Comparing two artificial intelligence software packages for normative brain volumetry in memory clinic imaging.
Purpose: To compare two artificial intelligence software packages performing normative brain volumetry and explore whether they could differently impact dementia diagnostics in a clinical context. Methods: Sixty patients (20 Alzheimer's disease, 20 frontotemporal dementia, 20 mild cognitive impairme...
| Publicado en: | Neuroradiology Vol. 64; no. 7; pp. 1359 - 1367 |
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| Autores principales: | , , , , , , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
Springer Nature
Jul2022
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=157319136&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 157319136 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 00283940 NYZ jtl: Neuroradiology issn: 00283940 maglogo: N pubinfo: dt: Jul2022 vid: 64 iid: 7 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 157319136 157319136 157319136 10.1007/s00234-022-02898-w 157319136 ppf: 1359 ppct: 8 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Comparing two artificial intelligence software packages for normative brain volumetry in memory clinic imaging. aug: au: Zaki, Lara A. M. Vernooij, Meike W. Smits, Marion Tolman, Christine Papma, Janne M. Visser, Jacob J. Steketee, Rebecca M. E. affil: Department of Radiology and Nuclear Medicine, Erasmus MC, University Medical Center Rotterdam, PO Box 2040, 3000 CA, Rotterdam, the Netherlands sug: subj: Dementia Diagnosis Artificial Intelligence Software Brain Mapping Methods Memory Human Alzheimer's Disease Cognition Disorders Retrospective Design Magnetic Resonance Imaging Descriptive Statistics Comparative Studies ab: Purpose: To compare two artificial intelligence software packages performing normative brain volumetry and explore whether they could differently impact dementia diagnostics in a clinical context. Methods: Sixty patients (20 Alzheimer's disease, 20 frontotemporal dementia, 20 mild cognitive impairment) and 20 controls were included retrospectively. One MRI per subject was processed by software packages from two proprietary manufacturers, producing two quantitative reports per subject. Two neuroradiologists assigned forced-choice diagnoses using only the normative volumetry data in these reports. They classified the volumetric profile as "normal," or "abnormal", and if "abnormal," they specified the most likely dementia subtype. Differences between the packages' clinical impact were assessed by comparing (1) agreement between diagnoses based on software output; (2) diagnostic accuracy, sensitivity, and specificity; and (3) diagnostic confidence. Quantitative outputs were also compared to provide context to any diagnostic differences. Results: Diagnostic agreement between packages was moderate, for distinguishing normal and abnormal volumetry (K =.41–.43) and for specific diagnoses (K =.36–.38). However, each package yielded high inter-observer agreement when distinguishing normal and abnormal profiles (K =.73–.82). Accuracy, sensitivity, and specificity were not different between packages. Diagnostic confidence was different between packages for one rater. Whole brain intracranial volume output differed between software packages (10.73%, p <.001), and normative regional data interpreted for diagnosis correlated weakly to moderately (rs =.12–.80). Conclusion: Different artificial intelligence software packages for quantitative normative assessment of brain MRI can produce distinct effects at the level of clinical interpretation. Clinics should not assume that different packages are interchangeable, thus recommending internal evaluation of packages before adoption. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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