Stroke population–specific neuroanatomical CT-MRI brain atlas.
Purpose: Development of a freely available stroke population–specific anatomical CT/MRI atlas with a reliable normalisation pipeline for clinical CT. Methods: By reviewing CT scans in suspected stroke patients and filtering the AIBL MRI database, respectively, we collected 50 normal-for-age CT and M...
| Publicado en: | Neuroradiology Vol. 64; no. 8; pp. 1557 - 1568 |
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| Autores principales: | , , , , , , , |
| Formato: | diagnostic images research tables/charts Journal Article |
| Publicado: |
Springer Nature
Aug2022
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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=157889441&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 157889441 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 00283940 NYZ jtl: Neuroradiology issn: 00283940 maglogo: N pubinfo: dt: Aug2022 vid: 64 iid: 8 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 157889441 157889441 157889441 10.1007/s00234-021-02875-9 157889441 ppf: 1557 ppct: 11 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Stroke population–specific neuroanatomical CT-MRI brain atlas. aug: au: Kaffenberger, Tina Venkatraman, Vijay Steward, Chris Thijs, Vincent N. Bernhardt, Julie Desmond, Patricia M. Campbell, Bruce C. V. Yassi, Nawaf affil: The Florey Institute of Neuroscience and Mental Health, University of Melbourne, 245 Burgundy Street, 3084, Heidelberg, VIC, Australia sug: subj: Cerebral Ischemia Pathology Stroke Diagnosis Diagnostic Imaging Brain Radiography Brain Anatomy and Histology Human Tomography, X-Ray Computed Magnetic Resonance Imaging Aged Male Female Algorithms Cerebral Cortex Radiography Aged: 65+ years Male Female ab: Purpose: Development of a freely available stroke population–specific anatomical CT/MRI atlas with a reliable normalisation pipeline for clinical CT. Methods: By reviewing CT scans in suspected stroke patients and filtering the AIBL MRI database, respectively, we collected 50 normal-for-age CT and MRI scans to build a standard-resolution CT template and a high-resolution MRI template. The latter was manually segmented into anatomical brain regions. We then developed and validated a MRI to CT registration pipeline to align the MRI atlas onto the CT template. Finally, we developed a CT-to-CT-normalisation pipeline and tested its reliability by calculating Dice coefficient (Dice) and Average Hausdorff Distance (AHD) for predefined areas in 100 CT scans from ischaemic stroke patients. Results: The resulting CT/MRI templates were age and sex matched to a general stroke population (median age 71.9 years (62.1–80.2), 60% male). Specifically, this accounts for relevant structural changes related to aging, which may affect registration. Applying the validated MRI to CT alignment (Dice > 0.78, Average Hausdorff Distance < 0.59 mm) resulted in our final CT-MRI atlas. The atlas has 52 manually segmented regions and covers the whole brain. The alignment of four cortical and subcortical brain regions with our CT-normalisation pipeline was reliable for small/medium/large infarct lesions (Dice coefficient > 0.5). Conclusion: The newly created CT-MRI brain atlas has the potential to standardise stroke lesion segmentation. Together with the automated normalisation pipeline, it allows analysis of existing and new datasets to improve prediction tools for stroke patients (free download at https://forms.office.com/r/v4t3sWfbKs). pubtype: Academic Journal doctype: diagnostic images research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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