5 research outputs found

    CT-based radiomics for predicting radio-chemotherapy response and overall survival in nonsurgical esophageal carcinoma

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    BackgroundTo predict treatment response and 2 years overall survival (OS) of radio-chemotherapy in patients with esophageal cancer (EC) by radiomics based on the computed tomography (CT) images.MethodsThis study retrospectively collected 171 nonsurgical EC patients treated with radio-chemotherapy from Jan 2010 to Jan 2019. 80 patients were randomly divided into training (n=64) and validation (n=16) cohorts to predict the radiochemotherapy response. The models predicting treatment response were established by Lasso and logistic regression. A total of 156 patients were allocated into the training cohort (n=110), validation cohort (n=23) and test set (n=23) to predict 2-year OS. The Lasso Cox model and Cox proportional hazards model established the models predicting 2-year OS.ResultsTo predict the radiochemotherapy response, WFK as a radiomics feature, and clinical stages and clinical M stages (cM) as clinical features were selected to construct the clinical-radiomics model, achieving 0.78 and 0.75 AUC (area under the curve) in the training and validation sets, respectively. Furthermore, radiomics features called WFI and WGI combined with clinical features (smoking index, pathological types, cM) were the optimal predictors to predict 2-year OS. The AUC values of the clinical-radiomics model were 0.71 and 0.70 in the training set and validation set, respectively.ConclusionsThis study demonstrated that planning CT-based radiomics showed the predictability of the radiochemotherapy response and 2-year OS in nonsurgical esophageal carcinoma. The predictive results prior to treatment have the potential to assist physicians in choosing the optimal therapeutic strategy to prolong overall survival

    Dynamic large-array terahertz imaging display based on high-performance 1D/2D tellurium homojunction modulators

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    Mixed-dimensional van der Waals systems could improve terahertz modulators’ performance by utilizing the advantages of different dimensional materials. However, the reported available mixed-dimensional heterojunctions using two-dimensional (2D) and three-dimensional materials usually sacrifice the modulation speed to realize a higher modulation depth. Here, we creatively integrate one-dimensional (1D) nanowires with 2D nanofilms to construct the novel mixed-dimensional tellurium (Te) homojunction and achieve optimal indices with an ultrahigh modulation depth and a shorter carrier lifetime. In addition, a Te-based large-array imaging element was fabricated to successfully reproduce the painting colors under specific pump conditions as well as the dynamic multicolor display. Further measurements with the introduction of metamaterials prove that the required energy consumption can be significantly reduced by one order of magnitude. Our proposed 1D/2D integration strategy opens a new way to build high-performance terahertz functional devices and greatly expands the application fields of Te nanomaterials
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