Evaluation of software tools for automated identification of neuroanatomical structures in quantitative β-amyloid PET imaging to diagnose Alzheimer's disease.
Introduction: For regional quantification of nuclear brain imaging data, defining volumes of interest (VOIs) by hand is still the gold standard. As this procedure is time-consuming and operator-dependent, a variety of software tools for automated identification of neuroanatomical structures were dev...
| Publicado en: | European Journal of Nuclear Medicine & Molecular Imaging Vol. 43; no. 6; pp. 1077 - 1088 |
|---|---|
| Autores principales: | , , , , , , , , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Jun2016
|
| 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=114818191&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 114818191 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 16197070 NPC jtl: European Journal of Nuclear Medicine & Molecular Imaging issn: 16197070 maglogo: N pubinfo: dt: Jun2016 vid: 43 iid: 6 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 114818191 10.1007/s00259-015-3300-6 114818191 ppf: 1077 ppct: 11 formats: fmt: @attributes: type: P tig: atl: Evaluation of software tools for automated identification of neuroanatomical structures in quantitative β-amyloid PET imaging to diagnose Alzheimer's disease. aug: au: Tuszynski, Tobias Rullmann, Michael Luthardt, Julia Butzke, Daniel Tiepolt, Solveig Gertz, Hermann-Josef Hesse, Swen Seese, Anita Lobsien, Donald Sabri, Osama Barthel, Henryk affil: Department of Nuclear Medicine, Leipzig University Medical Centre, Liebigstraße 18 04103 Leipzig Germany sug: ab: Introduction: For regional quantification of nuclear brain imaging data, defining volumes of interest (VOIs) by hand is still the gold standard. As this procedure is time-consuming and operator-dependent, a variety of software tools for automated identification of neuroanatomical structures were developed. As the quality and performance of those tools are poorly investigated so far in analyzing amyloid PET data, we compared in this project four algorithms for automated VOI definition (HERMES Brass, two PMOD approaches, and FreeSurfer) against the conventional method. We systematically analyzed florbetaben brain PET and MRI data of ten patients with probable Alzheimer's dementia (AD) and ten age-matched healthy controls (HCs) collected in a previous clinical study. Methods: VOIs were manually defined on the data as well as through the four automated workflows. Standardized uptake value ratios (SUVRs) with the cerebellar cortex as a reference region were obtained for each VOI. SUVR comparisons between ADs and HCs were carried out using Mann-Whitney-U tests, and effect sizes (Cohen's d) were calculated. SUVRs of automatically generated VOIs were correlated with SUVRs of conventionally derived VOIs (Pearson's tests). Results: The composite neocortex SUVRs obtained by manually defined VOIs were significantly higher for ADs vs. HCs ( p=0.010, d=1.53). This was also the case for the four tested automated approaches which achieved effect sizes of d=1.38 to d=1.62. SUVRs of automatically generated VOIs correlated significantly with those of the hand-drawn VOIs in a number of brain regions, with regional differences in the degree of these correlations. Best overall correlation was observed in the lateral temporal VOI for all tested software tools ( r=0.82 to r=0.95, p<0.001). Conclusion: Automated VOI definition by the software tools tested has a great potential to substitute for the current standard procedure to manually define VOIs in β-amyloid PET data analysis. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
|---|