Citations

Background: The CACNA1C -encoded cardiac L-type calcium channel (Cav1.2) is essential for cardiocyte action potential duration (APD). We previously reported the CACNA1C-p.R518C variant associated with prolonged QT intervals, cardiomyopathy, and sudden cardiac death in several pedigrees. Methods: To characterize a patient-derived human induced pluripotent stem cell–derived cardiomyocyte (hiPSC-CM) CACNA1C-p.R518C model, CACNA1C-p.R518C hiPSC-CMs were generated from a 13-year-old man (QTc, >480 ms) with a family history of sudden cardiac death. An isogenic hiPSC-CM gene-corrected control was created using CRISPR/Cas9 (clustered regularly interspaced short palindromic repeats/clustered regularly interspaced short palindromic repeat–associated 9). APD and calcium handling were assessed by live cell imaging with Arclight voltage and Fluo-4 calcium indicators, respectively. The APD and L-type calcium channel biophysical properties were further assessed by whole-cell patch clamp technique. Results: The Bazett formula-corrected, Arclight-measured APD 90 of CACNA1C-p.R518C hiPSC-CMs was significantly longer (622±11 ms; n=92) than the isogenic control hiPSC-CMs (453±5 ms; n=62; P <0.0001). Patch clamp assessment of CACNA1C-p.R518C hiPSC-CMs paced at 1 Hz confirmed a prolonged APD 90 (689±29 ms; n=10) compared with the patient’s isogenic control hiPSC-CMs (434±30 ms; n=8; P <0.05). Fluo-4–measured calcium transient decay time suggested calcium mishandling in CACNA1C-p.R518C. Patch clamp analysis revealed increased L-type calcium channel window current, slow decay time at various voltages, and increased late calcium current for CACNA1C-p.R518C hiPSC-CMs when compared with isogenic control hiPSC-CMs. Conclusions: Using patient-specific hiPSC-CM mutant and isogenic control lines, we demonstrate that the CACNA1C-p.R518C variant is the self-sufficient, monogenetic substrate for the patient’s long-QT syndrome phenotype. These data further bolster the conclusion that CACNA1C is a bona fide, definite evidence long-QT syndrome susceptibility gene.

Owing to the increasing worldwide burden of liver diseases, the crucial need for safe and effective interventions for treating end-stage liver failure has been a very productive line of inquiry in the discipline of hepatology for many years. Liver transplantation is recognized as the most effective treatment for end-stage liver disease; however, the shortage of donor organs, high medical costs, and lifelong use of immunosuppressive agents represent major drawbacks and demand exploration for alternative treatments. Stem cell-based therapies have been widely studied in the field of liver diseases and are considered to be among the most promising therapies. Herein, we review recent advances in the application of stem cell-related therapies in liver disease with the aim of providing readers with relevant knowledge in this field and inspiration to spur further inquiry.

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.

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.

Objectives The aim of this study was to investigate the impact on metal artifacts and dose efficiency of using a tin filter in combination with high-energy threshold (TH) images of a photon-counting detector (PCD) computed tomography (CT) system. Materials and Methods A 3D-printed spine with pedicle screws was scanned on a PCD-CT system with and without tin filtration. Image noise and severity of artifacts were measured for low-energy threshold (TL) and TH images. In a prospective, institutional review board–approved, Health Insurance Portability and Accountability Act-compliant study, 20 patients having a clinical energy-integrating detector (EID) CT were scanned on a PCD-CT system using tin filtration. Images were reviewed by 3 radiologists to evaluate visualization of anatomic structures, diagnostic confidence, and image preference. Artifact severity and image noise were measured. Wilcoxon signed rank was used to test differences between PCD-CT TH and EID-CT images. Results Phantom TH images with tin filtration reduced metal artifacts and had comparable noise (32 HU) to TL images (29 HU) acquired without tin filtration. Visualization scores for the cortex, trabeculae, and implant-trabecular interface from PCD-CT TH images (4.4 ± 0.9, 4.4 ± 1.0, and 4.4 ± 1.0) were significantly higher (P < 0.0001) than EID-CT images (3.3 ± 1.3, 3.3 ± 1.2, and 3.3 ± 1.6). A strong preference was shown for PCD-CT TH images due to improved diagnostic confidence and decreased artifact severity. Noise in PCD-CT TH images (93 ± 41 HU) was significantly lower than that in EID-CT images (133 ± 92 HU, P < 0.05). Conclusions Threshold high images acquired with tin filtration on PCD-CT demonstrated a substantial decrease in metal artifacts and an increase in dose efficiency compared with EID-CT.

Objective The aims of this study were to quantitatively assess two new scan modes on a photon-counting detector computed tomography system, each designed to maximize spatial resolution, and to qualitatively demonstrate potential clinical impact using patient data. Materials and Methods This Health Insurance Portability Act–compliant study was approved by our institutional review board. Two high–spatial-resolution scan modes (Sharp and UHR) were evaluated using phantoms to quantify spatial resolution and image noise, and results were compared with the standard mode (Macro). Patients were scanned using a conventional energy-integrating detector scanner and the photon-counting detector scanner using the same radiation dose. In first patient images, anatomic details were qualitatively evaluated to demonstrate potential clinical impact. Results Sharp and UHR modes had a 69% and 87% improvement in in-plane spatial resolution, respectively, compared with Macro mode (10% modulation-translation-function values of 16.05, 17.69, and 9.48 lp/cm, respectively). The cutoff spatial frequency of the UHR mode (32.4 lp/cm) corresponded to a limiting spatial resolution of 150 μm. The full-width-at-half-maximum values of the section sensitivity profiles were 0.41, 0.44, and 0.67 mm for the thinnest image thickness for each mode (0.25, 0.25, and 0.5 mm, respectively). At the same in-plane spatial resolution, Sharp and UHR images had up to 15% lower noise than Macro images. Patient images acquired in Sharp mode demonstrated better delineation of fine anatomic structures compared with Macro mode images. Conclusions Phantom studies demonstrated superior resolution and noise properties for the Sharp and UHR modes relative to the standard Macro mode and patient images demonstrated the potential benefit of these scan modes for clinical practice.

Objectives The ability to determine the severity of renal fibrosis, which is involved in most chronic kidney diseases, may be beneficial for monitoring disease progression and management. The aim of this study was to assess a new method involving gold nanoparticles conjugated to an anti-collagen-I antibody (Co-I-AuNPs) as a computed tomography (CT) imaging contrast for the evaluation of renal fibrosis in situ. Materials and Methods Gold nanoparticles conjugated to an anti-collagen-I antibody were prepared using gold chloride reduction with sodium citrate and coated with polyethylene glycol (PEG), and their size was determined by electron microscopy and nanoparticle tracking analysis. Anti-collagen-I antibody was then conjugated to PEG-SH/COOH on the AuNP surface. The success of antibody conjugation was tested in vitro using collagen-coated plate and mouse stenotic kidney sections and in vivo using micro-CT and multidetector CT imaging. Results Bare AuNPs were 18.7 ± 0.6 nm and PEG-coated AuNPs were 45.3 ± 0.1 nm in size. In vitro, Co-I-AuNPs specifically bound to both a collagen-coated plate and mouse fibrotic kidneys. Furthermore, the stenotic mouse kidney showed increased Co-I-AuNPs retention compared with the contralateral kidney (59.3 ± 5.1 vs 45.1 ± 1.7 HU, P = 0.05), which correlated with its collagen deposition. Micro-CT also detected gold signals in situ in the Co-I-AuNP-injected kidney, which colocalized with histological trichrome staining. Conclusion Gold nanoparticles conjugated to an anti-collagen-I antibody are able to visualize kidney fibrosis in vitro and in situ and may be useful for nondestructive quantification of tissue fibrosis.

Abstract Photon-counting computed tomography (PCCT) uses a photon counting detector to count individual photons and allocate them to specific energy bins by comparing photon energy to preset thresholds. This enables simultaneous multi-energy CT with a single source and detector. Phantom studies were performed to assess the spectral performance of a research PCCT scanner by assessing the accuracy of derived images sets. Specifically, we assessed the accuracy of iodine quantification in iodine map images and of CT number accuracy in virtual monoenergetic images (VMI). Vials containing iodine with five known concentrations were scanned on the PCCT scanner after being placed in phantoms representing the attenuation of different size patients. For comparison, the same vials and phantoms were also scanned on 2nd and 3rd generation dual-source, dual-energy scanners. After material decomposition, iodine maps were generated, from which iodine concentration was measured for each vial and phantom size and compared with the known concentration. Additionally, VMIs were generated and CT number accuracy was compared to the reference standard, which was calculated based on known iodine concentration and attenuation coefficients at each keV obtained from the U.S. National Institute of Standards and Technology (NIST). Results showed accurate iodine quantification (root mean square error of 0.5 mgI/cc) and accurate CT number of VMIs (percentage error of 8.9%) using the PCCT scanner. The overall performance of the PCCT scanner, in terms of iodine quantification and VMI CT number accuracy, was comparable to that of EID-based dual-source, dual-energy scanners.