Noninvasive Characterization Research Articles

Non-Invasive Optical Characterization of Tissue Hemodynamics in Sickle Cell Patients Undergoing Treatment with Isoquercetin

Sickle Cell Disease (SCD) is an inherited hemoglobin disorder which causes a mutation in the β subunit of hemoglobin (HbA), thus producing hemoglobin S (HbS) (Williams and Thein, 2018). When HbS is deoxygenated, red blood cells (RBC) can polymerize, which promotes increased rigidity and microvascular occlusions. The presence of mutated HbS increases the likelihood of recurrent venous thromboembolism (VTE). There is an unmet need for real-time, non-invasive methods of assessing microvascular hemodynamics and endothelial dysfunction. Near-Infrared Spectroscopy (NIRS), is a non-invasive, optical technique which measures tissue absorption and scattering between 650-1100 nm in subcutaneous tissue. NIRS has the capability to quantitatively measure the concentration of oxy- and deoxy- hemoglobin as well as blood flow. To determine the sensitivity of NIRS to changes in hemodynamics in SCD patients, we evaluated a cohort of SCD patients undergoing treatment with Isoquercetin (IQ), a flavonoid antithrombotic agent, and correlated the findings with D-dimer, a marker for blood clot degradation. We recruited a sub-cohort of 17 of 46 patients participating in a randomized, double-blind, placebo-controlled trial of IQ and performed an optical hemodynamic assessment at baseline and 4 weeks post-treatment. We used the commercial, multi-modal NIRS device (MetaOx, ISS Inc) which combines frequency-domain NIRS (FD-NIRS) and diffuse correlation spectroscopy (DCS) to acquire optical markers of tissue composition and blood flow, respectively. NIRS testing included resting baseline measurements and a brachial cuff occlusion. As seen in Figure 1A, a blood pressure cuff was wrapped around the bicep and the NIRS probe was placed on the ipsilateral forearm muscle. The challenge consisted of a 3-minute baseline, 3-minute cuff occlusion at 200 mmHg, and a 3-minute recovery. The decay constant τc of the intensity autocorrelation function g2(τ), which is an indicator of the bulk displacement of scattering particles (i.e. RBCs) in the forearm, was fitted from the DCS data. We compared the mean τc during the last 30s of the occlusion to D-dimer levels for all 17 patients at baseline and at 4 weeks follow up. Following a data quality review, 8 patients had NIRS data for baseline and follow up visits. D-dimer levels were 1.875 mcg/mL ± 0.869 mcg/mL at baseline and 1.449 mcg/mL ± 0.874 mcg/mL at 4 weeks follow up. Among the 8 patients with good quality data, 5/8 showed an average decrease in τc by 0.424 ms at 4 weeks follow up and an average decrease in D-dimer levels by 0.768 mcg/mL. The patient in Figure 1B showed 42.0% decrease in τc and 46.6% decrease in D-dimer levels from baseline to 4 weeks follow up. 2/8 patients showed an increase in τc by an average of 0.139 ms and an average increase in D-dimer levels by 0.320 mcg/mL. 1/8 patient showed a decrease in the τc with no change in D-dimer levels. We found that 7/8 patients with baseline and follow up visits had matching trends between D-dimer levels and τc. As demonstrated, a larger τc signified less movement of scattering particles, such as RBCs, due to increased blood coagulation. The remaining 9/17 patients had data from one visit of acceptable quality and were excluded from this analysis. The results of this initial analysis demonstrate autocorrelation decay time could be a promising metric that is reflective of blood coagulation and rheology. While this analysis focused on the changes observed in optical blood flow markers, further work will be performed to both expand upon this analysis and to integrate the compositional data acquired from the FD-NIRS portion of the measurements. NIRS can potentially complement traditional blood biomarkers when assessing anti-thrombotic effects of SCD treatments, such as Isoquercetin. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Towards a Whole Sample Imaging Approach Using Diffusion Tensor Imaging to Examine the Foreign Body Response to Explanted Medical Devices.

Analysing the composition and organisation of the fibrous capsule formed as a result of the Foreign Body Response (FBR) to medical devices, is imperative for medical device improvement and biocompatibility. Typically, analysis is performed using histological techniques which often involve random sampling strategies. This method is excellent for acquiring representative values but can miss the unique spatial distribution of features in 3D, especially when analysing devices used in large animal studies. To overcome this limitation, we demonstrate a non-destructive method for high-resolution large sample imaging of the fibrous capsule surrounding human-sized implanted devices using diffusion tensor imaging (DTI). In this study we analyse the fibrous capsule surrounding two unique macroencapsulation devices that have been implanted in a porcine model for 21 days. DTI is used for 3D visualisation of the microstructural organisation and validated using the standard means of fibrous capsule investigation; histological analysis and qualitative micro computed tomography (microCT) and scanning electron microscopy (SEM) imaging. DTI demonstrated the ability to distinguish microstructural differences in the fibrous capsules surrounding two macroencapsulation devices made from different materials and with different surface topographies. DTI-derived metrics yielded insight into the microstructural organisation of both capsules which was corroborated by microCT, SEM and histology. The non-invasive characterisation of the integration of implants in the body has the potential to positively influence analysis methods in pre-clinical studies and accelerate the clinical translation of novel implantable devices.

Abstract 11595: Applying Machine Learning on Myocardial Deformation Parameters for Identifying Subjects in High Risk of Heart Failure: The Copenhagen City Heart Study

Background Recently, speckle tracking echocardiography (STE) and tissue doppler imaging (TDI) has gained increasing traction as a non-invasive tissue characterisation method within cardiology. But until now many patterns from the strain and TDI curves remain uninvestigated. In this work we applied supervised machine learning (ML) to identify unknown pathophysiological drivers of heart failure (HF) in the general population. Methods A total of 2383 subjects from the general population (Mean age 55.9 years ± 17.3, male 42%) underwent STE, TDI, and clinical examination. We applied an ensemble decision tree and a logistic regression model to investigate unknown speckle tracking parameters and to predict the endpoint: Occurrence of HF within five years. The ML models were evaluated with 20-fold cross-validation to provide a clear split between training and validation data. Results The median follow up-time was 5.41 years (ICR 4.49 - 6.28). 88 subjects (3.7%) developed HF within 5 years.We identified 4 new echocardiographic characteristics that improved the prediction of HF: 1. Peak systolic strain rate (SRs), 2. Strain at AVC, 3. Accumulated systolic strain/HR, 4. TDI Peak LV Diastolic Acceleration(Figure 1 and Figure 2). The model combining both novel strain- and TDI parameters as well as conventional echo parameters and clinical features performed significantly better than a model based on clinical features alone (AUC echocardiographic and clinical parameters vs. clinical parameters = 0.88/0.84, p = 0.04). An ensemble decision tree model predicted the outcome reasonably well with a precision of 24% at a sensitivity of 50%. Conclusion Adding novel echocardiographic parameters to a clinical ML model for prediction of HF improved the prognostic performance significantly. We identified 4 new parameters relevant for prediction of HF and found that peak systolic strain rate (SRs) was the most important predictor.

Abstract 10938: Concomitant Latent Pulmonary Vascular Disease Leads to Impaired Global Cardiac Performance in Heart Failure With Preserved Ejection Fraction

Introduction: The REDUCE-LAP II trial demonstrated adverse outcomes after interatrial shunt device (IASD) placement in heart failure with preserved ejection fraction (HFpEF) attributed to latent pulmonary vascular disease (PVD). We hypothesized that exercise-stress cardiovascular magnetic resonance (CMR) imaging could provide non-invasive characterisation of cardiac and pulmonary physiology for improved patient selection. Methods: The HFpEF-Stress Trial prospectively enrolled 75 patients with exertional dyspnoea and diastolic dysfunction. Patients underwent rest and exercise-stress right heart catheterisation (RHC), echocardiography and CMR imaging. Pulmonary artery and capillary wedge pressures, cardiac index (CI) and vascular resistance (PVR) were calculated. Latent PVD was defined as increased PVR≥1.74 Wood-Units during exercise-stress. CMR assessed long axis strains (LAS) and filling volumes of all cardiac chambers. Right ventricular (RV) function was further quantified by stroke and peak flow volumes. Results: Patients with latent PVD (n=24) showed higher HFA-PEFF scores and lower RV function (rest TAPSE, p=0.010; stress RV LAS, p<0.001) compared to patients without (n=43). RV filling (p=0.007), stroke and peak flow volumes (p<0.001) were reduced and led to impaired left atrial (p≤0.010) and ventricular (LV) filling (p≤0.008) and LV-CI (p<0.001) despite normal LV contractility (LV LAS p≥0.255). The degree of RV dysfunction during exercise-stress best predicted latent PVD (RV peak flow, AUC rest 0.81 vs. stress 0.91, p=0.005). Conclusions: Latent PVD is a feature of advanced HFpEF and associated with impaired RV functional reserve, global diastolic filling and LV-CI. This can be quantified by CMR and used to identify patients likely to benefit from IASD implantation.

Multi-modality cardiac imaging in the management of diabetic heart disease.

Diabetic heart disease is a major healthcare problem. Patients with diabetes show an excess of death from cardiovascular causes, twice as high as the general population and those with diabetes type 1 and longer duration of the disease present with more severe cardiovascular complications. Premature coronary artery disease and heart failure are leading causes of morbidity and reduced life expectancy. Multimodality cardiac imaging, including echocardiography, cardiac computed tomography, nuclear medicine, and cardiac magnetic resonance play crucial role in the diagnosis and management of different pathologies included in the definition of diabetic heart disease. In this review we summarise the utility of multi-modality cardiac imaging in characterising ischaemic and non-ischaemic causes of diabetic heart disease and give an overview of the current clinical practice. We also describe emerging imaging techniques enabling early detection of coronary artery inflammation and the non-invasive characterisation of the atherosclerotic plaque disease. Furthermore, we discuss the role of MRI-derived techniques in studying altered myocardial metabolism linking diabetes with the development of diabetic cardiomyopathy. Finally, we discuss recent data regarding the use of artificial intelligence applied to large imaging databases and how those efforts can be utilised in the future in screening of patients with diabetes for early signs of disease.

Digital Image Correlation and Its Role in NDE

Advancements in nondestructive evaluation (NDE) have represented a continuous process of technology achievements moving toward easier approaches, a wider range of applications, and better results outcomes. Materials and component characterization is done in many instances using destructive testing, which is effective but time-consuming, costly, and difficult to obtain feedback during manufacturing. Today, new, efficient, and noninvasive materials characterization technologies are becoming standard in industry, offering cost-effective applicability and quality benefits. In addition, newer inventions, state-of-the-art methodologies and instrumentations in NDE, and characterization technologies are offering ample support to industry to advance work and operations.

Photon path distributions in optically thin slabs.

The probability distribution function of photon path length in a scattering medium contains valuable information on that medium. While strongly scattering optically thick media have been extensively studied, in particular, with resort to the diffusion approximation, optically thin media have received much less attention. Here, we derive the probability distribution functions for the lengths of singly- and twice-scattered photon paths in an isotropically scattering slab of optical thickness τ, for both reflected and transmitted photons. We show that, in the case of an optically thin slab, these photons dominate the overall response of the medium. We confirm that the second moment of the distribution deviates from the ballistic limit in the case of collimated illumination. Interestingly, we show that under diffuse illumination, the second moment of the distribution is dominated by unscattered transmitted photons, hence is proportional to lnτ, and independent of the phase function. Higher moments of order n (≥3) scale as Hnτn-2. When only reflected or transmitted photons are considered, the second moment scales as H2τ-1, whatever the illumination and viewing conditions. This provides direct access to τ. These theoretical results are extensively supported by Monte Carlo ray-tracing simulations. Extension to anisotropic scattering using these same simulations shows that the results hold, given a scaling factor for collimated illumination, and without any dependence on the phase function for diffuse illumination. These results overall demonstrate that the optical thickness of an optically thin slab can be estimated from the second moment of the distribution. Along with the fact that under diffuse illumination the geometrical thickness can be derived from the first moment of the distribution, this proves that the extinction coefficient of the medium can be estimated from the combination of both moments. This study thus opens new perspectives for non-invasive characterization of optically thin media either in the laboratory or by remote sensing.

Longitudinal monitoring of individual infection progression in Drosophila melanogaster

The innate immune system is critical for infection survival. Drosophila melanogaster is a key model for understanding the evolution and dynamics of innate immunity. Current toolsets for fly infection studies are limited in throughput and, because of their destructive nature, cannot generate longitudinal measurements in individual animals. We report a bioluminescent imaging strategy enabling non-invasive characterization of pathogen load. By using Escherichia coli expressing the ilux operon, we demonstrate that photon flux from autobioluminescent bacteriacan be used to monitor pathogen loads in individual, living flies. Because animal sacrifice is not necessary to estimate pathogen load, stochastic responses to infection can be characterized in individuals over time. The high temporal resolution of bioluminescence imaging enables visualization of the dynamics of microbial clearance on the hours time-scale. This non-invasive imaging strategy provides a simple and scalable platform to observe changes in pathogen load invivo over time.

Photoluminescence microscopy as a noninvasive characterization method for defects in gallium oxide and aluminum gallium oxide epitaxial films

Herein we utilize polarized photoluminescence (PL) microscopy and spectral analysis to locate and characterize many different types of µm-scale extended defects present in melt-grown bulk crystals and metal-organic vapor-phase epitaxy (MOVPE)-grown epitaxial thin films of β-Ga2O3 and β-(Al,Ga)2O3. These include pits, divots, mounds, scratches, rotation domain boundaries, stacking faults, cracks, and other defect categories. Some types of µm-scale defects simply decrease overall PL yield, while others emit different spectra than single crystal regions. We combine PL microscopy with atomic force microscopy (AFM) and scanning electron microscopy (SEM) to provide detailed characteristics of these different types of features which can arise from both bulk crystal growth, surface preparation, and epitaxial growth processes. We show that sample quality (in terms of extended defects) can be determined by using PL and that attributing spectral features to isolated point defects is invalid unless the sample is proven to not contain extended defects.

Noninvasive Characterization of Functional Pathways in Layer-Specific Microcircuits of the Human Brain Using 7T fMRI.

Layer-specific cortical microcircuits have been explored through invasive animal studies, yet it is not possible to reliably characterize them functionally and noninvasively in the human brain. However, recent advances in ultra-high-field functional magnetic resonance imaging (fMRI) have made it feasible to reasonably resolve layer-specific fMRI signals with sub-millimeter resolution. Here, we propose an experimental and analytical framework that enables the noninvasive functional characterization of layer-specific cortical microcircuits. Specifically, we illustrate this framework by characterizing layer-specific functional pathways in the corticogeniculate network of the human visual system by obtaining sub-millimeter fMRI at 7T using a task which engages the magnocellular pathway between the lateral geniculate nucleus (LGN) and the primary visual cortex. Our results demonstrate that: (i) center-surround inhibition in magnocellular neurons within LGN is detectable using localized fMRI responses; (ii) feedforward (LGN → layers VI/IV, layer IV → layer VI) and feedback (layer VI → LGN) functional pathways, known to exist from invasive animal studies, can be inferred using dynamic directional connectivity models of fMRI and could potentially explain the mechanism underlying center-surround inhibition as well as gain control by layer VI in the human visual system. Our framework is domain-neutral and could potentially be employed to investigate the layer-specific cortical microcircuits in other systems related to cognition, memory and language.

Scattering properties of acoustic beams off spinning objects: Induced radiation force and torque

Understanding the acoustic scattering and radiation force and torque of an object is important in various fields, such as underwater communication, acoustic imaging, and noninvasive characterization, as well as biomedical ultrasound. Generally, acoustic scattering is considered for static (non-moving) objects and the impinging signal is typically a plane wave. Here, we consider scattering off cylindrical objects in spinning motion around the axis of rotational symmetry. We investigate the radiation force and torque induced by various incident signals, e.g., cylindrical diverging and converging beams as well as quasi-Gaussian beams of different orders. It is assumed in this study (unless otherwise stated) that the acoustic parameters of the objects (density and compressibility) are identical to those of the surrounding medium, in order to isolate the effects purely attributed to rotation. The scenario of a spinning inhomogeneous object is also shown to play a prominent role for generating torque with single plane waves. Our findings may add to the current interest in time-varying and moving metamaterials and open vistas in manipulation of movement and position of ultra-small objects via acoustic beams.

Electrocardiogram metrics identify ionic current dysregulation relevant to atrial fibrillation

Abstract Background Personalisation of pharmacological treatment for atrial fibrillation (AF) is challenging. Pharmacological ionic current blockers such as digoxin or flecainide are commonly used, with caution given possible cardiotoxicity and proarrhythmia. Moreover, patients are stratified based on their associated heart disease rather than individual electrophysiological substrate, in part due to the inability for its non-invasive characterisation. Here we hypothesise that the ECG may contain information on key ionic currents regulating AF initiation and sustenance, and which would enable personalisation of pharmacological treatments to increase safety and efficacy. Purpose To identify clinical ECG markers that reflect dysregulation of key ionic currents for AF using modelling and simulation in populations of whole-atria models without structural heart disease. Methods Experimental data obtained from human AF and control patients was used to develop a virtual population of 200 whole-atria models (Figure, organ-level) with individual ionic profiles (Figure 1, bottom-left), including electrophysiological regional inhomogeneities (Figure 1, bottom-right). Modified-limb 12 lead ECGs were computed during sinus rhythm (Figure 1, body-surface-level) and biomarkers were quantified for the P and Ta-waves, such as duration, time-to-peak, decay, dispersion, amplitude and P-wave terminal force. Results Simulated modified-limb ECG consistently reproduced the clinical ECG observed in human subjects, with an apparent Ta-wave inversion in lead II (Figure 1, body-surface-level). The inward rectified K+ current (IK1), known to be critical for AF, was the only ionic current associated with Ta-wave duration, showing an inversely proportional relationship (236±48 vs. 466±53 ms, IK1 up-regulation vs. down-regulation in lead V5; median ± interquartile range; P<0.001). Elevated IK1 additionally yield Ta-wave inversion in lead V5 and a higher Ta-wave magnitude in lead II (0.15±0.03 vs. 0.07±0.04 mV, IK1 up-regulation vs. down-regulation; P<0.001). However, Ta-wave magnitude showed a predominant relationship with the Na+/K+ pump (INaK), especially in the precordial leads (0.17±0.13 vs. 0.07±0.04 mV, INaK up-regulation vs. down-regulation in V5; P<0.001). Thus, the up-regulation of both currents led to very short, high-amplitude Ta-waves. While elevated IK1 additionally increased the P-wave terminal force (1.58±0.37 vs. 1.31±0.33 mV ms, IK1 up-regulation vs. down-regulation; P<0.001), a higher increase was observed for decreased fast Na+ current (INa) (1.35±0.17 vs. 1.86±0.30 mV ms, INa up-regulation vs. down-regulation; P<0.001). Conclusion Ta-wave duration and amplitude are revealing of IK1 and INaK dysregulation, respectively, holding potential for improving cardiac safety and efficacy through a better stratification of AF patients for pharmacological treatment. Funding Acknowledgement Type of funding sources: Public grant(s) – EU funding. Main funding source(s): European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 860974

Non-invasive characterization of pancoronary inflammation by computed tomography angiography in patients with recent spontaneous coronary dissection

Abstract Background Spontaneous coronary artery dissection (SCAD) is a non-atherosclerotic cause of myocardial infarction of unclear aethiology. Histopathological analyses have identified increased coronary inflammation in patients with SCAD [1]. Recently the peri-coronary adipose tissue attenuation (PCAT) derived from standard computed tomography angiography (CTA) has been established as a reproducible method for measuring vascular inflammation which enhances risk stratification in patients with coronary atherosclerosis [2]. Purpose To characterize the pancoronary and vessel-specific inflammation by means of CTA-derived PCAT in patients with recent SCAD compared with individuals without prior SCAD. Methods Patients with confirmed SCAD referred to a tertiary center between 2017 and 2021 who underwent CTA as a routine cardiac evaluation were included in this retrospective study. Subjects were matched 1:1 with individuals with no prior SCAD who underwent CTA within the same timespan, using the same scanner and imaging protocol, with coronary arteries free of obstructive disease and similar clinical characteristics (Table 1). PCAT was analyzed on end-diastolic CTA reconstructions with a semi-automated software using standard methodology (Figure 1A) [3]. Proximal 40 mm of all major coronary vessels >2 mm in diameter as well as the SCAD-related vessel were included. The primary outcome was pancoronary PCAT defined as mean PCAT in the right (RCA), left anterior descending (LAD) and circumflex (LCX) artery. Secondary outcome was vessel-specific PCAT defined as PCAT in RCA and averaged PCAT in LAD and LCX (PCAT LCA). Results The final cohort comprised 35 patients with recent SCAD (median 6.1 mo. [4.0–16.8] since SCAD, 94.3% female) and 35 patients in the non-SCAD group. Pancoronary PCAT was higher in patients with SCAD compared with non-SCAD group (−80.1 [IQR: −74.5, −84.6] vs. −83.4 HU [−78.7, −88.0], P=0.008) suggestive of increased coronary inflammation. Vessel-specific PCAT was higher for the RCA (−80.7 [−70.4, −86.9] vs. −85.3 [−80.4, −90.6] HU, P<0.001) and borderline higher for the LCA (−79.2 [−73.9, −83.2] vs. −83.4 [−78.0, −88.3] HU, P=0.056) in patients with SCAD compared with non-SCAD respectively (Figure 1B). In patients with SCAD, PCAT in previously dissected vessel was not significantly different from averaged PCAT in unaffected vessels (−78.4 [−73.7, −89.0] vs. −80.9 [−74.9, −83.3], P=0.77; Figure 1C). While PCAT numerically decreased with time since SCAD, the association was not statistically significant when patients were stratified into tertiles according to time from SCAD (Figure 1D). Conclusions Patients with recent SCAD have higher pericoronary adipose tissue attenuation compared with non-SCAD patients suggesting increased perivascular inflammatory activity. This association is not restricted to the dissected vessel, nor reflected in routine serum inflammatory analysis and persists over time. Funding Acknowledgement Type of funding sources: None.

Fast Noninvasive Morphometric Characterization of Free Human Sperms Using Deep Learning.

The selection of high-quality sperms is critical to intracytoplasmic sperm injection, which accounts for 70–80% of in vitro fertilization (IVF) treatments. So far, sperm screening is usually performed manually by clinicians. However, the performance of manual screening is limited in its objectivity, consistency, and efficiency. To overcome these limitations, we have developed a fast and noninvasive three-stage method to characterize morphology of freely swimming human sperms in bright-field microscopy images using deep learning models. Specifically, we use an object detection model to identify sperm heads, a classification model to select in-focus images, and a segmentation model to extract geometry of sperm heads and vacuoles. The models achieve an F1-score of 0.951 in sperm head detection, a z-position estimation error within ±1.5 μm in in-focus image selection, and a Dice score of 0.948 in sperm head segmentation, respectively. Customized lightweight architectures are used for the models to achieve real-time analysis of 200 frames per second. Comprehensive morphological parameters are calculated from sperm head geometry extracted by image segmentation. Overall, our method provides a reliable and efficient tool to assist clinicians in selecting high-quality sperms for successful IVF. It also demonstrates the effectiveness of deep learning in real-time analysis of live bright-field microscopy images.

Three-dimensional characterization of spatial sound fields via acousto-optic sensing

Characterizing audible sound fields over space is at the core of many applications in acoustics and audio technology, including active sound field control, spatial audio, and the experimental analysis of sound radiation. For this purpose, arrays of microphones are commonly deployed across the sound field, with an inter-microphone spacing that depends on the highest frequency studied. Capturing sound fields at mid and high frequencies is nonetheless challenging, as the number of transducers required becomes impractically large and the scattering of sound introduced by the array is often significant. Acousto-optic sensing enables the remote and non-invasive characterization of acoustic fields, and thus it represents an attractive alternative to conventional electro-mechanical transducers in several applications. The phase-shift that laser beams experience as they travel through a pressure field are measured via optical interferometry. The optical measurements are then used to reconstruct the field that originated such phase variations. In this study, we project the measured data into a set of functions suitable to represent sound fields over space. The projection makes it possible to improve the reconstruction accuracy and extrapolate the reconstruction outside the measured region. We demonstrate the method by reconstructing the three-dimensional sound field inside a room using optical data.

Association of electrocardiographic markers with myocardial fibrosis as assessed by cardiac magnetic resonance in different clinical settings.

BACKGROUNDCardiac magnetic resonance (CMR) is a unique tool for non-invasive tissue characterization, especially for identifying fibrosis. AIMTo present the existing data regarding the association of electrocardiographic (ECG) markers with myocardial fibrosis identified by CMR - late gadolinium enhancement (LGE).METHODSA systematic search was performed for identifying the relevant studies in Medline and Cochrane databases through February 2021. In addition, we conducted a relevant search by Reference Citation Analysis (RCA) (https://www.referencecitationanalysis.com).RESULTSA total of 32 studies were included. In hypertrophic cardiomyopathy (HCM), fragmented QRS (fQRS) is related to the presence and extent of myocardial fibrosis. fQRS and abnormal Q waves are associated with LGE in ischemic cardiomyopathy patients, while fQRS has also been related to fibrosis in myocarditis. Selvester score, abnormal Q waves, and notched QRS have also been associated with LGE. Repolarization abnormalities as reflected by increased Tp-Te, negative T-waves, and higher QT dispersion are related to myocardial fibrosis in HCM patients. In patients with Duchenne muscular dystrophy, a significant correlation between fQRS and the amount of myocardial fibrosis as assessed by LGE-CMR was observed. In atrial fibrillation patients, advanced inter-atrial block is defined as P-wave duration ≥ 120 ms, and biphasic morphology in inferior leads is related to left atrial fibrosis.CONCLUSIONMyocardial fibrosis, a reliable marker of prognosis in a broad spectrum of cardiovascular diseases, can be easily understood with an easily applicable ECG. However, more data is needed on a specific disease basis to study the association of ECG markers and myocardial fibrosis as depicted by CMR.

Incident Clinical and Mortality Associations of Myocardial Native T1 in the UK Biobank

BackgroundCardiac magnetic resonance native T1-mapping provides noninvasive, quantitative, and contrast-free myocardial characterization. However, its predictive value in population cohorts has not been studied. ObjectivesThe associations of native T1 with incident events were evaluated in 42,308 UK Biobank participants over 3.17 ± 1.53 years of prospective follow-up. MethodsNative T1-mapping was performed in 1 midventricular short-axis slice using the Shortened Modified Look-Locker Inversion recovery technique (WIP780B) in 1.5-T scanners (Siemens Healthcare). Global myocardial T1 was calculated using an automated tool. Associations of T1 with: 1) prevalent risk factors (eg, diabetes, hypertension, and high cholesterol); 2) prevalent and incident diseases (eg, any cardiovascular disease [CVD], any brain disease, valvular heart disease, heart failure, nonischemic cardiomyopathies, cardiac arrhythmias, atrial fibrillation [AF], myocardial infarction, ischemic heart disease [IHD], and stroke); and 3) mortality (eg, all-cause, CVD, and IHD) were examined. Results are reported as odds ratios (ORs) or HRs per SD increment of T1 value with 95% CIs and corrected P values, from logistic and Cox proportional hazards regression models. ResultsHigher myocardial T1 was associated with greater odds of a range of prevalent conditions (eg, any CVD, brain disease, heart failure, nonischemic cardiomyopathies, AF, stroke, and diabetes). The strongest relationships were with heart failure (OR: 1.41 [95% CI: 1.26-1.57]; P = 1.60 × 10-9) and nonischemic cardiomyopathies (OR: 1.40 [95% CI: 1.16-1.66]; P = 2.42 × 10-4). Native T1 was positively associated with incident AF (HR: 1.25 [95% CI: 1.10-1.43]; P = 9.19 × 10-4), incident heart failure (HR: 1.47 [95% CI: 1.31-1.65]; P = 4.79 × 10-11), all-cause mortality (HR: 1.24 [95% CI: 1.12-1.36]; P = 1.51 × 10-5), CVD mortality (HR: 1.40 [95% CI: 1.14-1.73]; P = 0.0014), and IHD mortality (HR: 1.36 [95% CI: 1.03-1.80]; P = 0.0310). ConclusionsThis large population study demonstrates the utility of myocardial native T1-mapping for disease discrimination and outcome prediction.

Non-Invasive characterisation of renal stones using dual energy CT: A method to differentiate calcium stones

BackgroundNon-invasive DECT based characterization of renal stones using their effective atomic number (Zeff) and the electron density (ρe) in patients. AimThis paper aims to develop a method for in-vivo characterization of renal stone. Differentiation of renal stones in-vivo especially sub types of calcium stones have very important advantage for better judgement of treatment modality. Materials and Methods50 extracted renal stones were scanned ex-vivo using dual energy CT scanner. A method was developed to characterize these renal stones using effective atomic number and electron density obtained from dual energy CT data. The method and formulation developed in ex-vivo experiments was applied in in-vivo study of 50 randomly selected patients of renal stones who underwent dual energy CT scan. ResultsThe developed method was able to characterize Calcium Oxalate Monohydrate (COM) and the combination of COM and Calcium Oxalate Dihydrate (COD) stones non-invasively in patients with a sensitivity of 81% and 83%respectively. The method was also capable of differentiating Uric, Cystine and mixed stones with the sensitivity of 100, 100 and 85.71% respectively. ConclusionThe developed dual energy CT based method was capable of differentiating sub types of calcium stones which is not differentiable on single energy or dual energy CT images.

Ghost-imaging-enhanced noninvasive spectral characterization of stochastic x-ray free-electron-laser pulses

High-intensity ultrashort X-ray free-electron laser (XFEL) pulses are revolutionizing the study of fundamental nonlinear x-ray matter interactions and coupled electronic and nuclear dynamics. To fully exploit the potential of this powerful tool for advanced x-ray spectroscopies, a noninvasive spectral characterization of incident stochastic XFEL pulses with high resolution is a key requirement. Here we present a methodology that combines high-acceptance angle-resolved photoelectron time-of-flight spectroscopy and ghost imaging to enhance the quality of spectral characterization of x-ray free-electron laser pulses. Implementation of this noninvasive high-resolution x-ray diagnostic can greatly benefit the ultrafast x-ray spectroscopy community by functioning as a transparent beamsplitter for applications such as transient absorption spectroscopy in averaging mode as well as covariance-based x-ray nonlinear spectroscopies in single-shot mode where the shot-to-shot fluctuations inherent to a self-amplified spontaneous emission (SASE) XFEL pulse are a powerful asset.

A multi-modality physical phantom for mimicking tumor heterogeneity patterns in PET/CT and PET/MRI.

BackgroundHybrid imaging (e.g., positron emission tomography [PET]/computed tomography [CT], PET/magnetic resonance imaging [MRI]) helps one to visualize and quantify morphological and physiological tumor characteristics in a single study. The noninvasive characterization of tumor heterogeneity is essential for grading, treatment planning, and following‐up oncological patients. However, conventional (CONV) image‐based parameters, such as tumor diameter, tumor volume, and radiotracer activity uptake, are insufficient to describe tumor heterogeneities. Here, radiomics shows promise for a better characterization of tumors. Nevertheless, the validation of such methods demands imaging objects capable of reflecting heterogeneities in multi‐modality imaging. We propose a phantom to simulate tumor heterogeneity repeatably in PET, CT, and MRI.MethodsThe phantom consists of three 50‐ml plastic tubes filled partially with acrylic spheres of S1: 1.6 mm, S2: 50%(1.6 mm)/50%(6.3 mm), or S3: 6.3‐mm diameter. The spheres were fixed to the bottom of each tube by a plastic grid, yielding one sphere free homogeneous region and one heterogeneous (S1, S2, or S3) region per tube. A 3‐tube phantom and its replica were filled with a fluorodeoxyglucose (18F) solution for test–retest measurements in a PET/CT Siemens TPTV and a PET/MR Siemens Biograph mMR system. A number of 42 radiomic features (10 first order and 32 texture features) were calculated for each phantom region and imaging modality. Radiomic features stability was evaluated through coefficients of variation (COV) across phantoms and scans for PET, CT, and MRI. Further, the Wilcoxon test was used to assess the capability of stable features to discriminate the simulated phantom regions.ResultsThe different patterns (S1–S3) did present visible heterogeneity in all imaging modalities. However, only for CT and MRI, a clear visual difference was present between the different patterns. Across all phantom regions in PET, CT, and MR images, 10, 16, and 21 features out of 42 evaluated features in total had a COV of 10% or less. In particular, CONV, histogram, and gray‐level run length matrix features showed high repeatability for all the phantom regions and imaging modalities. Several of repeatable texture features allowed the image‐based discrimination of the different phantom regions (p < 0.05). However, depending on the feature, different pattern discrimination capabilities were found for the different imaging modalities.ConclusionThe proposed phantom appears suitable for simulating heterogeneities in PET, CT, and MRI. We demonstrate that it is possible to select radiomic features for the readout of the phantom. Most of these features had been shown to be relevant in previous clinical studies.