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. Author manuscript; available in PMC: 2022 Mar 1.
Published in final edited form as: J Neuroimaging. 2020 Dec 28;31(2):317–323. doi: 10.1111/jon.12828

Diffusion and perfusion MRI predicts response preceding and shortly after radiosurgery to brain metastases: a pilot study.

Akash Deelip Shah 1,*, Amaresha Shridhar Konar 2,*, Ramesh Paudyal 2, Jung Hun Oh 2, Eve LoCastro 2, David Aramburu Nuñez 2, Nathaniel Swinburne 1, Behroze Vachha 1, Gary A Ulaner 1, Robert J Young 1, Andrei I Holodny 1, Kathryn Beal 3, Amita Shukla-Dave 1,2,^, Vaios Hatzoglou 1,^,*
PMCID: PMC8005428  NIHMSID: NIHMS1654651  PMID: 33370467

Abstract

Background and Purpose:

To determine the ability of diffusion-weighted imaging (DWI) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to predict long-term response of brain metastases prior to and within 72 hours of stereotactic radiosurgery (SRS).

Methods:

In this prospective pilot study, multiple b-value DWI and T1-weighted DCE-MRI were performed in patients with brain metastases before and within 72 hours following SRS. Diffusion-weighted (DW) images were analyzed using the monoexponential and intravoxel incoherent motion (IVIM) models. DCE-MRI data were analyzed using the extended Tofts pharmacokinetic model. The parameters obtained with these methods were correlated with brain metastasis outcomes according to modified Response Assessment in Neuro-Oncology Brain Metastases (RANO-BM) criteria.

Results:

We included 25 lesions from 16 patients; 16 patients underwent pre-SRS MRI and 12/16 patients underwent both pre- and early (within 72 hours) post-SRS MRI. The perfusion fraction (f) derived from IVIM early post-SRS was higher in lesions demonstrating progressive disease than in lesions demonstrating stable disease, partial response, or complete response (q = 0.041). Pre-SRS extracellular extravascular volume fraction, ve, and volume transfer coefficient, ktrans, derived from DCE-MRI were higher in non-responders versus responders (q = 0.041).

Conclusions:

Quantitative DWI and DCE-MRI are feasible imaging methods in the pre- and early (within 72 hours) post-SRS evaluation of brain metastases. DWI- and DCE-MRI-derived parameters demonstrated physiologic changes (tumor cellularity and vascularity) and offer potentially useful biomarkers that can predict treatment response. This allows for initiation of alternate therapies within an effective time window that may help prevent disease progression.

Keywords: brain metastases, DCE-MRI, DWI, stereotactic radiosurgery, treatment response

INTRODUCTION

Approximately 10% of patients with systemic malignancies will develop brain metastases.1,2 Stereotactic radiosurgery (SRS), commonly used to treat patients with brain metastases, has demonstrated an 80–90% control rate up to two years after therapy.3 Treatment approaches for brain metastases that fail to respond to SRS include newer systemic therapies, surgery, and whole-brain radiation therapy. Some patients may also benefit from repeat SRS.4

Unfortunately, assessment of lesion size with conventional MRI after SRS is not a reliable predictor of long-term outcome. Some lesions may transiently increase after SRS due to inflammation. Furthermore, early apoptotic changes may precede tumor shrinkage; these changes cannot be assessed with conventional imaging and typically require follow-up over months to years.5 Multiple studies have assessed the predictive capabilities of conventional and advanced MRI features weeks to months after SRS5–9 with mixed results using mainly retrospective analysis. Advanced MRI hours after treatment may better predict long-term treatment response. Identifying patients almost immediately after therapy for whom SRS will ultimately fail would allow timely implementation of alternative or repeat treatment.

Diffusion-weighted imaging (DWI) is an advanced MRI technique that allows for quantification of water diffusion in tumors. Apparent diffusion coefficient (ADC), which is obtained from signal intensity with at least two b-values, is inversely correlated with tumor cellular density.10 Multiple b-value DWI data can be analyzed using a bi-exponential intravoxel incoherent motion (IVIM) model.11 Using this model, diffusion coefficient (D), pseudo-diffusion coefficient (D*), and perfusion fraction (f) can be extracted. IVIM estimates both molecular diffusion and the microcirculation of blood in the capillary network, and its feasibility has been tested in brain tumors.12 IVIM has shown promise in characterizing breast and pancreatic tumors,13,14 assessing tumor treatment response in head and neck cancer,15 and grading gliomas.12

Dynamic contrast-enhanced (DCE)-MRI pharmacokinetic analysis quantifies the volume transfer constant, Ktrans (min−1), which is an index of tumor vascular permeability; volume fraction of extracellular extravascular space, ve; and vascular volume, vp, by fitting the kinetic profile of an intravenously injected low-molecular-weight paramagnetic contrast agent when it extravasates into the extracellular extravascular space.16 To estimate these physiological parameters, the extended Tofts model is commonly applied in brain tumor studies.17,18

The near-immediate effects of SRS in human brain metastases have not yet been clearly defined by histopathologic or imaging analysis. A recent prospective imaging study assessed changes in DWI and DCE-MRI parameters at day 0 and day 3 post-SRS for brain metastases, finding no significant difference in imaging parameters between these two early timepoints.19 Another prospective imaging study assessed changes in blood volume in brain metastases one week and one month post-SRS using DCE-MRI and IVIM,20 demonstrating significant changes in blood volume only at one month.

The aim of this study was to determine whether MRI-derived diffusion and perfusion biomarkers can predict long-term response of brain metastases prior to and within the first 72 hours of SRS treatment. We hypothesize that quantitative multiparametric MRI biomarkers can differentiate brain metastases that will eventually respond to SRS treatment from those that will not. Rapid and non-invasive prediction of SRS failure could facilitate early implementation of more effective treatment strategies. This study could also help advance our understanding of the early radiobiological effects of SRS on tumor physiology.

METHODS

Patient cohort

This prospective trial was approved by the local institutional review board and privacy board. Written informed consent was obtained from all patients between August 2014 and December 2018. The inclusion criteria were age ≥ 18 years and clinical or radiological diagnosis of brain metastasis to be treated with SRS. The exclusion criterion was any contraindication to MRI, such as a non-compatible cardiac pacemaker. In total, 21 patients were enrolled in the study and underwent pre-treatment MRI within one month prior to SRS (mean 11 days).

For our primary analysis of predictive biomarkers, five patients were excluded due to insufficient follow-up (< 3 months of follow-up MRI after SRS), leaving 16 patients with 25 metastases. One of the five excluded patients was also excluded due to excessive imaging artifact. All 16 patients completed pre-SRS DWI. Fifteen patients with 23 metastases completed pre-SRS DCE-MRI; one patient was unable to complete pre-SRS DCE-MRI due to time constraints. Four patients declined to undergo early post-SRS repeat imaging (within 72 hours following singe-fraction SRS), while 12 patients with 18 metastases completed early post-SRS DWI and 11 patients with 15 metastases underwent early post-SRS DCE-MRI; one patient was unable to complete the early post-SRS DCE-MRI due to time constraints and only completed the DWI component. Fourteen metastases were imaged on the same day as SRS, one metastasis was imaged one day following SRS, and three metastases were imaged two days following SRS.

In addition to our primary analysis, we assessed for changes in MRI biomarkers in all patients who underwent both pre- and early post-SRS imaging, regardless of long-term follow-up (such as those initially excluded for <3 months follow-up after SRS). This included 16 patients with 23 metastases who underwent both pre- and post-SRS DWI, and 14 patients with 19 metastases who underwent both pre- and post-SRS DCE-MRI.

MRI acquisition

All pre- and early post-SRS MRI examinations were performed on a 3T MRI scanner (Philips Ingenia; Philips Healthcare, Netherlands) using an 8-channel head coil.

DWI included a single-shot echo-planar imaging sequence using 10 b-values (b = 0, 20, 50, 80, 200, 300, 500, 800, 1500, and 2000 s/mm2) in a single acquisition scan (TR, 4000; TE, 100 ms (minimum); NA, 2; matrix size, 128 × 128; FOV, 20–24 cm; number of slices, 8–10; slice thickness, 5 mm). The DWI acquisition time was ~5 min.

DCE-MRI acquisition included: 1) pre-contrast T1-weighted imaging using a fast 3D T1-weighted spoiled gradient-recalled (SPGR) sequence (flip angles [FA], 5°, 15°, and 30°; TR/TE, 5.6/2.3 ms; acquisition matrix size, 256 × 128; reconstruction matrix size, 256 × 256 by zero-filling; FOV, 20–24 cm; number of slices, 8–10; and slice thickness, 5 mm for T10 mapping); 2) dynamic scan using the same MR parameters as those used for pre-contrast T1 weighted images with FA = 30° before, during, and after the injection of a bolus of 0.1 mmol/kg gadolinium-based CA, Gadobutrol (Gadavist, Bayer Healthcare), through an antecubital vein catheter at 2 cc/s, followed by a 20-ml saline flush using an MR-compatible programmable power injector (Spectris; Medrad, Indianola, PA). The temporal resolution was ≤ 7 sec/image and the total acquisition time was ≤ 7.0 min; 3) post-contrast T1-weighted images using an inversion recovery based 2D sequence with similar matrix size (FA, 90°; TR/TE, 2072/20 ms; inversion time (TI), 800 ms; slice thickness, 3 mm; number of averages, 1).

Regions of interest analysis

Regions of interest (ROIs) were delineated on the brain metastases by a neuroradiologist with over seven years of neuroimaging experience on the DW image (b  =  0 s/mm2) and T1w dynamic image of the late phases using ITK-SNAP software.21 To determine the extent of the tumor, anatomical T2/contrast-enhanced T1-weighted images were used. ROIs were drawn on multiple slices to encompass the entire enhancing portion of the tumor, excluding cystic and necrotic regions. Contoured tumor ROIs were imported for image analysis. Volumetric data were calculated using ROIs drawn on multiple slices to encompass the entire tumor.

DWI and DCE fitting routines were performed as detailed elsewhere.22 DWI and DCE-MRI parametric maps were generated on a voxel-wise basis for each metric in each patient. The quantitative value of each metric obtained from the slices was reported as mean and standard deviation (STD). All DWI and DCE-MRI data postprocessing was performed using the in-house software MRI Quantitative Analysis of Multi-Parametric Evaluation Routines (MRI-QAMPER).23,24

Statistical analysis

We assessed pre- and early post-SRS values and the change (Δ) of quantitative metrics values derived from DWI (i.e., ADC, D, D*, and f) and DCE (i.e., Ktrans, ve, and vp) before and after treatment. In addition, the pre- and early post-SRS tumor volumes were analyzed.

Treatment response was classified as progressive disease (PD), stable disease (SD), partial response (PR), or complete response (CR) according to criteria defined by the modified Response Assessment in Neuro-Oncology Brain Metastases (RANO-BM).23 We modified the minimum size threshold for lesions to 5 mm, as we routinely treat metastases between 5 mm and 10 mm with SRS at our institution.26

Univariate analysis was performed using the Wilcoxon rank-sum test (WRST) to find the differences in the pre- and early post-SRS metrics values between the brain metastases that eventually demonstrated PD and those that did not. WRST was performed to compare brain metastases with PD or SD to those demonstrating objective response (with eventual PR or CR). We used Storey’s method for multiple comparisons to control for false positive discoveries and have reported q values for these analyses. Finally, Wilcoxon signed-rank test (WSRT) was performed using the quantitative metrics obtained from the patients who had both pre- and post-SRS DWI and DCE-MRI data to assess biomarker changes (pre- and early post-SRS) within the lesions regardless of outcome.

RESULTS

Brain metastasis characteristics

The majority (75%) of the brain metastases were from melanoma and lung primary tumors (Table 1). Median follow-up after treatment was 6 months (range 3–56 months) and 9/16 patients (56%) were followed until death. Two patients went to hospice after 6 months and 23 months, one patient left the institution after 8 months, one patient underwent whole-brain radiation therapy at 6 months, and one patient had metastasis resection at 27 months.

Table 1.

Patient Characteristics.

Characteristic Number (%)
Number of patients 16 (100)
Number of lesions 25 (100)
Median age (range), years 65 (35–85)
Sex
Male 5 (31)
Female 11 (69)
Primary tumor histology
Lung 6 (37.5)
Melanoma 6 (37.5)
Breast 2 (12.5)
Other 2 (12.5)
Number of brain metastases per patient
Single 10 (62.5)
Multiple 6 (37.5)
Brain metastases follow-up time (months)
3–6 8 (32)
6–12 8 (32)
≥ 12 9 (36)
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Using RANO-BM criteria, 20/25 lesions demonstrated local control after SRS. Rates of CR, PR, SD, and PD were 12%, 52%, 16%, and 20%, respectively. Eighty percent (20/25) of the lesions met the RANO-BM criteria for measurable disease. Twenty percent (5/25) were smaller and were included for analysis according to our modified criteria but none measured less than 5 mm.

Advanced imaging biomarkers

Representative DWI and DCE-derived parametric maps overlaid on corresponding DWI and DCE-MRI images (pre- and post-SRS) for two patients are shown in Figures 1–2.

Figure 1.

Figure 1.

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Representative pre- and early post-SRS MR images from an 80-year-old female with right occipital lobe brain metastasis that eventually demonstrated PD on follow-up.

Top panel: The yellow rectangle surrounds the metastatic lesion on the pre-SRS DWI (b=0 s/mm2) image. Diffusion coefficient (D) (× 10−3 mm2/s), pseudo-diffusion coefficient (D*) (× 10−3 mm2/s), and perfusion fraction (f) maps are zoomed in at the locations of the regions of interest (ROIs). The lesion volume was unchanged within 72 hours of SRS. Bottom panel: The yellow rectangle surrounds the metastatic lesion on the pre-SRS T1-postcontrast image. Ktrans (min−1), volume fraction of extracellular extravascular space (ve), and vascular volume (vp) maps are zoomed in at the locations of the ROIs.

Figure 2.

Figure 2.

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Representative pre-SRS and early post-SRS MR images from a 51-year-old female with right frontal lobe metastasis that eventually demonstrated CR on follow-up.

Top panel: The yellow rectangle surrounds the metastatic lesion on pre-SRS diffusion weighted (b=0 s/mm2) image. Diffusion coefficient (D) (×10−3 mm2/s), pseudo-diffusion coefficient (D*) (×10−3 mm2/s), and perfusion fraction (f) maps are zoomed at the locations of regions of interests (ROIs). The lesion volume was reduced on early post-SRS imaging. Bottom panel: The yellow rectangle surrounds the metastatic lesion on pre-SRS T1-postcontrast image. Ktrans (min−1), volume fraction of extracellular extravascular space (ve), and vascular volume (vp) maps are zoomed at the locations of ROIs.

Analysis of predictive MRI biomarkers

For comparisons between outcome groups, univariate analysis using the WRST demonstrated a significant difference in both mean and median f acquired early post-SRS (q = 0.041 and 0.033 respectively). Lesions that demonstrated PD had a higher f mean (0.416 vs. 0.336) and f median (0.500 vs. 0.358) than lesions that did not demonstrate PD. Using the Youden index, we determined that a post-SRS f mean cutoff value of 0.383 and f median cutoff value of 0.494 yielded a sensitivity of 100% and specificity of 86% for predicting PD and non-PD, with a receiver operating characteristic area under the curve (AUC) of 0.88 and 0.93 respectively (Figure 3). Notably, post-SRS D* mean demonstrated statistical significance between the PD and non-PD groups (P = 0.046) but did not demonstrate q < 0.05 upon multiple comparison analysis (q = 0.051).

Figure 3.

Figure 3.

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ROC curves for post-SRS f mean and median and D* and pre-SRS ve median and ktrans mean and median.

The area under the curve (AUC) for post-SRS perfusion fraction (f) mean, f median, and pseudo-diffusion coefficient (D*) mean, and pre-SRS Ktrans mean, Ktrans median, and volume fraction of extracellular extravascular space (ve) median was 0.88, 0.93, 0.84, 0.79, 0.85, and 0.78 respectively.

When the lesions were separated as responders (CR and PR) and non-responders (PD and SD), there was a significant difference in ve median on pre-SRS DCE-MRI (q = 0.041). Lesions that responded to SRS had a lower ve median than those that did not (0.089 vs. 0.181). A pre-SRS ve median cutoff value of 0.086 was 88% sensitive and 60% specific, with an AUC of 0.78 (Figure 3). There was also a significant difference in pre-SRS ktrans mean and median (q = 0.041 and 0.033 respectively). Lesions that responded to SRS had lower ktrans mean and median than those that did not (0.044 vs. 0.093 and 0.032 vs. 0.080 respectively). A pre-SRS ktrans mean cutoff value of 0.044 was 100% sensitive and 60% specific, with an AUC of 0.78. A pre-SRS ktrans median cutoff value of 0.029 was 100% sensitive and 67% specific, with an AUC of 0.85 (Figure 3). These findings are summarized in Figure 4.

Figure 4.

Figure 4.

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Univariate analysis of DWI and DCE-MRI metrics using WRST and comparison of DWI and DCE-MRI metrics pre- and post-SRS using WSRT.

Lesions that progressed had a higher perfusion fraction (f) mean and median than those that did not (0.416 vs. 0.336, q = 0.041; 0.500 vs. 0.358, q = 0.033 respectively). Lesions that responded to SRS had a lower pre-SRS ktrans mean, ktrans median, and ve median than those that did not (0.044 vs. 0.093, q = 0.041; 0.032 vs 0.080, q = 0.033; 0.089 vs. 0.181, q = 0.041 respectively). ADC mean and median trended higher in lesions post-SRS than pre-SRS (p = 0.0522 and 0.065 respectively). Vp was lower in lesions post-SRS than pre-SRS (p=0.009). ADC, apparent diffusion coefficient. Ktrans, index of tumor vascular permeability. Ve, volume fraction of extracellular extravascular space. Vp, vascular volume.

We did not find any significant differences in metrics (Δ) between pre- and early post-SRS images when comparing brain metastases with PD to those without progression (SD, PR, or CR), or when comparing brain metastases that objectively responded (PR or CR) to those with PD or SD.

Paired analysis of pre- and post-SRS imaging metrics

For this analysis, we included all patients with pre- and early post-SRS imaging regardless of the length of long-term follow-up.

When the differences in metrics (Δ) between pre- and early post-SRS scans for the entire cohort were compared regardless of outcome, WSRT showed statistically significant changes in vp mean (p = 0.009) as well as a trend toward significance in ADC mean and median (p = 0.052 and 0.065 respectively). These findings are summarized in Figure 4.

Tumor volume

Pre-SRS tumor volume was significant (p = 0.0218) for predicting response (CR/PR) versus non-response (PD/SD). A cutoff value of 2438 mm3 was 81% sensitive and 78% specific with an AUC of 0.80. Pre-SRS tumor volume was not significant when comparing PD to non-PD lesions. Only 2/5 lesions with PD demonstrated an increase in size on routine follow-up imaging within 3 months of SRS.

DISCUSSION

To our knowledge, our prospective study is the first to assess the predictive value of DWI and DCE-MRI biomarkers preceding and within the first 72 hours following SRS on brain metastases. Lesions that demonstrated PD had a higher early post-SRS perfusion fraction (f mean and median) derived from DWI than lesions that did not demonstrate PD. Additionally, the pre-SRS ktrans mean, ktrans median, and ve median derived from DCE-MRI were higher for lesions that did not objectively respond (PD and SD) compared to brain metastases that showed CR and PR. We assessed both PD versus others and PD/SD versus CR/PR because stable disease after therapy can be viewed favorably or unfavorably depending on the clinical context. Lastly, we observed changes in a few DWI- and DCE-MRI metrics (Δ) when comparing the pre- and early post-SRS scans for the entire cohort irrespective of lesion outcome.

IVIM modeling-based capillary perfusion based on DWI is advantageous because it can provide information on tissue microcirculation and capillary blood flow without contrast agents (i.e., D* and f). Perfusion fraction (f) represents the fraction of blood volume flowing into the capillaries. This biomarker demonstrates significant correlation with histologic microvessel density, with low values reflecting low density. We found that lesions with high f values after SRS had worse outcomes. Evidence suggests that SRS kills tumor cells not only directly but also indirectly by destroying tumor vascular beds.27–29 Higher capillary blood volume very early after SRS may therefore be an early marker of vascular bed preservation and therefore resistance to radiotherapy.

Pre-SRS ve, ktrans, and tumor volume were also predictive of outcome in this study. Responders had lower pre-SRS ve and ktrans than non-responders. ve and ktrans are derived from DCE-MRI, which has been extensively utilized to evaluate brain tumors.9,19,20,30–32 For example, Taunk et al. found that post-SRS Ktrans standard deviation within 12 weeks of treatment was a significant predictive biomarker for lung cancer brain metastases. Almeida-Freitas et al. found an that an increase of 15% in ktrans 4–8 weeks after SRS was predictive of tumor progression. Jakubovic et al. found a lower ktrans post-SRS in responders. These studies did not find a correlation between baseline ktrans and clinical outcome. Ktrans reflects both capillary permeability and tumor blood flow and lesions with higher ktrans can be expected to be more radiosensitive. It is therefore somewhat counterintuitive that higher pre-SRS ktrans values indicated worse outcomes in our study; this merits further investigation. In Tao et al.’s study assessing DCE-MRI for predicting lung cancer response to concurrent chemoradiotherapy, non-responders had a significantly higher ve than responders, similar to our study.33 Higher ve values may indicate decreased cell density, higher rates of necrosis, and less viable tissue. Further investigation of ve as a predictive biomarker is warranted.

The data showed significant and near-significant quantitative change for several DWI and DCE-MRI biomarkers measured before and within 72 hours post-SRS. These changes were not predictive of clinical outcomes, possibly because it may be too early in the temporal evolution of radiobiological effects for the correlation to become apparent. This is consistent with the study from Kapadia et al. which demonstrated temporal changes in vp, ktrans, and f within the first month following SRS with no significant difference among responders and non-responders.20 The precise temporal evolution of post-SRS effects on brain metastases should be assessed with larger multiparametric and longitudinal imaging studies.

In our study, no patients received systemic therapy concurrently with SRS. We did not assess for differences in lesion outcomes between patients who received systemic therapy after SRS and those who did not. This was not a significant variable in a larger retrospective study that assessed the predictive capabilities of DCE-MRI for 53 lung cancer brain metastases treated with SRS.9

Our study has several important limitations, such as its small cohort size. Another limitation is that we included brain metastases from different types of primary tumors. This does not account for variations in SRS response based on histopathology or variability in perfusion and permeability characteristics between tumors of different origin. However, the tumor control rate of SRS is high across histologies, and the radiobiological mechanisms that underpin this success likely overlap. Also limiting the study is that tumor response was based on RANO-BM criteria rather than histopathological evidence of response or progression in most cases. Additionally, we included several lesions smaller than the 10 mm threshold of the RANO-BM criteria, which may have limited our results. However, these smaller lesions are treated with SRS at many institutions, and our institution routinely uses high-resolution contrast-enhanced T1-weighted images with 1 mm slice thickness to allow for confident measurements. Quantitative analysis of DCE data is highly influenced by the temporal resolution. However, the moderate temporal resolution used for ETM in this study is consistent with previous studies.34–36

In conclusion, our study demonstrates that multiparametric MRI can demonstrate early (within 72 hours) radiobiological changes within brain metastases treated with SRS. Additionally, quantitative analysis of these biomarkers could predict long-term tumor response. Given this is a pilot study, our results are preliminary. Larger prospective trials with more homogeneous tumor histologies may reveal additional significant biomarkers than those demonstrated on this pilot study and would further our understanding of the mechanics and temporal evolution of changes at the cellular level after high dose radiation. We hope that our results lead to a more complete understanding of the radiobiology of SRS on human brain metastases. Rapidly identifying brain metastases at risk for long-term treatment failure after SRS can expedite the initiation of treatments within a more effective time window and thus enhance patient care.

Acknowledgements and Disclosures:

This work was supported by the National Institutes of Health/National Cancer Institute (Cancer Center Support Grant P30 CA008748). The authors report no conflicts of interest.

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