Conventional MRI radiomics in patients with suspected early- or pseudo-progression
Author(s) -
Alexandre BaniSadr,
Omer Eker,
Lise-Prune Berner,
Roxana Améli,
M. Hermier,
Marc Barritault,
David Meyronet,
Jacques Guyotat,
Emmanuel Jouanneau,
Jérôme Honnorat,
François Ducray,
Yves Berthezène
Publication year - 2019
Publication title -
neuro-oncology advances
Language(s) - English
Resource type - Journals
ISSN - 2632-2498
DOI - 10.1093/noajnl/vdz019
Subject(s) - medicine , radiomics , brier score , hazard ratio , univariate analysis , univariate , oncology , progression free survival , nuclear medicine , multivariate analysis , radiology , overall survival , multivariate statistics , confidence interval , machine learning , computer science
Background After radiochemotherapy, 30% of patients with early worsening MRI experience pseudoprogression (Psp) which is not distinguishable from early progression (EP). We aimed to assess the diagnostic value of radiomics in patients with suspected EP or Psp. Methods Radiomics features (RF) of 76 patients (53 EP and 23 Psp) retrospectively identified were extracted from conventional MRI based on four volumes-of-interest. Subjects were randomly assigned into training and validation groups. Classification model (EP versus Psp) consisted of a random forest algorithm after univariate filtering. Overall (OS) and progression-free survivals (PFS) were predicted using a semi-supervised principal component analysis, and forecasts were evaluated using C-index and integrated Brier scores (IBS). Results Using 11 RFs, radiomics classified patients with 75.0% and 76.0% accuracy, 81.6% and 94.1% sensitivity, 50.0% and 37.5% specificity, respectively, in training and validation phases. Addition of MGMT promoter status improved accuracy to 83% and 79.2%, and specificity to 63.6% and 75%. OS model included 14 RFs and stratified low- and high-risk patients both in the training (hazard ratio [HR], 3.63; P = .002) and the validation (HR, 3.76; P = .001) phases. Similarly, PFS model stratified patients during training (HR, 2.58; P = .005) and validation (HR, 3.58; P = .004) phases using 5 RF. OS and PFS forecasts had C-index of 0.65 and 0.69, and IBS of 0.122 and 0.147, respectively. Conclusions Conventional MRI radiomics has promising diagnostic value, especially when combined with MGMT promoter status, but with moderate specificity. In addition, our results suggest a potential for predicting OS and PFS.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom