False-Positive Measurement at 2-Hydroxyglutarate MR Spectroscopy in Isocitrate Dehydrogenase Wild-Type Glioblastoma: A Multifactorial Analysis

Suh, Chong Hyun; Kim, Ho Sung; Paik, Wooyul; Choi, Changho; Ryu, Kyu-Hyung; Kim, Dong-Hyun; Woo, Dong‐Cheol; Park, Ji Eun; Jung, Sung Eun; Choi, Choong Gon; Kim, Sang Joon

doi:10.1148/radiol.2019182200

Cited by 33 publications

(23 citation statements)

References 24 publications

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“…While these methods appear to work well in a research setting, in the busy clinical environment, the spectroscopic imaging data are frequently uninterpretable due to artifact, patient motion, poor shimming, small voxel sizes, non-ideal tumor location, or presence of hemorrhage or calcification affecting measurements. Even in the setting of good quality spectra, reliable clinical implementation using 2-HG spectroscopy is further compounded by the recently described high false positive rate of over 20% using this technique in the best hands 7 .…”

Section: Introductionmentioning

confidence: 99%

A novel fully automated MRI-based deep-learning method for classification of IDH mutation status in brain gliomas

Yogananda

Shah

Vejdani‐Jahromi

et al. 2019

Preprint

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BackgroundIsocitrate dehydrogenase (IDH) mutation status has emerged as an important prognostic marker in gliomas. Currently, reliable IDH mutation determination requires invasive surgical procedures. The purpose of this study was to develop a highly-accurate, MRI-based, voxel-wise deep-learning IDH-classification network using T2-weighted (T2w) MR images and compare its performance to a multi-contrast network.MethodsMulti-parametric brain MRI data and corresponding genomic information were obtained for 214 subjects (94 IDH-mutated, 120 IDH wild-type) from The Cancer Imaging Archive (TCIA) and The Cancer Genome Atlas (TCGA). Two separate networks were developed including a T2w image only network (T2-net) and a multi-contrast (T2w, FLAIR, and T1 post-contrast), network (TS-net) to perform IDH classification and simultaneous single label tumor segmentation. The networks were trained using 3D-Dense-UNets. A three-fold cross-validation was performed to generalize the networks’ performance. ROC analysis was also performed. Dice-scores were computed to determine tumor segmentation accuracy.ResultsT2-net demonstrated a mean cross-validation accuracy of 97.14% +/-0.04 in predicting IDH mutation status, with a sensitivity of 0.97 +/-0.03, specificity of 0.98 +/-0.01, and an AUC of 0.98 +/-0.01. TS-net achieved a mean cross-validation accuracy of 97.12% +/-0.09, with a sensitivity of 0.98 +/-0.02, specificity of 0.97 +/-0.001, and an AUC of 0.99 +/-0.01. The mean whole tumor segmentation Dice-scores were 0.85 +/-0.009 for T2-net and 0.89 +/-0.006 for TS-net.ConclusionWe demonstrate high IDH classification accuracy using only T2-weighted MRI. This represents an important milestone towards clinical translation.Keypoints – 1IDH status is an important prognostic marker for gliomas. 2. We developed a non-invasive, MRI based, highly accurate deep-learning method for the determination of IDH status 3. The deep-learning networks utilizes only T2 weighted MR images to predict IDH status thereby facilitating clinical translation.IMPORTANCE OF THE STUDYOne of the most important recent discoveries in brain glioma biology has been the identification of the isocitrate dehydrogenase (IDH) mutation status as a marker for therapy and prognosis. The mutated form of the gene confers a better prognosis and treatment response than gliomas with the non-mutated or wild-type form. Currently, the only reliable way to determine IDH mutation status is to obtain glioma tissue either via an invasive brain biopsy or following open surgical resection. The ability to non-invasively determine IDH mutation status has significant implications in determining therapy and predicting prognosis. We developed a highly accurate, deep learning network that utilizes only T2-weighted MR images and outperforms previously published methods. The high IDH classification accuracy of our T2w image only network (T2-net) marks an important milestone towards clinical translation. Imminent clinical translation is feasible because T2-weighted MR imaging is widely available and routinely performed in the assessment of gliomas.

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Section: Introductionmentioning

confidence: 99%

A novel fully automated MRI-based deep-learning method for classification of IDH mutation status in brain gliomas

Yogananda

Shah

Vejdani‐Jahromi

et al. 2019

Preprint

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“…Edited MRS offers some distinct advantages over other MRS techniques in the detection of 2‐HG. For example, at a similar CRLB threshold the false‐positive rate with edited MRS appears lower compared to that reported by other MRS techniques, such as short or long TE PRESS, which have a false‐positive rate up to 21% 23,24,27 . The second advantage is that the 2‐HG peak can be visualized directly at 4.02 ppm on the difference spectrum without overlap from other metabolites.…”

Section: Discussionmentioning

confidence: 74%

“…This is not a likely cause of false positivity in our study, since edited MRS detects 2‐HG peak at 4.02 ppm. False‐positive 2‐HG cases have also been linked to glioblastomas with necrosis and high lactate 23,24 …”

Section: Discussionmentioning

confidence: 99%

Preoperative Determination of Isocitrate Dehydrogenase Mutation in Gliomas Using Spectral Editing MRS: A Prospective Study

Nguyen

Melkus

Taccone

et al. 2020

Magnetic Resonance Imaging

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BackgroundThe edited magnetic resonance spectroscopy (MRS) technique has not yet been formally evaluated for the in vivo detection of 2‐hydroxyglutarate (2‐HG) in patients with gliomas of various grades.PurposeTo evaluate the diagnostic accuracy of edited MRS in the preoperative identification of the isocitrate dehydrogenase (IDH) mutation status in patients with gliomas.Study TypeProspective.PopulationFifty‐eight subjects (31 glioblastomas, 27 grade II and III gliomas).Field Strength/SequenceMescher–Garwood (MEGA)‐PRESS and routine clinical brain tumor MR sequences were used at 3T.AssessmentData were analyzed using an advanced method for accurate, robust, and efficient spectral fitting (AMARES) from jMRUI software. The amplitudes of the 2‐HG, N‐acetyl‐aspartate (NAA), choline (Cho), and creatine/phosphocreatine (Cr) resonances were calculated with their associated Cramer–Rao lower bound (CRLB). The IDH1 R132H mutation status was assessed by immunohistochemistry for all patients. Patients with grades II and III gliomas with negative immunohistochemistry underwent DNA sequencing to further interrogate IDH mutation status.Statistical TestThe differences in 2‐HG amplitudes, 2‐HG/NAA, 2‐HG/Cho, and 2‐HG/Cr between IDH‐mutant and IDH‐wildtype gliomas were assessed using Mann–Whitney U‐tests. Receiver operating characteristic curve analysis was performed to evaluate the diagnostic accuracy of each parameter.ResultsThe 2‐HG amplitudes, 2‐HG/NAA, and 2‐HG/Cho were higher for IDH‐mutant gliomas than IDH‐wildtype gliomas (P < 0.007). Using a CRLB threshold <30%, a 2‐HG cutoff greater than 0 had a sensitivity of 80% (95% confidence interval [CI]: 52–96%) and a specificity of 81% (95% CI: 54–96%) in identifying IDH‐mutant gliomas. In the subset of patients with grades II and III gliomas, the sensitivity was 80% (95% CI: 52–96%) and specificity was 100% (95% CI: 40–100%). Among 2‐HG ratios, the highest AUC for the identification of IDH mutant status was achieved using the 2‐HG/NAA (AUC = 0.8, 95% CI 0.67–.89).Data ConclusionPreoperative edited MRS appears to be able to help identify IDH‐mutant gliomas with high specificity.Level of Evidence 1Technical Efficacy Stage 2J. MAGN. RESON. IMAGING 2021;53:416–426.

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“…Advanced MR techniques such as dynamic perfusion MRI [18] and magnetic resonance spectroscopy [19] have also revealed differences between the IDH-mutant and wildtype gliomas. However, dynamic perfusion MRI requires contrast media and 2-hydroxyglutarate magnetic resonance spectroscopy have been shown to be associated with false positive cases with intratumoral hemorrhage [20]. In addition, 2-hydroxyglutarate detection with magnetic resonance spectroscopy is a technically challenging due to the spectral overlap of 2-hydroxyglutarate with background metabolites [21].…”

Section: Discussionmentioning

confidence: 99%

Quantitative Relaxometry using Synthetic MRI Could be Better than Qualitative T2-FLAIR Mismatch Sign: A Pilot Study

Kikuchi

Hiwatashi

Togao

et al. 2021

Preprint

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Introduction The diagnostic utility of synthetic MRI (SyMRI) in patients with isocitrate dehydrogenase (IDH)-mutant lower-grade gliomas has not been investigated. The purpose of this study was to determine whether quantitative relaxometry using SyMRI could differentiate between lower-grade gliomas with an increased sensitivity when compared to the qualitative T2-FLAIR mismatch sign.Methods Between May 2019 and May 2020, thirteen patients with IDH-mutant diffuse gliomas including seven astrocytomas and six oligodendrogliomas were evaluated. Five neuroradiologists independently evaluated the presence of the T2-FLAIR mismatch sign qualitatively. Inter-rater agreement of T2-FLAIR mismatch sign was calculated using the Fleiss kappa coefficient. SyMRI parameters (T1, T2-relaxation times, proton density [PD]) were measured in the gliomas and compared by Mann–Whitney U-test. The receiver operating characteristic analysis was used to evaluate the diagnostic performance. The simulated T2-FLAIR mismatch sign (%change) was also evaluated.Results The sensitivity, specificity, and kappa coefficient were 57.1%, 83.3%, and 0.38, respectively in T2-FLAIR mismatch sign. There were differences between the gliomas in the 10–90th percentiles and the mean in T1, T2-relaxation times, and PD (all p < .05). The T2-relaxation time of the 10th and 50th percentiles, and the mean showed the highest diagnostic performance (area under the curve = 1.00). The %change of present/absent T2-FLAIR mismatch cases were –49.3 ± 6.5%, –43.4 ± 7.9%, respectively.Conclusion Quantitative relaxometry using SyMRI could differentiate astrocytomas from oligodendrogliomas with an increased sensitivity and objectivity compared to the qualitative T2-FLAIR mismatch sign.

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False-Positive Measurement at 2-Hydroxyglutarate MR Spectroscopy in Isocitrate Dehydrogenase Wild-Type Glioblastoma: A Multifactorial Analysis

Cited by 33 publications

References 24 publications

A novel fully automated MRI-based deep-learning method for classification of IDH mutation status in brain gliomas

A novel fully automated MRI-based deep-learning method for classification of IDH mutation status in brain gliomas

Preoperative Determination of Isocitrate Dehydrogenase Mutation in Gliomas Using Spectral Editing MRS: A Prospective Study

Quantitative Relaxometry using Synthetic MRI Could be Better than Qualitative T2-FLAIR Mismatch Sign: A Pilot Study

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