AI-based platform for medical images analysis and processing · Intellogic, LLC | 2020 3 3...

AI-based platform for medical images analysis and processing

Intellogic, LLC | 2020


For healthcare providers and radiologists

• Medical errors probability reduction

• Workload of radiologists reduction

• Possibility of using the product for scientific work and additional training

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Product Value

For healthcare authorities

• Implementation of national healthcare programmes

• Mortality decrease, including a one-year mortality of patients with malignant neoplasms

• Healthcare equipment usage improvement


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Advantages of the Platform

• Cloud-based multimodal DICOM viewer

• Centralized cloud storage of depersonalized medical studies

• Integration with diagnostic devices in accordance to the DICOM standard

• Integration with HIS in accordance to HL7/FHIR

• Medical studies analysis for pathologies using AI technologies

• Visualization of detected pathologies in the medical image

• Flexible configuration of studies flow routing for the organization of collaboration between radiologist and AI (Botkin Workflow)

• Tools for the images mark-up

• Formation of protocols according to the DICOM-SR standard


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Key Elements of the Platform

Botkin Gateway

Own-developed Gateway for integration with Central Archive of Medical Images and PACS

It is deployed in medical institution network. With Botkin Gateway it is possible to configure the interaction between the PACS server of medical institution and the Cloud Platform for medical image analysis. The Gateway has following functions:

• Depersonification of medical images based on selected DICOM tags

• Filtering PACS server studies by tags content for processing transmission

• PACS server schedule for information extraction

• Integration with any number of PACS servers

Botkin Workflow Engine

Technology for studies flow received from customers via Botkin Gateway management

• Research processing scenarios setting, depending on tasks given, content of DICOM-tags, types of studies or pathologies, gateway settings

• Determination of processing status for each step of research scenario

• Logging of all research processing stages

• Visual representation of processing statuses to increase the work efficiency with a large flow of studies

DICOM Viewer Botkin Oncore

Professional DICOM Viewer with AI functions

• Web-based access from anywhere

• Visualization of pathologies detected by AI

• Professional DICOM Viewer Tools

• Automatic prioritization of studies

• Ability to compare multiple studies in one window

• Studies mark-up tools

• Tools for collaborative work


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Key Elements of the Technology

Botkin Hybrid Intelligence

Medical imaging technology combining the artificial intelligence usage tools and radiologists’ expertise

• Adaptable interaction processes for both artificial intelligence tools and radiologists (Botkin Workflows)

• Radiologists’ validation process analysis for artificial intelligence performance results assessment

• Option for cross-validation of the results by a group of radiologists

Botkin Edge

Hardware and software complex for medical images analysis

Key features:

• Possibility of integration with the clinic

• Connection to PACS or directly to a data source (CT, PET / CT, MRI, X-ray, Fluorography, Mammography)

• Flexible configuration (depending on image and diagnostics types)

Botkin Learning

Own technology that significantly improves the efficiency of using artificial intelligence technologies for analyzing images with various pathologies

Consists of:

• Automated machine learning pipelines, which operate when new data is received. They also produce, validate, and integrate updated models

• A meta algorithm for model architectures testing to determine the best model options for a particular dataset

• Subsystem for monitoring models’ performance


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Concept of Use


Task: Automatic revision of diagnostic images from PACS server of a healthcare provider or Central Archive of Medical Images

Goal: Reduced risk of skipping pathologies, especially oncological diseases in the early stages

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Platform Usage Example

Screening (revision) of diagnostic images


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Image Revision Relevance

Example: Lung cancer

54% visible on a previous CT

Cancer was visible on a previos CT,but it was missed by a radiologist

23% Diagnostics failure

A neoplasm was found on a previous CT but was not classified as malignant

23% Impossible to diagnose

Cancer wasn’t visible on a previous CT

In more than70% of cases

Radiologists miss lung cancer on Chest CT studies *


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Pilot Projects Results

Pilot projects conversion: A Commercial Agreement for the analysis of chest CT scans from all government medical organizations of the Yamalo-Nenets Autonomous District was signed

Regional pilot projects:

• Murmansk Oblast

• Novgorod Oblast

• Tula Oblast

• Yamalo-Nenets Autonomous District

Results:

• More that 1500 of chest CT scans were revised via Botkin.AI

• At least 15 cases which were not detected by radiologists before were identified.


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Opportunities for images revision

Example: Lung cancer diagnostics

3 000 000Chest CT scans per year are held in Russia


Besides chest organs X-Ray images further pathologies are also recognised:

• Atelectasis

• Cardiomegaly

• Infiltrative changes (pneumonia)

• Pneumothorax

• Pleural effusion

• Emphysema

• Pulmonary edema

Extended version of the product is to be launched in the 1-st quarter of 2020:

• Different types of foci recognition (solid, sub-solid, calcinates)

• Non-oncological lung pathologies’ recognition

• Integration with Lung-RADS classification and classification/recognition of various stages of cancer risk

• Nodule matching for images of the same person

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Products and the pipeline

The main version of the product is ready

Detection and indication of lung tumors

CT

The product is ready

Chest organs X-Ray recognition

Digital X-Ray

TBA: 2-nd quater

of 2020

Breast cancer diagnostics

Mammography

TBA: 2-nd quater

of 2020

Tuberculosis diagnostics

Fluorography


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Botkin.AI platform integration with HIS


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Botkin.AI for Teleradiology

• Be a customer of image description services

• Provide teleradiology services to other clinics

• Increase in radiologists’ effectiveness

• 100% quality control of diagnostic images description

A new model for organizing a teleradiology service using artificial intelligence technologies

Any medical institution can simultaneously:

Artificial intelligence technologies are used for:


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Botkin.HAI: Hybrid Artificial Intelligence

1. Data is analysed by AI only: 2. AI analysis result is further validated by a radiologist:

3. AI analysis result is further validated by a radiologist and processed by AI:

4. HAI Workflow is used as a teleradiological system by various radiologists:

HAI Workflow usage examples

Botkin.HAI — being a flexible and up-to-date system — can be implemented in various ways. These are just some examples of how it can be used:


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Analysed modalities

Computer Tomography

• Determination of the nodules’ dynamics

• Determination of non-oncological pathologies, including: emphysema, consolidation, fibrosis, cysts, bronchiectasis, ground glass

• Detection and indication of tumors

• Triage of studies

• Automatic classification studies according to Lung-RADS

• Volume and density measurement of nodules


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Analysed modalities

Digital X-Ray and Fluorography Mammography

• Detection and indication of tumors

• The area and density of nodules measurement


• Automatic classification of studies according to BI-RADS

• Detection and indication of radiological syndromes, including total/partial opacification pattern, diffuse lucency, nodular pattern, focal/diffuse pulmonary dissemination



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Comparison with the best analogues

Botkin.AI performs better than the best analogues in the world

International Conferences participation and publications:


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Intellectual Property

1. Patent: Method and System for supporting medical decision making using mathematical models of presenting patients Status: Russian registration of the patent is approved. The procedure of receiving international patents is in progress

2. Patent: Method of patient mathematical models assembling via Artificial Intelligence technologiesStatus: Application for Russian patent is being processed

3. Patent: Automatic analysis method for medical images of patient’s organsStatus: Application for Russian patent is being processed

Status: The trademark is registered in Russian Federation and abroad

Botkin.AI Trademark

Patents


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Scientific Advisory Board

MD, Professor, President of the Russian Society of Radiology, ex-President of the European society of cardiovascular radiology, ex-President of the European Congress of Radiology, Head of radiation diagnostics course, the faculty of Fundamental Medicine of Lomonosov Moscow State University

Valentin E. SINITSYN

Head of the Scientific Advisory Board at Botkin.AI


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Investors

RBV Capital Digital Evolution Ventures (Orbita Capital)

A venture capital fund established in 2018 with participation of ROSATOM investing into Russian and foreign technological startups in following fields: artificial intelligence and other digital solutions in the industry, healthcare and service applications, renewable and smart energy industry, 3D Printing, smart, eco and energy-effective cities development systems

Primer Capital ExpoCapital

A direct investment fund that focuses on investing into businesses holding a high potential of a value growth on Russian and global markets

Private biotechnological early-stage venture capital fund that has a portfolio of 11 projects in Russia, Europe and the USA. Partner of Bayer CoLaborator® and AstraZeneca Accelerator

RBV Capital is a specialised life sciences venture capital fund established in 2014 with participation of R-Farm, JSC and RBK, JSC. RBV Capital invests into innovative biomedical projects globally. The Company has several successful cases in global market.


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Contacts

121205 Moscow, Skolkovo, Bolshoy blvd., 42 / 1

+7 495 649-13-09

https://botkin.ai/en/ [email protected]

https://botkin.ai/en/


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AI-based platform for medical images analysis and processing · Intellogic, LLC | 2020 3 3...

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