Multimodal Imaging Approach for Tumor Treatment Response Evaluation in the Era of Immunotherapy.

ABSTRACT: Immunotherapy is likely the most remarkable advancement in lung cancer treatment during the past decade. Although immunotherapy provides substantial benefits, their therapeutic responses differ from those of conventional chemotherapy and targeted therapy, and some patients present unique immunotherapy response patterns that cannot be judged under the current measurement standards. Therefore, the response monitoring of immunotherapy can be challenging, such as the differentiation between real response and pseudo-response. This review outlines the various tumor response patterns to immunotherapy and discusses methods for quantifying computed tomography (CT) and 18F-fluorodeoxyglucose positron emission tomography (PET) in the field of lung cancer. Emerging technologies in magnetic resonance imaging (MRI) and non-FDG PET tracers are also explored. With immunotherapy responses, the role for imaging is essential in both anatomical radiological responses (CT/MRI) and molecular changes (PET imaging). Multiple aspects must be considered when assessing treatment responses using CT and PET. Finally, we introduce multimodal approaches that integrate imaging and nonimaging data, and we discuss future directions for the assessment and prediction of lung cancer responses to immunotherapy.

Taste Bud-Inspired Single-Drop Multitaste Sensing for Comprehensive Flavor Analysis with Deep Learning Algorithms.

The electronic tongue (E-tongue) system has emerged as a significant innovation, aiming to replicate the complexity of human taste perception. In spite of the advancements in E-tongue technologies, two primary challenges remain to be addressed. First, evaluating the actual taste is complex due to interactions between taste and substances, such as synergistic and suppressive effects. Second, ensuring reliable outcomes in dynamic conditions, particularly when faced with high deviation error data, presents a significant challenge. The present study introduces a bioinspired artificial E-tongue system that mimics the gustatory system by integrating multiple arrays of taste sensors to emulate taste buds in the human tongue and incorporating a customized deep-learning algorithm for taste interpretation. The developed E-tongue system is capable of detecting four distinct tastes in a single drop of dietary compounds, such as saltiness, sourness, astringency, and sweetness, demonstrating notable reversibility and selectivity. The taste profiles of six different wines are obtained by the E-tongue system and demonstrated similarities in taste trends between the E-tongue system and user reviews from online, although some disparities still exist. To mitigate these disparities, a prototype-based classifier with soft voting is devised and implemented for the artificial E-tongue system. The artificial E-tongue system achieved a high classification accuracy of ∼95% in distinguishing among six different wines and ∼90% accuracy even in an environment where more than 1/3 of the data contained errors. Moreover, by harnessing the capabilities of deep learning technology, a recommendation system was demonstrated to enhance the user experience.

Nondiagnostic, radial-probe endobronchial ultrasound-guided biopsy for peripheral lung lesions: The added value of radiomics from ultrasound imaging for predicting malignancy.

OBJECTIVES: This study investigated whether radiomic features extracted from radial-probe endobronchial ultrasound (radial EBUS) images can assist in decision-making for subsequent clinical management in cases with indeterminate pathologic results. METHODS: A total of 494 patients who underwent radial EBUS biopsy for lung nodules between January 2017 and December 2018 were allocated to our training set. For the validation set, 229 patients with radial EBUS biopsy results from January 2019 to April 2020 were used. A multivariate logistic regression analysis was used for feature selection and prediction modeling. RESULTS: In the training set, 157 (67 benign and 90 malignant) of 212 patients pathologically diagnosed as indeterminate were analyzed. In the validation set, 213 patients were diagnosed as indeterminate, and 158 patients (63 benign and 95 malignant) were included in the analysis. The performance of the radiomics-added model, which considered satellite nodules, linear arc, shape, patency of vessels and bronchi, echogenicity, spiculation, C-reactive protein, and minimum histogram, was 0.929 for the training set and 0.877 for the validation set, whereas the performance of the model without radiomics was 0.910 and 0.891, respectively. CONCLUSION: Although the next diagnostic step for indeterminate lung biopsy results remains controversial, integrating various factors, including radiomic features from radial EBUS, might facilitate decision-making for subsequent clinical management.

Surface Self-Assembly, Film Morphology, and Charge Transport Properties of Semiconducting Triazoloarenes.

Surface-assisted molecular self-assembly is a powerful strategy for forming molecular-scale architectures on surfaces. These molecular self-assemblies have potential applications in organic electronics, catalysis, photovoltaics, and many other technologies. Understanding the intermolecular interactions on a surface can help predict packing, stacking, and charge transport properties of films and allow for new molecular designs to be tailored for a required function. We have previously studied a molecular platform, tris( N-phenyltriazole) (TPT), that exhibits planar stacking through >20 molecular layers through donor-acceptor-type intermolecular π-π contacts between the electron-deficient tris(triazole) core and electron-rich peripheral phenyl units. Here, we investigate an expanded family of TPT-based molecules with variations made on the peripheral aryl groups to modulate the molecular electron distribution and examine the impact on molecular packing and charge transport properties. Molecular-resolution scanning tunneling microscopy was used to compare the molecular packing in the monolayer and to investigate the effects that the structural and electronic modifications have on the stacking in subsequent layers. Conductivity measurements were made using the four-point probe van der Pauw technique to demonstrate charge transport properties comparable to pentacene. Although molecular packing is clearly impacted by the chemical structure, we find that the charge transport efficiency is quite tolerant to small structural variations.

Mechanical Analysis of Ceramic/Polymer Composite with Mesh-Type Lightweight Design Using Binder-Jet 3D Printing.

3D printing technology has recently been highlighted as an innovative manufacturing process. Among various 3D printing methods, binder jetting (BJ) 3D printing is particularly known as technology used to produce the complex sand mold quickly for a casting process. However, high manufacturing costs, due to its expensive materials, need to be lowered for more industrial applications of 3D printing. In this study, we investigated mechanical properties of sand molds with a lightweight structure for low material consumption and short process time. Our stress analysis using a computational approach, revealed a structural weak point in the mesh-type lightweight design applied to the 3D-printed ceramic/polymer composite.