Pretreatment Prediction of Adaptive Radiation Therapy Eligibility Using MRI-Based Radiomics for Advanced Nasopharyngeal Carcinoma Patients.

Background and purpose: Adaptive radiotherapy (ART) can compensate for the dosimetric impacts induced by anatomic and geometric variations in patients with nasopharyngeal carcinoma (NPC); Yet, the need for ART can only be assessed during the radiation treatment and the implementation of ART is resource intensive. Therefore, we aimed to determine tumoral biomarkers using pre-treatment MR images for predicting ART eligibility in NPC patients prior to the start of treatment. Methods: Seventy patients with biopsy-proven NPC (Stage II-IVB) in 2015 were enrolled into this retrospective study. Pre-treatment contrast-enhanced T1-w (CET1-w), T2-w MR images were processed and filtered using Laplacian of Gaussian (LoG) filter before radiomic features extraction. A total of 479 radiomics features, including the first-order (n = 90), shape (n = 14), and texture features (n = 375), were initially extracted from Gross-Tumor-Volume of primary tumor (GTVnp) using CET1-w, T2-w MR images. Patients were randomly divided into a training set (n = 51) and testing set (n = 19). The least absolute shrinkage and selection operator (LASSO) logistic regression model was applied for radiomic model construction in training set to select the most predictive features to predict patients who were replanned and assessed in the testing set. A double cross-validation approach of 100 resampled iterations with 3-fold nested cross-validation was employed in LASSO during model construction. The predictive performance of each model was evaluated using the area under the receiver operator characteristic (ROC) curve (AUC). Results: In the present cohort, 13 of 70 patients (18.6%) underwent ART. Average AUCs in training and testing sets were 0.962 (95%CI: 0.961-0.963) and 0.852 (95%CI: 0.847-0.857) with 8 selected features for CET1-w model; 0.895 (95%CI: 0.893-0.896) and 0.750 (95%CI: 0.745-0.755) with 6 selected features for T2-w model; and 0.984 (95%CI: 0.983-0.984) and 0.930 (95%CI: 0.928-0.933) with 6 selected features for joint T1-T2 model, respectively. In general, the joint T1-T2 model outperformed either CET1-w or T2-w model alone. Conclusions: Our study successfully showed promising capability of MRI-based radiomics features for pre-treatment identification of ART eligibility in NPC patients.

Melding Vapor-Phase Organic Chemistry and Textile Manufacturing To Produce Wearable Electronics.

Body-mountable electronics and electronically active garments are the future of portable, interactive devices. However, wearable devices and electronic garments are demanding technology platforms because of the large, varied mechanical stresses to which they are routinely subjected, which can easily abrade or damage microelectronic components and electronic interconnects. Furthermore, aesthetics and tactile perception (or feel) can make or break a nascent wearable technology, irrespective of device metrics. The breathability and comfort of commercial fabrics is unmatched. There is strong motivation to use something that is already familiar, such as cotton/silk thread, fabrics, and clothes, and imperceptibly adapt it to a new technological application. (24) Especially for smart garments, the intrinsic breathability, comfort, and feel of familiar fabrics cannot be replicated by devices built on metalized synthetic fabrics or cladded, often-heavy designer fibers. We propose that the strongest strategy to create long-lasting and impactful electronic garments is to start with a mass-produced article of clothing, fabric, or thread/yarn and coat it with conjugated polymers to yield various textile circuit components. Commonly available, mass-produced fabrics, yarns/threads, and premade garments can in theory be transformed into a plethora of comfortably wearable electronic devices upon being coated with films of electronically active conjugated polymers. The definitive hurdle is that premade garments, threads, and fabrics have densely textured, three-dimensional surfaces that display roughness over a large range of length scales, from microns to millimeters. Tremendous variation in the surface morphology of conjugated-polymer-coated fibers and fabrics can be observed with different coating or processing conditions. In turn, the morphology of the conjugated polymer active layer determines the electrical performance and, most importantly, the device ruggedness and lifetime. Reactive vapor coating methods allow a conjugated polymer film to be directly formed on the surface of any premade garment, prewoven fabric, or fiber/yarn substrate without the need for specialized processing conditions, surface pretreatments, detergents, or fixing agents. This feature allows electronic coatings to be applied at the end of existing, high-throughput textile and garment manufacturing routines, irrespective of dye content or surface finish of the final textile. Furthermore, reactive vapor coating produces conductive materials without any insulating moieties and yields uniform and conformal films on fiber/fabric surfaces that are notably wash- and wear-stable and can withstand mechanically demanding textile manufacturing routines. These unique features mean that rugged and practical textile electronic devices can be created using sewing, weaving, or knitting procedures without compromising or otherwise affecting the surface electronic coating. In this Account, we highlight selected electronic fabrics and garments created by melding reactive vapor deposition with traditional textile manipulation processes, including electrically heated gloves that are lightweight, breathable, and sweat-resistant; surface-coated cotton, silk, and bast fiber threads capable of carrying large current densities and acting as sewable circuit interconnects; and surface-coated nylon threads woven together to form triboelectric textiles that can convert surface charge created during small body movements into usable and storable power.

Reactive Vapor Deposition of Conjugated Polymer Films on Arbitrary Substrates.

We demonstrate a method of conformally coating conjugated polymers on arbitrary substrates using a custom-designed, low-pressure reaction chamber. Conductive polymers, poly(3,4-ethylenedioxythiophene) (PEDOT) and poly(3,4-propylenedioxythiophene) (PProDOT), and a semiconducting polymer, poly(thieno[3,2-b]thiophene) (PTT), were deposited on unconventional highly-disordered and textured substrates with high surface areas, such as paper, towels and fabrics. This reported deposition chamber is an improvement of previous vapor reactors because our system can accommodate both volatile and nonvolatile monomers, such as 3,4-propylenedioxythiophene and thieno[3,2-b]thiophene. Utilization of both solid and liquid oxidants are also demonstrated. One limitation of this method is that it lacks sophisticated in situ thickness monitors. Polymer coatings made by the commonly used solution-based coating methods, such as spin-coating and surface grafting, are often not uniform or susceptible to mechanical degradation. This reported vapor phase deposition method overcomes those drawbacks and is a strong alternative to common solution-based coating methods. Notably, polymer films coated by the reported method are uniform and conformal on rough surfaces, even at a micrometer scale. This feature allows for future application of vapor deposited polymers in electronics devices on flexible and highly textured substrates.

Design of a Photoactive Hybrid Bilayer Dielectric for Flexible Nonvolatile Organic Memory Transistors.

Organic field-effect transistors (OFETs) featuring a photoactive hybrid bilayer dielectric (PHBD) that comprises a self-assembled monolayer (SAM) of photochromic diarylethenes (DAEs) and an ultrathin solution-processed hafnium oxide layer are described here. We photoengineer the energy levels of DAE SAMs to facilitate the charging and discharging of the interface of the two dielectrics, thus yielding an OFET that functions as a nonvolatile memory device. The transistors use light signals for programming and electrical signals for erasing (≤3 V) to produce a large, reversible threshold-voltage shift with long retention times and good nondestructive signal processing ability. The memory effect can be exercised by more than 10(4) memory cycles. Furthermore, these memory cells have demonstrated the capacity to be arrayed into a photosensor matrix on flexible plastic substrates to detect the spatial distribution of a confined light and then store the analog sensor input as a two-dimensional image with high precision over a long period of time.

Solution-processable, low-voltage, and high-performance monolayer field-effect transistors with aqueous stability and high sensitivity.

Low-voltage, low-cost, high-performance monolayer field-effect transistors are demonstrated, which comprise a densely packed, long-range ordered monolayer spin-coated from core-cladding liquid-crystalline pentathiophenes and a solution-processed high-k HfO2 -based nanoscale gate dielectric. These monolayer field-effect transistors are light-sensitive and are able to function as reporters to convert analyte binding events into electrical signals with ultrahigh sensitivity (≈10 ppb).

Point decoration of silicon nanowires: an approach toward single-molecule electrical detection.

Probing interactions of biological systems at the molecular level is of great importance to fundamental biology, diagnosis, and drug discovery. A rational bioassay design of lithographically integrating individual point scattering sites into electrical circuits is capable of realizing real-time, label-free biodetection of influenza H1N1 viruses with single-molecule sensitivity and high selectivity by using silicon nanowires as local reporters in combination with microfluidics. This nanocircuit-based architecture is complementary to more conventional optical techniques, but has the advantages of no bleaching problems and no fluorescent labeling. These advantages offer a promising platform for exploring dynamics of stochastic processes in biological systems and gaining information from genomics to proteomics to improve accurate molecular and even point-of-care clinical diagnosis.