Supplementary Data

Table 1S. Baseline metabolite levels relative to creatine.

Table 2S. Demographic, genomic, molecular, histological, radiological and

clinical data.

Table 3S. Fractional changes for all imaging biomarkers.

Table 4S. General Linear Model with change of KPS as dependent variable and

grade, age and fractional volume of decreased 2HG/Cre as covariates.

Figure 1S. 3D MRSI pulse sequence for 2HG imaging, detailed diagram.

Figure 2S. Quantum mechanics simulations of 2HG spectral editing for MEGA-

LASER, MEGA-PRESS and PRESS-97 sequences.

Figure 3S. Simulations of 2HG editing for MEGA-LASER and PRESS-97

sequences in the presence of B1 field inhomogeneity.

Figure 4S. Mitigation of subtraction artifacts caused by motion and scanner

instability in J-difference MR spectroscopy using real-time prospective motion

correction, shim update and reacquisition.

Figure 5S. Metabolic maps before image interpolation.

Figure 6S. Examples of OFF and difference (DIFF) MEGA-LASER spectra from

3D MRSI voxels located in the tumor and contralateral normal appearing white

matter, pre- and post-treatment respectively.

Figure 7S. Distributions of 2HG/Cre in the test-retest and post-pre longitudinal

data sets.

Figure 8S. Comparison of functional spectroscopic maps (fSM) and functional

diffusion maps (fDM).

Figure 9S. Relation between residual tumor measured by FLAIR hyperintensity

volume and the SNR and CRLB of 2HG.

Notes. Details related to data analysis in Figures 7S and 9S.

1

Table 1S. Pre-treatment metabolite levels in all 25 patients. Patients had: (1-9)

pre/post-treatment scans, (10-21) only pre-treatment scan, (22-25) gross total

resection of tumor and 2HG was not detectable.

Patient # Grade Type IDH1 mutation

2HG/Cre

Glx/Cre

Lac/Cre

GPC/Cre

NAA/Cre

Pt_01 2 A R132G 0.31 1.21 0.23 0.32 1.02Pt_02 2 OA R132H 0.35 1.35 0.35 0.18 0.93Pt_03 3 AA R132H 0.39 1.06 0.62 0.45 0.73Pt_04 3 AA R132S 0.70 0.93 0.86 0.40 0.69Pt_05 3 AA R132H 0.31 0.58 0.24 0.55 0.76Pt_06 3 AOD R132H 0.40 0.77 0.17 0.32 0.65Pt_07 3 AOA R132H 0.22 1.29 0.30 0.19 0.86Pt_08 4 GBM R132H 0.31 0.99 0.29 0.44 0.71Pt_09 4 GBMO R132H 0.23 1.38 0.09 0.17 1.10Pt_10 2 OD R132H 0.17 0.84 0.13 0.44 0.95Pt_11 3 AOD R132H 0.37 0.89 0.23 0.32 0.90Pt_12 2 A R132H 0.30 1.76 0.30 0.28 0.95Pt_13 4 GBM R132H 0.57 0.96 0.25 0.27 0.99Pt_14 3 AA R132H 0.16 1.46 0.23 0.14 0.60Pt_15 4 GBM R132H 0.27 1.20 0.37 0.40 0.90Pt_16 3 AOD R132H 0.86 0.87 0.91 0.34 1.18Pt_17 3 AOA R132H 0.35 1.65 0.36 0.35 0.90Pt_18 3 AA R132H 0.18 1.35 0.24 0.19 1.11Pt_19 3 AA R132H 0.19 1.76 0.93 0.27 1.13Pt_20 2 A R132H 0.54 1.40 0.37 0.22 1.45Pt_21 3 AA R132H 0.47 1.94 1.59 0.29 0.84Pt_22 3 AOA R132H - 1.86 0.18 0.57 1.57Pt_23 3 AA R132C - 1.39 0.17 0.25 0.87Pt_24 2 A R132H - 1.23 - 0.24 1.13Pt_25 2 OA R132H - 1.18 0.29 0.13 1.22

2

Table 2S. Demographic, genomic, molecular, histological, radiological and clinical data in patients with follow up scans

and positive 2HG. A=Astrocytoma, AA/OA=Anaplastic/Oligo astrocytoma, AOD/A=Anaplastic

oligo-dendroglioma/astrocytoma, GBM(O)=Glioblastoma (with oligodendroglial component).

Patient #

Age Grade Gliomatype

IDHmutation

Molecular markers

Tumor location Treatment Steroids KPSPre/Post

RANO

1 33 WHO-II A R132G - Left posterior cingulum/callosum RT 0 90/100 PR

2 38 WHO-II OA R132H 19q only Right parietal RT 0 100/100 SD

3 33 WHO-III AA R132H - Left frontal/temporal RT 0 90/90 SD

4 42 WHO-III AA R132S - Left frontal RT 0 50/80 MR5 38 WHO-III AA R132H 19q only Right parietal RT 0 90/80 SD

6 45 WHO-III AOD R132H 1p/19q, MGMT Right frontal RT 0 90/100 SD

7 46 WHO-III AOA R132H 1p/19q Left temporal CT 0 90/80 MR

8 63 WHO-IV GBM R132H - Left frontal RT 4mg qD (stable) 100/60 PD

9 55 WHO-IV GBMO R132H 1p/19q Right frontal CT 0 90/90 SD

3

Table 3S. Fractional changes for all imaging biomarkers.

Patient #

2HG/Cre GLX/Cre tCho/Cre Lac/Cre NAA/Cre tCho/NAA ADC Volume FLAIR

Volume 2HG

2HGVd/Vt

2HGVi/Vt

ADCVd/Vt

ADCVi/Vt

1 -37.37 -19.8 -11.5 -12.2 -4.7 -10.4 - 39.90 -50.09 60.01 0.00 - -2 -69.32 -13.7 -51.6 -29.0 -0.7 -50.9 2.72 -15.31 -51.87 58.23 24.58 0.65 1.423 -54.01 17.2 -17.5 -11.0 6.1 -32.2 - 6.90 -61.55 76.74 0.86 - -4 -65.39 -25.7 7.4 -20.0 -18.1 23.5 5.76 -16.45 -34.61 99.12 0.00 5.11 45.275 2.88 24.2 -0.3 -19.8 16.6 -30.3 - -14.37 -32.15 24.82 8.75 - -6 -34.34 -26.6 13.8 8.8 3.2 11.99 - -9.35 -14.86 60.76 1.09 - -7 -48.09 0.1 2.9 -12.5 -19.0 24.96 6.76 -8.80 -42.53 49.11 3.29 3.04 22.758 -22.30 -1.0 -29.8 0.8 -2.3 -27.6 -1.33 69.80 -26.29 19.78 7.95 7.01 15.229 -48.89 -5.3 -13.2 25.9 -2.7 23.3 -2.66 -11.85 -37.70 58.01 0.00 0.31 4.63

4

Table 4S. General Linear Model of KPS with grade, age and fractional volume of

decreased 2HG/Cre as covariates.

Patient # Grade Age 2HG/CreVd/Vt (<-0.11)

dKPS(KPSpost – KPSpre)

1 2 33 60.01 102 2 38 58.23 03 3 33 76.74 04 3 42 99.12 305 3 38 24.82 -106 3 45 60.76 107 3 46 49.11 -108 4 63 19.78 -409 4 55 58.01 0

P-value 0.72317 0.74637 0.015248 R2 = 0.82, aR2 = 0.71

dKPS = 0.61Vd - 0.24Age - 3.48Grade - 14.82

5

Figure 1S. 3D MRSI pulse sequence for 2HG imaging. MEGA-LASER is used to

edit 2HG signal at 4.02ppm. More details are given in Ref (1).

6

Figure 2S. GAMMA (2) quantum mechanics simulations of 2HG editing for

MEGA-LASER, MEGA-PRESS (3) and PRESS-97 (4). Experimental pulses,

2HG spin system (5), and relaxation (T2 = 180ms) were considered (6).

7

Figure 3S. Simulations of 2HG editing for MEGA-LASER and PRESS-97

sequences in the presence of B1 field inhomogeneity (15% from the nominal

value).

8

Figure 4S. Mitigation of subtraction artifacts caused by motion and scanner

instability in J-difference MR spectroscopy using real-time prospective motion

correction, shim update and reacquisition.

9

Figure 5S. Metabolic maps before image interpolation. The same intensity range

is shown in both pre- and post-treatment maps.

10

Figure 6S. Examples of OFF and difference (DIFF) MEGA-LASER spectra from

tumor and contralateral normal appearing white matter (fit red, experimental

black, 3 Hz line broadening).

11

Figure 7S. Distributions of 2HG/Cre in test-retest (A) and longitudinal (B) data

sets. Normality of distributions was verified by Kolmogorov-Smirnov test (red line,

further details in Notes).

12

Figure 8S. Comparison of functional spectroscopic maps (fSM) and functional

diffusion maps (fDM). Regions of decreased 2HG/Cre partially overlap regions of

increased ADC.

13

Figure 9S. Relation between residual tumor measured by FLAIR volume and the

SNR and CRLB of 2HG (further details in Notes).

14

Notes: 1) In Figure 7S the threshold of 0.115 for significant 2HG/Cre change was

determined from the test-retest 95% CI, and corresponds to a change in

2HG level of approximately 1mM assuming total Cre (creatine +

phosphocreatine) levels of 8-10 mM (7).

2) In Figure 9S there is a trend for positive correlation between the SNR and

FLAIR volume, and a trend for negative correlation between relative CRLB

and FLAIR volume. The correlations are not statistical significant (P >

0.05) and can be explained by a range of biological factors (efficiency of

2HG production, tumor cell density and metabolic activity do not scale with

FLAIR hyperintensity) and methodological factors (linewidths and shim

quality influence the signal maximum intensity while residual unfitted

signal can amplify the noise estimation).

3) SNR is underestimated by LCModel that overestimates noise by

considering the entire residual (experimental-fit), which often includes

unfitted signal.

4) The upper threshold for relative CRLB was set to 25%. While the proper

CRLB threshold and metric for quality of fit of MRS is still a matter of

debate among experts, investigators mostly agree on excluding

metabolites with CRLB larger than 50%. Metabolites with CRLB less than

20% are generally considered very well fitted, CRLB less than 30%

acceptable, and CRLB between 30%-50% as poor fits but potentially

acceptable in a given context (8-12). In particular, for multiplet lines of spin

coupled metabolites the CRLB threshold may be higher than for singlet

lines of uncoupled spins.

1)

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