Reduced Acquisition Time [18F]GE-180 PET Scanning Protocol Replaces Gold-Standard Dynamic Acquisition in a Mouse Ischemic Stroke Model

Machine learning-based approach reveals essential features for simplified TSPO PET quantification in ischemic stroke patients

INTRODUCTION

Neuroinflammation evaluation after acute ischemic stroke is a promising option for selecting an appropriate post-stroke treatment strategy. To assess neuroinflammation in vivo, translocator protein PET (TSPO PET) can be used. However, the gold standard TSPO PET quantification method includes a 90 min scan and continuous arterial blood sampling, which is challenging to perform on a routine basis. In this work, we determine what information is required for a simplified quantification approach using a machine learning algorithm.

MATERIALS AND METHODS

We analyzed data from 18 patients with ischemic stroke who received 0-90 min [18F]GE-180 PET as well as T1-weigted (T1w), FLAIR, and arterial spin labeling (ASL) MRI scans. During PET scans, five manual venous blood samples at 5, 15, 30, 60, and 85 min post injection (p.i.) were drawn, and plasma activity concentration was measured. Total distribution volume (VT) was calculated using Logan plot with the full dynamic PET and an image-derived input function (IDIF) from the carotid arteries. IDIF was scaled by a calibration factor derived from all the measured plasma activity concentrations. The calculated VT values were used for training a random forest regressor. As input features for the model, we used three late PET frames (60-70, 70-80, and 80-90 min p.i.), the ASL image reflecting perfusion, the voxel coordinates, the lesion mask, and the five plasma activity concentrations. The algorithm was validated with the leave-one-out approach. To estimate the impact of the individual features on the algorithm's performance, we used Shapley Additive Explanations (SHAP). Having determined that the three late PET frames and the plasma activity concentrations were the most important features, we tested a simplified quantification approach consisting of dividing a late PET frame by a plasma activity concentration. All the combinations of frames/samples were compared by means of concordance correlation coefficient and Bland-Altman plots.

RESULTS

When using all the input features, the algorithm predicted VT values with high accuracy (87.8 ± 8.3%) for both lesion and non-lesion voxels. The SHAP values demonstrated high impact of the late PET frames (60-70, 70-80, and 80-90 min p.i.) and plasma activity concentrations on the VT prediction, while the influence of the ASL-derived perfusion, voxel coordinates, and the lesion mask was low. Among all the combinations of the late PET frames and plasma activity concentrations, the 70-80 min p.i. frame divided by the 30 min p.i. plasma sample produced the closest VT estimate in the ischemic lesion.

CONCLUSION

Reliable TSPO PET quantification is achievable by using a single late PET frame divided by a late blood sample activity concentration.

Molecular Imaging of Innate Immunity and Immunotherapy

The innate immune system plays a key role as the first line of defense in various human diseases including cancer, cardiovascular and inflammatory diseases. In contrast to tissue biopsies and blood biopsies, in vivo imaging of the innate immune system can provide whole body measurements of immune cell location and function and changes in response to disease progression and therapy. Rationally developed molecular imaging strategies can be used in evaluating the status and spatio-temporal distributions of the innate immune cells in near real-time, mapping the biodistribution of novel innate immunotherapies, monitoring their efficacy and potential toxicities, and eventually for stratifying patients that are likely to benefit from these immunotherapies. In this review, we will highlight the current state-of-the-art in noninvasive imaging techniques for preclinical imaging of the innate immune system particularly focusing on cell trafficking, biodistribution, as well as pharmacokinetics and dynamics of promising immunotherapies in cancer and other diseases; discuss the unmet needs and current challenges in integrating imaging modalities and immunology and suggest potential solutions to overcome these barriers.

[18F]GE-180-PET and Post Mortem Marker Characteristics of Long-Term High-Fat-Diet-Induced Chronic Neuroinflammation in Mice

Obesity is characterized by immoderate fat accumulation leading to an elevated risk of neurodegenerative disorders, along with a host of metabolic disturbances. Chronic neuroinflammation is a main factor linking obesity and the propensity for neurodegenerative disorders. To determine the cerebrometabolic effects of diet-induced obesity (DIO) in female mice fed a long-term (24 weeks) high-fat diet (HFD, 60% fat) compared to a group on a control diet (CD, 20% fat), we used in vivo PET imaging with the radiotracer [¹⁸F]FDG as a marker for brain glucose metabolism. In addition, we determined the effects of DIO on cerebral neuroinflammation using translocator protein 18 kDa (TSPO)-sensitive PET imaging with [¹⁸F]GE-180. Finally, we performed complementary post mortem histological and biochemical analyses of TSPO and further microglial (Iba1, TMEM119) and astroglial (GFAP) markers as well as cerebral expression analyses of cytokines (e.g., Interleukin (IL)-1β). We showed the development of a peripheral DIO phenotype, characterized by increased body weight, visceral fat, free triglycerides and leptin in plasma, as well as increased fasted blood glucose levels. Furthermore, we found obesity-associated hypermetabolic changes in brain glucose metabolism in the HFD group. Our main findings with respect to neuroinflammation were that neither [¹⁸F]GE-180 PET nor histological analyses of brain samples seem fit to detect the predicted cerebral inflammation response, despite clear evidence of perturbed brain metabolism along with elevated IL-1β expression. These results could be interpreted as a metabolically activated state in brain-resident immune cells due to a long-term HFD.

A feasibility study for quantitative assessment of cerebrovascular malformations using flutriciclamide ([18F]GE-180) PET/MRI

Aim

Neuroinflammation plays a key role in both the pathogenesis and the progression of cerebral cavernous malformations (CCM). Flutriciclamide ([18F]GE-180) is a translocator protein (TSPO) targeting positron emission tomography (PET) tracer, developed for imaging neuroinflammation. The objectives of this study were to describe characteristics of flutriciclamide uptake in different brain tissue regions in CCM patients compared to controls, and to evaluate flutriciclamide uptake and iron deposition within CCM lesions.

Materials and methods

Five patients with CCM and six controls underwent a 60 or 90 min continuous PET/MRI scan following 315 ± 68.9 MBq flutriciclamide administration. Standardized uptake value (SUV) and standardized uptake value ratio (SUVr) were obtained using the striatum as a pseudo-reference. Quantitative susceptibility maps (QSM) were used to define the location of the vascular malformation and calculate the amount of iron deposition in each lesion.

Results

Increased flutriciclamide uptake was observed in all CCM lesions. The temporal pole demonstrated the highest radiotracer uptake; the paracentral lobule, cuneus and hippocampus exhibited moderate uptake; while the striatum had the lowest uptake, with average SUVs of 0.66, 0.55, 0.63, 0.55, and 0.33 for patient with CCM and 0.57, 0.50, 0.48, 0.42, and 0.32 for controls, respectively. Regional SUVr showed similar trends. The average SUV and QSM values in CCM lesions were 0.58 ± 0.23 g/ml and 0.30 ± 0.10 ppm. SUVs and QSM were positively correlated in CCM lesions (r = 0.53, p = 0.03).

Conclusion

The distribution of flutriciclamide ([18F]GE-180) in the human brain and CCM lesions demonstrated the potential of this TSPO PET tracer as a marker of neuroinflammation that may be relevant for characterizing CCM disease progression along with QSM.

18 kDa translocator protein positron emission tomography facilitates early and robust tumor detection in the immunocompetent SB28 glioblastoma mouse model

INTRODUCTION

The 18 kDa translocator protein (TSPO) receives growing interest as a biomarker in glioblastoma. Mouse models can serve as an important tool for the investigation of biomarkers in glioblastoma, but several glioblastoma models indicated only low TSPO-PET signals in contrast to high TSPO-PET signals of human glioblastoma. Thus, we aimed to investigate TSPO-PET imaging in the syngeneic immunocompetent SB28 mouse model, which is thought to closely represent the tumor microenvironment (TME) of human glioblastoma.

METHODS

Dynamic TSPO-PET/CT imaging was performed for 60 min after injection of 13.6 ± 4.2 MBq [18F]GE-180. Contrast enhanced CT (ceCT) was acquired prior to PET and served for assessment of tumor volumes and attenuation correction. SB28 and sham mice were imaged at an early (week-1; n = 6 SB28, n = 6 sham) and a late time-point (week-3; n = 8 SB28, n = 9 sham) after inoculation. Standard of truth ex vivo tumor volumes were obtained for SB28 mice at the late time-point. Tracer kinetics were analyzed for the lesion site and the carotid arteries to establish an image derived input function (IDIF). TSPO-PET and ceCT lesion volumes were compared with ex vivo volumes by calculation of root-mean-square-errors (RMSE). Volumes of distribution (VTmax/mean) in the lesion were calculated using carotid IDIF and standardized uptake values (SUVmax/mean) were obtained for a 40-60 min time frame.

RESULTS

Higher uptake rate constants (K1) were observed for week-1 SB28 tumor lesions when compared to week-3 SB28 tumor lesions. Highest agreement between TSPO-PET lesion volumes and ex vivo tumor volumes was achieved with a 50% maximum threshold (RMSE-VT: 39.7%; RMSE-SUV: 34.4%), similar to the agreement of ceCT tumor volumes (RMSE: 30.1%). Lesions of SB28 mice had higher PET signal when compared to sham mice at week-1 (VTmax 6.6 ± 2.9 vs. 3.9 ± 0.8, p = 0.035; SUVmax 2.3 ± 0.5 vs. 1.2 ± 0.1, p < 0.001) and PET signals remained at a similar level at week-3 (VTmax 5.0 ± 1.6 vs. 2.7 ± 0.8, p = 0.029; SUVmax 1.9 ± 0.5 vs. 1.2 ± 0.2, p = 0.0012). VTmax correlated with SUVmax (R 2 = 0.532, p < 0.001).

CONCLUSION

TSPO-PET imaging of immunocompetent SB28 mice facilitates early detection of tumor signals over sham lesions. SB28 tumors mirror high TSPO-PET signals of human glioblastoma and could serve as a valuable translational model to study TSPO as an imaging biomarker.