11 research outputs found

    Dynamic FDG-PET Imaging to Differentiate Malignancies from Inflammation in Subcutaneous and In Situ Mouse Model for Non-Small Cell Lung Carcinoma (NSCLC)

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    <div><p>Background</p><p>[<sup>18</sup>F]fluoro-2-deoxy-D-glucose positron emission tomography (FDG-PET) has been widely used in oncologic procedures such as tumor diagnosis and staging. However, false-positive rates have been high, unacceptable and mainly caused by inflammatory lesions. Misinterpretations take place especially when non-subcutaneous inflammations appear at the tumor site, for instance in the lung. The aim of the current study is to evaluate the use of dynamic PET imaging procedure to differentiate in situ and subcutaneous non-small cell lung carcinoma (NSCLC) from inflammation, and estimate the kinetics of inflammations in various locations.</p><p>Methods</p><p>Dynamic FDG-PET was performed on 33 female mice inoculated with tumor and/or inflammation subcutaneously or inside the lung. Standardized Uptake Values (SUVs) from static imaging (SUVmax) as well as values of influx rate constant (<i>Ki</i>) of compartmental modeling from dynamic imaging were obtained. Static and kinetic data from different lesions (tumor and inflammations) or different locations (subcutaneous, in situ and spontaneous group) were compared.</p><p>Results</p><p>Values of SUVmax showed significant difference in subcutaneous tumor and inflammation (<i>p</i><0.01), and in inflammations from different locations (<i>p</i><0.005). However, SUVmax showed no statistical difference between in situ tumor and inflammation (<i>p</i> = 1.0) and among tumors from different locations (subcutaneous and in situ, <i>p</i> = 0.91). Values of <i>Ki</i> calculated from compartmental modeling showed significant difference between tumor and inflammation both subcutaneously (<i>p</i><0.005) and orthotopically (<i>p</i><0.01). <i>Ki</i> showed also location specific values for inflammations (subcutaneous, in situ and spontaneous, <i>p</i><0.015). However, <i>Ki</i> of tumors from different locations (subcutaneous and in situ) showed no significant difference (<i>p</i> = 0.46).</p><p>Conclusion</p><p>In contrast to static PET based SUVmax, both subcutaneous and in situ inflammations and malignancies can be differentiated via dynamic FDG-PET based <i>Ki</i>. Moreover, Values of influx rate constant <i>Ki</i> from compartmental modeling can offer an assessment for inflammations at different locations of the body, which also implies further validation is necessary before the replacement of in situ inflammation with its subcutaneous counterpart in animal experiments.</p></div

    Examples of visual analysis.

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    <p>(A) In situ tumor. Red arrow: high FDG uptake caused by tumor inside the lung (value of SUV was around 1.7) (B) In situ inflammation. Yellow arrow: high FDG uptake caused by inflammation inside the lung (value of SUV was also around 1.7)</p

    Values of influx rate constant <i>Ki</i> from kinetic analysis.

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    <p><sup>a</sup>Influx rate constant <i>Ki</i> were calculated from estimated parameter values as (K<sub>1</sub>k<sub>3</sub>) / (k<sub>2</sub> + k<sub>3</sub>)</p><p>Values of influx rate constant <i>Ki</i> from kinetic analysis.</p

    Comparison of SUVmax and <i>Ki</i> in tumor or inflammation from different body locations.

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    <p>(A) SUVmax from tumor groups. (B) SUVmax from inflammation groups. (C) <i>Ki</i> from tumor groups. (D) <i>Ki</i> from inflammation groups.</p

    Comparison of SUVmax and <i>Ki</i> in tumors and inflammations from the same body location.

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    <p>(A) SUVmax from subcutaneous groups. (B) SUVmax from in situ groups. (C) <i>Ki</i> from subcutaneous groups. (D) <i>Ki</i> from in situ groups.</p
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