Colonic displacement as a marker of endoscopic skill: development of a novel tool for endoscopy training.

BACKGROUND: Colonoscopy is a technically challenging procedure. The colonoscope is prone to forming loops in the colon, which can lead patient discomfort and even perforation. We hypothesized that expert endoscopists use techniques to avoid loop formation, identify and straighten loops earlier, and thus exert less force. METHODS: Using a commercially available physical colon simulator model (Kyoto Kagaku), electromagnetic tracking markers (NDI Medical) were placed along the mobile segments of the colon (sigmoid, transverse) to measure the degree of displacement of the colon as the scope was advanced to the cecum. The colon model was set for each participant to simulate a redundant alpha loop in the sigmoid colon. Gastroenterology and surgical trainees and attendings were assessed. Demographic data were collected for each participant. RESULTS: Seventy-five participants were enrolled in the study. There were 17 (22.7%) attending physicians, and 58 (77.3%) trainees. Attending physicians advanced the scope to the cecum faster. The mean time required for procedure completion was 360.5 s compared to 178.4 s for the trainee and attending groups respectively (mean difference: 182.1 s, 95% CI: 93.0, 269.7; p = 0.0002). Attending physicians exerted significantly lower mean colonic displacement than trainees. The mean colonic displacement was 79.8 mm for the trainee group and 57.9 mm for the attending group (mean difference: 21.9 mm, 95% CI: 2.6, 41.2; p = 0.04). Those who used torque steering caused lower maximum colonic displacement than those who used knob steering. CONCLUSION: Attending physicians advance the scope during colonoscopy in a manner that results in significantly less colonic displacement than resident trainees. Although prior studies have shown a difference in force application between endoscopists and inexperienced students, ours is the first to differentiate across varying degrees of endoscopic skill. Future studies will define metrics for incorporation into endoscopic training curricula, focusing on techniques that encourage safety and comfort for patients.

Ultra-High Field 7-Tesla Magnetic Resonance Imaging and Electroencephalography Findings in Epilepsy.

PURPOSE: Assessment of patients for temporal lobe epilepsy (TLE) surgery requires multimodality input, including EEG recordings to ensure optimal surgical planning. Often EEG demonstrates abnormal foci not detected on 1.5T MRI. Ultra-high field MRI at 7T provides improved resolution of the brain. We investigated the utility of 7T MRI to detect potential anatomical abnormalities associated with EEG changes. METHODS: Ultra-high field data were acquired on a 7T MRI scanner for 13 patients with history of drug resistant TLE who had had EEG telemetry recordings. Qualitative evaluation of 7T imaging for presence of focal abnormalities detected on EEG was performed. Correlation of 7T MRI findings with EEG recordings of focal slowing or interictal epileptic spikes (IEDs), and seizures was performed. RESULTS: Assessment of 7T MRI demonstrated concordance with TLE as determined by the multidisciplinary team in 61.5% of cases (n = 8). Among these, 3 patients exhibited supportive abnormal 7T MRI abnormalities not detected by 1.5T MRI. In patients who underwent surgery, 72.7% had concordant histopathology findings with 7T MRI findings (n = 8). However, qualitative assessment of 7T images revealed focal anatomical abnormalities to account for EEG findings in only 15.4% of patients (n = 2). Other regions that were found to have localized IEDs in addition to the lesional temporal lobe, included the contralateral temporal lobe (n = 5), frontal lobe (n = 3), and parieto-occipital lobe (n = 2). CONCLUSION: Ultra-high field 7T MRI findings show concordance with clinical data. However, 7T MRI did not reveal anatomical findings to account for abnormalities detected by EEG.

Characterizing white matter alterations subject to clinical laterality in drug-naïve de novo Parkinson's disease.

Parkinson's disease (PD) is a progressive neurodegenerative disorder that is characterized by a range of motor and nonmotor symptoms, often with the motor dysfunction initiated unilaterally. Knowledge regarding disease-related alterations in white matter pathways can effectively help improve the understanding of the disease and propose targeted treatment strategies. Microstructural imaging techniques, including diffusion tensor imaging (DTI), allows inspection of white matter integrity to study the pathogenesis of various neurological conditions. Previous voxel-based analyses with DTI measures, such as fractional anisotropy and mean diffusivity have uncovered changes in brain regions that are associated with PD, but the conclusions were inconsistent, partially due to small patient cohorts and the lack of consideration for clinical laterality onset, particularly in early PD. Fixel-based analysis (FBA) is a recent framework that offers tract-specific insights regarding white matter health, but very few FBA studies on PD exist. We present a study that reveals strengthened and weakened white matter integrity that is subject to symptom laterality in a large drug-naïve de novo PD cohort using complementary DTI and FBA measures. The findings suggest that the disease gives rise to tissue degeneration and potential re-organization in the early stage.

Evaluating High Spatial Resolution Diffusion Kurtosis Imaging at 3T: Reproducibility and Quality of Fit.

BACKGROUND: Diffusion kurtosis imaging (DKI) quantifies the non-Gaussian diffusion of water within tissue microstructure. However, it has increased fitting parameters and requires higher b-values. Evaluation of DKI reproducibility is important for clinical purposes. PURPOSE: To assess the reproducibility in whole-brain high-resolution DKI at varying b-values. STUDY TYPE: Retrospective. SUBJECTS AND PHANTOMS: In all, 44 individuals from the test-retest Human Connectome Project (HCP) database and 12 3D-printed phantoms. FIELD STRENGTH/SEQUENCE: Diffusion-weighted multiband echo-planar imaging sequence at 3T and 9.4T. magnetization-prepared rapid acquisition gradient echo at 3T for in vivo structural data only. ASSESSMENT: From HCP data with b-values = 1000, 2000, 3000 s/mm2 (dataset A), two additional datasets with b-values = 1000, 3000 s/mm2 (dataset B) and b-values = 1000, 2000 s/mm2 (dataset C) were extracted. Estimated DKI metrics from each dataset were used for evaluating reproducibility and fitting quality in white matter (WM) and gray matter (GM) based on whole-brain and regions of interest (ROIs). STATISTICAL TESTS: DKI reproducibility was assessed using the within-subject coefficient of variation (CoV), fitting residuals to evaluate DKI fitting accuracy and Pearson's correlation to investigate the presence of systematic biases. Repeated measures analysis of variance was used for statistical comparison. RESULTS: Datasets A and B exhibited lower DKI CoVs (<20%) compared to C (<50%) in both WM and GM ROIs (all P < 0.05). This effect varies between DKI and DTI parameters (P < 0.005). Whole-brain fitting residuals were consistent across datasets (P > 0.05), but lower residuals in dataset B were detected for the WM ROIs (P < 0.001). A similar trend was observed for the phantom data CoVs (<7.5%) at varying fiber orientations for datasets A and B. Finally, dataset C was characterized by higher residuals across the different fiber crossings (P < 0.05). DATA CONCLUSION: The study demonstrates that high reproducibility can still be achieved within a reasonable scan time, specifically dataset B, supporting the potential of DKI for aiding clinical tools in detecting microstructural changes.

Direct visualization and characterization of the human zona incerta and surrounding structures.

The zona incerta (ZI) is a small gray matter region of the deep brain first identified in the 19th century, yet direct in vivo visualization and characterization has remained elusive. Noninvasive detection of the ZI and surrounding region could be critical to further our understanding of this widely connected but poorly understood deep brain region and could contribute to the development and optimization of neuromodulatory therapies. We demonstrate that high resolution (submillimetric) longitudinal (T1) relaxometry measurements at high magnetic field strength (7 T) can be used to delineate the ZI from surrounding white matter structures, specifically the fasciculus cerebellothalamicus, fields of Forel (fasciculus lenticularis, fasciculus thalamicus, and field H), and medial lemniscus. Using this approach, we successfully derived in vivo estimates of the size, shape, location, and tissue characteristics of substructures in the ZI region, confirming observations only previously possible through histological evaluation that this region is not just a space between structures but contains distinct morphological entities that should be considered separately. Our findings pave the way for increasingly detailed in vivo study and provide a structural foundation for precise functional and neuromodulatory investigation.

The Effects of Positioning on the Volume/Location of the Internal Jugular Vein Using 2-Dimensional Tracked Ultrasound.

OBJECTIVE: To investigate the effects of different positioning on the volume/location of the internal jugular vein (IJV) using 2-dimensional (2D) tracked ultrasound. DESIGN: This was a prospective, observational study. SETTING: Local research institute. PARTICIPANTS: Healthy volunteers. INTERVENTIONS: Twenty healthy volunteers were scanned in the following 6 positions: (1) supine with head neutral, rotated 15 and 30 degrees to the left and (2) 5-, 10-, and 15-degree Trendelenburg position with head neutral. In each position the volunteer's neck was scanned using a 2D ultrasound probe tracked with a magnetic tracker. These spatially tracked 2D images were collected and reconstructed into a 3D volume of the IJV and carotid artery. This 3D ultrasound volume then was segmented to obtain a 3D surface on which measurements and calculations were performed. MEASUREMENTS AND MAIN RESULTS: The measurements included average cross-section area (CSA), CSA along the length of IJV, and average overlap rate. CSA (mm2) in the supine and 5-, 10-, and 15-degree Trendelenburg positions were as follows: 86.7 ± 44.8, 104.3 ± 54.5, 119.1 ± 58.6, and 133.7 ± 53.3 (p < 0.0001). CSA enlarged with the increase of Trendelenburg degree. Neither Trendelenburg position nor head rotation showed a correlation with overlap rate. CONCLUSIONS: Trendelenburg position significantly increased the CSA of the IJV, thus facilitating IJV cannulation. This new 3D reconstruction method permits the creation of a 3D volume through a tracked 2D ultrasound scanning system with image acquisition and integration and may prove useful in providing the user with a "road map" of the vascular anatomy of a patient's neck or other anatomic structures.

A framework for evaluating correspondence between brain images using anatomical fiducials.

Accurate spatial correspondence between template and subject images is a crucial step in neuroimaging studies and clinical applications like stereotactic neurosurgery. In the absence of a robust quantitative approach, we sought to propose and validate a set of point landmarks, anatomical fiducials (AFIDs), that could be quickly, accurately, and reliably placed on magnetic resonance images of the human brain. Using several publicly available brain templates and individual participant datasets, novice users could be trained to place a set of 32 AFIDs with millimetric accuracy. Furthermore, the utility of the AFIDs protocol is demonstrated for evaluating subject-to-template and template-to-template registration. Specifically, we found that commonly used voxel overlap metrics were relatively insensitive to focal misregistrations compared to AFID point-based measures. Our entire protocol and study framework leverages open resources and tools, and has been developed with full transparency in mind so that others may freely use, adopt, and modify. This protocol holds value for a broad number of applications including alignment of brain images and teaching neuroanatomy.

Advanced Endoscopic Navigation: Surgical Big Data, Methodology, and Applications.

Interventional endoscopy (e.g., bronchoscopy, colonoscopy, laparoscopy, cystoscopy) is a widely performed procedure that involves either diagnosis of suspicious lesions or guidance for minimally invasive surgery in a variety of organs within the body cavity. Endoscopy may also be used to guide the introduction of certain items (e.g., stents) into the body. Endoscopic navigation systems seek to integrate big data with multimodal information (e.g., computed tomography, magnetic resonance images, endoscopic video sequences, ultrasound images, external trackers) relative to the patient's anatomy, control the movement of medical endoscopes and surgical tools, and guide the surgeon's actions during endoscopic interventions. Nevertheless, it remains challenging to realize the next generation of context-aware navigated endoscopy. This review presents a broad survey of various aspects of endoscopic navigation, particularly with respect to the development of endoscopic navigation techniques. First, we investigate big data with multimodal information involved in endoscopic navigation. Next, we focus on numerous methodologies used for endoscopic navigation. We then review different endoscopic procedures in clinical applications. Finally, we discuss novel techniques and promising directions for the development of endoscopic navigation.

Quantification of local geometric distortion in structural magnetic resonance images: Application to ultra-high fields.

Ultra-high field magnetic resonance imaging (MRI) provides superior visualization of brain structures compared to lower fields, but images may be prone to severe geometric inhomogeneity. We propose to quantify local geometric distortion at ultra-high fields in in vivo datasets of human subjects scanned at both ultra-high field and lower fields. By using the displacement field derived from nonlinear image registration between images of the same subject, focal areas of spatial uncertainty are quantified. Through group and subject-specific analysis, we were able to identify regions systematically affected by geometric distortion at air-tissue interfaces prone to magnetic susceptibility, where the gradient coil non-linearity occurs in the occipital and suboccipital regions, as well as with distance from image isocenter. The derived displacement maps, quantified in millimeters, can be used to prospectively evaluate subject-specific local spatial uncertainty that should be taken into account in neuroimaging studies, and also for clinical applications like stereotactic neurosurgery where accuracy is critical. Validation with manual fiducial displacement demonstrated excellent correlation and agreement. Our results point to the need for site-specific calibration of geometric inhomogeneity. Our methodology provides a framework to permit prospective evaluation of the effect of MRI sequences, distortion correction techniques, and scanner hardware/software upgrades on geometric distortion.

Modeling Patient-Specific Deformable Mitral Valves.

Medical imaging has advanced enormously over the last few decades, revolutionizing patient diagnostics and care. At the same time, additive manufacturing has emerged as a means of reproducing physical shapes and models previously not possible. In combination, they have given rise to 3-dimensional (3D) modeling, an entirely new technology for physicians. In an era in which 3D imaging has become a standard for aiding in the diagnosis and treatment of cardiac disease, this visualization now can be taken further by bringing the patient's anatomy into physical reality as a model. The authors describe the generalized process of creating a model of cardiac anatomy from patient images and their experience creating patient-specific dynamic mitral valve models. This involves a combination of image processing software and 3D printing technology. In this article, the complexity of 3D modeling is described and the decision-making process for cardiac anesthesiologists is summarized. The management of cardiac disease has been altered with the emergence of 3D echocardiography, and 3D modeling represents the next paradigm shift.

Investigation of hippocampal substructures in focal temporal lobe epilepsy with and without hippocampal sclerosis at 7T.

PURPOSE: To provide a more detailed investigation of hippocampal subfields using 7T magnetic resonance imaging (MRI) for the identification of hippocampal sclerosis in temporal lobe epilepsy (TLE). MATERIALS AND METHODS: Patients (n = 13) with drug-resistant TLE previously identified by conventional imaging as having hippocampal sclerosis (HS) or not (nine without HS, four HS) and 20 age-matched healthy controls were scanned and compared using a 7T MRI protocol. Using a manual segmentation scheme to delineate hippocampal subfields, subfield-specific volume changes and apparent transverse relaxation rate ( R2*) were studied between the two groups. In addition, qualitative assessment at 7T and clinical outcomes were correlated with measured subfield changes. RESULTS: Volumetry of the hippocampus at 7T in HS patients revealed significant ipsilateral subfield atrophy in CA1 (P = 0.001) and CA4+DG (P < 0.001). Volumetry also uncovered subfield atrophy in 33% of patients without HS, which had not been detected using conventional imaging. R2* was significantly lower in the CA4+DG subfields (P = 0.001) and the whole hippocampus (P = 0.029) of HS patients compared to controls but not significantly lower than the group without HS (P = 0.077, P = 0.109). No correlation was found between quantitative volumetry and qualitative assessment as well as surgical outcomes (Sub, P = 0.495, P = 0.567, P = 0.528; CA1, P = 0.104 ± 0.171, P = 0.273, P = 0.554; CA2+CA3, P = 0.517, P = 0.952, P = 0.130 ± 0.256; CA4+DG, P = 0.052 ± 0.173, P = 0.212, P = 0.124 ± 0.204; WholeHipp, P = 0.187, P = 0.132 ± 0.197, P = 0.628). CONCLUSION: These preliminary findings indicate that hippocampal subfield volumetry assessed at 7T is capable of identifying characteristic patterns of hippocampal atrophy in HS patients; however, difficulty remains in using imaging to identify hippocampal pathologies in cases without HS. LEVEL OF EVIDENCE: 2 J. MAGN. RESON. IMAGING 2017;45:1359-1370.

Evaluation of ex-vivo 9.4T MRI in post-surgical specimens from temporal lobe epilepsy patients.

PURPOSE: This study evaluates hippocampal pathology through usage of ultra-high field 9.4T ex-vivo imaging of resected surgical specimens in patients who have undergone temporal lobe epilepsy surgery. METHOD AND MATERIALS: This is a retrospective interpretation of prospectively acquired data. MRI scanning of resected surgical specimens from patients who have undergone temporal lobe epilepsy surgery was performed on a 9.4T small bore Varian MR magnet. Structural images employed a balanced steady-state free precession sequence (TrueFISP). Six patients (3 females; 3 males) were included in this study with an average age at surgery of 40.7 years (range 20Y_"60) (one was used as a control reference). Two neuroradiologists qualitatively reviewed the ex-vivo MRIs of resected specimens while blinded to the histopathology reports for the ability to identify abnormal features in hippocampal subfield structures. RESULTS: The hippocampal subfields were reliably identified on the 9.4T ex-vivo scans in the hippocampal head region and hippocampal body region by both neuroradiologists in all 6 patients. There was high concordance to pathology for abnormalities detected in the CA1, CA2, CA3 and CA4 subfields. Detection of abnormalities in the dentate gyrus was also high with detection in 4 of 5 cases. The Cohen's kappa between the two neuroradiologists was calculated at 0.734 SE=0.102. CONCLUSIONS: Ex-vivo 9.4T specimen imaging can detect abnormalities in CA1, CA2, CA3, CA4 and DG in both the hippocampal head and body. There was good concordance between qualitative findings and histopathological abnormalities for CA1, CA2, CA3, CA4 and DG.

In vivo MRI signatures of hippocampal subfield pathology in intractable epilepsy.

OBJECTIVES: Our aim is to assess the subfield-specific histopathological correlates of hippocampal volume and intensity changes (T1, T2) as well as diff!usion MRI markers in TLE, and investigate the efficacy of quantitative MRI measures in predicting histopathology in vivo. EXPERIMENTAL DESIGN: We correlated in vivo volumetry, T2 signal, quantitative T1 mapping, as well as diffusion MRI parameters with histological features of hippocampal sclerosis in a subfield-specific manner. We made use of on an advanced co-registration pipeline that provided a seamless integration of preoperative 3 T MRI with postoperative histopathological data, on which metrics of cell loss and gliosis were quantitatively assessed in CA1, CA2/3, and CA4/DG. PRINCIPAL OBSERVATIONS: MRI volumes across all subfields were positively correlated with neuronal density and size. Higher T2 intensity related to increased GFAP fraction in CA1, while quantitative T1 and diffusion MRI parameters showed negative correlations with neuronal density in CA4 and DG. Multiple linear regression analysis revealed that in vivo multiparametric MRI can predict neuronal loss in all the analyzed subfields with up to 90% accuracy. CONCLUSION: Our results, based on an accurate co-registration pipeline and a subfield-specific analysis of MRI and histology, demonstrate the potential of MRI volumetry, diffusion, and quantitative T1 as accurate in vivo biomarkers of hippocampal pathology.

Magnetic resonance imaging and histology correlation in the neocortex in temporal lobe epilepsy.

OBJECTIVE: To investigate the histopathological correlates of quantitative relaxometry and diffusion tensor imaging (DTI) and to determine their efficacy in epileptogenic lesion detection for preoperative evaluation of focal epilepsy. METHODS: We correlated quantitative relaxometry and DTI with histological features of neuronal density and morphology in 55 regions of the temporal lobe neocortex, selected from 13 patients who underwent epilepsy surgery. We made use of a validated nonrigid image registration protocol to obtain accurate correspondences between in vivo magnetic resonance imaging and histology images. RESULTS: We found T1 to be a predictor of neuronal density in the neocortical gray matter (GM) using linear mixed effects models with random effects for subjects. Fractional anisotropy (FA) was a predictor of neuronal density of large-caliber neurons only (pyramidal cells, layers 3 and 5). Comparing multivariate to univariate mixed effects models with nested variables demonstrated that employing T1 and FA together provided a significantly better fit than T1 or FA alone in predicting density of large-caliber neurons. Correlations with clinical variables revealed significant positive correlations between neuronal density and age (rs = 0.726, pfwe = 0.021). This study is the first to relate in vivo T1 and FA values to the proportion of neurons in GM. INTERPRETATION: Our results suggest that quantitative T1 mapping and DTI may have a role in preoperative evaluation of focal epilepsy and can be extended to identify GM pathology in a variety of neurological disorders.

Diagnostic quality assessment of compressed sensing accelerated magnetic resonance neuroimaging.

PURPOSE: To determine the efficacy of compressed sensing (CS) reconstructions for specific clinical magnetic resonance neuroimaging applications beyond more conventional acceleration techniques such as parallel imaging (PI) and low-resolution acquisitions. MATERIALS AND METHODS: Raw k-space data were acquired from five healthy volunteers on a 3T scanner using a 32-channel head coil using T2 -FLAIR, FIESTA-C, time of flight (TOF), and spoiled gradient echo (SPGR) sequences. In a series of blinded studies, three radiologists independently evaluated CS, PI (GRAPPA), and low-resolution images at up to 5× accelerations. Synthetic T2 -FLAIR images with artificial lesions were used to assess diagnostic accuracy for CS reconstructions. RESULTS: CS reconstructions were of diagnostically acceptable quality at up to 4× acceleration for T2 -FLAIR and FIESTA-C (average qualitative scores 3.7 and 4.3, respectively, on a 5-point scale at 4× acceleration), and at up to 3× acceleration for TOF and SPGR (average scores 4.0 and 3.7, respectively, at 3× acceleration). The qualitative scores for CS reconstructions were significantly better than low-resolution images for T2 -FLAIR, FIESTA-C, and TOF and significantly better than GRAPPA for TOF and SPGR (Wilcoxon signed rank test, P < 0.05) with no significant difference found otherwise. Diagnostic accuracy was acceptable for both CS and low-resolution images at up to 3× acceleration (area under the ROC curve 0.97 and 0.96, respectively.) CONCLUSION: Mild to moderate accelerations are possible for those sequences by a combined CS and PI reconstruction. Nevertheless, for certain sequences/applications one might mildly reduce the acquisition time by appropriately reducing the imaging resolution rather than the more complicated CS reconstruction. J. Magn. Reson. Imaging 2016;44:433-444.

In vivo normative atlas of the hippocampal subfields using multi-echo susceptibility imaging at 7 Tesla.

OBJECTIVES: To generate a high-resolution atlas of the hippocampal subfields using images acquired from 7 T, multi-echo, gradient-echo MRI for the evaluation of epilepsy and neurodegenerative disorders as well as investigating R2* (apparent transverse relaxation rate) and quantitative volume magnetic susceptibility (QS) of the subfields. EXPERIMENTAL DESIGN: Healthy control subjects (n=17) were scanned at 7 T using a multi-echo gradient-echo sequence and susceptibility-weighted magnitude images, R2* and QS maps were reconstructed. We defined a hippocampal subfield labeling protocol for the magnitude image produced from the average of all echoes and assessed reproducibility through volume and shape metrics. A group-wise diffeomorphic registration procedure was used to generate an average atlas of the subfields for the whole subject cohort. The quantitative MRI maps and subfield labels were then warped to the average atlas space and used to measure mean values of R2* and QS characterizing each subfield. PRINCIPAL OBSERVATIONS: We were able to reliably label hippocampal subfields on the multi-echo susceptibility images. The group-averaged atlas accurately aligns these structures to produce a high-resolution depiction of the subfields, allowing assessment of both quantitative susceptibility and R2* across subjects. Our analysis of variance demonstrates that there are more apparent differences between the subfields on these quantitative maps than the normalized magnitude images. CONCLUSION: We constructed a high-resolution atlas of the hippocampal subfields for use in voxel-based studies and demonstrated in vivo quantification of susceptibility and R2* in the subfields. This work is the first in vivo quantification of susceptibility values within the hippocampal subfields at 7 T.

Max-IDEAL: a max-flow based approach for IDEAL water/fat separation.

PURPOSE: To propose a novel approach to water/fat separation using a unique smoothness constraint. THEORY AND METHODS: Chemical-shift based water/fat separation is an established noninvasive imaging tool for the visualization of body fat in various anatomies. Nevertheless, B0 magnetic field inhomogeneities can hamper the water/fat separation process. In this work, B0 variations are mapped using a convex-relaxed labeling model which produces a coarse estimate of the field map, while considering T2* decay during the labeling process. Fat and water components are subsequently resolved using T2*-IDEAL. An adaptive spatial filtering (ASF) was introduced to improve the robustness of the estimate. The method was tested on cardiac and abdominal datasets from healthy volunteers and nonalcoholic fatty liver disease (NAFLD) patients. RESULTS: Out of 168 cardiac and abdominal images, only 1 case has shown water/fat swaps that can hinder the clinical interpretation of the underlying anatomy. CONCLUSION: This work demonstrates a new water/fat separation approach that prevents the occurrence of water/fat swaps, by means of a unique smoothness constraint. Incorporating T2* effect in the labeling procedure and including the ASF processing enhance the robustness of the proposed approach and permit the procedure to handle abrupt B0 variations within the field of view.

High-resolution 3-dimensional late gadolinium enhancement scar imaging in surgically corrected Tetralogy of Fallot: clinical feasibility of volumetric quantification and visualization.

BACKGROUND: The extent of surgical scarring in Tetralogy of Fallot (TOF) may be a marker of adverse outcomes and provide substrate for ventricular arrhythmia. In this study we evaluate the feasibility of high resolution three dimensional (3D) late gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) for volumetric scar quantification in patients with surgically corrected TOF. METHODS: Fifteen consecutive patients underwent 3D LGE imaging with 3 Tesla CMR using a whole-heart, respiratory-navigated technique. A novel, signal-histogram based segmentation technique was tested for the quantification and modeling of surgical scar. Total scar volume was compared to the gold standard manual expert segmentation. The feasibility of segmented scar fusion to matched coronary CMR data for volumetric display was explored. RESULTS: Image quality sufficient for 3D scar segmentation was acquired in fourteen patients. Mean patient age was 32.2 ± 11.9 years (range 21 to 57 years) with mean right ventricle (RV) ejection fraction (EF) of 53.9 ± 9.2% and mean RV end diastolic volume of 117.0 ± 41.5 mL/m². The mean total scar volume was 11.1 ± 8.2 mL using semi-automated 3D segmentation with excellent correlation to manual expert segmentation (r = 0.99, bias = 0.89 mL, 95% CI -1.66 to 3.44). The mean segmentation time was significantly reduced using the novel semi-automated segmentation technique (10.1 ± 2.6 versus 45.8 ± 12.6 minutes). Excellent intra-observer and good inter-observer reproducibility was observed. CONCLUSION: 3D high resolution LGE imaging with semi-automated scar segmentation is clinically feasible among patients with surgically corrected TOF and shows excellent accuracy and reproducibility. This approach may offer a valuable clinical tool for risk prediction and procedural planning among this growing population.

Intra-thoracic fat volume is associated with myocardial infarction in patients with metabolic syndrome.

BACKGROUND: Visceral adiposity is increased in those with Metabolic Syndrome (MetS) and atherosclerotic disease burden. In this study we evaluate for associations between intra-thoracic fat volume (ITFV) and myocardial infarction (MI) in patients with MetS. METHODS: Ninety-four patients with MetS, MI or both were identified from a cardiovascular CMR clinical registry. MetS was defined in accordance to published guidelines; where-as MI was defined as the presence of subendocardial-based injury on late gadolinium enhancement imaging in a coronary vascular distribution. A healthy control group was also obtained from the same registry. Patients were selected into the following groups: MetS+/MI- (N = 32), MetS-/MI + (N = 30), MetS+/MI + (N = 32), MetS-/MI- (N = 16). ITFV quantification was performed using signal threshold analysis of sequential sagittal CMR datasets (HASTE) and indexed to body mass index. RESULTS: The mean age of the population was 59.8 ± 12.5 years. MetS+ patients (N=64) demonstrated a significantly higher indexed ITFV compared to MetS- patients (p = 0.05). Patients in respective MetS-/MI-, MetS+/MI-, MetS-/MI+, and MetS+/MI + study groups demonstrated a progressive elevation in the indexed ITFV (22.3 ± 10.6, 28.6 ± 12.6, 30.6 ± 12.3, and 35.2 ± 1.4 ml/kg/m(2), (p = 0.002)). Among MetS+ patients those with MI showed a significantly higher indexed ITFV compared to those without MI (p = 0.02). CONCLUSIONS: ITFV is elevated in patients with MetS and incrementally elevated among those with evidence of prior ischemic myocardial injury. Accordingly, the quantification of ITFV may be a valuable marker of myocardial infarction risk among patients with MetS and warrants further investigation.

X-ray image decomposition for improved magnetic navigation.

PURPOSE: Existing field generators (FGs) for magnetic tracking cause severe image artifacts in X-ray images. While FG with radio-lucent components significantly reduces these imaging artifacts, traces of coils and electronic components may still be visible to trained professionals. In the context of X-ray-guided interventions using magnetic tracking, we introduce a learning-based approach to further reduce traces of field-generator components from X-ray images to improve visualization and image guidance. METHODS: An adversarial decomposition network was trained to separate the residual FG components (including fiducial points introduced for pose estimation), from the X-ray images. The main novelty of our approach lies in the proposed data synthesis method, which combines existing 2D patient chest X-ray and FG X-ray images to generate 20,000 synthetic images, along with ground truth (images without the FG) to effectively train the network. RESULTS: For 30 real images of a torso phantom, our enhanced X-ray image after image decomposition obtained an average local PSNR of 35.04 and local SSIM of 0.97, whereas the unenhanced X-ray images averaged a local PSNR of 31.16 and local SSIM of 0.96. CONCLUSION: In this study, we proposed an X-ray image decomposition method to enhance X-ray image for magnetic navigation by removing FG-induced artifacts, using a generative adversarial network. Experiments on both synthetic and real phantom data demonstrated the efficacy of our method.