Citations

AbstractPurposeIt is unclear if a 3D transducer with the special design of mechanical swing or 2D array could provide acceptable 2D grayscale image quality for the general diagnosis purpose. The aim of this study is to compare the 2D image quality of a 3D intracavitary transducer with a conventional 2D intracavitary transducer using clinically relevant phantom experiments.MethodsAll measurements were performed on a GE Logiq E9 scanner with both a 2D (IC5‐9‐D) and a 3D (RIC5‐9‐D) transducer used in 2D mode. Selection of phantom targets and acquisition parameters were determined from analysis of 33 clinical pelvic exams. Depth of penetration (DOP), contrast response, contrast of anechoic cylinders (diameter: 6.7 mm) at 1.5 and 4.5 cm depths in transverse planes, and in‐plane resolution represented by full‐width half‐maximum of pin targets at multiple depths were measured with transmit frequencies of 7 and 8 MHz. Spherical signal‐noise‐ratio (SNR) (diameter: 4 and 2 mm) at multiple depths were measured at 8 MHz.ResultsRIC5‐9‐D demonstrated <8% decrease in DOP for both transmit frequencies (7 MHz: 69.7 ± 8.2 mm; 8 MHz: 64.3 ± 7.8 mm) compared with those from IC5‐9‐D (7 MHz: 73.9 ± 4.4 mm; 8 MHz: 69.4 ± 7.8 mm). A decreased anechoic contrast was observed with a 4.5 cm depth for RIC5‐9‐D (7 MHz: 23.2 ± 1.8 dB, P > 0.05; 8 MHz: 17.7 ± 0.9 dB, P < 0.01) compared with IC5‐9‐D (7 MHz: 25.9 ± 1.2 dB; 8 MHz: 21.5 ± 0.8 dB). The contrast response and spatial resolution performance were comparable between the two transducers. RIC5‐9‐D showed comparable SNR of anechoic spheres compared to IC5‐9‐D.Conclusions2D images from a 3D probe exhibited comparable overall image quality for routine clinical pelvic imaging.

Abstract Depression is a seriously disabling psychiatric disorder with a significant burden of disease. Metabolic abnormalities have been widely reported in depressed patients and animal models. However, there are few systematic efforts that integrate meaningful biological insights from these studies. Herein, available metabolic knowledge in the context of depression was integrated to provide a systematic and panoramic view of metabolic characterization. After screening more than 10 000 citations from five electronic literature databases and five metabolomics databases, we manually curated 5675 metabolite entries from 464 studies, including human, rat, mouse and non-human primate, to develop a new metabolite-disease association database, called MENDA (http://menda.cqmu.edu.cn:8080/index.php). The standardized data extraction process was used for data collection, a multi-faceted annotation scheme was developed, and a user-friendly search engine and web interface were integrated for database access. To facilitate data analysis and interpretation based on MENDA, we also proposed a systematic analytical framework, including data integration and biological function analysis. Case studies were provided that identified the consistently altered metabolites using the vote-counting method, and that captured the underlying molecular mechanism using pathway and network analyses. Collectively, we provided a comprehensive curation of metabolic characterization in depression. Our model of a specific psychiatry disorder may be replicated to study other complex diseases.

Zebrafish are increasingly utilized to model cardiomyopathies and regeneration. Current methods evaluating cardiac function have known limitations, fail to reliably detect focal mechanics, and are not readily feasible in zebrafish. We developed a semiautomated, open-source method — displacement analysis of myocardial mechanical deformation (DIAMOND) — for quantitative assessment of 4D segmental cardiac function. We imaged transgenic embryonic zebrafish in vivo using a light-sheet fluorescence microscopy system with 4D cardiac motion synchronization. Our method permits the derivation of a transformation matrix to quantify the time-dependent 3D displacement of segmental myocardial mass centroids. Through treatment with doxorubicin, and by chemically and genetically manipulating the myocardial injury–activated Notch signaling pathway, we used DIAMOND to demonstrate that basal ventricular segments adjacent to the atrioventricular canal display the highest 3D displacement and are also the most susceptible to doxorubicin-induced injury. Thus, DIAMOND provides biomechanical insights into in vivo segmental cardiac function scalable to high-throughput research applications.

Tissue regeneration is a process by which the remaining cells of an injured organ regrow to offset the missed cells. This field is relatively a new discipline that has been a focus of intense research by clinicians, surgeons, and scientists for decades. It constitutes the cornerstone of tissue engineering, creation of artificial organs, and generation and utilization of therapeutic stem cells to undergo transformation to different types of mature cells. Many medical experts, scientists, biologists, and bioengineers have dedicated their efforts to deeply comprehend the process of liver regeneration, striving for harnessing it to invent new therapies for liver failure. Liver regeneration after partial hepatectomy in rodents has been extensively studied by researchers for many years. It is divided into three important distinctive phases including (a) Initiation or priming phase which includes an overexpression of specific genes to prepare the liver cells for replication, (b) Proliferation phase in which the liver cells undergo a series of cycles of cell division and expansion and finally, (c) termination phase which acts as brake to stop the regenerative process and prevent the liver tissue overgrowth. These events are well controlled by cytokines, growth factors, and signaling pathways. In this review, we describe the function, embryology, and anatomy of human liver, discuss the molecular basis of liver regeneration, elucidate the hepatocyte and cholangiocyte lineages mediating this process, explain the role of hepatic progenitor cells and elaborate the developmental signaling pathways and regulatory molecules required to procure a complete restoration of hepatic lobule. This article is categorized under: Adult Stem Cells, Tissue Renewal, and Regeneration > Regeneration Signaling Pathways > Global Signaling Mechanisms Gene Expression and Transcriptional Hierarchies > Cellular Differentiation

PurposeThis work aims to develop a new framework of image quality assessment using deep learning‐based model observer (DL‐MO) and to validate it in a low‐contrast lesion detection task that involves CT images with patient anatomical background.MethodsThe DL‐MO was developed using the transfer learning strategy to incorporate a pretrained deep convolutional neural network (CNN), a partial least square regression discriminant analysis (PLS‐DA) model and an internal noise component. The CNN was previously trained to achieve the state‐of‐the‐art classification accuracy over a natural image database. The earlier layers of the CNN were used as a deep feature extractor, with the assumption that similarity exists between the CNN and the human visual system. The PLSR model was used to further engineer the deep feature for the lesion detection task in CT images. The internal noise component was incorporated to model the inefficiency and variability of human observer (HO) performance, and to generate the ultimate DL‐MO test statistics. Seven abdominal CT exams were retrospectively collected from the same type of CT scanners. To compare DL‐MO with HO, 12 experimental conditions with varying lesion size, lesion contrast, radiation dose, and reconstruction types were generated, each condition with 154 trials. CT images of a real liver metastatic lesion were numerically modified to generate lesion models with four lesion sizes (5, 7, 9, and 11 mm) and three contrast levels (15, 20, and 25 HU). The lesions were inserted into patient liver images using a projection‐based method. A validated noise insertion tool was used to synthesize CT exams with 50% and 25% of routine radiation dose level. CT images were reconstructed using the weighted filtered back projection algorithm and an iterative reconstruction algorithm. Four medical physicists performed a two‐alternative forced choice (2AFC) detection task (with multislice scrolling viewing mode) on patient images across the 12 experimental conditions. DL‐MO was operated on the same datasets. Statistical analyses were performed to evaluate the correlation and agreement between DL‐MO and HO.ResultsA statistically significant positive correlation was observed between DL‐MO and HO for the 2AFC low‐contrast detection task that involves patient liver background. The corresponding Pearson product moment correlation coefficient was 0.986 [95% confidence interval (0.950, 0.996)]. Bland–Altman agreement analysis did not indicate statistically significant differences.ConclusionsThe proposed DL‐MO is highly correlated with HO in a low‐contrast detection task that involves realistic patient liver background. This study demonstrated the potential of the proposed DL‐MO to assess image quality directly based on patient images in realistic, clinically relevant CT tasks.

ABSTRACTTissue‐engineering approaches have great potential to improve the treatment of tendon injuries which are major musculoskeletal disorders. The purpose of this study was to assess the tissue engineering potential of a novel multilayered decellularized tendon “book” scaffold with bone marrow mesenchymal stem cells (BMSCs) sheets for repair of an Achilles tendon defect in a rabbit model. In this study, we developed a novel book‐shaped decellularized scaffold derived from the extracellular matrix of tendon tissues from New Zealand white rabbits. Hematoxylin and eosin (H&E) staining, 4′, 6‐diamidino‐2‐phenylindole (DAPI) staining, DNA quantitation, and scanning electron microscopy (SEM) confirmed the efficiency of decellularization. After culturing BMSCs on decellularized scaffolds, 3‐(4, 5‐dimethylthiazol‐2‐yl)‐2, 5‐diphenyltetrazolium bromide (MTT) assay, SEM, quantitative real time polymerase chain reaction (qRT‐PCR), and immunofluorescence analysis demonstrated that decellularized scaffolds have the capacity to yield homogeneous distribution and alignment of BMSCs, as well as support their differentiation into tendon. Tenomodulin and Alpha‐1 collagen type I are important indicators for evaluating tenogenic differentiation of BMSCs. When decellularized “book” scaffolds with BMSCs sheets were used to repair a 1 mm Achilles tendon defect, histomorphological analysis, immunohistochemical assessment, and biomechanical testing showed that the book‐shaped decellularized tendon matrix scaffold and BMSCs sheets could promote the regeneration of type I collagen at the wound site during healing, and improve the mechanical properties of the repaired tendon. Therefore, the results of this study suggest that the novel decellularized “book” tendon scaffolds combined with BMSCs sheets have therapeutic effects on improving the healing quality of the Achilles tendon. © 2019 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 9999:1–11, 2019.