High-resolution Three-dimensional Imaging Research Articles

A Simple and Fast Optical Clearing Method for Whole-Mount Fluorescence In Situ Hybridization (FISH)Imaging.

We report a single-step optical clearing method that is compatible with RNA fluorescence in situ hybridization (FISH) imaging. We previously demonstrated microscopy imaging with immunohistochemistry and genetic reporters using a technique called lipid-preserving refractive index matching for prolonged imaging depth (LIMPID). Our protocol reliably produces high-resolution three-dimensional (3D) images with minimal aberrations using high magnification objectives, captures large field-of-view images of whole-mount tissues, and supports co-labeling with antibody and FISH probes. We also custom-designed FISH probes for quail embryos, demonstrating the ease of fabricating probes for use with less common animal models. Furthermore, we show high-quality 3D images using a conventional fluorescence microscope, without using more advanced depth sectioning instruments such as confocal or light-sheet microscopy. For broader adoption, we simplified and optimized 3D-LIMPID-FISH to minimize the barrier to entry, and we provide a detailed protocol to aid users with navigating the thick and thin of 3D microscopy.

Novel High-Resolution Three-Dimensional Fluorescent Confocal Imaging Resolves Differences in Urinary Sediment

Novel High-Resolution Three-Dimensional Fluorescent Confocal Imaging Resolves Differences in Urinary Sediment

Long-term three-dimensional high-resolution imaging of live unlabeled small intestinal organoids via low-coherence holotomography.

Organoids, which are miniature in vitro versions of organs, possess significant potential for studying human diseases and elucidating their underlying mechanisms. Live imaging techniques play a crucial role in organoid research and contribute to elucidating the complex structure and dynamic biological phenomena of organoids. However, live, unlabeled high-resolution imaging of native organoids is challenging, primarily owing to the complexities of sample handling and optical scattering inherent in three-dimensional (3D) structures. Additionally, conventional imaging methods fail to capture the real-time dynamic processes of growing organoids. In this study, we introduce low-coherence holotomography as an advanced, label-free, quantitative imaging modality designed to overcome several technical obstacles for long-term live imaging of 3D organoids. We demonstrate the efficacy of low-coherence holotomography by capturing high-resolution morphological details and dynamic activities within mouse small intestinal organoids at subcellular resolution. Moreover, our approach facilitates the distinction between viable and nonviable organoids, significantly enhancing its utility in organoid-based research. This advancement underscores the critical role of live imaging in organoid studies, offering a more comprehensive understanding of these complex systems.

Rapid full-color serial sectioning tomography with speckle illumination and ultraviolet excitation

Three-dimensional (3D) high-resolution large-volume imaging has remained a challenge. Translational rapid ultraviolet-excited sectioning tomography (TRUST) achieves rapid and cost-effective whole-organ subcellular imaging through iterative optical scanning and mechanical sectioning. However, the axial resolution is limited by the mechanical sectioning thickness or the UV light penetration depth in tissue. Here, assisted with high-and-low-frequency (HiLo) microscopy (HiLoTRUST), the optical sectioning thickness has been reduced from tens of micrometers to ~5.8 µm. In addition, HiLoTRUST has attained a finer mechanical sectioning thickness (10–15 µm) compared to TRUST (50 µm). For high-content imaging as in TRUST, we employed two additional UV light-emitting diodes (LEDs) specifically for uniform illumination. The full-color imaging ability and improved axial resolution of HiLoTRUST have been validated by two-dimensional (2D)/3D imaging of various mouse organs and human lung cancer specimens. HiLoTRUST offers a cost-effective, full-color, and high-resolution 3D imaging approach, showing its great potential in 3D histology applications.

PREOPERATIVE AND POSTOPERATIVE TOMOGRAPHIC ASPECTS OF CONDYLE FIXATION AND MANDIBULAR FRACTURE: AN INTEGRATIVE LITERATURE REVIEW

Introduction: Computed tomography (CT) is crucial for the evaluation of mandibular fractures, especially in complex areas such as the condylar region. Its ability to provide detailed images in multiple planes has improved surgical planning and post-operative monitoring, offering precise information on the location and characteristics of fractures. Objective: This integrative review aims to analyze how tomographic aspects impact surgical planning and postoperative monitoring of condylar and mandibular fractures. The study discusses the advantages and limitations of tomographic techniques in order to understand how they influence the clinical outcome and rehabilitation of patients. Materials and Methods: An integrative literature review was carried out, without the need for submission to the Ethics Committee, in accordance with the guidelines of Normative Instruction No. 510/2016. The search was conducted in databases such as PubMed, Scopus and Web of Science, and expanded with Google Scholar. Results and Discussion: The analysis revealed that cone beam computed tomography (CBCT) provides high-resolution three-dimensional images, which are essential for the accurate assessment of fractures, especially in complex anatomical areas such as the mandibular condyle. Conclusion: Cone beam computed tomography (CBCT) is an indispensable tool for the management of condyle and mandible fractures. Its use in preoperative and post-fixation monitoring facilitates detailed visualization of anatomical structures, improving the precision of surgical interventions and contributing to superior functional and aesthetic results.

Taxonomic insights into medicinal plants pollen, using advanced microscopy techniques, from the Western Ghats, India

Pollen morphological study on 18 medicinal plants from the Western Ghats (India) was carried out using light microscopy (LM), confocal laser scanning microscopy (CLSM) and field emission scanning electron microscopy (FESEM) techniques. The principal aim was to obtain high-resolution three-dimensional images and ultra-structure of the pollen grains of the studied taxa. The palyno-morphological characters, such as polar axis, equatorial diameter, P/E ratio, pollen shape, aperture type and number, exine thickness and surface ornamentation will be useful in the identification and taxonomic classification of the studied medicinal plants. Statistical analysis reveals grouping of the taxa in three different clusters and also isolated presence of taxa on the principal component analysis (PCA) biplot, irrespective of their families, showing similarities and/or variations among the studied taxa, belonging to the same and/or different families. The present study has taxonomic significance, providing high taxonomic resolution (identification of the taxa up to species level), and further aid in the identification and delimitation of the 18 studied plants.

Progressive gray matter atrophy in parkinsonian variant of multiple system atrophy assessed by using causal structural covariance network.

Multiple system atrophy (MSA), a rare neurodegenerative disease, is usually accompanied by brain morphological alterations. However, the causal relationships between progressive gray matter atrophy in MSA parkinsonian (MSA-P) subtype remain unknown. In total, thirty-five MSA-P patients and thirty-five healthy controls (HC) underwent three-dimensional high-resolution T1-weighted structural imaging and voxel-based morphometry analysis. The causal structural covariance network (CaSCN) of gray matter was assessed to explore the causal relationships in MSA-P. With greater illness duration, the reduction of gray matter was originated from right cerebellum and progressed to bilateral cerebellum, fusiform gyrus, insula, putamen, caudate nucleus, frontal lobe, right angular gyrus, right precuneus, left middle occipital lobe and left inferior temporal lobe, then expanded to midbrain, bilateral para-hippocampus, thalamus, temporal lobe, inferior parietal lobule (IPL), precentral gyrus, postcentral gyrus and middle cingulate cortex. The right cerebellum was revealed to be the core node of the directional network and projected positive causal effects to bilateral cerebellum, caudate nucleus and left IPL. MSA-P patients showed progression of gray matter atrophy over time, with the right cerebellum probably as a primary hub. Furthermore, the early structural vulnerability of cerebellum in MSA-P may play a pivotal role in the modulation of motor and non-motor circuits at the structural level.

Deep learning constrained compressed sensing reconstruction improves high-resolution three-dimensional (3D) T2-weighted turbo spin echo magnetic resonance imaging (MRI) of the lumbar spine

We sought to assess the image quality of three-dimensional (3D) T2-weighted (T2w) turbo spin echo (TSE) sequences with deep learning (DL)-constrained compressed sensing (CS) reconstruction relative to a reference two-dimensional (2D) T2w TSE sequence for routine clinical lumbar spine MRI. Fifty-three patients underwent imaging of the lumbar spine with a sagittal 2D T2w TSE sequence and with two CS-accelerated 3D T2w TSE sequences (voxel size of 0.4×0.4×0.5 mm) with CS factors of 7 and 11. The CS-accelerated sequences were reconstructed with iterative reconstruction with wavelet transformation (conventional CS) and secondly with a DL-constrained CS reconstruction (named CS-AI). Two readers graded image quality, based on 8 metrics (overall image quality, presence of image noise, presence of motion artifacts, delineation/conspicuity and clarity of anatomical structures such as the spinal cord, cauda equine nerve roots, cerebrospinal fluid (CSF), intervertebral disc, and bone marrow and intervertebral foramen) using Likert scales. Overall inter-readout agreement was substantial (Krippendorff's α=0.724, 95% confidence interval [CI]: 0.692-0.755). The CS7-AI and CS11-AI sequences were comparable or better than the 2D sequence in all 8 metrics (p < 0.001-p > 0.99). The CS7 and CS11 sequences were comparable or better than the 2D sequence in only 5 and 3 of the 8 metrics, respectively (p < 0.001-p > 0.99). A DL-constrained CS reconstruction significantly improves the quality of accelerated high-resolution 3D T2w TSE imaging of the lumbar spine. Thus, high-quality imaging in a submillimeter resolution in all three imaging planes can be achieved without compromising the image quality as compared with standard 2D T2w TSE imaging.

Rapid, autonomous and ultra-large-area detection of latent fingerprints using object-driven optical coherence tomography

The detection of latent fingerprints plays a crucial role in criminal investigations and biometrics. However, conventional techniques are limited by their lack of depth-resolved imaging, extensive area coverage, and autonomous fingerprint detection capabilities. This study introduces an object-driven optical coherence tomography (OD-OCT) to achieve rapid, autonomous and ultra-large-area detection of latent fingerprints. First, by utilizing sparse sampling with the robotic arm along the slow axis, we continuously acquire B-scans across large, variably shaped areas (∼400 cm2), achieving a scanning speed up to 100 times faster. In parallel, a deep learning model autonomously processes the real-time stream of B-scans, detecting fingerprints and their locations. The system then performs high-resolution three-dimensional imaging of these detected areas, exclusively visualizing the latent fingerprints. This approach significantly enhances the imaging efficiency while balancing the traditional OCT system's trade-offs between scanning range, speed, and lateral resolution, thus offering a breakthrough in rapid, large-area object detection.

Compact broadband high-resolution real-time four-dimensional imaging spectrometer

A broadband high-resolution real-time four-dimensional imaging spectrometer (HRRFDIS) is presented, which can acquire both broadband fine spectra and high-resolution three-dimensional (3D) spatial images of a 3D object in real time. The HRRFDIS consists of a first microlens array arranged in a plane to achieve orthographic view spatial imaging, a second microlens array arranged on a conical surface to measure the depth and to achieve 360-degree side-view spatial imaging, multiple optical fibers, a collimating microlens array arranged in a straight line, a parallel planar transmission grating pair to obtain high spectral resolution over a broadband spectral range, and an area-array detector. Compared with the scanning four-dimensional imaging spectrometer (FDIS), the HRRFDIS can obtain a broadband high-resolution four-dimensional dataset using only one frame of data, and it is more stable, compact, small-sized, and lightweight. Compared to the staring FDIS using a liquid crystal filter and requiring at least one modulation period of liquid crystal to acquire a complete hyperspectral image, the HRRFDIS can acquire a complete broadband hyperspectral image in real time. Compared to existing snapshot FDIS, the HRRFDIS can achieve much higher spectral resolution, especially over a broadband spectral range. The HRRFDIS is a unique concept that is the first to obtain both high-resolution broadband spectral information and high-resolution 3D spatial information in real time, to the best of our knowledge. The HRRFDIS will be suitable for real-time measurement of 3D objects in the ultraviolet to infrared spectral range.

High-resolution three-dimensional imaging of topological textures in nanoscale single-diamond networks.

Topological defects-extended lattice deformations that are robust against local defects and annealing-have been exploited to engineer novel properties in both hard and soft materials. Yet, their formation kinetics and nanoscale three-dimensional structure are poorly understood, impeding their benefits for nanofabrication. We describe the fabrication of a pair of topological defects in the volume of a single-diamond network (space group Fd m) templated into gold from a triblock terpolymer crystal. Using X-ray nanotomography, we resolve the three-dimensional structure of nearly 70,000 individual single-diamond unit cells with a spatial resolution of 11.2 nm, allowing analysis of the long-range order of the network. The defects observed morphologically resemble the comet and trefoil patterns of equal and opposite half-integer topological charges observed in liquid crystals. Yet our analysis of strain in the network suggests typical hard matter behaviour. Our analysis approach does not require a priori knowledge of the expected positions of the nodes in three-dimensional nanostructured systems, allowing the identification of distorted morphologies and defects in large samples.

Click3D: Click reaction across deep tissues for whole-organ 3D fluorescence imaging.

Click chemistry offers various applications through efficient bioorthogonal reactions. In bioimaging, pretargeting strategies have often been used, using click reactions between molecular probes with a click handle and reporter molecules that make them observable. Recent efforts have integrated tissue-clearing techniques with fluorescent labeling through click chemistry, allowing high-resolution three-dimensional fluorescence imaging. Nevertheless, these techniques have faced a challenge in limited staining depth, confining their use to imaging tissue sections or partial organs. In this study, we introduce Click3D, a method for thoroughly staining whole organs using click chemistry. We identified click reaction conditions that improve staining depth with our custom-developed assay. The Click3D protocol exhibits a greater staining depth compared to conventional methods. Using Click3D, we have successfully achieved whole-kidney imaging of nascent RNA and whole-tumor imaging of hypoxia. We have also accomplished whole-brain imaging of hypoxia by using the clickable hypoxia probe, which has a small size and, therefore, has high permeability to cross the blood-brain barrier.

Characterizing PEM fuel cell catalyst layer properties from high resolution three-dimensional digital images, part I: A numerical procedure for the ionomer distribution reconstruction

In this work, a numerical approach is presented to reconstruct the ionomer three-dimensional distribution in the microstructure of the cathode catalyst layer (CCL) of a polymer electrolyte membrane fuel cell (PEMFC) from a 3D segmented image of the CCL obtained by focused ion beam-scanning electron microscopy (FIB-SEM). Three forms of ionomer are distinguished: the ionomer filaments, the coating ionomer and the inter-carbon grains ionomer. The ionomer filaments are identified by applying a filtering procedure to the size distribution in the segmented solid phase obtained via a maximum sphere inscription algorithm. The coating ionomer is reconstructed via a filtering procedure of the curvature distribution computed over the interface between the two segmented phases from the consideration that concave regions are preferential ionomer accumulation zones during the drying step of the CCL fabrication procedure. This procedure of coating controlled by the local curvature is applied until a desired value of coverage is reached. In a last step, catalyst nanoparticles, also not visible in the FIB-SEM image, are reconstructed in the image.

Characterizing PEM fuel cell catalyst layer properties from high resolution three-dimensional digital images, Part II: Oxygen effective diffusion and proton effective conductivity tensors

The oxygen effective diffusion and proton effective conductivity tensors of a cathode catalyst layer (CCL) are computed using a two-scale approach on CCL microstructure three-dimensional images obtained by focused ion beam-scanning electron microscopy (FIB-SEM) after reconstruction of the ionomer distribution. The results show that the obtained tensors are not isotropic. It is also found that some off-diagonal components are not negligible in the case of the proton effective conductivity tensor. The simulations confirm that Knudsen diffusion has a significant impact on oxygen diffusion. The results are comparable to those obtained in previous works on synthetic images as regards the oxygen effective diffusion through-plane component but differ as regards the proton conductivity through-plane component. Contrary to previous works using synthetic images which tend to underestimate the proton conductivity, they are globally in better agreement with experimental data. The results also show that the effective proton conductivity is heterogeneous at the scale of the computational domains typically considered in several previous works due to the variability in the ionomer distribution at this scale. The impact of liquid water in the primary pores on the proton transport is explored and found to have a significant impact.

From Diagnosis to Precision Surgery: The Transformative Role of Artificial Intelligence in Urologic Imaging.

The multidisciplinary nature of artificial intelligence (AI) has allowed for rapid growth of its application in medical imaging. Artificial intelligence algorithms can augment various imaging modalities, such as X-rays, CT, and MRI, to improve image quality and generate high-resolution three-dimensional images. AI reconstruction of three-dimensional models of patient anatomy from CT or MRI scans can better enable urologists to visualize structures and accurately plan surgical approaches. AI can also be optimized to create virtual reality simulations of surgical procedures based on patient-specific data, giving urologists more hands-on experience and preparation. Recent development of artificial intelligence modalities, such as TeraRecon and Ceevra, offer rapid and efficient medical imaging analyses aimed at enhancing the provision of urologic care, notably for intraoperative guidance during robot-assisted radical prostatectomy (RARP) and partial nephrectomy.

EDTP enhances and protects the fluorescent signal of GFP in cleared and expanded tissues

Advanced 3D high-resolution imaging techniques are essential for investigating biological challenges, such as neural circuit analysis and tumor microenvironment in intact tissues. However, the fluorescence signal emitted by endogenous fluorescent proteins in cleared or expanded biological samples gradually diminishes with repeated irradiation and prolonged imaging, compromising its ability to accurately depict the underlying scientific problem. We have developed a strategy to preserve fluorescence in cleared and expanded tissue samples during prolonged high-resolution three-dimensional imaging. We evaluated various compounds at different concentrations to determine their ability to enhance fluorescence intensity and resistance to photobleaching while maintaining the structural integrity of the tissue. Specifically, we investigated the impact of EDTP utilization on GFP, as it has been observed to significantly improve fluorescence intensity, resistance to photobleaching, and maintain fluorescence during extended room temperature storage. This breakthrough will facilitate extended hydrophilic and hydrogel-based clearing and expansion methods for achieving long-term high-resolution 3D imaging of cleared biological tissues by effectively safeguarding fluorescent proteins within the tissue.

A voxel-based magnetic resonance study of cortical gray matter structures in intermittent exotropia

Objective: To explore the changes in gray matter volume of the cerebral cortex in patients with intermittent exotropia (IXT) using the voxel-based analysis and to analyze the correlation between these changes and clinical manifestations. Methods: This was a cross-sectional study. A collection of 15 consecutive patients diagnosed with IXT at Tianjin Eye Hospital from March 2021 to May 2022 formed the exotropia group, which comprised 8 males and 7 females, with an average age of (23.5±5.2) years. Ten healthy individuals, 3 males and 7 females, with an average age of (27.0±7.5) years, were selected as the control group. All participants underwent assessments of exotropia severity and Titmus stereoacuity. Three-dimensional high-resolution brain images were obtained through MRI scans. Voxel-based morphometry was employed to preprocess the MRI data, and the SPM toolbox in MATLAB was utilized to analyze differences of images between the two groups. Regions of interest (ROI) with structural abnormalities in the gray matter volume analysis were selected, and the ratio of gray matter voxel values in the ROI to the mean gray matter voxel values of the whole brain for each participant was calculated using the MarsBaR software. The correlation between this ratio and exotropia severity as well as the common logarithm of Titmus stereoacuity was analyzed. Results: The differences in age, gender distribution, and refractive error between the two groups were not statistically significant (all P>0.05). However, there were statistically significant differences in the degree of strabismus and Titmus stereoacuity (both P<0.001). Compared to the control group, patients in the strabismus group exhibited decreased gray matter volume in several brain regions, including the wedges of the medial surface of the cerebral hemisphere (decreased by 89 voxels), the left lingual gyrus (decreased by 176 voxels), the left calcarine sulcus V3 area (decreased by 30 voxels), the central anterior gyrus of the right frontal lobe (decreased by 192 voxels), the gray matter of the left hippocampal gyrus (decreased by 20 voxels), and the bilateral lateral geniculate nuclei (decreased by 100 and 40 voxels on the left and right sides, respectively). These differences were all statistically significant (all P<0.001). Additionally, there was an increase in gray matter volume in several brain regions, including the bilateral caudate nuclei (increased by 60 and 76 voxels on the left and right sides, respectively) and the left precentral gyrus (increased by 36 voxels). These differences were also statistically significant (all P<0.001). A group-level analysis identified 10 brain regions with structural differences between the two groups, which were used as ROI. The gray matter volume ratio was negatively correlated with the degree of exotropia (all P<0.05) in the ROI of the left wedges (r=-0.670), left calcarine sulcus V3 area (r=-0.610), and left lingual gyrus (r=-0.684). The gray matter volume ratio was negatively correlated with lgTS (all P<0.05) in the ROI of the left wedges (r=-0.568) and the central anterior gyrus of the right frontal lobe (r=-0.563). Conclusions: Patients with IXT exhibit decreased gray matter volume in the horizontal connection areas between the primary visual cortices V1 and V2. The reduction in gray matter volume of the lingual gyrus and the dorsal visual pathway V3 area becomes more pronounced with increasing exotropia severity, while the gray matter volume of the precentral gyrus (BA6 area) decreases with worsening stereoacuity.

Toward Ground-Truth Optical Coherence Tomography via Three-Dimensional Unsupervised Deep Learning Processing and Data.

Optical coherence tomography (OCT) can perform non-invasive high-resolution three-dimensional (3D) imaging and has been widely used in biomedical fields, while it is inevitably affected by coherence speckle noise which degrades OCT imaging performance and restricts its applications. Here we present a novel speckle-free OCT imaging strategy, named toward-ground-truth OCT ( t GT-OCT), that utilizes unsupervised 3D deep-learning processing and leverages OCT 3D imaging features to achieve speckle-free OCT imaging. Specifically, our proposed t GT-OCT utilizes an unsupervised 3D-convolution deep-learning network trained using random 3D volumetric data to distinguish and separate speckle from real structures in 3D imaging volumetric space; moreover, t GT-OCT effectively further reduces speckle noise and reveals structures that would otherwise be obscured by speckle noise while preserving spatial resolution. Results derived from different samples demonstrated the high-quality speckle-free 3D imaging performance of t GT-OCT and its advancement beyond the previous state-of-the-art. The code is available online: https://github.com/Voluntino/tGT-OCT.

3D imaging of SARS-CoV-2 infected hamster lungs by X-ray phase contrast tomography enables drug testing

X-ray Phase Contrast Tomography (XPCT) based on wavefield propagation has been established as a high resolution three-dimensional (3D) imaging modality, suitable to reconstruct the intricate structure of soft tissues, and the corresponding pathological alterations. However, for biomedical research, more is needed than 3D visualisation and rendering of the cytoarchitecture in a few selected cases. First, the throughput needs to be increased to cover a statistically relevant number of samples. Second, the cytoarchitecture has to be quantified in terms of morphometric parameters, independent of visual impression. Third, dimensionality reduction and classification are required for identification of effects and interpretation of results. To address these challenges, we here design and implement a novel integrated and high throughput XPCT imaging and analysis workflow for 3D histology, pathohistology and drug testing. Our approach uses semi-automated data acquisition, reconstruction and statistical quantification. We demonstrate its capability for the example of lung pathohistology in Covid-19. Using a small animal model, different Covid-19 drug candidates are administered after infection and tested in view of restoration of the physiological cytoarchitecture, specifically the alveolar morphology. To this end, we then use morphometric parameter determination followed by a dimensionality reduction and classification based on optimal transport. This approach allows efficient discrimination between physiological and pathological lung structure, thereby providing quantitative insights into the pathological progression and partial recovery due to drug treatment. Finally, we stress that the XPCT image chain implemented here only used synchrotron radiation for validation, while the data used for analysis was recorded with laboratory μ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\mu$$\\end{document}CT radiation, more easily accessible for pre-clinical research.

Effect of deep learning-based reconstruction on high-resolution three-dimensional T2-weighted fast asymmetric spin-echo imaging in the preoperative evaluation of cerebellopontine angle tumors.

We aimed to evaluate the effect of deep learning-based reconstruction (DLR) on high-spatial-resolution three-dimensional T2-weighted fast asymmetric spin-echo (HR-3D T2-FASE) imaging in the preoperative evaluation of cerebellopontine angle (CPA) tumors. This study included 13 consecutive patients who underwent preoperative HR-3D T2-FASE imaging using a 3T MRI scanner. The reconstruction voxel size of HR-3D T2-FASE imaging was 0.23 × 0.23 × 0.5mm. The contrast-to-noise ratios (CNRs) of the structures were compared between HR-3D T2-FASE images with and without DLR. The observers' preferences based on four categories on the tumor side on HR-3D T2-FASE images were evaluated. The facial nerve in relation to the tumor on HR-3D T2-FASE images was assessed with reference to intraoperative findings. The mean CNR between the tumor and trigeminal nerve and between the cerebrospinal fluid and trigeminal nerve was significantly higher for DLR images than non-DLR-based images (14.3 ± 8.9 vs. 12.0 ± 7.6, and 66.4 ± 12.0 vs. 53.9 ± 8.5, P < 0.001, respectively). The observer's preference for the depiction and delineation of the tumor, cranial nerves, vessels, and location relation on DLR HR-3D T2FASE images was superior to that on non-DLR HR-3D T2FASE images in 7 (54%), 6 (46%), 6 (46%), and 6 (46%) of 13 cases, respectively. The facial nerves around the tumor on HR-3D T2-FASE images were visualized accurately in five (38%) cases with DLR and in four (31%) without DLR. DLR HR-3D T2-FASE imaging is useful for the preoperative assessment of CPA tumors.