CaBIG In Vivo Imaging Workspace Software for Image Based Cancer Research Fred Prior, Ph.D....

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CaBIG In Vivo Imaging Workspace Software for Image Based Cancer Research Fred Prior, Ph.D. Mallinckrodt Institute of Radiology Washington University School of Medicine

Transcript of CaBIG In Vivo Imaging Workspace Software for Image Based Cancer Research Fred Prior, Ph.D....

Page 1: CaBIG In Vivo Imaging Workspace Software for Image Based Cancer Research Fred Prior, Ph.D. Mallinckrodt Institute of Radiology Washington University School.

CaBIG In Vivo Imaging Workspace

Software for Image Based Cancer Research

Fred Prior, Ph.D.Mallinckrodt Institute of RadiologyWashington University School of Medicine

Page 2: CaBIG In Vivo Imaging Workspace Software for Image Based Cancer Research Fred Prior, Ph.D. Mallinckrodt Institute of Radiology Washington University School.

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Example: Multi-Center Clinical Trial The Silent Infarct Transfusion Trial (SITT) is a multi-center clinical

trial to determine the efficacy of blood transfusion therapy as a treatment for preventing silent strokes in children with sickle cell disease.

Silent strokes — strokes that do not cause immediately obvious symptoms — frequently go unrecognized and are one of the most serious afflictions associated with sickle cell disease.

Sickle cell disease, an inherited disorder of the red blood cells, is

the most common genetic disorder in African-Americans. The disease affects one in 400 African-American infants — and 22 percent of these children will suffer a silent stroke before they finish high school.

http://sitstudy.wustl.edu

Page 3: CaBIG In Vivo Imaging Workspace Software for Image Based Cancer Research Fred Prior, Ph.D. Mallinckrodt Institute of Radiology Washington University School.

What is a Silent Infarct?

T2 Flair image

Page 4: CaBIG In Vivo Imaging Workspace Software for Image Based Cancer Research Fred Prior, Ph.D. Mallinckrodt Institute of Radiology Washington University School.

Imaging Protocol

For this project we defined an MR imaging protocol that provided all the information needed for the complete clinical management of these patients and which supported the specific aims of the project

BUT, this protocol was not adequate for volumetric measurements and some sites could not reliably complete the protocol

Imaging protocols need to be standardized and they have a complex relationship with image QA and analysis procedures and software

NCI and ACR have an activity to define standard protocols for cancer research - UPICTS This activity needs to be coordinated with our activity to define

and develop analysis tools

Page 5: CaBIG In Vivo Imaging Workspace Software for Image Based Cancer Research Fred Prior, Ph.D. Mallinckrodt Institute of Radiology Washington University School.

InternetWU Network

Cisco VPN

ImageCollection/QA

Station

Stentor Image

Server

Firewall

Clinical Studies

Workstation Laptop

MRI Scanner or PACS

Imaging Site

Imaging Center

Transmitting MRI Images: Study Sites Imaging Center

Page 6: CaBIG In Vivo Imaging Workspace Software for Image Based Cancer Research Fred Prior, Ph.D. Mallinckrodt Institute of Radiology Washington University School.

CSW Software De-Identifies/Re-identifies Imaging Studies

BHJ

01-001-01

Page 7: CaBIG In Vivo Imaging Workspace Software for Image Based Cancer Research Fred Prior, Ph.D. Mallinckrodt Institute of Radiology Washington University School.

Tools for “Pseudonymization”

CSW MIRC for clinical trials ACRIN Undoubtedly many others We need a harmonized tool set that takes

the best features of all of the above and enables them over the grid.

Page 8: CaBIG In Vivo Imaging Workspace Software for Image Based Cancer Research Fred Prior, Ph.D. Mallinckrodt Institute of Radiology Washington University School.

Internet

WU Network

Cisco VPNFirewall

Radiologist

Imaging Center

Consensus Reading: Neuroradiology Panel

“iSite/Radiology”

queryretrieve

“iSite Server”

Page 9: CaBIG In Vivo Imaging Workspace Software for Image Based Cancer Research Fred Prior, Ph.D. Mallinckrodt Institute of Radiology Washington University School.
Page 10: CaBIG In Vivo Imaging Workspace Software for Image Based Cancer Research Fred Prior, Ph.D. Mallinckrodt Institute of Radiology Washington University School.

Lesion Detection In this study three neuroradiologists read each

case independently and report their results Imaging center staff review the report forms and if

there is agreement progress the case to the next step of the trial (or report that the subject is not eligible)

If there is not agreement a consensus conference call is held where all radiologists review the case together and reach consensus

Automated lesion detection can be a very difficult process

CAD tools obviously exist but need to be optimized to detect cancerous lesions

Page 11: CaBIG In Vivo Imaging Workspace Software for Image Based Cancer Research Fred Prior, Ph.D. Mallinckrodt Institute of Radiology Washington University School.

Measurement Tool Variability

Commercially available measurement tools (PACS and other workstations, image analysis packages, …) vary in the algorithms used, the accuracy that is possible and the repeatability of measurements

The same measurement taken on the same data can yield quite variable results across systems

We need measurement tools and procedures with known accuracy, precision and repeatability

Page 12: CaBIG In Vivo Imaging Workspace Software for Image Based Cancer Research Fred Prior, Ph.D. Mallinckrodt Institute of Radiology Washington University School.

Volumetric Measurements of Image Features

We have proposed an ancillary study to segment identified lesions, determine their volume and track volume changes

Imaging protocol limits our ability to do this

Key software issues include: segmentation algorithms Measurement tools

A critical problem facing the pharmaceutical industry is how to establish standard measurements of biomarkers, i.e. standardized, repeatable measurement techniques that can be applied to specific image features

Some industry experts have suggested that the cost of clinical trials can be reduced by 10s of millions of dollars by the establishment of FDA accepted, industry standard measurements and measurement techniques

Page 13: CaBIG In Vivo Imaging Workspace Software for Image Based Cancer Research Fred Prior, Ph.D. Mallinckrodt Institute of Radiology Washington University School.

Image Libraries

Information is frequently divided between the imaging core and data management core Critical meta-data is separated from the images

A common data representation (XML), federation approach and query model such as that used by MIRC is a possible first step to permit shared access

Beyond that we need data mining tools that work across the grid: Indexing tools that employ distance measures that are

appropriate for this application (not Google’s measure) Machine intelligence algorithms to search for correlations

Page 14: CaBIG In Vivo Imaging Workspace Software for Image Based Cancer Research Fred Prior, Ph.D. Mallinckrodt Institute of Radiology Washington University School.

The Start of a Discussion,…

Page 15: CaBIG In Vivo Imaging Workspace Software for Image Based Cancer Research Fred Prior, Ph.D. Mallinckrodt Institute of Radiology Washington University School.
Page 16: CaBIG In Vivo Imaging Workspace Software for Image Based Cancer Research Fred Prior, Ph.D. Mallinckrodt Institute of Radiology Washington University School.

MRI Imaging Protocol1) Scout Localizer (3 planes) 2) Fast/ /Turbo FLAIR T2-weighted Axial and Coronal

Basic diagnostic scan (must cover the whole brain) 3) T1-weighted Acquisition

For segmentation and volumetric studies 4) Fast/Turbo Spin Echo T2-weighted Axial Acquisition

Detailed diagnostic scan (must cover the whole brain) 5) Echo-Planar Axial Diffusion Acquisition

For ancillary DTI studies (Repeated 2 times without signal averaging)6) 3D Time-of-Flight Magnetic Resonance Angiography

Protocol Options for Symptomatic Patients:1) 2D Time-of-Flight Magnetic Resonance Venography 2) T2* (susceptibility) weighted Axial Acquisition

On average this results in about 600 images per study

Page 17: CaBIG In Vivo Imaging Workspace Software for Image Based Cancer Research Fred Prior, Ph.D. Mallinckrodt Institute of Radiology Washington University School.

Volumetric Measurements of Image Features

Multi-center clinical trials increasingly use image based measurements to determine end-points and progression and are essentially large scale teleradiology applications

A critical problem facing the pharmaceutical industry is how to establish standard measurements of biomarkers, i.e. standardized, repeatable measurement techniques that can be applied to specific image features

Some industry experts have suggested that the cost of clinical trials can be reduced by 10s of millions of dollars by the establishment of FDA accepted, industry standard measurements and measurement techniques