Yi Li1, Wesley K Thompson2, Chase Reuter2, Ryan Nillo1, Terry Jernigan3, Anders Dale3, Leo P Sugrue1, Julian Brown1, Robert F Dougherty4, Andreas Rauschecker1, Jeffrey Rudie1, Deanna M Barch5, Vince Calhoun6, Donald Hagler7, Sean Hatton8, Jody Tanabe9, Andrew Marshall10, Kenneth J Sher11, Steven Heeringa12, Robert Hermosillo13, Marie T Banich14, Lindsay Squeglia15, James Bjork16, Robert Zucker17, Michael Neale16, Megan Herting18, Chandni Sheth19, Rebeka Huber19, Gloria Reeves20, John M Hettema21, Katia Delrahim Howlett22, Christine Cloak23, Arielle Baskin-Sommers24, Kristina Rapuano24, Raul Gonzalez25, Nicole Karcher26, Angela Laird27, Fiona Baker28, Regina James29, Elizabeth Sowell10, Anthony Dick25, Samuel Hawes25, Matthew Sutherland25, Kara Bagot30, Jerzy Bodurka31, Florence Breslin31, Amanda Morris31, Martin Paulus31, Kevin Gray15, Elizabeth Hoffman22, Susan Weiss22, Nishadi Rajapakse32, Meyer Glantz33, Bonnie Nagel34, Sarah Feldstein Ewing34, Aimee Goldstone28, Adolf Pfefferbaum28, Devin Prouty28, Monica Rosenberg35, Susan Bookheimer36, Susan Tapert37, Maria Infante37, Joanna Jacobus37, Jay Giedd37, Paul Shilling37, Natasha Wade37, Kristina Uban38, Frank Haist39, Charles Heyser3, Clare Palmer3, Joshua Kuperman7, John Hewitt40, Linda Cottler41, Amal Isaiah42, Linda Chang43, Sarah Edwards20, Thomas Ernst44, Mary Heitzeg45, Leon Puttler45, Chandra Sripada45, William Iacono46, Monica Luciana46, Duncan Clark47, Beatriz Luna47, Claudiu Schirda48, John Foxe49, Edward Freedman49, Michael Mason50, Erin McGlade19, Perry Renshaw19, Deborah Yurgelun-Todd19, Matthew Albaugh51, Nicholas Allgaier51, Bader Chaarani51, Alexandra Potter51, Masha Ivanova51, Krista Lisdahl51, Elizabeth Do52, Hermine Maes53, Ryan Bogdan54, Andrey Anokhin26, Nico Dosenbach55, Paul Glaser26, Andrew Heath26, Betty J Casey24, Dylan Gee24, Hugh P Garavan51, Gaya Dowling22, Sandra Brown56. 1. Department of Radiology and Biomedical Imaging, University of California, San Francisco. 2. Department of Family Medicine and Public Health, University of California, San Diego, La Jolla. 3. Center for Human Development, University of California, San Diego, La Jolla. 4. Center for Cognitive and Neurobiological Imaging, Stanford University, Stanford, California. 5. Department of Psychological & Brain Sciences, Psychiatry, Radiology, Washington University in St Louis, St Louis, Missouri. 6. Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State University, Georgia Tech, Emory University, Atlanta. 7. Department of Radiology, University of California, San Diego, La Jolla. 8. Department of Neurosciences, University of California, San Diego, La Jolla. 9. Department of Radiology, University of Colorado Anschutz Medical Center, Aurora. 10. Department of Pediatrics, Children's Hospital Los Angeles/University of Southern California, Los Angeles. 11. Department of Psychological Sciences, University of Missouri, Columbia. 12. Institute for Social Research, University of Michigan, Ann Arbor. 13. Department of Behavioral Neuroscience, Oregon Health Sciences University, Portland. 14. Institute of Cognitive Science, Department of Psychology and Neuroscience, University of Colorado, Boulder. 15. Department of Psychiatry and Behavioral Sciences, Medical University of South Carolina, Charleston. 16. Department of Psychiatry, Virginia Commonwealth University, Richmond. 17. Department of Psychiatry and Psychology, University of Michigan, Ann Arbor. 18. Department of Preventive Medicine, University of Southern California, Los Angeles. 19. Department of Psychiatry, University of Utah School of Medicine, Salt Lake City. 20. Department of Psychiatry, University of Maryland, Baltimore. 21. Department of Psychiatry, Texas A&M Health Science Center, Bryan. 22. Division of Extramural Research, National Institute on Drug Abuse/National Institutes of Health, Bethesda, Maryland. 23. Department of Radiology and Nuclear Medicine, University of Maryland, Baltimore. 24. Department of Psychology, Yale University, New Haven, Connecticut. 25. Department of Psychology, Florida International University, Miami. 26. Department of Psychiatry, Washington University in St Louis, St Louis, Missouri. 27. Department of Physics, Florida International University, Miami. 28. SRI International, Menlo Park, California. 29. Department of Clinical Research, 2M Research Services, Arlington, Virginia. 30. Department of Psychiatry, Icahn School of Medicine at Mt Sinai, New York, New York. 31. Laureate Institute for Brain Research, Tulsa, Oklahoma. 32. Department of Scientific Programs, National Institute on Minority Health and Health Disparities, Bethesda, Maryland. 33. Department of Psychology, National Institute on Drug Abuse/National Institutes of Health, Bethesda, Maryland. 34. Department of Psychiatry, Oregon Health and Science University, Portland. 35. Department of Psychology, University of Chicago, Chicago, Illinois. 36. Department of Psychiatry and Biobehavioral Sciences, School of Medicine, University of California, Los Angeles. 37. Department of Psychiatry, University of California, San Diego, La Jolla. 38. Department of Public Health, University of California, Irvine. 39. Department of Psychiatry and Center for Human Development, University of California, San Diego, La Jolla. 40. Institute for Behavioral Genetics, University of Colorado, Boulder. 41. Department of Epidemiology, University of Florida, Gainesville. 42. Department of Otorhinolaryngology/Head and Neck Surgery and Pediatrics, University of Maryland School of Medicine, Baltimore. 43. Departments of Radiology and Neurology, University of Maryland, Baltimore. 44. Department of Radiology, University of Maryland, Baltimore. 45. Department of Psychiatry, University of Michigan, Ann Arbor. 46. Department of Psychology, University of Minnesota, Minneapolis. 47. Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania. 48. Department of Radiology, University of Pittsburgh, Pittsburgh, Pennsylvania. 49. Department of Neuroscience, University of Rochester Medical Center, Rochester, New York. 50. Center for Behavioral Health Research, University of Tennessee, Knoxville. 51. Department of Psychiatry, University of Vermont, Burlington. 52. Department of Health Behavior and Policy, Virginia Commonwealth University, Richmond. 53. Department of Human and Molecular Genetics, Virginia Commonwealth University, Richmond. 54. Department of Psychological and Brain Sciences, Washington University in St Louis, St Louis, Missouri. 55. Department of Neurology, Washington University in St Louis, St Louis, Missouri. 56. Department of Psychiatry and Psychology, University of California, San Diego, La Jolla.
Abstract
Importance: Incidental findings (IFs) are unexpected abnormalities discovered during imaging and can range from normal anatomic variants to findings requiring urgent medical intervention. In the case of brain magnetic resonance imaging (MRI), reliable data about the prevalence and significance of IFs in the general population are limited, making it difficult to anticipate, communicate, and manage these findings. Objectives: To determine the overall prevalence of IFs in brain MRI in the nonclinical pediatric population as well as the rates of specific findings and findings for which clinical referral is recommended. Design, Setting, and Participants: This cohort study was based on the April 2019 release of baseline data from 11 810 children aged 9 to 10 years who were enrolled and completed baseline neuroimaging in the Adolescent Brain Cognitive Development (ABCD) study, the largest US population-based longitudinal observational study of brain development and child health, between September 1, 2016, and November 15, 2018. Participants were enrolled at 21 sites across the US designed to mirror the demographic characteristics of the US population. Baseline structural MRIs were centrally reviewed for IFs by board-certified neuroradiologists and findings were described and categorized (category 1, no abnormal findings; 2, no referral recommended; 3; consider referral; and 4, consider immediate referral). Children were enrolled through a broad school-based recruitment process in which all children of eligible age at selected schools were invited to participate. Exclusion criteria were severe sensory, intellectual, medical, or neurologic disorders that would preclude or interfere with study participation. During the enrollment process, demographic data were monitored to ensure that the study met targets for sex, socioeconomic, ethnic, and racial diversity. Data were analyzed from March 15, 2018, to November 20, 2020. Main Outcomes and Measures: Percentage of children with IFs in each category and prevalence of specific IFs. Results: A total of 11 679 children (52.1% boys, mean [SD] age, 9.9 [0.62] years) had interpretable baseline structural MRI results. Of these, 2464 participants (21.1%) had IFs, including 2013 children (17.2%) assigned to category 2, 431 (3.7%) assigned to category 3, and 20 (0.2%) assigned to category 4. Overall rates of IFs did not differ significantly between singleton and twin gestations or between monozygotic and dizygotic twins, but heritability analysis showed heritability for the presence or absence of IFs (h2 = 0.260; 95% CI, 0.135-0.387). Conclusions and Relevance: Incidental findings in brain MRI and findings with potential clinical significance are both common in the general pediatric population. By assessing IFs and concurrent developmental and health measures and following these findings over the longitudinal study course, the ABCD study has the potential to determine the significance of many common IFs.
Importance: Incidental findings (IFs) are unexpected abnormalities discovered during imaging and can range from normal anatomic variants to findings requiring urgent medical intervention. In the case of brain magnetic resonance imaging (MRI), reliable data about the prevalence and significance of IFs in the general population are limited, making it difficult to anticipate, communicate, and manage these findings. Objectives: To determine the overall prevalence of IFs in brain MRI in the nonclinical pediatric population as well as the rates of specific findings and findings for which clinical referral is recommended. Design, Setting, and Participants: This cohort study was based on the April 2019 release of baseline data from 11 810 children aged 9 to 10 years who were enrolled and completed baseline neuroimaging in the Adolescent Brain Cognitive Development (ABCD) study, the largest US population-based longitudinal observational study of brain development and child health, between September 1, 2016, and November 15, 2018. Participants were enrolled at 21 sites across the US designed to mirror the demographic characteristics of the US population. Baseline structural MRIs were centrally reviewed for IFs by board-certified neuroradiologists and findings were described and categorized (category 1, no abnormal findings; 2, no referral recommended; 3; consider referral; and 4, consider immediate referral). Children were enrolled through a broad school-based recruitment process in which all children of eligible age at selected schools were invited to participate. Exclusion criteria were severe sensory, intellectual, medical, or neurologic disorders that would preclude or interfere with study participation. During the enrollment process, demographic data were monitored to ensure that the study met targets for sex, socioeconomic, ethnic, and racial diversity. Data were analyzed from March 15, 2018, to November 20, 2020. Main Outcomes and Measures: Percentage of children with IFs in each category and prevalence of specific IFs. Results: A total of 11 679 children (52.1% boys, mean [SD] age, 9.9 [0.62] years) had interpretable baseline structural MRI results. Of these, 2464 participants (21.1%) had IFs, including 2013 children (17.2%) assigned to category 2, 431 (3.7%) assigned to category 3, and 20 (0.2%) assigned to category 4. Overall rates of IFs did not differ significantly between singleton and twin gestations or between monozygotic and dizygotic twins, but heritability analysis showed heritability for the presence or absence of IFs (h2 = 0.260; 95% CI, 0.135-0.387). Conclusions and Relevance: Incidental findings in brain MRI and findings with potential clinical significance are both common in the general pediatric population. By assessing IFs and concurrent developmental and health measures and following these findings over the longitudinal study course, the ABCD study has the potential to determine the significance of many common IFs.
Authors: Kiley B Vander Wyst; Micah L Olson; Smita S Bailey; Ana Martinez Valencia; Armando Peña; Jeffrey Miller; Mitchell Shub; Lee Seabrooke; Janiel Pimentel; Kiri Olsen; Robert B Rosenberg; Gabriel Q Shaibi Journal: BMC Med Res Methodol Date: 2021-12-05 Impact factor: 4.612