Mixed-effects modeling of clinical DCE-MRI data: application to colorectal liver metastases treated with bevacizumab

Perfusion MR Imaging of Liver: Principles and Clinical Applications

Perfusion imaging techniques provide quantitative characterization of tissue microvasculature. Perfusion MR of liver is particularly challenging because of dual afferent flow, need for large organ high-resolution coverage, and significant movement with respiration. The most common MR technique used for quantifying liver perfusion is dynamic contrast-enhanced MR imaging. Here, the authors describe the various perfusion MR models of the liver, the basic concepts behind implementing a perfusion acquisition, and clinical results that have been obtained using these models.

DCE-MRI is more sensitive than IVIM-DWI for assessing anti-angiogenic treatment-induced changes in colorectal liver metastases

BACKGROUND

Diffusion weighted imaging (DWI) with intravoxel incoherent motion (IVIM) modelling can inform on tissue perfusion without exogenous contrast administration. Dynamic-contrast-enhanced (DCE) MRI can also characterise tissue perfusion, but requires a bolus injection of a Gadolinium-based contrast agent. This study compares the use of DCE-MRI and IVIM-DWI methods in assessing response to anti-angiogenic treatment in patients with colorectal liver metastases in a cohort with confirmed treatment response.

METHODS

This prospective imaging study enrolled 25 participants with colorectal liver metastases to receive Regorafenib treatment. A target metastasis > 2 cm in each patient was imaged before and at 15 days after treatment on a 1.5T MR scanner using slice-matched IVIM-DWI and DCE-MRI protocols. MRI data were motion-corrected and tumour volumes of interest drawn on b=900 s/mm2 diffusion-weighted images were transferred to DCE-MRI data for further analysis. The median value of four IVIM-DWI parameters [diffusion coefficient D (10-3 mm2/s), perfusion fraction f (ml/ml), pseudodiffusion coefficient D* (10-3 mm2/s), and their product fD* (mm2/s)] and three DCE-MRI parameters [volume transfer constant Ktrans (min-1), enhancement fraction EF (%), and their product KEF (min-1)] were recorded at each visit, before and after treatment. Changes in pre- and post-treatment measurements of all MR parameters were assessed using Wilcoxon signed-rank tests (P<0.05 was considered significant). DCE-MRI and IVIM-DWI parameter correlations were evaluated with Spearman rank tests. Functional MR parameters were also compared against Response Evaluation Criteria In Solid Tumours v.1.1 (RECIST) evaluations.

RESULTS

Significant treatment-induced reductions of DCE-MRI parameters across the cohort were observed for EF (91.2 to 50.8%, P<0.001), KEF (0.095 to 0.045 min-1, P<0.001) and Ktrans (0.109 to 0.078 min-1, P=0.002). For IVIM-DWI, only D (a non-perfusion parameter) increased significantly post treatment (0.83 to 0.97 × 10-3 mm2/s, P<0.001), while perfusion-related parameters showed no change. No strong correlations were found between DCE-MRI and IVIM-DWI parameters. A moderate correlation was found, after treatment, between Ktrans and D* (r=0.60; P=0.002) and fD* (r=0.67; P<0.001). When compared to RECIST v.1.1 evaluations, KEF and D correctly identified most clinical responders, whilst non-responders were incorrectly identified.

CONCLUSION

IVIM-DWI perfusion-related parameters showed limited sensitivity to the anti-angiogenic effects of Regorafenib treatment in colorectal liver metastases and showed low correlation with DCE-MRI parameters, despite profound and significant post-treatment reductions in DCE-MRI measurements.

TRIAL REGISTRATION

NCT03010722 clinicaltrials.gov; registration date 6th January 2015.

Functional imaging and circulating biomarkers of response to regorafenib in treatment-refractory metastatic colorectal cancer patients in a prospective phase II study

OBJECTIVE

Regorafenib demonstrated efficacy in patients with metastatic colorectal cancer (mCRC). Lack of predictive biomarkers, potential toxicities and cost-effectiveness concerns highlight the unmet need for better patient selection.

DESIGN

Patients with RAS mutant mCRC with biopsiable metastases were enrolled in this phase II trial. Dynamic contrast-enhanced (DCE) MRI was acquired pretreatment and at day 15 post-treatment. Median values of volume transfer constant (Ktrans), enhancing fraction (EF) and their product KEF (summarised median values of Ktrans× EF) were generated. Circulating tumour (ct) DNA was collected monthly until progressive disease and tested for clonal RAS mutations by digital-droplet PCR. Tumour vasculature (CD-31) was scored by immunohistochemistry on 70 sequential tissue biopsies.

RESULTS

Twenty-seven patients with paired DCE-MRI scans were analysed. Median KEF decrease was 58.2%. Of the 23 patients with outcome data, >70% drop in KEF (6/23) was associated with higher disease control rate (p=0.048) measured by RECIST V. 1.1 at 2 months, improved progression-free survival (PFS) (HR 0.16 (95% CI 0.04 to 0.72), p=0.02), 4-month PFS (66.7% vs 23.5%) and overall survival (OS) (HR 0.08 (95% CI 0.01 to 0.63), p=0.02). KEF drop correlated with CD-31 reduction in sequential tissue biopsies (p=0.04). RAS mutant clones decay in ctDNA after 8 weeks of treatment was associated with better PFS (HR 0.21 (95% CI 0.06 to 0.71), p=0.01) and OS (HR 0.28 (95% CI 0.07-1.04), p=0.06).

CONCLUSIONS

Combining DCE-MRI and ctDNA predicts duration of anti-angiogenic response to regorafenib and may improve patient management with potential health/economic implications.

Translational research and application of basic biology to clinical trial development in GI cancers

Cancers of the gastrointestinal tract have limited available treatments and are often associated with a poor prognosis. Clinical trials and translational work associated with these trials provide the opportunity to increase understanding of the mechanisms of sensitivity and resistance to cytotoxic chemotherapy and targeted therapy in these diseases. In this review we discuss the rationale for intensive translational work within the context of academic clinical trials and the successes and challenges which have been associated with translational work at our institution over the past number of years. We reflect on tissue, plasma and radiological biomarker work including a novel patient derived organoid programme and discuss the iterative application of previous results to next generation trial design.

Reduced respiratory motion artifacts using structural similarity in fast 2D dynamic contrast enhanced MRI of liver lesions

The purpose of this work was to improve dynamic contrast enhanced MRI (DCE-MRI) of liver lesions by removing motion corrupted images as identified by a structural similarity (SSIM) algorithm, and to assess the effect of this correction on the pharmacokinetic parameter K^trans using automatically determined arterial input functions (AIFs). Fifteen patients with colorectal liver metastases were measured twice with a T₁ weighted multislice 2D FLASH sequence for DCE-MRI (time resolution 1.2 s). AIFs were automatically derived from contrast inflow in the aorta of each patient. Thereafter, SSIM identified motion corrupted images of the liver were removed from the DCE dataset. From this corrected data set K^trans and its reproducibility were determined. Using the SSIM algorithm a median fraction of 46% (range 37-50%) of the liver images in DCE time series was labeled as motion distorted. Rejection of these images resulted in a significantly lower median K^trans (p < 0.05) and lower coefficient of repeatability of K^trans in liver metastases compared with an analysis without correction. SSIM correction improves the reproducibility of the DCE-MRI parameter K^trans in liver metastasis and reduces contamination of K^trans values of lesions by that of surrounding normal liver tissue.

PK-PD modeling of individual lesion FDG-PET response to predict overall survival in patients with sunitinib-treated gastrointestinal stromal tumor

Pharmacometric models were developed to characterize the relationships between lesion-level tumor metabolic activity, as assessed by the maximum standardized uptake value (SUVmax) obtained on [(18)F]-fluorodeoxyglucose (FDG) positron emission tomography (PET), tumor size, and overall survival (OS) in 66 patients with gastrointestinal stromal tumor (GIST) treated with intermittent sunitinib. An indirect response model in which sunitinib stimulates tumor loss best described the typically rapid decrease in SUVmax during on-treatment periods and the recovery during off-treatment periods. Substantial interindividual and interlesion variability were identified in SUVmax baseline and drug sensitivity. A parametric time-to-event model identified the relative change in SUVmax at one week for the lesion with the most pronounced response as a better predictor of OS than tumor size. Based on the proposed modeling framework, early changes in FDG-PET response may serve as predictor for long-term outcome in sunitinib-treated GIST.

Formation of parametric images using mixed-effects models: a feasibility study

Mixed-effects models have been widely used in the analysis of longitudinal data. By presenting the parameters as a combination of fixed effects and random effects, mixed-effects models incorporating both within- and between-subject variations are capable of improving parameter estimation. In this work, we demonstrate the feasibility of using a non-linear mixed-effects (NLME) approach for generating parametric images from medical imaging data of a single study. By assuming that all voxels in the image are independent, we used simulation and animal data to evaluate whether NLME can improve the voxel-wise parameter estimation. For testing purposes, intravoxel incoherent motion (IVIM) diffusion parameters including perfusion fraction, pseudo-diffusion coefficient and true diffusion coefficient were estimated using diffusion-weighted MR images and NLME through fitting the IVIM model. The conventional method of non-linear least squares (NLLS) was used as the standard approach for comparison of the resulted parametric images. In the simulated data, NLME provides more accurate and precise estimates of diffusion parameters compared with NLLS. Similarly, we found that NLME has the ability to improve the signal-to-noise ratio of parametric images obtained from rat brain data. These data have shown that it is feasible to apply NLME in parametric image generation, and the parametric image quality can be accordingly improved with the use of NLME. With the flexibility to be adapted to other models or modalities, NLME may become a useful tool to improve the parametric image quality in the future. Copyright © 2015 John Wiley & Sons, Ltd.

Metabolic and hypoxic adaptation to anti-angiogenic therapy: a target for induced essentiality

Anti-angiogenic therapy has increased the progression-free survival of many cancer patients but has had little effect on overall survival, even in colon cancer (average 6-8 weeks) due to resistance. The current licensed targeted therapies all inhibit VEGF signalling (Table 1). Many mechanisms of resistance to anti-VEGF therapy have been identified that enable cancers to bypass the angiogenic blockade. In addition, over the last decade, there has been increasing evidence for the role that the hypoxic and metabolic responses play in tumour adaptation to anti-angiogenic therapy. The hypoxic tumour response, through the transcription factor hypoxia-inducible factors (HIFs), induces major gene expression, metabolic and phenotypic changes, including increased invasion and metastasis. Pre-clinical studies combining anti-angiogenics with inhibitors of tumour hypoxic and metabolic adaptation have shown great promise, and combination clinical trials have been instigated. Understanding individual patient response and the response timing, given the opposing effects of vascular normalisation versus reduced perfusion seen with anti-angiogenics, provides a further hurdle in the paradigm of personalised therapeutic intervention. Additional approaches for targeting the hypoxic tumour microenvironment are being investigated in pre-clinical and clinical studies that have potential for producing synthetic lethality in combination with anti-angiogenic therapy as a future therapeutic strategy.