From Qualitative to Quantitative Radiological Reports...

Quantitative Imaging Biomarkers in Medicine

www.quibim.com

Ana Jiménez PastorImage Analysis Scientist

anajimenez@quibim.com

From Qualitative to Quantitative Radiological

Reports through AI and Automated Analysis

ANALOGIC MEDICAL IMAGE DIGITAL MEDICAL IMAGE

Thanks to digitalization, medical imaging is one of the medical sectors which has

experienced a huge technological revolution in the last 50 years

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Moderate Lung Emphysema 20% Lung Emphysema

DISEASE

vs.

HUMAN EYE

1896. William Morton

First Radiological Report: RX Abdomen

“… there is no stone of appreciable size in the kidney…”

2018. Radreport. RSNA

Modern Radiological Report: CT kidney stones

“… adenopathy is not observed…”

“There are not observed alterations”

The need: TO MEASURE

Steatohepatitis Alzheimer Articular degeneration Vertebral fractures Prostate cancer

Chondral degeneration Rectal cancer Emphysema Multiple SclerosisOsteoporosis

“When you can measure what you are

speaking about, and express it in

numbers, you know something about it”

Lord Kelvin

What is an Imaging Biomarker?

It is a parameter obtained objectively from medical images which represents and quantifies a tissue property (structural,

functional or biological) extracted after applying computational models and artificial intelligence,

to measure is to know

Imaging Biomarkers Development

Value

Proof of concept Proof of mechanism Image acquisition Image processing Image analysis

Measurements Proof of principleProof of efficacy

and effectivenessStructured report

Idea

Martí-Bonmati ́ L, Alberich-Bayarri A, et al. Imaging biomarkers, quantitative imaging, and bioengineering. Radiologia. 2012;54:269-278.

ONCOLOGYSolid tumors, hematology

Diffusion (IVIM, DKI),

Pharmacokinetics, bone

narrow infiltration,

multiparametric analysis

MSKOsteoporosis, arthrosis

Trabecular morphology,

fractal irregularity,

anisotropy, mechanical

resistence and elasticity

LUNGCOPD, RX

Classification, volumes,

emphysema, low functional

densities

NEUROAlzheimer, ALS, ME, ictus

Brain volumetry, cortical

thickness, White matter

lesions, tractography

LIVERSteatohepatitis, fibrosis,

hemochromatosis

Fat fraction, iron

concentration, fibrosis

Why do we need HPC?

HIGH DIMENSIONALITY!

2688x2672

512x512x1000

192x192x1300

COMPLEXITY IN AI ARCHITECTURES!

HIGH COMPUTATIONAL COST!

We need HPC integrated in

healthcare and medical imaging!

vs.

Which HPC installation does fit the best in the

healthcare sector?

AI IN MEDICAL IMAGING

LIVER FAT & IRON QUANTIFICATION

Nowadays, liver biopsy is the gold standard:

• Invasive

• Heterogeneous distribution – Biased sample

• Intra- and inter- observer variability

• Difficulties on patients follow-up

SOLUTION: Virtual biopsies through MRI

• Requires the delineation of the liver.

• Time consuming, exhausting and not

rewarding task.

• Requires radiologists’ expert

knowledge, therefore it is very

expensive.

LIVER FAT & IRON QUANTIFICATION

SOLUTION: Automatic liver segmentation using a CNN

SEGMENTATION. LIVER

AI VS HUMAN SEGMENTATION

AI SEGMENTATION HUMAN SEGMENTATION

DETECTION. VERTEBRAE

• Vertebra localization and identification are essential for

diagnosis, surgical planning and patients follow-up on spine

pathologies.

• Nowadays, this identification is done manually, hindering

radiologists’ workflow.

• SOLUTION: Automatic vertebrae detection through AI.

DETECTION. VERTEBRAE

DETECTION IDENTIFICATION

DETECTION. VERTEBRAE

DETECTION. PNEUMONIA

• Pneumonia accounts for over 15% of all deaths of children

under 5 years old internationally.

• The diagnosis on chest x-ray is complicated because of the

presence of other conditions in the lungs.

• SOLUTION: Pneumonia detection to improve efficiency and

reach of diagnostic services.

DETECTION. PNEUMONIA

Ground truth

AI Predictions

CLASSIFICATION. CHEST X-RAY

• X-ray is the most performed examination.

• Radiology departments have limitations in reporting all x-rays

generated due to the limited resources available.

• SOLUTION: Automatic chest x-ray classification to prioritize

those with abnormal findings.

CLASSIFICATION. CHEST X-RAY

Atelectasis

Cardiomegaly

Effusion

Infiltration

Mass

Nodule

Pneumonia

Pneumothorax

Consolidation

Edema

Emphysema

Fibrosis

Pleural

Thickening

Hernia

Abnormal Probability:

0.87

Weigthing

Fully Connected

Network

CNN Classifiers

RADIOMICS

• Multivariate analysis of large datasets of imaging

biomarkers with the goal of finding diagnostic, prognostic

or therapeutic relations.

• It is based on the analysis of large populations

characteristics to extract correlations that can be applied

to an individual patient.

RADIOMICS

Powerful GPUs are a must to develop

AI because of their high parallel

computing requirements

OUR

TEAM

Raúl Yébana

Huertas

Image Analysis

Technician

Andrew Tasker

Business

Development

Human Resources

Management

Inma López

Image Analysis

Scientist

Fabio García

Castro

CTO

Rafael

Hernández

Navarro

Alejandro Mañas

García

Full Stack

Senior Developer

Image Analysis

Scientist

Eduardo

Camacho

Irene Mayorga

Ruiz

Clinical Trials

Coordinator

Ana Jiménez

Pastor

Image Analysis

Scientist

Image Analysis

Scientist

Ismael González

Belén Fos

Guarinos

Quality Engineer

ManagerCOO

Encarna

Sánchez

Bernabé

Marketing

Manager

Katherine

WilischRamírez

Data Scientist

Rafael López

Inma Segarra

Business

DevelopmentFounder & CEO

Ángel

Alberich-Bayarri

Chief Strategy

Officer

Kabir Mahajan

Team Coordinator

Paula Moreno

AI

Quantitative Imaging Biomarkers in Medicine

www.quibim.com

Ana Jiménez PastorImage Analysis Scientist

anajimenez@quibim.com

From Qualitative to Quantitative Radiological

Reports through AI and Automated Analysis