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Background: Visualizing edges is critical for neuroimaging. For example, edge maps enable quality assurance for the automatic alignment of an image from one modality (or individual) to another., New Method: We suggest that using the second derivative (difference of Gaussian, or DoG) provides robust edge detection. This method is tuned by size (which is typically known in neuroimaging) rather than intensity (which is relative)., Results: We demonstrate that this method performs well across a broad range of imaging modalities. The edge contours produced consistently form closed surfaces, whereas alternative methods may generate disconnected lines, introducing potential ambiguity in contiguity., Comparison With Existing Methods: Current methods for computing edges are based on either the first derivative of the image (FSL), or a variation of the Canny Edge detection method (AFNI). These methods suffer from two primary limitations. First, the crucial tuning parameter for each of these methods relates to the image intensity. Unfortunately, image intensity is relative for most neuroimaging modalities making the performance of these methods unreliable. Second, these existing approaches do not necessarily generate a closed edge/surface, which can reduce the ability to determine the correspondence between a represented edge and another image., Conclusion: The second derivative is well suited for neuroimaging edge detection. We include this method as part of both the AFNI and FSL software packages, standalone code and online., Competing Interests: Declaration of Competing Interest The authors do not have any conflicts of interests that might appear to affect their ability to present data objectively. These include relevant financial (for example patent ownership, stock ownership, consultancies, speaker's fees), personal, political, intellectual, or religious interests. This work was supported by grants, as listed in the acknowledgments section., (Copyright © 2024 Elsevier B.V. All rights reserved.)

High Resolution (HR) medical images provide rich anatomical structure details to facilitate early and accurate diagnosis. In magnetic resonance imaging (MRI), restricted by hardware capacity, scan time, and patient cooperation ability, isotropic 3-dimensional (3D) HR image acquisition typically requests long scan time and, results in small spatial coverage and low signal-to-noise ratio (SNR). Recent studies showed that, with deep convolutional neural networks, isotropic HR MR images could be recovered from low-resolution (LR) input via single image super-resolution (SISR) algorithms. However, most existing SISR methods tend to approach scale-specific projection between LR and HR images, thus these methods can only deal with fixed up-sampling rates. In this paper, we propose ArSSR, an Arbitrary Scale Super-Resolution approach for recovering 3D HR MR images. In the ArSSR model, the LR image and the HR image are represented using the same implicit neural voxel function with different sampling rates. Due to the continuity of the learned implicit function, a single ArSSR model is able to achieve arbitrary and infinite up-sampling rate reconstructions of HR images from any input LR image. Then the SR task is converted to approach the implicit voxel function via deep neural networks from a set of paired HR and LR training examples. The ArSSR model consists of an encoder network and a decoder network. Specifically, the convolutional encoder network is to extract feature maps from the LR input images and the fully-connected decoder network is to approximate the implicit voxel function. Experimental results on three datasets show that the ArSSR model can achieve state-of-the-art SR performance for 3D HR MR image reconstruction while using a single trained model to achieve arbitrary up-sampling scales.

Allometric, metabolic, and biomechanical theories are the critical foundations for scientifically deciphering plant forms. Their concrete laws, however, are found to deviate for plenty of plant specimens. This phenomenon has not been extensively studied, due to technical restrictions. This bottleneck now can be overcome by the state-of-the-art three-dimensional (3D) mapping technologies, such as fine-scale terrestrial laser scanning. On these grounds, we proposed to reexamine the basic theories regarding plant forms, and then, we case validated the feasibility of upgrading them into 3D modes. As an in-time enlightening of 3D revolutionizing the related basic subject, our theoretical prospect further sorted out the potential challenges as the cutting points for advancing its future exploration, which may enable 3D reconstruction of the basic theories of plant forms and even boost life science., (© 2022. The Author(s).)

Ischemic heart disease is the leading cause of death in the United States, Canada, and worldwide. Severe disease is characterized by coronary artery occlusion, loss of blood flow to the myocardium, and necrosis of tissue, with subsequent remodeling of the heart wall, including fibrotic scarring. The current study aims to demonstrate the efficacy of quantitating infarct size via two-dimensional (2-D) echocardiographic akinetic length and four-dimensional (4-D) echocardiographic infarct volume and surface area as in vivo analysis techniques. We further describe and evaluate a new surface area strain analysis technique for estimating myocardial infarction (MI) size after ischemic injury. Experimental MI was induced in mice via left coronary artery ligation. Ejection fraction and infarct size were measured through 2-D and 4-D echocardiography. Infarct size established via histology was compared with ultrasound-based metrics via linear regression analysis. Two-dimensional echocardiographic akinetic length ( r = 0.76, P = 0.03), 4-D echocardiographic infarct volume ( r = 0.85, P = 0.008), and surface area ( r = 0.90, P = 0.002) correlate well with histology. Although both 2-D and 4-D echocardiography were reliable measurement techniques to assess infarct, 4-D analysis is superior in assessing asymmetry of the left ventricle and the infarct. Strain analysis performed on 4-D data also provides additional infarct sizing techniques, which correlate with histology (surface strain: r = 0.94, P < 0.001, transmural thickness: r = 0.76, P = 0.001). Two-dimensional echocardiographic akinetic length, 4-D echocardiography ultrasound, and strain provide effective in vivo methods for measuring fibrotic scarring after MI. NEW & NOTEWORTHY Our study supports that both 2-D and 4-D echocardiographic analysis techniques are reliable in quantifying infarct size though 4-D ultrasound provides a more holistic image of LV function and structure, especially after myocardial infarction. Furthermore, 4-D strain analysis correctly identifies infarct size and regional LV dysfunction after MI. Therefore, these techniques can improve functional insight into the impact of pharmacological interventions on the pathophysiology of cardiac disease.

Various advances in 3D automatic phenotyping and landmark-based geometric morphometric methods have been made. While it is generally accepted that automatic landmarking compromises the capture of the biological variation, no studies have directly tested the actual impact of such landmarking approaches in analyses requiring a large number of specimens and for which the precision of phenotyping is crucial to extract an actual biological signal adequately. Here, we use a recently developed 3D atlas-based automatic landmarking method to test its accuracy in detecting QTLs associated with craniofacial development of the house mouse skull and lower jaws for a large number of specimens (circa 700) that were previously phenotyped via a semiautomatic landmarking method complemented with manual adjustment. We compare both landmarking methods with univariate and multivariate mapping of the skull and the lower jaws. We find that most significant SNPs and QTLs are not recovered based on the data derived from the automatic landmarking method. Our results thus confirm the notion that information is lost in the automated landmarking procedure although somewhat dependent on the analyzed structure. The automatic method seems to capture certain types of structures slightly better, such as lower jaws whose shape is almost entirely summarized by its outline and could be assimilated as a 2D flat object. By contrast, the more apparent 3D features exhibited by a structure such as the skull are not adequately captured by the automatic method. We conclude that using 3D atlas-based automatic landmarking methods requires careful consideration of the experimental question., (© The Author(s) 2021. Published by Oxford University Press on behalf of Genetics Society of America.)

Despite the current advances in micro-CT analysis, the influence of some image acquisition parameters on the morphometric assessment outcome have not been fully elucidated. The aim of this study was to determine whether data binning and frame averaging affect the morphometric outcome of bone repair assessment using micro-CT. Four Wistar rats' tibiae with a surgically created bone defect were imaged with micro-CT six times each, frame averaging set to 1 and 2, and data binning set to 1, 2 and 4, for each of the averaging values. Two-way ANOVA followed by Bonferroni tests assessed the significance of frame averaging and data binning on a set of morphometric parameters assessed in the image volumes (p < 0.01). The effect of frame averaging was not significant for any of the assessed parameters. Increased data binning led to larger trabecular thickness. In contrast, smaller bone volume fraction and bone volume were found as data binning increased. Trabeculae number and trabecular separation were not influenced by any of the parameters. In conclusion, the morphometric outcome of bone repair assessment in micro-CT demonstrated dependency upon data binning, but not frame averaging. Therefore, image acquisition of small anatomical structures (e.g., rat trabeculae) should be performed without data binning., (© 2022. The Author(s).)

Recent advancements in Inertial Measurement Units (IMUs) offers the possibility of its use as a cost effective and portable alternative to traditional optoelectronic motion capture systems in analyzing biomechanical performance. One such commercially available IMU is the Perception Neuron motion capture system (PNS). The accuracy of the PNS had been tested and was reported to be a valid method for assessing the upper body range of motion to within 5° RMSE. However, testing of the PNS was limited to upper body motion involving functional movement within a single plane. Therefore, the purpose of this study is to further validate the Perception Neuron system with reference to a conventional optoelectronic motion capture system (VICON) through the use of dynamic movements (e.g., walking, jogging and a multi-articular sports movement with object manipulation) and to determine its feasibility through full-body kinematic analysis. Validation was evaluated using Pearson's R correlation, RMSE and Bland-Altman estimates. Present findings suggest that the PNS performed well against the VICON motion analysis system with most joint angles reporting a RMSE of < 4° and strong average Pearson's R correlation of 0.85, with the exception of the shoulder abduction/adduction where RMSE was larger and Pearson's R correlation at a moderate level. Bland-Altman analysis revealed that most joint angles across the different movements had a mean bias of less than 10°, except for the shoulder abduction/adduction and elbow flexion/extension measurements. It was concluded that the PNS may not be the best substitute for traditional motion analysis technology if there is a need to replicate raw joint angles. However, there was adequate sensitivity to measure changes in joint angles and would be suitable when normalized joint angles are compared and the focus of analysis is to identify changes in movement patterns., Competing Interests: The authors have declared that no competing interests exist.

Aneurysm wall enhancement (AWE) after the administration of contrast gadolinium is a potential biomarker of unstable intracranial aneurysms. While most studies determine AWE subjectively, this study comprehensively quantified AWE in 3D imaging using a semi-automated method. Thirty patients with 33 unruptured intracranial aneurysms prospectively underwent high-resolution imaging with 7T-MRI. The signal intensity (SI) of the aneurysm wall was mapped and normalized to the pituitary stalk (PS) and corpus callosum (CC). The CC proved to be a more reliable normalizing structure in detecting contrast enhancement (p < 0.0001). 3D-heatmaps and histogram analysis of AWE were used to generate the following metrics: specific aneurysm wall enhancement (SAWE), general aneurysm wall enhancement (GAWE) and focal aneurysm wall enhancement (FAWE). GAWE was more accurate in detecting known morphological determinants of aneurysm instability such as size ≥ 7 mm (p = 0.049), size ratio (p = 0.01) and aspect ratio (p = 0.002). SAWE and FAWE were aneurysm specific metrics used to characterize enhancement patterns within the aneurysm wall and the distribution of enhancement along the aneurysm. Blebs were easily identified on 3D-heatmaps and were more enhancing than aneurysm sacs (p = 0.0017). 3D-AWE mapping may be a powerful objective tool in characterizing different biological processes of the aneurysm wall., (© 2021. The Author(s).)

Measuring outcomes from treatments to the skin is either reliant upon patient's subjective feedback or scale-based peer assessments. Three-Dimensional stereophotogrammetry intend to accurately quantify skin microtopography before and after treatments. The objective of this study is comparing the accuracy of stereophotogrammetry with a scale-based peer evaluation in assessing topographical changes to skin surface following laser treatment. A 3D stereophotogrammetry system photographed skin surface of 48 patients with facial wrinkles or scars before and three months after laser resurfacing, followed immediately by topical application of vitamin C. The software measured changes in skin roughness, wrinkle depth and scar volume. Images were presented to three observers, each independently scoring cutaneous improvement according to Investigator Global Aesthetic Improvement Scale (IGAIS). As for the results, a trend reflecting skin/scar improvement was reported by 3D SPM measurements and raters. The percentage of topographical change given by the raters matched 3D SPM findings. Agreement was highest when observers analysed 3D images. However, observers overestimated skin improvement in a nontreatment control whilst 3D SPM was precise in detecting absence of intervention. This study confirmed a direct correlation between the IGAIS clinical scale and 3D SPM and confirmed the efficacy and accuracy of the latter when assessing cutaneous microtopography alterations as a response to laser treatment.

Purpose: To evaluate a 3-D visualization helmet (3DVH) during 23-gauge pars plana vitrectomy (PPV) for macular holes (MH) and macular puckers (MP)., Methods: A total of 184 eyes of 184 patients undergoing PPV for MH or MP were randomly selected for surgery with 3DVH or standard Galilean microscope (GM). Only one highly trained surgeon performed each PPV. A surgical comfort score, ranging from 1 to 10 was recorded after each operation. Statistical analysis was run with SPSS to compare parameters before and after surgery and between the two groups., Results: No statistical differences were found between the two groups for mean best correct visual acuity improvement after surgery (p < 0.001). Mean surgery comfort evaluation was 7.63 ± 0.48 in 3DVH eyes and 8.21 ± 0.62 in GM ones (p = 0.09); mean overall surgical time was 35.12 ± 3.8 min in 3DVH eyes and 32.7 ± 2.27 min in GM ones (p < 0.001); mean peeling time was 14.24 ± 3.42 min in 3DVH eyes and 13.61 ± 4.63 min in GM ones (p = 0.11)., Conclusions: According to the data observed in this study, the 3DVH provides adequate safety and efficacy in retinal and macular visualization during PPV for MH and MP., (© 2020 Acta Ophthalmologica Scandinavica Foundation. Published by John Wiley & Sons Ltd.)

Background: We report on the first use of a digital 3-dimensional (3D) exoscope equipped with a 5-aminolevulinic acid (5-ALA) fluorescence visual system., Methods: We conducted a prospective clinical trial to evaluate the utility and sensitivity/specificity of the Olympus Orbeye 3D digital exoscope when used to visualize 5-ALA-induced fluorescence in patients with high-grade glioma undergoing a clinically indicated craniotomy. At least 2 tissue samples were each obtained from regions of strong, weak. and no fluorescence and evaluated in a blinded manner by a neuropathologist., Results: Twenty patients were enrolled. Intraoperative fluorescence was observed in 100% of subjects. One hundred twenty-one surgical specimens were collected for histopathological analysis; 40 with strong, 40 weak, and 41 with no visible fluorescence. Histopathology demonstrated 62.8% of samples (n = 76) contained abundant, 20.7% (n = 25) scarce, and 16.5% (n = 20) no tumor cells. Thirty-three of the 40 specimens (82.5%) in the strong fluorescence group correlated with abundant tumor cells and 7 (17.5%) with scarce. Twenty-nine of the 40 specimens (72.5%) in the weak fluorescence group correlated with abundant tumor cells, 7 (17.5%) with scarce, and 4 (10%) with none. Fourteen of the 41 (34.2%) specimens in the no fluorescence group had abundant tumor cells, 11 (26.8%) had scarce, and 16 (39%) had none. The sensitivity was 75% and specificity was 80%. The positive predictive value was 95% and negative predictive value was 39%., Conclusions: Visualization of 5-ALA-induced tumor fluorescence with use of the Orbeye 3D digital exoscope was feasible and associated with a high positive predictive value., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Study Design: A retrospective analysis of a single-center consecutive series of patients., Objective: To test the hypothesis that using a mobile intraoperative computed tomography in combination with spinal navigation would result in better accuracy of lateral mass and pedicle screws between C3 and T5 levels, compared to cone-beam computed tomography and traditional 2D fluoroscopy., Summary of Background Data: Use of spinal navigation associated with 3D imaging has been shown to improve accuracy of screw positioning in the cervico-thoracic region. However, use of iCT imaging compared to a cone-beam CT has not been fully investigated in these types of surgical interventions., Methods: We retrospectively analyzed a series of patients who underwent posterior cervico-thoracic fixations using different intraoperative imaging systems in a single hospital. We identified three different groups of patients: Group A, operated under 2D-fluoroscopic guidance without navigation; Group B: O-arm guidance with navigation; Group C: iCT AIRO guidance with navigation. Primary outcome was the rate of accurately placed screws, measured on intra or postoperative CT scan with Neo et al. classification for cervical pedicles screws and Gertzbein et al. for thoracic pedicle screws. Screws in cervical lateral masses were evaluated according to a new classification created by the authors., Results: Data on 67 patients and 495 screws were available. Overall screw accuracy was 92.8% (95.6% for lateral mass screws, 81.6% for cervical pedicle screws, and 90% for thoracic pedicle screws). Patients operated with iCT AIRO navigation had significantly fewer misplaced screws (2.4%) compared to 2D-fluoroscopic guidance (9.1%) and O-arm navigation (9.7%) (P = 0.0152). Accuracy rate of iCT navigation versus O-arm navigation was significantly higher (P = 0.0042), and there was no statistically significant difference in surgical time between the three Groups (P = 0.5390)., Conclusion: Use of high-quality CT associated with spinal navigation significantly improved accuracy of screw positioning in the cervico-thoracic region.Level of Evidence: 3., (Copyright © 2020 Wolters Kluwer Health, Inc. All rights reserved.)

Objective: Focal cortical dysplasias (FCDs) are a common cause of drug-resistant focal epilepsy but frequently remain undetected by conventional magnetic resonance imaging (MRI) assessment. The visual detection can be facilitated by morphometric analysis of T1-weighted images, for example, using the Morphometric Analysis Program (v2018; MAP18), which was introduced in 2005, independently validated for its clinical benefits, and successfully integrated in standard presurgical workflows of numerous epilepsy centers worldwide. Here we aimed to develop an artificial neural network (ANN) classifier for robust automated detection of FCDs based on these morphometric maps and probe its generalization performance in a large, independent data set., Methods: In this retrospective study, we created a feed-forward ANN for FCD detection based on the morphometric output maps of MAP18. The ANN was trained and cross-validated on 113 patients (62 female, mean age ± SD =29.5 ± 13.6 years) with manually segmented FCDs and 362 healthy controls (161 female, mean age ± SD =30.2 ± 9.6 years) acquired on 13 different scanners. In addition, we validated the performance of the trained ANN on an independent, unseen data set of 60 FCD patients (28 female, mean age ± SD =30 ± 15.26 years) and 70 healthy controls (42 females, mean age ± SD = 40.0 ± 12.54 years)., Results: In the cross-validation, the ANN achieved a sensitivity of 87.4% at a specificity of 85.4% on the training data set. On the independent validation data set, our method still reached a sensitivity of 81.0% at a comparably high specificity of 84.3%., Significance: Our method shows a robust automated detection of FCDs and performance generalizability, largely independent of scanning site or MR-sequence parameters. Taken together with the minimal input requirements of a standard T1 image, our approach constitutes a clinically viable and useful tool in the presurgical diagnostic routine for drug-resistant focal epilepsy., (© 2021 The Authors. Epilepsia published by Wiley Periodicals LLC on behalf of International League Against Epilepsy.)

The extreme complexity of mammalian brains requires a comprehensive deconstruction of neuroanatomical structures. Scientists normally use a brain stereotactic atlas to determine the locations of neurons and neuronal circuits. However, different brain images are normally not naturally aligned even when they are imaged with the same setup, let alone under the differing resolutions and dataset sizes used in mesoscopic imaging. As a result, it is difficult to achieve high-throughput automatic registration without manual intervention. Here, we propose a deep learning-based registration method called DeepMapi to predict a deformation field used to register mesoscopic optical images to an atlas. We use a self-feedback strategy to address the problem of imbalanced training sets (sampling at a fixed step size in nonuniform brains of structures and deformations) and use a dual-hierarchical network to capture the large and small deformations. By comparing DeepMapi with other registration methods, we demonstrate its superiority over a set of ground truth images, including both optical and MRI images. DeepMapi achieves fully automatic registration of mesoscopic micro-optical images, even macroscopic MRI datasets, in minutes, with an accuracy comparable to those of manual annotations by anatomists.

Long scan times prohibit a widespread clinical applicability of 4D flow MRI in Fontan patients. As pulsatility in the Fontan pathway is minimal during the cardiac cycle, acquiring non-ECG gated 3D flow MRI may result in a reduction of scan time while accurately obtaining time-averaged clinical parameters in comparison with 2D and 4D flow MRI. Thirty-two Fontan patients prospectively underwent 2D (reference), 3D and 4D flow MRI of the Fontan pathway. Multiple clinical parameters were assessed from time-averaged flow rates, including the right-to-left pulmonary flow distribution (main endpoint) and systemic-to-pulmonary collateral flow (SPCF). A ten-fold reduction in scan time was achieved [4D flow 15.9 min (SD 2.7 min) and 3D flow 1.6 min (SD 7.8 s), p < 0.001] with a superior signal-to-noise ratio [mean ratio of SNRs 1.7 (0.8), p < 0.001] and vessel sharpness [mean ratio 1.2 (0.4), p = 0.01] with 3D flow. Compared to 2D flow, good-excellent agreement was shown for mean flow rates (ICC 0.82-0.96) and right-to-left pulmonary flow distribution (ICC 0.97). SPCF derived from 3D flow showed good agreement with that from 4D flow (ICC 0.86). 3D flow MRI allows for obtaining time-averaged flow rates and derived clinical parameters in the Fontan pathway with good-excellent agreement with 2D and 4D flow, but with a tenfold reduction in scan time and significantly improved image quality compared to 4D flow.

Objectives: To determine the level of agreement across assessments of follicle number per ovary (FNPO) and classifying of polycystic ovarian morphology (PCOM; FNPO ≥25) with the use of various real-time (RT) and off-line two-dimensional (2D) and three-dimensional (3D) ultrasonographic methods., Design: Method comparison study., Setting: University-based clinical research unit., Patient(s): Sixteen women with and without PCOM., Intervention: Thirty-two ovaries were analyzed with the use of eight ultrasonographic methods: 2D-Grid (reference method), 2D-RT, 2D-RT with Grid, multiplanar view (MPV), MPV-RT, tomographic ultrasound imaging (TUI), TUI-RT, and semiautomated volume calculation (SonoAVC)., Main Outcome Measure(s): FNPO, PCOM status, and time to obtain FNPO. Clinical feasibility, defined as the time taken to obtain FNPO, also was evaluated., Result(s): 2D-RT overestimated FNPO versus 2D-Grid (3 ± 9 follicles) owing to overcounting in non-PCOM ovaries (6 ± 6 follicles). However, systematic bias was not detected when a grid overlay was incorporated (2D-RT with Grid). SonoAVC underestimated FNPO (-3 ± 5 follicles), particularly in PCOM ovaries (-4.1 ± 5.0 follicles). No bias in FNPO was detected between MPV, TUI, or TUI-RT versus 2D-Grid. 2D-RT significantly misclassified ovaries as PCOM. All methods except MPV took less time to complete FNPO assessments compared with 2D-Grid., Conclusion(s): Variability in FNPO across ultrasonographic methods limits their interchangeable use, particularly when a precise metric is needed. 2D-RT may be problematic owing to its propensity to misclassify PCOM. 2D-RT with Grid and MPV-RT could represent clinically feasible alternatives to obtain FNPO and classify PCOM. Efforts to reduce variation in FNPO will clarify the relevance of PCOM in women's health., (Copyright © 2020 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.)

We assessed the histological accuracy of X-ray phase-contrast tomography (XPCT) and investigated three-dimensional (3D) ductal tissue distribution in coarctation of the aorta (CoA) specimens. We used nine CoA samples, including the aortic isthmus, ductus arteriosus (DA), and their confluences. 3D images were obtained using XPCT. After scanning, the samples were histologically evaluated using elastica van Gieson (EVG) staining and transcription factor AP-2 beta (TFAP2B) immunostaining. XPCT sectional images clearly depicted ductal tissue distribution as low-density areas. In comparison with EVG staining, the mass density of the aortic wall positively correlated with elastic fiber formation (R = 0.69, P < 0.001). TFAP2B expression was consistent with low-density area including intimal thickness on XPCT images. On 3D imaging, the distances from the DA insertion to the distal terminal of the ductal media and to the intima on the ductal side were 1.63 ± 0.22 mm and 2.70 ± 0.55 mm, respectively. In the short-axis view, the posterior extension of the ductal tissue into the aortic lumen was 79 ± 18% of the diameter of the descending aorta. In three specimens, the aortic wall was entirely occupied by ductal tissue. The ductal intima spread more distally and laterally than the ductal media. The contrast resolution of XPCT images was comparable to that of histological assessment. Based on the 3D images, we conclude that complete resection of intimal thickness, including the opposite side of the DA insertion, is required to eliminate residual ductal tissue and to prevent postoperative re-coarctation.

Whole brain neuroanatomy using tera-voxel light-microscopic data sets is of much current interest. A fundamental problem in this field is the mapping of individual brain data sets to a reference space. Previous work has not rigorously quantified in-vivo to ex-vivo distortions in brain geometry from tissue processing. Further, existing approaches focus on registering unimodal volumetric data; however, given the increasing interest in the marmoset model for neuroscience research and the importance of addressing individual brain architecture variations, new algorithms are necessary to cross-register multimodal data sets including MRIs and multiple histological series. Here we present a computational approach for same-subject multimodal MRI-guided reconstruction of a series of consecutive histological sections, jointly with diffeomorphic mapping to a reference atlas. We quantify the scale change during different stages of brain histological processing using the Jacobian determinant of the diffeomorphic transformations involved. By mapping the final image stacks to the ex-vivo post-fixation MRI, we show that (a) tape-transfer assisted histological sections can be reassembled accurately into 3D volumes with a local scale change of 2.0 ± 0.4% per axis dimension; in contrast, (b) tissue perfusion/fixation as assessed by mapping the in-vivo MRIs to the ex-vivo post fixation MRIs shows a larger median absolute scale change of 6.9 ± 2.1% per axis dimension. This is the first systematic quantification of local metric distortions associated with whole-brain histological processing, and we expect that the results will generalize to other species. These local scale changes will be important for computing local properties to create reference brain maps., (© 2020 Wiley Periodicals, Inc.)

Three-dimensional (3D) Magnetic resonance fingerprinting (MRF) permits whole-brain volumetric quantification of T1 and T2 relaxation values, potentially replacing conventional T1-weighted structural imaging for common brain imaging analysis. The aim of this study was to evaluate the repeatability and reproducibility of 3D MRF in evaluating brain cortical thickness and subcortical volumetric analysis in healthy volunteers using conventional 3D T1-weighted images as a reference standard. Scan-rescan tests of both 3D MRF and conventional 3D fast spoiled gradient recalled echo (FSPGR) were performed. For each sequence, the regional cortical thickness and volume of the subcortical structures were measured using standard automatic brain segmentation software. Repeatability and reproducibility were assessed using the within-subject coefficient of variation (wCV), intraclass correlation coefficient (ICC), and mean percent difference and ICC, respectively. The wCV and ICC of cortical thickness were similar across all regions with both 3D MRF and FSPGR. The percent relative difference in cortical thickness between 3D MRF and FSPGR across all regions was 8.0 ± 3.2%. The wCV and ICC of the volume of subcortical structures across all structures were similar between 3D MRF and FSPGR. The percent relative difference in the volume of subcortical structures between 3D MRF and FSPGR across all structures was 7.1 ± 3.6%. 3D MRF measurements of human brain cortical thickness and subcortical volumes are highly repeatable, and consistent with measurements taken on conventional 3D T1-weighted images. A slight, consistent bias was evident between the two, and thus careful attention is required when combining data from MRF and conventional acquisitions., (© 2020 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

BACKGROUND It is challenging to entirely show the anterior talofibular ligament (ATFL) and accurately diagnose ATFL injury with traditional 2-dimensional (2D) magnetic resonance imaging (MRI). With the introduction of 3.0T MRI, a 3-dimensional (3D) MRI sequence can achieve images with high spatial resolution. This study aimed to evaluate the accuracy of 3D MRI and compare it with 2D MRI in diagnosing ATFL injury. MATERIAL AND METHODS This was a prospective study in which 45 patients with clinically suspected ATFL injury underwent 2D MRI, 3D MRI, and 3D model reconstruction followed by arthroscopic surgery between February 2018 and April 2019. Two radiologists who had over 11 and 13 years of musculoskeletal experience assessed the injury of ATFL in consensus without any clinical clues. Arthroscopic surgery results were the standard reference of MRI accuracy. RESULTS The 3D MRI results of ATFL injury showed the sensitivity of diagnosis of complete tears of 83% and specificity of 82%. The partial tears diagnosis sensitivity was 78%, and specificity was 100%. The sensitivity of diagnosis of sprains was 100%, and the specificity was 97%. The 3D MRI accuracy of diagnosis was 98% for no injury, 98% for sprain, 91% for partial tear, and 82% for complete tear. The difference in the diagnosis of sprain and partial tears by 3D MRI and 2D MRI was statistically significant (P<0.05). A 3D reconstruction model was successfully created for all patients. CONCLUSIONS 3D MRI may be a reliable and accurate method to detect ATFL injury. The 3D reconstruction model using 3D MRI sequences has excellent prospects in application.

Purpose: To assess the signal composition of cone photoreceptors three-dimensionally in healthy retinas using adaptive optics optical coherence tomography (AO-OCT)., Methods: Study population. Twenty healthy eyes of ten subjects (age 23 to 67). Procedures. After routine ophthalmological assessments, eyes were examined using AO-OCT. Three-dimensional volumes were acquired at 2.5° and 6.5° foveal eccentricity in four main meridians (superior, nasal, inferior, temporal). Cone densities and signal compositions were investigated in four different planes: the cone inner segment outer segment junction (IS/OS), the cone outer segment combined with the IS/OS (ISOS+), the cone outer segment tips (COST) and full en-face plane (FEF) combining signals from all mentioned cone layers. Additionally, reliability of a simple semi-automated approach for assessment of cone density was tested. Main outcome measures. Cone density of IS/OS, IS/OS+, COST and FEF. Qualitative depiction and composition of each cone layer. Inter-rater agreement of cone density measurements., Results: Mean overall cone density at all eccentricities was highest at the FEF plane (21.160/mm2), followed by COST (20.450/mm2), IS/OS+ (19.920/mm2) and IS/OS (19.530/mm2). The different meridians and eccentricities had a significant impact on cone density, with lower eccentricity resulting in higher cone densities (p≤.001), which were highest at the nasal, then temporal, then inferior and then superior meridian. Depiction of the cone mosaic differed between all 4 layers regarding signal size and packing density. Therefore, different cone layers showed evident but not complete signal overlap. Using the semi-automated technique for counting of cone signals achieved high inter-rater reliability (ICC > .99)., Conclusions: In healthy individuals qualitative and quantitative changes in cone signals are found not only in different eccentricities and meridians, but also within different photoreceptor layers. The variation between cone planes has to be considered when assessing the integrity of cone photoreceptors in healthy and diseased eyes using adaptive optics technology., Competing Interests: The authors have declared that no competing interests exist.

Background: Frame-based stereotactic procedures are still the gold standard in neurosurgery. However, there is an increasing interest in robot-assisted technologies. Introducing these increasingly complex tools in the clinical setting raises the question about the time efficiency of the system and the essential learning curve of the surgeon., Methods: This retrospective study enrolled a consecutive series of patients undergoing a robot-assisted procedure after first system installation at one institution. All procedures were performed by the same neurosurgeon to capture the learning curve. The objective read-out were the surgical procedure time (SPT), the skin-to-skin time, and the intraoperative registration time (IRT) after laser surface registration (LSR), bone fiducial registration (BFR), and skin fiducial registration (SFR), as well as the quality of the registration (as measured by the fiducial registration error [FRE]). The time measures were compared to those for a patient group undergoing classic frame-based stereotaxy., Results: In the first 7 months, we performed 31 robot-assisted surgeries (26 biopsies, 3 stereotactic electroencephalography [SEEG] implantations, and 2 endoscopic procedures). The SPT was depending on the actual type of surgery (biopsies: 85.0 ± 36.1 min; SEEG: 154.9 ± 75.9 min; endoscopy: 105.5 ± 1.1 min; p = 0.036). For the robot-assisted biopsies, there was a significant reduction in SPT within the evaluation period, reaching the level of frame-based surgeries (58.1 ± 17.9 min; p < 0.001). The IRT was depending on the applied registration method (LSR: 16.7 ± 2.3 min; BFR: 3.5 ± 1.1 min; SFR: 3.5 ± 1.6 min; p < 0.001). In contrast to BFR and SFR, there was a significant reduction in LSR time during that period (p = 0.038). The FRE differed between the applied registration methods (LSR: 0.60 ± 0.17 mm; BFR: 0.42 ± 0.15 mm; SFR: 2.17 ± 0.78 mm; p < 0.001). There was a significant improvement in LSR quality during the evaluation period (p = 0.035)., Conclusion: Introducing stereotactic, robot-assisted surgery in an established clinical setting initially necessitates a prolonged intraoperative preparation time. However, there is a steep learning curve during the first cases, reaching the time level of classic frame-based stereotaxy. Thus, a stereotactic robot can be integrated into daily routine within a decent period of time, thereby expanding the neurosurgeons' armamentarium, especially for procedures with multiple trajectories., (© 2020 S. Karger AG, Basel.)

Deep brain stimulation (DBS) is a complex surgical procedure that requires detailed anatomical knowledge. In many fields of neurosurgery navigation systems are used to display anatomical structures during an operation to aid performing these surgeries. In frame-based DBS, the advantage of visualization has not yet been evaluated during the procedure itself. In this study, we added live visualization to a frame-based DBS system, using a standard navigation system and investigated its accuracy and potential use in DBS surgery. As a first step, a phantom study was conducted to investigate the accuracy of the navigation system in conjunction with a frame-based approach. As a second step, 5 DBS surgeries were performed with this combined approach. Afterwards, 3 neurosurgeons and 2 neurologists with different levels of experience evaluated the potential use of the system with a questionnaire. Moreover, the additional personnel, costs and required set up time were noted and compared to 5 consecutive standard procedures. In the phantom study, the navigation system showed an inaccuracy of 2.1 mm (mean SD 0.69 mm). In the questionnaire, a mean of 9.4/10 points was awarded for the use of the combined approach as a teaching tool, a mean of 8.4/10 for its advantage in creating a 3-dimensional (3-D) map and a mean of 8/10 points for facilitating group discussions. Especially neurosurgeons and neurologists in training found it useful to better interpret clinical results and side effects (mean 9/10 points) and neurosurgeons appreciated its use to better interpret microelectrode recordings (mean 9/10 points). A mean of 6/10 points was awarded when asked if the benefits were worth the additional efforts. Initially 2 persons, then one additional person was required to set up the system with no relevant added time or costs. Using a navigation system for live visualization during frame-based DBS surgery can improve the understanding of the complex 3-D anatomy and many aspects of the procedure itself. For now, we would regard it as an excellent teaching tool rather than a necessity to perform DBS surgeries., (© 2020 S. Karger AG, Basel.)

Segmentation is a complex task, faced by radiologists and researchers as radiomics and machine learning grow in potentiality. The process can either be automatic, semi-automatic, or manual, the first often not being sufficiently precise or easily reproducible, and the last being excessively time consuming when involving large districts with high-resolution acquisitions. A high-resolution CT of the chest is composed of hundreds of images, and this makes the manual approach excessively time consuming. Furthermore, the parenchymal alterations require an expert evaluation to be discerned from the normal appearance; thus, a semi-automatic approach to the segmentation process is, to the best of our knowledge, the most suitable when segmenting pneumonias, especially when their features are still unknown. For the studies conducted in our institute on the imaging of COVID-19, we adopted 3D Slicer, a freeware software produced by the Harvard University, and combined the threshold with the paint brush instruments to achieve fast and precise segmentation of aerated lung, ground glass opacities, and consolidations. When facing complex cases, this method still requires a considerable amount of time for proper manual adjustments, but provides an extremely efficient mean to define segments to use for further analysis, such as the calculation of the percentage of the affected lung parenchyma or texture analysis of the ground glass areas.

Mitochondria are dynamic organelles that change morphology to adapt to cellular energetic demands under both physiological and stress conditions. Cardiomyopathies and neuronal disorders are associated with structure-related dysfunction in mitochondria, but three-dimensional characterizations of the organelles are still lacking. In this study, we combined high-resolution imaging and 3D electron density information provided by cryo-soft X-ray tomography to characterize mitochondria cristae morphology isolated from murine. Using the linear attenuation coefficient, the mitochondria were identified (0.247 ± 0.04 µm -1 ) presenting average dimensions of 0.90 ± 0.20 µm in length and 0.63 ± 0.12 µm in width. The internal mitochondria structure was successfully identified by reaching up the limit of spatial resolution of 35 nm. The internal mitochondrial membranes invagination (cristae) complexity was calculated by the mitochondrial complexity index (MCI) providing quantitative and morphological information of mitochondria larger than 0.90 mm in length. The segmentation to visualize the cristae invaginations into the mitochondrial matrix was possible in mitochondria with MCI ≥ 7. Altogether, we demonstrated that the MCI is a valuable quantitative morphological parameter to evaluate cristae modelling and can be applied to compare healthy and disease state associated to mitochondria morphology.

Objective: We used a smartphone to construct three-dimensional (3D) models of keloids, then quantitatively simulate and evaluate these tissues., Methods: We uploaded smartphone photographs of 33 keloids on the chest, shoulder, neck, limbs, or abdomen of 28 patients. We used the parallel computing power of a graphics processing unit to calculate the spatial co-ordinates of each pixel in the cloud, then generated 3D models. We obtained the longest diameter, thickness, and volume of each keloid, then compared these data to findings obtained by traditional methods., Results: Measurement repeatability was excellent: intraclass correlation coefficients were 0.998 for longest diameter, 0.978 for thickness, and 0.993 for volume. When measuring the longest diameter and volume, the results agreed with Vernier caliper measurements and with measurements obtained after the injection of water into the cavity. When measuring thickness, the findings were similar to those obtained by ultrasound. Bland-Altman analyses showed that the ratios of 95% confidence interval extremes were 3.03% for longest diameter, 3.03% for volume, and 6.06% for thickness., Conclusion: Smartphones were used to acquire data that was then employed to construct 3D models of keloids; these models yielded quantitative data with excellent reliability and validity. The smartphone can serve as an additional tool for keloid diagnosis and research, and will facilitate medical treatment over the internet., (Copyright © 2020 Elsevier Ltd and ISBI. All rights reserved.)

Study Design: Prospective observational study., Objective: This article aims to develop a spatial augmented reality-based surgical navigation system to assist in the placement of pedicle screws in minimally invasive spine surgery and to verify the accuracy of this method., Summary of Background Data: Due to their high accuracy and good visualization ability, augmented reality surgical navigation systems have been used in minimally invasive surgeries. However, augmented reality does not allow information to be shared and restricts doctors., Methods: A surgical navigation system that implements augmented reality based on a projector can be used to realize the external visualization of virtual organs and surgical information through an improved multiple information fusion method. Using fiducial markers and imaging technology, the patient's spatial position is tracked and registered in real time. All the information is accurately fused with the patient's back skin, and the surgeon can see surgical information such as the preoperative plan and bones. Phantom experiments were used to verify the accuracy and effectiveness of the system., Results: In the phantom experiments, the accuracy of the pedicle screw insertion point on the dummy's skin was 0.441 ± 0.214 mm, the average location error into the dummy's body was 1.645 ± 0.355 mm, and the average axial and sagittal angulation errors were <0.9°., Conclusion: This article introduces and verifies the design of a new surgical navigation system based on spatial augmented reality for lumbar pedicle screw implantation. The system passed a series of phantom accuracy experiments. Compared with the traditional augmented reality navigation system, this system avoids the use of glasses and truly realizes the effect of naked-eye 3D, which is more convenient for doctors to use for communication during an operation., Level of Evidence: N/A.

Aim: To assess the validity of a new index, lateral head coverage (LHC), for describing hip dysplasia in a population of children with cerebral palsy (CP)., Method: LHC is derived from 3D ultrasound assessment. Twenty-two children (15 males, seven females; age 4-15y) with CP undergoing routine hip surveillance were recruited prospectively for the study. Each participant had both a planar radiograph acquired as part of their routine care and a 3D ultrasound assessment within 2 months. Reimer's migration percentage (RMP) and LHC were measured by the same assessor, and the correlation between them calculated using Pearson's correlation coefficient. The repeatability of LHC was investigated with three assessors, analysing each of 10 images three times. Inter- and intra-assessor variation was quantified using intraclass correlation coefficients., Results: LHC was strongly correlated with RMP (Spearman's rank correlation coefficient=-0.86, p<0.001). LHC had similar inter-assessor reliability to that reported for RMP (intraclass correlation coefficient=0.97 and intra-assessor intraclass correlation coefficient=0.98)., Interpretation: This is an initial validation of the use of 3D ultrasound in monitoring hip development in children with CP. LHC is comparable with RMP in estimating hip dysplasia with similar levels of reliability that are reported for RMP., (© 2020 The Authors. Developmental Medicine & Child Neurology published by John Wiley & Sons Ltd on behalf of Mac Keith Press.)

Eye motion is a major confound for magnetic resonance imaging (MRI) in neuroscience or ophthalmology. Currently, solutions toward eye stabilisation include participants fixating or administration of paralytics/anaesthetics. We developed a novel MRI protocol for acquiring 3-dimensional images while the eye freely moves. Eye motion serves as the basis for image reconstruction, rather than an impediment. We fully reconstruct videos of the moving eye and head. We quantitatively validate data quality with millimetre resolution in two ways for individual participants. First, eye position based on reconstructed images correlated with simultaneous eye-tracking. Second, the reconstructed images preserve anatomical properties; the eye's axial length measured from MRI images matched that obtained with ocular biometry. The technique operates on a standard clinical setup, without necessitating specialized hardware, facilitating wide deployment. In clinical practice, we anticipate that this may help reduce burdens on both patients and infrastructure, by integrating multiple varieties of assessments into a single comprehensive session. More generally, our protocol is a harbinger for removing the necessity of fixation, thereby opening new opportunities for ethologically-valid, naturalistic paradigms, the inclusion of populations typically unable to stably fixate, and increased translational research such as in awake animals whose eye movements constitute an accessible behavioural readout., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Objective: The initial wound measurement and regular monitoring of diabetic foot ulcers (DFU) is critical to assess treatment response. There is no standardized, universally accepted, quick, reliable, and quantitative assessment method to characterize DFU. To address this need, a novel topographic imaging system has been developed. Our study aims at assessing the reliability and practicality of the WoundVue ® camera technology in the assessment of DFU. Approach: The WoundVue system is a prototype device. It consists of two infrared cameras and an infrared projector, and it is able to produce a three-dimensional (3D) reconstruction of the wound structure. Fifty-seven diabetic foot wounds from patients seen in a multidisciplinary foot clinic were photographed from two different angles and distances by using the WoundVue camera. Wound area, volume, and maximum depth were measured for assessment of reliability. Thirty-one of these wounds also had area calculated by using the established Visitrak™ system, and a correlation between the area obtained by using both systems was assessed. Results: WoundVue images analysis showed excellent agreement for area (intraclass correlation coefficient [ICC]: 0.995), volume (ICC: 0.988), and maximum depth (ICC: 0.984). Good agreement was found for area measurement by using the WoundVue camera and Visitrak system (ICC: 0.842). The average percentage differences between measures obtained by using the WoundVue from different angles for assessment of different sizes and shapes of wounds were 2.9% (95% confidence interval [CI]: 0.3-5.4), 12.9% (95% CI: 9.6-35.7), and 6.2% (95% CI: 2.3-14.7) for area, maximum depth, and volume, respectively. Innovation: This is the first human trial evaluating this novel 3D wound measurement device. Conclusion: The WoundVue system is capable of recreating a 3D model of DFU and produces consistent data. Digital images are ideal for monitoring wounds over time, and the WoundVue camera has the potential to be a valuable adjunct in diabetic foot wound care.

Consistency and duplicability in Computed Tomography (CT) output is essential to quantitative imaging for lung cancer detection and monitoring. This study of CT-detected lung nodules investigated the reproducibility of volume-, density-, and texture-based features (outcome variables) over routine ranges of radiation dose, reconstruction kernel, and slice thickness. CT raw data of 23 nodules were reconstructed using 320 acquisition/reconstruction conditions (combinations of 4 doses, 10 kernels, and 8 thicknesses). Scans at 12.5%, 25%, and 50% of protocol dose were simulated; reduced-dose and full-dose data were reconstructed using conventional filtered back-projection and iterative-reconstruction kernels at a range of thicknesses (0.6-5.0 mm). Full-dose/B50f kernel reconstructions underwent expert segmentation for reference Region-Of-Interest (ROI) and nodule volume per thickness; each ROI was applied to 40 corresponding images (combinations of 4 doses and 10 kernels). Typical texture analysis metrics (including 5 histogram features, 13 Gray Level Co-occurrence Matrix, 5 Run Length Matrix, 2 Neighboring Gray-Level Dependence Matrix, and 3 Neighborhood Gray-Tone Difference Matrix) were computed per ROI. Reconstruction conditions resulting in no significant change in volume, density, or texture metrics were identified as "compatible pairs" for a given outcome variable. Our results indicate that as thickness increases, volumetric reproducibility decreases, while reproducibility of histogram- and texture-based features across different acquisition and reconstruction parameters improves. To achieve concomitant reproducibility of volumetric and radiomic results across studies, balanced standardization of the imaging acquisition parameters is required., Competing Interests: TPO and RG are employees of Siemens Healthineers. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

Introduction: During flow diversion, the choice of the length, diameter, and location of the deployed stent are critical for the success of the procedure. Sim&Size software, based on the three-dimensional rotational angiography (3D-RA) acquisition, simulates the release of the stent, suggesting optimal sizing, and displaying the degree of the wall apposition., Objective: To demonstrate technical and clinical impacts of the Sim&Size simulation during treatment with the Pipeline Flex Embolization Device., Methods: Consecutive patients who underwent aneurysm embolization with Pipeline at our department were retrospectively enrolled (January 2015-December 2017) and divided into two groups: treated with and without simulation. Through univariate and multivariate models, we evaluated: (1) rate of corrective intervention for non-optimal stent placement, (2) duration of intervention, (3) radiation dose, and (4) stent length., Results: 189 patients, 95 (50.2%) without and 94 (49.7%) with software assistance were analyzed. Age, sex, comorbidities, aneurysm characteristics, and operator's experience were comparable among the two groups. Procedures performed with the software had a lower rate of corrective intervention (9% vs 20%, p=0.036), a shorter intervention duration (46 min vs 52 min, p=0.002), a lower median radiation dose (1150 mGy vs 1558 mGy, p<0.001), and a shorter stent length (14 mm vs 16 mm, p<0.001)., Conclusions: In our experience, the use of the virtual simulation during Pipeline treatment significantly reduced the need for corrective intervention, the procedural time, the radiation dose, and the length of the stent., Competing Interests: Competing interests: VC declares having stocks of Sim&Cure., (© Author(s) (or their employer(s)) 2020. No commercial re-use. See rights and permissions. Published by BMJ.)

The zebrafish Weberian apparatus is an emerging model for human conductive hearing system. Their Weberian apparatus comprises minute bones and ligamentary links, and conducts sound pressure transmission from the gas bladder to inner ear through four pairs of Weberian ossicles along the vertebral column. We herein present a methodological study using MicroCT to image the Weberian apparatus for biomechanical and morphological analysis. The aim of this work is to evaluate computational models generated from multiple MicroCT scans with different parameters, to identify the most feasible scan combination for practical (minimized scan time) yet accurate (relative to highest resolution) biomechanical simulations. We segmented and created 3D models from CT scan image stacks at 4.64 μm, 5.05 μm, 9.30 μm and 13.08 μm voxel resolutions, respectively. Then, we used geometric morphometrics analysis to quantify inter-model shape differences, as well as a series of finite element modal and harmonic analyses to simulate auditory signal vibrations. Relative to the highest resolution and most accurate model, the Model 9.30 is closest in overall geometry and biomechanical behavior of all lower resolution models. The differences in resolution and quality of the CT substantially affect the segmentation and reconstruction process of the three-dimensional model of the ossicles, and the subsequent analyses. We conclude that scan voxel resolution is a key factor influencing outcomes of biomechanical simulations of delicate and minute structures, especially when studying the harmonic response of minute ossicles connected by ligaments using finite element modeling. Furthermore, contrast variations in CT images as determined by x-ray power and scan speed, also affect fidelity in 3D models and simulation outcomes., (Copyright © 2020 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: Stereotactic registration is the most critical step ensuring accuracy in deep brain stimulation (DBS) surgery. 3D fluoroscopy (XT) is emerging as an alternative to CT. XT has been shown to be safe and effective for intraoperative confirmation of lead position following implantation. However, there is a lack of studies evaluating the suitability of XT to be used for the more crucial step of registration and its capability of being merged to a preoperative MRI. This is the first study comparing accuracy, efficiency, and radiation exposure of XT- vs CT-based stereotactic registration and XT/MRI merging in deep brain stimulation., Methods: Mean absolute differences and Euclidean distance between planned (adjusted for intraoperative testing) and actual lead trajectories were calculated for accuracy of implantation. The radiation dose from each scan was recorded as the dose length product (DLP). Efficiency was measured as the time between the patient entering the operating room and the initial skin incision. A one-way ANOVA compared these parameters between patients that had either CT- or XT-based registration., Results: Forty-one patients underwent DBS surgery-25 in the CT group and 16 in the XT group. The mean absolute difference between CT and XT was not statistically significant in the x (p = 0.331), y (p = 0.951), or z (p = 0.807) directions. The Euclidean distance between patient groups did not differ significantly (p = 0.874). The average radiation exposure with XT (220.0 ± 0.1 mGy*cm) was significantly lower than CT (1269.3 ± 112.9 mGy*cm) (p < 0.001). There was no significant difference in registration time between CT (107.8 ± 23.1 min) and XT (106.0 ± 18.2 min) (p = 0.518)., Conclusion: XT-based frame registration was shown to result in similar implantation accuracy and significantly less radiation exposure compared with CT. Our results surprisingly showed no significant difference in registration time, but this may be due to a learning curve effect.

The aim of this study was to identify an efficient approach for 3D imaging of hand. The 3D photographs of hand were taken with Gemini structured-light scanning system (SL scanning) and CT scanning. The 3D photographs, average time of scanning and reconstruction were compared between these two indirect techniques. The reliability, reproducibility and accuracy were evaluated in these two indirect techniques and the direct measurement (DM). Statistical differences in the measurements were assessed by 99% probability, with clinical significance at > 0.5 mm. The Gemini structured-light scanning system established a complete and smooth 3D hand photograph with shorter scanning and reconstruction time. Reproducibility of CT scanning and SL scanning methods was better (P < 0.01, both) than the DM, but did not differ significantly from each other (P = 0.462). Of the 19 (31.58%) measurements obtained, 6 showed significant differences (P < 0.01). Significant differences were observed more often for circumference dimensions (5/9, 55.56%) than for length dimensions (1/10, 10%). Mean absolute error (AE) of the 10 subjects was very low for 3D CT (0.29 ± 0.10 mm) and SL scanning (0.30 ± 0.11 mm). Absolute percentage error (APE) was 4.69 ± 2.33% and 4.88 ± 2.22% for 3D CT and SL scanning, respectively. AE for the PIP circumference between the 3rd finger (0.58 mm) and 4th finger (0.53 mm) scan was > 0.5 mm, indicating significant difference between DM and CT scanning at the level of 99% probability. In this study, the Gemini structured-light scanning system not only successfully established a complete and smooth 3D hand photograph, but also shortened the scanning and reconstruction time. Compared to the DM, measurements obtained using the two indirect techniques did not show any statistically or clinically insignificant difference in the values of the remaining 17 of 19 measurements (89.47%). Therefore, either of the two alternative techniques could be used instead of the direct measurement method.

Although shown to have a great utility for a wide range of neuroscientific and clinical applications, diffusion-weighted magnetic resonance imaging (dMRI) faces a major challenge of low signal-to-noise ratio (SNR), especially when pushing the spatial resolution for improved delineation of brain's fine structure or increasing the diffusion weighting for increased angular contrast or both. Here, we introduce a comprehensive denoising framework for denoising magnitude dMRI. The framework synergistically combines the variance stabilizing transform (VST) with optimal singular value manipulation. The purpose of VST is to transform the Rician data to Gaussian-like data so that an asymptotically optimal singular value manipulation strategy tailored for Gaussian data can be used. The output of the framework is the estimated underlying diffusion signal for each voxel in the image domain. The usefulness of the proposed framework for denoising magnitude dMRI is demonstrated using both simulation and real-data experiments. Our results show that the proposed denoising framework can significantly improve SNR across the entire brain, leading to substantially enhanced performances for estimating diffusion tensor related indices and for resolving crossing fibers when compared to another competing method. More encouragingly, the proposed method when used to denoise a single average of 7 ​Tesla Human Connectome Project-style diffusion acquisition provided comparable performances relative to those achievable with ten averages for resolving multiple fiber populations across the brain. As such, the proposed denoising method is expected to have a great utility for high-quality, high-resolution whole-brain dMRI, desirable for many neuroscientific and clinical applications., (Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.)

Study Design: Method development., Objectives: To develop a reliable protocol for automatic segmentation of Thoracolumbar spinal cord using MRI based on K-means clustering algorithm in 3D images., Setting: University-based laboratory, Tehran, Iran., Methods: T2 structural volumes acquired from the spinal cord of 20 uninjured volunteers on a 3T MR scanner. We proposed an automatic method for spinal cord segmentation based on the K-means clustering algorithm in 3D images and compare our results with two available segmentation methods (PropSeg, DeepSeg) implemented in the Spinal Cord Toolbox. Dice and Hausdorff were used to compare the results of our method (K-Seg) with the manual segmentation, PropSeg, and DeepSeg., Results: The accuracy of our automatic segmentation method for T2-weighted images was significantly better or similar to the SCT methods, in terms of 3D DC (p < 0.001). The 3D DCs were respectively (0.81 ± 0.04) and Hausdorff Distance (12.3 ± 2.48) by the K-Seg method in contrary to other SCT methods for T2-weighted images., Conclusions: The output with similar protocols showed that K-Seg results match the manual segmentation better than the other methods especially on the thoracolumbar levels in the spinal cord due to the low image contrast as a result of poor SNR in these areas.

Introduction: Digital tools like 3D laser-based photonic scanners, which can assess external anthropometric measurements for population based studies, and predict body composition, are gaining in importance. Here we focus on a) systematic deviation between manually determined and scanned standard measurements, b) differences regarding the strength of association between these standard measurements and body composition, and c) improving these predictions of body composition by considering additional scan measurements., Methods: We analysed 104 men aged 19-23. Bioelectrical Impedance Analysis was used to estimate whole body fat mass, visceral fat mass and skeletal muscle mass (SMM). For the 3D body scans, an Anthroscan VITUSbodyscan was used to automatically obtain 90 body shape measurements. Manual anthropometric measurements (height, weight, waist circumference) were also taken., Results: Scanned and manually measured height, waist circumference, waist-to-height-ratio, and BMI were strongly correlated (Spearman Rho>0.96), however we also found systematic differences. When these variables were used to predict body fat or muscle mass, explained variation and prediction standard errors were similar between scanned and manual measurements. The univariable predictions performed well for both visceral fat (r2 up to 0.92) and absolute fat mass (AFM, r2 up to 0.87) but not for SMM (r2 up to 0.54). Of the 90 body scanner measures used in the multivariable prediction models, belly circumference and middle hip circumference were the most important predictors of body fat content. Stepwise forward model selection using the AIC criterion showed that the best predictive power (r2 up to 0.99) was achieved with models including 49 scanner measurements., Conclusion: The use of a 3D full body scanner produced results that strongly correlate to manually measured anthropometric measures. Predictions were improved substantially by including multiple measurements, which can only be obtained with a 3D body scanner, in the models., Competing Interests: The authors have declared that no competing interests exist.

Background and Purpose: Computational fluid dynamics (CFD) can provide valuable information regarding intracranial hemodynamics. Patient-specific models can be segmented from various imaging modalities, which may influence the geometric output and thus hemodynamic results. This study aims to compare CFD results from aneurysm models segmented from three-dimensional rotational angiography (3D-RA) versus novel four-dimensional CT angiography (4D-CTA)., Methods: Fourteen patients with 16 cerebral aneurysms underwent novel 4D-CTA followed by 3D-RA. Endoluminal geometries were segmented from each modality using an identical workflow, blinded to the other modality, to produce 28 'original' models. Each was then minimally edited a second time to match length of branches, producing 28 additional 'matched' models. CFD simulations were performed using estimated flow rates for 'original' models (representing real-world experience) and patient-specific flow rates from 4D-CTA for 'matched' models (to control for influence of modality alone)., Results: Overall, geometric and hemodynamic results were consistent between models segmented from 3D-RA and 4D-CTA, with correlations improving after matching to control for operator-introduced variability. Despite smaller 4D-CTA parent artery diameters (3.49±0.97 mm vs 3.78±0.92 mm for 3D-RA; p=0.005) and sac volumes (157 (37-750 mm 3 ) vs 173 (53-770 mm 3 ) for 3D-RA; p=0.0002), sac averages of time-averaged wall shear stress (TAWSS), oscillatory shear (OSI), and high frequency fluctuations (measured by spectral power index, SPI) were well correlated between 3D-RA and 4D-CTA 'matched' control models (TAWSS, R 2 =0.91; OSI, R 2 =0.79; SPI, R 2 =0.90)., Conclusions: Our study shows that CFD performed using 4D-CTA models produces reliable geometric and hemodynamic information in the intracranial circulation. 4D-CTA may be considered as a follow-up imaging tool for hemodynamic assessment of cerebral aneurysms., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2020. No commercial re-use. See rights and permissions. Published by BMJ.)

The annotation of three-dimensional (3D) cephalometric landmarks in 3D computerized tomography (CT) has become an essential part of cephalometric analysis, which is used for diagnosis, surgical planning, and treatment evaluation. The automation of 3D landmarking with high-precision remains challenging due to the limited availability of training data and the high computational burden. This paper addresses these challenges by proposing a hierarchical deep-learning method consisting of four stages: 1) a basic landmark annotator for 3D skull pose normalization, 2) a deep-learning-based coarse-to-fine landmark annotator on the midsagittal plane, 3) a low-dimensional representation of the total number of landmarks using variational autoencoder (VAE), and 4) a local-to-global landmark annotator. The implementation of the VAE allows two-dimensional-image-based 3D morphological feature learning and similarity/dissimilarity representation learning of the concatenated vectors of cephalometric landmarks. The proposed method achieves an average 3D point-to-point error of 3.63 mm for 93 cephalometric landmarks using a small number of training CT datasets. Notably, the VAE captures variations of craniofacial structural characteristics.

Objectives : Aneurysm remnants after microsurgical clipping have a risk of regrowth and rupture and have not been validated in the era of three-dimensional angiography. Therefore, this study aimed to evaluate the angiographic outcome using three-dimensional rotational images and determine the predictors for remnants after microsurgical clipping. Methods : Between January 2014 and May 2017, 139 aneurysms in 106 patients who were treated with microsurgical clipping, were eligible for this study. For the determination of aneurysm remnants after microsurgical clipping, the angiographic outcomes were evaluated using follow-up digital subtraction angiography within 7 days for unruptured aneurysms or within 2 weeks for ruptured aneurysms. According to the Sindou classification, the aneurysm remnants were dichotomized, and subgroup analysis was performed to identify the predictors of aneurysm remnants after clipping with various imaging parameters and clinical information. Results : The overall rate of aneurysm remnants was 29.5% (41/139), in which retreatments were needed in 6.5% (9/139). The neck size and maximum diameter of aneurysms were independent predisposing factors for the aneurysm remnants that need retreatment (OR: 2.30; p < 0.001; OR: 1.38; p < 0.001, respectively). Conclusions : This study demonstrated a low incidence of aneurysm remnants after microsurgical clipping which need to retreatment. However, selective postoperative angiography could provide us clear information of surgical result and evidence for long-term follow-up for some aneurysms with larger neck size (>5.7 mm) and maximum diameter (>7.1 mm).

Introduction: Three-dimensional (3D) printed models can be constructed utilising computed tomography (CT) data. This project aimed to determine the effect of changing the slice reconstruction interval (SRI) on the spatial replication accuracy of 3D-printed anatomical models constructed by fused deposition modelling (FDM)., Methods: Three bovine vertebrae and an imaging phantom were imaged using a CT scanner. The Queensland State Government's Animal Care and Protection Act 2001 did not apply as no animals were harmed to carry out scientific activity. The data were reconstructed into SRIs of 0.1, 0.3, 0.5 and 1 mm and processed by software before 3D printing. Specimens and printed models were measured with calipers to calculate mean absolute error prior to statistical analysis., Results: Mean absolute error from the original models for the 0.1, 0.3, 0.5 and 1 mm 3D-printed models was 0.592 ± 0.396 mm, 0.598 ± 0.479 mm, 0.712 ± 0.498 mm and 0.933 ± 0.457 mm, respectively. Paired t-tests (P < 0.05) indicated a statistically significant difference between all original specimens and corresponding 3D-printed models except the 0.1 mm vertebrae 2 (P = 0.061), 0.3 mm phantom 1 (P = 0.209) and 0.3 mm vertebrae 2 (P = 0.097)., Conclusion: This study demonstrated that changing the SRI influences the spatial replication accuracy of 3D-printed models constructed by FDM. Matching the SRI to the primary spatial resolution limiting factor of acquisition slice width or printer capabilities optimises replication accuracy., (© 2020 The Authors. Journal of Medical Radiation Sciences published by John Wiley & Sons Australia, Ltd on behalf of Australian Society of Medical Imaging and Radiation Therapy and New Zealand Institute of Medical Radiation Technology.)

Background: The three-dimensional surface imaging system is becoming more common in plastic surgeries. However, few studies have assessed three-dimensional periocular structures and surgical outcomes. This study aimed to propose a standardized three-dimensional anthropometric protocol for the periocular region, investigate its precision and accuracy, and determine the three-dimensional periocular anthropometric norms for young Caucasians., Methods: Thirty-nine healthy young Caucasians (78 eyes) were enrolled. Three-dimensional facial images were obtained with a VECTRA M3 stereophotogrammetry device. Thirty-eight measurements in periocular regions were obtained from these images. Every subject underwent facial surface capture twice to evaluate its precision. A paper ruler was applied to assess its accuracy., Results: Sixty-three percent of measurements in linear distances, curvatures, angles, and indices were found to reach a statistically significant difference between sexes (p ≤ 0.05, respectively). Across all measurements, the average mean absolute difference was 0.29 mm in linear dimensions, 0.56 mm in curvatures, 1.67 degrees in angles, and 0.02 in indices. In relative error of magnitude, 18 percent of the measurements were determined excellent, 51 percent very good, 31 percent good, and none moderate. The mean value of the paper-ruler scale was 10.01 ± 0.05 mm, the mean absolute difference value 0.02 mm, and the relative error of magnitude 0.17 percent., Conclusions: This is the first study to propose a detailed and standardized three-dimensional anthropometric protocol for the periocular region and confirm its high precision and accuracy. The results provided novel metric data concerning young Caucasian periocular anthropometry and determined the variability between sexes.

Background: Discriminating a junctional dilatation from a true saccular aneurysm is clinically important., Purpose: To evaluate the usefulness of high-resolution three-dimensional proton density-weighted turbo spin-echo magnetic resonance imaging (PD MRI) in distinguishing a junctional dilatation from an aneurysm of the posterior communicating artery (PcomA)., Methods: Eighty-two consecutive patients with 83 PcomA lesions, which were evaluated by time-of-flight (TOF) MR angiography (MRA), PD MRI, and digital subtraction angiography (DSA), were enrolled. These radiologic data were retrospectively and independently reviewed by two neurosurgeons, and each diagnosis based on TOF MRA, PD MRI, and DSA was compared. The diagnostic efficacy (interobserver agreement, intermodality agreement, and diagnostic performance) of PD MRI was compared with that of TOF MRA., Results: PD MRI showed higher AC1 (Gwet's agreement coefficient, PD MRI: 0.8942, 95% CI 0.8204 to 0.968; TOF MRA: 0.7185, 95% CI 0.5753 to 0.8617) and prevalence-adjusted bias-adjusted kappa coefficient (PABAK) (PD MRI: 0.8554, TOF MRA: 0.5904) than TOF MRA for interobserver agreement. For intermodality agreement, PD MRI also showed higher AC1 (PD MRI: 0.9069, 95% CI 0.8374 to 0.9764; TOF MRA: 0.7983, 95% CI 0.6969 to 0.8996) and PABAK (PD MRI: 0.8735, TOF MRA: 0.7289) than TOF MRA. The diagnostic performance of PD MRI was statistically superior to that of TOF MRA in sensitivity, specificity, positive predictive value, and negative predictive value., Conclusions: PD MRI could provide excellent diagnostic accuracy and better information in distinguishing a junctional dilatation from a true saccular aneurysm of the PcomA compared with TOF MRA., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2020. No commercial re-use. See rights and permissions. Published by BMJ.)

Rationale: Remodeling of the vessel wall and the formation of vascular networks are dynamic processes that occur during mammalian embryonic development and in adulthood. Plaque development and excessive neointima formation are hallmarks of atherosclerosis and vascular injury. As our understanding of these complex processes evolves, there is a need to develop new imaging techniques to study underlying mechanisms., Objective: We used tissue clearing and light-sheet microscopy for 3-dimensional (3D) profiling of the vascular response to carotid artery ligation and induction of atherosclerosis in mouse models., Methods and Results: Adipo-Clear and immunolabeling in combination with light-sheet microscopy were applied to image carotid arteries and brachiocephalic arteries, allowing for 3D reconstruction of vessel architecture. Entire 3D neointima formations with different geometries were observed within the carotid artery and scored by volumetric analysis. Additionally, we identified a CD31-positive adventitial plexus after ligation of the carotid artery that evolved and matured over time. We also used this method to characterize plaque extent and composition in the brachiocephalic arteries of ApoE-deficient mice on high-fat diet. The plaques exhibited inter-animal differences in terms of plaque volume, geometry, and ratio of acellular core to plaque volume. A 3D reconstruction of the endothelium overlying the plaque was also generated., Conclusions: We present a novel approach to characterize vascular remodeling in adult mice using Adipo-Clear in combination with light-sheet microscopy. Our method reconstructs 3D neointima formation after arterial injury and allows for volumetric analysis of remodeling, in addition to revealing angiogenesis and maturation of a plexus surrounding the carotid artery. This method generates complete 3D reconstructions of atherosclerotic plaques and uncovers their volume, geometry, acellular component, surface, and spatial position within the brachiocephalic arteries. Our approach may be used in a number of mouse models of cardiovascular disease to assess vessel geometry and volume. Visual Overview: An online visual overview is available for this article.

Imaging ultrastructures in cells using Focused Ion Beam Scanning Electron Microscope (FIB-SEM) yields section-by-section images at nano-resolution. Unfortunately, we observe that FIB-SEM often introduces sub-pixel drifts between sections, in the order of 2.5 nm. The accumulation of these drifts significantly skews distance measures and geometric structures, which standard image registration techniques fail to correct. We demonstrate that registration techniques based on mutual information and sum-of-squared-distances significantly underestimate the drift since they are agnostic to image content. For neuronal data at nano-resolution, we discovered that vesicles serve as a statistically simple geometric structure, making them well-suited for estimating the drift with sub-pixel accuracy. Here, we develop a statistical model of vesicle shapes for drift correction, demonstrate its superiority, and provide a self-contained freely available application for estimating and correcting drifted datasets with vesicles.

Optical tissue transparency permits scalable cellular and molecular investigation of complex tissues in 3D. Adult human organs are particularly challenging to render transparent because of the accumulation of dense and sturdy molecules in decades-aged tissues. To overcome these challenges, we developed SHANEL, a method based on a new tissue permeabilization approach to clear and label stiff human organs. We used SHANEL to render the intact adult human brain and kidney transparent and perform 3D histology with antibodies and dyes in centimeters-depth. Thereby, we revealed structural details of the intact human eye, human thyroid, human kidney, and transgenic pig pancreas at the cellular resolution. Furthermore, we developed a deep learning pipeline to analyze millions of cells in cleared human brain tissues within hours with standard lab computers. Overall, SHANEL is a robust and unbiased technology to chart the cellular and molecular architecture of large intact mammalian organs., Competing Interests: Declaration of Interests A.E. has filed a patent on SHANEL technologies described in this study., (Copyright © 2020 Elsevier Inc. All rights reserved.)

We present a comprehensive analysis of the submissions to the first edition of the Endoscopy Artefact Detection challenge (EAD). Using crowd-sourcing, this initiative is a step towards understanding the limitations of existing state-of-the-art computer vision methods applied to endoscopy and promoting the development of new approaches suitable for clinical translation. Endoscopy is a routine imaging technique for the detection, diagnosis and treatment of diseases in hollow-organs; the esophagus, stomach, colon, uterus and the bladder. However the nature of these organs prevent imaged tissues to be free of imaging artefacts such as bubbles, pixel saturation, organ specularity and debris, all of which pose substantial challenges for any quantitative analysis. Consequently, the potential for improved clinical outcomes through quantitative assessment of abnormal mucosal surface observed in endoscopy videos is presently not realized accurately. The EAD challenge promotes awareness of and addresses this key bottleneck problem by investigating methods that can accurately classify, localize and segment artefacts in endoscopy frames as critical prerequisite tasks. Using a diverse curated multi-institutional, multi-modality, multi-organ dataset of video frames, the accuracy and performance of 23 algorithms were objectively ranked for artefact detection and segmentation. The ability of methods to generalize to unseen datasets was also evaluated. The best performing methods (top 15%) propose deep learning strategies to reconcile variabilities in artefact appearance with respect to size, modality, occurrence and organ type. However, no single method outperformed across all tasks. Detailed analyses reveal the shortcomings of current training strategies and highlight the need for developing new optimal metrics to accurately quantify the clinical applicability of methods.

Transcatheter left atrial appendage occlusion is an increasingly used alternative to oral anticoagulation in selected patients with atrial fibrillation. Pre-procedural imaging is a prerequisite to a successful intervention, with transesophageal echocardiography as the current gold standard. However, cardiac computed tomography offers improved imaging with high-quality multiplanar and 3-dimensional reconstructed images. Nevertheless, the lack of a standardized imaging protocol has slowed the adoption of cardiac computed tomography into clinical practice. On the basis of current research and expert consensus, this paper provides a protocol for the preparation, acquisition, and interpretation of cardiac computed tomographic imaging in pre-procedural planning of left atrial appendage occlusion., (Copyright © 2020 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.)