A New Coordinate System for Magnetic Resonance Imaging of the Vestibular System

Objectives: To develop and evaluate a new coordinate system for MRI of the vestibular system.Methods: In this study, 53 internal auditory canal MRI and 78 temporal bone CT datasets were analyzed. Mimics Medical software version 21.0 was used to visualize and three-dimensionally reconstruct the image data. We established a new coordinate system, named W–X, based on the center of the bilateral eyeballs and vertex of the bilateral superior semicircular canals. Using the W–X coordinate system and Reid's coordinate system, we measured the orientations of the planes of the anterior semicircular canal (ASCC), the lateral semicircular canal (LSCC), and the posterior semicircular canal (PSCC).Results: No significant differences between the angles measured using CT and MRI were found for any of the semicircular canal planes (p > 0.05). No statistical differences were found between the angles measured using Reid's coordinate system (CT) and the W–X coordinate system (MRI). The mean values of ∠ASCC & LSCC, ∠ASCC & PSCC, and ∠LSCC & PSCC were 84.67 ± 5.76, 94.21 ± 3.81, and 91.79 ± 5.22 degrees, respectively. The angle between the LSCC plane and the horizontal imaging plane was 15.64 ± 3.92 degrees, and the angle between the PSCC plane and the sagittal imaging plane was 48.79 ± 4.46 degrees.Conclusion: A new W–X coordinate system was developed for MRI studies of the vestibular system and can be used to measure the orientations of the semicircular canals.

Cloaking, trapping and superlensing of lamb waves with negative refraction

We report on experimental and numerical implementations of devices based on the negative refraction of elastic guided waves, the so-called Lamb waves. Consisting in plates of varying thickness, these devices rely on the concept of complementary media, where a particular layout of negative index media can cloak an object with its anti-object or trap waves around a negative corner. The diffraction cancellation operated by negative refraction is investigated by means of laser ultrasound experiments. However, unlike original theoretical predictions, these intriguing wave phenomena remain, nevertheless, limited to the propagating component of the wave-field. To go beyond the diffraction limit, negative refraction is combined with the concept of metalens, a device converting the evanescent components of an object into propagating waves. The transport of an evanescent wave-field is then possible from an object plane to a far-field imaging plane. Twenty years after Pendry’s initial proposal, this work thus paves the way towards an elastic superlens.

Classification of Cardiomyopathies from MR Cine Images Using Convolutional Neural Network with Transfer Learning

The automatic classification of various types of cardiomyopathies is desirable but has never been performed using a convolutional neural network (CNN). The purpose of this study was to evaluate currently available CNN models to classify cine magnetic resonance (cine-MR) images of cardiomyopathies. Method: Diastolic and systolic frames of 1200 cine-MR sequences of three categories of subjects (395 normal, 411 hypertrophic cardiomyopathy, and 394 dilated cardiomyopathy) were selected, preprocessed, and labeled. Pretrained, fine-tuned deep learning models (VGG) were used for image classification (sixfold cross-validation and double split testing with hold-out data). The heat activation map algorithm (Grad-CAM) was applied to reveal salient pixel areas leading to the classification. Results: The diastolic–systolic dual-input concatenated VGG model cross-validation accuracy was 0.982 ± 0.009. Summed confusion matrices showed that, for the 1200 inputs, the VGG model led to 22 errors. The classification of a 227-input validation group, carried out by an experienced radiologist and cardiologist, led to a similar number of discrepancies. The image preparation process led to 5% accuracy improvement as compared to nonprepared images. Grad-CAM heat activation maps showed that most misclassifications occurred when extracardiac location caught the attention of the network. Conclusions: CNN networks are very well suited and are 98% accurate for the classification of cardiomyopathies, regardless of the imaging plane, when both diastolic and systolic frames are incorporated. Misclassification is in the same range as inter-observer discrepancies in experienced human readers.

Reproducibility of diffusion tensor image analysis along the perivascular space (DTI-ALPS) for evaluating interstitial fluid diffusivity and glymphatic function: CHanges in Alps index on Multiple conditiON acquIsition eXperiment (CHAMONIX) study

Purpose The diffusion tensor image analysis along the perivascular space (DTI-ALPS) method was developed to evaluate the brain’s glymphatic function or interstitial fluid dynamics. This study aimed to evaluate the reproducibility of the DTI-ALPS method and the effect of modifications in the imaging method and data evaluation. Materials and methods Seven healthy volunteers were enrolled in this study. Image acquisition was performed for this test–retest study using a fixed imaging sequence and modified imaging methods which included the placement of region of interest (ROI), imaging plane, head position, averaging, number of motion-proving gradients, echo time (TE), and a different scanner. The ALPS-index values were evaluated for the change of conditions listed above. Results This test–retest study by a fixed imaging sequence showed very high reproducibility (intraclass coefficient = 0.828) for the ALPS-index value. The bilateral ROI placement showed higher reproducibility. The number of averaging and the difference of the scanner did not influence the ALPS-index values. However, modification of the imaging plane and head position impaired reproducibility, and the number of motion-proving gradients affected the ALPS-index value. The ALPS-index values from 12-axis DTI and 3-axis diffusion-weighted image (DWI) showed good correlation (r = 0.86). Also, a shorter TE resulted in a larger value of the ALPS-index. Conclusion ALPS index was robust under the fixed imaging method even when different scanners were used. ALPS index was influenced by the imaging plane, the number of motion-proving gradient axes, and TE in the imaging sequence. These factors should be uniformed in the planning ALPS method studies. The possibility to develop a 3-axis DWI-ALPS method using three axes of the motion-proving gradient was also suggested.

High-Resolution Imaging of Bacterial Spatial Organization with Vertical Cell Imaging by Nanostructured Immobilisation (VerCINI)

Light microscopy is indispensable for analysis of bacterial spatial organization. However, imaging in bacteria is difficult due to their small sizes and the fact that most species are non-spherical, meaning they typically lie horizontally on a microscope coverslip. This is especially problematic when considering that many essential bacterial processes—such as cell division—occur along the short axes of these cells, and so are viewed side-on by standard microscopy. We recently developed a pair of methods to overcome this problem by forcing cells to stand vertically during imaging, named VerCINI (Vertical Cell Imaging by Nanostructured Immobilisation) and µVerCINI (Microfluidic VerCINI). The concept behind both methods is that cells are imaged while confined vertically inside cell traps made from a nanofabricated mould. By doing so, the short axes of the cells are rotated parallel to the microscope imaging plane and are imaged with high resolution. μVerCINI combines the vertical cell confinement with microfluidics so that vertical imaging can be done during fluid exchange, such as during antibiotic perturbations. Here, we provide a practical guide to implementing both VerCINI and µVerCINI, with detailed protocols and experience-based tips so that interested researchers can easily use one or both imaging methods to complement their current approaches.

Intracellular Vesicle Entrapment of Nanobubble Ultrasound Contrast Agents Targeted to PSMA Promotes Prolonged Enhancement and Stability In Vivo and In Vitro

Previous work has shown that active targeting of nanobubble (NB) ultrasound contrast agents to the prostate-specific membrane antigen (PSMA) significantly prolongs ultrasound signal enhancement in PSMA-expressing prostate cancer. However, the specific mechanism behind this effect is not well understood. Furthermore, prior studies were carried out using clinical ultrasound scanners in a single imaging plane. Because tumor heterogeneity can have a drastic effect on bubble kinetics and resulting contrast enhancement, a single region of interest in one imaging plane over time may not fully represent the contrast dynamics of the entire tumor. Accordingly, in the current work, we used high-frequency dynamic parametric contrast-enhanced ultrasound (DCE-US) imaging to gain a detailed understanding of NB kinetics in prostate tumors in mice. Specifically, we examined the differences in enhancement between the tumor periphery and tumor core in the same imaging plane. We also quantified intact nanobubble retention in the entire tumor volume. To better understand the mechanism behind prolonged tumor enhancement, intracellular retention and the acoustic activity of PSMA-NB were evaluated in cell culture. DCE-US US data suggest that both tumor wash-in and retention of PSMA-NB are delayed due to biomarker interaction and binding. The longer retention of PSMA-NB signal in tumor core supported target-driven bubble extravasation. In vitro studies demonstrated a higher level of internalization and prolonged-acoustic activity of internalized PSMA-NB. GC/MS analysis confirmed gas persistence in the cells after PSMA-NB internalization. The active-targeting of NB results in cellular internalization via receptor-mediated endocytosis, and the location with intracellular vesicles (late-stage endosomes/lysosomes) significantly prolongs gas retention within the cells. These features can enable background-free diagnostic imaging of the target cells/tissues, as well as highly focused ultrasound-modulated therapeutic interventions.

Is T2 mapping reliable in evaluation of native and repair cartilage tissue of the knee?

Purpose To evaluate the effect of imaging plane and experience of observers on the reliability of T2 mapping of native and repair cartilage tissue of the knee. Methods Fifteen consecutive patients from two randomised controlled trials (RCTs) were included in this cross-sectional study. Patients with an isolated knee cartilage lesion were randomised to receive either debridement or microfracture (RCT 1) or debridement or autologous chondrocyte implantation (RCT 2). T2 mapping was performed in coronal and sagittal planes two years postoperatively. A musculoskeletal radiologist, a resident of radiology and two orthopaedic surgeons measured the T2 values independently. Intraclass Correlation Coefficient (ICC) with 95% Confidence Intervals was used to calculate the inter- and intraobserver agreement. Results Mean age for the patients was 36.8 ± 11 years, 8 (53%) were men. The overall interobserver agreement varied from poor to good with ICCs in the range of 0.27– 0.76 for native cartilage and 0.00 – 0.90 for repair tissue. The lowest agreement was achieved for evaluations of repair cartilage tissue. The estimated ICCs suggested higher inter- and intraobserver agreement for radiologists. On medial femoral condyles, T2 values were higher for native cartilage on coronal images (p < 0.001) and for repair tissue on sagittal images (p < 0.001). Conclusions The reliability of T2 mapping of articular cartilage is influenced by the imaging plane and the experience of the observers. This influence may be more profound for repair cartilage tissue. This is important to consider when using T2 mapping to measure outcomes after cartilage repair surgery. Trial registration ClinicalTrials.gov, NCT02637505 and NCT02636881, registered December 2015. Level of evidence II, based on prospective data from two RCTs.

Single-pixel imaging of dynamic objects using multi-frame motion estimation

Single-pixel imaging (SPI) enables the visualization of objects with a single detector by using a sequence of spatially modulated illumination patterns. For natural images, the number of illumination patterns may be smaller than the number of pixels when compressed-sensing algorithms are used. Nonetheless, the sequential nature of the SPI measurement requires that the object remains static until the signals from all the required patterns have been collected. In this paper, we present a new approach to SPI that enables imaging scenarios in which the imaged object, or parts thereof, moves within the imaging plane during data acquisition. Our algorithms estimate the motion direction from inter-frame cross-correlations and incorporate it in the reconstruction model. Moreover, when the illumination pattern is cyclic, the motion may be estimated directly from the raw data, further increasing the numerical efficiency of the algorithm. A demonstration of our approach is presented for both numerically simulated and measured data.

Automated cardiac volume assessment and cardiac long- and short-axis imaging plane prediction from electrocardiogram-gated computed tomography volumes enabled by deep learning

Aims To develop an automated method for bloodpool segmentation and imaging plane re-slicing of cardiac computed tomography (CT) via deep learning (DL) for clinical use in coronary artery disease (CAD) wall motion assessment and reproducible longitudinal imaging. Methods and results One hundred patients who underwent clinically indicated cardiac CT scans with manually segmented left ventricle (LV) and left atrial (LA) chambers were used for training. For each patient, long-axis (LAX) and short-axis planes were manually defined by an imaging expert. A DL model was trained to predict bloodpool segmentations and imaging planes. Deep learning bloodpool segmentations showed close agreement with manual LV [median Dice: 0.91, Hausdorff distance (HD): 6.18 mm] and LA (Dice: 0.93, HD: 7.35 mm) segmentations and a strong correlation with manual ejection fraction (Pearson r: 0.95 LV, 0.92 LA). Predicted planes had low median location (6.96 mm) and angular orientation (7.96°) errors which were comparable to inter-reader differences (P &gt; 0.71). 84–97% of DL-prescribed LAX planes correctly intersected American Heart Association segments, which was comparable (P &gt; 0.05) to manual slicing. In a test cohort of 144 patients, we evaluated the ability of the DL approach to provide diagnostic imaging planes. Visual scoring by two blinded experts determined ≥94% of DL-predicted planes to be diagnostically adequate. Further, DL-enabled visualization of LV wall motion abnormalities due to CAD and provided reproducible planes upon repeat imaging. Conclusion A volumetric, DL approach provides multiple chamber segmentations and can re-slice the imaging volume along standardized cardiac imaging planes for reproducible wall motion abnormality and functional assessment.

Compact lightweight imager of both gamma rays and neutrons based on a pixelated stilbene scintillator coupled to a silicon photomultiplier array

Dual particle imaging, in which both neutrons and gamma-rays in the environment can be individually characterized, is particularly attractive for monitoring mixed radiation emitters such as special nuclear materials (SNM). Effective SNM localization and detection benefits from high instrument sensitivity so that real-time imaging or imaging with a limited number of acquired events is enabled. For portable applications, one also desires a dual particle imager (DPI) that is readily deployable. We have developed a hand-held type DPI equipped with a pixelated stilbene-silicon photomultiplier (SiPM) array module and low sampling-rate analog-to-digital converters (ADCs) processed via a multiplexed readout. The stilbene-SiPM array (12 × 12 pixels) is capable of effectively performing pulse shape discrimination (PSD) between gamma-ray and neutron events and neutron/gamma-ray source localization on the imaging plane, as demonstrated with 252Cf neutron/gamma and 137Cs gamma-ray sources. The low sampling rate ADCs connected to the stilbene-SiPM array module result in a compact instrument with high sensitivity that provides a gamma-ray image of a 137Cs source, producing 6.4 μR/h at 1 m, in less than 69 s. A neutron image for a 3.5 × 105 n/s 252Cf source can also be obtained in less than 6 min at 1 m from the center of the system. The instrument images successfully with field of view of 50° and provides angular resolution of 6.8°.