Assessment of quantitative FDG PET data in primary colorectal tumours: which parameters are important with respect to tumour detection?
- 217 Downloads
The impact of quantitative parameters on the differentiation of primary colorectal tumours from normal colon tissue was assessed. Dynamic PET data (DPET) were acquired, and compartment and non-compartment modelling applied. The discriminant power of single parameters and the combination of PET parameters was assessed. All lesions were confirmed by histology.
FDG DPET studies were acquired in 22 patients with colorectal tumours prior to surgery. Five of these patients also had liver metastases at the time of the PET study. The SUV 56–60 min p.i. was included in the evaluation. A two-tissue compartment model was applied and the parameters k 1–k 4 as well as the fractional blood volume (V B) were obtained. The FDG influx was calculated from the compartment data. Non-compartment modelling was used to calculate the fractal dimension (FD) of the time-activity data.
FD, SUV, influx and k 3 were the most important single parameters for lesion differentiation. The highest accuracy was achieved for FD (88.78%). The overall tracer uptake was mainly dependent on k 3 and not on k 1 or V B. The support vector machines (SVM) algorithm was used to predict the classification based on the combination of individual PET parameters. The overall accuracy was 97.3%, with only one false positive case and no false negative results. The analysis of the subgroup of five patients with primary tumours and synchronous metastases revealed no significant differences for the individual PET parameters. However, V B tended to be lower while k 1 and k 2 were higher in patients with synchronous metastases. The SVM classification analysis predicted the presence of metastases based on the PET data of the primary tumour in three of five patients.
Quantitative FDG PET studies provide very accurate data for the differentiation of primary colorectal tumours from normal tissue. The use of quantitative data has the advantage that the detection of a colorectal tumour is not primarily dependent on the individual assessment and experience of the physician evaluating the FDG PET data only visually. The results suggest that the presence of metastatic lesions may be predicted by analysis of the dynamic PET data of the corresponding primary tumour. Further studies are needed to assess this aspect in detail.
KeywordsColorectal Compartment Quantitative PET FDG
- 6.Mikolajczyk K, Szabatin M, Rudnicki P, Grodzki M, Burger C. A Java environment for medical image data analysis: initial application for brain PET quantitation. Med Inform 1998;23:207–14.Google Scholar
- 8.Sokoloff L, Smith CB. Basic principles underlying radioisotopic methods for assay of biochemical processes in vivo. In: Greitz T, Ingvar DH, Widén L, editors. The metabolism of the human brain studied with positron emission tomography. New York: Raven Press; 1983; p. 123–48.Google Scholar
- 10.Peitgen HO, Juergens H, Saupe D. Length, area and dimension: measuring complexity and scaling properties. In: Peitgen HO, Juergens H, Saupe D, editors. Chaos and fractals. New York: Springer; 1992; p. 192–219.Google Scholar
- 15.Strauss LG, Clorius JH, Schlag P, Lehner B, Kimmig B, Engenhart R, et al. Recurrence of colorectal tumours: PET evaluation. Radiology 1989;70:329–32.Google Scholar
- 18.Dev P. Basic principles and applications of fractal geometry in pathology: a review. Anal Quant Cytol Histol 2005;27:284–90.Google Scholar
- 22.Dimitrakopoulou-Strauss A, Georgoulias V, Eisenhut M, Koukouraki S, Mäcke HR, Haberkorn U, et al. Quantitative assessment of SSTR2 expression in patients with non-small cell lung cancer using 68Ga-DOTATOC PET and comparison with 18F-FDG PET. Eur J Nucl Med Mol Imaging 2006;33:823–30.PubMedCrossRefGoogle Scholar