR enhancements of 63% and 66% compared to the 80 and 140 kV full-fan protocols.

CONCLUSIONS

TIGRE-DE successfully implements DE-CBCT material decomposition and VM image creation in an accessible, open-source platform.

Multi-energy blended CBCT spectral imaging and scatter-decoupled material decomposition using a spectral modulator with flying focal spot (SMFFS)

BACKGROUND

Cone-beam CT (CBCT) has been extensively employed in industrial and medical applications, such as image-guided radiotherapy and diagnostic imaging, with a growing demand for quantitative imaging using CBCT. However, conventional CBCT can be easily compromised by scatter and beam hardening artifacts, and the entanglement of scatter and spectral effects introduces additional complexity.

PURPOSE

The intertwined scatter and spectral effects within CBCT pose significant challenges to the quantitative performance of spectral imaging. In this work, we present the first attempt to develop a stationary spectral modulator with flying focal spot (SMFFS) technology as a promising, low-cost approach to accurately solving the x-ray scattering problem and physically enabling spectral imaging in a unified framework, and with no significant misalignment in data sampling of spectral projections.

METHODS

To deal with the intertwined scatter-spectral challenge, we propose a novel scatter-decoupled material decomposition (SDMD) method for SMFFS, which consists of four steps in total, including (1) spatial resolution-preserved and noise-suppressed multi-energy "residual" projection generation free from scatter, based on a hypothesis of scatter similarity; (2) first-pass material decomposition from the generated multi-energy residual projections in non-penumbra regions, with a structure similarity constraint to overcome the increased noise and penumbra effect; (3) scatter estimation for complete data; and (4) second-pass material decomposition for complete data by using a multi-material spectral correction method. Monte Carlo simulations of a pure-water cylinder phantom with different focal spot deflections are conducted to validate the scatter similarity hypothesis. Both numerical simulations using a clinical abdominal CT dataset, and physics experiments on a tabletop CBCT system using a Gammex multi-energy CT phantom and an anthropomorphic chest phantom, are carried out to demonstrate the feasibility of CBCT spectral imaging with SMFFS and our proposed SDMD method.

RESULTS

Monte Carlo simulations show that focal spot deflections within a range of 2 mm share quite similar scatter distributions overall. Numerical simulations demonstrate that SMFFS with SDMD method can achieve better material decomposition and CT number accuracy with fewer artifacts. In physics experiments, for the Gammex phantom, the average error of the mean values (E RMSE ROI $E^{\text{ROI}}_{\text{RMSE}}$ ) in selected regions of interest (ROIs) of virtual monochromatic image (VMI) at 70 keV is 8 HU in SMFFS cone-beam (CB) scan, and 19 and 210 HU in sequential 80/120 kVp (dual kVp, DKV) CB scan with and without scatter correction, respectively. For the chest phantom, theE RMSE ROI $E^{\text{ROI}}_{\text{RMSE}}$ in selected ROIs of VMIs is 12 HU for SMFFS CB scan, and 15 and 438 HU for sequential 80/140 kVp CB scan with and without scatter correction, respectively. Also, the non-uniformity among selected regions of the chest phantom is 14 HU for SMFFS CB scan, and 59 and 184 HU for the DKV CB scan with and without a traditional scatter correction method, respectively.

CONCLUSIONS

We propose a SDMD method for CBCT with SMFFS. Our preliminary results show that SMFFS can enable spectral imaging with simultaneous scatter correction for CBCT and effectively improve its quantitative imaging performance.

Spectral Fluorescence Pathology of Protein Misfolding Disorders

Protein misfolding has been extensively studied in the context of neurodegenerative disorders and systemic amyloidoses. Due to misfolding and aggregation of proteins being highly heterogeneous and generating a variety of structures, a growing body of evidence illustrates numerous ways how the aggregates contribute to progression of diseases such as Alzheimer's disease, Parkinson's disease, and prion disorders. Different misfolded species of the same protein, commonly referred to as strains, appear to play a significant role in shaping the disease clinical phenotype and clinical progression. The distinct toxicity profiles of various misfolded proteins underscore their importance. Current diagnostics struggle to differentiate among these strains early in the disease course. This review explores the potential of spectral fluorescence approaches to illuminate the complexities of protein misfolding pathology and discusses the applications of advanced spectral methods in the detection and characterization of protein misfolding disorders. By examining spectrally variable probes, current data analysis approaches, and important considerations for the use of these techniques, this review aims to provide an overview of the progress made in this field and highlights directions for future research.

Label-Free, Noninvasive Bone Cell Classification by Hyperspectral Confocal Raman Microscopy

Characterizing and identifying cells in multicellular in vitro models remain a substantial challenge. Here, we utilize hyperspectral confocal Raman microscopy and principal component analysis coupled with linear discriminant analysis to form a label-free, noninvasive approach for classifying bone cells and osteosarcoma cells. Through the development of a library of hyperspectral Raman images of the K7M2-wt osteosarcoma cell lines, 7F2 osteoblast cell lines, RAW 264.7 macrophage cell line, and osteoclasts induced from RAW 264.7 macrophages, we built a linear discriminant model capable of correctly identifying each of these cell types. The model was cross-validated using a k-fold cross validation scheme. The results show a minimum of 72% accuracy in predicting cell type. We also utilize the model to reconstruct the spectra of K7M2 and 7F2 to determine whether osteosarcoma cancer cells and normal osteoblasts have any prominent differences that can be captured by Raman. We find that the main differences between these two cell types are the prominence of the β-sheet protein secondary structure in K7M2 versus the α-helix protein secondary structure in 7F2. Additionally, differences in the CH2 deformation Raman feature highlight that the membrane lipid structure is different between these cells, which may affect the overall signaling and functional contrasts. Overall, we show that hyperspectral confocal Raman microscopy can serve as an effective tool for label-free, nondestructive cellular classification and that the spectral reconstructions can be used to gain deeper insight into the differences that drive different functional outcomes of different cells.

Virtual calcium removal in calcified coronary arteries with photon-counting detector CT-first in-vivo experience

Purpose

To evaluate the feasibility and accuracy of quantification of calcified coronary stenoses using virtual non-calcium (VNCa) images in coronary CT angiography (CCTA) with photon-counting detector (PCD) CT compared with quantitative coronary angiography (QCA).

Materials and methods

This retrospective, institutional-review board approved study included consecutive patients with calcified coronary artery plaques undergoing CCTA with PCD-CT and invasive coronary angiography between July and December 2022. Virtual monoenergetic images (VMI) and VNCa images were reconstructed. Diameter stenoses were quantified on VMI and VNCa images by two readers. 3D-QCA served as the standard of reference. Measurements were compared using Bland-Altman analyses, Wilcoxon tests, and intraclass correlation coefficients (ICC).

Results

Thirty patients [mean age, 64 years ± 8 (standard deviation); 26 men] with 81 coronary stenoses from calcified plaques were included. Ten of the 81 stenoses (12%) had to be excluded because of erroneous plaque subtraction on VNCa images. Median diameter stenosis determined on 3D-QCA was 22% (interquartile range, 11%-35%; total range, 4%-88%). As compared with 3D-QCA, VMI overestimated diameter stenoses (mean differences -10%, p < .001, ICC: .87 and -7%, p < .001, ICC: .84 for reader 1 and 2, respectively), whereas VNCa images showed similar diameter stenoses (mean differences 0%, p = .68, ICC: .94 and 1%, p = .07, ICC: .93 for reader 1 and 2, respectively).

Conclusion

First experience in mainly minimal to moderate stenoses suggests that virtual calcium removal in CCTA with PCD-CT, when feasible, has the potential to improve the quantification of calcified stenoses.

A Triangular-Matrix-Based Spectral Encoding Method for Broadband Filtering and Reconstruction-Based Spectral Measurement

Broadband filtering and reconstruction-based spectral measurement represent a hot technical route for miniaturized spectral measurement; the measurement encoding scheme has a great effect on the spectral reconstruction fidelity. The existing spectral encoding schemes are usually complex and hard to implement; thus, the applications are severely limited. Considering this, here, a simple spectral encoding method based on a triangular matrix is designed. The condition number of the proposed spectral encoding system is estimated and demonstrated to be relatively low theoretically; then, verification experiments are carried out, and the results show that the proposed encoding can work well under precise or unprecise encoding and measurement conditions; therefore, the proposed scheme is demonstrated to be an effective trade-off of the spectral encoding efficiency and implementation cost.

Non-destructive assessment of soluble solids content in kiwifruit using hyperspectral imaging coupled with feature engineering

The maturity of kiwifruit is widely gauged by its soluble solids content (SSC), with accurate assessment being essential to guarantee the fruit's quality. Hyperspectral imaging offers a non-destructive alternative to traditional destructive methods for SSC evaluation, though its efficacy is often hindered by the redundancy and external disturbances of spectral images. This study aims to enhance the accuracy of SSC predictions by employing feature engineering to meticulously select optimal spectral features and mitigate disturbance effects. We conducted a comprehensive investigation of four spectral pre-processing and nine spectral feature selection methods, as components of feature engineering, to determine their influence on the performance of a linear regression model based on ordinary least squares (OLS). Additionally, the stacking generalization technique was employed to amalgamate the strengths of the two most effective models derived from feature engineering. Our findings demonstrate a considerable improvement in SSC prediction accuracy post feature engineering. The most effective model, when considering both feature engineering and stacking generalization, achieved an R M S E p of 0.721, a M A P E p of 0.046, and an R P D p of 1.394 in the prediction set. The study confirms that feature engineering, especially the careful selection of spectral features, and the stacking generalization technique are instrumental in bolstering SSC prediction in kiwifruit. This advancement enhances the application of hyperspectral imaging for quality assessment, offering benefits that extend across the agricultural industry.

Hyperspectral Mapping of Human Primary and Stem Cells at Cell-Matrix Interfaces

Extracellular matrices interface with cells to promote cell growth and tissue development. Given this critical role, matrix mimetics are introduced to enable biomedical materials ranging from tissue engineering scaffolds and tumor models to organoids for drug screening and implant surface coatings. Traditional microscopy methods are used to evaluate such materials in their ability to support exploitable cell responses, which are expressed in changes in cell proliferation rates and morphology. However, the physical imaging methods do not capture the chemistry of cells at cell-matrix interfaces. Herein, we report hyperspectral imaging to map the chemistry of human primary and embryonic stem cells grown on matrix materials, both native and artificial. We provide the statistical analysis of changes in lipid and protein content of the cells obtained from infrared spectral maps to conclude matrix morphologies as a major determinant of biochemical cell responses. The study demonstrates an effective methodology for evaluating bespoke matrix materials directly at cell-matrix interfaces.

An Intra-Individual Comparison of Low-keV Photon-Counting CT versus Energy-Integrating-Detector CT Angiography of the Aorta

This retrospective study aims to provide an intra-individual comparison of aortic CT angiographies (CTAs) using first-generation photon-counting-detector CT (PCD-CT) and third-generation energy-integrating-detector CT (EID-CT). High-pitch CTAs were performed with both scanners and equal contrast-agent protocols. EID-CT employed automatic tube voltage selection (90/100 kVp) with reference tube current of 434/350 mAs, whereas multi-energy PCD-CT scans were generated with fixed tube voltage (120 kVp), image quality level of 64, and reconstructed as 55 keV monoenergetic images. For image quality assessment, contrast-to-noise ratios (CNRs) were calculated, and subjective evaluation (overall quality, luminal contrast, vessel sharpness, blooming, and beam hardening) was performed independently by three radiologists. Fifty-seven patients (12 women, 45 men) were included with a median interval between examinations of 12.7 months (interquartile range 11.1 months). Using manufacturer-recommended scan protocols resulted in a substantially lower radiation dose in PCD-CT (size-specific dose estimate: 4.88 ± 0.48 versus 6.28 ± 0.50 mGy, p < 0.001), while CNR was approximately 50% higher (41.11 ± 8.68 versus 27.05 ± 6.73, p < 0.001). Overall image quality and luminal contrast were deemed superior in PCD-CT (p < 0.001). Notably, EID-CT allowed for comparable vessel sharpness (p = 0.439) and less pronounced blooming and beam hardening (p < 0.001). Inter-rater agreement was good to excellent (0.58-0.87). Concluding, aortic PCD-CTAs facilitate increased image quality with significantly lower radiation dose compared to EID-CTAs.

Signal-difference-to-noise comparison of temporal subtraction, kV-switching dual-energy and photon-counting dual-energy x-ray angiography

BACKGROUND

Dual-energy (DE) x-ray angiography with photon-counting detectors (PCDs) may enable single-exposure DE imaging of coronary vasculature.

PURPOSE

To compare the iodine signal-difference-to-noise ratio (SDNR) of single-exposure DE angiography with digital subtraction angiography (DSA) and kV-switching DE angiography for matched patient x-ray exposure.

METHODS

In a phantom study, we determined the technique parameters that maximized the iodine SDNR per root entrance air kerma for DSA, kV-switching DE angiography and single-exposure DE angiography. We measured SDNR from images of a phantom consisting of an iodine step-wedge immersed in a water tank of either 20  or 30 cm in thickness. We also imaged a phantom with simulated vessels embedded in background clutter and measured vessel SDNR. For this second phantom, we also applied anti-correlated noise reduction (ACNR) and calculated the resulting iodine SDNR. All images were acquired using a cadmium telluride PCD with two energy bins and analog charge summing for charge sharing suppression. The energy-discrimination capabilities were only used for the single-exposure DE approach. Optimized techniques were compared in terms of SDNR per root air kerma for two levels of x-ray scatter.

RESULTS

For the same patient x-ray exposure, the SDNR of single-exposure DE imaging without ACNR was 75% to 85% of that of kV-switching DE imaging (also without ACNR) and DSA, the latter two of which had nearly equal SDNR. The single-exposure DE approach required ∼50% of the tube load of the kV-switching approach to achieve the same SDNR. For matched patient air kermas, the single exposure approach required only ∼25% of the tube load of the kV-switching approach. ACNR increased SDNR by 2.4 and 3.0 for kV-switching and single-exposure DE imaging, respectively.

CONCLUSIONS

Photon-counting, single-exposure DE angiography can suppress soft tissues and provide iodine SDNR levels comparable to DSA and kV-switching DE angiography for matched patient radiation exposures. When ACNR is used to reduce DE image noise, the SDNR of single-exposure DE imaging and kV-switching DE imaging exceed that of DSA by more than a factor of two. Compared to kV-switching DE imaging, single-exposure DE imaging requires substantially lower tube loading to achieve the same SDNR.

Machine-Learning-Based Single-Molecule Quantification of Circulating MicroRNA Mixtures

MicroRNAs (miRs) are small noncoding RNAs that regulate gene expression and are emerging as powerful indicators of diseases. MiRs are secreted in blood plasma and thus may report on systemic aberrations at an early stage via liquid biopsy analysis. We present a method for multiplexed single-molecule detection and quantification of a selected panel of miRs. The proposed assay does not depend on sequencing, requires less than 1 mL of blood, and provides fast results by direct analysis of native, unamplified miRs. This is enabled by a novel combination of compact spectral imaging and a machine learning-based detection scheme that allows simultaneous multiplexed classification of multiple miR targets per sample. The proposed end-to-end pipeline is extremely time efficient and cost-effective. We benchmark our method with synthetic mixtures of three target miRs, showcasing the ability to quantify and distinguish subtle ratio changes between miR targets.

Alternative intraoperative optical imaging modalities for fluorescence angiography in gastrointestinal surgery: spectral imaging and imaging photoplethysmography

INTRODUCTION

Intraoperative near-infrared fluorescence angiography with indocyanine green (ICG-FA) is a well-established modality in gastrointestinal surgery. Its main drawback is the application of a fluorescent agent with possible side effects for patients. The goal of this review paper is the presentation of alternative, non-invasive optical imaging methods and their comparison with ICG-FA.

MATERIAL AND METHODS

The principles of ICG-FA, spectral imaging, imaging photoplethysmography (iPPG), and their applications in gastrointestinal surgery are described based on selected published works.

RESULTS

The main applications of the three modalities are the evaluation of tissue perfusion, the identification of risk structures, and tissue segmentation or classification. While the ICG-FA images are mainly evaluated visually, leading to subjective interpretations, quantitative physiological parameters and tissue segmentation are provided in spectral imaging and iPPG. The combination of ICG-FA and spectral imaging is a promising method.

CONCLUSIONS

Non-invasive spectral imaging and iPPG have shown promising results in gastrointestinal surgery. They can overcome the main drawbacks of ICG-FA, i.e. the use of contrast agents, the lack of quantitative analysis, repeatability, and a difficult standardization of the acquisition. Further technical improvements and clinical evaluations are necessary to establish them in daily clinical routine.

In Vitro Dental Plaque Culture Model for Biofilm Structural Analyses

Extensive research has focused on the compositional changes in dental plaque microbiome communities during the transition from health to disease, known as dysbiosis. However, alterations in the spatial composition of these communities throughout the progression from health to disease remain under-explored. We describe an in vitro dental plaque model for culturing oral biofilms seeded with dental plaque from human volunteers. Our model recapitulates important features of the in vivo environment including shear force induced by salivary flow over teeth and the nutritional milieu experienced by microbes that inhabit the transitional zone between supragingival and subgingival aspects of the teeth. Importantly, our model is amenable to multiplex fluorescent labeling and multispectral imaging for testing specific hypotheses regarding systems-level community structure and function. The model allows for precise manipulation of various environmental conditions, such as flow rate and nutrient availability to investigate their effects on biofilm development and spatial structure. Furthermore, this model can be used to test the effects of various therapeutic interventions, e.g., antimicrobial agents, on the biofilm composition and structure at the micron to millimeter scale, making it a valuable tool for studying the molecular and cellular basis of dental plaque-mediated diseases and for benchmarking new therapeutic interventions. © 2023 Wiley Periodicals LLC. Basic Protocol 1: Dental plaque-on-a-chip in vitro model culture system Support Protocol: Gingival margin (GM) medium preparation Basic Protocol 2: Microcosm labeling and multispectral image acquisition.

Influenza A Virus Infection Alters Lipid Packing and Surface Electrostatic Potential of the Host Plasma Membrane

The pathogenesis of influenza A viruses (IAVs) is influenced by several factors, including IAV strain origin and reassortment, tissue tropism and host type. While such factors were mostly investigated in the context of virus entry, fusion and replication, little is known about the viral-induced changes to the host lipid membranes which might be relevant in the context of virion assembly. In this work, we applied several biophysical fluorescence microscope techniques (i.e., Förster energy resonance transfer, generalized polarization imaging and scanning fluorescence correlation spectroscopy) to quantify the effect of infection by two IAV strains of different origin on the plasma membrane (PM) of avian and human cell lines. We found that IAV infection affects the membrane charge of the inner leaflet of the PM. Moreover, we showed that IAV infection impacts lipid-lipid interactions by decreasing membrane fluidity and increasing lipid packing. Because of such alterations, diffusive dynamics of membrane-associated proteins are hindered. Taken together, our results indicate that the infection of avian and human cell lines with IAV strains of different origins had similar effects on the biophysical properties of the PM.

Comprehensive evaluations of a prototype full field-of-view photon counting CT system through phantom studies

Objective. Photon counting CT (PCCT) has been a research focus in the last two decades. Recent studies and advancements have demonstrated that systems using semiconductor-based photon counting detectors (PCDs) have the potential to provide better contrast, noise and spatial resolution performance compared to conventional scintillator-based systems. With multi-energy threshold detection, PCD can simultaneously provide the photon energy measurement and enable material decomposition for spectral imaging. In this work, we report a performance evaluation of our first CdZnTe-based prototype full-size PCCT system through various phantom imaging studies.Approach.This prototype system supports a 500 mm scan field-of-view and 10 mmz-coverage at isocenter. Phantom scans were acquired using 120 kVp from 50 to 400 mAs to assess the imaging performance on: CT number accuracy, uniformity, noise, spatial resolution, material differentiation and quantification.Main results.Both qualitative and quantitative evaluations show that PCCT, under the tested conditions, has superior imaging performance with lower noise and improved spatial resolution compared to conventional energy integrating detector (EID)-CT. Using projection domain material decomposition approach with multiple energy bin measurements, PCCT virtual monoenergetic images have lower noise, and good accuracy in quantifying iodine and calcium concentrations. These results lead to increased contrast-to-noise ratio (CNR) for both high and low contrast study objects compared to EID-CT at matched dose and spatial resolution. PCCT can also generate super-high resolution images using much smaller detector pixel size than EID-CT and greatly improve image spatial resolution.Significance.Improved spatial resolution and quantification accuracy with reduced image noise of the PCCT images can potentially lead to better diagnosis at reduced radiation dose compared to conventional EID-CT. Increased CNR achieved by PCCT suggests potential reduction in iodine contrast media load, resulting in better patient safety and reduced cost.

Quantitative energy spectrum CT in differential diagnosis of aldosterone-producing adenoma and cortisol-producing adenoma

Background

Patients with aldosterone-producing adenoma (APA) and cortisol-producing adenoma (CPA) show some similar clinical symptoms, and a large overlap of conventional imaging manifestations, which make the differentiation difficult. The purpose of our study was to explore the value of gemstone spectral imaging (GSI) dual-energy computed tomography (DECT) in differential diagnosis of APA and CPA, screen out meaningful energy spectral indicators and provide theoretical basis for the differential diagnosis of the two.

Methods

We retrospectively analyzed the imaging and clinical data of 30 patients with APA and 27 patients with CPA who underwent GSI DECT in The First Affiliated Hospital of Zhengzhou University (a tertiary care institution). Patients were consecutively enrolled in this study, and the quantitative DECT parameters were compared between the APA and CPA groups by two-sample test. The diagnostic efficacies were evaluated by receiver operating characteristic (ROC) analysis.

Results

DECT parameters including CT (computed tomography) values at 40-70 keV in the arterial phase, concentrations of I (H2O) and fat (I) in the arterial phase, and the effective atomic number in the venous phase, were significantly different between the APA and CPA groups (all P<0.001), and the area under the curve (AUC) values are 0.80, 0.79, 0.88, 0.76, 0.82, 0.87, and 0.86.

Conclusions

DECT quantitative parameters can effectively identify APA and CPA, the CT values at 40 and 60 keV in the arterial phase, the normalized CT value at 60 keV, the I (H2O), fat (I) concentration in the arterial phase and the effective atomic number parameter in the venous phase had valuable diagnostic performance.

Exploring the Phytobeneficial and Biocontrol Capacities of Endophytic Bacteria Isolated from Hybrid Vanilla Pods

In this study, 58 endophytic bacterial strains were isolated from pods of two hybrid vanilla plants from Madagascar, Manitra ampotony and Tsy taitra. They were genetically characterized and divided into four distinct phylotypes. Three were associated to genus Bacillus species, and the fourth to the genus Curtobacterium. A selection of twelve strains corresponding to the identified genetic diversity were tested in vitro for four phytobeneficial capacities: phosphate solubilisation, free nitrogen fixation, and phytohormone and siderophore production. They were also evaluated in vitro for their ability to biocontrol the growth of the vanilla pathogenic fungi, Fusarium oxysporum f. sp. radicis vanillae and Cholletotrichum orchidophilum. Three bacteria of phylotype 4, m62a, m64 and m65, showed a high nitrogen fixation capacity in vitro, similar to the Pseudomonas florescens F113 bacterium used as a control (phospate solubilizing efficiency respectively 0.50 ± 0.07, 0.43 ± 0.07 and 0.40 ± 0.06 against 0.48 ± 0.03). Strain t2 related to B. subtilis showed a higher siderophore production than F113 (respectively 1.40 ± 0.1 AU and 1.2 ± 0.1 AU). The strain m72, associated with phylotype 2, showed the highest rate of production of Indole-3-acetic acid (IAA) in vitro. Bacteria belonging to the pylotype 4 showed the best capacity to inhibit fungal growth, especially the strains m62b m64 and t24, which also induced a significant zone of inhibition, suggesting that they may be good candidates for controlling fungal diseases of vanilla. This competence was highlighted with spectral imaging showing the production of lipopeptides (Iturin A2 and A3, C₁₆ and C₁₅-Fengycin A and C₁₄ and C₁₅-Surfactin) by the bacterial strains m65 confronted with the pathogenic fungi of vanilla.

A Review of Recent Advances for the Detection of Biological, Chemical, and Physical Hazards in Foodstuffs Using Spectral Imaging Techniques

Traditional methods for detecting foodstuff hazards are time-consuming, inefficient, and destructive. Spectral imaging techniques have been proven to overcome these disadvantages in detecting foodstuff hazards. Compared with traditional methods, spectral imaging could also increase the throughput and frequency of detection. This study reviewed the techniques used to detect biological, chemical, and physical hazards in foodstuffs including ultraviolet, visible and near-infrared (UV-Vis-NIR) spectroscopy, terahertz (THz) spectroscopy, hyperspectral imaging, and Raman spectroscopy. The advantages and disadvantages of these techniques were discussed and compared. The latest studies regarding machine learning algorithms for detecting foodstuff hazards were also summarized. It can be found that spectral imaging techniques are useful in the detection of foodstuff hazards. Thus, this review provides updated information regarding the spectral imaging techniques that can be used by food industries and as a foundation for further studies.

Demonstrating a Novel, Hidden Source of Spectral Distortion in X-ray Photon Counting Detectors and Assessing Novel Trigger Schemes Proposed to Avoid It

X-ray photon counting spectral imaging (x-CSI) determines a detected photon's energy by comparing the charge it induces with several thresholds, counting how many times each is crossed (the standard method, STD). This paper is the first to demonstrate that this approach can unexpectedly delete counts from the recorded energy spectrum under some clinically relevant conditions: a process we call negative counting. Four alternative counting schemes are proposed and simulated for a wide range of sensor geometries (pixel pitch 100-600 µm, sensor thickness 1-3 mm), number of thresholds (3, 5, 8, 24 and 130) and medically relevant X-ray fluxes (10⁶-10⁹ photons mm^-2 s^-1). Spectral efficiency and counting efficiency are calculated for each simulation. Performance gains are explained mechanistically and correlated well with the improved suppression of "negative counting". The best performing scheme (Shift Register, SR) entirely eliminates negative counting, remaining close to an ideal scheme at fluxes of up to 10⁸ photons mm^-2 s^-1. At the highest fluxes considered, the deviation from ideal behaviour is reduced by 2/3 in SR compared with STD. The results have significant implications both for generally improving spectral fidelity and as a possible path toward the 10⁹ photons mm^-2 s^-1 goal in photon-counting CT.

Compact and ultracompact spectral imagers: technology and applications in biomedical imaging

Significance

Spectral imaging, which includes hyperspectral and multispectral imaging, can provide images in numerous wavelength bands within and beyond the visible light spectrum. Emerging technologies that enable compact, portable spectral imaging cameras can facilitate new applications in biomedical imaging.

Aim

With this review paper, researchers will (1) understand the technological trends of upcoming spectral cameras, (2) understand new specific applications that portable spectral imaging unlocked, and (3) evaluate proper spectral imaging systems for their specific applications.

Approach

We performed a comprehensive literature review in three databases (Scopus, PubMed, and Web of Science). We included only fully realized systems with definable dimensions. To best accommodate many different definitions of "compact," we included a table of dimensions and weights for systems that met our definition.

Results

There is a wide variety of contributions from industry, academic, and hobbyist spaces. A variety of new engineering approaches, such as Fabry-Perot interferometers, spectrally resolved detector array (mosaic array), microelectro-mechanical systems, 3D printing, light-emitting diodes, and smartphones, were used in the construction of compact spectral imaging cameras. In bioimaging applications, these compact devices were used for in vivo and ex vivo diagnosis and surgical settings.

Conclusions

Compact and ultracompact spectral imagers are the future of spectral imaging systems. Researchers in the bioimaging fields are building systems that are low-cost, fast in acquisition time, and mobile enough to be handheld.

Application of CT functional imaging in the assessment of chemotherapy efficacy in lung cancer

In this research, we aim to investigate the feasibility of a one-stop CT energy spectrum perfusion imaging technique for chemotherapy efficacy assessment of lung cancer patients by obtaining both functional imaging parameters of energy spectrum and perfusion in one scan. From November 2018 to February 2020, a group of 23 patients with pathologically confirmed lung cancer were chosen to undergo CT energy spectrum scans both before and after treatment. The post-treatment CT perfusion data was acquired one week after the second conventional chemotherapy session. Out of the 23 patients, 15 were in the chemotherapy effective group and the remaining 8 were in the ineffective group. The reason for this group was according to recist criteria. Arterial phase iodine concentration (icap) and intravenous phase iodine concentration (icpp) of the lesions were measured, and standardized iodine base values (nic) were calculated. The maximum diameter of the tumor before and after treatment was compared to the perfusion parameters and energy spectrum parameters before and after chemotherapy in the effective group and the invalid group was compared by two tests that p<0.05. The differences between the maximum diameter of the tumor before and after chemotherapy. 2 of the 15 patients in the effective group had liquefied necrotic areas in their lesions. One-stop ct energy-spectrum perfusion imaging can show the disease progression from a functional perspective and assess the efficacy early according to the changes in perfusion parameters and energy-spectrum parameters after lung cancer treatment.

Spectral photon counting for panoramic dental imaging

Panoramic x-ray imaging is a versatile, low-dose imaging tool, which is routinely used for dental applications. In this work, we explore a further improvement of the concept by introducing recently developed spectral photon-counting detector technology into a conventional panoramic imaging unit. In addition we adapt spectral material decomposition algorithms to panoramic imaging needs. Finally, we provide first experimental results, demonstrating decomposition of an anthropomorphic head phantom into soft tissue and dentin basis material panoramic images, while keeping the noise level acceptable using regularization approaches. The obtained results reveal a potential benefit of spectral photon-counting technology also for dental imaging applications.

An experimental framework for assessing the detective quantum efficiency of spectroscopic x-ray detectors

BACKGROUND

Assessing the performance of spectroscopic x-ray detectors (SXDs) requires measurement of the frequency-dependent detective quantum efficiency (DQE). Analytical expressions of the task-based DQE and task-independent DQE of SXDs have been presented in the literature, but standardizable experimental methods for measuring them have not. The task-based DQE quantifies the efficiency with which an SXD uses the x-ray quanta incident upon it to either quantify or detect a basis material (e.g., soft tissue or bone) of interest. The task-independent DQE is akin to the conventional DQE in that it is independent of the basis material to be detected or quantified.

PURPOSE

The purpose of this paper is to develop an experimental framework to present a method for experimental analysis of the DQE of SXDs, including the task-based DQE and task-independent DQE.

METHODS

We develop methods to measure the frequency-dependent DQE for task of quantifying or detecting a perturbation in a known basis material. We also develop methods for measuring a task-independent DQE. We show that the task-based DQEs and the task-independent DQE can be measured using a modest extension of the methods prescribed by International Electrotechnical Commission (IEC). Specifically, measuring the task-independent DQE requires measuring the modulation transfer function (MTF) and noise power spectrum (NPS) of each energy-bin image, in addition to the cross NPS between energy-bin images. Measuring the task-based DQEs requires an additional measurement of the transmission fraction through a thin basis-material absorber. We implemented the developed methods using standardized IEC x-ray spectra, aluminum (Al) and polymethyl methacrylyte (PMMA) basis materials, and a cadmium telluride (CdTe) SXD equipped with two energy bins and analog charge summing (ACS) for charge-sharing suppression. We also performed a regression analysis to determine whether or not the task-independent DQE is predictive of the task-based DQEs.

RESULTS

Experimental results of the task-based DQEs were consistent with simulation results presented in the literature. In general, and as expected, ACS increased the task-based DQEs and task-independent DQE. This effect was most pronounced for quantification tasks, in some instances yielding a five-fold increase in the DQE. For both spectra, with and without ACS for charge sharing correction, the task-based DQEs were linearly related to the task-independent DQE, as demonstrated by R² -values ranging from 0.89 to 1.00.

CONCLUSIONS

We have extended experimental DQE analysis to SXDs that count photons in multiple energy bins in a single x-ray exposure. The developed framework is an extension of existing IEC methods, and provides a standardized approach to assessing the performance of SXDs.

Liver Iodine Quantification With Photon-Counting Detector CT: Accuracy in an Abdominal Phantom and Feasibility in Patients

RATIONALE AND OBJECTIVES

To compare the accuracy of iodine quantification in liver parenchyma and lesions between dual-source photon-counting detector CT (PCD-CT) and dual-source energy-integrating detector CT (EID-CT) in a phantom and to demonstrate the feasibility of iodine quantification with PCD-CT in liver parenchyma and lesions in patients.

MATERIALS AND METHODS

An anthropomorphic abdominal phantom with a liver insert containing parenchyma and lesions was imaged on a clinical PCD-CT at 120kV and in the dual-energy mode on an EID-CT with kV-combinations of 80/Sn150kV, 90/Sn150kV, and 100/Sn150kV. Three patient sizes were imaged at three different radiation doses (CTDI_vol: 5, 10, 15mGy). Thirty patients with liver cysts, hemangiomas or metastases imaged with PCD-CT were retrospectively included. Iodine maps were reconstructed and iodine concentrations were measured in liver parenchyma and lesions. For the phantom, iodine error was quantified as the absolute difference to the vendor's specifications as reference.

RESULTS

Overall iodine error was 0.33 ± 0.29, 0.34 ± 0.32, 0.39 ± 0.37, 0.35 ± 0.39 mgI/mL for 80/Sn150kV, 90/Sn150kV, 100/Sn150kV of EID-CT, and PCD-CT, respectively, without significant differences between PCD-CT and EID-CT (p > 0.05). Radiation dose did not significantly influence error of PCD-CT (p > 0.05) nor EID-CT (p > 0.05). For both scanners, smaller patient sizes were associated with lower errors (p < 0.05). Iodine concentration and base material attenuation significantly influenced quantification for EID-CT (p < 0.05) but not PCD-CT (p > 0.05). In patients, iodine quantification was feasible in liver parenchyma, cysts, hemangiomas, and metastases.

CONCLUSION

Iodine quantification with PCD-CT is accurate in simulated liver parenchyma and lesions irrespective of radiation dose, iodine concentration, and base attenuation and is feasible in common liver lesions in patients.

Multifaceted mirror array illuminator for fluorescence excitation-scanning spectral imaging microscopy

SIGNIFICANCE

Hyperspectral imaging (HSI) technologies offer great potential in fluorescence microscopy for multiplexed imaging, autofluorescence removal, and analysis of autofluorescent molecules. However, there are also associated trade-offs when implementing HSI in fluorescence microscopy systems, such as decreased acquisition speed, resolution, or field-of-view due to the need to acquire spectral information in addition to spatial information. The vast majority of HSI fluorescence microscopy systems provide spectral discrimination by filtering or dispersing the fluorescence emission, which may result in loss of emitted fluorescence signal due to optical filters, dispersive optics, or supporting optics, such as slits and collimators. Technologies that scan the fluorescence excitation spectrum may offer an approach to mitigate some of these trade-offs by decreasing the complexity of the emission light path.

AIM

We describe the development of an optical technique for hyperspectral imaging fluorescence excitation-scanning (HIFEX) on a microscope system.

APPROACH

The approach is based on the design of an array of wavelength-dependent light emitting diodes (LEDs) and a unique beam combining system that uses a multifurcated mirror. The system was modeled and optimized using optical ray trace simulations, and a prototype was built and coupled to an inverted microscope platform. The prototype system was calibrated, and initial feasibility testing was performed by imaging multilabel slide preparations.

RESULTS

We present results from optical ray trace simulations, prototyping, calibration, and feasibility testing of the system. Results indicate that the system can discriminate between at least six fluorescent labels and autofluorescence and that the approach can provide decreased wavelength switching times, in comparison with mechanically tuned filters.

CONCLUSIONS

We anticipate that LED-based HIFEX microscopy may provide improved performance for time-dependent and photosensitive assays.

A Review of Thermal Spectral Imaging Methods for Monitoring High-Temperature Molten Material Streams

Real-time closed-loop control of metallurgical processes is still in its infancy, mostly based on simple models and limited sensor data and challenged by extreme temperature and harsh process conditions. Contact-free thermal imaging-based measurement approaches thus appear to be particularly suitable for process monitoring. With the potential to generate vast amounts of accurate data in real time and combined with artificial intelligence methods to enable real-time analysis and integration of expert knowledge, thermal spectral imaging is identified as a promising method offering more robust and accurate identification of key parameters, such as surface temperature, morphology, composition, and flow rate.

Visualizing changes of metabolites during iron deficiency chlorosis in field-grown pear leaves using micro-Raman spectral imaging

Owing to iron chlorosis, pear trees are some of the most severely impacted by iron deficiency, and they suffer significant losses every year. While it is possible to determine the iron content of leaves using laboratory-standard analytical techniques, the sampling and analysis process is time-consuming and labor-intensive, and it does not quickly and accurately identify the physiological state of iron-deficient leaves. Therefore, it is crucial to find a precise and quick visualization approach for metabolites linked to leaf iron to comprehend the mechanism of iron deficiency and create management strategies for pear-tree planting. In this paper, we propose a micro-Raman spectral imaging method for non-destructive, rapid, and precise visual characterization of iron-deficiency-related metabolites in pear leaves. According to our findings, iron deficiency significantly decreased the Raman peak intensities of chlorophylls and lipids in leaves. The spatial distributions of chlorophylls and lipids in the leaves changed significantly as the symptoms of iron insufficiency worsened. The technique offers a new, prospective tool for rapid recognition of iron deficiency in pear trees because it is capable of visual detection of plant physiological metabolites induced by iron deficiency.

The Optimization of the Light-Source Spectrum Utilizing Neural Networks for Detecting Oral Lesions

Any change in the light-source spectrum modifies the color information of an object. The spectral distribution of the light source can be optimized to enhance specific details of the obtained images; thus, using information-enhanced images is expected to improve the image recognition performance via machine vision. However, no studies have applied light spectrum optimization to reduce the training loss in modern machine vision using deep learning. Therefore, we propose a method for optimizing the light-source spectrum to reduce the training loss using neural networks. A two-class classification of one-vs-rest among the classes, including enamel as a healthy condition and dental lesions, was performed to validate the proposed method. The proposed convolutional neural network-based model, which accepts a 5 × 5 small patch image, was compared with an alternating optimization scheme using a linear-support vector machine that optimizes classification weights and lighting weights separately. Furthermore, it was compared with the proposed neural network-based algorithm, which inputs a pixel and consists of fully connected layers. The results of the five-fold cross-validation revealed that, compared to the previous method, the proposed method improved the F1-score and was superior to the models that were using the immutable standard illuminant D65.

High Temporal Resolution Dual-Source Photon-Counting CT for Coronary Artery Disease: Initial Multicenter Clinical Experience

The aim of this paper is to evaluate the diagnostic image quality of spectral dual-source photon-counting detector coronary computed tomography angiography (PCD-CCTA) for coronary artery disease in a multicenter study. The image quality (IQ), assessability, contrast-to-noise ratio (CNR), Agatston score, and radiation exposure were measured. Stenoses were quantified and compared with invasive coronary angiography, if available. A total of 92 subjects (65% male, age 58 ± 14 years) were analyzed. The prevalence of significant coronary artery disease (CAD) (stenosis ≥ 50%) was 17% of all patients, the range of the Agatston score was 0−2965 (interquartile range (IQR) 0−135). The IQ was very good (one, IQR one−two), the CNR was very high (20 ± 10), and 5% of the segments were rated non-diagnostic. The IQ and assessability were higher in proximal coronary segments (p < 0.001). Agatston scores up to 600 did not significantly affect the assessability of the coronary segments (p = 0.3). Heart rate influenced assessability only at a high-pitch mode (p = 0.009). For the invasive coronary angiography (ICA) subgroup (n = nine), the diagnostic performance for CAD per segment was high (sensitivity 92%, specificity 96%), although the limited number of patients who underwent both diagnostic modalities limits the generalization of this finding at this stage. PCD-CCTA provides good image quality for low and moderate levels of coronary calcifications.

3D Polymer Architectures for the Identification of Optimal Dimensions for Cellular Growth of 3D Cellular Models

Organ-on-chips and scaffolds for tissue engineering are vital assay tools for pre-clinical testing and prediction of human response to drugs and toxins, while providing an ethical sound replacement for animal testing. A success criterion for these models is the ability to have structural parameters for optimized performance. Here we show that two-photon polymerization fabrication can create 3D test platforms, where scaffold parameters can be directly analyzed by their effects on cell growth and movement. We design and fabricate a 3D grid structure, consisting of wall structures with niches of various dimensions for probing cell attachment and movement, while providing easy access for fluorescence imaging. The 3D structures are fabricated from bio-compatible polymer SZ2080 and subsequently seeded with A549 lung epithelia cells. The seeded structures are imaged with confocal microscopy, where spectral imaging with linear unmixing is used to separate auto-fluorescence scaffold contribution from the cell fluorescence. The volume of cellular material present in different sections of the structures is analyzed, to study the influence of structural parameters on cell distribution. Furthermore, time-lapse studies are performed to map the relation between scaffold parameters and cell movement. In the future, this kind of differentiated 3D growth platform, could be applied for optimized culture growth, cell differentiation, and advanced cell therapies.

Dissecting the mechanisms of environment sensitivity of smart probes for quantitative assessment of membrane properties

The plasma membrane, as a highly complex cell organelle, serves as a crucial platform for a multitude of cellular processes. Its collective biophysical properties are largely determined by the structural diversity of the different lipid species it accommodates. Therefore, a detailed investigation of biophysical properties of the plasma membrane is of utmost importance for a comprehensive understanding of biological processes occurring therein. During the past two decades, several environment-sensitive probes have been developed and become popular tools to investigate membrane properties. Although these probes are assumed to report on membrane order in similar ways, their individual mechanisms remain to be elucidated. In this study, using model membrane systems, we characterized the probes Pro12A, NR12S and NR12A in depth and examined their sensitivity to parameters with potential biological implications, such as the degree of lipid saturation, double bond position and configuration (cis versus trans), phospholipid headgroup and cholesterol content. Applying spectral imaging together with atomistic molecular dynamics simulations and time-dependent fluorescent shift analyses, we unravelled individual sensitivities of these probes to different biophysical properties, their distinct localizations and specific relaxation processes in membranes. Overall, Pro12A, NR12S and NR12A serve together as a toolbox with a wide range of applications allowing to select the most appropriate probe for each specific research question.

The Role of Pathology-Based Methods in Qualitative and Quantitative Approaches to Cancer Immunotherapy

Simple Summary

Immunotherapy has become the filar of modern oncological treatment, and programmed death-ligand 1 expression is one of the primary immune markers assessed by pathologists. However, there are still some issues concerning the evaluation of the marker and limited information about the interaction between the tumour and associated immune cells. Recent studies have focused on cancer immunology to try to understand the complex tumour microenvironment, and multiplex imaging methods are more widely used for this purpose. The presented article aims to provide an overall review of a different multiplex in situ method using spectral imaging, supported by automated image-acquisition and software-assisted marker visualisation and interpretation. Multiplex imaging methods could improve the current understanding of complex tumour-microenvironment immunology and could probably help to better match patients to appropriate treatment regimens.

Abstract

Immune checkpoint inhibitors, including those concerning programmed cell death 1 (PD-1) and its ligand (PD-L1), have revolutionised the cancer therapy approach in the past decade. However, not all patients benefit from immunotherapy equally. The prediction of patient response to this type of therapy is mainly based on conventional immunohistochemistry, which is limited by intraobserver variability, semiquantitative assessment, or single-marker-per-slide evaluation. Multiplex imaging techniques and digital image analysis are powerful tools that could overcome some issues concerning tumour-microenvironment studies. This novel approach to biomarker assessment offers a better understanding of the complicated interactions between tumour cells and their environment. Multiplex labelling enables the detection of multiple markers simultaneously and the exploration of their spatial organisation. Evaluating a variety of immune cell phenotypes and differentiating their subpopulations is possible while preserving tissue histology in most cases. Multiplexing supported by digital pathology could allow pathologists to visualise and understand every cell in a single tissue slide and provide meaning in a complex tumour-microenvironment contexture. This review aims to provide an overview of the different multiplex imaging methods and their application in PD-L1 biomarker assessment. Moreover, we discuss digital imaging techniques, with a focus on slide scanners and software.

Extracellular Volume Quantification With Cardiac Late Enhancement Scanning Using Dual-Source Photon-Counting Detector CT

OBJECTIVES

The aim of this study was to evaluate the feasibility and accuracy of cardiac late enhancement (LE) scanning for extracellular volume (ECV) quantification with dual-source photon-counting detector computed tomography (PCD-CT).

MATERIALS AND METHODS

In this institutional review board-approved study, 30 patients (mean age, 79 years; 12 women; mean body mass index, 28 kg/m2) with severe aortic stenosis undergoing PCD-CT as part of their preprocedural workup for transcatheter aortic valve replacement were included. The scan protocol consisted of a nonenhanced calcium-scoring scan, coronary CT angiography (CTA) followed by CTA of the thoracoabdominal aorta, and a low-dose LE scan 5 minutes after the administration of 100 mL contrast media (all scans electrocardiogram-gated). Virtual monoenergetic (65 keV) and dual-energy (DE) iodine images were reconstructed from the LE scan. Extracellular volume was calculated using the iodine ratios of myocardium and blood-pool of the LE scan, and additionally based on single-energy (SE) subtraction of the nonenhanced scan from the LE scan. Three-dimensional analysis was performed automatically for the whole-heart myocardial volume by matching a heart model generated from the respective coronary CTA data. Bland-Altman and correlation analysis were used to compare the ECV values determined by both methods.

RESULTS

The median dose length product for the LE scan was 84 mGy·cm (interquartile range, 69; 125 mGy·cm). Extracellular volume quantification was feasible in all patients. The median ECV value was 30.5% (interquartile range, 28.4%-33.6%). Two focal ECV elevations matched known prior myocardial infarction. The DE- and SE-based ECV quantification correlated well (r = 0.87, P < 0.001). Bland-Altman analysis showed small mean errors between DE- and SE-based ECV quantification (0.9%; 95% confidence interval, 0.1%-1.6%) with narrow limits of agreement (-3.3% to 5.0%).

CONCLUSIONS

Dual-source PCD-CT enables accurate ECV quantification using an LE cardiac DE scan at low radiation dose. Extracellular volume calculation from iodine ratios of the LE scan obviates the need for acquisition of a true nonenhanced scan and is not affected by potential misregistration between 2 separate scans.

Photon-Counting Detector CT-Based Vascular Calcium Removal Algorithm: Assessment Using a Cardiac Motion Phantom

OBJECTIVES

The diagnostic performance of coronary computed tomography angiography is known to be negatively affected by the presence of severely calcified plaques in the coronary arteries. In this article, the performance of a novel image reconstruction algorithm (PureLumen) based on spectral CT data of a first-generation dual-source photon-counting detector computed tomography (PCD-CT) system was assessed in a phantom study. PureLumen tries to remove only the calcified contributions from the image while leaving the rest unmodified.

MATERIALS AND METHODS

The study uses 2 iodine contrast filled vessel phantoms (diameter 4 mm) filled with different concentrations of iodine and equipped with calcified stenosis inserts. Each phantom features 2 separate calcified lesions of 25% and 50% percentage diameter stenosis (PDS) size. The vessel phantoms were mounted inside an anthropomorphic thorax phantom attached to an artificial motion device, simulating realistic cardiac motion at heart rates between 50 beats per minute and 100 beats per minute. Acquisitions were performed using a prospectively electrocardiogram triggered dual-source sequence mode on a PCD-CT system (NAEOTOM Alpha, Siemens Healthineers). Images were reconstructed at 80% of the RR interval with virtual monoenergetic images (Mono) and with additional calcium-removal (PureLumen), both at 65 keV. PureLumen is based on a spectral base material decomposition into iodine and calcium, which aims to reconstruct images without calcium contributions, while leaving all other material contribution unchanged. Stenosis grade was assessed individually for each vessel insert in all reconstructed image series by 2 readers.

RESULTS

The measured median PDS values for the 50% lesion were 56.0% (52.0%, 57.0%) for the Mono case and 50.0% (48.5%, 51.0%) for PureLumen. The 25% lesion median PDS values were 36.0% (29.5%, 39.5%) for Mono and 31.5% (30.5%, 34.0%) for PureLumen. Both lesion sizes demonstrate a significant difference between Mono and PureLumen in their result (P < 0.05) with PureLumen median values being closer to the actual true stenosis size for the 50% and 25% lesion. A visual assessment of the image quality depending on the heart rate yielded good image quality up to a heart rate of 80 beats per minute in the PureLumen case.

CONCLUSIONS

This phantom study shows that a novel calcium-removal image reconstruction algorithm (PureLumen) using a first-generation dual-source PCD-CT effectively decreases blooming artifacts caused by heavily calcified plaques and improves image interpretability. It also shows that PureLumen retains its performance in the presence of motion with simulated heart rates up to 80 beats per minute. Future in vivo clinical studies are needed to confirm the benefits of this type of reconstruction in terms of coronary computed tomography angiography quality and accuracy.

Repeatability and reproducibility of a hyperspectral imaging system for in vivo color evaluation

BACKGROUND

Color imaging is a tried and true method for the evaluation of cosmetic and dermatological effects, but it fails to capture all the information in a scene's spectral reflectance. For this reason, there has been in recent years increasing interest in the use of imaging spectrometers for clinical studies and product evaluation.

MATERIAL AND METHODS

We developed a novel HyperSpectral Imager (HSI) able to take in vivo full-face format images as a next generation instrument for skin color measurement and beyond. Here, we report part of the results of our first full-scale validation test of the HSI. We replicated a make-up foundation screening test by applying three products to a panel of 9 models and evaluated the product L^∗ , a^∗ , b^∗ , and ∆E effect immediately after application relative to the bare skin condition. We repeated this test twice in order to study the repeatability of the HSI as an evaluation instrument and during each test two different operators duplicated the data acquisition so we can assess the reproducibility of the measurements.

RESULTS

We find that the measurements from the HSI provide repeatability and reproducibility as good or better than those of our previous benchmark devices.

CONCLUSION

From these results, we conclude that not only is the HSI suitable for use in color evaluation studies, but also that it gives operational advantages over the previous generation of evaluation instruments, as it provides a spectral measurement combined with good spatial resolution. This allows for analysis of color over an area and post hoc selection of study regions and so opens new possibilities for studies of complex in vivo phenomena which neither non-imaging spectrometers nor conventional cameras can pursue. This study also raises points for future work concerning proper inclusion of instrument uncertainty in comparisons of results between instruments and handling of systematic uncertainties from analyses based on a single area.

Hyperspectral Imaging: A Review and Trends towards Medical Imaging

Hyperspectral Imaging (HSI) is a pertinent technique to provide meaningful information about unique objects in the medical field. In this paper, the basic principles, imaging methods, comparisons, and current advances in the medical applications of HSI are discussed to accentuate the importance of HSI in the medical field. To date, there are numerous tools and methods to fix the problems, but reliable medical HSI tools and methods need to be studied. The enactment and analytical competencies of HSI for medical imaging are discussed. Specifically, the recent successes and limitations of HSI in biomedical are presented to offer the readers an insight into its current potential for medical research. Lastly, we have discussed the future challenges concerning medical applications and possible ways to overcome these limitations.

Spectral propagation-based x-ray phase-contrast computed tomography

Purpose: Propagation-based x-ray imaging (PBI) is a phase-contrast technique that is employed in high-resolution imaging by introducing some distance between sample and detector. PBI causes characteristic intensity fringes that have to be processed with appropriate phase-retrieval algorithms, which has historically been a difficult task for objects composed of several different materials. Spectral x-ray imaging has been introduced to PBI to overcome this issue and to potentially utilize the spectral nature of the data for material-specific imaging. We aim to explore the potential of spectral PBI in three-dimensional computed tomography (CT) imaging in this work. Approach: We demonstrate phase-retrieval for experimental high-resolution spectral propagation-based CT data of a simple two-component sample, as well as a multimaterial capacitor test sample. Phase-retrieval was performed using an algorithm based on the Alvarez-Macovski model. Virtual monochromatic (VMI) and effective atomic number images were calculated after phase-retrieval. Results: Phase-retrieval results from the spectral data set show a distinct gray-level for each material with no residual phase-contrast fringes. Several representations of the phase-retrieved data are provided. The VMI is used to display an attenuation-equivalent image at a chosen display energy of 80 keV, to provide good separation of materials with minimal noise. The effective atomic number image shows the material composition of the sample. Conclusions: Spectral photon-counting detector technology has already been shown to be compatible with spectral PBI, and there is a foreseeable need for robust phase-retrieval in high-resolution, spectral x-ray CT in the future. Our results demonstrate the feasibility of phase-retrieval for spectral PBI CT.

The Shared Core Resource as a Partner in Innovative Scientific Research: Illustration from an Academic Microscopy Imaging Center

Core facilities have a ubiquitous and increasingly valuable presence at research institutions. Although many shared cores were originally created to provide routine services and access to complex and expensive instrumentation for the research community, they are frequently called upon by investigators to design protocols and procedures to help answer complex research questions. For instance, shared microscopy resources are evolving from providing access to and training on complex imaging instruments to developing detailed innovative protocols and experimental strategies, including sample preparation techniques, staining, complex imaging parameters, and high-level image analyses. These approaches require close intellectual collaboration between core staff and research investigators to formulate and coordinate plans for protocol development suited to the research question. Herein, we provide an example of such coordinated collaboration between a shared microscopy facility and a team of scientists and clinician-investigators to approach a complex multiprobe immunostaining, imaging, and image analysis project investigating the tumor microenvironment from human breast cancer samples. Our hope is that this example may be used to convey to institute administrators the critical importance of the intellectual contributions of the scientific staff in core facilities to research endeavors.

Cutting-Edge Platforms for Analysis of Immune Cells in the Hepatic Microenvironment-Focus on Tumor-Associated Macrophages in Hepatocellular Carcinoma

The role of tumor-associated macrophages (TAMs) in the pathogenesis of hepatocellular carcinoma (HCC) is poorly understood. Most studies rely on platforms that remove intrahepatic macrophages from the microenvironment prior to evaluation. Cell isolation causes activation and phenotypic changes that may not represent their actual biology and function in situ. State-of-the-art methods provides new strategies to study TAMs without losing the context of tissue architecture and spatial relationship with neighboring cells. These technologies, such as multispectral imaging (e.g., Vectra Polaris), mass cytometry by time-of-flight (e.g., Fluidigm CyTOF), cycling of fluorochromes (e.g., Akoya Biosciences CODEX/PhenoCycler-Fusion, Bruker Canopy, Lunaphore Comet, and CyCIF) and digital spatial profiling or transcriptomics (e.g., GeoMx or Visium, Vizgen Merscope) are being utilized to accurately assess the complex cellular network within the tissue microenvironment. In cancer research, these platforms enable characterization of immune cell phenotypes and expression of potential therapeutic targets, such as PDL-1 and CTLA-4. Newer spatial profiling platforms allow for detection of numerous protein targets, in combination with whole transcriptome analysis, in a single liver biopsy tissue section. Macrophages can also be specifically targeted and analyzed, enabling quantification of both protein and gene expression within specific cell phenotypes, including TAMs. This review describes the workflow of each platform, summarizes recent research using these approaches, and explains the advantages and limitations of each.

Hyperspectral imaging and adaptive thresholding to identify agonist-induced cAMP signals in pulmonary microvascular endothelial cells

Cyclic AMP (cAMP) is a second messenger that regulates a wide variety of cellular functions. There is increasing evidence suggesting that signaling specificity is due in part to cAMP compartmentalization. In the last 15 years, development of cAMP-specific Förster resonance energy transfer (FRET) probes have allowed us to visualize spatial distributions of intracellular cAMP signals. The use of FRET-based sensors is not without its limitations, as FRET probes display low signal to noise ratio (SNR). Hyperspectral imaging and analysis approaches have, in part, allowed us to overcome these limitations by improving the SNR of FRET measurements. Here we demonstrate that the combination of hyperspectral imaging approaches, linear unmixing, and adaptive thresholding allow us to visualize regions of elevated cAMP (regions of interest - ROIs) in an unbiased manner. We transfected cDNA encoding the H188 FRET-based cAMP probe into pulmonary microvascular endothelial cells. Application of isoproterenol and prostaglandin E1 (PGE₁) triggered complex cAMP responses. Spatial and temporal aspects of cAMP responses were quantified using an adaptive thresholding approach and compared between agonist treatment groups. Our data indicate that both the origination sites and spatial/temporal distributions of cAMP signals are agonist dependent in PMVECs. We are currently analyzing the data in order to better quantify the distribution of cAMP signals triggered by different agonists.

An Overview of X-ray Photon Counting Spectral Imaging (x-CSI) with a Focus on Gold Nanoparticle Quantification in Oncology

This review article offers an overview of the differences between traditional energy integrating (EI) X-ray imaging and the new technique of X-ray photon counting spectral imaging (x-CSI). The review is motivated by the need to image gold nanoparticles (AuNP) in vivo if they are to be used clinically to deliver a radiotherapy dose-enhancing effect (RDEE). The aim of this work is to familiarise the reader with x-CSI as a technique and to draw attention to how this technique will need to develop to be of clinical use for the described oncological applications. This article covers the conceptual differences between x-CSI and EI approaches, the advantages of x-CSI, constraints on x-CSI system design, and the achievements of x-CSI in AuNP quantification. The results of the review show there are still approximately two orders of magnitude between the AuNP concentrations used in RDEE applications and the demonstrated detection limits of x-CSI. Two approaches to overcome this were suggested: changing AuNP design or changing x-CSI system design. Optimal system parameters for AuNP detection and general spectral performance as determined by simulation studies were different to those used in the current x-CSI systems, indicating potential gains that may be made with this approach.

Virtual monochromatic imaging reduces beam hardening artefacts in cardiac interior photon counting computed tomography: a phantom study with cadaveric specimens

In interior cardiac computed tomography (CT) imaging, the x-ray beam is collimated to a limited field-of-view covering the heart volume, which decreases the radiation exposure to surrounding tissues. Spectral CT enables the creation of virtual monochromatic images (VMIs) through a computational material decomposition process. This study investigates the utility of VMIs for beam hardening (BH) reduction in interior cardiac CT, and further, the suitability of VMIs for coronary artery calcium (CAC) scoring and volume assessment is studied using spectral photon counting detector CT (PCD-CT).Ex vivocoronary artery samples (N = 18) were inserted in an epoxy rod phantom. The rod was scanned in the conventional CT geometry, and subsequently, the rod was positioned in a torso phantom and re-measured in the interior PCD-CT geometry. The total energy (TE) 10-100 keV reconstructions from PCD-CT were used as a reference. The low energy 10-60 keV and high energy 60-100 keV data were used to perform projection domain material decomposition to polymethyl methacrylate and calcium hydroxylapatite basis. The truncated basis-material sinograms were extended using the adaptive detruncation method. VMIs from 30-180 keV range were computed from the detruncated virtual monochromatic sinograms using filtered back projection. Detrending was applied as a post-processing method prior to CAC scoring. The results showed that BH artefacts from the exterior structures can be suppressed with high (≥100 keV) VMIs. With appropriate selection of the monoenergy (46 keV), the underestimation trend of CAC scores and volumes shown in Bland-Altman (BA) plots for TE interior PCD-CT was mitigated, as the BA slope values were -0.02 for the 46 keV VMI compared to -0.21 the conventional TE image. To conclude, spectral PCD-CT imaging using VMIs could be applied to reduce BH artefacts interior CT geometry, and further, optimal selection of VMI may improve the accuracy of CAC scoring assessment in interior PCD-CT.

Helical Nanostructures of Ferroelectric Liquid Crystals as Fast Phase Retarders for Spectral Information Extraction Devices: A Comparison with the Nematic Liquid Crystal Phase Retarders

Extraction of spectral information using liquid crystal (LC) retarders has recently become a topic of great interest because of its importance for creating hyper- and multispectral images in a compact and inexpensive way. However, this method of hyperspectral imaging requires thick LC-layer retarders (50 µm-100 µm and above) to obtain spectral modulation signals for reliable signal reconstruction. This makes the device extremely slow in the case of nematic LCs (NLCs), since the response time of NLCs increases proportionally to the square of the LC-layer thickness, which excludes fast dynamic processes monitoring. In this paper, we explore two approaches for solving the speed problem: the first is based on the use of faster nanospiral ferroelectric liquid crystals as an alternative to NLCs, and the second is based on using a passive multiband filter and focuses on multispectral extraction rather than hyperspectral. A detailed comparative study of nematic and ferroelectric devices is presented. The study is carried out using a 9-spectral bands passive spectral filter, covering the visible and near-infrared ranges. We propose the concept of multispectral rather than hyperspectral extraction, where a small number of wavelengths are sufficient for specific applications.

Unravelling the Puzzle of Anthranoid Metabolism in Living Plant Cells Using Spectral Imaging Coupled to Mass Spectrometry

Vismione H (VH) is a fluorescent prenylated anthranoid produced by plants from the Hypericaceae family, with antiprotozoal activities against malaria and leishmaniosis. Little is known about its biosynthesis and metabolism in plants or its mode of action against parasites. When VH is isolated from Psorospermum glaberrimum, it is rapidly converted into madagascine anthrone and anthraquinone, which are characterized by markedly different fluorescent properties. To locate the fluorescence of VH in living plant cells and discriminate it from that of the other metabolites, an original strategy combining spectral imaging (SImaging), confocal microscopy, and non-targeted metabolomics using mass spectrometry, was developed. Besides VH, structurally related molecules including madagascine (Mad), emodin (Emo), quinizarin (Qui), as well as lapachol (Lap) and fraxetin (Fra) were analyzed. This strategy readily allowed a spatiotemporal characterization and discrimination of spectral fingerprints from anthranoid-derived metabolites and related complexes with cations and proteins. In addition, our study validates the ability of plant cells to metabolize VH into madagascine anthrone, anthraquinones and unexpected metabolites. These results pave the way for new hypotheses on anthranoid metabolism in plants.

Use of Hyperspectral Imaging for the Quantification of Organic Contaminants on Copper Surfaces for Electronic Applications

To correctly assess the cleanliness of technical surfaces in a production process, corresponding online monitoring systems must provide sufficient data. A promising method for fast, large-area, and non-contact monitoring is hyperspectral imaging (HSI), which was used in this paper for the detection and quantification of organic surface contaminations. Depending on the cleaning parameter constellation, different levels of organic residues remained on the surface. Afterwards, the cleanliness was determined by the carbon content in the atom percent on the sample surfaces, characterized by XPS and AES. The HSI data and the XPS measurements were correlated, using machine learning methods, to generate a predictive model for the carbon content of the surface. The regression algorithms elastic net, random forest regression, and support vector machine regression were used. Overall, the developed method was able to quantify organic contaminations on technical surfaces. The best regression model found was a random forest model, which achieved an R² of 0.7 and an RMSE of 7.65 At.-% C. Due to the easy-to-use measurement and the fast evaluation by machine learning, the method seems suitable for an online monitoring system. However, the results also show that further experiments are necessary to improve the quality of the prediction models.

Aggregation and mobility of membrane proteins interplay with local lipid order in the plasma membrane of T cells

To disentangle the elusive lipid-protein interactions in T-cell activation, we investigate how externally imposed variations in mobility of key membrane proteins (T-cell receptor [TCR], kinase Lck, and phosphatase CD45) affect the local lipid order and protein colocalisation. Using spectral imaging with polarity-sensitive membrane probes in model membranes and live Jurkat T cells, we find that partial immobilisation of proteins (including TCR) by aggregation or ligand binding changes their preference towards a more ordered lipid environment, which can recruit Lck. Our data suggest that the cellular membrane is poised to modulate the frequency of protein encounters upon alterations of their mobility, for example in ligand binding, which offers new mechanistic insight into the involvement of lipid-mediated interactions in membrane-hosted signalling events.

Mobile snapshot hyperspectral imaging device for skin evaluation using diffractive optical elements

OBJECTIVE

A mobile handheld snapshot hyperspectral imaging device was developed and tested for in vivo skin evaluation using a new spectral imaging technology.

METHODS

The device is equipped with four different LED light sources (VIS, 810 nm, 850 nm, and 940 nm) for illumination. Based on a diffractive optical element (DOE) combined with a CMOS sensor chip, a snapshot hyperspectral imager is achieved for the application on human skin. The diffractive optical element (DOE) consists of a two-dimensional array of identically repeated diffractive microstructures. One hyperspectral image for all wavelength regions is taken within a few seconds. Complex recalculation of the VIS spectral distribution and image information from the received DOE image requires several minutes, depending on computing performance. A risk assessment on the irradiation sources shows no risk of harm due to the LED radiation.

RESULTS

Skin tone color patches experiments reproducibly deliver images and spectra of different skin tones. First in vivo use of the device identified pigmentation changes within the field of view.

CONCLUSION

We present a working mobile snapshot hyperspectral imaging tool based on diffractive optical elements. This device or future developments thereof can be used for broad skin evaluation in vivo.

Environment-Sensitive Fluorescence of 7-Nitrobenz-2-oxa-1,3-diazol-4-yl (NBD)-Labeled Ligands for Serotonin Receptors

Serotonin is a neurotransmitter that plays a crucial role in the regulation of several behavioral and cognitive functions by binding to a number of different serotonin receptors present on the cell surface. We report here the synthesis and characterization of several novel fluorescent analogs of serotonin in which the fluorescent NBD (7-nitrobenz-2-oxa-1,3-diazol-4-yl) group is covalently attached to serotonin. The fluorescent ligands compete with the serotonin_1A receptor specific radiolabeled agonist for binding to the receptor. Interestingly, these fluorescent ligands display a high environmental sensitivity of their fluorescence. Importantly, the human serotonin_1A receptor stably expressed in CHO-K1 cells could be specifically labeled with one of the fluorescent ligands with minimal nonspecific labeling. Interestingly, we show by spectral imaging that the NBD-labeled ligand exhibits a red edge excitation shift (REES) of 29 nm when bound to the receptor, implying that it is localized in a restricted microenvironment. Taken together, our results show that NBD-labeled serotonin analogs offer an attractive fluorescent approach for elucidating the molecular environment of the serotonin binding site in serotonin receptors. In view of the multiple roles played by the serotonergic systems in the central and peripheral nervous systems, these fluorescent ligands would be useful in future studies involving serotonin receptors.

A spectroscopic approach for rapid and simple serial number restoration on polyamide 6 parts of firearms: The use of video spectral comparator 8000

Serial numbers have forensic value as they help to identify firearms. While the serial numbers are mostly stamped on the metal parts of firearms, the characters on polymer parts involve non-serial number information such as caliber, brand, model, or proof marks, which also serve for identification purposes. The forensic evidence indicates that the polymer frames of firearms bearing non-serial number information are obliterated through heating and scraping. Although the destructive restoration techniques for polymers are well-documented, there is little theoretical and practical knowledge regarding the non-destructive restoration techniques applied on polymers. In view of this gap, this study aims to devise a non-destructive spectral technique to recover the obliterated characters on Polyamide 6. Considering its wide use on polymers, the numbering is carried out by hot stamping and the numbers are defaced through heating, scraping, and hammering both superficially and deeply at varying depths. Herein, we focused on imitating the manual obliteration techniques used by criminals instead of the deepness-controlled techniques preferred by previous studies. The samples are then viewed under the UV and IR lights in the Video Spectral Comparator 8000 for the first time. The results suggest that spectral imaging provided restoration to a good extent after heating and scraping which made the characters invisible at a relatively low depth of deformation compared to hammering. The recovery of characters with this novel technique brings a new perspective forensic marks examination literature by producing quick, successful and reliable results and facilitating reexamination by not harming the sample.