Wavelet-based calculation of cerebral angiographic data from time-resolved CT perfusion acquisitions.
Objectives: To evaluate a new approach for reconstructing angiographic images by application of wavelet transforms on CT perfusion data.Methods: Fifteen consecutive patients with suspected stroke were examined with a multi-detector CT acquiring 32 dynamic phases (∆t = 1.5s) of 99 slices (total slab...
| Publicado en: | European Radiology Vol. 25; no. 8; pp. 2354 - 2362 |
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| Autores principales: | , , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Aug2015
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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=109594952&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 109594952 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 09387994 NPH jtl: European Radiology issn: 09387994 maglogo: N pubinfo: dt: Aug2015 vid: 25 iid: 8 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 109594952 103687096 NLM25716940 2013091319 10.1007/s00330-015-3651-1 NLM25716940 109594952 ppf: 2354 ppct: 8 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Wavelet-based calculation of cerebral angiographic data from time-resolved CT perfusion acquisitions. aug: au: Havla, Lukas Thierfelder, Kolja M Beyer, Sebastian E Sommer, Wieland H Dietrich, Olaf sug: ab: Objectives: To evaluate a new approach for reconstructing angiographic images by application of wavelet transforms on CT perfusion data.Methods: Fifteen consecutive patients with suspected stroke were examined with a multi-detector CT acquiring 32 dynamic phases (∆t = 1.5s) of 99 slices (total slab thickness 99mm) at 80kV/200mAs. Thirty-five mL of iomeprol-350 was injected (flow rate = 4.5mL/s). Angiographic datasets were calculated after initial rigid-body motion correction using (a) temporally filtered maximum intensity projections (tMIP) and (b) the wavelet transform (Paul wavelet, order 1) of each voxel time course. The maximum of the wavelet-power-spectrum was defined as the angiographic signal intensity. The contrast-to-noise ratio (CNR) of 18 different vessel segments was quantified and two blinded readers rated the images qualitatively using 5pt Likert scales.Results: The CNR for the wavelet angiography (501.8 ± 433.0) was significantly higher than for the tMIP approach (55.7 ± 29.7, Wilcoxon test p < 0.00001). Image quality was rated to be significantly higher (p < 0.001) for the wavelet angiography with median scores of 4/4 (reader 1/reader 2) than the tMIP (scores of 3/3).Conclusions: The proposed calculation approach for angiography data using temporal wavelet transforms of intracranial CT perfusion datasets provides higher vascular contrast and intrinsic removal of non-enhancing structures such as bone.Key Points: • Angiographic images calculated with the proposed wavelet-based approach show significantly improved contrast-to-noise ratio. • CT perfusion-based wavelet angiography is an alternative method for vessel visualization. • Provides intrinsic removal of non-enhancing structures such as bone. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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