High-Flow and Low-Flow Oxygen Delivery by Nasal Cannula Evaluated in Infant and Adult Airway Replicas.

BACKGROUND: The nasal cannula is widely regarded as a safe and effective means of administering low- and high-flow oxygen to patients irrespective of their age. However, variability in delivered oxygen concentration (FDO2 FDO2 ) via nasal cannula has the potential to pose health risks. The present study aimed to evaluate predictive equations for FDO2 over a large parameter space, including variation in breathing, oxygen flow, and upper-airway geometry representative of both young children and adults. METHODS: Realistic nasal airway geometries were previously collected from medical scans of adults, infants, and neonates. Nasal airway replicas based on these geometries were used to measure the FDO2 for low-flow oxygen delivery during simulated spontaneous breathing. The present study extends previously published data sets to include higher oxygen flows. The extended data sets included nasal cannula oxygen flows that ranged from 6 to 65 L/min for the adult replicas, and from 0.5 to 6 L/min for the infant replicas. For both age groups, FDO2 was measured over a range of breathing frequencies, inspiratory to expiratory time ratios, and tidal volumes. Measured FDO2 values were compared with values predicted by using a previously derived flow-weighted equation. RESULTS: For both age groups, FDO2 was observed to increase nonlinearly with the ratio between oxygen flow supplied to the nasal cannula and the average inhalation flow. The previously derived flow-weighted equation over-predicted FDO2 at higher oxygen flows. A new empirical equation, therefore, was proposed to predict FDO2 for either age group as a function of nasal cannula flow, tidal volume, and inspiratory time. Predicted FDO2 values matched measured values, with average relative errors of 2.4% for infants and 4.3% for adults. CONCLUSIONS: A new predictive equation for FDO2 was obtained that accurately matched measured data in both adult and infant airway replicas for low- and high-flow regimens.

MR Susceptibility Separation for Quantifying Lesion Paramagnetic and Diamagnetic Evolution in Relapsing-Remitting Multiple Sclerosis.

BACKGROUND: Multiple sclerosis (MS) lesion evolution may involve changes in diamagnetic myelin and paramagnetic iron. Conventional quantitative susceptibility mapping (QSM) can provide net susceptibility distribution, but not the discrete paramagnetic and diamagnetic components. PURPOSE: To apply susceptibility separation (χ separation) to follow lesion evolution in MS with comparison to R2 */R2 ' /QSM. STUDY TYPE: Longitudinal, prospective. SUBJECTS: Twenty relapsing-remitting MS subjects (mean age: 42.5 ± 9.4 years, 13 females; mean years of symptoms: 4.3 ± 1.4 years). FIELD STRENGTH/SEQUENCE: Three-dimensional multiple echo gradient echo (QSM and R2 * mapping), two-dimensional dual echo fast spin echo (R2 mapping), T2 -weighted fluid attenuated inversion recovery, and T1-weighted magnetization prepared gradient echo sequences at 3 T. ASSESSMENT: Data were analyzed from two scans separated by a mean interval of 14.4 ± 2.0 months. White matter lesions on fluid-attenuated inversion recovery were defined by an automatic pipeline, then manually refined (by ZZ/AHW, 3/25 years' experience in MRI), and verified by a radiologist (MN, 25 years' experience in MS). Susceptibility separation yielded the paramagnetic and diamagnetic susceptibility content of each voxel. Lesions were classified into four groups based on the variation of QSM/R2 * or separated into positive/negative components from χ separation. STATISTICAL TESTS: Two-sample paired t tests for assessment of longitudinal differences. Spearman correlation coefficients to assess associations between χ separation and R2 */R2 ' /QSM. Significant level: P < 0.005. RESULTS: A total of 183 lesions were quantified. Categorizing lesions into groups based on χ separation demonstrated significant annual changes in QSM//R2 */R2 ' . When lesions were grouped based on changes in QSM and R2 *, both changing in unison yielded a significant dominant paramagnetic variation and both opposing yielded a dominant diamagnetic variation. Significant Spearman correlation coefficients were found between susceptibility-sensitive MRI indices and χ separation. DATA CONCLUSION: Susceptibility separation changes in MS lesions may distinguish and quantify paramagnetic and diamagnetic evolution, potentially providing additional insight compared to R2 * and QSM alone. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 2.

Skeletal muscle fibre morphology in childhood-insights into myopenia in pediatric liver disease.

TAKE-HOME MESSAGE: Skeletal muscle morphology in healthy children changes with age. Liver disease may preferentially affect type II fibres in adults with end-stage liver disease (ESLD). More research is needed on the effects of ESLD on muscle morphology in children.

Deep Learning Based Parameterization of Diffeomorphic Image Registration for Cardiac Image Segmentation.

Cardiac segmentation from magnetic resonance imaging (MRI) is one of the essential tasks in analyzing the anatomy and function of the heart for the assessment and diagnosis of cardiac diseases. However, cardiac MRI generates hundreds of images per scan, and manual annotation of them is challenging and time-consuming, and therefore processing these images automatically is of interest. This study proposes a novel end-to-end supervised cardiac MRI segmentation framework based on a diffeomorphic deformable registration that can segment cardiac chambers from 2D and 3D images or volumes. To represent actual cardiac deformation, the method parameterizes the transformation using radial and rotational components computed via deep learning, with a set of paired images and segmentation masks used for training. The formulation guarantees transformations that are invertible and prevents mesh folding, which is essential for preserving the topology of the segmentation results. A physically plausible transformation is achieved by employing diffeomorphism in computing the transformations and activation functions that constrain the range of the radial and rotational components. The method was evaluated over three different data sets and showed significant improvements compared to exacting learning and non-learning based methods in terms of the Dice score and Hausdorff distance metrics.

Deep Learning Segmentation of the Right Ventricle in Cardiac MRI: The M&Ms Challenge.

In recent years, several deep learning models have been proposed to accurately quantify and diagnose cardiac pathologies. These automated tools heavily rely on the accurate segmentation of cardiac structures in MRI images. However, segmentation of the right ventricle is challenging due to its highly complex shape and ill-defined borders. Hence, there is a need for new methods to handle such structure's geometrical and textural complexities, notably in the presence of pathologies such as Dilated Right Ventricle, Tricuspid Regurgitation, Arrhythmogenesis, Tetralogy of Fallot, and Inter-atrial Communication. The last MICCAI challenge on right ventricle segmentation was held in 2012 and included only 48 cases from a single clinical center. As part of the 12th Workshop on Statistical Atlases and Computational Models of the Heart (STACOM 2021), the M&Ms-2 challenge was organized to promote the interest of the research community around right ventricle segmentation in multi-disease, multi-view, and multi-center cardiac MRI. Three hundred sixty CMR cases, including short-axis and long-axis 4-chamber views, were collected from three Spanish hospitals using nine different scanners from three different vendors, and included a diverse set of right and left ventricle pathologies. The solutions provided by the participants show that nnU-Net achieved the best results overall. However, multi-view approaches were able to capture additional information, highlighting the need to integrate multiple cardiac diseases, views, scanners, and acquisition protocols to produce reliable automatic cardiac segmentation algorithms.

Pediatric patient-specific three-dimensional virtual models for surgical decision making in resection of hepatic and retroperitoneal tumors.

PURPOSE: Typically, preoperative imaging is viewed in two dimensions (2D) only, but three-dimensional (3D) virtual models may improve viewers' anatomical perspective by permitting them to interact with the imaging through manipulating it in space. Research into the utility of these models in most surgical specialties is growing rapidly. This study investigates the utility of 3D virtual models of complex pediatric abdominal tumors for clinical decision making, particularly the decision to proceed with surgical resection or not. METHODS: 3D virtual models of tumors and adjacent anatomy were created from CT images of pediatric patients scanned for Wilms tumor, neuroblastoma or hepatoblastoma. Pediatric surgeons individually assessed the resectability of the tumors. First, they assessed resectability using the standard protocol of viewing imaging on conventional screens and then reassessed resectability after being presented with the 3D virtual models. Inter-physician agreement on resectability for each patient was analyzed using Krippendorff's alpha. Inter-physician agreement was used as a surrogate for correct interpretation. Participants were also surveyed afterward on the utility and practicality of the 3D virtual models for clinical decision making. RESULTS: Inter-physician agreement when using CT imaging alone was "fair" (Krippendorff's alpha α = 0.399), while inter-physician agreement when using 3D virtual models increased to "moderate" (Krippendorff's alpha α = 0.532). When surveyed about model utility, all 5 participants considered them helpful. Two participants felt the models would be practical for clinical use in most cases, while 3 felt they would be practical for select cases only. CONCLUSION: This study demonstrates the subjective utility of 3D virtual models of pediatric abdominal tumors for clinical decision making. The models are an adjunct that can be particularly useful in complicated tumors that efface or displace critical structures that may impact resectability. Statistical analysis demonstrates the improved inter-rater agreement with the 3D stereoscopic display over the 2D display. The use of 3D displays of medical images will increase over time, and evaluation of their potential usefulness in various clinical settings is necessary.

Benefit of stereoscopic volume rendering for the identification of pediatric pulmonary vein stenosis from CT angiography.

The use of three-dimensional (3D) technologies in medical practice is increasing; however, its use is largely untested. One 3D technology, stereoscopic volume-rendered 3D display, can improve depth perception. Pulmonary vein stenosis (PVS) is a rare cardiovascular pathology, often diagnosed by computed tomography (CT), where volume rendering may be useful. Depth cues may be lost when volume rendered CT is displayed on regular screens instead of 3D displays. The objective of this study was to determine whether the 3D stereoscopic display of volume-rendered CT improved perception compared to standard monoscopic display, as measured by PVS diagnosis. CT angiograms (CTAs) from 18 pediatric patients aged 3 weeks to 2 years were volume rendered and displayed with and without stereoscopic display. Patients had 0 to 4 pulmonary vein stenoses. Participants viewed the CTAs in 2 groups with half on monoscopic and half on stereoscopic display and the converse a minimum of 2 weeks later, and their diagnoses were recorded. A total of 24 study participants, comprised of experienced staff cardiologists, cardiovascular surgeons and radiologists, and their trainees viewed the CTAs and assessed the presence and location of PVS. Cases were classified as simple (2 or fewer lesions) or complex (3 or more lesions). Overall, there were fewer type 2 errors in diagnosis for stereoscopic display than standard display, an insignificant difference (p = 0.095). There was a significant decrease in type 2 errors for complex multiple lesion cases (≥3) vs simpler cases (p = 0.027) and improvement in localization of pulmonary veins (p = 0.011). Subjectively, 70% of participants stated that stereoscopy was helpful in the identification of PVS. The stereoscopic display did not result in significantly decreased errors in PVS diagnosis but was helpful for more complex cases.

T1 mapping of the myocardium and liver in the single ventricle population.

BACKGROUND: Fontan associated liver disease (FALD) is an increasingly recognized complication of the single ventricle circulation characterized by hepatic venous congestion leading to hepatic fibrosis. Within the Fontan myocardium, fibrotic myocardial remodeling may occur and lead to ventricular dysfunction. Magnetic resonance imaging (MRI) T1 mapping can characterize both myocardial and liver properties. OBJECTIVE: The aim of this study was to compare myocardial and liver T1 between single ventricle patients with and without a Fontan and biventricular controls. MATERIALS AND METHODS: A retrospective study of 3 groups of patients: 16 single ventricle patients before Fontan (SVpre 2 newborns, 9 pre-Glenn, 5 pre-Fontan, 31% single right ventricle [SRV]), 16 Fontans (56% SRV) and 10 repaired d-transposition of the great arteries (TGA). Native modified Look-Locker inversion T1 times were measured in the myocardium and liver. Cardiac MRI parameters, myocardial and liver T1 values were compared in the three groups. Correlations were assessed between liver T1 and cardiac parameters. RESULTS: Myocardial T1 was higher in SVpre (1,056 ± 48 ms) and Fontans (1,047 ± 41 ms) compared to TGA (1,012 ± 48 ms, P < 0.05). Increased liver T1 was found in both SVpre (683 ± 82 ms) and Fontan (727 ± 49 ms) patients compared to TGA patients (587 ± 58 ms, P < 0.001). There was no difference between single left ventricle (SLV) versus SRV myocardial or liver T1. Liver T1 showed moderate correlations with myocardial T1 (r = 0.48, confidence interval [CI] 0.26-0.72) and ejection fraction (r = -0.36, CI -0.66-0.95) but not with other volumetric parameters. CONCLUSION: Increased liver T1 at both pre- and post-Fontan stages suggests there are intrinsic liver abnormalities early in the course of single ventricle palliation. Increased myocardial T1 and its relationship to liver T1 suggest a combination of edema from passive venous congestion and/or myocardial fibrosis occurring in this population. Liver T1 may provide an earlier marker of liver disease warranting further study.

Variability in low-flow oxygen delivery by nasal cannula evaluated in neonatal and infant airway replicas.

BACKGROUND: The nasal cannula is considered a trusted and effective means of administering low-flow oxygen and is widely used for neonates and infants requiring oxygen therapy, despite an understanding that oxygen concentrations delivered to patients are variable. METHODS: In the present study, realistic nasal airway replicas derived from medical scans of children less than 3 months old were used to measure the fraction of oxygen inhaled (FiO2) through nasal cannulas during low-flow oxygen delivery. Parameters influencing variability in FiO2 were evaluated, as was the hypothesis that measured FiO2 values could be predicted using a simple, flow-weighted calculation that assumes ideal mixing of oxygen with entrained room air. Tidal breathing through neonatal and infant nasal airway replicas was controlled using a lung simulator. Parameters for nasal cannula oxygen flow rate, nasal airway geometry, tidal volume, respiratory rate, inhalation/exhalation, or I:E ratio (ti/te), breath waveform, and cannula prong insertion position were varied to determine their effect on measured FiO2. In total, FiO2 was measured for 384 different parameter combinations, with each combination repeated in triplicate. Analysis of variance (ANOVA) was used to assess the influence of parameters on measured FiO2. RESULTS: Measured FiO2 was not appreciably affected by the breath waveform shape, the replica geometry, or the cannula position but was significantly influenced by the tidal volume, the inhalation time, and the nasal cannula flow rate. CONCLUSIONS: The flow-weighted calculation overpredicted FiO2 for measured values above 60%, but an empirical correction to the calculation provided good agreement with measured FiO2 across the full range of experimental data.

'Teratoid' Hepatoblastoma: An Intriguing Variant of Mixed Epithelial-Mesenchymal Hepatoblastoma.

Liver neoplasms are quite rare in childhood. They often involve 6.7 cases per 10 million children aged 18 years or younger. Hepatoblastoma (HB) is the most frequent tumor, but this neoplasm's rarity points essentially to the difficulty of performing biologic studies and large-scale therapeutic trials. On the pathological ground, HB is separated into an entirely epithelial neoplasm or a mixed neoplasm with epithelial and mesenchymal components. This last category has been further subdivided into harboring teratoid features or not. The 'teratoid' HB includes a mixture of components with heterologous origin. The heterologous components include neuroectoderm, endoderm, or melanin-holding cells with or without mesenchymal components. The most important criterium for the teratoid component is neuroepithelium, melanin, and, more recently, a yolk-sac-like component and neuroendocrine components. The mesenchymal components include muscle, osteoid, and cartilage, which are most often observed mainly in 'teratoid' neoplasms. The teratoid component or mesenchymal components are diagnosed with biopsies. They appear more prominent after chemotherapy due to the response and shrinkage of epithelial elements and non- or low-responsive components of mixed HB. This review focuses on the clinical, radiological, and pathological findings of HB with teratoid features.

Tracheal Reconstruction for Congenital Tracheal Stenosis: A 950-Gram Neonate.

Congenital tracheal stenosis is a rare but life-threatening malformation of the trachea. Surgical reconstruction is high risk, and not frequently performed in neonates born of extreme prematurity and low birth weight. We present the case of an extremely premature 950-gram neonate with severe congenital tracheal stenosis who underwent tracheal reconstruction. Complete repair, with no residual stenosis, was achieved with slide tracheoplasty without the need for cardiopulmonary bypass.

A New Semi-automated Algorithm for Volumetric Segmentation of the Left Ventricle in Temporal 3D Echocardiography Sequences.

PURPOSE: Echocardiography is commonly used as a non-invasive imaging tool in clinical practice for the assessment of cardiac function. However, delineation of the left ventricle is challenging due to the inherent properties of ultrasound imaging, such as the presence of speckle noise and the low signal-to-noise ratio. METHODS: We propose a semi-automated segmentation algorithm for the delineation of the left ventricle in temporal 3D echocardiography sequences. The method requires minimal user interaction and relies on a diffeomorphic registration approach. Advantages of the method include no dependence on prior geometrical information, training data, or registration from an atlas. RESULTS: The method was evaluated using three-dimensional ultrasound scan sequences from 18 patients from the Mazankowski Alberta Heart Institute, Edmonton, Canada, and compared to manual delineations provided by an expert cardiologist and four other registration algorithms. The segmentation approach yielded the following results over the cardiac cycle: a mean absolute difference of 1.01 (0.21) mm, a Hausdorff distance of 4.41 (1.43) mm, and a Dice overlap score of 0.93 (0.02). CONCLUSION: The method performed well compared to the four other registration algorithms.

Thyroid Nodule Segmentation and Classification Using Deep Convolutional Neural Network and Rule-based Classifiers.

Thyroid cancer has a high prevalence all over the world. Accurate thyroid nodule diagnosis can lead to effective treatment and decrease the mortality rate. Ultrasound imaging is a safe, portable, and inexpensive tool for thyroid nodule monitoring. However, the widespread use of ultrasound has also resulted in over-diagnosis and over-treatment of nodules. There is also large variability in the assessment and characterization of nodules. Thyroid nodule classification requires precise delineation of the nodule boundary which is tedious and time- consuming. Automatic segmentation of nodule boundaries is highly desirable, however, it is challenging due to the wide range of nodule appearances, shapes, and sizes. In this study, we propose an end-to-end pipeline for nodule segmentation and classification. A residual dilated UNet (resDUnet) model is proposed for nodule segmentation. The output of resDUnet is fed to two rule-based classifiers to categorize the composition and echogenicity of the segmented nodule. We evaluate our segmentation method on a large dataset of 352 ultrasound images reviewed by a certified radiologist. When compared with ground-truth, resDUnet gives a higher Dice score than the standard UNet (82% vs. 81%). Our method requires minimal user interaction and it is robust to reasonable variations in the user-specified region-of-interest. We expect the proposed method to reduce variability in thyroid nodule assessment which results in more efficient and cost-effective monitoring of thyroid cancer.

Comparison of airway pressures and expired gas washout for nasal high flow versus CPAP in child airway replicas.

BACKGROUND: For children and adults, the standard treatment for obstructive sleep apnea is the delivery of continuous positive airway pressure (CPAP). Though effective, CPAP masks can be uncomfortable to patients, contributing to adherence concerns. Recently, nasal high flow (NHF) therapy has been investigated as an alternative, especially in CPAP-intolerant children. The present study aimed to compare and contrast the positive airway pressures and expired gas washout generated by NHF versus CPAP in child nasal airway replicas. METHODS: NHF therapy was investigated at a flow rate of 20 L/min and compared to CPAP at 5 cmH2O and 10 cmH2O for 10 nasal airway replicas, built from computed tomography scans of children aged 4-8 years. NHF was delivered with three different high flow nasal cannula models provided by the same manufacturer, and CPAP was delivered with a sealed nasal mask. Tidal breathing through each replica was imposed using a lung simulator, and airway pressure at the trachea was recorded over time. For expired gas washout measurements, carbon dioxide was injected at the lung simulator, and end-tidal carbon dioxide (EtCO2) was measured at the trachea. Changes in EtCO2 compared to baseline values (no intervention) were assessed. RESULTS: NHF therapy generated an average positive end-expiratory pressure (PEEP) of 5.17 ± 2.09 cmH2O (mean ± SD, n = 10), similar to PEEP of 4.95 ± 0.03 cmH2O generated by nominally 5 cmH2O CPAP. Variation in tracheal pressure was higher between airway replicas for NHF compared to CPAP. EtCO2 decreased from baseline during administration of NHF, whereas it increased during CPAP. No statistical difference in tracheal pressure nor EtCO2 was found between the three high flow nasal cannulas. CONCLUSION: In child airway replicas, NHF at 20 L/min generated average PEEP similar to CPAP at 5 cm H2O. Variation in tracheal pressure was higher between airway replicas for NHF than for CPAP. The delivery of NHF yielded expired gas washout, whereas CPAP impeded expired gas washout due to the increased dead space of the sealed mask.

Automated detection of pneumonia in lung ultrasound using deep video classification for COVID-19.

There is a crucial need for quick testing and diagnosis of patients during the COVID-19 pandemic. Lung ultrasound is an imaging modality that is cost-effective, widely accessible, and can be used to diagnose acute respiratory distress syndrome in patients with COVID-19. It can be used to find important characteristics in the images, including A-lines, B-lines, consolidation, and pleural effusion, which all inform the clinician in monitoring and diagnosing the disease. With the use of portable ultrasound transducers, lung ultrasound images can be easily acquired, however, the images are often of poor quality. They often require an expert clinician interpretation, which may be time-consuming and is highly subjective. We propose a method for fast and reliable interpretation of lung ultrasound images by use of deep learning, based on the Kinetics-I3D network. Our learned model can classify an entire lung ultrasound scan obtained at point-of-care, without requiring the use of preprocessing or a frame-by-frame analysis. We compare our video classifier against ground truth classification annotations provided by a set of expert radiologists and clinicians, which include A-lines, B-lines, consolidation, and pleural effusion. Our classification method achieves an accuracy of 90% and an average precision score of 95% with the use of 5-fold cross-validation. The results indicate the potential use of automated analysis of portable lung ultrasound images to assist clinicians in screening and diagnosing patients.

Multi-View 3-D Fusion Echocardiography: Enhancing Clinical Feasibility with a Novel Processing Technique.

A novel system for fusing 3-D echocardiography data sets from complementary acoustic windows was evaluated in 12 healthy volunteers and 12 patients with heart failure. We hypothesized that 3-D fusion would enable 3-D echocardiography in patients with limited acoustic windows. At least nine 3-D data sets were recorded, while three infrared cameras tracked the position and orientation of the transducer and chest respiratory movements. Corresponding 2-D planes of the fused 3-D data sets and of single-view 3-D data sets were assessed for image quality and compared with measurements of left ventricular function obtained with contrast 2-D echocardiography. The signal-to-noise ratio in accurately fused 3-D echocardiography recordings improved by 55% in systole (p < 0.001) and 47% in diastole (p < 0.00001) compared with the apical single-view recordings. The 3-D data sets acquired during short breath holds were successfully fused in 11 of 12 patients. The improvement in endocardial border definition (from 11.7 ± 6.0 to 24.0 ± 3.3, p < 0.01) enabled quantitative assessment of left ventricular function in 10 patients, with no significant difference in ejection fraction compared with contrast 2-D echocardiography. In patients with heart failure and limited acoustic windows, the novel fusion protocol provides 3-D data sets suitable for quantitative analysis of left ventricular function.