Weekend Course

ORGANIZERS: Dwight G. Nishimura, Ph.D.

Sunday, 23 April 2017

Skill Level: Basic to Intermediate

Slack Channel: #e_crosscutting
Session Number: WE26

Please note the schedule of this session is as follows: 
Foundations of Imaging Studies  
13:15 Designing Studies of Diagnostic Imaging - Nancy Obuchowski, Ph.D.
13:45 Basic Concepts in Calculations of Sample Size & Statistical Power - Todd A. Alonzo, Ph.D.
14:15 Break & Meet the Teachers  

Statistical Methods in Imaging Studies  
14:30 Part 1 of Assessing Quantitative Imaging Biomarkers (QIBs) - Nancy Obuchowski, Ph.D.
14:55 Part 1 of ROC Analysis in Diagnostic Medicine - Todd A. Alonzo, Ph.D.
15:20 Break & Meet the Teachers  

Advanced Methods  
15:35 Part 2 of ROC Analysis: Multi-Reader ROC & Other Advanced ROC Methods - Nancy Obuchowski, Ph.D.
15:55 Part 2 of Assessing QIBs: Statistical Prognostic/Predictive Modeling of QIBs - Todd A. Alonzo, Ph.D.
16:15 Adjournment & Meet the Teachers

Overview
An understanding of statistical analysis methods is fundamental to all scientific and clinical research. This half-day Educational Course will provide an introduction to bio statistical methods for imaging studies. The course will focus on common data analysis methods, including single-reader and multi-reader ROC analysis and methods for quantitative imaging biomarkers, with case studies presented to illustrate when they are applicable. The course will also cover the key concepts in designing a study, including common biases and methods for minimizing bias, designs to improve study efficiency, and sample size considerations.

Target Audience
Scientists, medical physicists, engineers, and clinicians who would like an overview of bio statistical techniques and study designs used for imaging studies.

Educational Objectives
Upon completion of this course, participants should be able to:

-Describe common data analysis methods used in imaging studies;
-Identify appropriate methods for different types of studies;
-Apply key concepts for unbiased and efficient study designs; and
-Assess technical performance of quantitative imaging biomarkers.