State of the Art: Contrast Enhanced 4D Ultrasound to Monitor or Assess Locoregional Therapies

2022 ◽  
Author(s):  
Mohamed Tantawi ◽  
Susan Shamimi-Noori ◽  
Colette M. Shaw ◽  
John R. Eisenbrey
Keyword(s):  
Machine Learning Algorithms ◽  
Management Tool ◽  
Ultrasound Transducers ◽  
Two Dimensional ◽  
Time Dynamic ◽  
4D Ultrasound ◽  
Contrast Enhanced ◽  
Liver Cancers ◽  
Locoregional Therapies ◽  
Early Tumor

AbstractLocoregional therapies (LRTs) are an essential management tool in the treatment of primary liver cancers or metastatic liver disease. LRTs include curative and palliative modalities. Monitoring treatment response of LRTs is crucial for maximizing benefit and improving clinical outcomes. Clinical use of contrast-enhanced ultrasound (CEUS) was introduced more than two decades ago. Its portability, cost effectiveness, lack of contraindications and safety make it an ideal tool for treatment monitoring in numerous situations. Two-dimensional dynamic CEUS has been proved to be equivalent to the current imaging standard in the guidance of LRTs, assessment of their adequacy, and detection of early tumor recurrence. Recent technical advances in ultrasound transducers and image processing have made 3D CEUS scanning widely available on most commercial ultrasound systems. 3D scanning offers a broad multiplanar view of anatomic structures, overcoming many limitations of two-dimensional scanning. Furthermore, many ultrasound systems provide real-time dynamic 3D CEUS, also known as 4D CEUS. Volumetric CEUS has shown to perform better than 2D CEUS in the assessment and monitoring of some LRTs. CEUS presents a valid alternative to the current imaging standards with reduced cost and decreased risk of complications. Future efforts will be directed toward refining the utility of 4D CEUS through approaches such as multi-parametric quantitative analysis and machine learning algorithms.

Dynamic Contrast-Enhanced MRI and Fractal Characteristics of Percolation Clusters in Two-Dimensional Tumor Blood Perfusion

1999 ◽  
Vol 121 (5) ◽  
pp. 480-486 ◽  
Author(s):  
O. I. Craciunescu ◽  
S. K. Das ◽  
S. T. Clegg
Keyword(s):  
Tumor Tissue ◽  
Blood Perfusion ◽  
Percolation Cluster ◽  
Three Dimensions ◽  
Invasion Percolation ◽  
Two Dimensional ◽  
Tumor Perfusion ◽  
Dynamic Contrast Enhanced ◽  
Contrast Enhanced ◽  
Fractal Characteristics

Dynamic contrast-enhanced magnetic resonance imaging (DE-MRI) of the tumor blood pool is used to study tumor tissue perfusion. The results are then analyzed using percolation models. Percolation cluster geometry is depicted using the wash-in component of MRI contrast signal intensity. Fractal characteristics are determined for each two-dimensional cluster. The invasion percolation model is used to describe the evolution of the tumor perfusion front. Although tumor perfusion can be depicted rigorously only in three dimensions, two-dimensional cases are used to validate the methodology. It is concluded that the blood perfusion in a two-dimensional tumor vessel network has a fractal structure and that the evolution of the perfusion front can be characterized using invasion percolation. For all the cases studied, the front starts to grow from the periphery of the tumor (where the feeding vessel was assumed to lie) and continues to grow toward the center of the tumor, accounting for the well-documented perfused periphery and necrotic core of the tumor tissue.

scholarly journals Changes in Tumor Stem Cell Markers and Epithelial-Mesenchymal Transition Markers in Nonluminal Breast Cancer after Neoadjuvant Chemotherapy and Their Correlation with Contrast-Enhanced Ultrasound

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Xiaoling Leng ◽  
Guofu Huang ◽  
Lianhua Zhang ◽  
Jianbing Ding ◽  
Fucheng Ma
Keyword(s):  
Breast Cancer ◽  
Epithelial Mesenchymal Transition ◽  
Two Dimensional ◽  
Intensity Curve ◽  
Time Intensity Curve ◽  
Mesenchymal Transition ◽  
Contrast Enhanced ◽  
Response To Chemotherapy ◽  
Perfusion Defects ◽  
Emt Markers

Nonluminal breast cancer has high early metastasis and treatment resistance, and neoadjuvant chemotherapy (NAC) is needed. The presence of cancer stem cells (CSC) and epithelial-mesenchymal transition (EMT) leads to poor prognosis. This study investigated the changes in CSC markers and EMT markers after NAC in nonluminal breast cancer and their correlation with contrast-enhanced ultrasound (CEUS) features and chemotherapy efficacy. Before NAC, the range of nonluminal breast cancer on CEUS was larger than that of two-dimensional ultrasound, but after NAC, it was significantly smaller than that of two-dimensional ultrasound and closer to the postoperative pathological size. After NAC, the enlarged lesions and perfusion defects were significantly less than those before NAC. The time-intensity curve showed the characteristics of slow-in, low enhancement, and low perfusion. Nonluminal breast cancer downregulated the expression of CSC markers and EMT markers after NAC, but the epithelial phenotype of nonluminal breast cancer with good response to chemotherapy was upregulated. In nonluminal breast cancer with poor response to chemotherapy, markers of CSC and EMT were highly expressed before chemotherapy. In conclusion, CEUS is better than conventional ultrasound in estimating NAC efficacy in this mode. CEUS can also predict the prognosis of nonluminal breast cancer before NAC with the characteristics of enhanced enlargement and perfusion defects. The contrast-enhanced time-intensity curve of lesions with relatively poor blood supply may have more CSC and EMT characteristics.

scholarly journals A Systematic Evaluation of Interneuron Morphology Representations for Cell Type Discrimination

2020 ◽  
Vol 18 (4) ◽  
pp. 591-609 ◽  
Author(s):  
Sophie Laturnus ◽  
Dmitry Kobak ◽  
Philipp Berens
Keyword(s):  
Cell Types ◽  
Bipolar Cells ◽  
Machine Learning Algorithms ◽  
Feature Representation ◽  
Inhibitory Neurons ◽  
Systematic Evaluation ◽  
Two Dimensional ◽  
Feature Representations ◽  
Density Maps ◽  
The Difference

Abstract Quantitative analysis of neuronal morphologies usually begins with choosing a particular feature representation in order to make individual morphologies amenable to standard statistics tools and machine learning algorithms. Many different feature representations have been suggested in the literature, ranging from density maps to intersection profiles, but they have never been compared side by side. Here we performed a systematic comparison of various representations, measuring how well they were able to capture the difference between known morphological cell types. For our benchmarking effort, we used several curated data sets consisting of mouse retinal bipolar cells and cortical inhibitory neurons. We found that the best performing feature representations were two-dimensional density maps, two-dimensional persistence images and morphometric statistics, which continued to perform well even when neurons were only partially traced. Combining these feature representations together led to further performance increases suggesting that they captured non-redundant information. The same representations performed well in an unsupervised setting, implying that they can be suitable for dimensionality reduction or clustering.

Increased volume of coverage for abdominal contrast-enhanced MR angiography with two-dimensional autocalibrating parallel imaging: Initial experience at 3.0 Tesla

2009 ◽  
Vol 30 (5) ◽  
pp. 1093-1100 ◽  
Author(s):  
Darren P. Lum ◽  
Reed F. Busse ◽  
Christopher J. Francois ◽  
Anja C. Brau ◽  
Philip J. Beatty ◽  
...  
Keyword(s):  
Mr Angiography ◽  
Parallel Imaging ◽  
Initial Experience ◽  
Two Dimensional ◽  
3.0 Tesla ◽  
Contrast Enhanced

Short-time dynamic behavior of the two-dimensional square lattice fully frustrated XY model

2002 ◽  
Vol 292 (6) ◽  
pp. 303-308 ◽  
Author(s):  
Meng-Bo Luo ◽  
Qing-Hu Chen ◽  
He-Ping Ying ◽  
Zheng-Kuan Jiao
Keyword(s):  
Dynamic Behavior ◽  
Square Lattice ◽  
Xy Model ◽  
Two Dimensional ◽  
Time Dynamic ◽  
Short Time

Application of the Alternating Direction Explicit Procedure To Two-Dimensional Natural Gas Reservoirs

1966 ◽  
Vol 6 (02) ◽  
pp. 137-142 ◽  
Author(s):  
D. Quon ◽  
P.M. Dranchuk ◽  
S.R. Allada ◽  
P.K. Leung
Keyword(s):  
Natural Gas ◽  
Boundary Conditions ◽  
Computer Hardware ◽  
Management Tool ◽  
Two Dimensional ◽  
Gas Reservoirs ◽  
Fluid Saturation ◽  
Alternating Direction ◽  
Explicit Procedure ◽  
Natural Gas Reservoirs

Abstract The alternating direction explicit procedure (ADEP) makes use of the boundary conditions to reduce multi-dimensional problems to a series of one-dimensional problems. The method, previously applied to reservoirs containing only an undersaturated oil, bas now been extended to cover the case of natural gas reservoirs. Although this involves solving a non-linear partial differential equation, application of the procedure is straight- forward and no calculational problems were encountered. Introduction There has been a growing interest in formulating mathematical models of petroleum and natural gas reservoirs - models which permit the engineer to examine and evaluate the physical and economic consequences of various alternative production policies. The tremendous reduction in the cost of solving such models in recent years has made possible their use as an almost routine management tool. This reduction is the result not only of improved computer hardware but also of the development of more efficient mathematical techniques. The present paper is concerned with the application of a recently proposed numerical method (ADEP) to two-dimensional gas reservoirs. STATEMENT OF THE PROBLEM Given a two-dimensional Region R, bounded by a closed Curve C (Fig. 1) such that the behavior on Curve is known, the differential mass balance for each fluid phase in R, neglecting gravitational effects and assuming Darcy's law for fluid transport, can be written as: A typical and common set of boundary conditions is given by (1) / = 0 on Curve C where r is the direction normal to Curve C; (2) p is known throughout Region R at some time t; and (3) wf is known for all x, y and t. Physically, this represents the case where the reservoir is bounded by impermeable media, where the initial pressure throughout the reservoir at the beginning of gas production is known and where the production rate at each well is specified at all times. For single-phase reservoirs, the problem is to determine the pressure throughout Region R at all times; for multi-phase reservoirs, in addition to the pressure, the value of the fluid saturation is also required. Since analytical solutions to this equation for the general case are not available, we must resort to numerical integrating techniques, using finite-difference approximations. SPEJ P. 137ˆ

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