Methods and system for characterizing ligament properties using elastography are disclosed. An ultrasound system capable of performing shear wave elasticity imaging and/or supersonic shear imaging may retrieve one or more images from a proposed surgical site. The one or more images may be provided to a surgical planning system that identifies one or more properties of ligaments proximate to the surgical site. Musculoskeletal simulations may be performed using the identified properties to preoperatively identify a surgical plan. Preoperative identification of a surgical plan may enable a surgeon to select from more fine-tuning options for a joint replacement than conventional systems.

An information processing apparatus according to an embodiment includes a processing circuit. The processing circuit acquires a measurement field corresponding to a spatial distribution of a predetermined physical quantity in a subject of measurement. The processing circuit calculates an unknown quantity in the subject of measurement based on a first equation between the measurement field and the unknown quantity having spatial dependence, and on the acquired measurement field. The first equation is one that is acquired based on a second equation expressing a dual field divergence of which can be expressed using the measurement field, by using the measurement field and the unknown quantity, and on the Helmholtz decomposition of the dual field.

Magnetic resonance elastography (“MRE”), or other imaging-based elastography techniques, generate estimates of the mechanical properties, such as stiffness and damping ratio, of tissues in a subject. A machine learning approach, such as an artificial neural network, is implemented to perform an inversion of displacement data in order to generate the estimates of the mechanical properties.

Described here are systems and methods for a robust magnetic resonance elastography (“MRE”) imaging platform for rapid dynamic 3D MRE imaging. The imaging platform includes an MRE pulse sequence and advanced image reconstruction framework that work synergistically in order to greatly expand the domains where MRE can be deployed successfully.

Aspects of the disclosure are directed to a phantom apparatus, such as may be used in MRI imaging. As may be implemented with a particular embodiment, such an apparatus may include a first tissue-mimicking region having a first tissue property, and at least one additional tissue-mimicking region, including a second tissue-mimicking region having a second tissue property that is different than the first tissue property. The second tissue-mimicking region is stacked on the first tissue-mimicking region.

The present disclosure generally relate to a method and system for performing three-dimensional, 3D, magnetic resonance elastography, MRE. In particular, the present disclosure relates to a method and system for imaging an area of a patient using a multi-slice gradient echo, GRE, imaging sequence. Advantageously, the present techniques enable the four scans that are typically required to be performed during MRE, and during four breath-holds, to be combined into a single measurement that can be performed during a single breath-hold.

Systems and methods are described for inducing tissue vibration for magnetic resonance elastography is described. The system includes a hydraulic drive component that is mechanically linked to a pneumatic drive component. The pneumatic drive component is pneumatically linked to a passive pneumatic actuator component that is positionable on a patient proximate to a target tissue. Alternating linear movement of an actuator piston within the passive actuator component induces vibration of the target tissue. The frequency of the alternating linear movement of the actuator piston within the passive pneumatic actuator component is controlled by adjusting how fluid is pumped in the hydraulic drive component.

Techniques for co-imaging tissue stiffness and blood flow using a single MRI scan are disclosed. The methods use a combined gradient waveform that provides adequate sensitivity for concurrent encodings of flow and tissue stiffness. During a scan, the application of the combined gradient waveform, in the presence of an applied oscillatory motion, simultaneously encodes both flow and stiffness information into the phase of the resulting MRI image. To separate the flow information from the tissue displacement caused by the oscillatory motion, a Fourier transform applied along the direction of applied oscillatory motion. After the transformation, baseband information (flow velocity) may be separated from modulated information (tissue displacement). The separated data may be used to create a velocity map and a displacement map, which can then be converted to a stiffness map.

A system for determining parameters of porous media or material, which in an embodiment is biological tissue, includes an actuator and a displacement monitor. The actuator is adapted to apply a displacement to tissue at a particular frequency selected from a range of frequencies, and the force monitor adapted to monitor a mechanical response of tissue. The system also has a processor coupled to drive the actuator and to read the mechanical response, the processor coupled to execute from memory a poroelastic model of mechanical properties of the material, and a convergence procedure for determining parameters for the poroelastic model such that the model predicts mechanical response of the tissue to within limits.

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.