A method for magnetic resonance imaging (MRI)-guided interstitial thermal therapy includes receiving MRI data for tissue of a patient, generating an apparent diffusion coefficient (ADC) map from the MRI data, identifying a target site for thermal therapy based on the ADC map, wherein the target site is a tumor identified by low ADC values on the ADC map, planning the thermal therapy for the target site including identifying a plurality of individual localized areas to be ablated during delivery of the thermal therapy, the plurality of individual localized areas having the lowest ADC values among the low ADC values within the target site, activating a laser to deliver the thermal therapy to the plurality of individual localized areas using a laser fiber, and monitoring progress of the thermal therapy using MR thermometry.

The present disclosure provides a system for MRI. The system may obtain a plurality of echo signals relating to a subject that are excited by an MRI pulse sequence applied to the subject. The system may perform a quantitative measurement on the subject based on the plurality of echo signals. The MRI pulse sequence may include a CEST module configured to selectively excite exchangeable protons or exchangeable molecules in the subject, an RF excitation pulse applied after the CEST module configured to excite a plurality of gradient echoes, and one or more refocusing pulses applied after the RF excitation pulse. Each of the refocusing pulses may be configured to excite one or more spin echoes. The one or more spin echoes excited by at least one of the one or more refocusing pulses may include a symmetric spin echo and one or more asymmetric spin echoes.

A shimming system for magnetic resonance imaging is provided, which includes: a multi-channel local shim coil unit configured to be installed on an inspection table of a magnetic resonance imaging system, where the multi-channel local shim coil unit includes a local multi-channel shim coil and a radio frequency receiving coil for receiving magnetic resonance signals, and the radio frequency receiving coil is placed inside the local multi-channel shim coil and separated by a distance from the local multi-channel shim coil; a computer control system configured to install and set software controlled by a DC power and calculate field maps and calculate optimization processes; a DC power system communicatively connected to the computer control system to control a value of current of each channel; and a housing having a semi-cylindrical configuration, where the local multi-channel shim coil is only distributed on a semi-cylindrical surface of the semi-cylindrical configuration of the housing.

By producing the proper wave interference using superimposed waves that overlap with the proper time-phase relationship (called “Time-Correlated Standing-wave Interference”), wave energy is amplified (by “Coherent Intensity Amplification”) and teleported to precise locations. For instance, in one application, energy is teleported to one or more areas within a living body for such therapeutic applications as destroying cancer cells or plaques within arteries. A system implementing this technique creates amplified constructive interference at one or more selected disease locations, while producing destructive interference at surrounding locations. In this application example, the technique allows energy to be “teleported” to tumor cells, plaques, or other diseased cells, for instance, to destroy them, while surrounding healthy cells receive virtually no energy, obviating collateral damage from the treatment. The same method can be used to diagnose disease by detecting energy teleported to different locations.

During the delivery of thermal therapy, the measured temperature at each pixel in a cross-sectional temperature slice of a multi-pixel thermal image is compared to a maximum temperature limit. When the measured temperature of a pixel is higher than the maximum temperature limit for a predetermined number of consecutive cross-sectional temperature slices, the pixel is masked if the absolute value of the average difference between the measured temperature at the pixel and the measured temperatures at the pixel's neighbors is greater than a maximum temperature variation. The measured temperature of the masked pixel is ignored in subsequent cross-sectional temperature slices until the delivery of thermal therapy is complete.

Provided are a system and a method for determining the temperature of a body by imaging a hydrogen proton-rich material positioned within the body using nuclear magnetic resonance imaging. A method to increase changes in the MRI signal strength as a function of temperature, thus improving temperature sensitivity, is also provided. The system and method employ polymers having mechanical stability and magnetic image brightness at low temperatures of between 0° C. and −65° C. or high temperatures of between +37° C. and +80° C.

Applications related to non-invasive magnetic resonance guided focused ultrasound (MRgFUS) in a patient's vasculature are described. For example, the applications can include an ablation procedure, an occlusion procedure, a cauterization procedure, and the like. Accordingly, one aspect of the present disclosure is directed to a method for performing an MRgFUS application that includes selecting a target area within a patient's vasculature, configuring multifocal acoustic waves, and applying the multifocal acoustic waves to the target area to heat sequential locations in the target area simultaneously to facilitate the MRgFUS application.

During operation, a system may apply an external magnetic field and an RF pulse sequence to a sample. Then, the system may measure at least a component of a magnetization associated with the sample, such as MR signals of one or more types of nuclei in the sample. Moreover, the system may calculate at least a predicted component of the magnetization for voxels associated with the sample based on the measured component of the magnetization, a forward model, the external magnetic field and the RF pulse sequence. Next, the system may solve an inverse problem by iteratively modifying the parameters associated with the voxels in the forward model until a difference between the predicted component of the magnetization and the measured component of the magnetization is less than a predefined value. Note that the calculations may be performed concurrently with the measurements and may not involve performing a Fourier transform.

During operation, a system may apply an external magnetic field and an RF pulse sequence to a sample. Then, the system may measure at least a component of a magnetization associated with the sample, such as MR signals of one or more types of nuclei in the sample. Moreover, the system may calculate at least a predicted component of the magnetization for voxels associated with the sample based on the measured component of the magnetization, a forward model, the external magnetic field and the RF pulse sequence. Next, the system may solve an inverse problem by, iteratively modifying the parameters associated with the voxels in the forward model until a difference between the predicted component of the magnetization and the measured component of the magnetization is less than a predefined value. Note that the calculations may be performed concurrently with the measurements and may not involve performing a Fourier transform.

A method for temperature quantification using magnetic resonance fingerprinting (MRF) includes acquiring MRF data from a region of interest in a subject using an MRF pulse sequence with smoothly varying RF phase for MR resonant frequencies that is played out continuously. For each of a plurality of time intervals during acquisition of the MRF data the method further includes comparing a set of the MRF data associated with the time interval to an MRF dictionary to determine at least one quantitative parameter of the acquired MRF data, determining a temperature change based on the at least one quantitative parameter and generating a quantitative map of the temperature change in the region of interest. The region of interest can include aqueous and adipose tissue.