Analysis of heterogeneity in T$ 2$-weighted MR images can differentiate pseudoprogression from progression in glioblastomaReport as inadecuate


Analysis of heterogeneity in T$ 2$-weighted MR images can differentiate pseudoprogression from progression in glioblastoma


Analysis of heterogeneity in T$ 2$-weighted MR images can differentiate pseudoprogression from progression in glioblastoma - Download this document for free, or read online. Document in PDF available to download.

Publication Date: 2017-05-17

Journal Title: PLoS ONE

Publisher: Public Library of Science (PLoS)

Volume: 12

Issue: 5

Number: e0176528

Language: English

Type: Article

This Version: VoR

Metadata: Show full item record

Citation: Booth, T., Larkin, T., Yuan, Y., Kettunen, M., Dawson, S., Scoffings, D., Canuto, H., et al. (2017). Analysis of heterogeneity in T$_2$-weighted MR images can differentiate pseudoprogression from progression in glioblastoma. PLoS ONE, 12 (5. e0176528)https://doi.org/10.1371/journal.pone.0176528

Abstract: $\textbf{Purpose}$ To develop an image analysis technique that distinguishes pseudoprogression from true progression by analyzing tumour heterogeneity in $T_2$-weighted images using topological descriptors of image heterogeneity called Minkowski functionals (MFs).$\textbf{Methods}$ Using a retrospective patient cohort ($n$ = 50), and blinded to treatment response outcome, unsupervised feature estimation was performed to investigate MFs for the presence of outliers, potential confounders, and sensitivity to treatment response. The progression and pseudoprogression groups were then unblinded and supervised feature selection was performed using MFs, size and signal intensity features. A support vector machine model was obtained and evaluated using a prospective test cohort.$\textbf{Results}$ The model gave a classification accuracy, using a combination of MFs and size features, of more than 85% in both retrospective and prospective datasets. A different feature selection method (Random Forest) and classifier (Lasso) gave the same results. Although not apparent to the reporting radiologist, the $T_2$-weighted hyperintensity phenotype of those patients with progression was heterogeneous, large and frond-like when compared to those with pseudoprogression.$\textbf{Conclusion}$ Analysis of heterogeneity, in $T_2$-weighted MR images, which are acquired routinely in the clinic, has the potential to detect an earlier treatment response allowing an early change in treatment strategy. Prospective validation of this technique in larger datasets is required.

Sponsorship: Funded by Medical Research Council/ Royal College of Radiologists (UK) Clinical Research Fellowship (G1000265); Cancer Research UK Clinical Research Fellowship; Addenbrookes Charitable Trust Award to TCB. Cancer Research UK Programme grant (C197/ A3514) to KMB.

Embargo Lift Date: 2100-01-01

Identifiers:

External DOI: https://doi.org/10.1371/journal.pone.0176528

This record's URL: https://www.repository.cam.ac.uk/handle/1810/263831



Rights: Attribution 4.0 International

Licence URL: http://creativecommons.org/licenses/by/4.0/





Author: Booth, TCLarkin, TJYuan, YKettunen, MIDawson, SNScoffings, DCanuto, HCVowler, SLKirschenlohr, HHobson, MPMarkowetz, FJefferies, S

Source: https://www.repository.cam.ac.uk/handle/1810/263831



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