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CryptoCEST, a promising tool for differential diagnosis and treatment monitoring of fungal brain lesions
Liesbeth Vanherp1,2, Kristof Govaerts1,2, Matteo Riva3,4, Katrien Lagrou5, Greetje Vande Velde1,2, Willy Gsell1,2, and Uwe Himmelreich1,2

1Biomedical MRI, KU Leuven, Leuven, Belgium, 2MoSAIC, KU Leuven, Leuven, Belgium, 3Laboratory of Tumor Immunology and Immunotherapy, KU Leuven, Leuven, Belgium, 4Department of Neurosurgery, Erasme Hospital, Brussels, Belgium, 5Laboratory of Clinical Bacteriology and Mycology, KU Leuven, Leuven, Belgium

Synopsis

Differential diagnosis of fungal brain infections from other types of lesions is challenging. We assessed the presence of fungal metabolites in Cryptococcus lesions using in vivo MR spectroscopy and CEST. Hereby, we studied the use of trehalose, a disaccharide and fungal biomarker, for endogenous contrast in CEST imaging. Using the novel CryptoCEST technique, we were able to non-invasively differentiate Cryptococcus lesions from glioma. However, no significant effect of antifungal treatment on the CEST contrast was observed. If translated to the clinic, this technique has great potential in assisting in the differential diagnosis and specific spatial localization of cryptococcal brain lesions.

Introduction

Cryptococcus neoformans and C. gattii are the most common causes of fungal brain infections and can induce localized brain lesions or meningitis. Differential diagnosis based on conventional radiological examination is challenging, as e.g. cystic tumors or bacterial abscesses have a similar presentation on MRI or CT. The disaccharide trehalose has previously been identified in cryptococcal cells and lesion material through NMR spectroscopy1. We assessed the presence of trehalose in vivo in a model of focal cryptococcal lesions (cryptococcoma) by use of MR spectroscopy. Based on previous reports on glucoCEST2, we investigated whether trehalose would generate a detectable CEST contrast. Furthermore, we applied CryptoCEST in vivo to differentiate cryptococcoma from glioma, and to follow up response to antifungal treatment.

Methods

Unilateral focal brain lesions were induced by stereotactic injection of 104 Cryptococcus cells (C. gattii R265 (n=6), C. neoformans (CN) H99 (n=5) or CN-KN99α-FLuc (n=16, treatment study)) in the striatum of female Balb/C mice. Orthotopic high-grade gliomas were generated by inoculating 5x103 neurospheres-cultured CT-2A cells in the brain of female C57BL/6 mice, as previously described3. Antifungal treatment was initiated three days after inoculation. Mice (n=4 per group) received intraperitoneal (i.p.) injections with saline, fluconazole (TCI Europe, 75 mg/kg/day) or liposomal amphotericin-B (AmBisome, Gilead, 10 mg/kg/day i.p. or 1x20 mg/kg intravenously).

Images were acquired 8/9 days (Cryptococcus models) or 14 days (glioma model) after inoculation using a 9.4T Bruker Biospec small animal MR system with a 20cm horizontal bore and an actively-decoupled mouse brain surface coil (Rapid Biomedical) for receiving. MR spectra were acquired using a PRESS sequence with TR/TE 1800/20ms, voxel size of 2x2x2mm and VAPOR water suppression. RARE CEST images were acquired using the following parameters: TR/TE 2620/23ms, RARE factor 6, echo spacing 7.67ms, one 1.5mm slice with matrix size 96x96 and 0.208mm in-plane resolution. The saturation pulse train consisted of 300x8.5ms pulses with an RF peak amplitude of 1.4µT and bandwidth 150Hz. In total, 105 CEST images were acquired at saturation offsets ranging from -6.25ppm to 6.25ppm, plus control images at +50ppm. CEST spectra were B0-corrected using the WASSR method4. In vitro 1H-NMR spectra of Cryptococcus cells in PBS-D2O were acquired using a Bruker Avance 400MHz NMR spectrometer.

Results

In vitro CEST imaging of trehalose

To determine detection limits and concentration dependency, we imaged phantoms with different concentrations of trehalose and glucose in PBS (Fig. 1). Z-spectra for glucose and trehalose were similar, but trehalose produced higher MTRasym values than glucose. A linear relationship between trehalose concentration and area under the curve (AUC) between 0.2 and 2 ppm was observed.

In vivo: Can CryptoCEST distinguish between lesion types?

MRS confirmed the presence of trehalose in cerebral cryptococcomas (Fig. 2). Conversely, gliomas were characterized by an increased choline/creatine ratio and the presence of lipids. CEST imaging allowed identification and localization of cryptococcomas on the MTRasym maps at 0.7 ppm, while gliomas were only visible at 3ppm (Fig. 3). Cryptococcus lesions had an MTRasym pattern similar to the trehalose phantoms, which was distinct from that observed in gliomas or the contralateral brain. Quantification of the AUC (0.2 – 2 ppm) allowed discrimination of the different lesion types.

In vivo: Can CryptoCEST monitor response to antifungal treatment?

CEST contrast was slightly lower in animals that received amphotericin B, but no significant effect of treatment on the CEST contrast was detected (Fig. 4). MRS showed a significantly lower trehalose concentration in lesions of fluconazole-treated animals. Fungal load analysis indicated only a limited effect of antifungal treatment, with fluconazole being the most effective. In vitro NMR of Cryptococcus cells showed that trehalose is converted to glucose upon exposure to antifungals (Fig. 5).

Discussion

In vitro, the disaccharide trehalose generated a dose-dependent contrast that was approximately twice as high as for glucose, corresponding to the doubled amount of exchanging –OH groups. In vivo data showed that trehalose provides endogenous CEST contrast in cryptococcomas, with a z-spectrum distinct from that observed in gliomas. Although fluconazole treatment reduced fungal burden and trehalose concentrations, no significant changes were observed in CEST images, possibly due to metabolic conversion of trehalose to other carbohydrates with similar CEST contrast.

Conclusion

Due to the presence of trehalose in cryptococcal cells, CryptoCEST can be used to differentiate cryptococcal brain lesions from brain tumors. Unlike MRS, which is limited to large voxels, CEST imaging can achieve differential diagnosis and specific spatial localization of Cryptococcus infection even for smaller lesions. In-depth studies on carbohydrate metabolism are currently performed to further assess the potential for treatment follow-up.

Acknowledgements

LV and KG contributed equally to this work. We are thankful for financial support from the European Commission for the Infect-ERA project CryptoVIEW. LV is an SB PhD fellow at Research Foundation Flanders (FWO).

References

1. Himmelreich U, Dzendrowskyj TE, Allen C, Dowd S, Malik R, Shehan BP, et al. Cryptococcomas distinguished from gliomas with MR spectroscopy: an experimental rat and cell culture study. Radiology. 2001 Jul;220(1):122–8.

2. Walker-Samuel S, Ramasawmy R, Torrealdea F, Rega M, Rajkumar V, Johnson SP, et al. In vivo imaging of glucose uptake and metabolism in tumors. Nat Med. 2013 Aug;19(8):1067–72.

3. Riva, M, Baert T, Coosemans A, Giovannoni R, Radaelli E, Gsell W, Himmelreich U, Van Ranst M. A strategy to improve the translational impact of murine high grade glioma. In: Abstracts from the 4th ImmunoTherapy of Cancer Conference, Prague, Czech Republic. 20–22 March 2017. J Immunother Cancer. 2017; 5(Suppl 1): 12.

4. Kim M, Gillen J, Landman BA, Zhou J, van Zijl PCM. Water saturation shift referencing (WASSR) for chemical exchange saturation transfer (CEST) experiments. Magn Reson Med. 2009 Jun;61(6):1441–50.


Figures

Figure 1. In vitro characterization of the CEST signal in trehalose and glucose phantoms. A) MTRasym values at different saturation offsets. Although peak locations ware largely the same between glucose and trehalose, glucose exhibited lower MTRasym. B) Concentration dependency. AUC between 0.2 and 2 ppm was linearly correlated with trehalose concentration (R²=0.997, p=0.0013).

Figure 2: Comparison of representative in vivo MR spectra acquired in mice with Cryptococcus lesions (C. neoformans (CN) H99 or C. gattii (CG) R265) or glioma. Spectra of cryptococcomas were dominated by the presence of trehalose, mannitol, lipids and lactate, while the gliomas showed increased choline and lipid levels. Tre: trehalose, Man: mannitol, Lip: lipids, Lac: lactate, Cr: (phospo)creatine, Glx: glutamate/glutamine, tCho: total choline, NAA: N-acetylaspartate. Metabolite assignment was confirmed by ex vivo NMR spectroscopy according to 1.

Figure 3: CEST imaging of Cryptococcus lesions using trehalose for endogenous contrast. A) MTRasym maps at 0.7 and 3 ppm allowed identification and localization of cryptococcomas and gliomas. T2-weighted anatomical MRI scans showed similar contrast between cryptococcomas and gliomas. B) Averaged MTRasym curves showed different patterns in the different lesion types. C) Quantification of the AUC confirmed the possibility for lesion type differentiation based on CEST. CN: C. neoformans, CG: C. gattii, Glio: glioma, CL: contralateral brain.

Figure 4: CEST imaging of the response to antifungal treatment. Animals received saline, fluconazole (FLU) or liposomal amphotericin B (L-AMB, in 1 dose i.v. or daily i.p.) (n = 4 per group). A) Averaged MTRasym curves (day 8 p.i.). B) Quantification of the AUC from 0.2 to 2 ppm showed no significant effects of treatment on the CEST contrast. C) Quantification of trehalose concentration based on MR spectroscopy (day 9 p.i.) demonstrated lower trehalose levels in the FLU-treated animals. D) Fungal load analysis (colony-forming unit, CFU) in the brain showed only a limited effect of the antifungal treatment.

Figure 5: In vitro NMR spectroscopy of the effect of antifungal treatment on trehalose. C. neoformans H99 cells were exposed to amphotericin-B deoxycholate (AMB-d, 0.1 mg/ml), or not exposed (control) and 1H-NMR spectra were acquired after 30 min, 4, 24 or 48 hours. Based on the resonances of the protons on the anomeric carbons of trehalose (5.19 ppm) and glucose (5.22 pm), the treated cells showed a conversion of trehalose to glucose.

Proc. Intl. Soc. Mag. Reson. Med. 27 (2019)
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