DCE-MRI and MRI
MRI is the modality of choice for evaluating both structural and functional information, and musculoskeletal imaging is one of the most important applications. MRI is widely used in clinical trials setting, clinical practice and clinical research. In particular, dynamic contrast enhanced (DCE)-MRI is increasingly being used to model the concentration of contrast agent as it moves from the blood vasculature to the extra cellular interstitial space.
DCE-MRI determines the actual pharmaco-dynamics of soft tissue inflammation in rheumatology and of tumour contrast enhancement, specifically the degree and rate of early enhancement. Recent research has indicated that the dynamics of the enhancing synovium in Rheumatoid Arthritis patients change significantly following administration of disease modifying therapies.
Approaches for analysis of DCE-MRI data assume that
- relationship between the contrast agent concentration and signal change are known and well defined;
- all intensity changes at each voxel
- can be attributed to the contrast leakage
- each voxel would represent the same tissue type
Voxel is a 3-dimensional pixel or an element of volume. If a pixel is placed at the same (X.Y) position on several dynamic frames with a series (Z coordinate will vary from 1 to N, where N is the number of frames in the entire dynamic acquisition)
However, intensity change in a DCE-MRI dataset will depend on image acquisition parameters, dose of the contrast agent, and scanning equipment. Problems with the MR coils, pulse sequence, magnetic field inhomogeneity and patient motion during the imaging can introduce artefactual enhancement, which might lead to over-estimating the degree of inflammation.
At the end of an examination, a radiologist receives a dataset of up to 100s images, which can be corrupted by noise and patient motion artefacts. A reader semi-manually or manually views the images, in order to locate the tissues of interest and then makes a decision about the patient’s condition by viewing the images one by one.
Read More...Assessment and comparison of images acquired in follow-up examinations is performed in a similar manner.
- Such evaluation is obviously subjective to the reader opinion and the results are not easy to reproduce.
- There is no technique for comparison of the data acquired from the same patient on two different scanners.
- The quality of the data can render the entire analysis invalid.
Therefore, several problems are being dealt with:
- Firstly, there is a need for efficient pre-processing techniques that can compensate for patient motion, locate tissue of interest, and thereby contribute to data fidelity.
- Secondly, efficient quantitative techniques that allow assessment and interpretation of the results of examinations are required.
- There is a need for easy way to report and reproduce the results.
- Standard motion correction techniques fail to perform under assumptions imposed by the dynamic data acquisition settings. Quantitative analysis often performs a threshold-dependent method, which cannot be trusted when the intensity change varies due to the scanner settings or in-homogeneity of the field.
Dynamika is the standard for quantitative analysis of Dynamic Contrast Enhanced data in cross sectional and longitudinal studies. This award winning software improves the quality and efficiency of data analysis, speeding-up interpretation and offering computer-guided decision support.