ArticleMagma (New York, N.Y.)2021
Effect of MRI acquisition acceleration via compressed sensing and parallel imaging on brain volumetry.
Article in Magma (New York, N.Y.), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.
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Who cites it
16 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Commercial volumetric MRI reporting tools in multiple sclerosis: a systematic review of the evidence.Neuroradiology · 2023Pooled it
- Validation of Compressed Sensing Accelerated Magnetization Prepared Rapid Acquisition Gradient Echo for Fast and Reliable Brain Volume Measurement.Tomography (Ann Arbor, Mich.) · 2026Article
- Mitigating the Impact of MR Sequence Parameters: Increasing the Robustness of DL-Based Cortical Thickness Estimates.Human brain mapping · 2026Article
- Precision estimates of longitudinal brain aging capture unexpected individual differences in one year.Nature communications · 2026Article
- Easy-to-use and easy-to-interpret quality control of 3D gradient echo T1-weighted MR acquisition sequences for improved test-retest stability of MRI-based hippocampus volumetry.Journal of Alzheimer's disease : JAD · 2025Article
- Voxel-Based Morphometry of Progressive Supranuclear Palsy Using a 3D Fast Low-angle Shot Localizer Image: A Comparison with Magnetization-Prepared Rapid Gradient Echo.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2025Article
- Volumetry of Selected Brain Regions-Can We Compare MRI Examinations of Different Manufacturers and Field Strengths?Clinical neuroradiology · 2025Article
- Voxel-based Morphometry of Alzheimer's Disease Using a Localizer Image: A Comparative Study with Magnetization Prepared Rapid Acquisition with Gradient Echo.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2025Article
- AI-Assisted Compressed Sensing Enables Faster Brain MRI for the Elderly: Image Quality and Diagnostic Equivalence with Conventional Imaging.International journal of general medicine · 2025Article
- Normal cohorts in automated brain atrophy estimation: how many healthy subjects to include?European radiology · 2024Article
- Brain and Ventricle Volume Alterations in Idiopathic Normal Pressure Hydrocephalus Determined by Artificial Intelligence-Based MRI Volumetry.Diagnostics (Basel, Switzerland) · 2024Article
- Compressed Sensitivity Encoding Artificial Intelligence Accelerates Brain Metastasis Imaging by Optimizing Image Quality and Reducing Scan Time.AJNR. American journal of neuroradiology · 2024Article
- Compressed sensing magnetic resonance imaging (CS-MRI) diagnosis of rotator cuff tears.American journal of translational research · 2024Article
- Precision brain morphometry using cluster scanning.Imaging neuroscience (Cambridge, Mass.) · 2024Article
- Brain morphometry in older adults with and without dementia using extremely rapid structural scans.NeuroImage · 2023Article
- Brain Volume Changes after COVID-19 Compared to Healthy Controls by Artificial Intelligence-Based MRI Volumetry.Diagnostics (Basel, Switzerland) · 2023Article
Corrections and comments
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesTo investigate the effect of compressed SENSE (CS), an acceleration technique combining parallel imaging and compressed sensing, on potential bias and precision of brain volumetry and evaluate it in the context of normative brain volumetry. MATERIALS AND
methodsIn total, 171 scans from scan-rescan experiments on three healthy subjects were analyzed. Each subject received 3D-T1-weighted brain MRI scans at increasing degrees of acceleration (CS-factor = 1/4/8/12/16/20/32). Single-scan acquisition times ranged from 00:41 min (CS-factor = 32) to 21:52 min (CS-factor = 1). Brain segmentation and volumetry was performed using two different software tools: md.brain, a proprietary software based on voxel-based morphometry, and FreeSurfer, an open-source software based on surface-based morphometry. Four sub-volumes were analyzed: brain parenchyma (BP), total gray matter, total white matter, and cerebrospinal fluid (CSF). Coefficient of variation (CoV) of the repeated measurements as a measure of intra-subject reliability was calculated. Intraclass correlation coefficient (ICC) with regard to increasing CS-factor was calculated as another measure of reliability. Noise-to-contrast ratio as a measure of image quality was calculated for each dataset to analyze the association between acceleration factor, noise and volumetric brain measurements.
resultsFor all sub-volumes, there is a systematic bias proportional to the CS-factor which is dependent on the utilized software and subvolume. Measured volumes deviated significantly from the reference standard (CS-factor = 1), e.g. ranging from 1 to 13% for BP. The CS-induced systematic bias is driven by increased image noise. Except for CSF, reliability of brain volumetry remains high, demonstrated by low CoV (< 1% for CS-factor up to 20) and good to excellent ICC for CS-factor up to 12.
conclusionCS-acceleration has a systematic biasing effect on volumetric brain measurements.
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