Monodisperse versus polydisperse ultrasound contrast agents: nonlinear response, sensitivity, and deep tissue imaging potential

Monodisperse microbubble ultrasound contrast agents have been proposed to further increase the signal-to-noise-ratio of contrast enhanced ultrasound imaging. Here, the sensitivity of a polydisperse preclinical agent was compared experimentally to that of its size- and acoustically-sorted derivatives by using narrowband pressure- and frequency-dependent scattering and attenuation measurements. The sorted monodisperse agents showed up to a two orders of magnitude increase in sensitivity, i.e. in the average scattering cross-section per bubble. Moreover, we demonstrate here, for the first time, that the highly nonlinear response of acoustically sorted microbubbles can be exploited to confine scattering and attenuation to the focal region of ultrasound fields used in clinical imaging. This property is a result of minimal prefocal scattering and attenuation and can be used to minimize shadowing effects in deep tissue imaging. Moreover, it potentially allows for more localized therapy using microbubbles through the spatial control of resonant microbubble oscillations

ULTRA HIGH FIELD MR CAROTID VESSEL WALL IMAGING: COMPARISON BETWEEN 7T AND 3T

Cardiovascular Aspects of Radiolog

A review of machine learning applications for the proton MR spectroscopy workflow

This literature review presents a comprehensive overview of machine learning (ML) applications in proton MR spectroscopy (MRS). As the use of ML techniques in MRS continues to grow, this review aims to provide the MRS community with a structured overview of the state-of-the-art methods. Specifically, we examine and summarize studies published between 2017 and 2023 from major journals in the MR field. We categorize these studies based on a typical MRS workflow, including data acquisition, processing, analysis, and artificial data generation. Our review reveals that ML in MRS is still in its early stages, with a primary focus on processing and analysis techniques, and less attention given to data acquisition. We also found that many studies use similar model architectures, with little comparison to alternative architectures. Additionally, the generation of artificial data is a crucial topic, with no consistent method for its generation. Furthermore, many studies demonstrate that artificial data suffers from generalization issues when tested on in vivo data. We also conclude that risks related to ML models should be addressed, particularly for clinical applications. Therefore, output uncertainty measures and model biases are critical to investigate. Nonetheless, the rapid development of ML in MRS and the promising results from the reviewed studies justify further research in this field.</p

Systemic LRG1 Expression in Melanoma is Associated with Disease Progression and Recurrence

The response rates upon neoadjuvant immune checkpoint blockade (ICB) in stage III melanoma are higher as compared with stage IV disease. Given that successful ICB depends on systemic immune response, we hypothesized that systemic immune suppression might be a mechanism responsible for lower response rates in late-stage disease, and also potentially with disease recurrence in early-stage disease. Plasma and serum samples of cohorts of patients with melanoma were analyzed for circulating proteins using mass spectrometry proteomic profiling and Olink proteomic assay. A cohort of paired samples of patients with stage III that progressed to stage IV disease (n = 64) was used to identify markers associated with higher tumor burden. Baseline patient samples from the OpACIN-neo study (n = 83) and PRADO study (n = 49; NCT02977052) were used as two independent cohorts to analyze whether the potential identified markers are also associated with disease recurrence after neoadjuvant ICB therapy. When comparing baseline proteins overlapping between patients with progressive disease and patients with recurrent disease, we found leucine-rich alpha-2-glycoprotein 1 (LRG1) to be associated with worse prognosis. Especially nonresponder patients to neoadjuvant ICB (OpACIN-neo) with high LRG1 expression had a poor outcome with an estimated 36-month event-free survival of 14% as compared with 83% for nonresponders with a low LRG1 expression (P = 0.014). This finding was validated in an independent cohort (P = 0.0021). LRG1 can be used as a biomarker to identify patients with high risk for disease progression and recurrence, and might be a target to be combined with neoadjuvant ICB. Significance: LRG1 could serve as a potential target and as a biomarker to identify patients with high risk for disease recurrence, and consequently benefit from additional therapies and intensive follow-up

Systemic LRG1 Expression in Melanoma is Associated with Disease Progression and Recurrence

UNLABELLED: The response rates upon neoadjuvant immune checkpoint blockade (ICB) in stage III melanoma are higher as compared with stage IV disease. Given that successful ICB depends on systemic immune response, we hypothesized that systemic immune suppression might be a mechanism responsible for lower response rates in late-stage disease, and also potentially with disease recurrence in early-stage disease. Plasma and serum samples of cohorts of patients with melanoma were analyzed for circulating proteins using mass spectrometry proteomic profiling and Olink proteomic assay. A cohort of paired samples of patients with stage III that progressed to stage IV disease (n = 64) was used to identify markers associated with higher tumor burden. Baseline patient samples from the OpACIN-neo study (n = 83) and PRADO study (n = 49; NCT02977052) were used as two independent cohorts to analyze whether the potential identified markers are also associated with disease recurrence after neoadjuvant ICB therapy. When comparing baseline proteins overlapping between patients with progressive disease and patients with recurrent disease, we found leucine-rich alpha-2-glycoprotein 1 (LRG1) to be associated with worse prognosis. Especially nonresponder patients to neoadjuvant ICB (OpACIN-neo) with high LRG1 expression had a poor outcome with an estimated 36-month event-free survival of 14% as compared with 83% for nonresponders with a low LRG1 expression (P = 0.014). This finding was validated in an independent cohort (P = 0.0021). LRG1 can be used as a biomarker to identify patients with high risk for disease progression and recurrence, and might be a target to be combined with neoadjuvant ICB. SIGNIFICANCE: LRG1 could serve as a potential target and as a biomarker to identify patients with high risk for disease recurrence, and consequently benefit from additional therapies and intensive follow-up

Human voltage-gated Na+ and K+ channel properties underlie sustained fast AP signaling

Human cortical pyramidal neurons are large, have extensive dendritic trees, and yet have unexpectedly fast input-output properties: Rapid subthreshold synaptic membrane potential changes are reliably encoded in timing of action potentials (APs). Here, we tested whether biophysical properties of voltage-gated sodium (Na+) and potassium (K+) currents in human pyramidal neurons can explain their fast input-output properties. Human Na+ and K+ currents exhibited more depolarized voltage dependence, slower inactivation, and faster recovery from inactivation compared with their mouse counterparts. Computational modeling showed that despite lower Na+ channel densities in human neurons, the biophysical properties of Na+ channels resulted in higher channel availability and contributed to fast AP kinetics stability. Last, human Na+ channel properties also resulted in a larger dynamic range for encoding of subthreshold membrane potential changes. Thus, biophysical adaptations of voltage-gated Na+ and K+ channels enable fast input-output properties of large human pyramidal neurons