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Title: SU-D-207A-02: Possible Characterization of the Brain Tumor Vascular Environment by a Novel Strategy of Quantitative Analysis in Dynamic Contrast Enhanced MR Imaging: A Combination of Both Patlak and Logan Analyses

Abstract

Purpose: The majority of quantitative analyses involving dynamic contrast enhanced (DCE) MRI have been performed to obtain kinetic parameters such as Ktrans and ve. Such analyses are generally performed assuming a “reversible” tissue compartment, where the tracer is assumed to be rapidly equilibrated between the plasma and tissue compartments. However, some tumor vascular environments may be more suited for a “non-reversible” tissue compartment, where, as with FDG PET imaging, the tracer is continuously deposited into the tissue compartment (or the return back to the plasma compartment is very slow in the imaging time scale). Therefore, Patlak and Logan analyses, which represent tools for the “non-reversible” and “reversible” modeling, respectively, were performed to better characterize the brain tumor vascular environment. Methods: A voxel-by-voxel analysis was performed to generate both Patlak and Logan plots in two brain tumor patients, one with grade III astrocytoma and the other with grade IV astrocytoma or glioblastoma. The slopes of plots and the r-square were then obtained by linear fitting and compared for each voxel. Results: The 2-dimensional scatter plots of Logan (Y-axis) vs. Patlak slopes (X-axis) clearly showed increased Logan slopes for glioblastoma (Figure 3A). The scatter plots of goodness-of-fit (Figure 3B) also suggested glioblastoma,more » relative to grade III astrocytoma, might consist of more voxels that are kinetically Logan-like (i.e. rapidly equilibrated extravascular space and active vascular environment). Therefore, the enhanced Logan-like behavior (and the Logan slope) in glioblastoma may imply an increased fraction of active vascular environment, while the enhanced Patlak-like behavior implies the vascular environment permitting a relatively slower washout of the tracer. Conclusion: Although further verification is required, the combination of Patlak and Logan analyses in DCE MRI may be useful in characterizing the tumor vascular environment, and thus, may have implications in tumor grading and monitoring response to anti-vascular therapy.« less

Authors:
; ; ; ;  [1]
  1. Beaumont Health System, Royal Oak, MI (United States)
Publication Date:
OSTI Identifier:
22624393
Resource Type:
Journal Article
Resource Relation:
Journal Name: Medical Physics; Journal Volume: 43; Journal Issue: 6; Other Information: (c) 2016 American Association of Physicists in Medicine; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
60 APPLIED LIFE SCIENCES; 61 RADIATION PROTECTION AND DOSIMETRY; ANIMAL TISSUES; ASTROCYTOMAS; BIOMEDICAL RADIOGRAPHY; BRAIN; NMR IMAGING; POSITRON COMPUTED TOMOGRAPHY; THERAPY

Citation Formats

Yee, S, Chinnaiyan, P, Wloch, J, Pirkola, M, and Yan, D. SU-D-207A-02: Possible Characterization of the Brain Tumor Vascular Environment by a Novel Strategy of Quantitative Analysis in Dynamic Contrast Enhanced MR Imaging: A Combination of Both Patlak and Logan Analyses. United States: N. p., 2016. Web. doi:10.1118/1.4955649.
Yee, S, Chinnaiyan, P, Wloch, J, Pirkola, M, & Yan, D. SU-D-207A-02: Possible Characterization of the Brain Tumor Vascular Environment by a Novel Strategy of Quantitative Analysis in Dynamic Contrast Enhanced MR Imaging: A Combination of Both Patlak and Logan Analyses. United States. doi:10.1118/1.4955649.
Yee, S, Chinnaiyan, P, Wloch, J, Pirkola, M, and Yan, D. 2016. "SU-D-207A-02: Possible Characterization of the Brain Tumor Vascular Environment by a Novel Strategy of Quantitative Analysis in Dynamic Contrast Enhanced MR Imaging: A Combination of Both Patlak and Logan Analyses". United States. doi:10.1118/1.4955649.
@article{osti_22624393,
title = {SU-D-207A-02: Possible Characterization of the Brain Tumor Vascular Environment by a Novel Strategy of Quantitative Analysis in Dynamic Contrast Enhanced MR Imaging: A Combination of Both Patlak and Logan Analyses},
author = {Yee, S and Chinnaiyan, P and Wloch, J and Pirkola, M and Yan, D},
abstractNote = {Purpose: The majority of quantitative analyses involving dynamic contrast enhanced (DCE) MRI have been performed to obtain kinetic parameters such as Ktrans and ve. Such analyses are generally performed assuming a “reversible” tissue compartment, where the tracer is assumed to be rapidly equilibrated between the plasma and tissue compartments. However, some tumor vascular environments may be more suited for a “non-reversible” tissue compartment, where, as with FDG PET imaging, the tracer is continuously deposited into the tissue compartment (or the return back to the plasma compartment is very slow in the imaging time scale). Therefore, Patlak and Logan analyses, which represent tools for the “non-reversible” and “reversible” modeling, respectively, were performed to better characterize the brain tumor vascular environment. Methods: A voxel-by-voxel analysis was performed to generate both Patlak and Logan plots in two brain tumor patients, one with grade III astrocytoma and the other with grade IV astrocytoma or glioblastoma. The slopes of plots and the r-square were then obtained by linear fitting and compared for each voxel. Results: The 2-dimensional scatter plots of Logan (Y-axis) vs. Patlak slopes (X-axis) clearly showed increased Logan slopes for glioblastoma (Figure 3A). The scatter plots of goodness-of-fit (Figure 3B) also suggested glioblastoma, relative to grade III astrocytoma, might consist of more voxels that are kinetically Logan-like (i.e. rapidly equilibrated extravascular space and active vascular environment). Therefore, the enhanced Logan-like behavior (and the Logan slope) in glioblastoma may imply an increased fraction of active vascular environment, while the enhanced Patlak-like behavior implies the vascular environment permitting a relatively slower washout of the tracer. Conclusion: Although further verification is required, the combination of Patlak and Logan analyses in DCE MRI may be useful in characterizing the tumor vascular environment, and thus, may have implications in tumor grading and monitoring response to anti-vascular therapy.},
doi = {10.1118/1.4955649},
journal = {Medical Physics},
number = 6,
volume = 43,
place = {United States},
year = 2016,
month = 6
}
  • Purpose: To investigate whether changes in the volume transfer coefficient (K{sup trans}) in a growing tumor could be used as a surrogate marker for predicting tumor responses to radiation therapy (RT) and chemotherapy (CT). Methods and Materials: Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) was consecutively performed on tumor-bearing mice, and temporal and spatial changes of K{sup trans} values were measured along with tumor growth. Tumor responses to RT and CT were studied before and after observed changes in K{sup trans} values with time. Results: Dynamic changes with an initial increase and subsequent decline in K{sup trans} values were found tomore » be associated with tumor growth. When each tumor was divided into core and peripheral regions, the K{sup trans} decline was greater in core, although neither vascular structure or necrosis could be linked to this spatial difference. Tumor responses to RT were worse if applied after the decline of K{sup trans}, and there was less drug distribution and cell death in the tumor core after CT. Conclusion: The K{sup trans} value in growing tumors, reflecting the changes of tumor microenvironment and vascular function, is strongly associated with tumor responses to RT and CT and could be a potential surrogate marker for predicting the tumor response to these treatments.« less
  • Objectives: Development of perfusion imaging as a biomarker requires more robust methodologies for quantification of tumor physiology that allow assessment of volumetric tumor heterogeneity over time. This study proposes a parametric method for automatically analyzing perfused tissue from volumetric dynamic contrast-enhanced (DCE) computed tomography (CT) scans and assesses whether this 4-dimensional (4D) DCE approach is more robust and accurate than conventional, region-of-interest (ROI)-based CT methods in quantifying tumor perfusion with preliminary evaluation in metastatic brain cancer. Methods and Materials: Functional parameter reproducibility and analysis of sensitivity to imaging resolution and arterial input function were evaluated in image sets acquired from amore » 320-slice CT with a controlled flow phantom and patients with brain metastases, whose treatments were planned for stereotactic radiation surgery and who consented to a research ethics board-approved prospective imaging biomarker study. A voxel-based temporal dynamic analysis (TDA) methodology was used at baseline, at day 7, and at day 20 after treatment. The ability to detect changes in kinetic parameter maps in clinical data sets was investigated for both 4D TDA and conventional 2D ROI-based analysis methods. Results: A total of 7 brain metastases in 3 patients were evaluated over the 3 time points. The 4D TDA method showed improved spatial efficacy and accuracy of perfusion parameters compared to ROI-based DCE analysis (P<.005), with a reproducibility error of less than 2% when tested with DCE phantom data. Clinically, changes in transfer constant from the blood plasma into the extracellular extravascular space (K{sub trans}) were seen when using TDA, with substantially smaller errors than the 2D method on both day 7 post radiation surgery (±13%; P<.05) and by day 20 (±12%; P<.04). Standard methods showed a decrease in K{sub trans} but with large uncertainty (111.6 ± 150.5) %. Conclusions: Parametric voxel-based analysis of 4D DCE CT data resulted in greater accuracy and reliability in measuring changes in perfusion CT-based kinetic metrics, which have the potential to be used as biomarkers in patients with metastatic brain cancer.« less
  • Purpose: To analyze, in a pilot study, rapidly acquired dynamic contrast-enhanced (DCE)-MRI data with a general two-compartment exchange tracer kinetic model and correlate parameters obtained with measurements of hypoxia and vascular endothelial growth factor (VEGF) expression in patients with squamous cell carcinoma of the head and neck. Methods and Materials: Eight patients were scanned before surgery. The DCE-MRI data were acquired with 1.5-s temporal resolution and analyzed using the two-compartment exchange tracer kinetic model to obtain estimates of parameters including perfusion and permeability surface area. Twelve to 16 h before surgery, patients received an intravenous injection of pimonidazole. Samples takenmore » during surgery were used to determine the level of pimonidazole staining using immunohistochemistry and VEGF expression using quantitative real-time polymerase chain reaction. Correlations between the biological and imaging data were examined. Results: Of the seven tumors fully analyzed, those that were poorly perfused tended to have high levels of pimonidazole staining (r = -0.79, p = 0.03) and VEGF expression (r = -0.82, p = 0.02). Tumors with low permeability surface area also tended to have high levels of hypoxia (r = -0.75, p = 0.05). Hypoxic tumors also expressed higher levels of VEGF (r = 0.82, p = 0.02). Conclusions: Estimates of perfusion obtained with rapid DCE-MRI data in patients with head-and-neck cancer correlate inversely with pimonidazole staining and VEGF expression.« less
  • Purpose: To assess noninvasively the tumor microenvironment of neck nodal metastases in patients with head-and-neck cancer by investigating the relationship between tumor perfusion measured using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and hypoxia measured by {sup 18}F-fluoromisonidazole ({sup 18}F-FMISO) positron emission tomography (PET). Methods and Materials: Thirteen newly diagnosed head-and-neck cancer patients with metastatic neck nodes underwent DCE-MRI and {sup 18}F-FMISO PET imaging before chemotherapy and radiotherapy. The matched regions of interests from both modalities were analyzed. To examine the correlations between DCE-MRI parameters and standard uptake value (SUV) measurements from {sup 18}F-FMISO PET, the nonparametric Spearman correlation coefficient wasmore » calculated. Furthermore, DCE-MRI parameters were compared between nodes with {sup 18}F-FMISO uptake and nodes with no {sup 18}F-FMISO uptake using Mann-Whitney U tests. Results: For the 13 patients, a total of 18 nodes were analyzed. The nodal size strongly correlated with the {sup 18}F-FMISO SUV ({rho} = 0.74, p < 0.001). There was a strong negative correlation between the median k{sub ep} (redistribution rate constant) value ({rho} = -0.58, p = 0.042) and the {sup 18}F-FMISO SUV. Hypoxic nodes (moderate to severe {sup 18}F-FMISO uptake) had significantly lower median K{sup trans} (volume transfer constant) (p = 0.049) and median k{sub ep} (p = 0.027) values than did nonhypoxic nodes (no {sup 18}F-FMISO uptake). Conclusion: This initial evaluation of the preliminary results support the hypothesis that in metastatic neck lymph nodes, hypoxic nodes are poorly perfused (i.e., have significantly lower K{sup trans} and k{sub ep} values) compared with nonhypoxic nodes.« less
  • Purpose: For focal boost strategies in the prostate, the robustness of magnetic resonance imaging-based tumor delineations needs to be improved. To this end we developed a statistical model that predicts tumor presence on a voxel level (2.5 Multiplication-Sign 2.5 Multiplication-Sign 2.5 mm3) inside the peripheral zone. Furthermore, we show how this model can be used to derive a valuable input for radiotherapy treatment planning. Methods and Materials: The model was created on 87 radiotherapy patients. For the validation of the voxelwise performance of the model, an independent group of 12 prostatectomy patients was used. After model validation, the model wasmore » stratified to create three different risk levels for tumor presence: gross tumor volume (GTV), high-risk clinical target volume (CTV), and low-risk CTV. Results: The model gave an area under the receiver operating characteristic curve of 0.70 for the prediction of tumor presence in the prostatectomy group. When the registration error between magnetic resonance images and pathologic delineation was taken into account, the area under the curve further improved to 0.89. We propose that model outcome values with a high positive predictive value can be used to define the GTV. Model outcome values with a high negative predictive value can be used to define low-risk CTV regions. The intermediate outcome values can be used to define a high-risk CTV. Conclusions: We developed a logistic regression with a high diagnostic performance for voxelwise prediction of tumor presence. The model output can be used to define different risk levels for tumor presence, which in turn could serve as an input for dose planning. In this way the robustness of tumor delineations for focal boost therapy can be greatly improved.« less