Standardizing a large-scale, whole body CT image database

1. Standardizing a large-scale, whole body CT image database 2018 NIJ FORENSIC SCIENCE R&D SYMPOSIUM Heather J.H. Edgar and Shamsi Daneshvari Berry

2. Background • OMI Unique • State-Wide • Centralized • Ethnic and racial diversity similar to NM census, about 10% NA and 35% Hispanic • New (2010) biohazard 3 facility • CT and MRI

3. Background • New Mexico’s Office of the Medical Investigator (OMI) • 2010 NIJ grant to test: CT to supplement or supplant traditional autopsies • GSW, Sharp force, Shaken babies • Scanning since 2010 has resulted in about 15,000 CT scans • No plan for reuse of images

4. “Findability” of Images • OMI database separate • Text fields • Few standards • Cannot search image • But…can search metadata

5. Creation of the data set • Modified Delphi method • Queried 42 experts from multiple domains

6. Minimum Data Set 59 variables • Date of Birth • Date of Death • Medical Diagnoses • Primary Cause of Death • Contributing Cause of Death • Current Smoking Status • Drinking History • Current Drug Use • Drug Use History • Surgical History • Current Medications • History of Broken Bones • Dental Health as an Adult • Environmental Conditions of the Cadaver • Method used for Decedent ID • Number of Years in the US if Born Elsewhere • Smoking History • Current Drinking Status • Presence of Implanted Devices • Presence of Dental Caries • Last Occupation • Length at Last Occupation • Zip Code at death • Sex/gender • Race • Country of Origin • Parents’ Country of Origin • Number of Pregnancies • Number of Live Births • Highest Education Level • Childhood Socioeconomic Status • Adult Socioeconomic Status • Repetitive or Habitual Activities • Dietary Pattern • Birth Weight • Presence of Congenital Abnormalities • Current Height • Cadaver Length • Current Weight • Cadaver Weight • Current Bone Density • Family History of Cancer • History of radiation Therapy • History of Facial Trauma • Presence of Genetic Disorders • Family History of Genetic Disorders • Presence of Scoliosis • History of Plastic Surgery • Dental health as a Child • Major Occupation during Life • Occupation History • Exposure to Carcinogens or Lethal Substances • Exposure to Strenuous Lifting at Work • Length of Military Service • Manner of Death • Time Delay between Death and CT Scan • Location of Death • CT Scanner Settings • Name of Person Entering Information into Database

7. Additional variables added • Marital status • Mother’s birthplace • Father’s birthplace • Mother’s mother’s birthplace • Mother’s father’s birthplace • Father’s mother’s birthplace • Father’s father’s birthplace

8. Building the database • Received an NIJ grant in 2016 to develop and share the database • Creation of data standards • Clean data from OMI database • Call next of kin for remaining information • Website interface • Providing metadata and CT scans to researchers

9. Creation of data standards • Search Unified Medical Language System for metadata variables • Create list of standards used using the Metathesaurus Browser • Search each standard • Search LOINC and SNOMED CT even if not listed • Determine the normative answer list • Compare standards for THIS database • Select standard/modify standard/create new standard

10. Example 1: Smoking • Smoking status • NCI • SNOMED CT codes

11. Example 1: Smoking • Smoking status • LOINC • NHIS

12. Example 1: smoking • Smoking Status • LOINC • FTND

13. Example 1: smoking • Smoking status • Options: • NHIS using SNOMED CT codes • FTND • Modify • Create new

14. Example 1: smoking • Smoking status • Information coming from • Next of kin interview • Medical Examiner’s case notes • How is it captured elsewhere? • Medical record: LOINC NHIS codes using SNOMED CT • CDC: LOINC NHIS codes using SNOMED CT

15. Example 1: smoking • Smoking status • Match medical record answers • Selected LOINC NHIS codes using SNOMED CT codes • Current everyday smoker • Current someday smoker • Former smoker • Never smoker • Smoker, current status unknown • Unknown if ever smoked • Heavy tobacco smoker • Light tobacco smoker 100 cigarettes in a lifetime and smokes every day 100 cigarettes in a lifetime and smokes some days => 10 cigarettes per day <10 cigarettes per day

16. Example 2: diagnoses • Medical Diagnoses • SNOMED CT • Over 100,000 codes • Very specific • ICD 10 codes • Over 70,000 codes • 7 characters long • Characters 1–3 (the category of disease) • 4 (etiology of disease) • 5 (body part affected) • 6 (severity of illness) • 7 (placeholder for extension of the code to increase specificity)

17. Example 2: diagnoses • ICD 10 • Using 3 characters • 2040 diagnoses categories • Some categories will not be seen is this population • A66: Yaws • A67: Pinta • Some next of kin will not know the details • Malaria • B50: Plasmodium falciparum malaria • B51: Plasmodium vivax malaria • B52: Plasmodium malariae malaria • B53: Other parasitologically confirmed malaria

18. Example 2:diagnoses • Options: • SNOMED CT • ICD 10 full codes • ICD 10 category codes • Modify an existing code • Create a new standard

19. Example 2: diagnoses • Modifying an existing code • Too many options • Create new code • Trying to capture the most common diseases • At the level that next of kin would recognize

20. Example 2: Diagnoses • New Standard • Sought to capture 20 most common disorders seen in THIS population • Cancer separated out • Congenital abnormalities separated out • Chromosomal abnormalities separated out

21. Example 2: Diagnoses • Autism spectrum • Mental illness • Diabetes Type II • Hypertension • Hyperlipidemia • Chronic heart failure • COPD • Cirrhosis of the liver • Autoimmune diseases • Insect borne disease • Tuberculosis • Asthma • HIV/AIDS • Stroke • Epilepsy • Coronary artery disease • Staphylococcus aureus • Dementia • Arthritis • Osteoporosis

22. Discussion • Balance of multiple forces • Current standards used commonly • Specifics of this population • Knowledge at the level next of kin would know • Level given in medical examiner case notes • Ease of entering into database • Researchers interests

23. Free Access Decedent Database • Currently under development • Website available by end of 2018 • Determining if CT scans can be downloaded directly • No cost • Available to all bona fide researchers

24. What Will you do with… • 15,000 whole body decedent CT scans • All that metadata • Demographics, COD, occupation, etc., etc. • The possibilities are endless!

25. Thanks to • National Institute of Justice • Emily Moes, project graduate assistant • UNM divisions: • Phil Kroth and the Biomedical Informatics Program • Patrick Bridges and staff of Center for Advanced Research Computing • Natalie Adolphi and the Center for Forensic Imaging • Arts and Sciences Information Technologies • Office of the Medical Investigator • You, for your time and attention