Rational Design of Oil-Resistant and Electrically Conductive Fluorosilicone Rubber Foam Nanocomposites for Sensitive Detectability in Complex Solvent Environments.

Recent years have witnessed the explosive development of highly sensitive smart sensors based on conductive polymer foam materials. However, the design and development of multifunctional polymeric foam composites as smart sensors applied in complex solvent and oil environments remain a critical challenge. Herein, we design and synthesize vinyl-terminated polytrifluoropropylmethylsiloxane through anionic ring-opening polymerization to fabricate fluorosilicone rubber foam (FSiRF) materials with nanoscale wrinkled surfaces and reactive Si-H groups via a green and rapid chemical foaming strategy. Based on the strong adhesion between FSiRF materials and consecutive oxidized ketjen black (OKB) nano-network, multifunctional FSiRF nanocomposites were prepared by a dip-coating strategy followed by fluoroalkylsilane modification. The optimized F-OKB@FSiRF nanocomposites exhibit outstanding mechanical flexibility in wide-temperature range (100 cycle compressions from -20 to 200 °C), structure stability (no detached particles after being immersed into various aqueous solutions for up to 15 days), surface superhydrophobicity (water contact angle of 154° and sliding angle of ∼7°), and tunable electrical conductivity (from 10-5 to 10-2 S m-1). Additionally, benefiting from the combined actions of multiple lines of defense (low surface energy groups, physical barriers, and "shielding effect"), the F-OKB@FSiRF sensor presents excellent anti-swelling property and high sensitivity in monitoring both large-deformation and tiny vibrations generated by knocking the beaker, ultrasonic action, agitating, and sinking objects in weak-polar or nonpolar solvents. This work conceivably provides a chemical strategy for the fabrication of multifunctional polymeric foam nanocomposite materials as smart sensors for broad applications.

Standardization of scan protocols for RT CT simulator from different vendors using quantitative image quality technique.

OBJECTIVE: To investigate the feasibility of standardizing RT simulation CT scanner protocols between vendors using target-based image quality (IQ) metrics. METHOD AND MATERIALS: A systematic assessment process in phantom was developed to standardize clinical scan protocols for scanners from different vendors following these steps: (a) images were acquired by varying CTDIvol and using an iterative reconstruction (IR) method (IR: iDose and model-based iterative reconstruction [IMR] of CTp-Philips Big Bore scanner, SAFIRE of CTs-Siemens biograph PETCT scanner), (b) CT exams were classified into body and brain protocols, (c) the rescaled noise power spectrum (NPS) was calculated, (d) quantified the IQ change due to varied CTDIvol and IR, and (e) matched the IR strength level. IQ metrics included noise and texture from NPS, contrast, and contrast-to-noise ratio (CNR), low contrast detectability (d'). Area under curve (AUC) of the receiver operation characteristic curve of d' was calculated and compared. RESULTS: The level of change in the IQ ratio was significant (>0.6) when using IMR. The IQ ratio change was relatively low to moderate when using either iDose in CTp (0.1-0.5) or SAFIRE in CTs (0.1-0.6). SAFIRE-2 in CTs showed a closer match to the reference body protocol when compared to iDose-3 in CTp. In the brain protocol, iDose-3 in CTp could be matched to the low to moderate level of SAFIRE in CTs. The AUC of d' was highest when using IMR in CTp with lower CTDIvol, and SAFIRE in CTs performed better than iDose in CTp CONCLUSION: It is possible to use target-based IQ metrics to evaluate the performance of the system and operations across various scanners in a phantom. This can serve as an initial reference to convert clinical scanned protocols from one CT simulation scanner to another.

Evaluating eDNA and eRNA metabarcoding for aquatic biodiversity assessment: From bacteria to vertebrates.

The monitoring and management of aquatic ecosystems depend on precise estimates of biodiversity. Metabarcoding analyses of environmental nucleic acids (eNAs), including environmental DNA (eDNA) and environmental RNA (eRNA), have garnered attention for their cost-effective and non-invasive biomonitoring capabilities. However, the accuracy of biodiversity estimates obtained through eNAs can vary among different organismal groups. Here we evaluate the performance of eDNA and eRNA metabarcoding across nine organismal groups, ranging from bacteria to terrestrial vertebrates, in three cross-sections of the Yangtze River, China. We observe robust complementarity between eDNA and eRNA data. The relative detectability of eNAs was notably influenced by major taxonomic groups and organismal sizes, with eDNA providing more robust signals for larger organisms. Both eDNA and eRNA exhibited similar cross-sectional and longitudinal patterns. However, the detectability of larger organisms declined in eRNA metabarcoding, possibly due to differential RNA release and decay among different organismal groups or sizes. While underscoring the potential of eDNA and eRNA in large river biomonitoring, we emphasize the need for differential interpretation of eDNA versus eRNA data. This highlights the importance of careful method selection and interpretation in biomonitoring studies.

The modelling of flower colour: spectral purity or colour contrast as biologically relevant descriptors of flower colour signals for bees depending upon the perceptual task.

Flower colour is an important mediator of plant-pollinator interactions. While the reflectance of light from the flower surface and background are governed by physical properties, the perceptual interpretation of such information is generated by complex multilayered visual processing. Should quantitative modelling of flower signals strive for repeatable consistency enabled by parameter simplification, or should modelling reflect the dynamic way in which bees are known to process signals? We discuss why colour is an interpretation of spectral information by the brain of an animal. Different species, or individuals within a species, may respond differently to colour signals depending on sensory apparatus and/or individual experience. Humans and bees have different spectral ranges, but colour theory is strongly rooted in human colour perception and many principles of colour vision appear to be common. We discuss bee colour perception based on physiological, neuroanatomical and behavioural evidence to provide a pathway for modelling flower colours. We examine whether flower petals and floral guides as viewed against spectrally different backgrounds should be considered as a simple colour contrast problem or require a more dynamic consideration of how bees make perceptual decisions. We discuss that plants such as deceptive orchids may present signals to exploit bee perception, whilst many plants do provide honest signalling where perceived saturation indicates the probability of collecting nutritional rewards towards the centre of a flower that then facilitates effective pollination.

Task-based image quality assessment of an intraoperative CBCT for spine surgery compared with conventional CT.

PURPOSE: To analyze the image quality of a novel, state-of-the art platform for CBCT image-guided spine surgery, focusing particularly on the dose-effectiveness compared with conventional CT (the gold standard for postoperative assessment). METHODS: The ClarifEye platform (Philips Healthcare) with integrated augmented-reality surgical navigation, has been compared with a GE Revolution CT (GE Healthcare). The 3D spatial resolution (TTF) and noise (NPS) were evaluated considering relevant feature contrasts (200-900 HU) and background noise for differently sized patients (200-300 mm water-equivalent diameter). These measures were used to determine the noise equivalent quanta (NEQ) and observer model detectability. RESULTS: The CBCT system exhibited a linear response with 50% TTF at 5.7 cycles/cm (10% TTF at 9.2 cycles/cm), and the axial noise power peaking at about 3.6 cycles/cm (average frequency of 4.1 cycles/cm). The noise magnitude and texture differed markedly compared to iteratively reconstructed CT images (GE ASiR-V). The CBCT system had 26% lower detectability for a high-frequency task (related to edge detection) compared with CT images reconstructed using the Bone kernel combined with ASiR-V 50%. Likewise, it had 18% lower detectability for low- and mid-frequency tasks compared with CT images reconstructed using the Standard kernel. This difference translates to 50%-80% higher CBCT imaging doses required to match the CT image quality. CONCLUSIONS: The ClarifEye platform demonstrates intraoperative CBCT-imaging capabilities that under certain circumstances are comparable with conventional CT. However, due to limited dose-effectiveness, a trade-off between timeliness and radiation exposure must be considered if end-of-procedure CBCT is to replace postoperative CT.

Alpine songbirds at higher elevations are only raised with a slight delay and therefore under harsher environmental conditions.

The breeding phenology of birds is often timed to coincide with a peak in food availability. However, the shortening of the vegetation period with increasing elevation may force bird species at high elevations to breed earlier in relation to optimal environmental conditions due to time constraints. We investigated differences in fledging dates in five Alpine woodland songbird species along an elevational gradient from 1500 to 2200 m in Switzerland. We estimated fledging dates from a nationwide citizen science bird monitoring dataset and used the date when the proportion of observations of 'fledged young' reached 50% among all observations indicating breeding behaviour. This measure had the advantage that we could estimate average timing of the broods across a wide geographic range and over many years without the need to search for individual nests. We then compared differences in timing of the broods with climatic conditions and larch budburst across different elevational bands. The daily mean air temperature of 10-15°C was reached 34-38 days later at 2200 m compared to 1500 m, which is a similar delay as found in previous reports on snow melt-out date. The average delay in larch budburst was 19.2 days at 2200 m compared to 1500 m. In comparison, the average timing of the birds' broods was only 5.4 days later in coal tits and 0.5 days later in Alpine tits at 2200 compared to 1500 m (the two species for which we had the narrowest interval estimates). Also, the estimated delay at higher elevations in the broods of song thrushes, mistle thrushes and Eurasian chaffinches was relatively small. Rather than postponing breeding dates to better environmental conditions later in the season that would match the earlier conditions at low elevation, songbirds breeding at higher elevations may thus have evolved adaptations to cope with the harsher conditions.

New records of non-indigenous species from the eastern Mediterranean Sea (Crustacea, Mollusca), with a revision of genus Isognomon (Mollusca: Bivalvia).

We report new data on non-indigenous invertebrates from the Mediterranean Sea (four ostracods and 20 molluscs), including five new records for the basin: the ostracods Neomonoceratina iniqua, Neomonoceratina aff. mediterranea, Neomonoceratina cf. entomon, Loxoconcha cf. gisellae (Arthropoda: Crustacea)-the first records of non-indigenous ostracods in the Mediterranean-and the bivalve Striarca aff. symmetrica (Mollusca). Additionally, we report for the first time Electroma vexillum from Israel, and Euthymella colzumensis, Joculator problematicus, Hemiliostraca clandestina, Pyrgulina nana, Pyrgulina microtuber, Turbonilla cangeyrani, Musculus aff. viridulus and Isognomon bicolor from Cyprus. We also report the second record of Fossarus sp. and of Cerithiopsis sp. cf. pulvis in the Mediterranean Sea, the first live collected specimens of Oscilla galilae from Cyprus and the northernmost record of Gari pallida in Israel (and the Mediterranean). Moreover, we report the earliest records of Rugalucina angela, Ervilia scaliola and Alveinus miliaceus in the Mediterranean Sea, backdating their first occurrence in the basin by 3, 5 and 7 years, respectively. We provide new data on the presence of Spondylus nicobaricus and Nudiscintilla aff. glabra in Israel. Finally, yet importantly, we use both morphological and molecular approaches to revise the systematics of the non-indigenous genus Isognomon in the Mediterranean Sea, showing that two species currently co-occur in the basin: the Caribbean I. bicolor, distributed in the central and eastern Mediterranean, and the Indo-Pacific I. aff. legumen, at present reported only from the eastern Mediterranean and whose identity requires a more in-depth taxonomic study. Our work shows the need of taxonomic expertise and investigation, the necessity to avoid the unfounded sense of confidence given by names in closed nomenclature when the NIS belong to taxa that have not enjoyed ample taxonomic work, and the necessity to continue collecting samples-rather than relying on visual censuses and bio-blitzes-to enable accurate detection of non-indigenous species.

Characterization of Near Infrared-Dye Colored Fabrics Using Hyperspectral Imaging.

Near-infrared (NIR) dyes have a unique ability to interact favorably with light in the NIR region, which is particularly interesting where stealth and camouflage are paramount, such as in military uniforms. Characterization of cotton fabric dyed with NIR-absorbing dyes using visible-NIR (Vis-NIR) and short-wave infrared (SWIR) hyperspectral imaging was done. The aim of the study was to discern spectral changes caused by variations in dye concentration and dyeing temperature as these parameters directly influence color- and crocking-fastness of fabrics impacting the camouflage effect. The fabric was dyed at three concentrations (2.5, 5, and 10%) and two dyeing temperatures (55 °C and 85 °C) and principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were performed on the spectra to discriminate the fabrics based on dye concentrations. The PCA models successfully segregated the fabrics based on the dye concentration and dyeing temperature, while PLS-DA models demonstrated classification accuracies between 75 and 100% in the Vis-NIR range. Spectra in the SWIR region could not be used to detect the differences in the concentrations of the NIR dyes. This finding is promising, as it aligns with the objective of creating NIR-dyed camouflage fabrics that remain indistinguishable under varying dye concentrations. These results open possibilities for further exploration in enhancing the stealth capabilities of textiles in military applications.

Evaluating Machine Learning-Based MRI Reconstruction Using Digital Image Quality Phantoms.

Quantitative and objective evaluation tools are essential for assessing the performance of machine learning (ML)-based magnetic resonance imaging (MRI) reconstruction methods. However, the commonly used fidelity metrics, such as mean squared error (MSE), structural similarity (SSIM), and peak signal-to-noise ratio (PSNR), often fail to capture fundamental and clinically relevant MR image quality aspects. To address this, we propose evaluation of ML-based MRI reconstruction using digital image quality phantoms and automated evaluation methods. Our phantoms are based upon the American College of Radiology (ACR) large physical phantom but created in k-space to simulate their MR images, and they can vary in object size, signal-to-noise ratio, resolution, and image contrast. Our evaluation pipeline incorporates evaluation metrics of geometric accuracy, intensity uniformity, percentage ghosting, sharpness, signal-to-noise ratio, resolution, and low-contrast detectability. We demonstrate the utility of our proposed pipeline by assessing an example ML-based reconstruction model across various training and testing scenarios. The performance results indicate that training data acquired with a lower undersampling factor and coils of larger anatomical coverage yield a better performing model. The comprehensive and standardized pipeline introduced in this study can help to facilitate a better understanding of the performance and guide future development and advancement of ML-based reconstruction algorithms.

A novel method for developing contrast-detail curves from clinical patient images based on statistical low-contrast detectability.

Purpose. To develop a method to extract statistical low-contrast detectability (LCD) and contrast-detail (C-D) curves from clinical patient images.Method. We used the region of air surrounding the patient as an alternative for a homogeneous region within a patient. A simple graphical user interface (GUI) was created to set the initial configuration for region of interest (ROI), ROI size, and minimum detectable contrast (MDC). The process was started by segmenting the air surrounding the patient with a threshold between -980 HU (Hounsfield units) and -1024 HU to get an air mask. The mask was trimmed using the patient center coordinates to avoid distortion from the patient table. It was used to automatically place square ROIs of a predetermined size. The mean pixel values in HU within each ROI were calculated, and the standard deviation (SD) from all the means was obtained. The MDC for a particular target size was generated by multiplying the SD by 3.29. A C-D curve was obtained by iterating this process for the other ROI sizes. This method was applied to the homogeneous area from the uniformity module of an ACR CT phantom to find the correlation between the parameters inside and outside the phantom, for 30 thoracic, 26 abdominal, and 23 head images.Results. The phantom images showed a significant linear correlation between the LCDs obtained from outside and inside the phantom, with R2values of 0.67 and 0.99 for variations in tube currents and tube voltages. This indicated that the air region outside the phantom can act as a surrogate for the homogenous region inside the phantom to obtain the LCD and C-D curves.Conclusion. The C-D curves obtained from outside the ACR CT phantom show a strong linear correlation with those from inside the phantom. The proposed method can also be used to extract the LCD from patient images by using the region of air outside as a surrogate for a region inside the patient.

Reliability and Detectability of Emergency Management Systems in Smart Cities under Common Cause Failures.

Urban areas are undergoing significant changes with the rise of smart cities, with technology transforming how cities develop through enhanced connectivity and data-driven services. However, these advancements also bring new challenges, especially in dealing with urban emergencies that can disrupt city life and infrastructure. The emergency management systems have become crucial elements for enabling cities to better handle urban emergencies, although ensuring the reliability and detectability of such system remains critical. This article introduces a new method to perform reliability and detectability assessments. By using Fault Tree Markov chain models, this article evaluates their performance under extreme conditions, providing valuable insights for designing and operating urban emergency systems. These analyses fill a gap in the existing research, offering a comprehensive understanding of emergency management systems functionality in complex urban settings.

Automated Web-based Software for CT Quality Control Testing of Low-contrast Detectability using Model Observers.

The Channelized Hotelling observer (CHO) is well correlated with human observer performance in many CT detection/classification tasks but has not been widely adopted in routine CT quality control and performance evaluation, mainly because of the lack of an easily available, efficient, and validated software tool. We developed a highly automated solution - CT image quality evaluation and Protocol Optimization (CTPro), a web-based software platform that includes CHO and other traditional image quality assessment tools such as modulation transfer function and noise power spectrum. This tool can allow easy access to the CHO for both the research and clinical community and enable efficient, accurate image quality evaluation without the need of installing additional software. Its application was demonstrated by comparing the low-contrast detectability on a clinical photon-counting-detector (PCD)-CT with a traditional energy-integrating-detector (EID)-CT, which showed UHR-T3D had 6.2% higher d' than EID-CT with IR (p = 0.047) and 4.1% lower d' without IR (p = 0.122).

Technical note: Characterization, validation, and spectral optimization of a dedicated breast CT system for contrast-enhanced imaging.

BACKGROUND: The development of a new imaging modality, such as 4D dynamic contrast-enhanced dedicated breast CT (4D DCE-bCT), requires optimization of the acquisition technique, particularly within the 2D contrast-enhanced imaging modality. Given the extensive parameter space, cascade-systems analysis is commonly used for such optimization. PURPOSE: To implement and validate a parallel-cascaded model for bCT, focusing on optimizing and characterizing system performance in the projection domain to enhance the quality of input data for image reconstruction. METHODS: A parallel-cascaded system model of a state-of-the-art bCT system was developed and model predictions of the presampled modulation transfer function (MTF) and the normalized noise power spectrum (NNPS) were compared with empirical data collected in the projection domain. Validation was performed using the default settings of 49 kV with 1.5 mm aluminum filter and at 65 kV and 0.257 mm copper filter. A 10 mm aluminum plate was added to replicate the breast attenuation. Air kerma at the isocenter was measured at different tube current levels. Discrepancies between the measured projection domain metrics and model-predicted values were quantified using percentage error and coefficient of variation (CoV) for MTF and NNPS, respectively. The optimal filtration was for a 5 mm iodine disk detection task at 49, 55, 60, and 65 kV. The detectability index was calculated for the default aluminum filtration and for copper thicknesses ranging from 0.05 to 0.4 mm. RESULTS: At 49 kV, MTF errors were +5.1% and -5.1% at 1 and 2 cycles/mm, respectively; NNPS CoV was 5.3% (min = 3.7%; max = 8.5%). At 65 kV, MTF errors were -0.8% and -3.2%; NNPS CoV was 13.1% (min = 11.4%; max = 16.9%). Air kerma output was linear, with 11.67 µGy/mA (R2 = 0.993) and 19.14 µGy/mA (R2 = 0.996) at 49 and 65 kV, respectively. For iodine detection, a 0.25 mm-thick copper filter at 65 kV was found optimal, outperforming the default technique by 90%. CONCLUSION: The model accurately predicts bCT system performance, specifically in the projection domain, under varied imaging conditions, potentially contributing to the enhancement of 2D contrast-enhanced imaging in 4D DCE-bCT.

Parametric net influx rate imaging of 68Ga-DOTATATE in patients with neuroendocrine tumors: assessment of lesion detectability.

OBJECTIVES: There has been developed a clinical dynamic total-body 68Ga-DOTATATE PET/CT imaging protocol that allows quantitative imaging of net influx rate (Ki). Using qualitative and quantitative analyses of clinical studies, this retrospective study aims to assess whether parametric Ki images improve lesion detectability. METHODS: Using a 194-cm axial field-of-view PET/CT scanner, 52 patients with neuroendocrine tumors underwent a 60-min dynamic total-body 68Ga-DOTATATE scan. Parametric Ki images and static standardized uptake value (SUV) images were generated. In addition to visual inspection of both sets of images, a quantitative analysis of 249 individual lesions was conducted using the target-to-background (TBR) metric. RESULTS: There were 52 patients who underwent dynamic total-body 68Ga-DOTATATE PET/CT scans. A total of 249 lesions were evaluated, of which 66 lesions were biopsy-proven and 183 lesions were unproven. Ki images produced two fewer false positives than the SUV images. Overall, our results from 66 proven NET lesions suggested similar sensitivity (98.5%) but improved accuracy (from 95.6 to 97.1%) and potentially enhanced specificity with Ki over SUV imaging. Besides, there was no difference in the number of pathological lesions identified visually in both images. However, Ki TBR was significantly higher than SUV TBR quantitatively (P < 0.001). CONCLUSIONS: Patlak Ki imaging provides nuclear physicians with a PET image with higher tumor contrast which may enhance confidence in diagnosis with possibly reduced false positive results, albeit an equivalent detectability, compared to static SUV image.

The impact of automatic tube current modulation related settings of a modern GE CT scanner on image quality and patient dose; details do matter.

PURPOSE: To investigate the operation principles of the automatic tube current modulation (ATCM) of a modern GE healthcare CT scanner, and the impact of related settings on image quality and patient dose. MATERIAL & METHODS: A dedicated phantom (Mercury 4.0) was scanned using two of the most frequently used clinical scanning protocols (chest and abdomen-pelvis). The preset protocol settings were used as starting points (reference conditions). Scan direction, scan mode (helical vs. axial), total beam width, tube potential (kVp), and ATCM settings were then modified individually to understand their impact on radiation dose and image quality. Regarding the ATCM settings, the SmartmA minimum and maximum mA limits, and the noise index (NI) values were varied. As surrogates of patient dose, the CTDIvol and DLP values of each scan were used. As surrogates of image quality were used the image noise and the detectability index (d') of five different materials (air, solid water, polystyrene, iodine, and bone) embedded in the Mercury phantom calculated with the ImQuest software. RESULTS: The scanning direction did not have any effect on ATCM curves, unlike what has been observed in CT scanners from other manufacturers. Total beam width does matter, however, the SmartmA limit settings and kVp selection had the greatest impact on image quality and dose. It was seen that improper minimum mA limit settings practically invalidated the ATCM operation. In contrast, when full modulation was allowed without restrictions, noise standard deviation, and detectability index became much more consistent across the wide range of phantom diameters. For lower kVp settings an impressive dose reduction was observed that requires further investigation. CONCLUSION: SmartmA is a tool that if not properly used may increase the patient doses considerably. Therefore, its settings should be carefully adjusted for each preset different clinical protocol.

3D printed phantom with 12 000 submillimeter lesions to improve efficiency in CT detectability assessment.

BACKGROUND: The detectability performance of a CT scanner is difficult to precisely quantify when nonlinearities are present in reconstruction. An efficient detectability assessment method that is sensitive to small effects of dose and scanner settings is desirable. We previously proposed a method using a search challenge instrument: a phantom is embedded with hundreds of lesions at random locations, and a model observer is used to detect lesions. Preliminary tests in simulation and a prototype showed promising results. PURPOSE: In this work, we fabricated a full-size search challenge phantom with design updates, including changes to lesion size, contrast, and number, and studied our implementation by comparing the lesion detectability from a nonprewhitening (NPW) model observer between different reconstructions at different exposure levels, and by estimating the instrument sensitivity to detect changes in dose. METHODS: Designed to fit into QRM anthropomorphic phantoms, our search challenge phantom is a cylindrical insert 10 cm wide and 4 cm thick, embedded with 12 000 lesions (nominal width of 0.6 mm, height of 0.8 mm, and contrast of -350 HU), and was fabricated using PixelPrint, a 3D printing technique. The insert was scanned alone at a high dose to assess printing accuracy. To evaluate lesion detectability, the insert was placed in a QRM thorax phantom and scanned from 50 to 625 mAs with increments of 25 mAs, once per exposure level, and the average of all exposure levels was used as high-dose reference. Scans were reconstructed with three different settings: filtered-backprojection (FBP) with Br40 and Br59, and Sinogram Affirmed Iterative Reconstruction (SAFIRE) with strength level 5 and Br59 kernel. An NPW model observer was used to search for lesions, and detection performance of different settings were compared using area under the exponential transform of free response ROC curve (AUC). Using propagation of uncertainty, the sensitivity to changes in dose was estimated by the percent change in exposure due to one standard deviation of AUC, measured from 5 repeat scans at 100, 200, 300, and 400 mAs. RESULTS: The printed insert lesions had an average position error of 0.20 mm compared to printing reference. As the exposure level increases from 50 mAs to 625 mAs, the lesion detectability AUCs increase from 0.38 to 0.92, 0.42 to 0.98, and 0.41 to 0.97 for FBP Br40, FBP Br59, and SAFIRE Br59, respectively, with a lower rate of increase at higher exposure level. FBP Br59 performed best with AUC 0.01 higher than SAFIRE Br59 on average and 0.07 higher than FBP Br40 (all P < 0.001). The standard deviation of AUC was less than 0.006, and the sensitivity to detect changes in mAs was within 2% for FBP Br59. CONCLUSIONS: Our 3D-printed search challenge phantom with 12 000 submillimeter lesions, together with an NPW model observer, provide an efficient CT detectability assessment method that is sensitive to subtle effects in reconstruction and is sensitive to small changes in dose.

Investigation of a potential upstream harmonization based on image appearance matching to improve radiomics features robustness: a phantom study.

Objective. Radiomics is a promising valuable analysis tool consisting in extracting quantitative information from medical images. However, the extracted radiomics features are too sensitive to variations in used image acquisition and reconstruction parameters. This limited robustness hinders the generalizable validity of radiomics-assisted models. Our aim is to investigate a possible harmonization strategy based on matching image quality to improve feature robustness.Approach.We acquired CT scans of a phantom with two scanners across different dose levels and percentages of Iterative Reconstruction algorithms. The detectability index was used as a comprehensive task-based image quality metric. A statistical analysis based on the Intraclass Correlation Coefficient was performed to determine if matching image quality/appearance could enhance the robustness of radiomics features extracted from the phantom images. Additionally, an Artificial Neural Network was trained on these features to automatically classify the scanner used for image acquisition.Main results.We found that the ICC of the features across protocols providing a similar detectability index improves with respect to the ICC of the features across protocols providing a different detectability index. This improvement was particularly noticeable in features relevant for distinguishing between scanners.Significance.This preliminary study demonstrates that a harmonization based on image quality/appearance matching could improve radiomics features robustness and heterogeneous protocols can be used to obtain a similar image appearance in terms of the detectability index. Thus protocols with a lower dose level could be selected to reduce the amount of radiation dose delivered to the patient and simultaneously obtain a more robust quantitative analysis.

Increased lesion detectability in patients with locally advanced breast cancer-A pilot study using dynamic whole-body [18F]FDG PET/CT.

BACKGROUND: Accurate diagnosis of axillary lymph node (ALN) metastases is essential for prognosis and treatment planning in breast cancer. Evaluation of ALN is done by ultrasound, which is limited by inter-operator variability, and by sentinel lymph node biopsy and/or ALN dissection, none of which are without risks and/or long-term complications. It is known that conventional 2-deoxy-2-[18F]fluoro-D-glucose ([18F]FDG) positron emission tomography/computed tomography (PET/CT) has limited sensitivity for ALN metastases. However, a recently developed dynamic whole-body (D-WB) [18F]FDG PET/CT scanning protocol, allowing for imaging of tissue [18F]FDG metabolic rate (MRFDG), has been shown to have the potential to increase lesion detectability. The study purpose was to examine detectability of malignant lesions in D-WB [18F]FDG PET/CT compared to conventional [18F]FDG PET/CT. RESULTS: This study prospectively included ten women with locally advanced breast cancer who were referred for an [18F]FDG PET/CT as part of their diagnostic work-up. They all underwent D-WB [18F]FDG PET/CT, consisting of a 6 min single bed dynamic scan over the chest region started at the time of tracer injection, a 64 min dynamic WB PET scan consisting of 16 continuous bed motion passes, and finally a contrast-enhanced CT scan, with generation of MRFDG parametric images. Lesion visibility was assessed by tumor-to-background and contrast-to-noise ratios using volumes of interest isocontouring tumors with a set limit of 50% of SUVmax and background volumes placed in the vicinity of tumors. Lesion visibility was best in the MRFDG images, with target-to-background values 2.28 (95% CI: 2.04-2.54) times higher than target-to-background values in SUV images, and contrast-to-noise values 1.23 (95% CI: 1.12-1.35) times higher than contrast-to-noise values in SUV images. Furthermore, five imaging experts visually assessed the images and three additional suspicious lesions were found in the MRFDG images compared to SUV images; one suspicious ALN, one suspicious parasternal lymph node, and one suspicious lesion located in the pelvic bone. CONCLUSIONS: D-WB [18F]FDG PET/CT with MRFDG images show potential for improved lesion detectability compared to conventional SUV images in locally advanced breast cancer. Further validation in larger cohorts is needed. CLINICAL TRIAL REGISTRATION: The trial is registered in clinicaltrials.gov, NCT05110443, https://www. CLINICALTRIALS: gov/study/NCT05110443?term=NCT05110443&rank=1 .

Foraging rates from metabarcoding: Predators have reduced functional responses in wild, diverse prey communities.

Functional responses describe foraging rates across prey densities and underlie many fundamental ecological processes. Most functional response knowledge comes from simplified lab experiments, but we do not know whether these experiments accurately represent foraging in nature. In addition, the difficulty of conducting multispecies functional response experiments means that it is unclear whether interaction strengths are weakened in the presence of multiple prey types. We developed a novel method to estimate wild predators' foraging rates from metabarcoding data and use this method to present functional responses for wild wolf spiders foraging on 27 prey families. These field functional responses were considerably reduced compared to lab functional responses. We further find that foraging is sometimes increased in the presence of other prey types, contrary to expectations. Our novel method for estimating field foraging rates will allow researchers to determine functional responses for wild predators and address long-standing questions about foraging in nature.

Assessment of temporal resolution and detectability of moving objects in CT: A task-based image quality study.

The metrics used for assessing image quality in computed tomography (CT) do not integrate the influence of temporal resolution. A shortcoming in the assessment of image quality for imaging protocols where motion blur can therefore occur. We developed a method to calculate the temporal resolution of standard CT protocols and introduced a specific spatiotemporal formulation of the non-prewhitening with eye filter (NPWE) model observer to assess the detectability of moving objects as a function of their speed. We scanned a cubic water phantom with a plexiglass cylindrical insert (120 HU) using a large panel of acquisition parameters (rotation times, pitch factors and collimation widths) on two systems (GE Revolution Apex and Siemens SOMATOM Force) to determine the in-plane task-based transfer functions (TTF) and noise power spectra (NPS). The phantom set in a uniform rectilinear motion in the transverse plane allowed the temporal modulation transfer function (MTF) calculation. The temporal MTF appropriately compared the temporal resolution of the various acquisition protocols. The longitudinal TTF was measured using a thin tungsten wire. The detectability index showed the advantage of applying high rotation speed, wide collimations and high pitch for object detection in the presence of motion. No counterpart to the increase in these three parameters was found in the in-plane and longitudinal image quality.