The present disclosure provides systems and methods for predicting a disease state of a subject using ultrasound imaging. The method includes identifying at least one quantitative measurement of a subject using ultrasound imaging, the at least one quantitative measurement included as part of quantitative information of the subject gathered based on the ultrasound imaging, comparing the at least one quantitative measurement to a first predetermined standard to determine a first initial value, the first predetermined standard falling within a first range of quantities, identifying at least one qualitative measurement of the subject using the ultrasound imaging, the at least one qualitative measurement included as part of qualitative information of the subject gathered based on the ultrasound imaging, comparing the at least one qualitative measurement to a second predetermined standard to determine a second initial value, the second predetermined standard falling within a second range of quantities; and correlating at least the quantitative information and the qualitative information using the first initial value and the second initial value to determine a final value that is used in predicting a disease state of the subject.

A computer-assisted medical device is configured and used to endoluminally navigate to a location in the gastrointestinal system and there treat certain body lumen wall areas while avoiding other body lumen wall areas. Embodiments ablate the inner mucosal layer and sub-mucosal nerve plexus of the stomach, duodenum and jejunum to effect treatment of insulin resistance and metabolic disorders, such as Type II diabetes (T2D), polycystic ovarian syndrome (PCOS), non-alcoholic steatohepatitis (NASH), non-alcoholic fatty liver disease (NAFLD), congestive heart failure (CHF) and obstructive sleep apnea (OSA). Various sensors are used to assist a clinical operator to navigate from the mouth through the pyloric sphincter and into and through the duodenum and/or jejunum. Various sensors are used to map and identify portions of the duodenum and/or jejunum. Various lumen wall ablation devices and methods are described. Various post-treatment assessments are described.

An electronic device is provided. The electronic device includes a photoplethysmography (PPG) sensor comprising a light source and a light sensor, an ultrasonic device, at least one processor operatively connected to the PPG sensor and the ultrasonic device, and a memory operatively connected with the at least one processor. The memory may store one or more instructions which, when executed, cause the at least one processor to acquire a PPG signal based on light detected by the light sensor, and control the operation of the ultrasonic device on the basis of an index value indicating the quality of the PPG signal.

An apparatus for measuring a bio-signal includes: a light source configured to emit light; an ultrasonic transducer configured to obtain a photoacoustic signal generated from an object; a photoacoustic coupler disposed in contact with the ultrasonic transducer and configured to direct the light transmitted from the light source to a scanner and to direct the photoacoustic signal generated from the object to the ultrasonic transducer; the scanner configured to reflect the light incident from the photoacoustic coupler to the object, and reflect the photoacoustic signal generated from the object to the photoacoustic coupler; a scanner controller configured to adjust a light incident position on the object by controlling the angle of the scanner; a light detector configured to obtain a light signal by detecting the light scattered or reflected from the object; and a processor configured to obtain bio-information based on the light signal and the photoacoustic signal.

A fractionated photoacoustic flow cytometry (PAFC) system and methods for the in vivo detection of target objects in biofluidic systems (e.g., blood, lymph, urine, or cerebrospinal fluid) of a living organism is described. The fractionated system includes a fractionated laser system, a fractionated optical system, a fractionated acoustic system, and combinations thereof. The fractionated laser system includes at least one laser or laser array for pulsing a target object within the circulatory vessel with fractionated focused laser beams. The fractionated optical system separates one or several laser beams into multiple beams in a spatial configuration on the skin above the circulatory vessel of the living organism. The fractionated acoustic system includes multiple focused ultrasound transducers for receiving photoacoustic signals emitted by the target object in response to the fractionated laser beams.

A photoacoustic remote sensing system (NI-PARS) for imaging a subsurface structure in a sample, has an excitation beam configured to generate ultrasonic signals in the sample at an excitation location; an interrogation beam incident on the sample at the excitation location, a portion of the interrogation beam returning from the sample that is indicative of the generated ultrasonic signals; an optical system that focuses at least one of the excitation beam and the interrogation beam with a focal point that is below the surface of the sample; and a detector that detects the returning portion of the interrogation beam.

A method for quantifying an amount of fat contained in a liver or other tissue of a subject in vivo includes varying the temperature of a target area in a subject, imaging thermal strain of the target area using an ultrasound scanner, and quantifying the amount of fat in the targeted area based on the thermal strain imaging. In some embodiments, the thermal strain imaging is performed using high-resolution, phase-sensitive speckle tracking to differentiate between fat-based tissue and water-based tissue.

Provided herein are cranial implant devices that include at least one acoustic, optical, and/or photoacoustic lens element comprising one or more electromagnetically translucent, electromagnetically transparent, sonolucent, and/or acoustically active materials. The cranial implant devices are structured for subgaleal scalp implantation within, beneath, and/or over at least one cranial opening of a subject and typically includes a substantially anatomically-compatible shape. In addition, the cranial implant devices permit transcranial therapeutic ultrasound, transcranial diagnostic ultrasound, photoacoustic imaging, electromagnetic wave diagnostic imaging, and/or electromagnetic wave therapeutic intervention of intracranial matter of the subject via the acoustic, optical, and/or photoacoustic lens element when the cranial implant device is subgalealy implanted within, beneath, and/or over the cranial opening of the subject. Other aspects are directed to various related systems and methods of obtaining diagnostic information from, and/or administering therapy to, a subject.

A system includes a computing device that receives a query thyroid image, where the query thyroid image is an ultrasound image of a thyroid comprising a thyroid nodule of interest. The computing device processes the query thyroid nodule image using a machine learning model to identify at least one labelled thyroid image from a plurality of labelled thyroid images that is similar to the query thyroid nodule image. The plurality of labelled thyroid images are used as training data to generate the machine learning model. The at least one labelled thyroid image has labels associated therewith and comprises an ultrasound image of a thyroid nodule that has a confirmed diagnosis. The computing device generates an output report based on the labels associated with the at least one labelled thyroid image, where the output report indicates whether the thyroid nodule of interest resembles a malignant thyroid nodule or benign thyroid nodule.

A surgical suturing tracking system is disclosed. The surgical suturing tracking system is configured to detect and guide a suturing needle during a surgical suturing procedure. The surgical suturing track system comprises a control circuit configured to predict a path of a needle suturing stroke after receiving an input from a clinician, detect an embedded tissue structure, and assess proximity of the predicted path and the detected embedded tissue structure.