Added Value of Superb Microvascular Imaging and Virtual Touch Imaging Quantification in Assisting Thyroid Cancer Classification

Abstract

This prospective study determined the value added by superb microvascular imaging (SMI) and Virtual Touch imaging quantification (VTIQ) to conventional ultrasonography in classifying malignant and benign thyroid nodules. One hundred eighty-three thyroid nodules (TNs) in 120 patients (112 benign and 71 malignant TNs) were evaluated. SMI revealed noticeable variance between benign and malignant TNs (p < 0.001). Malignant nodules tended to have rich vascularity (grade 3: 38/71, 53.5%) compared with benign nodules (grade 3: 33/ 112, 29.5%). There is a statistically significant difference between malignant and benign TNs with respect to shear-wave speed (SWS) values (all p values <0.001). The SWS mean, maximum and ratio of malignant nodules were 3.97 § 1.34, 4.79 § 1.70 and 1.25 § 0.39, respectively. The SWS mean, maximum and ratio of benign nodules were 2.65 § 0.42, 2.97 § 0.46 and 1.15 § 0.35, respectively. With respect to area under the curve values, the combined use of SMI or VTIQ improved the diagnostic performance of classifying malignant and benign TNs compared with that of ultrasonography alone. The combination of three modalities achieved the greatest area under the curve values (0.9811, 95% confidence interval: 0.95529À1.000), followed by US + VTIQ (0.9747, 0.94543À1.000), US + SMI (0.9032, 0.85345À0.95391) and ultrasonography (0.8291, 0.76417À0.89403).

Usefulness of Ultrasonographic Detective Flow Imaging for Detecting Parathyroid Tumors: A Report of Two Cases

“…Lu et al [14] reported that SMI was significantly more effective in the detection of microvascular flow signals than CDU and/or power Doppler ultrasonography (PDU) in 52 thyroid nodules (TNs), benign (n = 13), and malignant (n = 39) nodules. Furthermore, Zhu et al [19] reported that SMI revealed noticeable variation between malignant (n = 39) and benign (n = 13) TNs (p < 0.001), and that malignant nodules tended to have richer vascularity compared with benign nodules.…”

“…Compared to conventional ultrasonography, SMI can detect low-velocity blood flow with greater sensitivity and display more microvascular information [12]. The diagnostic application of SMI has been reported in thyroid nodules [12][13][14][15][16][17][18][19] and breast cancers [20][21][22], although there are no publications on PTs. Lu et al [14] reported that SMI was significantly more effective in the detection of microvascular flow signals than CDU and/or power Doppler ultrasonography (PDU) in 52 thyroid nodules (TNs), benign (n = 13), and malignant (n = 39) nodules.…”

The Value of Ultrasonic Elastography in Detecting Placental Stiffness for the Diagnosis of Preeclampsia: A Meta-Analysis

“…The risk of severe complications during the perinatal period is increased 3–25 times in patients with PE, including placental abruption, disseminated intravascular coagulation, pulmonary oedema, and aspiration pneumonia [ 36 ]. The pathogenesis of PE is believed to be closely related to placental defects, including vascular growth factors such as sFlt-1 and PlGF [ 11 ]. In recent years, some original studies have focused on the value of using ultrasound elastography for evaluating placental stiffness to diagnose PE.…”

“…Medical imaging techniques play a crucial role in helping us understand the effect of placental function on pregnancy-related health and outcomes. Ultrasonic elastography is a non-invasive technique that evaluates the stiffness of target tissues and has been widely used in organs such as the liver, thyroid, and breasts with promising results [ 11 , 12 , 13 , 14 , 15 , 16 ]. Initial studies on placental elastography measured the elastic modulus of the human placenta during late pregnancy and found that it was independent of the uterine artery pulsatility index, thus serving as an independent assessment parameter [ 17 ].…”

Potential diagnostic value of quantitative superb microvascular imaging in premalignant and malignant cervical lesions

“…It effectively distinguishes the noise generated by blood flow and tissue motion, employing adaptive computational methods to display accurate blood flow data ( 14 ). In comparison to conventional two-dimensional color Doppler ultrasound, SMI has the ability to detect microvascular and low-velocity blood flow, enabling visual assessment of blood perfusion as well as the distribution and density of blood vessels ( 15 – 17 ). SMI serves as a noninvasive approach for monitoring blood flow and displaying vascular distribution, offering advantages in terms of speed, cost-effectiveness, and repeatability.…”