DCE-MRI raw data were imported into Omni-Kinetics (GE Healthcare) software for analysis. First, 3D non-rigid motion correction was performed on the 35-phase dynamic enhanced image to reduce respiratory motion artefacts. Then, the LAVA sequence images with two rotation angles (9° and 12°) were imported for T1 mapping calculation. Next, we imported the modified 35-stage enhanced image and fit the time-concentration curve of the contrast solution inside the aorta as an arterial input function (AIF) of the thigh vastus lateralis muscle, with selection of extended Tofts for the pharmacokinetic model. We selected the midlevel image of the femur and manually drew the region-of-interest (ROI). The ROI was placed so as to avoid the subcutaneous fat layer. Fascia software automatically calculated Ktrans, the rate constant (Kep), and the volume of extravascular extracellular space (Ve) three times for each ROI; these three measurements were then averaged for use (Figure 1 Figures 1A–D
Omni kinetics
Manufactured by GE Healthcare
Sourced in China
Omni-Kinetics is a laboratory equipment product from GE Healthcare. It is a multi-axis motion control system designed for precise and programmable movement of various laboratory instruments and devices. The core function of Omni-Kinetics is to provide accurate and reproducible positioning and automation capabilities for scientific applications.
Automatically generated - may contain errors
Lab products found in correlation
19 protocols using omni kinetics
1
Quantitative DCE-MRI Analysis of Muscle
2
Quantitative Perfusion Analysis of Tumors
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
A software module (OmniKinetics, GE Healthcare, China) was applied for post-processing. The volume transfer constant (Ktrans) and volume of extravascular extracellular space per unit volume of tissue (Ve) were obtained based on the extended Tofts and Kermode pharmacokinetic model. The arterial input function was located on the superior sagittal sinus. The postcontrast T1-weighted imaging functioned as reference. When the tumor was without enhancement, the T2-Flair images were registered in the DCE images, and the registration images were taken as reference. Regions of interest (ROIs) covering tumor parenchyma were placed after consensus was reached between two experienced radiologists. The ROIs placed on the reference images can automatically transfer onto the parameters maps, and then histogram parameters of Ktrans and Ve were generated automatically.
3
Texture Analysis of Brain Tumor Imaging
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
Preoperative axial T2WI and DWI (b value =1,000 mm2/s) maps were exported in DICOM format from the picture archiving and communication system to Omni-Kinetics software (Omni-Kinetics Version V2.0.10, GE Healthcare) to extract texture features. Prior to TA, image quality had been visually evaluated to avoid severe artifacts and mismatches between images. Two radiologists manually drew the regions of interest (ROIs) along the margin of the tumor avoiding peripheral fat, artifacts, and blood vessels in order to get rid of partial volume effect on both T2WI and DWI (Figure 2 ). For iso-dense tumors on T2WI maps, contrast-enhanced sequences and DWI were referred for tumor margin identification. For each lesion, we drew the ROIs by slice-by-slice segmentation of the whole tumor on each sequence. A total of 68 features were automatically extracted from T2WI or DWI maps. They were separated into five categories: 1) first-order statistics; 2) histogram; 3) gray-level co-occurrence matrix; 4) Haralick; and 5) run-length matrix.
4
Texture Analysis of Brain Tumors
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
TA was performed on axial T2WI and ADC maps, respectively, using in-house software (Omni-Kinetics, GE Healthcare) by two authors (Zhihua Lu and Ming Li). The regions of interest (ROIs) involve as much tumor tissue as possible on the largest tumor slice, excluding necrosis, cysts, and gas (Figures 1 and 2 ). Then, texture features based on T2WI and ADC maps were calculated automatically. The seven texture features that we chose included skewness, kurtosis, and uniformity (first-order statistics) and entropy, energy, inertia, and correlation (second-order statistics).
5
Quantitative DCE-MRI of Terminal Ileum
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
DCE-MRI parameters were calculated using a noncommercial software (Omni-Kinetics, GE Healthcare). First, the individual artery input function (AIF) was obtained from a region of interest (ROI) drawn on the abdominal aorta located in close proximity to the terminal ileum. Second, extended Tofts liner model was chosen for fitting of the tissue response curves.[22 (link)] The pharmacokinetic parameter as Ktrans and hemodynamic parameter as BV were generated as color maps (Fig. 1 ). ROI (30–50 mm2) for these DCE-MRI parameters (Ktrans, BV) was placed on the maximal enhancing region of the terminal ileum.
6
DCE-MRI Radiomics Analysis of LARC
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
All sequences acquired from the DCE-MRI of eligible patients with LARC were imported into Omni Kinetics (GE Healthcare, China) software for post-processing. First, multi-flip angles of 5°, 10°, and 15° and corrected dynamic enhancement sequence scans were processed using Omni Kinetics software. Second, the external iliac artery was selected as the input artery. Third, the Tofts pharmacokinetic model was used to obtain three DCE-MRI pseudo-color images (Ktrans, Kep, and Ve). Furthermore, the region of interest (ROI) was manually delineated on each slice of the sagittal DCE pseudo-color images for calculation, using T2-weighted images as a guide. The ROI was placed in an area to avoid necrosis, calcification, and blood vessels on each slice (Figure 1
7
DCE-MRI Analysis of Tumor Heterogeneity
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
The original DCE data was transferred to the Omni Kinetics (GE Healthcare, China) software. First, in order to correct the ROI displacement caused by patients' breathing and other involuntary movements, the DCE images were pre-processed with three-dimensional non-rigid registration. Second, multi-flip angles of 5°, 10°, and 15° and corrected dynamic enhancement sequence scans were processed by the Omni Kinetics software. Further, the arterial input function was performed, and abdominal aorta was selected as the input artery. Third, application of the Tofts model obtained four quantitative parameter maps (Ktrans, Kep, Ve, and Vp) [13 (link)]. The volume of interest was designed as a region containing necrotic and cystic tissues to determine the heterogeneity of tumor. Two senior radiologists manually outlined each layer of the AGC lesion in the quantitative parameter maps to form a 3D ROI for calculation. The software then automatically generated several commonly used histogram parameters (mean value; skewness; 10th, 25th, 50th, 75th, and 90th percentiles; uniformity; kurtosis; energy; and entropy) (Figure 1 ). All calculations were repeated three times to obtain the average value.
8
Texture Analysis of MRI Tumor Imaging
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
All the MR images were retrieved from the picture archiving and communication system and transferred to a personal computer in the Digital Imaging and Communications in Medicine format. The same two radiologists reviewed and processed the images in a random patient order by using an in-house developed software, Omni-kinetics (version 2.0.10; GE Healthcare Life Sciences), to obtain texture features. A 3D volume of interest (VOI) of the tumor was manually contoured by the two readers, slightly along the borders of the tumor to include the entire approximated tumor volume.
After generating the VOI, a total of 58 texture features were automatically extracted from the AP and PP images using the Omni-kinetics software. The texture features could be divided into four categories: i) 29 histogram features, ii) 8 gray-level co-occurrence matrix (GLCM) features, iii) 11 Haralick features, and iv) 10 run-length matrix (RLM) features. A detailed list of the features included in the present study is presented inTable I . Fig. 2B shows the diagram of texture analysis.
After generating the VOI, a total of 58 texture features were automatically extracted from the AP and PP images using the Omni-kinetics software. The texture features could be divided into four categories: i) 29 histogram features, ii) 8 gray-level co-occurrence matrix (GLCM) features, iii) 11 Haralick features, and iv) 10 run-length matrix (RLM) features. A detailed list of the features included in the present study is presented in
9
Radiomics Feature Extraction and Evaluation
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
Radiomics features were computed based on the 3D ROIs segmentation results using a locally developed scientific software Omni-kinetics (GE Healthcare, Shanghai, China) that is not commercially available. Features were categorized into five primary subgroups: (1) 14 first-order, (2) 13 histogram, (3) 13 GLCM, (4) 16 RLM, and (5) 16 pharmacokinetic parameters. Intra-reader agreement of each radiomics feature was assessed by Inter-class correlation coefficient (ICC), and ICC with greater than 0.70 was considered a good agreement.
10
Quantitative DCE-MRI Pharmacokinetic Analysis
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
DCE-MRI data were analyzed using in-house software (Omni Kinetics; GE Healthcare, China).[6 (link)] For assessing the arterial input function (AIF), 1 ROI was placed manually in the carotid artery ipsilateral to the tumor. The AIF curve was approved by a senior neuro-radiologist to ensure its accuracy. Modified Tofts model was used to calculate the pharmacokinetic parameters, including Ktrans (volume transfer constant between the plasma and the extracellular extravascular space [EES]), Kep (flux rate constant from EES to blood plasma), and Ve (extravascular extracellular volume fraction).
About PubCompare
Our mission is to provide scientists with the largest repository of trustworthy protocols and intelligent analytical tools, thereby offering them extensive information to design robust protocols aimed at minimizing the risk of failures.
We believe that the most crucial aspect is to grant scientists access to a wide range of reliable sources and new useful tools that surpass human capabilities.
However, we trust in allowing scientists to determine how to construct their own protocols based on this information, as they are the experts in their field.
Ready to get started?
Sign up for free.
Registration takes 20 seconds.
Available from any computer
No download required
Revolutionizing how scientists
search and build protocols!