Recent advancements in image-enhanced endoscopy in the pancreatobiliary field.

Image-enhanced endoscopy (IEE) has advanced gastrointestinal disease diagnosis and treatment. Traditional white-light imaging has limitations in detecting all gastrointestinal diseases, prompting the development of IEE. In this review, we explore the utility of IEE, including texture and color enhancement imaging and red dichromatic imaging, in pancreatobiliary (PB) diseases. IEE includes methods such as chromoendoscopy, optical-digital, and digital methods. Chromoendoscopy, using dyes such as indigo carmine, aids in delineating lesions and structures, including pancreato-/cholangio-jejunal anastomoses. Optical-digital methods such as narrow-band imaging enhance mucosal details and vessel patterns, aiding in ampullary tumor evaluation and peroral cholangioscopy. Moreover, red dichromatic imaging with its specific color allocation, improves the visibility of thick blood vessels in deeper tissues and enhances bleeding points with different colors and see-through effects, proving beneficial in managing bleeding complications post-endoscopic sphincterotomy. Color enhancement imaging, a novel digital method, enhances tissue texture, brightness, and color, improving visualization of PB structures, such as PB orifices, anastomotic sites, ampullary tumors, and intraductal PB lesions. Advancements in IEE hold substantial potential in improving the accuracy of PB disease diagnosis and treatment. These innovative techniques offer advantages paving the way for enhanced clinical management of PB diseases. Further research is warranted to establish their standard clinical utility and explore new frontiers in PB disease management.

Visibility of esophageal squamous cell carcinoma under iodine staining on texture and color enhancement imaging.

Objective: Iodine staining on white light imaging (WLI) is the gold standard for detecting and demarcating esophageal squamous cell carcinoma (ESCC). We examined the effects of texture and color enhancement imaging (TXI) on improving the endoscopic visibility of ESCC under iodine staining. Methods: Twenty ESCC lesions that underwent endoscopic submucosal dissection were retrospectively included. The color difference between ESCC and the surrounding mucosa (ΔEe) on WLI, TXI, and narrow-band imaging was assessed, and ΔEe under 1% iodine staining on WLI and TXI. Furthermore, the visibility grade determined by endoscopists was evaluated on each imaging. Result: The median ΔEe was greater on TXI than on WLI (14.53 vs. 10.71, respectively; p < 0.005). Moreover, the median ΔEe on TXI under iodine staining was greater than the median ΔEe on TXI and narrow-band imaging (39.20 vs. 14.53 vs. 16.42, respectively; p < 0.005 for both). A positive correlation in ΔEe under iodine staining was found between TXI and WLI (correlation coefficient = 0.61, p < 0.01). Moreover, ΔEe under iodine staining on TXI in each lesion was greater than the corresponding ΔEe on WLI. The visibility grade assessed by endoscopists on TXI was also significantly greater than that on WLI under iodine staining (p < 0.01). Conclusions: The visibility of ESCC after iodine staining was greater on TXI than on WLI.

Enhanced tissue slide imaging in the complex domain via cross-explainable GAN for Fourier ptychographic microscopy.

Achieving microscopy with large space-bandwidth products plays a key role in diagnostic imaging and is widely significant in the overall field of clinical practice. Among quantitative microscopy techniques, Fourier Ptychography (FP) provides a wide field of view and high-resolution images, suitable to the histopathological field, but onerous in computational terms. Artificial intelligence can be a solution in this sense. In particular, this research delves into the application of Generative Adversarial Networks (GAN) for the dual-channel complex FP image enhancement of human kidney samples. The study underscores the GANs' efficacy in promoting biological architectures in FP domain, thereby still guaranteeing high resolution and visibility of detailed microscopic structures. We demonstrate successful GAN-based enhanced reconstruction through two strategies: cross-explainability and expert survey. The cross-explainability is evaluated through the comparison of explanation maps for both real and imaginary components underlining its robustness. This comparison further shows that their interplay is pivotal for accurate reconstruction without hallucinations. Secondly, the enhanced reconstruction accuracy and effectiveness in a clinical workflow are confirmed through a two-step survey conducted with nephrologists.

Green Nanoengineered Fabrics: Waste-Derived Polyphenol-Zinc@ Silica Core-Shell Reactive Janus Nanoparticles for Functional Fabrics.

Fabricating Janus nanoparticle-functionalized fabrics with UV protection, strength enhancement, self-cleaning properties, and wash durability, with a biocompatible nature, is crucial in modern functional fabrics engineering. Particularly, tailoring multifunctional nanoparticles capable of exhibiting several distinct properties, utilizing low-cost raw materials, and adhering to green chemistry principles is pivotal. A fabrication strategy for developing multifunctional reactive Janus nanoparticles, utilizing waste-derived natural polyphenol (quercetin-3-glucuronide, myricetin-3-galactoside, gossypin, phlorizin, kaempferol, myricetin-3-arabinoside)-integrated zinc-silica core-shell Janus nanoparticles with UV protection, strength enhancement, and self-cleaning properties, is proposed. Polyphenols were utilized as sustainable precursors for synthesizing zinc-polyphenol complexes, which were then encapsulated within a silica shell to form a core-shell structure. Furthermore, Janus particles were created by introducing a bifunctional layer with half amine/carboxylic acid and half methyl terminals, imparting reactive hydrophilic and hydrophobic properties. Janus-coated textiles and leather exhibited significant attenuation of harmful UV radiation, with water contact angle measurements confirming improved water repellency. The coexistence of natural phenols and bifunctional groups within a material bolstered textile strength, fostering superior adhesion and markedly enhancing wash durability. This eco-friendly approach, utilizing waste-derived materials, presents a promising solution for sustainable textile engineering with enhanced performance in UV protection and water resistance, thereby contributing to the advancement of green nanotechnology in textile applications.

Enhancing Rose Bengal penetration in ex vivo human corneas using iontophoresis.

Aim: Rose Bengal photodynamic antimicrobial therapy (RB-PDAT) has poor corneal penetration, limiting its efficacy against acanthamoeba keratitis (AK). Iontophoresis enhances corneal permeation of charged molecules, piquing interest in its effects on RB in ex vivo human corneas. Methods: Five donor whole globes each underwent iontophoresis with RB, soaking in RB, or were soaked in normal saline (controls). RB penetration and corneal thickness was assessed using confocal microscopy. Results: Iontophoresis increased RB penetration compared with soaking (177 ± 9.5 µm vs. 100 ± 5.7 µm, p < 0.001), with no significant differences in corneal thickness between groups (460 ± 87 µm vs. 407 ± 69 µm, p = 0.432). Conclusion: Iontophoresis significantly improves RB penetration and its use in PDAT could offer a novel therapy for acanthamoeba keratitis. Further studies are needed to validate clinical efficacy.

The study aimed to improve a new treatment for eye infections known as photodynamic antimicrobial therapy. It investigated whether the use of electricity through a technique called iontophoresis could help a chemical called Rose Bengal go deeper into the eye in order to target more severe infections. The iontophoresis machine was custom built, with patient-contacting components 3D printed. The experiments were performed using donated human eye tissue and found that iontophoresis significantly improved the penetration depth of Rose Bengal as compared with the current technique of only soaking the eye in Rose Bengal.

An ethical assessment of powered exoskeletons: Implications from clinical use to industry and military contexts.

Exoskeletons are technologies that can help to increase or improve mobility, dexterity, and strength. They can be used as assistive devices, to restore lost affordances, or for rehabilitation. While mechanical exoskeletons are passive and rely on the body's power for movement, powered exoskeletons are active mechanical systems that can assist or enhance a user's capacity, including in strength and performance. They also offer scope to augment or enhance beyond simple medical support, with potential in the future for superhuman power and strength. While these technologies present promising clinical opportunities, including for those who want to regain walking capacity, they also bring ethical questions, such as about data privacy and accessibility. In addition, the physical features of the technology can prove mentally, physically, and financially demanding, and may be deployed in contexts where user choice and autonomy is constrained. In this article, we discuss these issues, and raise some pertinent ethical questions, not all of which can be easily answered. We touch upon medical and therapeutic uses, for industrial and workplace settings, and in military contexts specially, given these are contexts where such technology may be required or even imposed. We argue that reasonable optimism for such technologies needs to be tempered by sufficient ethical assessment to identify and address barriers to research, development, and use. As well as managing any impacts and expectations for the health and wellbeing of users, the potential impact on autonomy and the risk of coercion, we have to consider what kind of data may be recorded or used, and the risk that these technologies could exacerbate existing inequalities or harms.

Insights about cervical lymph nodes: Evaluating deep learning-based reconstruction for head and neck computed tomography scan.

Purpose: This study aimed to investigate differences in cervical lymph node image quality on dual-energy computed tomography (CT) scan with datasets reconstructed using filter back projection (FBP), hybrid iterative reconstruction (IR), and deep learning-based image reconstruction (DLIR) in patients with head and neck cancer. Method: Seventy patients with head and neck cancer underwent follow-up contrast-enhanced dual-energy CT examinations. All datasets were reconstructed using FBP, hybrid IR with 30 % adaptive statistical IR (ASiR-V), and DLIR with three selectable levels (low, medium, and high) at 2.5- and 0.625-mm slice thicknesses. Herein, signal, image noise, signal-to-noise ratio, and contrast-to-noise ratio of lymph nodes and overall image quality, artifact, and noise of selected regions of interest were evaluated by two radiologists. Next, cervical lymph node sharpness was evaluated using full width at half maximum. Results: DLIR exhibited significantly reduced noise, ranging from 3.8 % to 35.9 % with improved signal-to-noise ratio (11.5-105.6 %) and contrast-to-noise ratio (10.5-107.5 %) compared with FBP and ASiR-V, for cervical lymph nodes (p < 0.001). Further, 0.625-mm-thick images reconstructed using DLIR-medium and DLIR-high had a lower noise than 2.5-mm-thick images reconstructed using FBP and ASiR-V. The lymph node margins and vessels on DLIR-medium and DLIR-high were sharper than those on FBP and ASiR-V (p < 0.05). Both readers agreed that DLIR had a better image quality than the conventional reconstruction algorithms. Conclusion: DLIR-medium and -high provided superior cervical lymph node image quality in head and neck CT. Improved image quality affords thin-slice DLIR images for dose-reduction protocols in the future.

How to discriminate wood of CITES-listed tree species from their look-alikes: using an attention mechanism with the ResNet model on an enhanced macroscopic image dataset.

Introduction: Global illegal trade in timbers is a major cause of the loss of tree species diversity. The Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES) has been developed to combat the illegal international timber trade. Its implementation relies on accurate wood identification techniques for field screening. However, meeting the demand for timber field screening at the species level using the traditional wood identification method depending on wood anatomy is complicated, time-consuming, and challenging for enforcement officials who did not major in wood science. Methods: This study constructed a CITES-28 macroscopic image dataset, including 9,437 original images of 279 xylarium wood specimens from 14 CITES-listed commonly traded tree species and 14 look-alike species. We evaluated a suitable wood image preprocessing method and developed a highly effective computer vision classification model, SE-ResNet, on the enhanced image dataset. The model incorporated attention mechanism modules [squeeze-and-excitation networks (SENet)] into a convolutional neural network (ResNet) to identify 28 wood species. Results: The results showed that the SE-ResNet model achieved a remarkable 99.65% accuracy. Additionally, image cropping and rotation were proven effective image preprocessing methods for data enhancement. This study also conducted real-world identification using images of new specimens from the timber market to test the model and achieved 82.3% accuracy. Conclusion: This study presents a convolutional neural network model coupled with the SENet module to discriminate CITES-listed species with their look-alikes and investigates a standard guideline for enhancing wood transverse image data, providing a practical computer vision method tool to protect endangered tree species and highlighting its substantial potential for CITES implementation.

Sensory-directed flavor analysis reveals the improvement in aroma quality of summer green tea by osmanthus scenting.

Flower scenting is an effective way to enhance the aroma of green tea (GT), including those osmanthus scented green tea (OSGT). However, the mechanism of aroma enhancement by scenting is still unclear. Here, the volatiles of GT, OSGT, and osmanthus were detected by GC-MS. The total volatile content of OSGT was significantly increased compared to GT, with the flowery and coconut aromas enhanced. Furthermore, 17 of 139 volatiles were responsible for the enhancement by GC-olfactometry and their absolute odor activity values (OAVs). Aroma recombination, omission and addition experiments showed that dihydro-ß-ionone, (E)-ß-ionone, (E, E)-2,4-heptadienal, geraniol, linalool, α-ionone, and γ-decalactone were the key aroma volatiles with flowery or coconut aromas. Additionally, the dynamics of the key volatiles (OAVs >1) from different scenting durations were analyzed, proving that the optimal duration was 6-12 h. This study provides new insight into the mechanism of aroma formation during OSGT production.

Hierarchical Self-Assembly and Aggregation-Induced EmissionEnhancement in Tetrabenzofluorene-based Red Emitting Molecules.

The newly synthesized chiral active [5]helicene-like tetrabenzofluorene (TBF) based highly red-emitting molecules exhibit flower-like self-assembly. These molecules display photophysical and structural properties such as intramolecular charge transfer, dual state emission, large fluorescence  quantum yield, and solvatochromism. In TBFID, the indandione functional group attached on both sides as the terminal group offers an A-D-A push-pull effect and acts as a strong acceptor to cause more redshift in solution as well as in solid state as compared to TBFPA (TBF with benzaldehyde functional group in terminal position). The self-assembly studies of TBFID demonstrate the aggregation-induced emission enhancement (AIEE) attributed to the restriction of intramolecular rotation at the aggregated state. Furthermore, TBFID shows high quantum yield and intense red emission, making the molecule fit for organic light-emitting diodes (OLED) and bioimaging applications.

Anticipatory gaps challenge the public governance of heritable human genome editing.

Considering public moral attitudes is a hallmark of the anticipatory governance of emerging biotechnologies, such as heritable human genome editing. However, such anticipatory governance often overlooks that future morality is open to change and that future generations may perform different moral assessments on the very biotechnologies we are trying to govern in the present. In this article, we identify an 'anticipatory gap' that has not been sufficiently addressed in the discussion on the public governance of heritable genome editing, namely, uncertainty about the moral visions of future generations about the emerging applications that we are currently attempting to govern now. This paper motivates the relevance of this anticipatory gap, identifying the challenges it generates and offering various recommendations so that moral uncertainty does not lead to governance paralysis with regard to human germline genome editing.

Unpaired fundus image enhancement based on constrained generative adversarial networks.

Fundus photography (FP) is a crucial technique for diagnosing the progression of ocular and systemic diseases in clinical studies, with wide applications in early clinical screening and diagnosis. However, due to the nonuniform illumination and imbalanced intensity caused by various reasons, the quality of fundus images is often severely weakened, brings challenges for automated screening, analysis, and diagnosis of diseases. To resolve this problem, we developed strongly constrained generative adversarial networks (SCGAN). The results demonstrate that the quality of various datasets were more significantly enhanced based on SCGAN, simultaneously more effectively retaining tissue and vascular information under various experimental conditions. Furthermore, the clinical effectiveness and robustness of this model were validated by showing its improved ability in vascular segmentation as well as disease diagnosis. Our study provides a new comprehensive approach for FP and also possesses the potential capacity to advance artificial intelligence-assisted ophthalmic examination.

Cyclodextrins as a Strategy for Enhancing Solubility of Therapeutic Agents for Neglected Tropical Diseases: A Systematic Review.

BACKGROUND: Neglected Tropical Diseases (NTD) are chronic infectious conditions that primarily affect marginalized populations. The chemotherapeutic arsenal available for treating NTD is limited and outdated, which poses a challenge in controlling and eradicating these diseases. This is exacerbated by the pharmaceutical industry's lack of interest in funding the development of new therapeutic alternatives. In addition, a considerable number of drugs used in NTD therapy have low aqueous solubility. To address this issue, solubility enhancement strategies, such as the use of inclusion complexes with cyclodextrins (CD) can be employed. OBJECTIVE: Therefore, this systematic review aims to present the application of CD in complexing with drugs and chemotherapeutic compounds used in the therapy of some of the most prevalent NTD worldwide and how these complexes can enhance the treatment of these diseases. METHODS: Two bibliographic databases, Science Direct and PubMed, were used to conduct the search. The selection of studies and the writing of this systematic review followed the criteria outlined by the PRISMA guidelines. RESULTS: From a total of 978 articles, 23 were selected after applying the exclusion criteria. All the studies selected were consistent with the use of CD as a strategy to increase the solubility of therapeutic agents used in NTD. CONCLUSION: The results indicate that CD can enhance the solubility of chemotherapeutic agents for the treatment of Neglected Tropical Diseases (NTD). This review presents data that clearly highlights the potential use of CD in the development of new treatments for neglected tropical diseases. It can assist in the formulation of future treatments that are more effective and safer.

Acute effects of eccentric overload training with different loading doses in male sprinters.

Objective: The primary objective of this study was to investigate the immediate effects of two doses (Dose1 and Dose2,D1 and D2) of inertial Flywheel Eccentric Overload (FEOL), Eccentric Hook (EH), and High-intensity Half Squat (HHS) on muscle explosiveness in male sprinters. Methods: Twenty-one sub-elite male sprinters were randomly assigned to three groups: the FEOL group (n=7), the EH group (n=7), and the HSS group (n=7),Measurements of athletes' explosive jumps (CMJ, SJ, SLJ) heights, relative peak power indices, and 30-m sprint times were collected before and 6 min after the intervention. Results: At D1 loading dose, CMJ, SJ jump height, and relative peak power increased significantly (p < 0.05) after HHS training intervention, while there was no significant change in FEOL and EH training (p > 0.05). At D2 loading dose, CMJ, SJ jump height, and relative peak power increased significantly (p < 0.01) after FEOL and EH training intervention, but at D2HHS intervention, these indexes tended to decrease (p < 0.05). None of the three training protocols significantly improved SLJ performance (p > 0.05). CMJ vertical jump height and relative peak power were significantly higher after D2FEOL and D2EH interventions than after D1HHS (P < 0.05). Conclusion: D1HHS, D2FEOL and D2EH3 intervention methods can all improve the performance of sub-elite athletes in the 30-m test, CMJ test and SJ test. in the CMJ test, FEOL training demonstrated a higher acute augmentation effect compared to EH training.

Vertical root fracture diagnosis in teeth with metallic posts: Impact of metal artifact reduction and sharpening filters.

Purpose: This study examined the influence of a metal artifact reduction (MAR) tool, sharpening filters, and their combination on the diagnosis of vertical root fracture (VRF) in teeth with metallic posts using cone-beam computed tomography (CBCT). Materials and Methods: Twenty single-rooted human premolars - 9 with VRF and 11 without - were individually placed in a human mandible. A metallic post composed of a cobalt-chromium alloy was inserted into the root canal of each tooth. CBCT scans were then acquired under the following parameters: 8 mA, a 5×5 cm field of view, a voxel size of 0.085 mm, 90 kVp, and with MAR either enabled or disabled. Five oral and maxillofacial radiologists independently evaluated the CBCT exams under each MAR mode and across 3 sharpening filter conditions: no filter, Sharpen 1×, and Sharpen 2×. The diagnostic performance was quantified by the area under the receiver operating characteristic curve (AUC), sensitivity, and specificity. These metrics were compared using 2-way analysis of variance with a significance level of α=5%. Intra- and inter-examiner agreement were assessed using the weighted kappa test. Results: Neither MAR nor the application of sharpening filters significantly impacted AUC or specificity (P>0.05). However, sensitivity increased when MAR was combined with Sharpen 1× and Sharpen 2× (P=0.015). The intra-examiner agreement ranged from fair to substantial (0.34-0.66), while the inter-examiner agreement ranged from fair to moderate (0.27-0.41). Conclusion: MAR in conjunction with sharpening filters improved VRF detection; therefore, their combined use is recommended in cases of suspected VRF.

Computational single fundus image restoration techniques: a review.

Fundus cameras are widely used by ophthalmologists for monitoring and diagnosing retinal pathologies. Unfortunately, no optical system is perfect, and the visibility of retinal images can be greatly degraded due to the presence of problematic illumination, intraocular scattering, or blurriness caused by sudden movements. To improve image quality, different retinal image restoration/enhancement techniques have been developed, which play an important role in improving the performance of various clinical and computer-assisted applications. This paper gives a comprehensive review of these restoration/enhancement techniques, discusses their underlying mathematical models, and shows how they may be effectively applied in real-life practice to increase the visual quality of retinal images for potential clinical applications including diagnosis and retinal structure recognition. All three main topics of retinal image restoration/enhancement techniques, i.e., illumination correction, dehazing, and deblurring, are addressed. Finally, some considerations about challenges and the future scope of retinal image restoration/enhancement techniques will be discussed.

Progressive Neighbor-masked Contrastive Learning for Fusion-style Deep Multi-view Clustering.

Fusion-style Deep Multi-view Clustering (FDMC) can efficiently integrate comprehensive feature information from latent embeddings of multiple views and has drawn much attention recently. However, existing FDMC methods suffer from the interference of view-specific information for fusion representation, affecting the learning of discriminative cluster structure. In this paper, we propose a new framework of Progressive Neighbor-masked Contrastive Learning for FDMC (PNCL-FDMC) to tackle the aforementioned issues. Specifically, by using neighbor-masked contrastive learning, PNCL-FDMC can explicitly maintain the local structure during the embedding aggregation, which is beneficial to the common semantics enhancement on the fusion view. Based on the consistent aggregation, the fusion view is further enhanced by diversity-aware cluster structure enhancement. In this process, the enhanced cluster assignments and cluster discrepancies are employed to guide the weighted neighbor-masked contrastive alignment of semantic structure between individual views and the fusion view. Extensive experiments validate the effectiveness of the proposed framework, revealing its ability in discriminative representation learning and improving clustering performance.

Edge and Dense Attention U-Net for Atrial Scar Segmentation in LGE-MRI.

The segmentation of atrial scars in LGE-MRI images has huge potential value for clinical diagnosis and subsequent treatment. In clinical practice, atrial scars are usually manually calibrated by experienced experts, which is time-consuming and prone to errors. However, automatic segmentation also faces difficulties due to myocardial scars' small size and variable shape. The present study introduces a dual branch network, incorporating edge attention, and deep supervision strategy. Edge attention is introduced to fully utilize the spatial relationship between the scar and the atrium. Besides, dense attention is embedded in bottom layer to solve feature disappearance. At the same time, deep supervision accelerates the convergence of the model and improves segmentation accuracy. The experiments were conducted on the 2022 atrial and scar segmentation challenge dataset. The results demonstrate that the proposed method has achieved superior performance.

Diagnostic Value of Late Gadolinium Enhancement at Cardiac Magnetic Resonance to distinguish Arrhythmogenic Right Ventricular Cardiomyopathy from Differentials.

BACKGROUND: While late gadolinium enhancement (LGE) is proposed as a diagnostic criterion for arrhythmogenic right ventricular cardiomyopathy (ARVC), the potential of LGE to distinguish ARVC from differentials remains unknown. We aimed to assess the diagnostic value of LGE for ARVC diagnosis. METHODS: We included 132 subjects (60% male, 47±11 years) who had undergone cardiac magnetic resonance imaging with LGE assessment present for ARVC or ARVC-differentials. ARVC was diagnosed as per 2010 Task Force Criteria (n=55). ARVC-differentials consisted of familial/genetic dilated cardiomyopathy (n=25), myocarditis (n=13), sarcoidosis (n=20), and amyloidosis (n=19). The diagnosis of all differentials was based upon the most current golden standard. Presence of LGE was evaluated using a 7-segment RV and 17-segment LV model. Subsequently, we assessed LGE patterns for every patient individually for fulfilling LV- and/or RV-LGE per Padua criteria, independent of their clinical diagnosis (i.e. phenotype). Diagnostic values were analysed using sensitivity and specificity for any RV-LGE, any LV-LGE, RV-LGE per Padua criteria, and prevalence graphs for LV-LGE per Padua criteria. Optimal integration of LGE for ARVC diagnosis was determined using classification-and-regression-tree analysis. RESULTS: one-third (38%) of ARVC patients had RV-LGE, while half (51%) had LV-LGE. RV-LGE was less frequently observed in ARVC vs. non-ARVC patients (38% vs. 58%, p=0.034) leading to a poor discriminatory potential (any RV-LGE: sensitivity 38%, specificity 42%; RV-LGE per Padua criteria: sensitivity 36%, specificity 44%). Compared to ARVC patients, non-ARVC patients more often had LV-LGE (91% vs. 51%, p<0.001) which was also more globally distributed (median 9 [IQR: 3-13] vs. 0 [IQR: 0-3] segments, p<0.001). Absence of anteroseptal and absence of extensive (≥5 segments) mid- mid-myocardial LV-LGE, and absence of moderate (≥2 segments) mid-myocardial LV-LGE predicted ARVC with good diagnostic performance (sensitivity 93%, specificity 78%). CONCLUSIONS: LGE is often present in ARVC differentials and may lead to false positive diagnoses when used without knowledge of LGE patterns. Moderate RV-LGE without anteroseptal and mid-myocardial LV-LGE is typically observed in ARVC.

Enhancing fluid signal in driven-equilibrium short-TI inversion-recovery imaging with short TR times: A feasibility study.

PURPOSE: Fluid-sensitive turbo spin echo (TSE) MRI with short-TI inversion-recovery preparation for fat suppression (STIR) plays a critical role in the diagnostics of the musculoskeletal system (e.g., close to metal implants). Potential advantages of 3D acquisitions, however, are difficult to exploit due to long acquisition times. Shortening the TR incurs a signal loss, and a driven-equilibrium (DE) extension reduces fluid signal even further. METHODS: The phase of the flip-back pulse was changed by 180° relative to the conventional implementation (i.e., 90° along the positive x-axis (90°x) instead of -90°x). After signal modeling and numerical simulations, the modification was implemented in STIR-TSE sequences and tested on a clinical 3T system. Imaging was performed in the lumbar spine, and long-TR images without DE were acquired as reference. CSF SNR and fluid-muscle contrast were measured and compared between the sequences. Imaging was repeated in a metal implant phantom. RESULTS: A shortening of TR by 43%-57% reduced the CSF SNR by 39%-59%. A conventional DE module further reduced SNR to 26%-40%, whereas the modified DE recovered SNR to 59%-108% compared with the long-TR acquisitions. Fluid-tissue contrast was increased by about 340% with the modified DE module compared with the conventional extension. Similar results were obtained in implant measurements. CONCLUSIONS: The proposed DE element for TSE-STIR sequences has the potential to accelerate the acquisition of fluid-sensitive images. DE-STIR may work most efficiently for 3D acquisitions, in which no temporo-spatial interleaving of inversion and imaging pulses is possible.