ABSTRACT
We demonstrate a nonmechanical, on-chip optical beam-steering device using a photonic-crystal waveguide with a doubly periodic structure that repeats the increase and decrease of the hole diameter. We fabricated the device using a complementary metal-oxide-semiconductor process. We obtained a beam-deflection angle of 24° in the longitudinal direction, while maintaining a divergence angle of 0.3°. Four such waveguides were integrated, and one was selected by a Mach-Zehnder optical switch. We obtained lateral beam steering by placing a cylindrical lens above these waveguides. By combining the lateral and longitudinal beam steering, we were able to scan the collimated beam in two dimensions, with 80 × 4 resolution points.
ABSTRACT
The doubly periodic Si photonic crystal waveguide radiates the guided slow light into free space as an optical beam. The waveguide also functions as a beam steering device, in which the steering angle is changed substantially by a slight variation in the wavelength generated due to the large angular dispersion of the slow light. A similar function is obtained when the wavelength is fixed and the refractive index of the waveguide is changed. In this study, we tested two kinds of integrated heater structures and observed the beam steering using the thermo-optic effect. For a p-i-p doped waveguide, the heating current was made to flow directly across the waveguide and a beam steering range of 21° was obtained with a relatively low heating power and high-speed response of the order of 100 kHz, maintaining a narrow beam divergence of 0.1-0.3° and a 120 resolution points. We also performed a preliminary life test of the device but did not observe any severe degradation in the temperature variation of 80-430 K for the duration up to 20â40 h. For a TiN heater device, we obtained the comparable beam steering characteristics, but the required heating power increased, and the response speed decreased drastically.
ABSTRACT
PURPOSE: To construct a diagnostic model for differentiating carcinosarcoma from carcinoma of the uterus. MATERIALS AND METHODS: Twenty-six patients with carcinosarcomas and 26 with uterine corpus carcinomas constituted a derivation cohort. The following nine MRI features of the tumors were evaluated: inhomogeneity, predominant signal intensity, presence of hyper- and hypointense areas, conspicuity of tumor margin, cervical canal extension on T2WI, presence of hyperintense areas on T1WI, contrast defect area volume percentage, and degree of enhancement. Two predictive models-with and without contrast-were constructed using multivariate logistic regression analysis. Fifteen other patients with carcinosarcomas and 30 patients with carcinomas constituted a validation cohort. The sensitivity and specificity of each model for the validation cohort were calculated. RESULTS: Inhomogeneity, predominant signal intensity on T2WI, and presence of hyperintense areas on T1WI were significant predictors in the unenhanced-MRI-based model. Presence of hyperintensity on T1WI, contrast defect area volume percentage, and degree of enhancement were significant predictors in the enhanced-MRI-based model. The sensitivity/specificity of unenhanced MRI were 87/73 and 87/70% according to reviewer 1 and 2, respectively. The sensitivity/specificity of the enhanced-MRI-based model were 87/70% according to both reviewers. CONCLUSIONS: Our diagnostic models can differentiate carcinosarcoma from carcinoma of the uterus with high sensitivity and moderate specificity.
Subject(s)
Carcinosarcoma/diagnostic imaging , Magnetic Resonance Imaging/methods , Uterine Neoplasms/diagnostic imaging , Aged , Aged, 80 and over , Carcinosarcoma/pathology , Contrast Media , Female , Humans , Middle Aged , Predictive Value of Tests , Retrospective Studies , Sensitivity and Specificity , Uterine Neoplasms/pathologyABSTRACT
OBJECTIVE: To assess the value of contrast-enhanced MRI, apparent diffusion coefficient (ADC) measurement, and CA-125 measurement for differentiating borderline ovarian tumors (BOTs) from stage I malignant epithelial ovarian tumors (MEOTs). MATERIAL AND METHODS: This retrospective study included 43 patients with BOTs and 43 patients with stage I MEOTs who underwent contrast-enhanced MRI with DWI and CA-125 analysis. Two radiologists evaluated the MRI findings in consensus. Univariate and multivariate analyses were performed to detect the best predictor variables for MEOTs. RESULTS: Mixed cystic/solid and predominantly solid appearances, as well as thickened irregular septa, were more frequent in MEOTs. A papillary architecture and internal branching (PA&IB) pattern was more frequent in BOTs. MEOTs had thicker walls and septa, larger solid components, and higher CA-125 values. The mean ADC value of solid components (ADCmean) and minimum ADC value of whole lesions (ADCmin) were lower in MEOTs. Multivariate analysis revealed that ADCmin and maximum diameter of the solid components were independent indicators of MEOTs with an AUC, sensitivity, and specificity of 0.86, 81%, and 84%, respectively. CONCLUSION: ADCmin and maximum diameter of solid components were useful for differentiating BOTs from MEOTs.
