No abstract

For over two decades photoacoustic imaging has been tested clinically, but successful human trials have been limited. To enable quantitative clinical spectroscopy, the fundamental issues of wavelength-dependent fluence variations and inter-wavelength motion must be overcome. Here we propose a real-time, spectroscopic photoacoustic/ultrasound (PAUS) imaging approach using a compact, 1-kHz rate wavelength-tunable laser. Instead of illuminating tissue over a large area, the fiber-optic delivery system surrounding an US array sequentially scans a narrow laser beam, with partial PA image reconstruction for each laser pulse. The final image is then formed by coherently summing partial images. This scheme enables (i) automatic compensation for wavelength-dependent fluence variations in spectroscopic PA imaging and (ii) motion correction of spectroscopic PA frames using US speckle tracking in real-time systems. The 50-Hz video rate PAUS system is demonstrated in vivo using a murine model of labelled drug delivery.

Background We aimed to analyse the trends in ageism among health care providers and medical students in the Republic of Korea. Methods We used the Fraboni Scale of Ageism (FSA), Relating to Older People Evaluation (ROPE) questionnaire, Anxiety about Aging Scale (AAS), and the Facts on Aging Quiz II to assess ageism in medical students (n=90), nurses (n=114), and physicians (n=83). We grouped health care providers based on the percentage of aged patients (over 65 years) that they treated. Results Compared to the other groups, physicians had more knowledge about aging and the highest and lowest total scores in the FSA and ROPE, respectively. The total FSA scores were negatively correlated with the percentage of aged patients treated. Regarding the ROPE score, negative and positive ageist behaviors were positively correlated with the percentage of aged patients. Conclusions: Ageism and ageist behavior among physicians differed from previous reports and those of the other groups mentioned in the present study. Although physicians had more knowledge of aging, they had expressed a high levels of ageism. However, they did not act ageistically. Health care providers who treat a large number of older patients had minimal ageism but more ageist behavior. These findings indicate that continued education of geriatrics and ageism for medical staff and prospective medical personnel could help improve this situation.

Combinations of novel pulse-echo acquisitions and clutter filtering techniques can improve the sensitivity and the specificity of power Doppler (PD) images, thus reducing the need for exogenous contrast enhancement. We acquire echoes following bursts of Doppler pulse transmissions sparsely applied in regular patterns over long durations. The goal is to increase the sensitivity of the acquisition to slow disorganized patterns of motion from the peripheral blood perfusion. To counter a concomitant increase in clutter signal power, we arrange the temporal echo acquisitions into two data-array axes, combine them with a spatial axis for the tissue region of interest, and apply 3-D singular-value decomposition (SVD) clutter filtering. Successful separation of blood echoes from other echo signal sources requires that we partition the 3-D SVD core tensor. Unfortunately, the clutter and blood subspaces do not completely uncouple in all situations, so we developed a statistical classifier that identifies the core tensor subspace dominated by tissue clutter power. This paper describes an approach to subspace partitioning as required for optimizing PD imaging of peripheral perfusion. The technique is validated using echo simulation, flow-phantom data, and in vivo data from a murine melanoma model. We find that for narrow eigen-bandwidth clutter signals, we can routinely map phantom flows and tumor perfusion signals at speeds less than 3 mL/min. The proposed method is well suited to peripheral perfusion imaging applications.

Pharmacopuncture, or herbal acupuncture, is a new form of therapy derived from combinations of two traditional therapeutic methods, herbal medicine and acupuncture therapy. To compare the efficacy between dexamethasone-pharmacopuncture (DP) and dexamethasone-oral administration (DO), the effect of DP was investigated in murine models. Anti-anaphylactic effects of dexamethasone treatments were investigated in compound 48/80-induced systemic anaphylactic reaction, ear swelling response, and passive cutaneous anaphylaxis (PCA). DP treatment significantly inhibited the compound 48/80-induced systemic anaphylactic reaction, ear swelling response, and PCA. The effects between DP and DO were on a similar level. These results indicate that DP can be used as an alternative method for DO in case of emergency.

Objective: Functional near-infrared spectroscopy (fNIRS) is a neuroimaging technique for monitoring hemoglobin concentration changes in a non-invasive manner. However, subject movements are often significant sources of artifacts. While several methods have been developed for suppressing this confounding noise, the conventional techniques have limitations on optimal selections of model parameters across participants or brain regions. To address this shortcoming, we aim to propose a method based on a deep convolutional neural network (CNN). Approach: The U-net is employed as a CNN architecture. Specifically, large-scale training and testing data are generated by combining variants of hemodynamic response function (HRF) with experimental measurements of motion noises. The neural network is then trained to reconstruct hemodynamic response coupled to neuronal activity with a reduction of motion artifacts. Main results: Using extensive analysis, we show that the proposed method estimates the task-related HRF more accurately than the existing methods of wavelet decomposition and autoregressive models. Specifically, the mean squared error and variance of HRF estimates, based on the CNN, are the smallest among all methods considered in this study. These results are more prominent when the semi-simulated data contains variants of shapes and amplitudes of HRF. Significance: The proposed CNN method allows for accurately estimating amplitude and shape of HRF with significant reduction of motion artifacts. This method may have a great potential for monitoring HRF changes in real-life settings that involve excessive motion artifacts.

Objective To compare a deep learning-based reconstruction (DLR) algorithm for pediatric abdominopelvic computed tomography (CT) with filtered back projection (FBP) and iterative reconstruction (IR) algorithms. Materials and Methods Post-contrast abdominopelvic CT scans obtained from 120 pediatric patients (mean age ± standard deviation, 8.7 ± 5.2 years; 60 males) between May 2020 and October 2020 were evaluated in this retrospective study. Images were reconstructed using FBP, a hybrid IR algorithm (ASiR-V) with blending factors of 50% and 100% (AV50 and AV100, respectively), and a DLR algorithm (TrueFidelity) with three strength levels (low, medium, and high). Noise power spectrum (NPS) and edge rise distance (ERD) were used to evaluate noise characteristics and spatial resolution, respectively. Image noise, edge definition, overall image quality, lesion detectability and conspicuity, and artifacts were qualitatively scored by two pediatric radiologists, and the scores of the two reviewers were averaged. A repeated-measures analysis of variance followed by the Bonferroni post-hoc test was used to compare NPS and ERD among the six reconstruction methods. The Friedman rank sum test followed by the Nemenyi-Wilcoxon-Wilcox all-pairs test was used to compare the results of the qualitative visual analysis among the six reconstruction methods. Results The NPS noise magnitude of AV100 was significantly lower than that of the DLR, whereas the NPS peak of AV100 was significantly higher than that of the high- and medium-strength DLR ( p < 0.001). The NPS average spatial frequencies were higher for DLR than for ASiR-V ( p < 0.001). ERD was shorter with DLR than with ASiR-V and FBP ( p < 0.001). Qualitative visual analysis revealed better overall image quality with high-strength DLR than with ASiR-V ( p < 0.001). Conclusion For pediatric abdominopelvic CT, the DLR algorithm may provide improved noise characteristics and better spatial resolution than the hybrid IR algorithm.

Interreader agreement among the 3 readers and intermethod agreement among the 4 protocols were calculated using Fleiss κ analysis. ACL, anterior cruciate ligament; P2, 2-fold parallel acquisition technique; DL with P2/4S2, deep learning application in P2/4 with 2-fold simultaneous multislice imaging.