Respiration gating and Bloch fitting improve pH measurements with acidoCEST MRI in an ovarian orthotopic tumor model

A machine learning approach that measures pH using acidoCEST MRI of iopamidol

Tumor acidosis is an important biomarker for aggressive tumors, and extracellular pH (pHe) of the tumor microenvironment can be used to predict and evaluate tumor responses to chemotherapy and immunotherapy. AcidoCEST MRI measures tumor pHe by exploiting the pH-dependent chemical exchange saturation transfer (CEST) effect of iopamidol, an exogenous CT agent repurposed for CEST MRI. However, all pH fitting methodologies for acidoCEST MRI data have limitations. Herein we present results of the application of machine learning for extracting pH values from CEST Z-spectra of iopamidol. We acquired 36,000 experimental CEST spectra from 200 phantoms of iopamidol prepared at five concentrations, five T1 values, and eight pH values at five temperatures, acquired at six saturation powers and six saturation times. We also acquired T1 , T2 , B1 RF power, and B0 magnetic field strength supplementary MR information. These MR images were used to train and validate machine learning models for the tasks of pH classification and pH regression. Specifically, we tested the L1-penalized logistic regression classification (LRC) model and the random forest classification (RFC) model for classifying the CEST Z-spectra for thresholds at pH 6.5 and 7.0. Our results showed that both RFC and LRC were effective for pH classification, although the RFC model achieved higher predictive value, and improved the accuracy of classification accuracy with CEST Z-spectra with a more limited set of saturation frequencies. Furthermore, we used LASSO and random forest regression (RFR) models to explore pH regression, which showed that the RFR model achieved higher accuracy and precision for estimating pH across the entire pH range of 6.2-7.3, especially when using a more limited set of features. Based on these results, machine learning for analysis of acidoCEST MRI is promising for eventual in vivo determination of tumor pHe.

Development of a Nanoscale Chemical Exchange Saturation Transfer Magnetic Resonance Imaging Contrast Agent That Measures pH

AcidoCEST MRI can measure the extracellular pH (pHe) of the tumor microenvironment in mouse models of human cancers and in patients who have cancer. However, chemical exchange saturation transfer (CEST) is an insensitive magnetic resonance imaging (MRI) contrast mechanism, requiring a high concentration of small-molecule agent to be delivered to the tumor. Herein, we developed a nanoscale CEST agent that can measure pH using acidoCEST MRI, which may decrease the requirement for high delivery concentrations of agent. We also developed a monomer agent for comparison to the polymer. After optimizing CEST experimental conditions, we determined that the polymer agent could be used during acidoCEST MRI studies at 125-fold and 488-fold lower concentration than the monomer agent and iopamidol, respectively. We also determined that both agents can measure pH with negligible dependence on temperature. However, pH measurements with both agents were dependent on concentration, which may be due to concentration-dependent changes in hydrogen bonding and/or steric hindrance. We performed in vivo acidoCEST MRI studies using the three agents to study a xenograft MDA-MB-231 model of mammary carcinoma. The tumor pHe measurements were 6.33 ± 0.12, 6.70 ± 0.15, and 6.85 ± 0.15 units with iopamidol, the monomer agent, and polymer agent, respectively. The higher pHe measurements with the monomer and polymer agents were attributed to the concentration dependence of these agents. This study demonstrated that nanoscale agents have merit for CEST MRI studies, but consideration should be given to the dependence of CEST contrast on the concentration of these agents.

Impact of Inhibition of the Mitochondrial Pyruvate Carrier on the Tumor Extracellular pH as Measured by CEST-MRI

(1) Background: The acidosis of the tumor micro-environment may have profound impact on cancer progression and on the efficacy of treatments. In the present study, we evaluated the impact of a treatment with UK-5099, a mitochondrial pyruvate carrier (MPC) inhibitor on tumor extracellular pH (pHe); (2) Methods: glucose consumption, lactate secretion and extracellular acidification rate (ECAR) were measured in vitro after exposure of cervix cancer SiHa cells and breast cancer 4T1 cells to UK-5099 (10 µM). Mice bearing the 4T1 tumor model were treated daily during four days with UK-5099 (3 mg/kg). The pHe was evaluated in vivo using either chemical exchange saturation transfer (CEST)-MRI with iopamidol as pHe reporter probe or ³¹P-NMR spectroscopy with 3-aminopropylphosphonate (3-APP). MR protocols were applied before and after 4 days of treatment; (3) Results: glucose consumption, lactate release and ECAR were increased in both cell lines after UK-5099 exposure. CEST-MRI showed a significant decrease in tumor pHe of 0.22 units in UK-5099-treated mice while there was no change over time for mice treated with the vehicle. Parametric images showed a large heterogeneity in response with 16% of voxels shifting to pHe values under 7.0. In contrast, ³¹P-NMR spectroscopy was unable to detect any significant variation in pHe; (4) Conclusions: MPC inhibition led to a moderate acidification of the extracellular medium in vivo. CEST-MRI provided high resolution parametric images (0.44 µL/voxel) of pHe highlighting the heterogeneity of response within the tumor when exposed to UK-5099.

Imaging methods to evaluate tumor microenvironment factors affecting nanoparticle drug delivery and antitumor response

Standard small molecule and nanoparticulate chemotherapies are used for cancer treatment; however, their effectiveness remains highly variable. One reason for this variable response is hypothesized to be due to nonspecific drug distribution and heterogeneity of the tumor microenvironment, which affect tumor delivery of the agents. Nanoparticle drugs have many theoretical advantages, but due to variability in tumor microenvironment (TME) factors, the overall drug delivery to tumors and associated antitumor response are low. The nanotechnology field would greatly benefit from a thorough analysis of the TME factors that create these physiological barriers to tumor delivery and treatment in preclinical models and in patients. Thus, there is a need to develop methods that can be used to reveal the content of the TME, determine how these TME factors affect drug delivery, and modulate TME factors to increase the tumor delivery and efficacy of nanoparticles. In this review, we will discuss TME factors involved in drug delivery, and how biomedical imaging tools can be used to evaluate tumor barriers and predict drug delivery to tumors and antitumor response.

Measuring Kidney Perfusion, pH, and Renal Clearance Consecutively Using MRI and Multispectral Optoacoustic Tomography

Purpose: To establish multi-modal imaging for the assessment of kidney pH, perfusion, and clearance rate using magnetic resonance imaging (MRI) and multispectral optoacoustic tomography (MSOT) in healthy mice. Kidney pH and perfusion values were measured on a pixel-by-pixel basis using the MRI acidoCEST and FAIR-EPI methods. Kidney filtration rate was measured by analyzing the renal clearance rate of IRdye 800 using MSOT. To test the effect of one imaging method on the other, a set of 3 animals were imaged with MSOT followed by MRI, and a second set of 3 animals were imaged with MRI followed by MSOT. In a subsequent study, the reproducibility of pH, perfusion, and renal clearance measurements were tested by imaging 4 animals twice, separated by 4 days. The contrast agents used for acidoCEST based pH measurements influenced the results of MSOT. Specifically, the exponential decay time from the kidney cortex, as measured by MSOT, was significantly altered when MRI was performed prior to MSOT. However, no significant difference in the cortex to pelvis area under the curve (AUC) was noted. When the order of experiments was reversed, no significant differences were noted in the pH or perfusion values. Reproducibility measurements demonstrated similar pH and cortex to pelvis AUC; however, perfusion values were significantly different with the cortex values being higher and the pelvic values being lower in the second imaging time. We demonstrate that using a combination of MRI and MSOT, physiological measurements of pH, blood flow, and clearance rates can be measured in the mouse kidney in the same imaging session.

Non-invasive Investigation of Tumor Metabolism and Acidosis by MRI-CEST Imaging

Altered metabolism is considered a core hallmark of cancer. By monitoring in vivo metabolites changes or characterizing the tumor microenvironment, non-invasive imaging approaches play a fundamental role in elucidating several aspects of tumor biology. Within the magnetic resonance imaging (MRI) modality, the chemical exchange saturation transfer (CEST) approach has emerged as a new technique that provides high spatial resolution and sensitivity for in vivo imaging of tumor metabolism and acidosis. This mini-review describes CEST-based methods to non-invasively investigate tumor metabolism and important metabolites involved, such as glucose and lactate, as well as measurement of tumor acidosis. Approaches that have been exploited to assess response to anticancer therapies will also be reported for each specific technique.

Extracellular acidosis differentiates pancreatitis and pancreatic cancer in mouse models using acidoCEST MRI

Differentiating pancreatitis from pancreatic cancer would improve diagnostic specificity, and prognosticating pancreatitis that progresses to pancreatic cancer would also improve diagnoses of pancreas pathology. The high glycolytic metabolism of pancreatic cancer can cause tumor acidosis, and different levels of pancreatitis may also have different levels of acidosis, so that extracellular acidosis may be a diagnostic biomarker for these pathologies. AcidoCEST MRI can noninvasively measure extracellular pH (pHe) in the pancreas and pancreatic tissue. We used acidoCEST MRI to measure pHe in a KC model treated with caerulein, which causes pancreatitis followed by development of pancreatic cancer. We also evaluated the KC model treated with PBS, and wild-type mice treated with caerulein or PBS as controls. The caerulein-treated KC cohort had lower pHe of 6.85–6.92 before and during the first 48 h after initiating treatment, relative to a pHe of 6.92 to 7.05 pHe units for the other cohorts. The pHe of the caerulein-treated KC cohort decreased to 6.79 units at 5 weeks when pancreatic tumors were detected with anatomical MRI, and sustained a pHe of 6.75 units at the 8-week time point. Histopathology was used to evaluate and validate the presence of tumors and inflammation in each cohort. These results showed that acidoCEST MRI can differentiate pancreatic cancer from pancreatitis in this mouse model, but does not appear to differentiate pancreatitis that progresses to pancreatic cancer vs. pancreatitis that does not progress to cancer.

In vivo assessment of extracellular pH of joint tissues using acidoCEST-UTE MRI

Background

Degradation of cartilage and meniscus may be mediated by changes in extracellular pH. The purpose of this study was to optimize saturation powers used with the acidoCEST magnetic resonance imaging (MRI) technique with a 3D ultrashort echo time readout (acidoCEST-UTE) and to demonstrate feasibility of the method for measuring pH in cartilage and meniscus in vivo.

Methods

Magnetization transfer ratio asymmetry and ratio of radiofrequency (RF) power mismatch at different powers were evaluated in cartilage and meniscus tissue phantoms for iopamidol and iohexol. Using optimized RF powers, the acidoCEST-UTE MRI sequence was used to assess pH of joint fluid and tissues in four patients after direct intra-articular administration of iodinated contrast.

Results

In the phantoms, the ratio of powers 0.54/1.10 µT showed the strongest correlation with pH. In vivo acidoCEST-UTE pH measurements of intra-articular fluid were similar to electrode measurements of the contrast agent (7.22 vs. 7.1 for iopamidol, respectively; 7.65 vs. 7.5 for iohexol, respectively). As measured with the acidoCEST-UTE technique, overall mean cartilage pH was significantly lower than overall mean meniscus pH (6.60 vs. 6.72, respectively; P=0.043).

Conclusions

AcidoCEST-UTE MRI after direct intra-articular administration of either iopamidol or iohexol can be used to measure cartilage and meniscus pH in vivo.

Differentiating lung cancer and infection based on measurements of extracellular pH with acidoCEST MRI

Lung cancer diagnosis via imaging may be confounded by the presence of indolent infectious nodules in imaging studies. This issue is pervasive in the southwestern US where coccidioidomycosis (Valley Fever) is endemic. AcidoCEST MRI is a noninvasive imaging method that quantifies the extracellular pH (pHe) of tissues in vivo, allowing tumor acidosis to be used as a diagnostic biomarker. Using murine models of lung adenocarcinoma and coccidoidomycosis, we found that average lesion pHe differed significantly between tumors and granulomas. Our study shows that acidoCEST MRI is a promising tool for improving the specificity of lung cancer diagnosis.

Preliminary Results that Assess Metformin Treatment in a Preclinical Model of Pancreatic Cancer Using Simultaneous [18F]FDG PET and acidoCEST MRI

PURPOSE

We sought to determine if the synergy between evaluations of glucose uptake in tumors and extracellular tumor acidosis measured with simultaneous positron emission tomography (PET)/magnetic resonance imaging (MRI) can improve longitudinal evaluations of the response to metformin treatment.

PROCEDURES

A standard 2-deoxy-2-[¹⁸F]fluoro-D-glucose ([¹⁸F]FDG) PET protocol that evaluates glucose uptake in tumors, and a standard acidoCEST MRI protocol that measures extracellular pH (pHe) in tumors, were simultaneously performed to assess eight vehicle-treated (control) mice and eight metformin-treated mice 1 day before treatment, 1 day after initiating daily treatment with metformin, and 7 days after initiating treatment. Longitudinal changes in SUV_max and extracellular pH (pHe) were evaluated for each treatment group, and differences in SUV_max and pHe between metformin-treated and control groups were also evaluated.

RESULTS

MRI acquisition protocols had little effect on the PET count rate, and the PET instrumentation had little effect on image contrast during acidoCEST MRI, verifying that [¹⁸F]FDG PET and acidoCEST MRI can be performed simultaneously. The average SUV_max of the tumor model had a significant decrease after 7 days of treatment with metformin, as expected. The average tumor pHe decreased after 7 days of metformin treatment, which reflected the inhibition of the consumption of cytosolic lactic acid caused by metformin. However, the average SUV_max of the tumor model was not significantly different between the metformin-treated and control groups after 7 days of treatment, and average pHe was also not significantly different between these groups. For comparison, the combination of average SUV_max and pHe measurements significantly differed between the treatment group and control group on Day 7.

CONCLUSIONS

[¹⁸F]FDG PET and acidoCEST MRI studies can be performed simultaneously. The synergistic combination of assessing glucose uptake and tumor acidosis can improve differentiation of a drug-treated group from a control group during drug treatment of a tumor model.

Machine learning improves classification of preclinical models of pancreatic cancer with chemical exchange saturation transfer MRI

PURPOSE

We sought to assess whether machine learning-based classification approaches can improve the classification of pancreatic tumor models relative to more simplistic analysis methods, using T1 relaxation, CEST, and DCE MRI.

METHODS

The T1 relaxation time constants, % CEST at five saturation frequencies, and vascular permeability constants from DCE MRI were measured from Hs 766 T, MIA PaCa-2, and SU.86.86 pancreatic tumor models. We used each of these measurements as predictors for machine learning classifier algorithms. We also used principal component analysis to reduce the dimensionality of entire CEST spectra and DCE signal evolutions, which were then analyzed using classification methods.

RESULTS

The T1 relaxation time constants, % CEST amplitudes at specific saturation frequencies, and the relative Ktrans and kep values from DCE MRI could not classify all three tumor types. However, the area under the curve from DCE signal evolutions could classify each tumor type. Principal component analysis was used to analyze the entire CEST spectrum and DCE signal evolutions, which predicted the correct tumor model with 87.5% and 85.1% accuracy, respectively.

CONCLUSIONS

Machine learning applied to the entire CEST spectrum improved the classification of the three tumor models, relative to classifications that used % CEST values at single saturation frequencies. A similar improvement was not attained with machine learning applied to T1 relaxation times or DCE signal evolutions, relative to more simplistic analysis methods.

A comparison of exogenous and endogenous CEST MRI methods for evaluating in vivo pH

PURPOSE

Extracellular pH (pHe) is an important biomarker for cancer cell metabolism. Acido-chemical exchange saturation transfer (CEST) MRI uses the contrast agent iopamidol to create spatial maps of pHe. Measurements of amide proton transfer exchange rates (kex ) from endogenous CEST MRI were compared to pHe measurements by exogenous acido-CEST MRI to determine whether endogenous kex could be used as a proxy for pHe measurements.

METHODS

Spatial maps of pHe and kex were obtained using exogenous acidoCEST MRI and an endogenous CEST MRI analyzed with the omega plot method, respectively, to evaluate mouse kidney, a flank tumor model, and a spontaneous lung tumor model. The pHe and kex results were evaluated using pixelwise comparisons.

RESULTS

The kex values obtained from endogenous CEST measurements did not correlate with the pHe results from exogenous CEST measurements. The kex measurements were limited to fewer pixels and had a limited dynamic range relative to pHe measurements.

CONCLUSION

Measurements of kex with endogenous CEST MRI cannot substitute for pHe measurements with acidoCEST MRI. Whereas endogenous CEST MRI may still have good utility for evaluating some specific pathologies, exogenous acido-CEST MRI is more appropriate when evaluating pathologies based on pHe values. Magn Reson Med 79:2766-2772, 2018. © 2017 International Society for Magnetic Resonance in Medicine.