Noise suppression of proton magnetic resonance spectroscopy improves paediatric brain tumour classification
Author
Zhao, TeddyGrist, James T
Auer, Dorothee P
Avula, Shivaram
Bailey, Simon
Davies, Nigel P
Grundy, Richard G
Khan, Omar
MacPherson, Lesley
Morgan, Paul S
Pizer, Barry
Rose, Heather E L
Sun, Yu
Wilson, Martin
Worthington, Lara
Arvanitis, Theodoros N
Peet, Andrew C
Publication date
2024-03-17
Metadata
Show full item recordAbstract
Proton magnetic resonance spectroscopy (1 H-MRS) is increasingly used for clinical brain tumour diagnosis, but suffers from limited spectral quality. This retrospective and comparative study aims at improving paediatric brain tumour classification by performing noise suppression on clinical 1 H-MRS. Eighty-three/forty-two children with either an ependymoma (ages 4.6 ± 5.3/9.3 ± 5.4), a medulloblastoma (ages 6.9 ± 3.5/6.5 ± 4.4), or a pilocytic astrocytoma (8.0 ± 3.6/6.3 ± 5.0), recruited from four centres across England, were scanned with 1.5T/3T short-echo-time point-resolved spectroscopy. The acquired raw 1 H-MRS was quantified by using Totally Automatic Robust Quantitation in NMR (TARQUIN), assessed by experienced spectroscopists, and processed with adaptive wavelet noise suppression (AWNS). Metabolite concentrations were extracted as features, selected based on multiclass receiver operating characteristics, and finally used for identifying brain tumour types with supervised machine learning. The minority class was oversampled through the synthetic minority oversampling technique for comparison purposes. Post-noise-suppression 1 H-MRS showed significantly elevated signal-to-noise ratios (P < .05, Wilcoxon signed-rank test), stable full width at half-maximum (P > .05, Wilcoxon signed-rank test), and significantly higher classification accuracy (P < .05, Wilcoxon signed-rank test). Specifically, the cross-validated overall and balanced classification accuracies can be improved from 81% to 88% overall and 76% to 86% balanced for the 1.5T cohort, whilst for the 3T cohort they can be improved from 62% to 76% overall and 46% to 56%, by applying Naïve Bayes on the oversampled 1 H-MRS. The study shows that fitting-based signal-to-noise ratios of clinical 1 H-MRS can be significantly improved by using AWNS with insignificantly altered line width, and the post-noise-suppression 1 H-MRS may have better diagnostic performance for paediatric brain tumours.Citation
Zhao T, Grist JT, Auer DP, Avula S, Bailey S, Davies NP, Grundy RG, Khan O, MacPherson L, Morgan PS, Pizer B, Rose HEL, Sun Y, Wilson M, Worthington L, Arvanitis TN, Peet AC. Noise suppression of proton magnetic resonance spectroscopy improves paediatric brain tumour classification. NMR Biomed. 2024 Jun;37(6):e5129. doi: 10.1002/nbm.5129. Epub 2024 Mar 17.Type
ArticleAdditional Links
http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1099-1492DOI
10.1002/nbm.5129PMID
38494431Journal
NMR in BiomedicinePublisher
Wileyae974a485f413a2113503eed53cd6c53
10.1002/nbm.5129