Ludwig G. Strauss

Fluorine-18 deoxyglucose and false-positive results: a major problem in the diagnostics of oncological patients

Fluorine-18 deoxyglucose (FDG) is not a very tumour-specific substance, and its accumulation in benign lesions with increased glucose metabolism may give rise to false-positive results and hence cause FDG positron emission tomography (PET) to display relatively low specificity (frequently below 85%). Correct interpretation of FDG PET studies is predicated upon detailed knowledge of morphological abnormalities, and the importance of the correlation of functional and morphological information, as derived from computed tomography or magnetic resonance imaging, is discussed. It is emphasized that image fusion programs cannot substitute for understanding of functional and morphological methods. The reconstruction of PET cross-sections is considered, and it is concluded that an iterative image reconstruction method is to be favoured, given its advantages in reducing image artefacts and improving quantification of radioactivity concentrations. The differentiation of malignant and benign lesions when using FDG PET is then reviewed; false-positive findings may be obtained, for example, in patients with acute inflammatory lesions, chronic pancretitis, retroperitoneal fibrosis or salivary gland tumours. It is suggested that these problems may be alleviated by means of multitracer studies, e.g. using carbon-11 labelled aminoisobutyric acid for quantification of A-type amino acid transport. Finally, the effects of radiotherapy and chemotherapy on FDG uptake and the problems that accrue from these effects are reviewed. Both radiotherapy and chemotherapy can cause increased FDG uptake, complicating diagnosis and evaluation. Knowledge of the effects of different treatment procedures on regional FDG metabolism is therefore necessary for correct interpretation of the PET data.

Three dimensional image correlation of CT, MR, and PET studies in radiotherapy treatment planning of brain tumors

Abstract A treatment planning system for stereotactic convergent beam irradiation of deeply localized brain tumors is reported. The treatment technique consists of several moving field irradiations in noncoplanar planes at a linear accelerator facility. Using collimated narrow beams, a high concentration of dose within small volumes with a dose gradient of 10-15%/mm was obtained. The dose calculation was based on geometrical information of multiplanar CT or magnetic resonance (MR) imaging data. The patients head was fixed in a stereotactic localization system, which is usable at CT, MR, and positron emission tomography (PET) installations. Special computer programs for correction of the geometrical MR distortions allowed a precise correlation of the different imaging modalities. The therapist can use combinations of CT, MR, and PET data for defining target volume. For instance, the superior soft tissue contrast of MR coupled with the metabolic features of PET may be a useful addition in the radiation treatment planning process. Furthermore, other features such as calculated dose distribution to critical structures can also be transferred from one set of imaging data to another and can be displayed as three-dimensional shaded structures.

68Ga-Labeled Bombesin Studies in Patients with Gastrointestinal Stromal Tumors: Comparison with 18F-FDG

Dynamic PET studies with a 68Ga-bombesin analog, DOTA-PEG2-[d-Tyr6, β-Ala11,Thi13,Nle14] BN(6-14) amide (68Ga-BZH3; DOTA is 1,4,7,10-tetraazacyclododecane-N,N′,N″,N‴-tetraacetic acid, and PEG is ethylene glycol [2-aminoethyl-carboxymethyl ether]), were performed on patients with gastrointestinal stromal tumors (GIST) to investigate the impact of complementary receptor scintigraphy on diagnosis and the potential of a radionuclide treatment. Furthermore, dynamic 18F-FDG studies were performed on the same patients. Methods: This study comprised 17 patients with GIST. All patients were scheduled for therapy with imatinib because of unresectable primary or recurrent GIST or because of metastatic disease. Dynamic PET scans using 68Ga-BZH3 and 18F-FDG were obtained on 2 consecutive days. Multivariate analysis was used to evaluate the kinetic data. Standardized uptake values (SUVs) were calculated, and a compartmental model (2-tissue) and noncompartmental model were used for data evaluation of both tracers. Results: Fourteen of 17 patients (25/30 lesions) were positive for uptake on 18F-FDG imaging, whereas 68Ga-BZH3 demonstrated an enhanced accumulation in 7 of 17 patients (8/30 lesions). Thirteen lesions were confirmed by histologic examination, and the remaining 17 were confirmed by follow-up. One recurrent tumor in the stomach could not be delineated on 18F-FDG imaging but showed enhanced 68Ga-BZH3 uptake. The median SUV for 68Ga-BZH3 was 3.3, in comparison with 7.9 for 18F-FDG. Best-subset analysis demonstrated that the global SUV (55–60 min after injection) for 18F-FDG was primarily dependent on k3, followed by k1. Multivariate analysis did not show a significant correlation between the kinetic parameters (k1–k4, fractional blood volume, and SUV) for 18F-FDG and bombesin. Conclusion: 68Ga-BZH3 may be helpful for diagnostic reasons in a subgroup of patients with GIST, as in the case of negative 18F-FDG findings and suspicion of viable tumor tissue. The meaning of the enhanced 68Ga-BZH3 uptake is open at the moment.

Evaluation of tumour metabolism and multidrug resistance in patients with treated malignant lymphomas

The management of patients with treated malignant lymphomas requires functional methods to differentiate a residual soft tissue mass. Patients with treated Hodgkins lymphoma (HL,n = 20, 68 malignant lesions, three benign lesions) or non-Hodgkins lymphoma (NHL,n = 26, 46 malignant lesions, one benign lesion) were studied with positron emission tomography (PET) and fluorine-18 deoxyglucose (FDG). Oxygen-15 labelled water was used (n = 14, 25 lesions) in addition to FDG in order to obtain information on the tissue perfusion. Long-term follow-up studies with PET and FDG were performed in nine patients up to 511 days after the initiation of second-line therapy. Fourteen patients underwent single-photon emission tomography (SPET) with technetium-99m sestamibi immediately prior to the first PET examination. PET with FDG displays a high sensitivity for the detection of viable tumour tissue, all the malignant lesions being correctly classified in this study. The possible limitations are inflammatory processes, which may obscure tumour detection due to increased FDG uptake, and malignant lesions with low FDG uptake due to reduced perfusion. Difficulties exist in the prognosis of long-term response, since the change in FDG uptake may be variable. Long-term therapy outcome was correlated with the slope values obtained from the standardized integral uptake (SIU) data, which provides a new approach for the evaluation of PET follow-up studies.99mTc-sestamibi, which should reflect the multidrug resistance, was evaluated with respect to therapy outcome. A high uptake of99m-Tc-sestamibi was observed in patients with stable disease or better. The data support the hypothesis that sestamibi may reflect multidrug resistance. Due to technical limitations of the SPET technique, the use of a positron-labelled compound would be superior to SPET for clinical application.

Quantitative assessment of SSTR2 expression in patients with non-small cell lung cancer using 68 Ga-DOTATOC PET and comparison with 18 F-FDG PET

PurposeDynamic PET studies with68Ga-DOTATOC were performed in patients with non-small cell lung cancer (NSCLC) to assess the somatostatin receptor 2 (SSTR2) expression. Furthermore, dynamic18F-fluorodeoxyglucose (FDG) studies were performed in the same patients to compare the SSTR2 expression with the tumour viability.MethodsThe study population comprised nine patients, examined with both tracers on two different days within 1 week. Standardised uptake values (SUVs) were calculated and a two-tissue compartment model was applied to the data. Furthermore, a non-compartment model based on the fractal dimension (FD) was applied to the data.ResultsThe DOTATOC uptake was generally lower than the FDG uptake. Moderately enhanced DOTATOC uptake was noted in seven of the nine tumours. All kinetic parameters exceptk4 were lower for DOTATOC than for FDG. The mean SUV was 2.018 for DOTATOC, in comparison to 5.683 for FDG. In particular,k3 was highly variable for DOTATOC and showed an overlap with the normal lung tissue. The fractional blood volumeVB was relatively low for both tracers, not exceeding 0.3. The highest significant logarithmic correlation was found for the FD of the two tracers (r=0.764,p=0.017). The logarithmic correlation for SUVs was also significant (r=0.646,p=0.060), as was that forVB (r=0.629,p=0.069). In contrast, none of the eight metastases which were positive on FDG PET showed any DOTATOC uptake.ConclusionThe results demonstrated moderate68Ga-DOTATOC uptake in primary NSCLC but did not provide any evidence for SSTR2 expression in metastases. This may be caused by loss of the gene expression in metastases as compared with the primary tumours.

Impact of Angiogenesis-Related Gene Expression on the Tracer Kinetics of 18F-FDG in Colorectal Tumors

18F-FDG kinetics are primarily dependent on the expression of genes associated with glucose transporters and hexokinases but may be modulated by other genes. The dependency of 18F-FDG kinetics on angiogenesis-related gene expression was evaluated in this study. Methods: Patients with primary colorectal tumors (n = 25) were examined with PET and 18F-FDG within 2 days before surgery. Tissue specimens were obtained from the tumor and the normal colon during surgery, and gene expression was assessed using gene arrays. Results: Overall, 23 angiogenesis-related genes were identified with a tumor-to-normal ratio exceeding 1.50. Analysis revealed a significant correlation between k1 and vascular endothelial growth factor (VEGF-A, r = 0.51) and between fractal dimension and angiopoietin-2 (r = 0.48). k3 was negatively correlated with VEGF-B (r = −0.46), and a positive correlation was noted for angiopoietin-like 4 gene (r = 0.42). A multiple linear regression analysis was used for the PET parameters to predict the gene expression, and a correlation coefficient of r = 0.75 was obtained for VEGF-A and of r = 0.76 for the angiopoietin-2 expression. Thus, on the basis of these multiple correlation coefficients, angiogenesis-related gene expression contributes to about 50% of the variance of the 18F-FDG kinetic data. The global 18F-FDG uptake, as measured by the standardized uptake value and influx, was not significantly correlated with angiogenesis-associated genes. Conclusion: 18F-FDG kinetics are modulated by angiogenesis-related genes. The transport rate for 18F-FDG (k1) is higher in tumors with a higher expression of VEGF-A and angiopoietin-2. The regression functions for the PET parameters provide the possibility to predict the gene expression of VEGF-A and angiopoietin-2.

Impact of Dynamic 18F-FDG PET on the Early Prediction of Therapy Outcome in Patients with High-Risk Soft-Tissue Sarcomas After Neoadjuvant Chemotherapy: A Feasibility Study

Dynamic PET (dPET) studies with 18F-FDG were performed in patients with soft-tissue sarcomas who received neoadjuvant chemotherapy early in the course of therapy. The goal of the study was to evaluate the impact of early dPET studies and assess their value with regard to the therapy outcome using histopathologic data. Methods: The evaluation included 31 patients with nonmetastatic soft-tissue sarcomas, who were treated with neoadjuvant chemotherapy consisting of etoposide, ifosfamide, and doxorubicin. Patients were examined before the onset of therapy and after the completion of the second cycle. Histopathologic response served for reference and was available for 25 of 31 patients. Response was defined as less than 10% viable tumor tissue in the resected tumor tissue. The following parameters were retrieved from dPET studies: standardized uptake value (SUV); fractal dimension; 2-compartment model with computation of K1, k2, k3, and k4 (unit, 1/min); fractional blood volume; and influx according to Patlak. Results: The mean SUV was 4.6 before therapy and 2.8 after 2 cycles. The mean influx was 0.059 before therapy and 0.043 after 2 cycles. The mean SUV was 3.9 in the responders and 5.5 in the nonresponders before therapy. After therapy, responders revealed a mean SUV of 2.5, whereas nonresponders had a mean SUV of 3.5. We used linear discriminant analysis to categorize the patients into 2 groups: response (n = 12) and nonresponse (n = 13). The correct classification rate of the responders (positive predictive value) was generally higher (>67%) than that for the nonresponders. Finally, the combined use of the 2 predictor variables, namely SUV and influx, of each study led to the highest accuracy of 83%. This combination was particularly useful for the prediction of responders (positive predictive value, 92%). The use of the percentage change in maximum SUV led to an accuracy of 58%. Conclusion: On the basis of these results, only a multiparameter analysis based on kinetic 18F-FDG data of a baseline study and after 2 cycles is helpful for the early prediction of chemosensitivity in patients with soft-tissue sarcomas receiving neoadjuvant chemotherapy.

Prediction of Progression-Free Survival in Patients With Multiple Myeloma Following Anthracycline-Based Chemotherapy Based on Dynamic FDG-PET

Methods: Dynamic positron emission tomography (PET) studies with F-18-deoxyglucose were performed in patients with multiple myeloma who received anthracycline-based chemotherapy to evaluate the impact of full kinetic analysis and assess its value with regard to progression-free survival (PFS). The evaluation included 19 patients (56 metastatic lesions) with multiple myelomas. All patients received combined anthracycline-based chemotherapy. PFS served as a reference for the PET data. All patients were examined prior to the onset of chemotherapy and on days 23 to 28 after the onset of the first cycle (prior to the second cycle). The following parameters were retrieved from the dynamic PET studies: Standardized Uptake Value (SUV), fractal dimension (FD), 2 compartment model with computation of K1, k2, k3, k4 (unit: 1/min), the fractional blood volume (vB), and the FDG-influx according to Patlak were calculated. Results: The observed PFS varied from <1 month to 64.1 months with a median PFS of 26 months. Most kinetic parameters demonstrated only small changes, primarily declining after 1 cycle. We compared the kinetic data of each study using a Wilcoxon matched-pairs signed rank test. The results were considered significant for P < 0.05. The test revealed a significant change for the SUV (z = 4.954, P < 0.0000), the FD (z = 5.036, P < 0.0000), the fractional blood volume vB (z = 4.116, P < 0.0000) and influx (z = 2.614, P < 0.0090) when the absolute values of the first and the second study were compared. We dichotomized the patients according to the PFS of 18 months and defined 2 survival groups. The data demonstrate that the correct classification rate (CCR) of group 2 (survival: >18 months) was generally higher (exceeding 94%) than for group 1. The use of the baseline SUV led to a CCR of 82% for the group 2 with the longer survival. The CCR of group 1 with the short survival varied between 55% and 70% depending on the parameter and the study used for prediction. Furthermore, the CCR for both groups based only on the data of the second study was somewhat lower (74%–75%) as compared with the baseline FDG study (75%–82%). Finally, the combined use of the 6 predictor variables, namely SUV, k3, and FD (selected by the Wilcoxon rank sum test) of each study led to the highest CCR of 85% for both groups. This combination was in particular useful for the prediction of group 2 with the longer survival with a CCR of 94%. Best cutoff-values for the differentiation between short and long PFS were SUV of 4.0 and a k3 of 0.07 of the baseline study. Conclusions: The results demonstrate, that a full kinetic analysis of the FDG studies prior and after 1 chemotherapeutic cycle in patients with multiple myeloma is helpful for the prediction of PFS and may be used to identify those patients who benefit from this chemotherapeutic protocol. A high SUV (>4.0 SUV) as well as a high k3 (>0.07) of the baseline study were bad prognostic parameters and related to a short PFS.

Tumor Aggressiveness and Patient Outcome in Cancer of the Pancreas Assessed by Dynamic 18F-FDG PET/CT

This study aimed to assess the role of a quantitative dynamic PET model in pancreatic cancer as a potential index of tumor aggressiveness and predictor of survival. Methods: Seventy-one patients with 18F-FDG–avid adenocarcinoma of the pancreas before treatment were recruited, including 27 with localized tumors (11 underwent pancreatectomy, and 16 had localized nonresectable tumors) and 44 with metastatic disease. Dynamic 18F-FDG PET images were acquired over a 60-min period, followed by a whole-body PET/CT study. Quantitative data measurements were based on a 2-compartment model, and the following variables were calculated: VB (fractional blood volume in target area), K1 and k2 (kinetic membrane transport parameters), k3 and k4 (intracellular 18F-FDG phosphorylation and dephosphorylation parameters, respectively), and 18F-FDG INF (global 18F-FDG influx). Results: The single significant variable for overall survival (OS) in patients with localized disease was 18F-FDG INF. Patients with a high 18F-FDG INF (>0.033 min−1) had a median OS of 6 and 5 mo for nonresectable and resected tumors, respectively, versus 15 and 19 mo for a low 18F-FDG INF in nonresectable and resected tumors, respectively (P < 0.04). In metastatic disease, multivariate analysis found VB, K1, and k3 to be significant variables for OS (P < 0.043, <0.031, and <0.009, respectively). Prognostic factors for OS in the entire group of patients that were significant at multivariate analysis were stage of disease, VB, K1, and 18F-FDG INF (P < 0.00035, <0.03, <0.024, and <0.008, respectively). Median OS for all patients with a high 18F-FDG INF, low VB, and high K1 was 3 mo, as opposed to 14 mo in patients with a low 18F-FDG INF, high VB, and low K1 (P < 0.021), irrespective of stage and resectability. Conclusion: Quantitative 18F-FDG kinetic parameters measured by dynamic PET in newly diagnosed pancreatic cancer correlated with the aggressiveness of disease. The 18F-FDG INF was the single most significant variable for OS in patients with localized disease, whether resectable or not.

Noninvasive determination of the arterial input function of an anticancer drug from dynamic PET scans using the population approach

For the application of a kinetic model to PET data, it is generally necessary to obtain the arterial input function (AIF). It was the aim of the present study to introduce a method suitable for the determination of the AIF of a substance that undergoes biochemical transformation from noisy PET data: the population approach. F-18 labeled 5-fluorouracil (5-[18F]FU) was administered i.v. to eight patients suffering from liver metastases of colorectal carcinoma. Radioactivity concentrations in liver and aorta were dynamically measured with PET over 120 min. Pharmacokinetic analysis was carried out by applying a five-compartment model to individual activity-time data for the eight patients or to the mean activity-time data among the eight patients. The mean values of all parameters describing 5-FU transport and catabolism, i.e., volumes of distribution and clearances, as well as interindividual coefficients of variation (CV) were calculated according to both approaches. With our model, we were able to separate the concentration-time course of 5-FU in plasma, i.e., the AIF, from that of its major catabolite alpha-fluoro-beta-alanine (FBAL). As far as the mean parameter estimates are concerned, the differences between both approaches are not significant. For the liver data, the CVs are almost the same for both approaches. For the parameters concerning the aorta, however, there is a decrease in the CVs by using the population approach. For example, the CV of the central distribution volume of 5-FU was 30% for the individual approach and 18% for the population approach. With the population approach, it is possible to determine the AIF of drugs that undergo metabolic conversion, such as anticancer drugs, from the abdominal aorta visualized on PET images. The population approach helps to overcome noise in individual data. Since no measurements are needed in addition to the PET examination, the suggested method helps to reduce risk and pain for the patients as well as cost and thus facilitates large scale patient studies.