Assessment of Transarterial Chemoembolization Using Super-resolution Ultrasound Imaging and a Rat Model of Hepatocellular Carcinoma

Optically Validated Microvascular Phantom for Super-Resolution Ultrasound Imaging

Super-resolution ultrasound (SRUS) visualizes microvasculature beyond the ultrasound (US) diffraction limit (wavelength( )/2) by localizing and tracking spatially isolated microbubble (MB) contrast agents. SRUS phantoms typically consist of simple tube structures, where diameter channels below m are not available. Furthermore, these phantoms are generally fragile and unstable, have limited ground truth validation, and their simple structure limits the evaluation of SRUS algorithms. To aid SRUS development, robust and durable phantoms with known and physiologically relevant microvasculature are needed for repeatable SRUS testing. This work proposes a method to fabricate durable microvascular phantoms that allow optical gauging for SRUS validation. The methodology used a microvasculature negative print embedded in a Polydimethylsiloxane (PDMS) to fabricate a microvascular phantom. Branching microvascular phantoms with variable microvascular density were demonstrated with optically validated vessel diameters down to m ( ; m). SRUS imaging was performed and validated with optical measurements. The average SRUS error was m ( ) with a standard deviation error of m. The average error decreased to m ( ) once the number of localized MBs surpassed 1000 per estimated diameter. In addition, less than 10% variance of acoustic and optical properties and the mechanical toughness of the phantoms measured a year after fabrication demonstrated their long-term durability. This work presents a method to fabricate durable and optically validated complex microvascular phantoms which can be used to quantify SRUS performance and facilitate its further development.

Super-resolution ultrasound and microvasculomics: a consensus statement

This is a summary of a consensus statement on the introduction of "Ultrasound microvasculomics" produced by The Chinese Artificial Intelligence Alliance for Thyroid and Breast Ultrasound. The evaluation of microvessels is a very important part for the assessment of diseases. Super-resolution ultrasound (SRUS) microvascular imaging surpasses traditional ultrasound imaging in the morphological and functional analysis of microcirculation. SRUS microvascular imaging relies on contrast microbubbles to gain sensitivity to microvessels and improves the spatial resolution of ultrasound blood flow imaging for a more detailed depiction of vascular structures and hemodynamics. This method has been applied in preclinical animal models and pilot clinical studies, involving areas including neurology, oncology, nephrology, and cardiology. However, the current quantitative parameters of SRUS images are not enough for precise evaluation of microvessels. Therefore, by employing omics methods, more quantification indicators can be obtained, enabling a more precise and personalized assessment of microvascular status. Ultrasound microvasculomics - a high-throughput extraction of image features from SRUS images - is one novel approach that holds great promise but needs further validation in both bench and clinical settings. CLINICAL RELEVANCE STATEMENT: Super-resolution Ultrasound (SRUS) blood flow imaging improves spatial resolution. Ultrasound microvasculomics is possible to acquire high-throughput information of features from SRUS images. It provides more precise and abundant micro-blood flow information in clinical medicine. KEY POINTS: This consensus statement reviews the development and application of super-resolution ultrasound (SRUS). The shortcomings of the current quantification indicators of SRUS and strengths of the omics methodology are addressed. "Ultrasound microvasculomics" is introduced for a high-throughput extraction of image features from SRUS images.

Dynamic Contrast-Enhanced Ultrasonography Combined With LR-M Classification Criteria for Differentiating Malignant Liver Nodules at High Risk for Hepatocellular Carcinoma

OBJECTIVE

We aimed to investigate the value of quantitative parameters derived from dynamic contrast-enhanced ultrasonography (DCE-US) and a combination of these quantitative parameters with the LR-M classification criteria in distinguishing hepatocellular carcinoma (HCC) nodules and non-HCC malignancies.

METHODS

HCC and non-HCC malignant nodules were grouped using pathologic results, and each nodule was classified using CEUS LI-RADS 2017. Quantitative CEUS analysis of each nodule was performed using VueBox, and quantitative parameters were compared between the HCC and non-HCC groups. The diagnostic efficacy of the LR-5 category for HCC was analyzed using the LR-M classification criteria along with time-related quantitative parameters.

RESULTS

Of the 190 malignant liver nodules, 137 and 53 were HCCs and non-HCC malignancies, respectively. The median values of quantitative parameters RT (rise time), TTP (time to peak), mTTl (mean transit time local), and FT (fall time) in the non-HCC malignant group were lower than those in the HCC group, with p < 0.05. There was a statistically significant difference in WiAUC (wash-in area under the curve), WoAUC (wash-out area under the curve), WiWoAUC (wash-in and wash-out area under the curve), and WoR (wash-out rate) values between HCC and non-HCC malignant groups, with p < 0.05. Using LR-M washout time <60 s and FT ≤21.2 s as the new diagnostic standard, the LR-5 category showed a sensitivity of 83.9%, specificity of 96.2%, and positive predictive value of 98.3% for HCC diagnosis.

CONCLUSION

DCE-US can facilitate the distinction of HCCs and non-HCC malignancies. Non-HCC malignancies present with earlier peak enhancement and more rapid and marked washout than HCC nodules. The combination of the LR-M classification criteria and FT ≤21.2 s can significantly improve the diagnostic sensitivity of the LR-5 category for HCC.