Emerging contrast-enhanced ultrasound applications in children.
Ryne A DidierDavid M BikoMisun HwangSunil UnnikrishnanMagdalena M WoźniakGibran T YusufAnush SridharanPublished in: Pediatric radiology (2021)
Ultrasound contrast agent (UCA) use in radiology is expanding beyond traditional applications such as evaluation of liver lesions, vesicoureteral reflux and echocardiography. Among emerging techniques, 3-D and 4-D contrast-enhanced ultrasound (CEUS) imaging have demonstrated potential in enhancing the accuracy of voiding urosonography and are ready for wider clinical adoption. US contrast-based lymphatic imaging has been implemented for guiding needle placement in MR lymphangiography in children. In adults, intraoperative CEUS imaging has improved diagnosis and assisted surgical management in tumor resection, and its translation to pediatric brain tumor surgery is imminent. Because of growing interest in precision medicine, targeted US molecular imaging is a topic of active preclinical research and early stage clinical translation. Finally, an exciting new development in the application of UCA is in the field of localized drug delivery and release, with a particular emphasis on treating aggressive brain tumors. Under the appropriate acoustic settings, UCA can reversibly open the blood-brain barrier, allowing drug delivery into the brain. The aim of this article is to review the emerging CEUS applications and provide evidence regarding the feasibility of these applications for clinical implementation.
Keyphrases
- contrast enhanced ultrasound
- drug delivery
- early stage
- high resolution
- magnetic resonance
- minimally invasive
- young adults
- cancer therapy
- primary care
- computed tomography
- heart failure
- magnetic resonance imaging
- left ventricular
- lymph node
- radiation therapy
- squamous cell carcinoma
- climate change
- stem cells
- patients undergoing
- machine learning
- photodynamic therapy
- coronary artery bypass
- functional connectivity
- quality improvement
- rectal cancer
- electronic health record
- deep learning
- atrial fibrillation