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Simplified Kinetic Analysis of Tumor ¹⁸F-FDG Uptake: A Dynamic Approach

¹ National Institutes of Health, Bethesda, Maryland
² Hadassah University Hospital, Jerusalem, Israel

View larger version (12K): [in a new window]   FIGURE 1. Population input function generated by averaging the input functions from the 18 subjects in population B. The error bars represent the SE of blood activity across all patients.

View larger version (8K): [in a new window]   FIGURE 2. Illustration of SKA-M for 1 field of view. Both axes are similar to regular Patlak analysis except that a population input function, Apop(t), is used for A(t). Ameas(t) is determined as in Equation 2. One-level SKA-M requires only a few late time points (in this case between 25 and 55 min after injection). The regular Patlak analysis requires a full dynamic acquisition from the time of injection to about 60 min. Two-level SKA-M uses only every other point at each field of view, whereas 3-level SKA-M uses every third point from 10 min to 55 min (not shown).

View larger version (9K): [in a new window]   FIGURE 3. (A) Correlation between SKA-S (mL/g/min) and Ki (mL/g/min), along with the regression line. (B) Correlation between 1-level SKA-M (mL/g/min) and Ki (mL/g/min), along with the regression line. Visually, the scatter appears to be larger in the SKA-S plot than in the SKA-M plot. The SD of the data about the line was 3.5% for 1-level SKA-M and 12.9% for SKA-S (P < 0.01). (C) Correlation between 3-level SKA-M (mL/g/min) and Ki (mL/g/min), along with the regression line. There is less variability about the regression line (4.6%) for 3-level SKA-M than for SKA-S (P < 0.05).

View larger version (12K): [in a new window]   FIGURE 4. (A) Effect on SKA-M variability of changing the starting time for the SKA-M fit. The variability of SKA-M progressively increases as later starting times are used. (B) The effect on percentage difference between Ki and SKA-M of changing the starting time for SKA-M. Delaying the starting time for SKA-M results in progressively larger differences between SKA-M and Ki (mean bias of SKA-M).