Precision Brain Morphometry Using Cluster Scanning.

Autor: Elliott ML; Department of Psychology, Center for Brain Science, Harvard University, Cambridge, MA 02138, USA., Nielsen JA; Department of Psychology, Neuroscience Center, Brigham Young University, Provo, UT, 84602, USA., Hanford LC; Department of Psychology, Center for Brain Science, Harvard University, Cambridge, MA 02138, USA., Hamadeh A; Baylor College of Medicine, Houston, TX 77030., Hilbert T; Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland.; Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.; LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland., Kober T; Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland.; Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.; LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland., Dickerson BC; Frontotemporal Disorders Unit.; Alzheimer's Disease Research Center.; Athinoula A. Martinos Center for Biomedical Imaging.; Department of Neurology, Massachusetts General Hospital & Harvard Medical School.; Department of Psychiatry, Massachusetts General Hospital & Harvard Medical School, Charlestown, MA 02129, USA., Hyman BT; Alzheimer's Disease Research Center.; Department of Neurology, Massachusetts General Hospital & Harvard Medical School., Mair RW; Department of Psychology, Center for Brain Science, Harvard University, Cambridge, MA 02138, USA.; Athinoula A. Martinos Center for Biomedical Imaging., Eldaief MC; Frontotemporal Disorders Unit.; Alzheimer's Disease Research Center.; Department of Neurology, Massachusetts General Hospital & Harvard Medical School.; Department of Psychiatry, Massachusetts General Hospital & Harvard Medical School, Charlestown, MA 02129, USA., Buckner RL; Department of Psychology, Center for Brain Science, Harvard University, Cambridge, MA 02138, USA.; Alzheimer's Disease Research Center.; Athinoula A. Martinos Center for Biomedical Imaging.; Department of Psychiatry, Massachusetts General Hospital & Harvard Medical School, Charlestown, MA 02129, USA.
Jazyk: angličtina
Zdroj: MedRxiv : the preprint server for health sciences [medRxiv] 2023 Dec 28. Date of Electronic Publication: 2023 Dec 28.
DOI: 10.1101/2023.12.23.23300492
Abstrakt: Measurement error limits the statistical power to detect group differences and longitudinal change in structural MRI morphometric measures (e.g., hippocampal volume, prefrontal thickness). Recent advances in scan acceleration enable extremely fast T 1 -weighted scans (~1 minute) to achieve morphometric errors that are close to the errors in longer traditional scans. As acceleration allows multiple scans to be acquired in rapid succession, it becomes possible to pool estimates to increase measurement precision, a strategy known as "cluster scanning." Here we explored brain morphometry using cluster scanning in a test-retest study of 40 individuals (12 younger adults, 18 cognitively unimpaired older adults, and 10 adults diagnosed with mild cognitive impairment or Alzheimer's Dementia). Morphometric errors from a single compressed sensing (CS) 1.0mm scan with 6x acceleration (CSx6) were, on average, 12% larger than a traditional scan using the Alzheimer's Disease Neuroimaging Initiative (ADNI) protocol. Pooled estimates from four clustered CSx6 acquisitions led to errors that were 34% smaller than ADNI despite having a shorter total acquisition time. Given a fixed amount of time, a gain in measurement precision can thus be achieved by acquiring multiple rapid scans instead of a single traditional scan. Errors were further reduced when estimates were pooled from eight CSx6 scans (51% smaller than ADNI). Neither pooling across a break nor pooling across multiple scan resolutions boosted this benefit. We discuss the potential of cluster scanning to improve morphometric precision, boost statistical power, and produce more sensitive disease progression biomarkers.
Competing Interests: Disclosures Tom Hilbert and Tobias Kober are employed by Siemens Healthineers International AG, Switzerland. The authors have no other conflicts of interest to report.
Databáze: MEDLINE
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