1
|
Rahmani F, Jindal S, Raji CA, Wang W, Nazeri A, Perez-Carrillo GG, Miller-Thomas MM, Graner P, Marechal B, Shah A, Zimmermann M, Chen CD, Keefe S, LaMontagne P, Benzinger TLS. Validity Assessment of an Automated Brain Morphometry Tool for Patients with De Novo Memory Symptoms. AJNR Am J Neuroradiol 2023; 44:261-267. [PMID: 36797031 PMCID: PMC10187815 DOI: 10.3174/ajnr.a7790] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Accepted: 01/09/2023] [Indexed: 02/18/2023]
Abstract
BACKGROUND AND PURPOSE Automated volumetric analysis of structural MR imaging allows quantitative assessment of brain atrophy in neurodegenerative disorders. We compared the brain segmentation performance of the AI-Rad Companion brain MR imaging software against an in-house FreeSurfer 7.1.1/Individual Longitudinal Participant pipeline. MATERIALS AND METHODS T1-weighted images of 45 participants with de novo memory symptoms were selected from the OASIS-4 database and analyzed through the AI-Rad Companion brain MR imaging tool and the FreeSurfer 7.1.1/Individual Longitudinal Participant pipeline. Correlation, agreement, and consistency between the 2 tools were compared among the absolute, normalized, and standardized volumes. Final reports generated by each tool were used to compare the rates of detection of abnormality and the compatibility of radiologic impressions made using each tool, compared with the clinical diagnoses. RESULTS We observed strong correlation, moderate consistency, and poor agreement between absolute volumes of the main cortical lobes and subcortical structures measured by the AI-Rad Companion brain MR imaging tool compared with FreeSurfer. The strength of the correlations increased after normalizing the measurements to the total intracranial volume. Standardized measurements differed significantly between the 2 tools, likely owing to differences in the normative data sets used to calibrate each tool. When considering the FreeSurfer 7.1.1/Individual Longitudinal Participant pipeline as a reference standard, the AI-Rad Companion brain MR imaging tool had a specificity of 90.6%-100% and a sensitivity of 64.3%-100% in detecting volumetric abnormalities. There was no difference between the rate of compatibility of radiologic and clinical impressions when using the 2 tools. CONCLUSIONS The AI-Rad Companion brain MR imaging tool reliably detects atrophy in cortical and subcortical regions implicated in the differential diagnosis of dementia.
Collapse
Affiliation(s)
- F Rahmani
- From the Mallinckrodt Institute of Radiology, Division of Neuroradiology (F.R., S.J., C.A.R., W.W., A.N., G.G.P.-C., M.M.M.-T., C.D.C., S.K., P.L., T.L.S.B.)
- Charles F. and Joanne Knight Alzheimer Disease Research Center (F.R., S.J., C.A.R., W.W., A.N., C.D.C., T.L.S.B.), Washington University in St. Louis, St. Lous, Missouri
| | - S Jindal
- From the Mallinckrodt Institute of Radiology, Division of Neuroradiology (F.R., S.J., C.A.R., W.W., A.N., G.G.P.-C., M.M.M.-T., C.D.C., S.K., P.L., T.L.S.B.)
- Charles F. and Joanne Knight Alzheimer Disease Research Center (F.R., S.J., C.A.R., W.W., A.N., C.D.C., T.L.S.B.), Washington University in St. Louis, St. Lous, Missouri
| | - C A Raji
- From the Mallinckrodt Institute of Radiology, Division of Neuroradiology (F.R., S.J., C.A.R., W.W., A.N., G.G.P.-C., M.M.M.-T., C.D.C., S.K., P.L., T.L.S.B.)
- Charles F. and Joanne Knight Alzheimer Disease Research Center (F.R., S.J., C.A.R., W.W., A.N., C.D.C., T.L.S.B.), Washington University in St. Louis, St. Lous, Missouri
| | - W Wang
- From the Mallinckrodt Institute of Radiology, Division of Neuroradiology (F.R., S.J., C.A.R., W.W., A.N., G.G.P.-C., M.M.M.-T., C.D.C., S.K., P.L., T.L.S.B.)
- Charles F. and Joanne Knight Alzheimer Disease Research Center (F.R., S.J., C.A.R., W.W., A.N., C.D.C., T.L.S.B.), Washington University in St. Louis, St. Lous, Missouri
| | - A Nazeri
- From the Mallinckrodt Institute of Radiology, Division of Neuroradiology (F.R., S.J., C.A.R., W.W., A.N., G.G.P.-C., M.M.M.-T., C.D.C., S.K., P.L., T.L.S.B.)
- Charles F. and Joanne Knight Alzheimer Disease Research Center (F.R., S.J., C.A.R., W.W., A.N., C.D.C., T.L.S.B.), Washington University in St. Louis, St. Lous, Missouri
| | - G G Perez-Carrillo
- From the Mallinckrodt Institute of Radiology, Division of Neuroradiology (F.R., S.J., C.A.R., W.W., A.N., G.G.P.-C., M.M.M.-T., C.D.C., S.K., P.L., T.L.S.B.)
| | - M M Miller-Thomas
- From the Mallinckrodt Institute of Radiology, Division of Neuroradiology (F.R., S.J., C.A.R., W.W., A.N., G.G.P.-C., M.M.M.-T., C.D.C., S.K., P.L., T.L.S.B.)
| | - P Graner
- Siemens Medical Solutions (P.G., B.M., M.Z.), Malvern, Pennsylvania
- Advanced Clinical Imaging Technology (P.G., B.M., M.Z.), Siemens Healthcare, Lausanne, Switzerland
- Department of Radiology (P.G., B.M., M.Z.), Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- LTS5, École Polytechnique Fédérale de Lausanne (P.G., B.M., A.S., M.Z.), Lausanne, Switzerland
- Siemens Healthcare (P.G., B.M., M.Z.), Erlangen, Germany
| | - B Marechal
- Siemens Medical Solutions (P.G., B.M., M.Z.), Malvern, Pennsylvania
- Advanced Clinical Imaging Technology (P.G., B.M., M.Z.), Siemens Healthcare, Lausanne, Switzerland
- Department of Radiology (P.G., B.M., M.Z.), Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- LTS5, École Polytechnique Fédérale de Lausanne (P.G., B.M., A.S., M.Z.), Lausanne, Switzerland
- Siemens Healthcare (P.G., B.M., M.Z.), Erlangen, Germany
| | - A Shah
- LTS5, École Polytechnique Fédérale de Lausanne (P.G., B.M., A.S., M.Z.), Lausanne, Switzerland
| | - M Zimmermann
- Siemens Medical Solutions (P.G., B.M., M.Z.), Malvern, Pennsylvania
- Advanced Clinical Imaging Technology (P.G., B.M., M.Z.), Siemens Healthcare, Lausanne, Switzerland
- Department of Radiology (P.G., B.M., M.Z.), Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- LTS5, École Polytechnique Fédérale de Lausanne (P.G., B.M., A.S., M.Z.), Lausanne, Switzerland
- Siemens Healthcare (P.G., B.M., M.Z.), Erlangen, Germany
| | - C D Chen
- From the Mallinckrodt Institute of Radiology, Division of Neuroradiology (F.R., S.J., C.A.R., W.W., A.N., G.G.P.-C., M.M.M.-T., C.D.C., S.K., P.L., T.L.S.B.)
- Charles F. and Joanne Knight Alzheimer Disease Research Center (F.R., S.J., C.A.R., W.W., A.N., C.D.C., T.L.S.B.), Washington University in St. Louis, St. Lous, Missouri
| | - S Keefe
- From the Mallinckrodt Institute of Radiology, Division of Neuroradiology (F.R., S.J., C.A.R., W.W., A.N., G.G.P.-C., M.M.M.-T., C.D.C., S.K., P.L., T.L.S.B.)
| | - P LaMontagne
- From the Mallinckrodt Institute of Radiology, Division of Neuroradiology (F.R., S.J., C.A.R., W.W., A.N., G.G.P.-C., M.M.M.-T., C.D.C., S.K., P.L., T.L.S.B.)
| | - T L S Benzinger
- From the Mallinckrodt Institute of Radiology, Division of Neuroradiology (F.R., S.J., C.A.R., W.W., A.N., G.G.P.-C., M.M.M.-T., C.D.C., S.K., P.L., T.L.S.B.)
- Charles F. and Joanne Knight Alzheimer Disease Research Center (F.R., S.J., C.A.R., W.W., A.N., C.D.C., T.L.S.B.), Washington University in St. Louis, St. Lous, Missouri
| |
Collapse
|
3
|
Cogswell PM, Barakos JA, Barkhof F, Benzinger TS, Jack CR, Poussaint TY, Raji CA, Ramanan VK, Whitlow CT. Amyloid-Related Imaging Abnormalities with Emerging Alzheimer Disease Therapeutics: Detection and Reporting Recommendations for Clinical Practice. AJNR Am J Neuroradiol 2022; 43:E19-E35. [PMID: 35953274 PMCID: PMC9451628 DOI: 10.3174/ajnr.a7586] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
Monoclonal antibodies are emerging disease-modifying therapies for Alzheimer disease that require brain MR imaging for eligibility assessment as well as for monitoring for amyloid-related imaging abnormalities. Amyloid-related imaging abnormalities result from treatment-related loss of vascular integrity and may occur in 2 forms. Amyloid-related imaging abnormalities with edema or effusion are transient, treatment-induced edema or sulcal effusion, identified on T2-FLAIR. Amyloid-related imaging abnormalities with hemorrhage are treatment-induced microhemorrhages or superficial siderosis identified on T2* gradient recalled-echo. As monoclonal antibodies become more widely available, treatment screening and monitoring brain MR imaging examinations may greatly increase neuroradiology practice volumes. Radiologists must become familiar with the imaging appearance of amyloid-related imaging abnormalities, how to select an appropriate imaging protocol, and report findings in clinical practice. On the basis of clinical trial literature and expert experience from clinical trial imaging, we summarize imaging findings of amyloid-related imaging abnormalities, describe potential interpretation pitfalls, and provide recommendations for a standardized imaging protocol and an amyloid-related imaging abnormalities reporting template. Standardized imaging and reporting of these findings are important because an amyloid-related imaging abnormalities severity score, derived from the imaging findings, is used along with clinical status to determine patient management and eligibility for continued monoclonal antibody dosing.
Collapse
Affiliation(s)
- P M Cogswell
- From the Departments of Radiology (P.M.C., C.R.J.)
| | - J A Barakos
- Department of Radiology (J.A.B.), California Pacific Medical Center, San Francisco, California
| | - F Barkhof
- Departments of Radiology (F.B.)
- Nuclear Medicine (F.B.), VU University Medical Center, Amsterdam, the Netherlands
- Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, UK
| | - T S Benzinger
- Departments of Radiology (T.S.B., C.A.R.)
- Neurosurgery (T.S.B.)
| | - C R Jack
- From the Departments of Radiology (P.M.C., C.R.J.)
| | - T Y Poussaint
- Department of Radiology (T.Y.P.), Boston Children's Hospital, Boston, Massachusetts
| | - C A Raji
- Departments of Radiology (T.S.B., C.A.R.)
- Neurology (C.A.R.),Washington University School of Medicine, St. Louis, Missouri
| | - V K Ramanan
- Neurology (V.K.R.), Mayo Clinic, Rochester, Minnesota
| | - C T Whitlow
- Departments of Radiology (C.T.W.)
- Biomedical Engineering (C.T.W.), Wake Forest School of Medicine, Winston-Salem, North Carolina
| |
Collapse
|
4
|
Samara A, Raji CA, Li Z, Hershey T. Comparison of Hippocampal Subfield Segmentation Agreement between 2 Automated Protocols across the Adult Life Span. AJNR Am J Neuroradiol 2021; 42:1783-1789. [PMID: 34353786 DOI: 10.3174/ajnr.a7244] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2021] [Accepted: 05/14/2021] [Indexed: 12/20/2022]
Abstract
BACKGROUND AND PURPOSE The hippocampus is a frequent focus of quantitative neuroimaging research, and structural hippocampal alterations are related to multiple neurocognitive disorders. An increasing number of neuroimaging studies are focusing on hippocampal subfield regional involvement in these disorders using various automated segmentation approaches. Direct comparisons among these approaches are limited. The purpose of this study was to compare the agreement between two automated hippocampal segmentation algorithms in an adult population. MATERIALS AND METHODS We compared the results of 2 automated segmentation algorithms for hippocampal subfields (FreeSurfer v6.0 and volBrain) within a single imaging data set from adults (n = 176, 89 women) across a wide age range (20-79 years). Brain MR imaging was acquired on a single 3T scanner as part of the IXI Brain Development Dataset and included T1- and T2-weighted MR images. We also examined subfield volumetric differences related to age and sex and the impact of different intracranial volume and total hippocampal volume normalization methods. RESULTS Estimated intracranial volume and total hippocampal volume of both protocols were strongly correlated (r = 0.93 and 0.9, respectively; both P < .001). Hippocampal subfield volumes were correlated (ranging from r = 0.42 for the subiculum to r = 0.78 for the cornu ammonis [CA]1, all P < .001). However, absolute volumes were significantly different between protocols. volBrain produced larger CA1 and CA4-dentate gyrus and smaller CA2-CA3 and subiculum volumes compared with FreeSurfer v6.0. Regional age- and sex-related differences in subfield volumes were qualitatively and quantitatively different depending on segmentation protocol and intracranial volume/total hippocampal volume normalization method. CONCLUSIONS The hippocampal subfield volume relationship to demographic factors and disease states should undergo nuanced interpretation, especially when considering different segmentation protocols.
Collapse
Affiliation(s)
- A Samara
- From the Department of Psychiatry (A.S., Z.L., T.H.), Washington University School of Medicine, St. Louis, Missouri
| | - C A Raji
- From the Department of Psychiatry (A.S., Z.L., T.H.), Washington University School of Medicine, St. Louis, Missouri
- Mallinckrodt Institute of Radiology (C.A.R., T.H.), Washington University School of Medicine, St. Louis, Missouri
- Department of Neurology (C.A.R., T.H.), Washington University School of Medicine, St. Louis, Missouri
| | - Z Li
- From the Department of Psychiatry (A.S., Z.L., T.H.), Washington University School of Medicine, St. Louis, Missouri
- Department of Psychological and Brain Sciences (Z.L.), Washington University School of Medicine, St. Louis, Missouri
| | - T Hershey
- From the Department of Psychiatry (A.S., Z.L., T.H.), Washington University School of Medicine, St. Louis, Missouri
- Mallinckrodt Institute of Radiology (C.A.R., T.H.), Washington University School of Medicine, St. Louis, Missouri
- Department of Neurology (C.A.R., T.H.), Washington University School of Medicine, St. Louis, Missouri
| |
Collapse
|
5
|
Raji CA, Eyre H, Wei SH, Bredesen DE, Moylan S, Law M, Small G, Thompson PM, Friedlander RM, Silverman DH, Baune BT, Hoang TA, Salamon N, Toga AW, Vernooij MW. Hot Topics in Research: Preventive Neuroradiology in Brain Aging and Cognitive Decline. AJNR Am J Neuroradiol 2015; 36:1803-9. [PMID: 26045577 DOI: 10.3174/ajnr.a4409] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2015] [Accepted: 02/23/2015] [Indexed: 01/26/2023]
Abstract
Preventive neuroradiology is a new concept supported by growing literature. The main rationale of preventive neuroradiology is the application of multimodal brain imaging toward early and subclinical detection of brain disease and subsequent preventive actions through identification of modifiable risk factors. An insightful example of this is in the area of age-related cognitive decline, mild cognitive impairment, and dementia with potentially modifiable risk factors such as obesity, diet, sleep, hypertension, diabetes, depression, supplementation, smoking, and physical activity. In studying this link between lifestyle and cognitive decline, brain imaging markers may be instrumental as quantitative measures or even indicators of early disease. The purpose of this article is to provide an overview of the major studies reflecting how lifestyle factors affect the brain and cognition aging. In this hot topics review, we will specifically focus on obesity and physical activity.
Collapse
Affiliation(s)
- C A Raji
- From the Departments of Radiology (C.A.R., S.H.W., T.A.H., N.S.)
| | - H Eyre
- Psychiatry (H.E., G.S.) Discipline of Psychiatry (H.E., B.T.B.), University of Adelaide, Adelaide, South Australia, Australia
| | - S H Wei
- From the Departments of Radiology (C.A.R., S.H.W., T.A.H., N.S.)
| | | | - S Moylan
- School of Medicine (S.M.), Deakin University, Geelong, Victoria, Australia
| | - M Law
- Department of Radiology (M.L.)
| | | | - P M Thompson
- Laboratory of Neuroimaging (P.M.T., A.W.T.), University of Southern California, Los Angeles, California
| | - R M Friedlander
- Department of Neurosurgery (R.M.F.), University of Pittsburgh, Pittsburgh, Pennsylvania
| | - D H Silverman
- Nuclear Medicine (D.H.S.), University of California at Los Angeles Medical Center, University of California at Los Angeles, Los Angeles, California
| | - B T Baune
- Discipline of Psychiatry (H.E., B.T.B.), University of Adelaide, Adelaide, South Australia, Australia
| | - T A Hoang
- From the Departments of Radiology (C.A.R., S.H.W., T.A.H., N.S.)
| | - N Salamon
- From the Departments of Radiology (C.A.R., S.H.W., T.A.H., N.S.)
| | - A W Toga
- Laboratory of Neuroimaging (P.M.T., A.W.T.), University of Southern California, Los Angeles, California
| | - M W Vernooij
- Departments of Radiology and Epidemiology (M.W.V.), Erasmus University Medical Center, Rotterdam, the Netherlands
| |
Collapse
|
6
|
Braskie MN, Boyle CP, Rajagopalan P, Gutman BA, Toga AW, Raji CA, Tracy RP, Kuller LH, Becker JT, Lopez OL, Thompson PM. Physical activity, inflammation, and volume of the aging brain. Neuroscience 2014; 273:199-209. [PMID: 24836855 PMCID: PMC4076831 DOI: 10.1016/j.neuroscience.2014.05.005] [Citation(s) in RCA: 41] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2014] [Revised: 04/23/2014] [Accepted: 05/02/2014] [Indexed: 01/06/2023]
Abstract
Physical activity influences inflammation, and both affect brain structure and Alzheimer's disease (AD) risk. We hypothesized that older adults with greater reported physical activity intensity and lower serum levels of the inflammatory marker tumor necrosis factor α (TNFα) would have larger regional brain volumes on subsequent magnetic resonance imaging (MRI) scans. In 43 cognitively intact older adults (79.3±4.8 years) and 39 patients with AD (81.9±5.1 years at the time of MRI) participating in the Cardiovascular Health Study, we examined year-1 reported physical activity intensity, year-5 blood serum TNFα measures, and year-9 volumetric brain MRI scans. We examined how prior physical activity intensity and TNFα related to subsequent total and regional brain volumes. Physical activity intensity was measured using the modified Minnesota Leisure Time Physical Activities questionnaire at year 1 of the study, when all subjects included here were cognitively intact. Stability of measures was established for exercise intensity over 9 years and TNFα over 3 years in a subset of subjects who had these measurements at multiple time points. When considered together, more intense physical activity intensity and lower serum TNFα were both associated with greater total brain volume on follow-up MRI scans. TNFα, but not physical activity, was associated with regional volumes of the inferior parietal lobule, a region previously associated with inflammation in AD patients. Physical activity and TNFα may independently influence brain structure in older adults.
Collapse
Affiliation(s)
- M N Braskie
- Imaging Genetics Center, Institute for Neuroimaging and Informatics, Dept. of Neurology, Keck/USC School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - C P Boyle
- Imaging Genetics Center, Institute for Neuroimaging and Informatics, Dept. of Neurology, Keck/USC School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - P Rajagopalan
- Imaging Genetics Center, Institute for Neuroimaging and Informatics, Dept. of Neurology, Keck/USC School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - B A Gutman
- Imaging Genetics Center, Institute for Neuroimaging and Informatics, Dept. of Neurology, Keck/USC School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - A W Toga
- Imaging Genetics Center, Institute for Neuroimaging and Informatics, Dept. of Neurology, Keck/USC School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - C A Raji
- Department of Radiology, University of California Los Angeles School of Medicine, Los Angeles, CA, USA
| | - R P Tracy
- Departments of Pathology, Biochemistry, and Center for Clinical and Translational Science, University of Vermont, Burlington, VT, USA
| | - L H Kuller
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - J T Becker
- Departments of Neurology, Psychiatry, and Psychology, University of Pittsburgh, Pittsburgh, PA, USA
| | - O L Lopez
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA, USA
| | - P M Thompson
- Imaging Genetics Center, Institute for Neuroimaging and Informatics, Dept. of Neurology, Keck/USC School of Medicine, University of Southern California, Los Angeles, CA, USA; Depts. of Psychiatry, Engineering, Radiology, & Ophthalmology, Keck/USC School of Medicine, University of Southern California, Los Angeles, CA, USA.
| |
Collapse
|