Dynamic contrast-enhanced ultrasound (US) imaging, a technique that uses microbubble contrast agents with diagnostic US, has recently been technically summarized and reviewed by a European Federation of Societies for Ultrasound in Medicine and Biology position paper. However, the practical applications of this imaging technique were not included. This article reviews and discusses the published literature on the clinical use of dynamic contrast-enhanced US. This review finds that dynamic contrast-enhanced US imaging is the most sensitive cross-sectional real-time method for measuring the perfusion of parenchymatous organs noninvasively. It can measure parenchymal perfusion and therefore can differentiate between benign and malignant tumors. The most important routine clinical role of dynamic contrast-enhanced US is the prediction of tumor responses to chemotherapy within a very short time, shorter than using Response Evaluation Criteria in Solid Tumors criteria. Other applications found include quantifying the hepatic transit time, diabetic kidneys, transplant grafts, and Crohn disease. In addition, the problems involved in using dynamic contrast-enhanced US are discussed.
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http://dx.doi.org/10.7863/ultra.34.2.179 | DOI Listing |
JCO Clin Cancer Inform
January 2025
SimBioSys Inc, Chicago, IL.
Purpose: Perfusion modeling presents significant opportunities for imaging biomarker development in breast cancer but has historically been held back by the need for data beyond the clinical standard of care (SoC) and uncertainty in the interpretability of results. We aimed to design a perfusion model applicable to breast cancer SoC dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) series with results stable to low temporal resolution imaging, comparable with published results using full-resolution DCE-MRI, and correlative with orthogonal imaging modalities indicative of biophysical markers.
Methods: Subsampled high-temporal-resolution DCE-MRI series were run through our perfusion model and resulting fits were compared for consistency.
Radiology
January 2025
From the Department of Radiology, Shenzhen Nanshan People's Hospital, Shenzhen University, Taoyuan Rd No. 89, Nanshan District, Shenzhen 518000, Guangdong, China (H.H., Z.D., Y.Q.); Medical AI Laboratory and Guangdong Key Laboratory of Biomedical Measurements and Ultrasound Imaging, School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University, Shenzhen, China (J.M., R.L., B.H.); Department of Medical Imaging, People's Hospital of Longhua, Shenzhen, Guangdong, China (X.P., Y.Z.); and Department of Radiology, Shenzhen People's Hospital, Shenzhen, Guangdong, China (D.Z., G.H.).
Background Multiparametric MRI, including contrast-enhanced sequences, is recommended for evaluating suspected prostate cancer, but concerns have been raised regarding potential contrast agent accumulation and toxicity. Purpose To evaluate the feasibility of generating simulated contrast-enhanced MRI from noncontrast MRI sequences using deep learning and to explore their potential value for assessing clinically significant prostate cancer using Prostate Imaging Reporting and Data System (PI-RADS) version 2.1.
View Article and Find Full Text PDFAlzheimers Dement
January 2025
Institute for Biomedical Engineering and Institute of Pharmacology and Toxicology, Faculty of Medicine, University of Zurich, Zurich, Switzerland.
Introduction: Transcranial pulse stimulation (TPS) is increasingly being investigated as a promising potential treatment for Alzheimer's disease (AD). Although the safety and preliminary clinical efficacy of TPS short pulses have been supported by neuropsychological scores in treated AD patients, its fundamental mechanisms are uncharted.
Methods: Herein, we used a multi-modal preclinical imaging platform combining real-time volumetric optoacoustic tomography, contrast-enhanced magnetic resonance imaging, and ex vivo immunofluorescence to comprehensively analyze structural and hemodynamic effects induced by TPS.
J Hepatocell Carcinoma
January 2025
School of Medicine, University of Electronic Science and Technology, Sichuan, China.
Objective: This study aimed to investigate how dynamic contrast-enhanced CT imaging signs correlate with the differentiation grade and microvascular invasion (MVI) of hepatocellular carcinoma (HCC), and to assess their predictive value for MVI when combined with clinical characteristics.
Methods: We conducted a retrospective analysis of clinical data from 232 patients diagnosed with HCC at our hospital between 2021 and 2022. All patients underwent preoperative enhanced CT scans, laboratory tests, and postoperative pathological examinations.
Sci Rep
January 2025
Department of Radiation Oncology, Henry Ford Hospital, Detroit, USA.
Best current practice in the analysis of dynamic contrast enhanced (DCE)-MRI is to employ a voxel-by-voxel model selection from a hierarchy of nested models. This nested model selection (NMS) assumes that the observed time-trace of contrast-agent (CA) concentration within a voxel, corresponds to a singular physiologically nested model. However, admixtures of different models may exist within a voxel's CA time-trace.
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