Improving 3D edge detection for visual inspection of MRI coregistration and alignment.

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.

An Arbitrary Scale Super-Resolution Approach for 3D MR Images via Implicit Neural Representation.

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.

Towards 3D basic theories of plant forms.

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.

Validation of the Perception Neuron system for full-body motion capture.

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.

Effect of data binning and frame averaging for micro-CT image acquisition on the morphometric outcome of bone repair assessment.

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.

Testing the accuracy of 3D automatic landmarking via genome-wide association studies.

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.

Quantification of murine myocardial infarct size using 2-D and 4-D high-frequency ultrasound.

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.

Semiautomated 3D mapping of aneurysmal wall enhancement with 7T-MRI.

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.

Scientific validation of three-dimensional stereophotogrammetry compared to the IGAIS clinical scale for assessing wrinkles and scars after laser treatment.

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.

Reduced scan time and superior image quality with 3D flow MRI compared to 4D flow MRI for hemodynamic evaluation of the Fontan pathway.

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.

A comparison of two- and three-dimensional ultrasonographic methods for evaluation of ovarian follicle counts and classification of polycystic ovarian morphology.

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.

External validation of automated focal cortical dysplasia detection using morphometric analysis.

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.

A Prospective Validation Study of the First 3D Digital Exoscope for Visualization of 5-ALA-Induced Fluorescence in High-Grade Gliomas.

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.

Evaluation of 3-Dimensional Magnetic Resonance Imaging (3D MRI) in Diagnosing Anterior Talofibular Ligament Injury.

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.

Evaluation of Ductal Tissue in Coarctation of the Aorta Using X-Ray Phase-Contrast Tomography.

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.

Three-dimensional composition of the photoreceptor cone layers in healthy eyes using adaptive-optics optical coherence tomography (AO-OCT).

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.

To estimate the safety and efficacy of a 3-D visualization helmet for vitreoretinal surgery.

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.

Navigated Deep Brain Stimulation Surgery: Evaluating the Combined Use of a Frame-Based Stereotactic System and a Navigation System.

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.

Repeatability and reproducibility of human brain morphometry using three-dimensional magnetic resonance fingerprinting.

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.

DeepMapi: a Fully Automatic Registration Method for Mesoscopic Optical Brain Images Using Convolutional Neural Networks.

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.