Methods for detecting abnormalities and degenerative processes in soft tissue using magnetic resonance imaging
View Patent ↗The present invention provides methods to detect degenerative processes and abnormalities in soft tissues at high spatial resolution, high signal-to-noise ratio and short scanning times, based on quantitative tissue properties. These methods might provide a useful tool to detect and assess abnormalities in soft tissues and to monitor disease progression.
1. A computer-implemented method for non-invasively detecting structural abnormalities or diagnosing a demyelination disorder in a test subject's soft tissue, the method comprising
acquiring, via a magnetic resonance imaging system, magnetic resonance images and magnetic resonance imaging (MRI) parameters from said soft tissue;
calculating, by a computer, an MRI M0 image and T1 map data based on acquired data and predicted data;
calculating, by a computer, proton density (PD) with algorithms that calculate PD from the MRI M0 image using regularization by T1 relaxation time thereby achieving removal of instrumental bias in the MRI M0 image;
calculating, by a computer, non-water tissue volume (TV) and volume of interacting protons (VIP) values in said test subject's soft tissue from said magnetic resonance imaging parameters by using algorithms that combine proton density (PD) and T1 map data;
calculating, by a computer, said subject's water pool and non-water pool concentrations from said subject's TV and VIP values;
comparing, by a computer, said subject's water pool and non-water pool concentrations to water pool and non-water pool concentrations from soft tissue TV and VIP values obtained from a healthy control subject;
determining, by a computer, a difference between said test subject's water pool as well as non-water pool concentrations and said healthy control subject's water pool and non-water pool concentrations; and
determining, by a computer, structural abnormalities or a demyelination disorder in said test subject's soft tissue responsive to said difference.
2. The method of claim 1 , wherein said structural abnormalities are changes in tissue volume, myelination or tissue microstructure.
3. The method of claim 1 , wherein the soft tissue is one of the group consisting of cartilage, fatty tissue, muscle tissue, peripheral nerve tissue, and central nervous tissue.
4. The method of claim 3 , wherein said central nervous tissue is brain white matter or brain gray matter.
5. The method of claim 3 , wherein said central nervous tissue comprises ventricles carrying cerebrospinal fluid.
6. The method of claim 1 , wherein said subject may suffer from a neurological disease.
7. The method of claim 1 , wherein said subject may suffer from a neurodegenerative disease.
8. A computer-implemented method of noninvasively assessing brain development in a test subject's brain tissue, the method comprising
acquiring, via a magnetic resonance imaging system, magnetic resonance images and magnetic resonance imaging (MRI) parameters from said test subject's brain tissue;
calculating, by a computer, an MRI M0 image and T1 map data based on acquired data and predicted data;
calculating, by a computer, proton density (PD) with algorithms that calculate PD from the MRI M0 image using regularization by T1 relaxation time thereby achieving removal of instrumental bias in the MRI M0 image;
calculating, by a computer, non-water tissue volume and volume of interacting protons values in said test subject's brain tissue from said magnetic resonance imaging parameters by using algorithms that combine proton density and T1 map data;
calculating, by a computer, said subject's water pool and non-water pool concentrations from said subject's TV and VIP values;
comparing, by a computer, said subject's water pool and non-water pool concentrations to water pool and non-water pool concentrations from brain tissue TV and VIP values obtained from a healthy control subject;
determining, by a computer, a difference between said test subject's water pool as well as non-water pool concentrations and said healthy control subject's water pool and non-water pool concentrations; and
determining, by a computer, a degree of brain development in said test subject's brain tissue responsive to said difference.
9. The method of claim 8 , wherein said brain tissue is brain white tissue or brain gray tissue.
10. The method of claim 8 , wherein said subject is a child between the age of 0-17 years and said control subject is an adult.
11. A computer-implemented method of non-invasively correlating brain microstructure with a cognitive ability in a subject, the method comprising
acquiring, via a magnetic resonance imaging system, magnetic resonance images and magnetic resonance imaging (MRI) parameters from said subject's soft tissue;
calculating, by a computer, an MRI M0 image and T1 map data based on acquired data and predicted data;
calculating, by a computer, proton density (PD) with algorithms that calculate PD from the MRI M0 image using regularization by T1 relaxation time thereby achieving removal of instrumental bias in the MRI M0 image;
calculating, by a computer, non-water tissue volume (TV) and volume of interacting protons (VIP) values in said test subject's soft tissue from said magnetic resonance imaging parameters by using algorithms that combine proton density (PD) and T1 map data;
calculating, by a computer, said subject's water pool and non-water pool concentrations from said subject's TV and VIP values; comparing and correlating, by a computer, said subject's water pool and non-water pool concentrations with said cognitive ability in said subject.
12. The method of claim 11 , wherein the cognitive ability is reading ability.
13. The method of claim 11 , wherein the cognitive ability is writing ability.
14. A computer-implemented method for monitoring response to treatment of a demyelination disease in said subject's soft tissue, the method comprising
acquiring, before the treatment, via a magnetic resonance imaging system, magnetic resonance images and magnetic resonance imaging (MRI) parameters from said soft tissue;
calculating, by a computer, an MRI M0 image and T1 map data based on acquired data and predicted data;
calculating, by a computer, proton density (PD) with algorithms that calculate PD from the MRI M0 image using regularization by T1 relaxation time thereby achieving removal of instrumental bias in the MRI M0 image;
calculating, by a computer, non-water tissue volume (TV) and volume of interacting protons (VIP) values in said test subject's soft tissue from said magnetic resonance imaging parameters by using algorithms that combine proton density (PD) and T1 map data;
calculating, by a computer, said subject's water pool and non-water pool concentrations from said subject's TV and VIP values, said subject's water pool and non-water pool concentrations being indicative of structural abnormalities or demyelination disorders in said subject's soft tissue;
repeating, during the treatment, each of the steps of acquiring and calculating in order to calculate said subject's water pool and non-water pool concentrations;
comparing, by a computer, said subject's water pool and non-water pool concentrations to said subject's previously assessed water pool and non-water pool concentrations;
determining, by a computer, a difference between said subject's water pool and non-water pool concentrations and said subject's previously assessed water pool and non-water pool concentrations; and
establishing, by a computer, a positive treatment response if the difference-determining step indicates an improvement of said structural abnormalities or demyelination disorders in said subject over said subject's previously assessed water pool and non-water pool concentrations.