Reorganization of H3K9me heterochromatin leads to neuronal impairment via the cascading destruction of the KDM3B-centered epigenomic network.

Histone H3K9 methylated heterochromatin silences repetitive non-coding sequences and lineage-specific genes during development, but how tissue-specific genes escape from heterochromatin in differentiated cells is unclear. Here, we examine age-dependent transcriptomic profiling of terminally differentiated mouse retina to identify epigenetic regulators involved in heterochromatin reorganization. The single-cell RNA sequencing analysis reveals a gradual downregulation of Kdm3b in cone photoreceptors during aging. Disruption of Kdm3b (Kdm3b +/- ) of 12-month-old mouse retina leads to the decreasing number of cones via apoptosis, and it changes the morphology of cone ribbon synapses. Integration of the transcriptome with epigenomic analysis in Kdm3b +/- retinas demonstrates gains of heterochromatin features in synapse assembly and vesicle transport genes that are downregulated via the accumulation of H3K9me1/2. Contrarily, losses of heterochromatin in apoptotic genes exacerbated retinal neurodegeneration. We propose that the KDM3B-centered epigenomic network is crucial for balancing of cone photoreceptor homeostasis via the modulation of gene set-specific heterochromatin features during aging.

3D Multiparametric Photoacoustic Computed Tomography of Primary and Metastatic Tumors in Living Mice.

Photoacoustic computed tomography (PACT), an emerging imaging modality in preclinical cancer research, can provide multiparametric 3D information about structures, physiological functions, and pharmacokinetics. Here, we demonstrate the use of high-definition 3D multiparametric PACT imaging of both primary and metastatic tumors in living mice to noninvasively monitor angiogenesis, carcinogenesis, hypoxia, and pharmacokinetics. The high-definition PACT system with a 1024-element hemispherical ultrasound transducer array provides an isotropic spatial resolution of 380 µm, an effective volumetric field-of-view of 12.8 mm × 12.8 mm × 12.8 mm without scanning, and an acquisition time of <30 s for a whole mouse body. Initially, we monitor the structural progression of the tumor microenvironment (e.g., angiogenesis and vessel tortuosity) after tumor cell inoculation. Then, we analyze the change in oxygen saturation of the tumor during carcinogenesis, verifying induced hypoxia in the tumor's core region. Finally, the whole-body pharmacokinetics are photoacoustically imaged after intravenous injection of micelle-loaded IR780 dye, and the in vivo PACT results are validated in vivo and ex vivo by fluorescence imaging. By employing the premium PACT system and applying multiparametric analyses to subcutaneous primary tumors and metastatic liver tumors, we demonstrate that this PACT system can provide multiparametric analyses for comprehensive cancer research.

Robust Ensemble of Two Different Multimodal Approaches to Segment 3D Ischemic Stroke Segmentation Using Brain Tumor Representation Among Multiple Center Datasets.

Ischemic stroke segmentation at an acute stage is vital in assessing the severity of patients' impairment and guiding therapeutic decision-making for reperfusion. Although many deep learning studies have shown attractive performance in medical segmentation, it is difficult to use these models trained on public data with private hospitals' datasets. Here, we demonstrate an ensemble model that employs two different multimodal approaches for generalization, a more effective way to perform on external datasets. First, after we jointly train a segmentation model on diffusion-weighted imaging (DWI) and apparent diffusion coefficient (ADC) MR modalities, the model is inferred on the DWI images. Second, a channel-wise segmentation model is trained by concatenating the DWI and ADC images as input, and then is inferred using both MR modalities. Before training with ischemic stroke data, we utilized BraTS 2021, a public brain tumor dataset, for transfer learning. An extensive ablation study evaluates which strategy learns better representations for ischemic stroke segmentation. In our study, nnU-Net well-known for robustness is selected as our baseline model. Our proposed method is evaluated on three different datasets: the Asan Medical Center (AMC) I and II, and the 2022 Ischemic Stroke Lesion Segmentation (ISLES). Our experiments are widely validated over a large, multi-center, and multi-scanner dataset with a huge amount of 846 scans. Not only stroke lesion models can benefit from transfer learning using brain tumor data, but combining the MR modalities using different training schemes also highly improves segmentation performance. The method achieved a top-1 ranking in the ongoing ISLES'22 challenge and performed particularly well on lesion-wise metrics of interest to neuroradiologists, achieving a Dice coefficient of 78.69% and a lesion-wise F1 score of 82.46%. Also, the method was relatively robust on the AMC I (Dice, 60.35%; lesion-wise F1, 68.30%) and II (Dice; 74.12%; lesion-wise F1, 67.53%) datasets in different settings. The high segmentation accuracy of our proposed method could improve radiologists' ability to detect ischemic stroke lesions in MRI images. Our model weights and inference code are available on https://github.com/MDOpx/ISLES22-model-inference .

Nonlinear beamforming for intracardiac echocardiography: a comparative study.

Intracardiac echocardiography (ICE) enables cardiac imaging with a wide field of view, deep imaging depth, and high frame rate during surgery. However, strong sidelobe and grating lobe artifacts created by the ultra-compact transducer degrade its image quality, making diagnosis and monitoring of treatment difficult. Conventionally, aperture apodization algorithms are often used to suppress sidelobe and grating lobe artifacts at the expense of lateral resolution, which is undesirable in ICE. In this study, we present comparative results of the beamforming methods specifically in ICE application. We demonstrate and compare five nonlinear beamforming algorithms in ICE: nonlinear pth root delay and sum (NL-p-DAS), nonlinear pth root spectral magnitude scaling (NL-p-SMS), delay-and-sum with coherence factors (DAS + SCF), delay and sum with apodization (DAS + apodization) and delay and sum (DAS). Phantom and ex-vivo experiment compare the performance of each algorithm in static and dynamic conditions. DAS + SCF shows the best lateral resolution, and all four algorithms improve the image contrast and sidelobe suppression over conventional DAS. NL-p-SMS stands out for the best axial resolution and suppression of grating lobe artifacts. For motion tracking, NL-p-SMS shows better temporal resolution than other methods. Overall, all the beamforming algorithms other than DAS showed improved image quality. Among them, NL-p-SMS, which has a high temporal resolution, showed the potential for providing more accurate information regards movement tracking. Supplementary Information: The online version contains supplementary material available at 10.1007/s13534-024-00352-9.

Video-rate endocavity photoacoustic/harmonic ultrasound imaging with miniaturized light delivery.

Significance: Endocavity ultrasound (US) imaging is a frequently employed diagnostic technique in gynecology and urology for the assessment of male and female genital diseases that present challenges for conventional transabdominal imaging. The integration of photoacoustic (PA) imaging with clinical US imaging has displayed promising outcomes in clinical research. Nonetheless, its application has been constrained due to size limitations, restricting it to spatially confined locations such as vaginal or rectal canals. Aim: This study presents the development of a video-rate (20 Hz) endocavity PA/harmonic US imaging (EPAUSI) system. Approach: The approach incorporates a commercially available endocavity US probe with a miniaturized laser delivery unit, comprised of a single large-core fiber and a line beamshaping engineered diffuser. The system facilitates real-time image display and subsequent processing, including angular energy density correction and spectral unmixing, in offline mode. Results: The spatial resolutions of the concurrently acquired PA and harmonic US images were measured at 318 µm and 291 µm in the radial direction, respectively, and 1.22 deg and 1.50 deg in the angular direction, respectively. Furthermore, the system demonstrated its capability in multispectral PA imaging by successfully distinguishing two clinical dyes in a tissue-mimicking phantom. Its rapid temporal resolution enabled the capture of kinetic dye perfusion into an ex vivo porcine ovary through the depth of porcine uterine tissue. EPAUSI proved its clinical viability by detecting pulsating hemodynamics in the male rat's prostate in vivo and accurately classifying human blood vessels into arteries and veins based on sO2 measurements. Conclusions: Our proposed EPAUSI system holds the potential to unveil previously overlooked indicators of vascular alterations in genital cancers or endometriosis, addressing pressing requirements in the fields of gynecology and urology.

X-ray free-electron laser induced acoustic microscopy (XFELAM).

The X-ray free-electron laser (XFEL) has remarkably advanced X-ray imaging technology and enabled important scientific achievements. The XFEL's extremely high power, short pulse width, low emittance, and high coherence make possible such diverse imaging techniques as absorption/emission spectroscopy, diffraction imaging, and scattering imaging. Here, we demonstrate a novel XFEL-based imaging modality that uses the X-ray induced acoustic (XA) effect, which we call X-ray free-electron laser induced acoustic microscopy (XFELAM). Initially, we verified the XA effect by detecting XA signals from various materials, then we validated the experimental results with simulation outcomes. Next, in resolution experiments, we successfully imaged a patterned tungsten target with drilled various-sized circles at a spatial resolution of 7.8 ± 5.1 µm, which is the first micron-scale resolution achieved by XA imaging. Our results suggest that the novel XFELAM can expand the usability of XFEL in various areas of fundamental scientific research.

An ultrasensitive and broadband transparent ultrasound transducer for ultrasound and photoacoustic imaging in-vivo.

Transparent ultrasound transducers (TUTs) can seamlessly integrate optical and ultrasound components, but acoustic impedance mismatch prohibits existing TUTs from being practical substitutes for conventional opaque ultrasound transducers. Here, we propose a transparent adhesive based on a silicon dioxide-epoxy composite to fabricate matching and backing layers with acoustic impedances of 7.5 and 4-6 MRayl, respectively. By employing these layers, we develop an ultrasensitive, broadband TUT with 63% bandwidth at a single resonance frequency and high optical transparency ( > 80%), comparable to conventional opaque ultrasound transducers. Our TUT maximises both acoustic power and transfer efficiency with maximal spectrum flatness while minimising ringdowns. This enables high contrast and high-definition dual-modal ultrasound and photoacoustic imaging in live animals and humans. Both modalities reach an imaging depth of > 15 mm, with depth-to-resolution ratios exceeding 500 and 370, respectively. This development sets a new standard for TUTs, advancing the possibilities of sensor fusion.