Bayer Healthcare LLC

Medrad, Inc.

Bayer Medical Care Inc.

Ge Precision Healthcare LLC

The General Hospital Corporation

The Brigham and Women's Hospital, Inc.

Partners Healthcare System, Inc.

John Francis Kalafut

David M Reilly

Arthur E Uber, Iii

Corey A Kemper

David A Mishler

Alan D Hirschman

David M Griffiths

Frederick W Trombley, Iii

Dennis P Hack

Neil Tenenholtz

Edward J Rhinehart

Mark Trocki

Larry McCutchan

Marc A Mabie

Bernardo Canedo Bizzo

Stuart Pomerantz

Sean Doyle

Mark Heinz Michalski

Keith Dreyer

Ralph H Schriver

Steven J Remis

Douglas Descalzi

Scott Griffith

Michael Lev

Richard Dewit

Julie Gulick

Christopher P Bridge

Robert S Schwartz

Kevin P Cowan

Michael A Spohn

Robert A Van Tassel

John A Haury

James Albert Dedig

Gerald W Callan

Thomas P Joyce

Eugene A Gelblum

Herbert M Grubic

Jerry A Stokes

John A Brosovich

Michael J Yanniello

Anthony S McCoppin

Andreas Maihoefer

Ramon Gilberto Gonzalez

Sridhar R Balasubramanian

Markus Daniel Herrmann

Erin Cosgrove

Ruediger Lawaczek

L George Siddoway

Lisa M Coates

Aaron Hughes

Romane Gauriau

Peter Twichell

David M Rellly

Guy Ezekiel

Stefano Pedemonte

James Hillis

Charles J Lu

Frederick P Windham

Mark Michalski

Arthur E Iii Uber

Frederick W Iii Trombley

Bronwyn Uber

Paul Levin

Techniques are described that facilitate integrating artificial intelligence (AI) informatics in healthcare systems using a distributed learning platform. In one embodiment, a computer-implemented is provided that comprises interfacing, by a system operatively coupled to a processor, with a medical imaging application that provides for viewing medical image data. The method further comprises, facilitating, by the system, generation of structured diagnostic data according to a defined ontology in association with usage of the imaging application to perform a clinical evaluation of the medical image data. The method further comprises providing, by the system, the structured diagnostic data to one or more machine learning systems, wherein based on the providing, the one or more machine learning systems employ the structured diagnostic data as training data to generate or train one or more diagnostic models configured to provide artificial intelligence-based diagnostic evaluations of new medical image data.

Facilitating artificial intelligence integration into systems using a distributed learning platform

Systems and techniques that facilitate automated localization of large vessel occlusions are provided. In various embodiments, an input component can receive computed tomography angiogram (CTA) images of a patient's brain. In various embodiments, a localization component can determine, via a machine learning algorithm, a location of a large vessel occlusion (LVO) in the patient's brain based on the CTA images. In various instances, the location of the LVO can comprise a laterality and an occlusion site. In various aspects, the laterality can indicate a right side or a left side of the patient's brain, and the occlusion site can indicate an internal carotid artery (ICA), an M1 segment of a middle cerebral artery (MCA) or an M2 segment of an MCA. In various cases, a visualization component can generate and display to a user a three-dimensional maximum intensity projection (MIP) reconstruction of the patient's brain based on the CTA images to facilitate visual verification of the LVO by the user.

CTA large vessel occlusion model

Systems and techniques for generating and/or employing a medical imaging stroke model are presented. In one example, a system employs a convolutional neural network to generate output data regarding a brain anatomical region based on diffusion-weighted imaging (DWI) data associated with the brain anatomical region and apparent diffusion coefficient (ADC) data associated with the brain anatomical region. The system also detects presence or absence of a medical stroke condition associated with the brain anatomical region based on the output data.

Medical imaging stroke model

Systems and techniques for generating and/or employing a computed tomography (CT) medical imaging stroke model are presented. In one example, a system employs a convolutional neural network to generate learned medical imaging stroke data regarding a brain anatomical region based on CT data associated with the brain anatomical region and diffusion-weighted imaging (DWI) data associated with one or more segmentation masks for the brain anatomical region. The system also detects presence or absence of a medical stroke condition in a CT image based on the learned medical imaging stroke data.

Computed tomography medical imaging stroke model

A system for patient imaging is provided. The system includes an imaging system and a parameter generator to determine parameters of at least a first phase of an injection procedure. The imaging system includes a scanner that has at least one x-ray tube. The parameter generator is programmed to determine at least one of the parameters on the basis of a voltage to be applied to the at least one x-ray tube during an imaging procedure. A method of controlling an injector system is also provided, and the method includes determining injection parameters, at least one of which is determined on the basis of a voltage to be applied to an x-ray tube during the imaging procedure, as well as controlling the injector system at least in part on the basis of the determined injection parameters.

Systems and methods for determination of pharmaceutical fluid injection protocols based on x-ray tube voltage

A system has a parameter generation system that includes a processor, an input system and a memory system in which an algorithm is stored. Upon execution by the processor, the algorithm is used to determine parameters of at least one phase of an injection procedure to be performed on a patient based at least in part upon the type of injection procedure selected via the input system. The volume of a pharmaceutical to be delivered to the patient during the injection procedure is determined at least in part on the basis of the concentration of a contrast enhancing agent contained in the pharmaceutical and at least in part on the basis of a function that depends upon and varies with a parameter of the patient such as the weight, the body mass index, the body surface area or the cardiac output of the patient.

Patient-based parameter generation systems for medical injection procedures

A system for enabling delivery of fluid in an injection procedure to be performed on a patient in connection with a diagnostic imaging procedure is disclosed. The system includes a controller operably associated with at least one pressurizing mechanism though which at least one of a first and a second fluid contained within at least one fluid container is injectable into the patient. The first fluid includes a contrast enhancing agent while the second fluid does not. The controller includes a programming system for programming an injection protocol having a plurality of phases to effect enhancement of at least one region of interest of the patient over a scan duration of the diagnostic imaging procedure. The programming system includes an algorithm that enables computation of a ratio of the first and second fluids based on at least a peak enhancement that occurs in at least one region of interest.

Devices, systems and methods for determining parameters of one or more phases of an injection procedure

Provided is a method of collecting and managing information relating to medical diagnostic procedures which includes collecting objective information about a plurality of procedures and subjective information about the results of those procedures. The objective information provides information about the parameters of the procedure and the patient who underwent the procedure while the subjective information includes an assessment of the quality of the results of the procedure. This information can be stored in a database. The database can be accessed and the information therein used in connection with understanding the results of past procedures and planning for future procedures.

Methods and techniques for collecting, reporting and managing ionizing radiation dose

An integrated radiopharmaceutical patient treatment system is disclosed including a patient support platform with an associated patient stimulus apparatus, an imager proximate the patient support platform, a radiopharmaceutical fluid delivery system for infusing a radiopharmaceutical fluid into a patient, a patient monitor to be associated with a patient, and an integrated system controller operably associated with the patient stimulus apparatus, imager, radiopharmaceutical fluid delivery system, and patient monitor to control and coordinate their operations. Within the patient treatment system the radiopharmaceutical fluid delivery system may be included comprising a radionuclide supply module, a radiopharmaceutical processing module, a quality control module, a patient injection module, and a controller. A hazardous fluid handling system including a docking station and a hazardous fluid transport device adapted to detachably dock with the docking station is further disclosed.

Methods and systems for integrated radiopharmaceutical generation, preparation, transportation and administration

A system includes a parameter generation system to determine at least one parameter for an injection procedure (for example, a parameter of an injection protocol or an imaging system parameter), the parameter generator system includes a physiologically based pharmacokinetic model to model propagation of a contrast medium injected into a patient including at least one of a non-linear saturation term in a peripheral venous compartment, at least one configurable transport delay term through at least one compartment, or an adaptation to model volumetric flow rate of blood and an effect thereof on the propagation of contrast medium after injection of contrast medium ceases. The physiologically based pharmacokinetic model can, for example, be discretizable.

Modeling of pharmaceutical propagation and parameter generation for injection protocols

A system and method of managing workflow for a variety of injection procedures preferably includes a display that provides a graphical representation of the steps required to initiate an injection procedure. The system can, for example, set forth a suggested order or sequence for the steps to be completed, and display the suggested sequence of steps graphically. Various steps may optionally require completion of ancillary operations as a requirement for completion of the selected step.

Systems and methods for managing workflow for injection procedures

Systems and methods for delivering a medical fluid are disclosed. The system includes a fluid flow path, a fluid administration device adapted to deliver the medical fluid through the fluid flow path, and a controller in communication with the fluid administration device. The method includes using the system to determine a desired flow rate of the medical fluid at a distal end of the fluid flow path based upon at least a desired flow profile of the medical fluid at the distal end. The method further includes initiating a fluid delivery operation by delivering the medical fluid through the fluid flow path according to fluid delivery parameters provided to the fluid administration device by the controller. Information about the fluid delivery operation may be received at the controller which executes a control function to adjust the fluid delivery parameters based on the received information.

Apparatus and methods for delivery of fluid injection boluses to patients and handling harmful fluids

Growing community of inventors

Pittsburgh, PA, United States of America

John Francis Kalafut