Blood-Based Ultra-High-Throughput Radiation Biodosimetry David J. Brenner, PhD, DSc Center for Radiological Research Columbia University Medical Center New York, NY djb3@columbia.edu
Biodosimetry The use of biological markers to assess past radiation exposure Advantages over physical dosimetry: No need to be present during exposure Potentially more relevant medically
Example: A hypothetical population all exposed to the same radiation dose DISTRIBUTION OF DOSIMETER RESPONSES 100 DISTRIBUTION OF BIODOSIMETER RESPONSES 100 80 80 60 60 40 40 20 20 0 0
Ultra-High-Throughput Radiation Biodosimetry Scenarios Nuclear accident Dirty bomb Nuclear device detonation
The need for ultra-high-throughput biodosimetry 1. Triage: To prevent treatment locations from being overwhelmed 2. Treatment decisions: Treatment options are dose dependent 3. Long-term considerations: Assessment of cancer risks and other long-term disease risks 4. Psycho-Social Considerations: Active reassurance is an effective antidote to mass panic or mass skepticism
The need for ultra-high-throughput biodosimetry Triage 1987 radiation incident in Goiânia, Brazil, a city with about the same population as Manhattan. In the first few days after the incident became known, 130,000 people (10% of the population) came for screening, of whom 20 required treatment.
The need for ultra-high-throughput biodosimetry 1. Triage: To prevent treatment locations from being overwhelmed 2. Treatment decisions: Treatment options are dose dependent 3. Long-term considerations: Assessment of cancer risks and other long-term disease risks 4. Psycho-Social Considerations: Active reassurance is an effective antidote to mass panic or mass skepticism
Biodosimetry Is Essential to Optimize Treatment Decisions Cytokine therapy
The need for ultra-high-throughput biodosimetry 1. Triage: To prevent treatment locations from being overwhelmed 2. Treatment decisions: Treatment options are dose dependent 3. Long-term considerations: Assessment of cancer risks and other long-term disease risks 4. Psycho-Social Considerations: Active reassurance is an effective antidote to mass panic or mass skepticism
Few people in Japan believe what they are being told about their radiation exposure More than 80% of Japanese distrust government information on radiation
There is widespread skepticism of what the Japanese authorities are saying Unfortunately, Japanese people, particularly the residents of Fukushima Prefecture, have begun to suspect that the Japanese government and local authorities are keeping important information from them Suminori Akiba, Kagoshima University Journal of Radiological Protection, March 2012
In future large-scale radiological events, worldwide, we should anticipate much skepticism regarding radiation information coming from the authorities One solution is to provide rapid and individualized measured radiation doses, for every person To identify individuals who really got high doses To reassure the great majority of people who got very low doses
What sort of sample numbers are needed for biodosimetry after a large radiological event? Some scenarios will require analysis of ~10 2 to 10 3 samples Cytogenetic laboratory networks can effectively cover this range Other scenarios will require analysis of ~10 4 to 10 7 samples
Issues for an Effective Ultra-High-Throughput Radiation Biodosimeter Processing throughput minimal invasiveness Sensitivity / specificity Processing time Signal stability Multi-use technology
Columbia Center for High-Throughput Minimally-Invasive Radiation Biodosimetry Three independent approaches towards high-throughput radiation biodosimetry: Speed up classical biodosimetry assays Genomic signature assays Metabolomic signature assays
RABiT: Converting mature manually-based biodosimeters to ultra-high throughput Mature biomarkers (until now, manually-based) Fully automated robotically-based ultrahigh-throughput system
The classic cytogenetic biodosimetry endpoints are dicentrics, translocations, and micronuclei Translocations
RABiT assays Micronuclei in binucleated lymphocytes Ratio of mononucleates to binucleates after induced cell division Mn M/B
RABiT: Rapid Automated Biodosimetry Tool Fully-automated ultra high-speed robotic biodosimetry workstation One fingerstick of blood No further human intervention after blood samples put into the RABiT Automates well-established manual assays Can deal with partial-body exposure Phase II (2010): 30,000 samples/day The main technical innovations are: 1) Use of smaller samples single drop of blood from a fingerstick 2) Complete full automation of biology, in a 96 tube / plate format 3) Innovations in high-speed imaging 4) Potential for use as a hospital-based multi-use routine diagnostic tool
RABiT logistics 1. In the field, fingersticks of blood are taken by minimallytrained collectors and loaded into bar-coded blood storage tubes 2. Blood storage tubes, in standard 96-tube format, are transported to the RABiT 3. Still in the 96-tube format, the tubes are placed on the RABiT input shelf 4. From then on, the RABiT system is fully automated...
Collection Points: Hospitals Fingerstick blood samples Fingerstick blood samples. RABiT Locations Collection Points: Schools Collection Points: Temporary Locations Fingerstick blood samples Collection Points: Railway Stations
RABiT device overview
What goes on inside the RABiT? The first parts of the automated RABiT processing is done in the blood storage tubes, in standard 96 tube format The remaining automated processing, and then the automated imaging, is done in optically-clear 96-well plates
We need to image very fast We have ~3 sec to analyze each well (sample), and want to analyze 150 frames within each well We must image and analyze each frame in < 20 msec During this time, we need to: move to next frame adjust focus grab image analyze Each task is individually optimized, and some are multi-tasked
Where are we now with the RABiT? All the individual components are functioning to specification (30,000 samples / day) Validation / Calibration / Product development Validation Time since exposure High doses Confounders Human blood ex-vivo irradiation Mice, in-vivo irradiation Radiotherapy patients
RABiT dose predictions from blinded studies Accuracy: Percent Percent of RABiT of dose dose predictions predictions within 0.5 Gy that were within a given dose error Dicentric assay (Wilkins et al 2009): 83% Percent predictions within given dose 100 90 80 70 60 50 40 30 20 10 0 Dicentric assay (Beinke et al 2011): 78% RABiT Mn Assay: 76% 94% within 1 Gy 76% within 0.5 Gy 60% within 0.3 Gy 1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 Dose prediction accuracy (Gy)
Multi-use technology: Other applications of the RABiT A multiple-use scenario will significantly increase the likelihood that the RABiT will be immediately functional after an RDD or an IND event Hospital cytogenetic screening e.g. automated amniocentesis Radiation sensitivity screening Applications for radiology and radiation oncology
Columbia University Center for High-Throughput Minimally-Invasive Radiation Biodosimetry www.cmcr.columbia.edu