Predicting response to radiotherapy of intracranial metastases with hyperpolarized \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$^{13}$$\end{document}13C MRI

Background Stereotactic radiosurgery (SRS) is used to manage intracranial metastases in a significant fraction of patients. Local progression after SRS can often only be detected with increased volume of enhancement on serial MRI scans which may lag true progression by weeks or months. Methods Patients with intracranial metastases (N = 11) were scanned using hyperpolarized \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$^{13}$$\end{document}13C MRI prior to treatment with stereotactic radiosurgery (SRS). The status of each lesion was then recorded at six months post-treatment follow-up (or at the time of death). Results The positive predictive value of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$^{13}$$\end{document}13C-lactate signal, measured pre-treatment, for prediction of progression of intracranial metastases at six months post-treatment with SRS was 0.8 \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$p < 0.05$$\end{document}p<0.05, and the AUC from an ROC analysis was 0.77 \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$p < 0.05$$\end{document}p<0.05. The distribution of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$^{13}$$\end{document}13C-lactate z-scores was different for intracranial metastases from different primary cancer types (F = 2.46, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$p = 0.1$$\end{document}p=0.1). Conclusions Hyperpolarized \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$^{13}$$\end{document}13C imaging has potential as a method for improving outcomes for patients with intracranial metastases, by identifying patients at high risk of treatment failure with SRS and considering other therapeutic options such as surgery. Supplementary Information The online version contains supplementary material available at 10.1007/s11060-021-03725-7.


Introduction
Upwards of 20% of cancer patients will develop brain metastases during the course of their illness, many of which become symptomatic [1,2,3,4]. The most common primary tumours responsible for brain metastases include lung cancer, melanoma, renal cancer, breast cancer, and colorectal cancer. The management of brain metastases has become more complex and may involve surgery, stereotactic radiosurgery (SRS), whole brain radiotherapy (WBRT), systemic therapy or best supportive care [5].
Over the past several decades, with improved imaging and radiation therapy technology, stereotactic radiosurgery (SRS) has cemented a role in a significant proportion of patients with brain metastases. SRS has been shown to improve survival in patients with brain metastases over WBRT alone [6] and avoids the the neurocognitive side effects of WBRT [7]. However, local control of brain metastases with SRS decreases with increasing tumour diameter as the dose is dialed back to reduce the risk of radiation injury [8,9]. Local progression can often only be detected with increased volume of enhancement on serial MRI scans which may lag true progression by weeks or months [10,11]. Therefore predictive tools for radiation resistance prior to SRS may help identify patients better suited for dose escalation or even upfront surgical resection. If the risk of treatment failure could be better assessed beforehand, some of these patients might be reclassified as candidates for surgery, improving outcomes.
The impact of lactate accumulation on radiosensitivity was only recognized relatively recently [12], but is now well established. Lactate accumulates in malignant tumours through a number of mechanisms, including hypoxia-inducible factor 1 (HIF-1) mediated reprogramming. It has been hypothesized that lactate affects radioresistance by antioxidant properties, inducing angiogenesis, mediating resistance to apoptosis, as well as by stabilizing HIF-1α and perpetuating the activation of HIF-1 independent of hypoxia [13]. Tumour lactate levels were shown to be inversely correlated with overall and disease-free patient survival in cervical cancer, head and neck squamous cell carcinoma, and glioblastoma in humans [14,15,16,17]. All rights reserved. No reuse allowed without permission. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this this version posted November 10, 2020. ; https://doi.org/10.1101/2020.11.06.20227298 doi: medRxiv preprint However, these findings were all based on lactate measurements in biopsy or surgical tumour samples, which are not available pre-treatment for intracranial metastases.
Hyperpolarized (HP) 13 C MRI is an new imaging approach that has the potential to predict radiation treatment failure by probing lactate metabolism. This technique uses a non-radioactive labelled metabolite, [1-13 C]pyruvate, as a contrast agent. Prior to imaging, the signal of [1-13 C]pyruvate is amplified by approximately 10,000-fold, or hyperpolarized, via dynamic nuclear polarization (DNP) [18]. While the amplified signal is short-lived (exponential decay constant of ∼ 40s in vivo), images of [1-13 C]pyruvate and its metabolic products such as [1-13 C]lactate and 13 C-bicarbonate, can be detected within seconds of injection. Clinical applications of HP 13 C MRI have been explored in recent years, starting with the first in-human imaging of prostate cancer patients in 2013 [19]. The application of HP 13 C MRI in patients with brain tumours and metastases is currently an active area of investigation [20,21,22].
In this work, patients (N=11) with one or more newly developed intracranial metastases were scanned using hyperpolarized 13 C MRI prior to treatment with SRS. The mean 13 Clactate signal from each lesion was normalized using the consistent pattern of 13 C-lactate in the brain parenchyma. The status of each lesion was then recorded at the six months post-treatment follow-up (or at the time of death). This enabled estimation of the positive predictive value and receiver operating characteristic (ROC) curve for prediction of lesion progression at six months post-treatment with SRS.

Materials and Methods
Written informed consent was obtained from patients with intracranial metastases (N = 11) prior to study participation under a protocol approved by the institutional Research Ethics Board and by Health Canada as a Clinical Trial Application. All participants had one or more newly developed intracranial metastasis and were scheduled for SRS immediately All rights reserved. No reuse allowed without permission. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
Prior to being positioned head-first in a General Electric (GE) MR750 3.0T MRI scanner (GE Healthcare, Waukesha, WI), a 20-gauge intravenous catheter was inserted into each patient's forearm. The patient's head was then secured in the support for the head coil base for a standard 8-channel neurovascular receive array (Invivo Inc.). This support could be docked with either the 8-channel 1 H array or a home-built single-tuned 13 C birdcage coil without moving the patient's head during the study. At the beginning of each exam, localizer images and a reference scan to be used during the image reconstruction [23] were acquired using the scanner's built-in body coil. The 13 C birdcage coil was then put in place.
Each subject was injected with a 0.43 mL/kg dose of 250 mM [1-13 C]pyruvate via an intravenous injection at 4 mL per second using a MEDRAD Spectris solaris injector (Bayer).
The doses were prepared within a sterile fluid path and hyperpolarized in a GE SPINLab polarizer equipped with a quality control QC module. The 13 C image acquisition was initiated upon the completion of a saline flush. All patients tolerated the [1-13 C]pyruvate injection without any adverse events.
Following the 13 C image acquisition, the 13 C head coil was replaced with an 8-channel 1 H neurovascular array (Invivo Inc.) for a standard suite of anatomical brain image acquisitions.
T 1 -weighted images were acquired using 3D fast spoiled GRE (axial prescription, FOV 25.6 × 25.6 cm 2 , 1-mm isotropic resolution, TR 7.6 ms, TE 2.9 ms, flip angle 11 • ). Gadolinium enhanced T 1 -weighted images were acquired 2 min after administering a gadolinium dose of 0.1 mmol/kg via hand injection in a subset of patients that required these images for radiation treatment planning. T 2 -weighted images were acquired using T 2 -FLAIR (axial, FOV 22 × 22 cm 2 , in-plane resolution 0.6875 × 0.982 mm 2 , 3-mm slice thickness, TR/TE All rights reserved. No reuse allowed without permission. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
All 13 C image reconstruction was performed offline using MATLAB R2018b (The Math-Works Inc., MA, Natick, Massachusetts). Data-driven geometric distortion artifact correction was performed as in [23]. The time-resolved images were summed to compute the area-under-the-curve (AUC) for each metabolite which were stored as final 13 C images.
The structural parcellation of metabolite signals within the brain was performed using BrainParser [25], which uses T 1 -weighted images to parcellate the brain into the 56 structural regions contained in the LPBA40 atlas. For each subject, the mean 13 C-lactate signal from each atlas region, x i , was computed and normalized by converting a z -score, z i as in [26]: where µ and σ are the mean and standard deviation of the 13 C-metabolite signals across the 56 atlas regions for that subject.
A region of interest (ROI) for each metastasis was manually contoured onto each slice of the post-Gd T 1 -weighted images, if available, by a radiation oncologist. In cases where post-Gd T 1 -weighted images were not acquired, manual contouring was performed on the non-contrast T 1 -weighted images or the T 2 -weighted images. The mean 13 C metabolite signal from each lesion, x lesion , was converted to a z -score, z lesion , by using the mean and standard deviation of the background 13 C-lactate signal in the normal brain, as follows: where µ and σ are as defined above, based on the 56 atlas regions for that patient.
Treated brain metastases were evaluated at the 6 month follow-up or last follow up prior to death. Tumour response was evaluated according to the RANO brain metastases criteria [11]. No cases of radiation necrosis were seen.
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preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this this version posted November 10, 2020. ; https://doi.org/10.1101/2020.11.06.20227298 doi: medRxiv preprint 3 Results Fig. 1 shows an example 13 C-lactate and 13 C-pyruvate image from one of the subjects. The background 13 C-lactate pattern across cortical regions, expressed as a plot of z-scores vs.
atlas region, appeared similar to the pattern from healthy participants, but with weaker concordance across patients (Kendall's W = 0.70) as compared with healthy participants (W = 0.83) [26]. The pattern is shown for all patients in Fig. 2. Despite the moderate reduction in concordance, the range of lactate z -scores from the 56 atlas regions spanned roughly the same range in all subjects, from -3 to 2, which is similar to the range seen in healthy volunteers and sufficiently consistent across patients for the normalization of the tumour 13 C-lactate signal in this analysis.
The metastatic lesions displayed a broad range of lactate z -scores, from -2.23 to 3.74, as shown in Fig. 3. A different range of lactate z-scores was observed for each of the four primary tumour types: non-small cell lung carcinoma (NSCLC, N=4), renal cell carcinoma (RCC, N=2), breast cancer (N=4) and colorerectal cancer (N=1). To test whether this apparent difference was statistically significant, a 1-way ANOVA was used with the primary cancer type as a categorical variable and the lactate z-scores as the dependent variable, giving F = 2.46 and p = 0.1.
Based on this result and the observation that the highest lactate z-scores from each primary cancer type appeared to be associated with treatment failure (arrows in Fig. 3), the set of lactate z-scores for each primary cancer type was rescaled to a prediction score, ranging from 0 to 1. This allowed the prediction score values from all tumour types to be included in the same ROC analysis, resulting in the ROC curve shown in Fig. 4. The areaunder-the-curve (AUC) was 0.77 with an optimal threshold giving a true positive rate of 0.8, a false positive rate of 0.2 and a positive predictive value of 0.8. Based on the equivalency relationship between the AUC and the parameter U derived in the Mann-Whitney U test, as described in [27], the statistical significance of this ROC result was calculated to be p < 0.05. All rights reserved. No reuse allowed without permission. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

Discussion
The performance of 13 C-lactate as a predictor of treatment failure was superior to other markers previously investigated for this purpose, such as the apparent diffusion coefficient (ADC) [28] measured after SRS. ROC analysis on the prediction of progression using ADC values at 1 week and 1 month post-radiation gave an AUC of 0.704 and 0.748, respectively.
Furthermore, a limitation of this study was that lesions from different primary cancers were pooled in the analysis and this required rescaling to equalize the range of values for each primary cancer. In the future, a sufficient number of patients will be scanned so that ROC analysis can be performed on each primary cancer type separately, which will likely improve the AUC.
In this study, a brain parcellation-based approach was used to normalize 13 C signals from metastatic lesions using the 13 C signals from other brain regions for reference. This normalization method, based on comparison to the consistent background metabolite pattern in the brain, is a key element of this project as it allows for a 13 C-lactate measurement of each lesion computed from just the 13 C-lactate images alone. This is important because elevated 13 C-lactate signal has been shown to occur alongside elevated 13 C-pyruvate (substrate) signal under several common conditions such as high tumour vascularity and elevated expression of MCT1 transporters [29]. The conventional normalization methods found in the literature, which involve computation of a lactate-to-pyruvate ratio or fitting a first-order rate constant to time-resolved data, both inherently reduce the number that results from high-lactate/highpyruvate condition. This condition, in fact, is likely a highly malignant phenotype. One of the lesions that progressed in the preliminary study fell into this category (the highest 13 Clactate z-score in Fig. 3).
A limitation to this study was the coarse spatial resolution used for the 13 C imaging (1.5-cm isotropic). This may have lead to contamination of the tumour 13 C-lactate signal from the surrounding tissues, which would be worse for smaller lesions. Thus the positive predictive value of this method may improve with advances in the data acquisition method All rights reserved. No reuse allowed without permission. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
Three lesions across two patients were treated with SRS prior to 13 C imaging. The lactate z -scores from these lesions were -1.13, -1.29 and 1.04. Future studies should investigate whether the observed z -scores in previously treated lesions reflect treatment-related metabolic changes or are consistent with the 13 C-lactate signal levels observed in healthy brain tissues.

Conclusions
The positive predictive value of 13 C-lactate signal, measured pre-treatment, for prediction of progression of intracranial metastases at six months post-treatment with SRS was 0.8 p < 0.05, and the AUC from an ROC analysis was 0.77 p < 0.05. The distribution of 13 Clactate z-scores was different for intracranial metastases from different primary cancer types (F = 2.46, p = 0.1). Hyperpolarized 13 C imaging has thus shown the potential as a method for improving outcomes for patients with intracranial metastases, by identifying patients at high risk of treatment failure with SRS and considering other therapeutic options such as surgery. All rights reserved. No reuse allowed without permission. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.   All rights reserved. No reuse allowed without permission. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

Author Contributions
The copyright holder for this this version posted November 10, 2020. ; https://doi.org/10.1101/2020.11.06.20227298 doi: medRxiv preprint atlas region # lactate z-score Figure 2: Lactate z -scores from 56 LPBA40 atlas regions from 11 patients. The atlas regions are indicated with LPBA40 atlas region numbers. This consistent pattern is used for normalization of the tumour 13 C-lactate signal.
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The copyright holder for this this version posted November 10, 2020. ; https://doi.org/10.1101/2020.11.06.20227298 doi: medRxiv preprint Primary Cancer Type Tumour Lactate z-Score Note the apparent relationship between the higher lactate z-scores for each primary cancer type and progression.
All rights reserved. No reuse allowed without permission. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this this version posted November 10, 2020.  All rights reserved. No reuse allowed without permission. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this this version posted November 10, 2020. All rights reserved. No reuse allowed without permission. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.