Spatial fuzzy c-means thresholding for semiautomated calculation of percentage lung ventilated volume from hyperpolarized gas and 1 H MRI.
Purpose: To develop an image-processing pipeline for semiautomated (SA) and reproducible analysis of hyperpolarized gas lung ventilation and proton anatomical magnetic resonance imaging (MRI) scan pairs. To compare results from the software for total lung volume (TLV), ventilated volume (VV), and pe...
| Publicado en: | Journal of Magnetic Resonance Imaging Vol. 47; no. 3; pp. 640 - 647 |
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| Autores principales: | , , , , , |
| Formato: | research Journal Article |
| Publicado: |
Wiley-Blackwell
Mar2018
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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=128053068&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 128053068 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 10531807 O63 jtl: Journal of Magnetic Resonance Imaging issn: 10531807 maglogo: Y pubinfo: dt: Mar2018 vid: 47 iid: 3 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 128053068 128053068 NLM28681470 128053068 10.1002/jmri.25804 NLM28681470 128053068 ppf: 640 ppct: 7 formats: tig: atl: Spatial fuzzy c-means thresholding for semiautomated calculation of percentage lung ventilated volume from hyperpolarized gas and 1 H MRI. aug: au: Hughes, Paul J. C. Horn, Felix C. Collier, Guilhem J. Biancardi, Alberto Marshall, Helen Wild, Jim M. affil: Academic Unit of Radiology, University of Sheffield, Sheffield, South Yorkshire, UK sug: subj: Magnetic Resonance Imaging Methods Lung Diseases Image Processing, Computer Assisted Methods Lung Diseases Physiopathology Protons Human Reproducibility of Results Algorithms Young Adult Middle Age Lung Male Lung Physiopathology Aged Female Lung Volume Measurements Adult Validation Studies Comparative Studies Evaluation Research Multicenter Studies Clinical Assessment Tools Scales Middle Aged: 45-64 years Aged: 65+ years Adult: 19-44 years Male Female ab: Purpose: To develop an image-processing pipeline for semiautomated (SA) and reproducible analysis of hyperpolarized gas lung ventilation and proton anatomical magnetic resonance imaging (MRI) scan pairs. To compare results from the software for total lung volume (TLV), ventilated volume (VV), and percentage lung ventilated volume (%VV) calculation to the current manual "basic" method and a K-means segmentation method.Materials and Methods: Six patients were imaged with hyperpolarized 3 He and same-breath lung 1 H MRI at 1.5T and six other patients were scanned with hyperpolarized 129 Xe and separate-breath 1 H MRI. One expert observer and two users with experience in lung image segmentation carried out the image analysis. Spearman (R), Intraclass (ICC) correlations, Bland-Altman limits of agreement (LOA), and Dice Similarity Coefficients (DSC) between output lung volumes were calculated.Results: When comparing values of %VV, agreement between observers improved using the SA method (mean; R = 0.984, ICC = 0.980, LOA = 7.5%) when compared to the basic method (mean; R = 0.863, ICC = 0.873, LOA = 14.2%) nonsignificantly (pR = 0.25, pICC = 0.25, and pLOA = 0.50 respectively). DSC of VV and TLV masks significantly improved (P < 0.01) using the SA method (mean; DSCVV = 0.973, DSCTLV = 0.980) when compared to the basic method (mean; DSCVV = 0.947, DSCTLV = 0.957). K-means systematically overestimated %VV when compared to both basic (mean overestimation = 5.0%) and SA methods (mean overestimation = 9.7%), and had poor agreement with the other methods (mean ICC; K-means vs. basic = 0.685, K-means vs. SA = 0.740).Conclusion: A semiautomated image processing software was developed that improves interobserver agreement and correlation of lung ventilation volume percentage when compared to the currently used basic method and provides more consistent segmentations than the K-means method.Level Of Evidence: 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;47:640-646. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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