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Objectives: To evaluate the diagnostic value of histogram analysis using grayscale sonograms for differentiation of malignant and benign thyroid nodules., Methods: From July 2013 through October 2013, 579 nodules in 563 patients who had undergone ultrasound-guided fine-needle aspiration were included. For the grayscale histogram analysis, pixel echogenicity values in regions of interest were measured as 0 to 255 (0, black; 255, white) with in-house software. Five parameters (mean, skewness, kurtosis, standard deviation, and entropy) were obtained for each thyroid nodule. With principal component analysis, an index was derived. Diagnostic performance rates for the 5 histogram parameters and the principal component analysis index were calculated., Results: A total of 563 patients were included in the study (mean age ± SD, 50.3 ± 12.3 years;range, 15-79 years). Of the 579 nodules, 431 were benign, and 148 were malignant. Among the 5 parameters and the principal component analysis index, the standard deviation (75.546 ± 14.153 versus 62.761 ± 16.01; P < .001), kurtosis (3.898 ± 2.652 versus 6.251 ± 9.102; P < .001), entropy (0.16 ± 0.135 versus 0.239 ± 0.185; P < .001), and principal component analysis index (-0.386±0.774 versus 0.134 ± 0.889; P < .001) were significantly different between the malignant and benign nodules. With the calculated cutoff values, the areas under the curve were 0.681 (95% confidence interval, 0.643-0.721) for standard deviation, 0.661 (0.620-0.703) for principal component analysis index, 0.651 (0.607-0.691) for kurtosis, 0.638 (0.596-0.681) for entropy, and 0.606 (0.563-0.647) for skewness. The subjective analysis of grayscale sonograms by radiologists alone showed an area under the curve of 0.861 (0.833-0.888)., Conclusions: Grayscale histogram analysis was feasible for differentiating malignant and benign thyroid nodules but did not show better diagnostic performance than subjective analysis performed by radiologists. Further technical advances will be needed to objectify interpretations of thyroid grayscale sonograms., (© 2016 by the American Institute of Ultrasound in Medicine.)

Objectives: The purpose of this study was to evaluate diagnostic performance of histogram analysis using grayscale ultrasound (US) images in the diagnosis of lymphocytic thyroiditis., Methods: Three radiologists reviewed a total of 505 US images and classified the images according to the presence/existence of lymphocytic thyroiditis. After 2 months, each reviewer repeated the process with the same 505 images in a randomly mixed order. The intraobserver and interobserver variability was analyzed with a generalized κ value. Four histogram parameters (mean value, standard deviation, skewness, and kurtosis) were obtained, and an index was calculated from principal component analysis. Diagnostic performances were compared., Results: Of 505 patients, 125 (24.8%) had lymphocytic thyroiditis, and 380 (75.2%) had normal thyroid parenchyma on pathologic analysis. The κ value for intraobserver variance ranged from -0.002 to 0.781, and the overall κ values for interobserver variance were 0.570 and 0.214 in the first and second tests, respectively. The sensitivity, specificity, accuracy, positive predictive value, and negative predictive value for the 3 reviewers versus the principal component analysis index were 28.0% to 83.2%, 43.7% to 82.6%, 53.5% to 79.0%, 24.6% to 56.2%, and 75.2% to 88.9% versus 58.4%, 72.4%, 68.9%, 41.0%, and 84.1%., Conclusions: Histogram analysis of grayscale US images provided confirmable and quantitative information about lymphocytic thyroiditis and was comparable with performers' assessments in diagnostic performance., (© 2016 by the American Institute of Ultrasound in Medicine.)

A compressed sensing dynamic MR technique called k-t FOCUSS (k-t FOCal Underdetermined System Solver) has been recently proposed. It outperforms the conventional k-t BLAST/SENSE (Broad-use Linear Acquisition Speed-up Technique/SENSitivity Encoding) technique by exploiting the sparsity of x-f signals. This paper applies this idea to radial trajectories for high-resolution cardiac cine imaging. Radial trajectories are more suitable for high-resolution dynamic MRI than Cartesian trajectories since there is smaller tradeoff between spatial resolution and number of views if streaking artifacts due to limited views can be resolved. As shown for Cartesian trajectories, k-t FOCUSS algorithm efficiently removes artifacts while preserving high temporal resolution. k-t FOCUSS algorithm applied to radial trajectories is expected to enhance dynamic MRI quality. Rather than using an explicit gridding method, which transforms radial k-space sampling data to Cartesian grid prior to applying k-t FOCUSS algorithms, we use implicit gridding during FOCUSS iterations to prevent k-space sampling errors from being propagated. In addition, motion estimation and motion compensation after the first FOCUSS iteration were used to further sparsify the residual image. By applying an additional k-t FOCUSS step to the residual image, improved resolution was achieved. In vivo experimental results show that this new method can provide high spatiotemporal resolution even from a very limited radial data set., (Copyright (c) 2009 Wiley-Liss, Inc.)