C A R L O S P É R E Z C A S T I L L O

Imaging Biomarkers Automated Structured Assembly Pipeline

(IB-ASAP)

www.cuantificacionquironvalencia.es www.quiron.es

Digital Radiology

• The workspace of radiologists has changed dramatically with the development and implementation of digital imaging

Radiologist’s Workspace

Multidisciplinary collaboration New workflows

New challenges…

Technology

Radiologists

Engineers

Objective characteristics extracted from medical images

Indicators and measures of normal biological processes, diseases or responses to therapeutic interventions

Obtained before a lesion or biological process becomes evident in the radiological observation, by analyzing properties and multivariate combination of medical images and data

Non invasive

Imaging Biomarkers

Purpose: Workflow improvement

Brain: Morphometry

Sequence optimization for brain morphometry

Brain: Functional MRI

Schizophrenia Auditory

hallucinations

Brain injury Patients with

mobility restriction

Other diseases Tumours, language

disorders

Brain: Neuro-tractography

o Diffusion Tensor Imaging o Neuronal Pathway o Surgical Planning

Prostate: Diffusion

Healthy tissue Pathological tissue

microscopic mobility of tissue water

Prostate: Perfusion

Overlay a vascular

permeability parametric map on anatomical

images

Prostate: Spectroscopy

Biochemical and metabolic profile of the gland. Indicators of tumor presence :

-increased choline - regional reduction in the levels of citrate

Data Pipeline

Workflow Description

DICOM images and

data reception

Organized data storage

and classification

Data preparation

Notifications Post-

processing Algorithms Execution

Post-Processing

Results Management

Post-Processing

Results Management

IB-ASAP

The developments have provided an innovative service that follows an organized process, as a proper technological support to leverage the usability and ease the development and implementation of quantitative imaging

In addition, the software is fully automated, vendor independent and compatible with DICOM standards

cvREMOD (CENIT-E)

Quantify and understand the mechanisms of cardiovascular remodeling, improving the knowledge of the pathophysiological mechanisms

Apply new imaging and modeling technologies

Help with diagnosis Optimize planning and

personalized treatment decisions Improve the monitoring and

prevention of future diseases

Thank you

Supported by grants from SERAM (Sociedad

Española de Radiología Médica)

The authors also thank the Radiology Department of Hospital Quirón Valencia for their help and continuous support with image acquisition and for the clinical validation