The Pathologically Evolving Aggregation-State of Cells in Cancerous Tissues as Interpreted by Fractal and Multi-Fractal Dispersion Theory in Saturated Porous Formations.

A recent author's fractal fluid-dynamic dispersion theory in porous media has focused on the derivation of the associated nonergodic (or effective) macrodispersion coefficients by a 3-D stochastic Lagrangian approach. As shown by the present study, the Fickian (i.e., the asymptotic constant) component of a properly normalized version of these coefficients exhibits a clearly detectable minimum in correspondence with the same fractal dimension (d ≅ 1.7) that seems to characterize the diffusion-limited aggregation state of cells in advanced stages of cancerous lesion progression. That circumstance suggests that such a critical fractal dimension, which is also reminiscent of the colloidal state of solutions (and may therefore identify the microscale architecture of both living and non-living two-phase systems in state transition conditions) may actually represent a sort of universal nature imprint. Additionally, it suggests that the closed-form analytical solution that was provided for the effective macrodispersion coefficients in fractal porous media may be a reliable candidate as a physically-based descriptor of blood perfusion dynamics in healthy as well as cancerous tissues. In order to evaluate the biological meaningfulness of this specific fluid-dynamic parameter, a preliminary validation is performed by comparison with the results of imaging-based clinical surveys. Moreover, a multifractal extension of the theory is proposed and discussed in view of a perspective interpretative diagnostic utilization.

The Role of Magnetic Resonance Imaging in Cardiomyopathies in the Light of New Guidelines: A Focus on Tissue Mapping.

Cardiomyopathies (CMPs) are a group of myocardial disorders that are characterized by structural and functional abnormalities of the heart muscle. These abnormalities occur in the absence of coronary artery disease (CAD), hypertension, valvular disease, and congenital heart disease. CMPs are an increasingly important topic in the field of cardiovascular diseases due to the complexity of their diagnosis and management. In 2023, the ESC guidelines on cardiomyopathies were first published, marking significant progress in the field. The growth of techniques such as cardiac magnetic resonance imaging (CMR) and genetics has been fueled by the development of multimodal imaging approaches. For the diagnosis of CMPs, a multimodal imaging approach, including CMR, is recommended. CMR has become the standard for non-invasive analysis of cardiac morphology and myocardial function. This document provides an overview of the role of CMR in CMPs, with a focus on tissue mapping. CMR enables the characterization of myocardial tissues and the assessment of cardiac functions. CMR sequences and techniques, such as late gadolinium enhancement (LGE) and parametric mapping, provide detailed information on tissue composition, fibrosis, edema, and myocardial perfusion. These techniques offer valuable insights for early diagnosis, prognostic evaluation, and therapeutic guidance of CMPs. The use of quantitative CMR markers enables personalized treatment plans, improving overall patient outcomes. This review aims to serve as a guide for the use of these new tools in clinical practice.

Swept-source Raman spectroscopy of chemical and biological materials.

Significance: Raman spectroscopy has been used as a powerful tool for chemical analysis, enabling the noninvasive acquisition of molecular fingerprints from various samples. Raman spectroscopy has proven to be valuable in numerous fields, including pharmaceutical, materials science, and biomedicine. Active research and development efforts are currently underway to bring this analytical instrument into the field, enabling in situ Raman measurements for a wider range of applications. Dispersive Raman spectroscopy using a fixed, narrowband source is a common method for acquiring Raman spectra. However, dispersive Raman spectroscopy requires a bulky spectrometer, which limits its field applicability. Therefore, there has been a tremendous need to develop a portable and sensitive Raman system. Aim: We developed a compact swept-source Raman (SS-Raman) spectroscopy system and proposed a signal processing method to mitigate hardware limitations. We demonstrated the capabilities of the SS-Raman spectroscopy by acquiring Raman spectra from both chemical and biological samples. These spectra were then compared with Raman spectra obtained using a conventional dispersive Raman spectroscopy system. Approach: The SS-Raman spectroscopy system used a wavelength-swept source laser (822 to 842 nm), a bandpass filter with a bandwidth of 1.5 nm, and a low-noise silicon photoreceiver. Raman spectra were acquired from various chemical samples, including phenylalanine, hydroxyapatite, glucose, and acetaminophen. A comparative analysis with the conventional dispersive Raman spectroscopy was conducted by calculating the correlation coefficients between the spectra from the SS-Raman spectroscopy and those from the conventional system. Furthermore, Raman mapping was obtained from cross-sections of swine tissue, demonstrating the applicability of the SS-Raman spectroscopy in biological samples. Results: We developed a compact SS-Raman system and validated its performance by acquiring Raman spectra from both chemical and biological materials. Our straightforward signal processing method enhanced the quality of the Raman spectra without incurring high costs. Raman spectra in the range of 900 to 1200 cm-1 were observed for phenylalanine, hydroxyapatite, glucose, and acetaminophen. The results were validated with correlation coefficients of 0.88, 0.84, 0.87, and 0.73, respectively, compared with those obtained from dispersive Raman spectroscopy. Furthermore, we performed scans across the cross-section of swine tissue to generate a biological tissue mapping plot, providing information about the composition of swine tissue. Conclusions: We demonstrate the capabilities of the proposed compact SS-Raman spectroscopy system by obtaining Raman spectra of chemical and biological materials, utilizing straightforward signal processing. We anticipate that the SS-Raman spectroscopy will be utilized in various fields, including biomedical and chemical applications.

Tissue mapping by cardiac magnetic resonance imaging for the prognostication of cardiac amyloidosis: A systematic review and meta-analysis.

BACKGROUND: Cardiac amyloidosis is increasingly recognized as a significant contributor to cardiovascular morbidity and mortality. With the emergence of novel therapies, there is a growing interest in prognostication of patients with cardiac amyloidosis using cardiac magnetic resonance imaging (CMR). In this systematic review and meta-analysis, we aimed to examine the prognostic significance of myocardial native T1 and T2, and extracellular volume (ECV). METHODS: Observational cohort studies or single arms of clinical trials were eligible. MEDLINE, EMBASE and CENTRAL were systematically searched from their respective dates of inception to January 2023. No exclusions were made based on date of publication, study outcomes, or study language. The study populations composed of adult patients (≥18 years old) with amyloid cardiomyopathy. All studies included the use of CMR with and without intravenous gadolinium contrast administration to assess myocardial native T1 mapping, T2 mapping, and ECV in association with the pre-specified primary outcome of all-cause mortality. Data were extracted from eligible primary studies by two independent reviewers and pooled via the inverse variance method using random effects models for meta-analysis. RESULTS: A total of 3852 citations were reviewed. A final nine studies including a total of 955 patients (mean age 65 ± 10 years old, 32% female, mean left ventricular ejection fraction (LVEF) 59 ± 12% and 24% had NYHA class III or IV symptoms) with cardiac amyloidosis [light chain amyloidosis (AL) 50%, transthyretin amyloidosis (ATTR) 49%, other 1%] were eligible for inclusion and suitable for data extraction. All included studies were single centered (seven with 1.5 T MRI scanners, two with 3.0 T MRI scanners) and non-randomized in design, with follow-up spanning from 8 to 64 months (median follow-up = 25 months); 320 patients died during follow-up, rendering a weighted mortality rate of 33% across studies. Compared with patients with AL amyloid, patients with ATTR amyloid had significantly higher mean left ventricular mass index (LVMi) (102 ± 34 g/m2 vs 127 ± 37 g/m2, p = 0.02). N-terminal pro-brain natriuretic peptide (NT-proBNP), troponin T levels, mean native T1 values, ECV and T2 values did not differ between patients with ATTR amyloid and AL amyloid (all p > 0.25). Overall, the hazard ratios for mortality were 1.33 (95% CI = [1.10, 1.60]; p = 0.003; I2 = 29%) for every 60 ms higher T1 time, 1.16 (95% CI = [1.09, 1.23], p < 0.0001; I2 = 76%) for every 3% higher ECV, and 5.23 (95% CI = [2.27, 12.02]; p < 0.0001; I2 = 0%) for myocardial-to-skeletal T2 ratio below the mean (vs above the mean). CONCLUSION: Higher native T1 time and ECV, and lower myocardial to skeletal T2 ratio, on CMR are associated with worse mortality in patients with cardiac amyloidosis. Therefore, tissue mapping using CMR may offer a useful non-invasive technique to monitor disease progression and determine prognosis in patients with cardiac amyloidosis.

Myocardial tissue changes detected by cardiac MRI in a patient with suspected systemic sarcoidosis.

BACKGROUND: The role of cardiac magnetic resonance imaging in the early management of chronic cardiac inflammatory conditions is growing. Our case enlightens the benefit of quantitative mapping in the monitoring and treatment guidance in systemic sarcoidosis. CASE PRESENTATION: We report about a 29-year-old man with an ongoing dyspnea and bihilar lymphadenopathy, suggesting sarcoidosis. Cardiac magnetic resonance showed high mapping values, but no scarring. In follow-ups, cardiac remodeling was noted; cardioprotective treatment normalized cardiac function and mapping markers. Definitive diagnosis was achieved in extracardiac lymphatic tissue during a relapse. CONCLUSION: This case shows the role that mapping markers can play in the detection and treatment at early stage of systemic sarcoidosis.

Reconstructing neural circuits using multiresolution correlated light and electron microscopy.

Correlated light and electron microscopy (CLEM) can be used to combine functional and molecular characterizations of neurons with detailed anatomical maps of their synaptic organization. Here we describe a multiresolution approach to CLEM (mrCLEM) that efficiently targets electron microscopy (EM) imaging to optically characterized cells while maintaining optimal tissue preparation for high-throughput EM reconstruction. This approach hinges on the ease with which arrays of sections collected on a solid substrate can be repeatedly imaged at different scales using scanning electron microscopy. We match this multiresolution EM imaging with multiresolution confocal mapping of the aldehyde-fixed tissue. Features visible in lower resolution EM correspond well to features visible in densely labeled optical maps of fixed tissue. Iterative feature matching, starting with gross anatomical correspondences and ending with subcellular structure, can then be used to target high-resolution EM image acquisition and annotation to cells of interest. To demonstrate this technique and range of images used to link live optical imaging to EM reconstructions, we provide a walkthrough of a mouse retinal light to EM experiment as well as some examples from mouse brain slices.

Limits of Cardiovascular Adaptation During an Extreme Ultramarathon: Insights From Serial Multidimensional, Multiparametric CMR.

Extreme endurance athletic challenges provide unique opportunities to study the cardiovascular system's capacity for structural, functional, and hemodynamic adaptation. The authors present a case of a male subject who ran 2,469 km, with serial multiparametric cardiac magnetic resonance imaging used to demonstrate adaptive and maladaptive alterations in cardiac remodeling and myocardial tissue health. (Level of Difficulty: Advanced.).

Laser desorption tissue imaging with Differential Mobility Spectrometry.

Pathological gross examination of breast carcinoma samples is sometimes laborious. A tissue pre-mapping method could indicate neoplastic areas to the pathologist and enable focused sampling. Differential Mobility Spectrometry (DMS) is a rapid and affordable technology for complex gas mixture analysis. We present an automated tissue laser analysis system for imaging approaches (iATLAS), which utilizes a computer-controlled laser evaporator unit coupled with a DMS gas analyzer. The system is demonstrated in the classification of porcine tissue samples and three human breast carcinomas. Tissue samples from eighteen landrace pigs were classified with the system based on a pre-designed matrix (spatial resolution 1-3 mm). The smoke samples were analyzed with DMS, and tissue classification was performed with several machine learning approaches. Porcine skeletal muscle (n = 1030), adipose tissue (n = 1329), normal breast tissue (n = 258), bone (n = 680), and liver (n = 264) were identified with 86% cross-validation (CV) accuracy with a convolutional neural network (CNN) model. Further, a panel tissue that comprised all five tissue types was applied as an independent validation dataset. In this test, 82% classification accuracy with CNN was achieved. An analogous procedure was applied to demonstrate the feasibility of iATLAS in breast cancer imaging according to 1) macroscopically and 2) microscopically annotated data with 10-fold CV and SVM (radial kernel). We reached a classification accuracy of 94%, specificity of 94%, and sensitivity of 93% with the macroscopically annotated data from three breast cancer specimens. The microscopic annotation was applicable to two specimens. For the first specimen, the classification accuracy was 84% (specificity 88% and sensitivity 77%). For the second, the classification accuracy was 72% (specificity 88% and sensitivity 24%). This study presents a promising method for automated tissue imaging in an animal model and lays foundation for breast cancer imaging.

Noninvasive Cardiac Imaging in Formerly Preeclamptic Women for Early Detection of Subclinical Myocardial Abnormalities: A 2022 Update.

Preeclampsia is a maternal hypertensive disease, complicating 2-8% of all pregnancies. It has been linked to a 2-7-fold increased risk for the development of cardiovascular disease, including heart failure, later in life. A total of 40% of formerly preeclamptic women develop preclinical heart failure, which may further deteriorate into clinical heart failure. Noninvasive cardiac imaging could assist in the early detection of myocardial abnormalities, especially in the preclinical stage, when these changes are likely to be reversible. Moreover, imaging studies can improve our insights into the relationship between preeclampsia and heart failure and can be used for monitoring. Cardiac ultrasound is used to assess quantitative changes, including the left ventricular cavity volume and wall thickness, myocardial mass, systolic and diastolic function, and strain. Cardiac magnetic resonance imaging may be of additional diagnostic value to assess diffuse and focal fibrosis and perfusion. After preeclampsia, sustained elevated myocardial mass along with reduced myocardial circumferential and longitudinal strain and decreased diastolic function is reported. These findings are consistent with the early phases of heart failure, referred to as preclinical (asymptomatic) or B-stage heart failure. In this review, we will provide an up-to-date overview of the potential of cardiac magnetic resonance imaging and echocardiography in identifying formerly preeclamptic women who are at high risk for developing heart failure. The potential contribution to early cardiac screening of women with a history of preeclampsia and the pros and cons of these imaging modalities are outlined. Finally, recommendations for future research are presented.

Advances in MALDI Mass Spectrometry Imaging Single Cell and Tissues.

Compared with conventional optical microscopy techniques, mass spectrometry imaging (MSI) or imaging mass spectrometry (IMS) is a powerful, label-free analytical technique, which can sensitively and simultaneously detect, quantify, and map hundreds of biomolecules, such as peptides, proteins, lipid, and other organic compounds in cells and tissues. So far, although several soft ionization techniques, such as desorption electrospray ionization (DESI) and secondary ion mass spectrometry (SIMS) have been used for imaging biomolecules, matrix-assisted laser desorption/ionization (MALDI) is still the most widespread MSI scanning method. Here, we aim to provide a comprehensive review of MALDI-MSI with an emphasis on its advances of the instrumentation, methods, application, and future directions in single cell and biological tissues.

Genomics- and Peptidomics-Based Discovery of Conserved and Novel Neuropeptides in the American Cockroach.

As a model hemimetabolous insect species and an invasive urban pest that is globally distributed, the American cockroach, Periplaneta americana, is of great interest in both basic and applied research. Previous studies on P. americana neuropeptide identification have been based on biochemical isolation and molecular cloning. In the present study, an integrated approach of genomics- and peptidomics-based discovery was performed for neuropeptide identification in this insect species. First, 67 conserved neuropeptide or neurohormone precursor genes were predicted via an in silico analysis of the P. americana genome and transcriptome. Using a large-scale peptidomic analysis of peptide extracts from four different tissues (the central nervous system, corpora cardiac and corpora allata complex, midgut, and male accessory gland), 35 conserved (predicted) neuropeptides and a potential (novel) neuropeptide were then identified. Subsequent experiments revealed the tissue distribution, sex difference, and developmental patterns of two conserved neuropeptides (allatostatin B and short neuropeptide F) and a novel neuropeptide (PaOGS36577). Our study shows a comprehensive neuropeptidome and detailed spatiotemporal distribution patterns, providing a solid basis for future functional studies of neuropeptides in the American cockroach (data are available via ProteomeXchange with identifier PXD021660).

Transceive phase corrected 2D contrast source inversion-electrical properties tomography.

PURPOSE: To remove the necessity of the tranceive phase assumption for CSI-EPT and show electrical properties maps reconstructed from measured data obtained using a standard 3T birdcage body coil setup. METHODS: The existing CSI-EPT algorithm is reformulated to use the transceive phase rather than relying on the transceive phase assumption. Furthermore, the radio frequency (RF)-shield is numerically implemented to accurately model the RF fields inside the MRI scanner. We verify that the reformulated two-dimensional (2D) CSI-EPT algorithm can reconstruct electrical properties maps given 2D electromagnetic simulations. Afterward, the algorithm is tested with three-dimensional (3D) FDTD simulations to investigate if the 2D CSI-EPT can retrieve the electrical properties for 3D RF fields. Finally, an MR experiment at 3T with a phantom is performed. RESULTS: From the results of the 2D simulations, it is seen that CSI-EPT can reconstruct the electrical properties using MRI accessible quantities. For 3D simulations, it is observed that the electrical properties are underestimated, nonetheless, CSI-EPT has a lower standard deviation than the standard Helmholtz based methods. Finally, the first CSI-EPT reconstructions based on measured data are presented showing comparable accuracy and precision to reconstructions based on simulated data, and demonstrating the feasibility of CSI-EPT. CONCLUSIONS: The CSI-EPT algorithm was rewritten to use MRI accessible quantities. This allows for CSI-EPT to fully exploit the benefits of the higher static magnetic field strengths with a standard quadrature birdcage coil setup.

Pediatric Myocardial T1 and T2 Value Associations with Age and Heart Rate at 1.5 T.

The objective of the study was to determine normal global left ventricular reference values for T1 and T2 in children. This is a retrospective study that included healthy subjects, age 5-19 years, who underwent CMR for the indication of pectus excavatum from 2018 to 2019. Linear regression models were used to determine associations of native T1 and T2 values to heart rate, age, and other CMR parameters. 102 patients with a mean age of 14.0 ± 2.4 years were included (range 5.4-18.8). 87 (85%) were males and 15 (15%) were females. The mean global T1 was 1018 ± 25 ms and the mean T2 was 53 ± 3 ms. T1 was negatively correlated with age (r = - 0.39, p < 0.001) and positively correlated with heart rate (r = 0.32, p < 0.001) by univariate analysis. Multivariable analysis showed that age and heart rate were independently associated with T1. T2 demonstrated a weak negative correlation with age (r = - 0.20, p = 0.047) and no correlation with heart rate. There was no difference in T1 (p = 0.23) or T2 (p = 0.52) between genders. This study reports normal pediatric T1 and T2 values at a 1.5 Tesla scanner. T1 was dependent on age and heart rate, while T2 was less dependent on age with no correlation with heart rate.

Differential mobility spectrometry imaging for pathological applications.

Pathologic examination of clinical tissue samples is time consuming and often does not involve the comprehensive analysis of the whole specimen. Automated tissue analysis systems have potential to make the workflow of a pathologist more efficient and to support in clinical decision-making. So far, these systems have been based on application of mass spectrometry imaging (MSI). MSI provides high fidelity and the results in tissue identification are promising. However, the high cost and need for maintenance limit the adoption of MSI in the clinical setting. Thus, there is a need for new innovations in the field of pathological tissue imaging. In this study, we show that differential ion mobility spectrometry (DMS) is a viable option in tissue imaging. We demonstrate that a DMS-driven solution performs with up to 92% accuracy in differentiating between two grossly distinct animal tissues. In addition, our model is able to classify the correct tissue with 81% accuracy in an eight-class setting. The DMS-based system is a significant innovation in a field dominated by mass-spectrometry-based solutions. By developing the presented platform further, DMS technology could be a cost-effective and helpful tool for automated pathological analysis.

Enhanced Photothermal Treatment Efficacy and Normal Tissue Protection via Vascular Targeted Gold Nanocages.

A major challenge in photothermal treatment is generating sufficient heat to eradicate diseased tissue while sparing normal tissue. Au nanomaterials have shown promise as a means to achieve highly localized photothermal treatment. Toward that end, the synthetic peptide anginex was conjugated to Au nanocages. Anginex binds to galectin-1, which is highly expressed in dividing endothelial cells found primarily in the tumor vasculature. The skin surface temperature during a 10 min laser exposure of subcutaneous murine breast tumors did not exceed 43°C and no normal tissue damage was observed, yet a significant anti-tumor effect was observed when laser was applied 24 h post-injection of targeted nanocages. Untargeted particles showed little effect in immunocompetent, tumor-bearing mice under these conditions. Photoacoustic, photothermal, and ICP-MS mapping of harvested tissue showed distribution of particles near the vasculature throughout the tumor. This uptake pattern within the tumor combined with a minimal overall temperature rise were nonetheless sufficient to induce marked photothermal efficacy and evidence of tumor control. Importantly, this evidence suggests that bulk tumor temperature during treatment does not correlate with treatment outcome, which implies that targeted nanomedicine can be highly effective when closely bound/distributed in and around the tumor endothelium and extensive amounts of direct tumor cell binding may not be a prerequisite of effective photothermal approaches.

Partial volume mapping using magnetic resonance fingerprinting.

Magnetic resonance fingerprinting (MRF) is a quantitative imaging technique that maps multiple tissue properties through pseudorandom signal excitation and dictionary-based reconstruction. The aim of this study is to estimate and validate partial volumes from MRF signal evolutions (PV-MRF), and to characterize possible sources of error. Partial volume model inversion (pseudoinverse) and dictionary-matching approaches to calculate brain tissue fractions (cerebrospinal fluid, gray matter, white matter) were compared in a numerical phantom and seven healthy subjects scanned at 3 T. Results were validated by comparison with ground truth in simulations and ROI analysis in vivo. Simulations investigated tissue fraction errors arising from noise, undersampling artifacts, and model errors. An expanded partial volume model was investigated in a brain tumor patient. PV-MRF with dictionary matching is robust to noise, and estimated tissue fractions are sensitive to model errors. A 6% error in pure tissue T1 resulted in average absolute tissue fraction error of 4% or less. A partial volume model within these accuracy limits could be semi-automatically constructed in vivo using k-means clustering of MRF-mapped relaxation times. Dictionary-based PV-MRF robustly identifies pure white matter, gray matter and cerebrospinal fluid, and partial volumes in subcortical structures. PV-MRF could also estimate partial volumes of solid tumor and peritumoral edema. We conclude that PV-MRF can attribute subtle changes in relaxation times to altered tissue composition, allowing for quantification of specific tissues which occupy a fraction of a voxel.

Advanced cardiac MRI techniques for evaluation of left-sided valvular heart disease.

The most common types of left-sided valvular heart disease (VHD) in the Western world are aortic valve stenosis, aortic valve regurgitation, and mitral valve regurgitation. Comprehensive clinical evaluation entails both hemodynamic analysis and structural as well as functional characterization of the left ventricle. Cardiac magnetic resonance imaging (MRI) is an established diagnostic modality for assessment of left-sided VHD and is progressively gaining ground in modern-day clinical practice. Detailed flow visualization and quantification of flow-related biomarkers in VHD can be obtained using 4D flow MRI, an imaging technique capable of measuring blood flow in three orthogonal directions over time. In addition, recent MRI sequences enable myocardial tissue characterization and strain analysis. In this review we discuss the emerging potential of state-of-the-art MRI including 4D flow MRI, tissue mapping, and strain quantification for the diagnosis and prognosis of left-sided VHD. LEVEL OF EVIDENCE: 1 Technical Efficacy Stage: 1 J. Magn. Reson. Imaging 2018. J. MAGN. RESON. IMAGING 2018;48:318-329.