Longitudinal [18]UCB-H/[18F]FDG imaging depicts complex patterns of structural and functional neuroplasticity following bilateral vestibular loss in the rat

Neuronal lesions trigger mechanisms of structural and functional neuroplasticity, which can support recovery. However, the temporal and spatial appearance of structure–function changes and their interrelation remain unclear. The current study aimed to directly compare serial whole-brain in vivo measurements of functional plasticity (by [ 18 F]FDG-PET) and structural synaptic plasticity (by [ 18 F]UCB-H-PET) before and after bilateral labyrinthectomy in rats and investigate the effect of locomotor training. Complex structure–function changes were found after bilateral labyrinthectomy: in brainstem-cerebellar circuits, regional cerebral glucose metabolism (rCGM) decreased early, followed by reduced synaptic density. In the thalamus, increased [ 18 F]UCB-H binding preceded a higher rCGM uptake. In frontal-basal ganglia loops, an increase in synaptic density was paralleled by a decrease in rCGM. In the group with locomotor training, thalamic rCGM and [ 18 F]UCB-H binding increased following bilateral labyrinthectomy compared to the no training group. Rats with training had considerably fewer body rotations. In conclusion, combined [ 18 F]FDG/[ 18 F]UCB-H dual tracer imaging reveals that adaptive neuroplasticity after bilateral vestibular loss is not a uniform process but is composed of complex spatial and temporal patterns of structure–function coupling in networks for vestibular, multisensory, and motor control, which can be modulated by early physical training

Concept development of an on-chip PET system.

BACKGROUND Organs-on-Chips (OOCs), microdevices mimicking in vivo organs, find growing applications in disease modeling and drug discovery. With the increasing number of uses comes a strong demand for imaging capabilities of OOCs as monitoring physiologic processes within OOCs is vital for the continuous improvement of this technology. Positron Emission Tomography (PET) would be ideal for OOC imaging, however, current PET systems are insufficient for this task due to their inadequate spatial resolution. In this work, we propose the concept of an On-Chip PET system capable of imaging OOCs and optimize its design using a Monte Carlo Simulation (MCS). MATERIAL AND METHODS The proposed system consists of four detectors arranged around the OOC device. Each detector is made of two monolithic LYSO crystals and covered with Silicon photomultipliers (SiPMs) on multiple surfaces. We use a Convolutional Neural Network (CNN) trained with data from a MCS to predict the first gamma-ray interaction position inside the detector from the light patterns that are recorded by the SiPMs on the detector's surfaces. RESULTS The CNN achieves a mean average prediction error of 0.80 mm in the best configuration. The proposed system achieves a sensitivity of 34.81% for 13 mm thick crystals and does not show a prediction degradation near the boundaries of the detector. We use the trained network to reconstruct an image of a grid of 21 point sources spread across the field-of-view and obtain a mean spatial resolution of 0.55 mm. We show that 25,000 Line of Responses (LORs) are needed to reconstruct a realistic OOC phantom with adequate image quality. CONCLUSIONS We demonstrate that it is possible to achieve a spatial resolution of almost 0.5 mm in a PET system made of multiple monolithic LYSO crystals by directly predicting the scintillation position from light patterns created with SiPMs. We observe that a thinner crystal performs better than a thicker one, that increasing the SiPM size from 3 mm to 6 mm only slightly decreases the prediction performance, and that certain surfaces encode significantly more information for the scintillation-point prediction than others

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

Aim Understanding neuroinflammation after acute ischemic stroke is a crucial step on the way to an individualized post-stroke treatment. Microglia activation, an essential part of neuroinflammation, can be assessed using [ 18 F]GE-180 18 kDa translocator protein positron emission tomography (TSPO-PET). However, the commonly used 60–90 min post-injection (p.i.) time window was not yet proven to be suitable for post-stroke neuroinflammation assessment. In this study, we compare semi-quantitative estimates derived from late time frames to quantitative estimates calculated using a full 0–90 min dynamic scan in a mouse photothrombotic stroke (PT) model. Materials and Methods Six mice after PT and six sham mice were included in the study. For a half of the mice, we acquired four serial 0–90 min scans per mouse (analysis cohort) and calculated standardized uptake value ratios (SUVRs; cerebellar reference) for the PT volume of interest (VOI) in five late 10 min time frames as well as distribution volume ratios (DVRs) for the same VOI. We compared late static 10 min SUVRs and the 60–90 min time frame of the analysis cohort to the corresponding DVRs by linear fitting. The other half of the animals received a static 60–90 min scan and was used as a validation cohort. We extrapolated DVRs by using the static 60–90 min p.i. time window, which were compared to the DVRs of the analysis cohort. Results We found high linear correlations between SUVRs and DVRs in the analysis cohort for all studied 10 min time frames, while the fits of the 60–70, 70–80, and 80–90 min p.i. time frames were the ones closest to the line of identity. For the 60–90 min time window, we observed an excellent linear correlation between SUVR and DVR regardless of the phenotype (PT vs . sham). The extrapolated DVRs of the validation cohort were not significantly different from the DVRs of the analysis group. Conclusion Simplified quantification by a reference tissue ratio of the late 60–90 min p.i. [ 18 F]GE-180 PET image can replace full quantification of a dynamic scan for assessment of microglial activation in the mouse PT model

Direct comparison of activation maps during galvanic vestibular stimulation: A hybrid H-2[(15) O] PET-BOLD MRI activation study

Previous unimodal PET and fMRI studies in humans revealed a reproducible vestibular brain activation pattern, but with variations in its weighting and expansiveness. Hybrid studies minimizing methodological variations at baseline conditions are rare and still lacking for task-based designs. Thus, we applied for the first time hybrid 3T PET-MRI scanning (Siemens mMR) in healthy volunteers using galvanic vestibular stimulation (GVS) in healthy volunteers in order to directly compare (H2O)-O-15-PET and BOLD MRI responses. List mode PET acquisition started with the injection of 750 MBq (H2O)-O-15 simultaneously to MRI EPI sequences. Group-level statistical parametric maps were generated for GVS vs. rest contrasts of PET, MR-onset (event-related), and MR-block. All contrasts showed a similar bilateral vestibular activation pattern with remarkable proximity of activation foci. Both BOLD contrasts gave more bilateral wide-spread activation clusters than PET;no area showed contradictory signal responses. PET still confirmed the right-hemispheric lateralization of the vestibular system, whereas BOLD-onset revealed only a tendency. The reciprocal inhibitory visual-vestibular interaction concept was confirmed by PET signal decreases in primary and secondary visual cortices, and BOLD-block decreases in secondary visual areas. In conclusion, MRI activation maps contained a mixture of CBF measured using (H2O)-O-15-PET and additional non-CBF effects, and the activation-deactivation pattern of the BOLD-block appears to be more similar to the (H2O)-O-15-PET than the BOLD-onset

Proof-of-concept Study to Estimate Individual Post-Therapy Dosimetry in Men with Advanced Prostate Cancer Treated with 177Lu-PSMA I&T Therapy

It is still debating if individualized dose should be applied for the emerging PSMA-targeted radionuclide therapy (RLT). A critical consideration in this debate is the necessity and feasibility of individual estimation of post-therapy dosimetry before the treatment. In this study, we aimed to prove the concept of individual dosimetry prediction based on pre-therapy imaging and laboratory measurements. Methods: 23 patients with metastatic castration-resistant prostate cancer (mCRPC) treated with 177Lu-PSMA-I&T RLT were included retrospectively. Included patients had available pre-therapeutic 68Ga-PSMA-HEBD-CC PET/CT and at least 3 planar and 1 SPECT/CT dosimetry imaging. Overall, 43 cycles of 177Lu-PSMA I&T RLT were applied. Organ-based standard uptake value (SUV) uptake was obtained from pretherapy PET/CT scans. Patient individual dosimetry was calculated for kidney, liver, spleen, and salivary glands using Hermes Hybrid Dosimetry 4.0 from the post-treatment 177Lu-PSMA I&T imaging studies. Machine learning methods were explored for individual dose prediction from PET images. The accuracy of these dose predictions was compared with the accuracy of population-based dosimetry estimates. Mean absolute percentage error was used to assess the prediction error of estimated dosimetry. Results: An optimal machine learning method achieved a dosimetry prediction error of 15.8 ± 13.2% for kidney, 29.6%±13.7% for liver, 23.8%±13.1% for salivary glands and 32.1 ± 31.4% for spleen. In contrast, the prediction based on literature population mean has significantly larger error (p < 0.01), 25.5 ± 17.3% for kidney, 139.1%±111.5% for liver, 67.0 ± 58.3% for salivary glands, and 54.1 ± 215.3% for spleen. Conclusion: The preliminary results confirmed the feasibility of individual estimation of post-therapy dosimetry before the RLT and its added value to empirical population-based estimation. The exploration of individual dose prediction may support the identification of the role of treatment planning for RLT

Application of machine learning to pretherapeutically estimate dosimetry in men with advanced prostate cancer treated with 177Lu-PSMA I&T therapy

Purpose: Although treatment planning and individualized dose application for emerging prostate-specific membrane antigen (PSMA)-targeted radioligand therapy (RLT) are generally recommended, it is still difficult to implement in practice at the moment. In this study, we aimed to prove the concept of pretherapeutic prediction of dosimetry based on imaging and laboratory measurements before the RLT treatment. Methods: Twenty-three patients with metastatic castration-resistant prostate cancer (mCRPC) treated with 177Lu-PSMA I&T RLT were included retrospectively. They had available pre-therapy 68 Ga-PSMA-HEBD-CC PET/CT and at least 3 planar and 1 SPECT/CT imaging for dosimetry. Overall, 43 cycles of 177Lu-PSMA I&T RLT were applied. Organ-based standard uptake values (SUVs) were obtained from pre-therapy PET/CT scans. Patient dosimetry was calculated for the kidney, liver, spleen, and salivary glands using Hermes Hybrid Dosimetry 4.0 from the planar and SPECT/CT images. Machine learning methods were explored for dose prediction from organ SUVs and laboratory measurements. The uncertainty of these dose predictions was compared with the population-based dosimetry estimates. Mean absolute percentage error (MAPE) was used to assess the prediction uncertainty of estimated dosimetry. Results: An optimal machine learning method achieved a dosimetry prediction MAPE of 15.8 ± 13.2% for the kidney, 29.6% ± 13.7% for the liver, 23.8% ± 13.1% for the salivary glands, and 32.1 ± 31.4% for the spleen. In contrast, the prediction based on literature population mean has significantly larger MAPE (p < 0.01), 25.5 ± 17.3% for the kidney, 139.1% ± 111.5% for the liver, 67.0 ± 58.3% for the salivary glands, and 54.1 ± 215.3% for the spleen. Conclusion: The preliminary results confirmed the feasibility of pretherapeutic estimation of treatment dosimetry and its added value to empirical population-based estimation. The exploration of dose prediction may support the implementation of treatment planning for RLT

Application of machine learning to pretherapeutically estimate dosimetry in men with advanced prostate cancer treated with 177Lu-PSMA I&T therapy.

PURPOSE Although treatment planning and individualized dose application for emerging prostate-specific membrane antigen (PSMA)-targeted radioligand therapy (RLT) are generally recommended, it is still difficult to implement in practice at the moment. In this study, we aimed to prove the concept of pretherapeutic prediction of dosimetry based on imaging and laboratory measurements before the RLT treatment. METHODS Twenty-three patients with metastatic castration-resistant prostate cancer (mCRPC) treated with 177Lu-PSMA I&T RLT were included retrospectively. They had available pre-therapy 68 Ga-PSMA-HEBD-CC PET/CT and at least 3 planar and 1 SPECT/CT imaging for dosimetry. Overall, 43 cycles of 177Lu-PSMA I&T RLT were applied. Organ-based standard uptake values (SUVs) were obtained from pre-therapy PET/CT scans. Patient dosimetry was calculated for the kidney, liver, spleen, and salivary glands using Hermes Hybrid Dosimetry 4.0 from the planar and SPECT/CT images. Machine learning methods were explored for dose prediction from organ SUVs and laboratory measurements. The uncertainty of these dose predictions was compared with the population-based dosimetry estimates. Mean absolute percentage error (MAPE) was used to assess the prediction uncertainty of estimated dosimetry. RESULTS An optimal machine learning method achieved a dosimetry prediction MAPE of 15.8 ± 13.2% for the kidney, 29.6% ± 13.7% for the liver, 23.8% ± 13.1% for the salivary glands, and 32.1 ± 31.4% for the spleen. In contrast, the prediction based on literature population mean has significantly larger MAPE (p < 0.01), 25.5 ± 17.3% for the kidney, 139.1% ± 111.5% for the liver, 67.0 ± 58.3% for the salivary glands, and 54.1 ± 215.3% for the spleen. CONCLUSION The preliminary results confirmed the feasibility of pretherapeutic estimation of treatment dosimetry and its added value to empirical population-based estimation. The exploration of dose prediction may support the implementation of treatment planning for RLT

Ginkgo biloba Extract EGb 761 Improves Vestibular Compensation and Modulates Cerebral Vestibular Networks in the Rat

Unilateral inner ear damage is followed by behavioral recovery due to central vestibular compensation. The dose-dependent therapeutic effect of Ginkgo biloba extract EGb 761 on vestibular compensation was investigated by behavioral testing and serial cerebral [18F]-Fluoro-desoxyglucose ([18F]-FDG)-μPET in a rat model of unilateral labyrinthectomy (UL). Five groups of 8 animals each were treated with EGb 761-supplemented food at doses of 75, 37.5 or 18.75 mg/kg body weight 6 weeks prior and 15 days post UL (groups A,B,C), control food prior and EGb 761-supplemented food (75 mg/kg) for 15 days post UL (group D), or control food throughout (group E). Plasma levels of EGb 761 components bilobalide, ginkgolide A and B were analyzed prior and 15 days post UL. Behavioral testing included clinical scoring of nystagmus, postural asymmetry, head roll tilt, body rotation during sensory perturbation and instrumental registration of mobility in an open field before and 1, 2, 3, 5, 7, 15 days after UL. Whole-brain [18F]-FDG-μPET was recorded before and 1, 3, 7, 15 days after UL. The EGb 761 group A (75 mg/kg prior/post UL) showed a significant reduction of nystagmus scores (day 3 post UL), of postural asymmetry (1, 3, 7 days post UL), and an increased mobility in the open field (day 7 post UL) as compared to controls (group E). Application of EGb 761 at doses of 37.5 and 18.75 mg/kg prior/post UL (groups B,C) resulted in faster recovery of postural asymmetry, but did not influence mobility relative to controls. Locomotor velocity increased with higher plasma levels of ginkgolide A and B. [18F]-FDG-μPET revealed a significant decrease of the regional cerebral glucose metabolism (rCGM) in the vestibular nuclei and cerebellum and an increase in the hippocampal formation with higher plasma levels of ginkgolides and bilobalide 1 and 3 days post UL. Decrease of rCGM in the vestibular nucleus area and increase in the hippocampal formation with higher plasma levels persisted until day 15 post UL. In conclusion, Ginkgo biloba extract EGb 761 improves vestibulo-ocular motor, vestibulo-spinal compensation, and mobility after UL. This rat study supports the translational approach to investigate EGb 761 at higher dosages for acceleration of vestibular compensation in acute vestibular loss

The sodium iodide symporter (NIS) as theranostic gene: its emerging role in new imaging modalities and non-viral gene therapy

Cloning of the sodium iodide symporter (NIS) in 1996 has provided an opportunity to use NIS as a powerful theranostic transgene. Novel gene therapy strategies rely on image-guided selective NIS gene transfer in non-thyroidal tumors followed by application of therapeutic radionuclides. This review highlights the remarkable progress during the last two decades in the development of the NIS gene therapy concept using selective non-viral gene delivery vehicles including synthetic polyplexes and genetically engineered mesenchymal stem cells. In addition, NIS is a sensitive reporter gene and can be monitored by high resolution PET imaging using the radiotracers sodium [ 124 I]iodide ([ 124 I]NaI) or [ 18 F]tetrafluoroborate ([ 18 F]TFB). We performed a small preclinical PET imaging study comparing sodium [ 124 I]iodide and in-house synthesized [ 18 F]TFB in an orthotopic NIS-expressing glioblastoma model. The results demonstrated an improved image quality using [ 18 F]TFB. Building upon these results, we will be able to expand the NIS gene therapy approach using non-viral gene delivery vehicles to target orthotopic tumor models with low volume disease, such as glioblastoma