Clinical trial · Observational
Clinical Application of Super-resolution Ultrasound(SR-US) Imaging in Solid Tumors
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 8, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260908-000001
Summary
Brief summary (as posted)
It has well accepted that tumor angiogenesis present aberrant vascular architecture and functional abnormalities, which is associated with tumorigenesis, tumor propagation and progression. By locating, separating and tracking microbubbles, the recently introduced and upgraded Ultrasound Localization Microscopy (ULM) surpassed classical wave diffraction limit. However, the acquisition of structural and functional parameters of microcirculation in vivo for ULM is still confined by the compromise between the resolution and penetration depth. The relatively long acquisition time induced the difficulty of motion correction potentially, which hampers the preclinical to clinical application in organs with distinct tissue motion such as the liver. Therefore, we take the lead in studying human liver lesion microvasculature, which remains a challenge for noninvasive, quantitative and functional intravital imaging especially due to its deep-seated location and strong motion. We developed a Super-resolution Ultrasound (SR-US) imaging technique based on ULM to assess its feasibility of visualizing and quantifying microvasculature in human organs.
Conditions
Conditions (5)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Microvessels | — | UNRESOLVED | — |
| Neoplasm Metastasis | — | UNRESOLVED | — |
| Neoplasms, Liver | Liver Neoplasm | ONTOLOGY_EXACT | 0.98 |
| Neoplasms Malignant | Malignant Neoplasm | ALIAS | 0.90 |
| Ultrasound | — | UNRESOLVED | — |
Interventions
Interventions (0)
Data not yet available
Design
Arms and outcomes
Arms (0)
[]Primary outcomes (7)
- measure
- Perfusion index
- timeFrame
- 30 minutes
- description
- The product of the average speed of microbubbles in region of interest (ROI) and the ROI area
- measure
- Vessel diameter
- timeFrame
- 30 minutes
- description
- To describe the diameters of the tiniest blood vessels that can be explored
- measure
- Vessel density
- timeFrame
- 30 minutes
- description
- To describe the ratio of the number of blood vessels in the tumor to the cross-sectional area of the tumor
- measure
- Vessel density ratio
- timeFrame
Eligibility
Eligibility (as posted)
- Sex
- All
- Minimum age
- 18 Years
- Maximum age
- 80 Years
Show eligibility criteria text
Inclusion Criteria: 1. Age over 18 years old, gender unlimited; 2. Patients with solid organ tumors with a maximum diameter \> 1cm; 3. No contraindications with contrast ultrasound agents; 4. It can improve the pathological results of the tumor or the diagnostic results supported by other relevant imaging tests. 5. Patients can understand the purpose of the examination, voluntarily participate and sign the informed consent. Exclusion Criteria: 1. The subject is known to be allergic to any component of the contrast agent Sonovue; 2. Lesions were diffuse or borderless on contrast ultrasound; 3. Patients who underwent previous anti-angiogenesis and chemotherapy, or other local treatment of the tumor; 4. Poor image display or deep position in conventional ultrasound evaluation (\<10 cm from skin), 5. The researchers determined that there were any other factors that were not suitable for inclusion or affected participants' participation in the study 6. Patients with severe heart disease or lung disease; 7. Patients who are pregnant, may be pregnant or breastfeeding; 8. No enhanced MRI or enhanced CT results can be obtained; 9. The investigator considers the subjects unfit to participate in this study.
References
Publications (2)
- DERIVEDLiang M, Liu J, Wang H, An S, Chen C, Chu H, Zhu M, Su X, Liang P, Zong Y, Wan M. Ultrasound super-resolved hemodynamic estimation in microvessel using physics-informed neural networks and data assimilation. Comput Methods Programs Biomed. 2026 Feb 1;274:109136. doi: 10.1016/j.cmpb.2025.109136. Epub 2025 Oct 30. PMID 41202508
- DERIVEDZeng QQ, An SZ, Chen CN, Wang Z, Liu JC, Wan MX, Zong YJ, Jian XH, Yu J, Liang P. Focal liver lesions: multiparametric microvasculature characterization via super-resolution ultrasound imaging. Eur Radiol Exp. 2024 Dec 5;8(1):138. doi: 10.1186/s41747-024-00540-3. PMID 39636384