Image Volume Research Articles

Advancing yeast cell analysis: A cryomethod for serial block-face scanning electron microscopy imaging in mitochondrial morphology studies.

Conventional Transmission Electron Microscopy analysis of biological samples often provides limited insights due to its inherent two-dimensional (2D) nature. This limitation hampers a comprehensive understanding of the three-dimensional (3D) complexity of cellular structures, occasionally leading to misinterpretations. Serial block-face scanning electron microscopy emerges as a powerful method for acquiring high-resolution 3D images of cellular volumes. By iteratively removing ultrathin sample sections and capturing images of each newly exposed surface, Serial block-face scanning electron microscopy allows for the meticulous reconstruction of a comprehensive 3D volume. In this study, we investigate the 3D architecture of altered mitochondrial morphologies in Saccharomyces cerevisiae using Serial block-face scanning electron microscopy imaging. We have developed a novel cryomethod based on plunge freezing and a dedicated freeze-substitution protocol. This protocol enhances ultrastructural preservation enabling a more accurate understanding of mitochondrial defects observed in 2D electron microscopy. Our findings underscore the utility of Serial block-face scanning electron microscopy coupled with optimized sample preparation techniques in elucidating complex cellular structures in 3D.

Use of Three-Dimensional (3D) Airway Modeling and Virtual Reality for Diagnosis, Communication, and Surgical Planning of Complex Airway Stenosis.

We hypothesized that a method to segment human airways from clinical cases and import them into a case presentation environment in Virtual Reality (VR)could be developed to model and visualize complex airway stenosis for efficient surgical planning. One normal and two pathological airways modeled from CT scans at a slice thickness of 0.625 mm were processed. A multidisciplinary team composed of airway surgeons, VR engineers, educators, and radiologists collaborated to create a clinically relevant VR rendering and explanatory Narrations of the three clinical cases. Segmentation and postprocessing were completed in the Mimics Innovation Suite v24 from Materialize. Structures were segmented from the level of bifurcation of common carotid arteries to the level of bifurcation of the main bronchi, including cartilaginous and bony airway structures, vessels, and soft tissues. They were then postprocessed into 3D image volumes and imported into syGlass (IstoVisio Inc.), a VR software. Direct visualization and free manipulation of these 3D airway models within the VR environment provided improved geometrical and anatomical details compared to traditional two-dimensional (2D) CT. Then, specialized presentation and active learning tools developed for scientific communication using the VR environment permitted the creation of VR Narrations to explain pathological cases. The method to segment human airways from clinical cases used in this paper, combined with intuitive VR tools to overlay segmentation and image data in an active learning environment, shows potential in the use of 3D airway modeling and VR in clinical practice for the description and surgical planning of complex airways. Further work is needed to validate the use of these models in clinical practice and patient education. Level 4.

Safety and therapeutic potential of allogeneic adipose-derived stem cell spray transplantation in ischemic cardiomyopathy: a phase I clinical trial

BackgroundIschemic cardiomyopathy, characterized by coronary artery atherosclerosis, impairs the myocardial tissue. Coronary artery bypass grafting (CABG) is commonly used to revascularize affected areas and improve patient survival rates; however, it can fail to enhance cardiac function. Impaired capillary blood flow may obstruct functional recovery, prompting interest in treatments, such as angiogenic factor administration. Adipose-derived stem cells (ADSCs), which are known for immune evasion, have shown the potential to construct capillary networks and improve myocardial function. This clinical trial aimed to evaluate the safety and efficacy of ADSC spray therapy combined with CABG.MethodsThis single-center, randomized, double-blind study involved patients with ischemic cardiomyopathy who were scheduled for CABG and who had a left ventricular ejection fraction ≤ 40%. The participants were randomized to receive CABG as well as ADSC spray therapy or placebo. The primary endpoints were safety, changes in late gadolinium-enhanced (LGE) magnetic resonance imaging (MRI) volumes, and feasibility. The secondary endpoints included left ventricular function, exercise tolerance, and heart failure symptoms.ResultsSeven patients were enrolled; of them, six were randomized to receive ADSC therapy (n = 3) or placebo (n = 3). The procedure was successfully completed with minimal adverse events. One patient in the ADSC group developed pleural effusion that was resolved with drainage. The LGE-MRI volumes decreased in the ADSC group but remained unchanged in the placebo group. Improvements in left ventricular function and exercise tolerance were noted in the ADSC group, with heart failure symptoms improving to New York Heart Association class I. In contrast, the placebo group showed no significant changes, with one patient experiencing worsening symptoms.ConclusionsADSC spray therapy combined with CABG demonstrated safety and efficacy at enhancing cardiac function. ADSC likely contributes to capillary network reconstruction, thereby augmenting the benefits of CABG. Future phase II and III trials are warranted to confirm its therapeutic efficacy and long-term outcomes. This novel approach represents a significant advancement in the treatment of ischemic cardiomyopathy and offers a viable strategy for improving myocardial function and patient prognosis.Trial registration This study was registered with the Japan Registry of Clinical Trials (jRCT2053190103) and ClinicalTrials.gov (NCT04695522)Graphical

White matter hyperintensities are independently associated with systemic vascular aging and cerebrovascular dysfunction.

In the Oxford Haemodynamic Adaptation to Reduce Pulsatility trial (OxHARP), sildenafil increased cerebrovascular reactivity but did not reduce cerebral pulsatility, a marker of vascular aging. This analysis of OxHARP tested whether these potentially causative mechanisms were independently associated with severity of white matter hyperintensities (WMH). To determine independence of the relationship between severity of white matter hyperintensities with both cerebral pulsatility and cerebrovascular reactivity in the same population. OxHARP was a double-blind, randomised, placebo-controlled, crossover trial of phosphodiesterase inhibitors in patients with mild-moderate WMH and previous minor cerebrovascular events. It determined effects on cerebrovascular pulsatility and reactivity on transcranial ultrasound, and reactivity on MRI. Associations were determined between baseline ultrasound measures, and averaged MRI measures across follow-up, with severity of WMH on clinical imaging (Fazekas or modified Blennow scores) and WMH volume in the MRI substudy, by ordinal and linear regression. In 75/75 patients (median 70 years, 78% male), cerebral pulsatility was associated with age (p<0.001) whereas reactivity on ultrasound was not (p=0.29). Severity of WMH in all participants was independently associated with decreased cerebrovascular reactivity and increased cerebral pulsatility (pulsatility p=0.016; reactivity p=0.03), with a trend to a synergistic interaction (p=0.075). Reactivity on ultrasound was still associated with WMH after further adjustment for age (p=0.017) but pulsatility was not (p=0.31). Volume of WMH in the MRI substudy was also independently associated with both markers on ultrasound (pulsatility p=0.005; reactivity p=0.029), and was associated with reduced cerebrovascular reactivity within WMH on MRI (p<0.0001). WMH are independently associated with cerebral pulsatility and reactivity, representing complementary potential disease mechanisms and treatment targets. clinicaltrials.org: https://classic.clinicaltrials.gov/ct2/show/NCT03855332.

First linac-mounted photon counting detector for image guided radiotherapy: Planar image quality characterization.

Image guided radiotherapy (IGRT) with cone-beam computed tomography (CBCT) is limited by the sub-optimal soft-tissue contrast and spatial resolution of energy-integrating flat panel detectors (FPDs) which produce quasi-quantitative CT numbers. Spectral CT with high resolution photon-counting detectors (PCDs) could improve tumor delineation by enhancing the soft-tissue contrast, spatial resolution, dose-efficiency, and CT numberaccuracy. This study presents the first linac-mounted PCD. On the journey to developing spectral cone-beam CT for IGRT, the planar image quality of a linac-mounted PCD is first fundamentally characterized and compared to an FPD in terms of the 2D spatial resolution, noise, andcontrast. A Medipix3RX-based PCD was mounted to the kV FPD of an x-ray volume imaging (XVI) system on an Elekta linac and the PCD acquisition was synchronized with the pulsed kV source. The energy calibration of the Medipix3RX was determined with various radioisotope gamma emissions up to 60 keV. To compare the 2D spatial resolution and noise between the PCD and FPD, the pre-sampling modulation transfer function (MTF) and normalized noise power spectrum (NPS) were measured using an RQA5 spectrum and a fluoroscopy phantom was imaged to determine the limiting resolution of line pairs. Spectral planar images of phantom inserts containing two different concentrations of calcium (60 and 240 mg/cc) and iodine (5 and 15 mg/cc) were optimally energy weighted to maximize the contrast using tube voltages of 60, 80, 100, and 120 kV. To account for drifts in the sensor temperature, the PCD was dynamically translated in and out of the insert shadow during acquisitions to obtain flat field corrections per frame. The raw contrast of the resultant planar images was compared to the energy-integrating FPD. The energy calibration of the Medipix3RX was observed to be linear up to 60 keV. The limiting resolution observed on the fluoroscopy phantom was 2 lp/mm for the FPD and 5 lp/mm for the PCD. The pre-sampling MTF was higher across all frequencies comparing the PCD to the FPD. The normalized NPS of the PCD did not vary with frequency, whereas the spectrum for the FPD decreased monotonically and was lower than the PCD noise power across most of the spatial frequency range studied due to optical light spreading. Optimal energy weights were applied to the dynamically acquired PCD images and the raw contrast of the 60 mg/cc calcium insert increased by factors of and at 60 and 120 kV respectively compared to theFPD. A Medipix3RX-based PCD was successfully integrated with the kilovoltage imaging system on an Elekta linac. The initial planar image quality characterization indicated improvements in the MTF and energy-weighted contrast compared to the FPD. Future work will focus on obtaining linac-mounted spectral CBCT images with a translate-rotate geometry, however this initial study indicates that variations in the PCD sensor response during acquisitions must be addressed to realise the full potential of linac-mounted spectralCBCT.

Morphological Changes of Liver Among Post-Fontan Surgery Patients

Abstract Purpose Liver screening and longitudinal study of Fontan Associated Liver Diseases (FALD) is essential to identifying hepatomegaly and how hepatomegaly relates to various stages of liver fibrosis. In this study, we investigated longitudinal liver shape changes and liver stiffness in a cohort of patients with Fontan Associated Liver Disease. Methods We used 170 image volumes of 40 Fontan stage 3 completion patients. We also used 65 computed tomography images of healthy individuals from three datasets for comparison. Thirteen radiomic shape features of Fontan patients and individuals with a healthy liver were extracted and analyzed longitudinally. We studied correlations among features, liver spleen ratio, and liver stiffness with shape features. Results The enlargement of the liver, along with all shape features, was observed in all post-surgery intervals related to hepatomegaly and fibrosis. The shape features of healthy individuals and Fontan cases differ significantly in the longitudinal analysis and in the liver-spleen ratio. There is a positive correlation among body mass index, body surface area, age, Fontan surgery years, and liver stiffness. Conclusion The changes in shape features between Fontan patients and healthy subjects are statistically significant, which shows the relation for hepatomegaly and liver fibrosis. Accurate delineation of these features with artificial intelligence-based segmentation could serve as a valuable adjunct for the clinical follow-up of Fontan patients.

A novel approach for the early prediction and prevention of placenta accreta spectrum and severe peripartum hemorrhage in patients with complete placenta previa: leveraging three-dimensional placental topography, cervical length, and dilatation parameters on magnetic resonance imaging

BackgroundTo evaluate the reliability of placental volume and other magnetic resonance imaging (MRI) markers for predicting placenta accreta spectrum and severe peripartum hemorrhage in patients with complete placenta previa.MethodsThis single-center retrospective cohort study was conducted at a tertiary care facility and included 216 pregnant women diagnosed with complete placenta previa. Two radiologists, blinded to each other’s assessments, independently evaluated the prenatal placental magnetic resonance imaging (pMRI) findings of 150 singleton pregnancies that met the inclusion criteria and were delivered in the third trimester. The three-dimensional placental volume (from the S1 and S2 sectors), cervical canal length (CCL), and degree of cervical canal dilatation (CCD) were compared with clinical and pathological findings. Univariate and multivariate logistic regression analyses identified risk factors for placenta accreta spectrum (PAS) and severe peripartum hemorrhage (SPPH). Receiver operating characteristic (ROC) curve analysis determined the cutoff values of significant predictors.ResultsUnivariate analysis revealed significant risk factors for PAS, including decreased cervical canal length (odds ratio [OR] = 1.330, p < 0.001), increased cervical canal dilation (OR = 1.869, p < 0.001), decreased S1 volume (OR = 1.008, p < 0.001), and increased S2 volume (OR = 1.008, p < 0.001). Multivariate analysis confirmed that cervical canal length was an independent risk factor (odds ratio [OR] = 1.253, p = 0.03). Significant predictors of severe peripartum hemorrhage included decreased cervical canal length (odds ratio [OR] = 0.406, p = 0.006), increased cervical canal dilatation (OR = 3.22, p < 0.001), decreased S1 volume (OR = 1.079, p = 0.017), and increased S2 volume (OR = 1.032, p < 0.001), all of which were confirmed as independent risk factors. ROC analysis demonstrated high precision for MRI markers, with area under the curve values above 0.8 for critical predictors of PAS and severe peripartum hemorrhage, confirming their reliability (all p < 0.001).ConclusionThis study emphasizes the pivotal role of three-dimensional placental volume measurements in the S1 and S2 sectors, along with cervical canal length and dilation, in predicting PAS and severe peripartum hemorrhage in patients with complete placenta previa. Integrating these advanced MRI markers into prenatal care can enhance early detection, improve clinical decision-making, and ultimately improve maternal and fetal outcomes.

HyperGAN: A Hyperspectral Image Fusion Approach Based on Generative Adversarial Networks

The objective of hyperspectral pansharpening is to fuse low-resolution hyperspectral images (LR-HSI) with corresponding panchromatic (PAN) images to generate high-resolution hyperspectral images (HR-HSI). Despite advancements in hyperspectral (HS) pansharpening using deep learning, the rich spectral details and large data volume of HS images place higher demands on models for effective spectral extraction and processing. In this paper, we present HyperGAN, a hyperspectral image fusion approach based on Generative Adversarial Networks. Unlike previous methods that deepen the network to capture spectral information, HyperGAN widens the structure with a Wide Block for multi-scale learning, effectively capturing global and local details from upsampled HSI and PAN images. While LR-HSI provides rich spectral data, PAN images offer spatial information. We introduce the Efficient Spatial and Channel Attention Module (ESCA) to integrate these features and add an energy-based discriminator to enhance model performance by learning directly from the Ground Truth (GT), improving fused image quality. We validated our method on various scenes, including the Pavia Center, Eastern Tianshan, and Chikusei. Results show that HyperGAN outperforms state-of-the-art methods in visual and quantitative evaluations.

A Dilemma-Based Learning-to-Rank Approach for Generative Design in Urban Architectural Regeneration

Continuous urbanization and climate change degrade urban living conditions. Nature-based solutions in architectural and urban design offer promising remedies but are often hindered by time, cost, and early design phase challenges. To address this, we present a Generative Design System framework utilizing AI-generated images and learning-to-rank algorithms. This system generates numerous image solutions to inspire architects and urban planners, significantly accelerating early design stages. To manage the overwhelming volume of images, we introduce a dilemma-based learning approach that employs learning-to-rank and smart bubble sorting algorithms to prioritize images based on user preference. A case study demonstrates the framework’s potential, providing valuable insights into its application, benefits, and limitations in urban design.

Added prognostic value of DCE blood volume imaging in patients with suspected recurrent or residual glioblastoma – a hybrid [18F]FET PET/MRI study

Abstract Background MRI cerebral blood volume (CBV) measurements improves diagnosis of recurrent gliomas. The study investigated the prognostic value of dynamic contrast enhanced (DCE) CBV imaging in treated IDH wildtype glioblastoma when added to MRI or amino acid PET. Methods Hybrid [18F]FET PET/MRI with 2CXM (2-compartment exchange model) DCE from 86 adult patients with suspected recurrent or residual glioblastoma were retrospectively analysed. High CBV tumour volume (VOLCBV), and contrast enhancing (VOLCE) and [18F]FET active tumour (VOLFET) volumes were delineated. Absolute and fractional high CBV subvolumes within VOLCE and VOLFET were determined. Associations with overall survival (OS) were assessed by Cox analysis. Results Adjusted for MGMT status and steroid all total tumour volumes were individually associated with shorter OS. Adding VOLCBV to VOLCE, or VOLFET only the effect of VOLCBV was prognostic of OS (HR 1.327, p=0.042 and 1.352, p=0.011, respectively). High CBV subvolume within both VOLCE and VOLFET, were associated with shorter survival (HR 1.448, p=0.042 and 1.416, p=0011, respectively), and the low CBV subvolumes with longer survival (HR 0.504, p=0.002 and 0.365, p=0.001, respectively). The fraction of VOLCE and VOLFET with high CBV was a strong predictor of OS with shorter median OS in upper vs lower tertiles (8.3 vs 14.5 months and 7.1 vs 15.6 months, respectively, both p&amp;lt;0.001). Conclusions The high CBV tumour volume was a strong prognosticator of survival and allowed for separation of high and low risk subvolumes underlining the heterogeneous physiological environment represented in the contrast enhancing or metabolically active tumour volumes of treated glioblastoma.

Evaluation of a compact cone beam CT concept with high image fidelity for point-of-care brain imaging.

Cone beam computed tomography (CBCT) has potential advantages for developing portable, cost-effective point-of-care CT systems for intracranial imaging, such as early stroke diagnosis, hemorrhage detection, and intraoperative navigation. However, large volume imaging with flat panel detector based CBCT significantly increases the scattered radiation fluence which reduces its image quality and utility. To address these issues, a compact CBCT concept with enhanced image quality was investigated for intracranial imaging. The new system features a novel antiscatter collimator and data correction method to address the challenges in imaging large volumes with CBCT. A benchtop CBCT prototype was constructed. Imaging studies with anthropomorphic phantoms showed that soft tissue visualization, Hounsfield Unit (HU) accuracy, contrast, and spatial resolution increased significantly with the proposed CBCT concept, and they were comparable to the values measured in the gold standard multidetector-row CT (MDCT) images. Contrast-to-noise ratio (CNR) in CBCT images was within 12-31% of the CNR in MDCT images. These findings indicate that a compact CBCT system integrated with effective scatter suppression techniques may have increased utility in the context of brain imaging, and the proposed approach may enable the development of point-of-care CT systems for head imaging based on flat panel detector based CBCT technology.

Automated Geographic-Information-System-Based Framework for Detecting Crosswalk Changes from Bi-Temporal High-Resolution Aerial Images

Identifying changes in pavement markings has become crucial for infrastructure monitoring, maintenance, development, traffic management, and safety. Automated extraction of the roadway geometry is critical in helping with this, given the increasing availability of high-resolution images and advancements in computer vision and object detection. Specifically, because of the substantial volume of satellite and high-resolution aerial images captured at different time instances, change detection has become a viable solution. In this study, an automated framework is developed to detect changes in crosswalks in Orange, Osceola, and Seminole counties in Florida, utilizing data extracted from high-resolution images obtained at various time intervals. Specifically, for Orange County, crosswalk changes between 2019 and 2021 were manually extracted, verified, and categorized as either new or modified crosswalks. For Seminole County, the developed model was used to automatically extract crosswalk changes between 2018 and 2021, while for Osceola County, changes between 2019 and 2020 were extracted. Findings indicate that Orange County witnessed approximately 2,094 crosswalk changes, with 314 occurring on state roads. In Seminole and Osceola counties, on the other hand, 1,040 and 1,402 crosswalk changes were observed on both local and state roads, respectively. Among these, 340 and 344 were identified on state roads in Seminole and Osceola, respectively. Spatiotemporal changes observed in crosswalks can be utilized to regularly update the existing crosswalk inventories, which is essential for agencies engaged in traffic and safety studies. Data extracted from these crosswalk changes can be combined with traffic and crash data to provide valuable insights to policymakers.

Real-time volumetric imaging of cells and molecules in deep tissues with Takoyaki ultrasound.

Acoustic contrast agents and reporter genes play a critical role in allowing ultrasound to visualize blood flow, map molecules and track cellular function in opaque living organisms. However, existing ultrasound methods to image acoustic contrast agents predominantly focus on 2D planar imaging, while the biological phenomena of interest unfurl in three dimensions. Here, we introduce a method for efficient, dynamic imaging of contrast agents and reporter genes in 3D using multiplexed matrix array transducers. Our "Takoyaki" pulse sequence uses the simultaneous scanning of multiple focal points to excite contrast agents with sufficient acoustic pressure for nonlinear imaging while efficiently covering 3D space. Through in vitro experiments, we first show that the Takoyaki sequence produces highly sensitive volume images of gas vesicle contrast agents and compare its performance with alternative imaging schemes. We then establish its utility in cellular imaging in vivo by visualizing acoustic reporter gene-expressing tumors in a mouse model of glioblastoma. Finally, we demonstrate real-time volumetric imaging by tracking the dynamics of fluid motion in brain ventricles after intraventricular contrast injection. Takoyaki imaging enables a more comprehensive understanding of biological processes by providing spatiotemporal information in 3D within the constraints of accessible multiplexed matrix array systems.

Sparse Annotation is Sufficient for Bootstrapping Dense Segmentation.

Producing dense 3D reconstructions from biological imaging data is a challenging instance segmentation task that requires significant ground-truth training data for effective and accurate deep learning-based models. Generating training data requires intense human effort to annotate each instance of an object across serial section images. Our focus is on the especially complicated brain neuropil, comprising an extensive interdigitation of dendritic, axonal, and glial processes visualized through serial section electron microscopy. We developed a novel deep learning-based method to generate dense 3D segmentations rapidly from sparse 2D annotations of a few objects on single sections. Models trained on the rapidly generated segmentations achieved similar accuracy as those trained on expert dense ground-truth annotations. Human time to generate annotations was reduced by three orders of magnitude and could be produced by non-expert annotators. This capability will democratize generation of training data for large image volumes needed to achieve brain circuits and measures of circuit strengths.

EGS SO21 - The undifferentiated general surgical take over 10 years: Emergency imaging

Abstract Background The undifferentiated emergency general surgical take in July 2013 and July 2023, at a District General Hospital, was reviewed with the aim of understanding increasing pressures on the surgical and radiology departments, and subsequently identifying areas in which we could adapt to facilitate these demands. Method Patients were identified retrospectively if they had been cared for by the emergency general surgical team in July 2013 or July 2023. Further information was collected from electronic notes, with a focus on admission and initial imaging modalities. Patients were excluded if information was not available electronically. Results Of the 395 patients in July 2013, and 594 in July 2023, 55% and 61% respectively had imaging studies within 7 days of admission. 11% (n=44/395) of patients in 2013 had abdominal X-ray without further imaging, compared to 6% (n=33/594) in 2023. Computed Tomography (CT) use increased by 35%, whilst ultrasound scanning (USS) increased only by 11%. Time from admission to scans of all types has reduced from 0.79 days (+/-0.16, p=0.02) in 2013 to 0.60 (+/-0.1, p=0.02) days in 2023. Conclusion Overall volume of imaging has increased slightly, although the proportion of patients being scanned is largely unchanged, with subtle variation in preferred imaging modalities. CT is marginally more common, whilst USS remains mostly unchanged. The use of abdominal x-ray without subsequent imaging has decreased, demonstrating its reducing use in clinical judgement and reliance on alternative imaging techniques. Time from admission to scan of all kinds has reduced, despite increasing demands on radiology departments.

Ultrastructure Expansion Microscopy (U-ExM) of the Fission Yeast Schizosaccharomyces pombe.

Among widely used super-resolution microscopy techniques, including stimulated emission depletion (STED), photoactivated localization microscopy (PALM), and stochastic optical reconstruction microscopy (STORM), expansion microscopy (ExM) is unique in achieving increased resolution through a physical manipulation of the actual sample rather than optics or postprocessing. Originally developed for applications in neuroscience, ExM now has a solid foothold across many fields and model systems, and has been adapted to work for organisms with cell walls, including budding and fission yeasts, through the inclusion of a pre-expansion enzymatic digestion step. A variant of the ExM technique optimized for preserving the architecture of protein complexes, ultrastructure expansion microscopy (U-ExM), enables super-resolution imaging of full 3D volumes at increased throughput using conventional microscopes and can be readily combined with commonly used antibodies, dyes, and stains. Here, we present its application to the fission yeast Schizosaccharomyces pombe.

TMOD-09. NEWLY DESIGNED TUMOR TREATING FIELDS (TTFIELDS) ARRAYS FOR THE MOUSE HEAD DEMONSTRATE EFFICACY FOR TREATMENT OF GLIOBLASTOMA

Abstract Tumor Treating Fields (TTFields) therapy is a cancer treatment modality based on continuous, non-invasive delivery of electric fields. TTFields therapy is approved for treatment of glioblastoma (GBM), delivered to the patient’s brain by two array pairs placed on the scalp. Further research in animals to expand the knowledge regarding TTFields treatment of GBM is limited, as this is mainly performed in mouse models and arrays for application of TTFields to the mouse head are lacking. The small dimensions and specific geometries of the mouse head make the development of such arrays challenging. The aim of this study was to design arrays that will allow efficient and stable delivery of TTFields to the mouse head. To overcome the small head size, we developed a layout with two arrays situated on the head of the mouse, each divided into two smaller disks, and positioned opposite two arrays on the torso. We identified a thin and transparent adhesive tape (facilitating correct array positioning) with good tackiness and easy removal (without leaving residual adhesive on the skin). The arrays met the minimum treatment requirements: current ≥ 50 mA, usage ≥ 75%, field intensity ≥ 1 V/cm RMS. We then conducted an efficacy study with the new arrays, using GL-261 GBM cells intracranially injected into C57BL/6 mice. Treatment with sham-heat (control) or TTFields was initiated 11 days following tumor inoculation and maintained continuously for 12 days. Efficacy was measured via magnetic resonance imaging (MRI) of tumor volume, showing a decrease of 31% at treatment end in TTFields-treated mice versus the control. Overall, the new arrays are flexible, strongly adherent, deliver TTFields at a sufficient intensity, and showed efficacy for treating GBM in mice.

WASPSYN: A Challenge for Domain Adaptive Synapse Detection in Microwasp Brain Connectomes.

The size of image volumes in connectomics studies now reaches terabyte and often petabyte scales with a great diversity of appearance due to different sample preparation procedures. However, manual annotation of neuronal structures (e.g., synapses) in these huge image volumes is time-consuming, leading to limited labeled training data often smaller than 0.001% of the large-scale image volumes in application. Methods that can utilize in-domain labeled data and generalize to out-of-domain unlabeled data are in urgent need. Although many domain adaptation approaches are proposed to address such issues in the natural image domain, few of them have been evaluated on connectomics data due to a lack of domain adaptation benchmarks. Therefore, to enable developments of domain adaptive synapse detection methods for large-scale connectomics applications, we annotated 14 image volumes from a biologically diverse set of Megaphragma viggianii brain regions originating from three different whole-brain datasets and organized the WASPSYN challenge at ISBI 2023. The annotations include coordinates of pre-synapses and post-synapses in the 3D space, together with their one-to-many connectivity information. This paper describes the dataset, the tasks, the proposed baseline, the evaluation method, and the results of the challenge. Limitations of the challenge and the impact on neuroscience research are also discussed. The challenge is and will continue to be available at https://codalab.lisn.upsaclay.fr/competitions/9169. Successful algorithms that emerge from our challenge may potentially revolutionize real-world connectomics research and further the cause that aims to unravel the complexity of brain structure and function.

Ultrafast 3D synthetic aperture imaging with Hadamard-encoded aperiodic interval codes and aperiodic sparse arrays with separate transmitters and receivers

3D synthetic aperture (SA) imaging of volumes can be obtained using sparse 2D ultrasound arrays. However, even with just 256 elements, the volumetric imaging rate can be relatively slow due to having to transmit on each element in succession. Hadamard Aperiodic Interval (HAPI) codes can be used to image the full SA dataset in one extended transmit to speed up the synthetic aperture imaging, but their long nature produces large deadzones if the same elements are used as both transmitters and receivers. In this simulation study, we use a 2D Costas sparse array with separate transmitters and receivers to remedy the deadzone problem, and use it with the HAPI-coded imaging scheme to obtain fully transmit-receive focused, wide field-of-view 3D volumes with high-resolution and high SNR at ultrafast volumetric imaging rates of more than 500 volumes per second, almost nine times faster than non-coded SA imaging with the same imaging parameters. We show similar PSF performance compared to non-coded SA, and a 26 dB improvement in SNR with order-256 HAPI codes. We also present cyst simulations showing similar contrast for the HAPI-coded SA method compared to non-coded SA in the context of no noise, and improved contrast in the context of noise.

Separation of sand and gravel particles in volume images using a random forest

Separation of sand and gravel particles in volume images using a random forest