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Purpose: The aim of the study was to compare three different elastography methods, namely Strain Elastography (SE), Point Shear-Wave Elastography (pSWE) using Acoustic Radiation Force Impulse (ARFI)-Imaging and 2D-Shear Wave Elastography (2D-SWE), in the same study population for the differentiation of thyroid nodules.
Materials and methods: All patients received a conventional ultrasound scan, SE and 2D-SWE, and all patients except for two received ARFI-Imaging. Cytology/histology of thyroid nodules was used as a reference method. SE measures the relative stiffness within the region of interest (ROI) using the surrounding tissue as reference tissue. ARFI mechanically excites the tissue at the ROI using acoustic pulses to generate localized tissue displacements. 2D-SWE measures tissue elasticity using the velocity of many shear waves as they propagate through the tissue.
Results: 84 nodules (73 benign and 11 malignant) in 62 patients were analyzed. Sensitivity, specificity and NPV of SE were 73%, 70% and 94%, respectively. Sensitivity, specificity and NPV of ARFI and 2D-SWE were 90%, 79%, 98% and 73%, 67%, 94% respectively, using a cut-off value of 1.98m/s for ARFI and 2.65m/s (21.07kPa) for 2D-SWE. The AUROC (Area under the Receiver Operating Characteristic) of SE, ARFI and 2D-SWE for the diagnosis of malignant thyroid nodules were 52%, 86% and 71%, respectively. A significant difference in AUROC was found between SE and ARFI (p = 0.008), while no significant difference was found between ARFI and SWE (86% vs. 71%, p = 0.31), or SWE and SE (71% vs. 52%, p = 0.26).
Conclusion: pSWE using ARFI and 2D-SWE showed comparable results for the differentiation of thyroid nodules. ARFI was superior to elastography using SE.
Research on the music-language interface has extensively investigated similarities and differences of poetic and musical meter, but largely disregarded melody. Using a measure of melodic structure in music––autocorrelations of sound sequences consisting of discrete pitch and duration values––, we show that individual poems feature distinct and text-driven pitch and duration contours, just like songs and other pieces of music. We conceptualize these recurrent melodic contours as an additional, hitherto unnoticed dimension of parallelistic patterning. Poetic speech melodies are higher order units beyond the level of individual syntactic phrases, and also beyond the levels of individual sentences and verse lines. Importantly, auto-correlation scores for pitch and duration recurrences across stanzas are predictive of how melodious naive listeners perceive the respective poems to be, and how likely these poems were to be set to music by professional composers. Experimentally removing classical parallelistic features characteristic of prototypical poems (rhyme, meter, and others) led to decreased autocorrelation scores of pitches, independent of spoken renditions, along with reduced ratings for perceived melodiousness. This suggests that the higher order parallelistic feature of poetic melody strongly interacts with the other parallelistic patterns of poems. Our discovery of a genuine poetic speech melody has great potential for deepening the understanding of the music-language interface.