The ISMRM Open Science Initiative for Perfusion Imaging (OSIPI): Results from the OSIPI-Dynamic Contrast-Enhanced challenge.

PURPOSE: K trans $$ {K}^{\mathrm{trans}} $$ has often been proposed as a quantitative imaging biomarker for diagnosis, prognosis, and treatment response assessment for various tumors. None of the many software tools for K trans $$ {K}^{\mathrm{trans}} $$ quantification are standardized. The ISMRM Open Science Initiative for Perfusion Imaging-Dynamic Contrast-Enhanced (OSIPI-DCE) challenge was designed to benchmark methods to better help the efforts to standardize K trans $$ {K}^{\mathrm{trans}} $$ measurement. METHODS: A framework was created to evaluate K trans $$ {K}^{\mathrm{trans}} $$ values produced by DCE-MRI analysis pipelines to enable benchmarking. The perfusion MRI community was invited to apply their pipelines for K trans $$ {K}^{\mathrm{trans}} $$ quantification in glioblastoma from clinical and synthetic patients. Submissions were required to include the entrants' K trans $$ {K}^{\mathrm{trans}} $$ values, the applied software, and a standard operating procedure. These were evaluated using the proposed OSIP I gold $$ \mathrm{OSIP}{\mathrm{I}}_{\mathrm{gold}} $$ score defined with accuracy, repeatability, and reproducibility components. RESULTS: Across the 10 received submissions, the OSIP I gold $$ \mathrm{OSIP}{\mathrm{I}}_{\mathrm{gold}} $$ score ranged from 28% to 78% with a 59% median. The accuracy, repeatability, and reproducibility scores ranged from 0.54 to 0.92, 0.64 to 0.86, and 0.65 to 1.00, respectively (0-1 = lowest-highest). Manual arterial input function selection markedly affected the reproducibility and showed greater variability in K trans $$ {K}^{\mathrm{trans}} $$ analysis than automated methods. Furthermore, provision of a detailed standard operating procedure was critical for higher reproducibility. CONCLUSIONS: This study reports results from the OSIPI-DCE challenge and highlights the high inter-software variability within K trans $$ {K}^{\mathrm{trans}} $$ estimation, providing a framework for ongoing benchmarking against the scores presented. Through this challenge, the participating teams were ranked based on the performance of their software tools in the particular setting of this challenge. In a real-world clinical setting, many of these tools may perform differently with different benchmarking methodology.

First-in-human technique translation of oxygen-enhanced MRI to an MR Linac system in patients with head and neck cancer.

BACKGROUND AND PURPOSE: Tumour hypoxia is prognostic in head and neck cancer (HNC), associated with poor loco-regional control, poor survival and treatment resistance. The advent of hybrid MRI - radiotherapy linear accelerator or 'MR Linac' systems - could permit imaging for treatment adaptation based on hypoxic status. We sought to develop oxygen-enhanced MRI (OE-MRI) in HNC and translate the technique onto an MR Linac system. MATERIALS AND METHODS: MRI sequences were developed in phantoms and 15 healthy participants. Next, 14 HNC patients (with 21 primary or local nodal tumours) were evaluated. Baseline tissue longitudinal relaxation time (T1) was measured alongside the change in 1/T1 (termed ΔR1) between air and oxygen gas breathing phases. We compared results from 1.5 T diagnostic MR and MR Linac systems. RESULTS: Baseline T1 had excellent repeatability in phantoms, healthy participants and patients on both systems. Cohort nasal concha oxygen-induced ΔR1 significantly increased (p < 0.0001) in healthy participants demonstrating OE-MRI feasibility. ΔR1 repeatability coefficients (RC) were 0.023-0.040 s-1 across both MR systems. The tumour ΔR1 RC was 0.013 s-1 and the within-subject coefficient of variation (wCV) was 25% on the diagnostic MR. Tumour ΔR1 RC was 0.020 s-1 and wCV was 33% on the MR Linac. ΔR1 magnitude and time-course trends were similar on both systems. CONCLUSION: We demonstrate first-in-human translation of volumetric, dynamic OE-MRI onto an MR Linac system, yielding repeatable hypoxia biomarkers. Data were equivalent on the diagnostic MR and MR Linac systems. OE-MRI has potential to guide future clinical trials of biology guided adaptive radiotherapy.

Clinical translation of quantitative magnetic resonance imaging biomarkers - An overview and gap analysis of current practice.

PURPOSE: This overview of the current landscape of quantitative magnetic resonance imaging biomarkers (qMR IBs) aims to support the standardisation of academic IBs to assist their translation to clinical practice. METHODS: We used three complementary approaches to investigate qMR IB use and quality management practices within the UK: 1) a literature search of qMR and quality management terms during 2011-2015 and 2016-2020; 2) a database search for clinical research studies using qMR IBs during 2016-2020; and 3) a survey to ascertain the current availability and quality management practices for clinical MRI scanners and associated equipment at research institutions across the UK. RESULTS: The analysis showed increased use of all qMR methods between the periods 2011-2015 and 2016-2020 and diffusion-tensor MRI and volumetry to be popular methods. However, the "translation ratio" of journal articles to clinical research studies was higher for qMR methods that have evidence of clinical translation via a commercial route, such as fat fraction and T2 mapping. The number of journal articles citing quality management terms doubled between the periods 2011-2015 and 2016-2020; although, its proportion relative to all journal articles only increased by 3.0%. The survey suggested that quality assurance (QA) and quality control (QC) of data acquisition procedures are under-reported in the literature and that QA/QC of acquired data/data analysis are under-developed and lack consistency between institutions. CONCLUSIONS: We summarise current attempts to standardise and translate qMR IBs, and conclude by outlining the ideal quality management practices and providing a gap analysis between current practice and a metrological standard.

Habitat Imaging of Tumors Enables High Confidence Sub-Regional Assessment of Response to Therapy.

Imaging biomarkers are used in therapy development to identify and quantify therapeutic response. In oncology, use of MRI, PET and other imaging methods can be complicated by spatially complex and heterogeneous tumor micro-environments, non-Gaussian data and small sample sizes. Linear Poisson Modelling (LPM) enables analysis of complex data that is quantitative and can operate in small data domains. We performed experiments in 5 mouse models to evaluate the ability of LPM to identify responding tumor habitats across a range of radiation and targeted drug therapies. We tested if LPM could identify differential biological response rates. We calculated the theoretical sample size constraints for applying LPM to new data. We then performed a co-clinical trial using small data to test if LPM could detect multiple therapeutics with both improved power and reduced animal numbers compared to conventional t-test approaches. Our data showed that LPM greatly increased the amount of information extracted from diffusion-weighted imaging, compared to cohort t-tests. LPM distinguished biological response rates between Calu6 tumors treated with 3 different therapies and between Calu6 tumors and 4 other xenograft models treated with radiotherapy. A simulated co-clinical trial using real data detected high precision per-tumor treatment effects in as few as 3 mice per cohort, with p-values as low as 1 in 10,000. These findings provide a route to simultaneously improve the information derived from preclinical imaging while reducing and refining the use of animals in cancer research.

Quantitative Magnetic Resonance Imaging in Perianal Crohn's Disease at 1.5 and 3.0 T: A Feasibility Study.

Perianal Crohn's Disease (pCD) is a common manifestation of Crohn's Disease. Absence of reliable disease measures makes disease monitoring unreliable. Qualitative MRI has been increasingly used for diagnosing and monitoring pCD and has shown potential for assessing response to treatment. Quantitative MRI sequences, such as diffusion-weighted imaging (DWI), dynamic contrast enhancement (DCE) and magnetisation transfer (MT), along with T2 relaxometry, offer opportunities to improve diagnostic capability. Quantitative MRI sequences (DWI, DCE, MT and T2) were used in a cohort of 25 pCD patients before and 12 weeks after biological therapy at two different field strengths (1.5 and 3 T). Disease activity was measured with the Perianal Crohn's Disease Activity index (PDAI) and serum C-reactive protein (CRP). Diseased tissue areas on MRI were defined by a radiologist. A baseline model to predict outcome at 12 weeks was developed. No differences were seen in the quantitative MR measured in the diseased tissue regions from baseline to 12 weeks; however, PDAI and CRP decreased. Baseline PDAI, CRP, T2 relaxometry and surgical history were found to have a moderate ability to predict response after 12 weeks of biological treatment. Validation in larger cohorts with MRI and clinical measures are needed in order to further develop the model.

A model selection framework to quantify microvascular liver function in gadoxetate-enhanced MRI: Application to healthy liver, diseased tissue, and hepatocellular carcinoma.

PURPOSE: We introduce a novel, generalized tracer kinetic model selection framework to quantify microvascular characteristics of liver and tumor tissue in gadoxetate-enhanced dynamic contrast-enhanced MRI (DCE-MRI). METHODS: Our framework includes a hierarchy of nested models, from which physiological parameters are derived in 2 regimes, corresponding to the active transport and free diffusion of gadoxetate. We use simulations to show the sensitivity of model selection and parameter estimation to temporal resolution, time-series duration, and noise. We apply the framework in 8 healthy volunteers (time-series duration up to 24 minutes) and 10 patients with hepatocellular carcinoma (6 minutes). RESULTS: The active transport regime is preferred in 98.6% of voxels in volunteers, 82.1% of patients' non-tumorous liver, and 32.2% of tumor voxels. Interpatient variations correspond to known co-morbidities. Simulations suggest both datasets have sufficient temporal resolution and signal-to-noise ratio, while patient data would be improved by using a time-series duration of at least 12 minutes. CONCLUSIONS: In patient data, gadoxetate exhibits different kinetics: (a) between liver and tumor regions and (b) within regions due to liver disease and/or tumor heterogeneity. Our generalized framework selects a physiological interpretation at each voxel, without preselecting a model for each region or duplicating time-consuming optimizations for models with identical functional forms.

Effect of oxaliplatin plus 5-fluorouracil or capecitabine on circulating and imaging biomarkers in patients with metastatic colorectal cancer: a prospective biomarker study.

BACKGROUND: Patients with metastatic colorectal cancer are treated with cytotoxic chemotherapy supplemented by molecularly targeted therapies. There is a critical need to define biomarkers that can optimise the use of these therapies to maximise efficacy and avoid unnecessary toxicity. However, it is important to first define the changes in potential biomarkers following cytotoxic chemotherapy alone. This study reports the impact of standard cytotoxic chemotherapy across a range of circulating and imaging biomarkers. METHODS: A single-centre, prospective, biomarker-driven study. Eligible patients included those diagnosed with colorectal cancer with liver metastases that were planned to receive first line oxaliplatin plus 5-fluorouracil or capecitabine. Patients underwent paired blood sampling and magnetic resonance imaging (MRI), and biomarkers were associated with progression-free survival (PFS) and overall survival (OS). RESULTS: Twenty patients were recruited to the study. Data showed that chemotherapy significantly reduced the number of circulating tumour cells as well as the circulating concentrations of Ang1, Ang2, VEGF-A, VEGF-C and VEGF-D from pre-treatment to cycle 2 day 2. The changes in circulating concentrations were not associated with PFS or OS. On average, the MRI perfusion/permeability parameter, Ktrans, increased in response to cytotoxic chemotherapy from pre-treatment to cycle 2 day 2 and this increase was associated with worse OS (HR 1.099, 95%CI 1.01-1.20, p = 0.025). CONCLUSIONS: In patients diagnosed with colorectal cancer with liver metastases, treatment with standard chemotherapy changes cell- and protein-based biomarkers, although these changes are not associated with survival outcomes. In contrast, the imaging biomarker, Ktrans, offers promise to direct molecularly targeted therapies such as anti-angiogenic agents.

Image Contrast, Image Pre-Processing, and T1 Mapping Affect MRI Radiomic Feature Repeatability in Patients with Colorectal Cancer Liver Metastases.

Imaging biomarkers require technical, biological, and clinical validation to be translated into robust tools in research or clinical settings. This study contributes to the technical validation of radiomic features from magnetic resonance imaging (MRI) by evaluating the repeatability of features from four MR sequences: pre-contrast T1- and T2-weighted images, pre-contrast quantitative T1 maps (qT1), and contrast-enhanced T1-weighted images. Fifty-one patients with colorectal cancer liver metastases were scanned twice, up to 7 days apart. Repeatability was quantified using the intraclass correlation coefficient (ICC) and repeatability coefficient (RC), and the impact of non-Gaussian feature distributions and image normalisation was evaluated. Most radiomic features had non-Gaussian distributions, but Box-Cox transformations enabled ICCs and RCs to be calculated appropriately for an average of 97% of features across sequences. ICCs ranged from 0.30 to 0.99, with volume and other shape features tending to be most repeatable; volume ICC > 0.98 for all sequences. 19% of features from non-normalised images exhibited significantly different ICCs in pair-wise sequence comparisons. Normalisation tended to increase ICCs for pre-contrast T1- and T2-weighted images, and decrease ICCs for qT1 maps. RCs tended to vary more between sequences than ICCs, showing that evaluations of feature performance depend on the chosen metric. This work suggests that feature-specific repeatability, from specific combinations of MR sequence and pre-processing steps, should be evaluated to select robust radiomic features as biomarkers in specific studies. In addition, as different repeatability metrics can provide different insights into a specific feature, consideration of the appropriate metric should be taken in a study-specific context.

Oxygen-enhanced MRI Is Feasible, Repeatable, and Detects Radiotherapy-induced Change in Hypoxia in Xenograft Models and in Patients with Non-small Cell Lung Cancer.

PURPOSE: Hypoxia is associated with poor prognosis and is predictive of poor response to cancer treatments, including radiotherapy. Developing noninvasive biomarkers that both detect hypoxia prior to treatment and track change in tumor hypoxia following treatment is required urgently. EXPERIMENTAL DESIGN: We evaluated the ability of oxygen-enhanced MRI (OE-MRI) to map and quantify therapy-induced changes in tumor hypoxia by measuring oxygen-refractory signals in perfused tissue (perfused Oxy-R). Clinical first-in-human study in patients with non-small cell lung cancer (NSCLC) was performed alongside preclinical experiments in two xenograft tumors (Calu6 NSCLC model and U87 glioma model). RESULTS: MRI perfused Oxy-R tumor fraction measurement of hypoxia was validated with ex vivo tissue pathology in both xenograft models. Calu6 and U87 experiments showed that MRI perfused Oxy-R tumor volume was reduced relative to control following single fraction 10-Gy radiation and fractionated chemoradiotherapy (P < 0.001) due to both improved perfusion and reduced oxygen consumption rate. Next, evaluation of 23 patients with NSCLC showed that OE-MRI was clinically feasible and that tumor perfused Oxy-R volume is repeatable [interclass correlation coefficient: 0.961 (95% CI, 0.858-0.990); coefficient of variation: 25.880%]. Group-wise perfused Oxy-R volume was reduced at 14 days following start of radiotherapy (P = 0.015). OE-MRI detected between-subject variation in hypoxia modification in both xenograft and patient tumors. CONCLUSIONS: These findings support applying OE-MRI biomarkers to monitor hypoxia modification, to stratify patients in clinical trials of hypoxia-modifying therapies, to identify patients with hypoxic tumors that may fail treatment with immunotherapy, and to guide adaptive radiotherapy by mapping regional hypoxia.

Plasma Tie2 is a tumor vascular response biomarker for VEGF inhibitors in metastatic colorectal cancer.

Oncological use of anti-angiogenic VEGF inhibitors has been limited by the lack of informative biomarkers. Previously we reported circulating Tie2 as a vascular response biomarker for bevacizumab-treated ovarian cancer patients. Using advanced MRI and circulating biomarkers we have extended these findings in metastatic colorectal cancer (n = 70). Bevacizumab (10 mg/kg) was administered to elicit a biomarker response, followed by FOLFOX6-bevacizumab until disease progression. Bevacizumab induced a correlation between Tie2 and the tumor vascular imaging biomarker, Ktrans (R:-0.21 to 0.47) implying that Tie2 originated from the tumor vasculature. Tie2 trajectories were independently associated with pre-treatment tumor vascular characteristics, tumor response, progression free survival (HR for progression = 3.01, p = 0.00014; median PFS 248 vs. 348 days p = 0.0008) and the modeling of progressive disease (p < 0.0001), suggesting that Tie2 should be monitored clinically to optimize VEGF inhibitor use. A vascular response is defined as a 30% reduction in Tie2; vascular progression as a 40% increase in Tie2 above the nadir. Tie2 is the first, validated, tumor vascular response biomarker for VEGFi.

Mapping Hypoxia in Renal Carcinoma with Oxygen-enhanced MRI: Comparison with Intrinsic Susceptibility MRI and Pathology.

Purpose To cross-validate T1-weighted oxygen-enhanced (OE) MRI measurements of tumor hypoxia with intrinsic susceptibility MRI measurements and to demonstrate the feasibility of translation of the technique for patients. Materials and Methods Preclinical studies in nine 786-0-R renal cell carcinoma (RCC) xenografts and prospective clinical studies in eight patients with RCC were performed. Longitudinal relaxation rate changes (∆R1) after 100% oxygen inhalation were quantified, reflecting the paramagnetic effect on tissue protons because of the presence of molecular oxygen. Native transverse relaxation rate (R2*) and oxygen-induced R2* change (∆R2*) were measured, reflecting presence of deoxygenated hemoglobin molecules. Median and voxel-wise values of ∆R1 were compared with values of R2* and ∆R2*. Tumor regions with dynamic contrast agent-enhanced MRI perfusion, refractory to signal change at OE MRI (referred to as perfused Oxy-R), were distinguished from perfused oxygen-enhancing (perfused Oxy-E) and nonperfused regions. R2* and ∆R2* values in each tumor subregion were compared by using one-way analysis of variance. Results Tumor-wise and voxel-wise ∆R1 and ∆R2* comparisons did not show correlative relationships. In xenografts, parcellation analysis revealed that perfused Oxy-R regions had faster native R2* (102.4 sec-1 vs 81.7 sec-1) and greater negative ∆R2* (-22.9 sec-1 vs -5.4 sec-1), compared with perfused Oxy-E and nonperfused subregions (all P < .001), respectively. Similar findings were present in human tumors (P < .001). Further, perfused Oxy-R helped identify tumor hypoxia, measured at pathologic analysis, in both xenografts (P = .002) and human tumors (P = .003). Conclusion Intrinsic susceptibility biomarkers provide cross validation of the OE MRI biomarker perfused Oxy-R. Consistent relationship to pathologic analyses was found in xenografts and human tumors, demonstrating biomarker translation. Published under a CC BY 4.0 license. Online supplemental material is available for this article.

Data-driven mapping of hypoxia-related tumor heterogeneity using DCE-MRI and OE-MRI.

PURPOSE: Previous work has shown that combining dynamic contrast-enhanced (DCE)-MRI and oxygen-enhanced (OE)-MRI binary enhancement maps can identify tumor hypoxia. The current work proposes a novel, data-driven method for mapping tissue oxygenation and perfusion heterogeneity, based on clustering DCE/OE-MRI data. METHODS: DCE-MRI and OE-MRI were performed on nine U87 (glioblastoma) and seven Calu6 (non-small cell lung cancer) murine xenograft tumors. Area under the curve and principal component analysis features were calculated and clustered separately using Gaussian mixture modelling. Evaluation metrics were calculated to determine the optimum feature set and cluster number. Outputs were quantitatively compared with a previous non data-driven approach. RESULTS: The optimum method located six robustly identifiable clusters in the data, yielding tumor region maps with spatially contiguous regions in a rim-core structure, suggesting a biological basis. Mean within-cluster enhancement curves showed physiologically distinct, intuitive kinetics of enhancement. Regions of DCE/OE-MRI enhancement mismatch were located, and voxel categorization agreed well with the previous non data-driven approach (Cohen's kappa = 0.61, proportional agreement = 0.75). CONCLUSION: The proposed method locates similar regions to the previous published method of binarization of DCE/OE-MRI enhancement, but renders a finer segmentation of intra-tumoral oxygenation and perfusion. This could aid in understanding the tumor microenvironment and its heterogeneity. Magn Reson Med 79:2236-2245, 2018. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Evaluation of dynamic contrast-enhanced MRI biomarkers for stratified cancer medicine: How do permeability and perfusion vary between human tumours?

BACKGROUND: Solid tumours exhibit enhanced vessel permeability and fenestrated endothelium to varying degree, but it is unknown how this varies in patients between and within tumour types. Dynamic contrast-enhanced (DCE) MRI provides a measure of perfusion and permeability, the transfer constant Ktrans, which could be employed for such comparisons in patients. AIM: To test the hypothesis that different tumour types exhibit systematically different Ktrans. MATERIALS AND METHODS: DCE-MRI data were retrieved from 342 solid tumours in 230 patients. These data were from 18 previous studies, each of which had had a different analysis protocol. All data were reanalysed using a standardised workflow using an extended Tofts model. A model of the posterior density of median Ktrans was built assuming a log-normal distribution and fitting a simple Bayesian hierarchical model. RESULTS: 12 histological tumour types were included. In glioma, median Ktrans was 0.016min-1 and for non-glioma tumours, median Ktrans ranged from 0.10 (cervical) to 0.21min-1 (prostate metastatic to bone). The geometric mean (95% CI) across all the non-glioma tumours was 0.15 (0.05, 0.45)min-1. There was insufficient separation between the posterior densities to be able to predict the Ktrans value of a tumour given the tumour type, except that the median Ktrans for gliomas was below 0.05min-1 with 80% probability, and median Ktrans measurements for the remaining tumour types were between 0.05 and 0.4min-1 with 80% probability. CONCLUSION: With the exception of glioma, our hypothesis that different tumour types exhibit different Ktrans was not supported. Studies in which tumour permeability is believed to affect outcome should not simply seek tumour types thought to exhibit high permeability. Instead, Ktrans is an idiopathic parameter, and, where permeability is important, Ktrans should be measured in each tumour to personalise that treatment.

Oxygen-Enhanced MRI Accurately Identifies, Quantifies, and Maps Tumor Hypoxia in Preclinical Cancer Models.

There is a clinical need for noninvasive biomarkers of tumor hypoxia for prognostic and predictive studies, radiotherapy planning, and therapy monitoring. Oxygen-enhanced MRI (OE-MRI) is an emerging imaging technique for quantifying the spatial distribution and extent of tumor oxygen delivery in vivo. In OE-MRI, the longitudinal relaxation rate of protons (ΔR1) changes in proportion to the concentration of molecular oxygen dissolved in plasma or interstitial tissue fluid. Therefore, well-oxygenated tissues show positive ΔR1. We hypothesized that the fraction of tumor tissue refractory to oxygen challenge (lack of positive ΔR1, termed "Oxy-R fraction") would be a robust biomarker of hypoxia in models with varying vascular and hypoxic features. Here, we demonstrate that OE-MRI signals are accurate, precise, and sensitive to changes in tumor pO2 in highly vascular 786-0 renal cancer xenografts. Furthermore, we show that Oxy-R fraction can quantify the hypoxic fraction in multiple models with differing hypoxic and vascular phenotypes, when used in combination with measurements of tumor perfusion. Finally, Oxy-R fraction can detect dynamic changes in hypoxia induced by the vasomodulator agent hydralazine. In contrast, more conventional biomarkers of hypoxia (derived from blood oxygenation-level dependent MRI and dynamic contrast-enhanced MRI) did not relate to tumor hypoxia consistently. Our results show that the Oxy-R fraction accurately quantifies tumor hypoxia noninvasively and is immediately translatable to the clinic.