C-Arm Computed Tomographic Image Fusion for Repetitive Transarterial Chemoembolization of Hepatocellular Carcinoma.

OBJECTIVE: The aim of this study was to evaluate the potential implications of fusion imaging with C-arm computed tomography (CACT) scans for repetitive conventional transarterial chemoembolization (cTACE) for hepatocellular carcinoma. MATERIALS AND METHODS: Fifty-six cTACE sessions were performed using fusion CACT images from September 2020 to June 2021 in a tertiary referral center, and the data were retrospectively analyzed. Fusion of unenhanced and enhanced CACT images was considered when previously accumulated iodized oil hampered the identification of local tumor progression or intrahepatic distant metastasis (indication A), when a tumor was supplied by multiple arteries with different origins from the aorta and missing tumor enhancement was suspected (indication B), or when iodized oil distribution on immediate post-cTACE CACT images needed to be precisely compared with the pre-cTACE images (indication C). Fusion image quality, initial tumor response, time to local progression (TTLP) of index tumors, and time to progression (TTP) were evaluated. RESULTS: The fusion quality was satisfactory with a mean misregistration distance of 1.4 mm. For the 40 patients with indication A, the initial tumor responses at 3 months were nonviable, equivocal, and viable in 27 (67.5%), 4 (10.0%), and 9 (22.5%) index tumors, respectively. The median TTLP and TTP were 14.8 months and 4.5 months, respectively. For 10 patients with indication B, the median TTLP and TTP were 8.3 months and 2.6 months, respectively. Among the 6 patients with indication C, 2 patients were additionally treated at the same cTACE session after confirming incomplete iodized oil uptake on fusion imaging. CONCLUSIONS: Fusion CACT images are useful in patients with hepatocellular carcinoma undergoing repetitive cTACE.

Elucidating Charge Carrier Dynamics in Perovskite-Based Tandem Solar Cells.

Recently, multijunction tandem solar cells (TSCs) have presented high power conversion efficiency and revealed their immense potential in photovoltaic evolution. It is demonstrated that multiple light absorbers with various bandgap energies overcome the Shockley-Queisser limit of single-junction solar cells by absorbing the wide-range wavelength photons. Here, the main key challenges are reviewed, especially the charge carrier dynamics in perovskite-based 2-terminal (2-T) TSCs in terms of current matching, and how to manage these issues from a vantage point of characterization. To do this, the effect of recombination layers, optical and fabrication hurdles, and the impact of wide bandgap perovskite solar cells are discussed extensively. Afterward, this review focuses on various optoelectronics, spectroscopic, and theoretical (optical simulation) characterizations to figure out those issues, especially current-matching issues faced by the photovoltaic society. This review comprehensively provides deep insights into the relationship between the current-matching problems and the photovoltaic performance of TSCs through a variety of perspectives. Consequently, it is believed that this review is essential to address the main problems of 2-T TSCs, and the suggestions to elucidate the charge carrier dynamics and its characterization may pave the way to overcome such obstacles to further improve the development of 2-T TSCs in relation to the current-matching problems.

Mammographic density changes after neoadjuvant chemotherapy in triple-negative breast cancer: Association with treatment and survival outcome.

PURPOSE: To investigate the association of mammographic breast density with treatment and survival outcomes in patients with triple-negative breast cancer (TNBC) undergoing neoadjuvant chemotherapy (NAC). METHODS: This retrospective study evaluated 306 women with TNBC who underwent NAC followed by surgery between 2010 and 2019. The baseline density and the density changes after NAC were evaluated. Qualitative breast density (a-d) was evaluated using the Breast Imaging Reporting and Data System. Quantitative breast density (%) was evaluated using fully automated software (the Laboratory for Individualized Breast Radiodensity Assessment) in the contralateral breast. Multivariable logistic regression analysis was used to evaluate the association between breast density and pathologic complete response (pCR), stratified by menopausal status. Cox proportional hazard regression analysis was used to evaluate the association among breast density, the development of contralateral breast cancer, and the development of locoregional recurrence and/or distant metastasis. RESULTS: Contralateral density reduction ≥10 % was independently associated with pCR in premenopausal women (odds ratio [OR], 2.5; p = 0.022) but not in postmenopausal women (OR, 0.9; p = 0.823). During a mean follow-up of 65 months, 10 (3 %) women developed contralateral breast cancer, and 68 (22 %) women developed locoregional recurrences and/or distant metastases. Contralateral density reduction ≥10 % showed no association with the occurrence of contralateral breast cancer (hazard ratio [HR], 3.1; p = 0.308) or with locoregional recurrence and/or distant metastasis (HR, 1.1; p = 0.794). CONCLUSION: In premenopausal women, a contralateral breast density reduction of ≥10 % after NAC was independently associated with pCR, although it did not translate into improved outcomes.

Methods of Visualizing the Results of an Artificial-Intelligence-Based Computer-Aided Detection System for Chest Radiographs: Effect on the Diagnostic Performance of Radiologists.

It is unclear whether the visualization methods for artificial-intelligence-based computer-aided detection (AI-CAD) of chest radiographs influence the accuracy of readers' interpretation. We aimed to evaluate the accuracy of radiologists' interpretations of chest radiographs using different visualization methods for the same AI-CAD. Initial chest radiographs of patients with acute respiratory symptoms were retrospectively collected. A commercialized AI-CAD using three different methods of visualizing was applied: (a) closed-line method, (b) heat map method, and (c) combined method. A reader test was conducted with five trainee radiologists over three interpretation sessions. In each session, the chest radiographs were interpreted using AI-CAD with one of the three visualization methods in random order. Examination-level sensitivity and accuracy, and lesion-level detection rates for clinically significant abnormalities were evaluated for the three visualization methods. The sensitivity (p = 0.007) and accuracy (p = 0.037) of the combined method are significantly higher than that of the closed-line method. Detection rates using the heat map method (p = 0.043) and the combined method (p = 0.004) are significantly higher than those using the closed-line method. The methods for visualizing AI-CAD results for chest radiographs influenced the performance of radiologists' interpretations. Combining the closed-line and heat map methods for visualizing AI-CAD results led to the highest sensitivity and accuracy of radiologists.

Emissions of Fungal Volatile Organic Compounds in Residential Environments and Temporal Emission Patterns: Implications for Sampling Methods.

Currently, little is known about the occurrences of fungi-derived microbial volatile organic compounds (mVOCs) in various indoor materials and their detection in residential environments, despite mVOCs being linked to several acute health effects. We identified various mVOCs emitted from fungi grown on PVC wallpaper, silicone rubber, and malt extract agar. We also investigated mVOCs temporal emission and whether fungi-derived VOCs concentration can be used to estimate fungal concentration in the air using active and passive air sampling methods. Among the three fungal growth media included in this study, silicone rubber produced the most variety of mVOCs: 106 compounds (from Aspergillus niger), 35 compounds (from Alternaria alternata), and 85 compounds (from Penicillium chrysogenum). We also found the emission patterns of eight chemical classes (i.e., aromatics, ethers, aliphatics, alcohols, ketones, aldehydes, chlorides, and nitrides) from the three different fungi. From the results of our field experiments in 11 residential environments, passive air samplers led to higher correlations coefficients (0.08 to 0.86) between mVOCs' air concentrations and airborne fungal concentrations, compared with active air samplers, which showed negative correlation coefficients (-0.99 to -0.02) for most compounds. This study elucidated the occurrence and temporal emission patterns of fungal VOCs in residential environments.

High-Performance Perovskite Quantum Dot Solar Cells Enabled by Incorporation with Dimensionally Engineered Organic Semiconductor.

Perovskite quantum dots (PQDs) have been considered promising and effective photovoltaic absorber due to their superior optoelectronic properties and inherent material merits combining perovskites and QDs. However, they exhibit low moisture stability at room humidity (20-30%) owing to many surface defect sites generated by inefficient ligand exchange process. These surface traps must be re-passivated to improve both charge transport ability and moisture stability. To address this issue, PQD-organic semiconductor hybrid solar cells with suitable electrical properties and functional groups might dramatically improve the charge extraction and defect passivation. Conventional organic semiconductors are typically low-dimensional (1D and 2D) and prone to excessive self-aggregation, which limits chemical interaction with PQDs. In this work, we designed a new 3D star-shaped semiconducting material (Star-TrCN) to enhance the compatibility with PQDs. The robust bonding with Star-TrCN and PQDs is demonstrated by theoretical modeling and experimental validation. The Star-TrCN-PQD hybrid films show improved cubic-phase stability of CsPbI3-PQDs via reduced surface trap states and suppressed moisture penetration. As a result, the resultant devices not only achieve remarkable device stability over 1000 h at 20-30% relative humidity, but also boost power conversion efficiency up to 16.0% via forming a cascade energy band structure.

Roles and Impacts of Ancillary Materials for Multi-Component Blend Organic Photovoltaics towards High Efficiency and Stability.

Organic photovoltaics (OPVs) are a promising next-generation photovoltaic technology with great potential for wearable and transparent device applications. Over the past decades, remarkable advances in device efficiency close to 20 % have been made for bulk heterojunction (BHJ)-based OPV devices with long-term stability, and room for further improvements still exists. In recent years, ancillary components have been demonstrated as effective in improving the photovoltaic performance of OPVs by controlling the optoelectronic and morphological properties of BHJ blends. Herein, an updated understanding of polymer-based blend OPVs is provided, and the role and impact of ancillary components in various blend systems are categorized and discussed. Lastly, a strategic perspective on the ancillary components of blend-based OPVs for commercialization is provided.