Evaluation Of Tissue Elasticity Research Articles

Elasticity of the Cervix in Relation to Uterus Position.

Strain elastography allows the evaluation of tissue elasticity. Background/Objectives: Tissue elasticity depends on the content and distribution of collagen fibers and is shaped by the applied tensile forces that may differ in uteri with a different angle of flexion of the corpus on the cervix. The objective was to investigate whether the angle of uterine flexion is related to cervical tissue elasticity. Methods: The anterior angle between the longitudinal axis of the uterus corpus and that of the cervix was measured in 275 non-pregnant young women by transvaginal ultrasonography and considered both as an absolute value or categorized as ≤150°, between >150° and ≤210°, and >210°. Strain elastography was used to assess tissue elasticity by placing the probe in the anterior vaginal fornix. Tissue elasticity was evaluated in the middle of the anterior cervical compartment (ACC), in the middle of the posterior cervical compartment (PCC), in the middle portion of the cervical canal (MCC), and at the internal cervical os (ICO). In a sagittal plane MCC was evaluated across the cervical canal, and ACC and PCC at a distance equal between the cervical canal and the outer anterior or posterior part of the cervix. MCC, ACC and PCC were evaluated at equal distance between the ICO and the external cervical os. Elasticity was expressed as a color score ranging from 0.1 (low elasticity) to 3 (high elasticity). Results: The angle of uterine flexion show a negative linear relation with the elasticity of the ACC (p = 0.001) and MCC (p = 0.002) and a positive relation with the elasticity of the PCC (p = 0.054). In comparison to uteri with an angle of flexion of <150°, those with an angle of flexion of >210° had lower elasticity of the ACC (p = 0.001) and MCC (p = 0.001) and higher elasticity of the PCC (p = 0.004). The ACC/PCC and PCC/MCC elasticity ratios were also significantly different (p = 0.001). Conclusions: The angle of uterine flexion is associated with changes in cervix elasticity. Retroflexion is associated with stiffer ACC and MCC and a more elastic PCC. Differences in tissue elasticity suggest structural changes of the cervix that may have implication in variate obstetric and gynecological conditions.

Evaluation of Different Types of Breast Lesions With Apparent Diffusion Coefficient and Shear Wave Elastography Values: Comparison of Shear Wave Elastography and Apparent Diffusion Coefficient in Breast Lesions

Objective: The aim of this study was to compare the stiffness of different histological types of breast lesions by obtaining shear wave elastography (SWE) and apparent diffusion coefficient (ADC) values, and to determine the contribution of these two methods to the diagnosis. Materials and Methods: In total, 70 patients with biopsy-proven breast lesions were included in the study. The mean SWE values of breast lesions were recorded and ADC values of these lesions were calculated. Receiver operating characteristic (ROC) curve analyses and the diagnostic accuracies of SWE-ADC values were determined. Results: The mean SWE values were 45.47 ± 25.11 kPa and 3.51 ± 1.04 m/s in benign group, and 161.11 ± 219.34 kPa and 5.96 ± 1.06 m/s in malignant group, respectively. The mean ADC values were 1.38 ± 0.32 (×10–3 mm2/s) in benign group and 0.96 ± 0.22 (×10–3 mm2/s) in malignant group, respectively. When the diagnostic performances of both imaging modalities on mass stiffness are evaluated, statistically significant negative correlations were found between SWE lesion values and ADC lesion values. Conclusion: Evaluation of tissue elasticity has recently been used frequently in the diagnosis of breast diseases. SWE-ADC values, which are negatively correlated in the diagnosis of breast masses, may prove to be a powerful alternative diagnostic tool that can be used interchangeably, as appropriate.

Su1991 Novel Technology for the Quantitative Evaluation of Tissue Elasticity Using a Newly Developed EUS System

Su1991 Novel Technology for the Quantitative Evaluation of Tissue Elasticity Using a Newly Developed EUS System

Sonoelastography: the method of choice for evaluation of tissue elasticity

Ultrasound devices and methodologies have been continuously evolving and becoming more important as tools in diagnostic medicine. Recently a new ultrasound diagnostic technique has been developed. Named sonoelastography, the technique enables evaluation of tissue elasticity and is based on differences in stiffness (hardness, compressibility, elasticity) of pathological changes and normal adjacent tissue. Sonoelastography (SE) is also known as Real-time tissue elastography (RTE), Real-time sonoelastography (RTSE), Tissue type imaging (TTI) and Ultrasound Strain Imaging Technology. It has been found useful in many medicine elds and adopted readily by clinicians of different specialties. It gives more information than conventional ultrasound in evaluation of tumors, liver disease, skeletal muscles, rheumatoid nodules and other pathological changes. This review covers the basics of elastography, its applications, instruments, techniques, the scoring system and the indications for elastography.

A quality-guided displacement tracking algorithm for ultrasonic elasticity imaging

Displacement estimation is a key step in the evaluation of tissue elasticity by quasistatic strain imaging. An efficient approach may incorporate a tracking strategy whereby each estimate is initially obtained from its neighbours’ displacements and then refined through a localized search. This increases the accuracy and reduces the computational expense compared with exhaustive search. However, simple tracking strategies fail when the target displacement map exhibits complex structure. For example, there may be discontinuities and regions of indeterminate displacement caused by decorrelation between the pre- and post-deformation radio frequency (RF) echo signals. This paper introduces a novel displacement tracking algorithm, with a search strategy guided by a data quality indicator. Comparisons with existing methods show that the proposed algorithm is more robust when the displacement distribution is challenging.