PT  - JOURNAL ARTICLE
AU  - Antonia Dimitrakopoulou-Strauss
AU  - Ludwig G. Strauss
AU  - Cyrill Burger
AU  - Anne Rühl
AU  - Gisela Irngartinger
AU  - Wolfgang Stremmel
AU  - Jochen Rudi
TI  - Prognostic Aspects of <sup>18</sup>F-FDG PET Kinetics in Patients with Metastatic Colorectal Carcinoma Receiving FOLFOX Chemotherapy
DP  - 2004 Sep 01
TA  - Journal of Nuclear Medicine
PG  - 1480--1487
VI  - 45
IP  - 9
4099  - http://jnm.snmjournals.org/content/45/9/1480.short
4100  - http://jnm.snmjournals.org/content/45/9/1480.full
SO  - J Nucl Med2004 Sep 01; 45
AB  - We evaluated quantitative measurement series (MS) with 18F-FDG and PET and compared different quantification methods for prediction of individual survival in patients with metastatic colorectal cancer receiving chemotherapy with 5-fluorouracil, folinic acid, and oxaliplatin (FOLFOX). Methods: The study comprised 25 patients. All patients were examined before the onset of FOLFOX therapy and after completion of the first and fourth cycles. SUV, fractal dimension (FD), a 2-compartment model with computation of k1, k2, k3, and k4, and vascular fraction (VB) were used for data evaluation. Survival data served as a reference for the PET data. Discriminant analysis (DA), regression, and best-subset analysis were applied to the data. Results: Twenty of 25 patients died up to 801 d after the first PET study. A cutoff of 1 y (364 d) was used to classify the patients into 2 a priori groups, namely the short- and long-term survival groups. DA was used to predict the 2 categories using SUV and kinetic parameters of 18F-FDG metabolism as predictor variables. SUV provided a correct classification rate (CCR) ranging from 62% to 69%. SUV of the third MS resulted in a CCR of 69% as a single parameter. The best results were yielded by the use of kinetic parameters (k1, k3, VB, and FD) as predictor variables. CCR was 78% using kinetic 18F-FDG parameters of the first and third MS, in comparison with 69% for the corresponding SUVs. A multiple linear regression model was applied to the data to assess the relationship between individual survival and the PET data. The best-subset method revealed a correlation coefficient of 0.850 for the kinetic parameters of the first (k3, k4, VB, and FD) and third (k1, k2, k4, and VB) MS. Conclusion: The combination of kinetic parameters of the first and the third MS is acceptable for classification into a short or long survival class. Furthermore, even an individual prognosis of survival can be achieved using kinetic 18F-FDG parameters of the first and third MS.