| Title |
MRI radiomics analysis of molecular alterations in low-grade gliomas
|
|---|---|
| Published in |
International Journal of Computer Assisted Radiology and Surgery, December 2017
|
| DOI | 10.1007/s11548-017-1691-5 |
| Pubmed ID | |
| Authors |
Ben Shofty, Moran Artzi, Dafna Ben Bashat, Gilad Liberman, Oz Haim, Alon Kashanian, Felix Bokstein, Deborah T. Blumenthal, Zvi Ram, Tal Shahar |
| Abstract |
Low-grade gliomas (LGG) are classified into three distinct groups based on their IDH1 mutation and 1p/19q codeletion status, each of which is associated with a different clinical expression. The genomic sub-classification of LGG requires tumor sampling via neurosurgical procedures. The aim of this study was to evaluate the radiomics approach for noninvasive classification of patients with LGG and IDH mutation, based on their 1p/19q codeletion status, by testing different classifiers and assessing the contribution of the different MR contrasts. Preoperative MRI scans of 47 patients diagnosed with LGG with IDH1-mutated tumors and a genetic analysis for 1p/19q deletion status were included in this study. A total of 152 features, including size, location and texture, were extracted from fluid-attenuated inversion recovery images, [Formula: see text]-weighted images (WI) and post-contrast [Formula: see text]. Classification was performed using 17 machine learning classifiers. Results were evaluated by a fivefold cross-validation analysis. Radiomic analysis differentiated tumors with 1p/19q intact ([Formula: see text]; astrocytomas) from those with 1p/19q codeleted ([Formula: see text]; oligodendrogliomas). Best classification was obtained using the Ensemble Bagged Trees classifier, with sensitivity [Formula: see text] 92%, specificity [Formula: see text] 83% and accuracy [Formula: see text] 87%, and with area under the curve [Formula: see text] 0.87. Tumors with 1p/19q intact were larger than those with 1p/19q codeleted ([Formula: see text] vs. [Formula: see text] cc, respectively; [Formula: see text]) and predominantly located to the left insula ([Formula: see text]). The proposed method yielded good discrimination between LGG with and without 1p/19q codeletion. Results from this study demonstrate the great potential of this method to aid decision-making in the clinical management of patients with LGG. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 1 | 50% |
| Members of the public | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 98 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 98 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 19 | 19% |
| Student > Ph. D. Student | 10 | 10% |
| Student > Postgraduate | 10 | 10% |
| Student > Doctoral Student | 9 | 9% |
| Student > Bachelor | 8 | 8% |
| Other | 18 | 18% |
| Unknown | 24 | 24% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 25 | 26% |
| Engineering | 10 | 10% |
| Computer Science | 5 | 5% |
| Biochemistry, Genetics and Molecular Biology | 4 | 4% |
| Agricultural and Biological Sciences | 3 | 3% |
| Other | 12 | 12% |
| Unknown | 39 | 40% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 15 September 2018.
All research outputs
#18,579,736
of 23,012,811 outputs
Outputs from International Journal of Computer Assisted Radiology and Surgery
#616
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Outputs of similar age
#328,891
of 440,666 outputs
Outputs of similar age from International Journal of Computer Assisted Radiology and Surgery
#5
of 7 outputs
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