European Journal of Nuclear Medicine and Molecular Imaging

PurposeThe radionuclide pair cerium-134/lanthanum-134 (134Ce/134La) was recently proposed as a suitable diagnostic counterpart for the therapeutic alpha-emitter actinium-225 (225Ac). The unique properties of 134Ce offer perspectives for developing innovative in vivo investigations not possible with 225Ac. In this work, 225Ac- and 134Ce-labeled tracers were directly compared using internalizing and slow-internalizing cancer models to evaluate their in vivo comparability, progeny meandering, and potential as a matched theranostic pair for clinical translation. Despite being an excellent chemical match, 134Ce/134La has limitations to the setting of quantitative positron emission tomography imaging. MethodsThe precursor PSMA-617 and a macropa-based tetrazine-conjugate (mcp-PEG8-Tz) were radiolabelled with 225Ac or 134Ce and compared in vitro and in vivo using standard (radio)chemical methods. Employing biodistribution studies and positron emission tomography (PET) imaging in athymic nude mice, the radiolabelled PSMA-617 tracers were evaluated in a PC3/PIP (PC3 engineered to express a high level of prostate-specific membrane antigen) prostate cancer mouse model. The 225Ac and 134Ce-labeled mcp-PEG8-Tz were investigated in a BxPC-3 pancreatic tumour model harnessing the pretargeting strategy based on a trans-cyclooctene-modified 5B1 monoclonal antibody. ResultsIn vitro and in vivo studies with both 225Ac and 134Ce-labelled tracers led to comparable results, confirming the matching pharmacokinetics of this theranostic pair. However, PET imaging of the 134Ce-labelled precursors indicated that quantification is highly dependent on tracer internalization due to the redistribution of 134Ces PET-compatible daughter 134La. Consequently, radiotracers based on internalizing vectors like PSMA-617 are suited for this theranostic pair, while slow-internalizing 225Ac-labelled tracers are not quantitatively represented by 134Ce PET imaging. ConclusionWhen employing slow-internalizing vectors, 134Ce might not be an ideal match for 225Ac due to the underestimation of tumour uptake caused by the in vivo redistribution of 134La. However, this same characteristic makes it possible to estimate the redistribution of 225Acs progeny noninvasively. In future studies, this unique PET in vivo generator will further be harnessed to study tracer internalization, trafficking of receptors, and the progression of the tumour microenvironment. TOC Graphic O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=167 SRC="FIGDIR/small/591165v1_ufig1.gif" ALT="Figure 1"> View larger version (61K): org.highwire.dtl.DTLVardef@ca3cb6org.highwire.dtl.DTLVardef@157eac6org.highwire.dtl.DTLVardef@f6ac6dorg.highwire.dtl.DTLVardef@b24d87_HPS_FORMAT_FIGEXP M_FIG C_FIG Redistribution of progeny. Investigating the 225Ac and 134Ce decay chain. This figure was created with BioRender.

One of the main challenges of PET imaging with 89Zr-labeled monoclonal antibodies (mAbs) remains the long blood circulation of the radiolabeled mAbs, leading to high background signals, decreasing image quality. To overcome this limitation, here we report the use of a bioorthogonal linker cleavage approach (click-to-release chemistry) to selectively liberate [89Zr]Zr-DFO from trans-cyclooctene-functionalized trastuzumab (TCO-Tmab) in blood, following the administration of a tetrazine compound (trigger) in BT-474 tumor-bearing mice. MethodsWe created a series of TCO-DFO constructs and evaluated their performance in [89Zr]Zr-DFO release from Tmab in vitro using different trigger compounds. The in vivo behavior of the best performing [89Zr]Zr-TCO-Tmab was studied in healthy mice first, to determine the optimal dose of the trigger. To find the optimal time for the trigger administration, the rate of [89Zr]Zr-TCO-Tmab internalization was studied in BT-474 cancer cells. Finally, the trigger was administered 6 h or 24 h after [89Zr]Zr-TCO-Tmab-administration in tumor-bearing mice to liberate the [89Zr]Zr-DFO fragment. PET scans were obtained of tumor-bearing mice that received the trigger 6 h post-[89Zr]Zr-TCO-Tmab administration. ResultsThe [89Zr]Zr-TCO-Tmab and trigger pair with the best in vivo properties exhibited 83% release in 50 % mouse plasma. In tumor-bearing mice the tumor-blood ratios were markedly increased from 1.0 {+/-} 0.4 to 2.3 {+/-} 0.6 (p=0.0057) and from 2.5 {+/-} 0.7 to 6.6 {+/-} 0.9 (p<0.0001) when the trigger was administered at 6 h and 24 h post-mAb, respectively. Same day PET imaging clearly showed uptake in the tumor combined with a strongly reduced background due to the fast clearance of the released [89Zr]Zr-DFO-containing fragment from the circulation through the kidneys. ConclusionsThis is the first demonstration of the use of trans-cyclooctene-tetrazine click-to-release chemistry to release a radioactive chelator from a mAb in mice to increase tumor-blood ratios. Our results suggest that click-cleavable radioimmunoimaging may allow for substantially shorter intervals in PET imaging with full mAbs, reducing radiation doses and potentially even enabling same day imaging.

Quantitative total-body PET imaging of blood flow can be performed with freely diffusible flow radiotracers such as 15O-water and 11C-butanol, but their short half-lives necessitate close access to a cyclotron. Past efforts to measure blood flow with the widely available radiotracer 18F-fluorodeoxyglucose (FDG) were limited to tissues with high 18F-FDG extraction fraction. In this study, we developed an early-dynamic 18F-FDG PET method with high temporal resolution kinetic modeling to assess total-body blood flow based on deriving the vascular transit time of 18F-FDG and conducted a pilot comparison study against a 11C-butanol reference. MethodsThe first two minutes of dynamic PET scans were reconstructed at high temporal resolution (60x1 s, 30x2 s) to resolve the rapid passage of the radiotracer through blood vessels. In contrast to existing methods that use blood-to-tissue transport rate (K1) as a surrogate of blood flow, our method directly estimates blood flow using a distributed kinetic model (adiabatic approximation to the tissue homogeneity model; AATH). To validate our 18F-FDG measurements of blood flow against a flow radiotracer, we analyzed total-body dynamic PET images of six human participants scanned with both 18F-FDG and 11C-butanol. An additional thirty-four total-body dynamic 18F-FDG PET scans of healthy participants were analyzed for comparison against literature blood flow ranges. Regional blood flow was estimated across the body and total-body parametric imaging of blood flow was conducted for visual assessment. AATH and standard compartment model fitting was compared by the Akaike Information Criterion at different temporal resolutions. Results18F-FDG blood flow was in quantitative agreement with flow measured from 11C-butanol across same-subject regional measurements (Pearson R=0.955, p<0.001; linear regression y=0.973x-0.012), which was visually corroborated by total-body blood flow parametric imaging. Our method resolved a wide range of blood flow values across the body in broad agreement with literature ranges (e.g., healthy cohort average: 0.51{+/-}0.12 ml/min/cm3 in the cerebral cortex and 2.03{+/-}0.64 ml/min/cm3 in the lungs, respectively). High temporal resolution (1 to 2 s) was critical to enabling AATH modeling over standard compartment modeling. ConclusionsTotal-body blood flow imaging was feasible using early-dynamic 18F-FDG PET with high-temporal resolution kinetic modeling. Combined with standard 18F-FDG PET methods, this method may enable efficient single-tracer flow-metabolism imaging, with numerous research and clinical applications in oncology, cardiovascular disease, pain medicine, and neuroscience.

Tryptophan (Trp) is the precursor for serotonin synthesis and other biologically relevant metabolites. We evaluated the novel radiotracer 7-[18F]Fluorotryptophan (7-[18F]FTrp) to assess its biodistribution, dosimetry, and potential for imaging brain Trp metabolism in humans. Six healthy volunteers underwent whole-body PET/CT imaging over 5.5 hours following intravenous injection of 7-[18F]FTrp. An additional four subjects underwent dynamic brain PET imaging for 2 hours. Time-activity curves (TACs) were extracted for source organs using VOIs defined on co-registered CT and PET images, and dosimetry was calculated using OLINDA software. The radiotracer showed rapid uptake and distribution, with highest activity observed in the liver, pancreas, salivary glands, in combination with urinary excretion. Brain pharmacokinetic analyses with image-derived input function (IDIF) determined that Patlak analyses were the best fit for brain image analyses. Brain uptake was modest, with highest region-specific accumulation in the pineal gland, which is a known site for serotonin synthesis. The estimated effective dose was within the expected range for 18F-labeled compounds (14.1 {+/-} 0.2 Sv/MBq). Our findings indicate that 7-[18F]FTrp is safe for human use, demonstrates favorable kinetics for studying both brain and peripheral Trp metabolism, and warrants further exploration in patients with serotonin metabolism disorders.

Rationale"Gold standard" blood-based quantification of dynamic 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET) data has limited practical clinical applications due to cost and complexity of data collection and analysis. We previously presented a blood-free quantification alternative, STARE (Source-to-Target Automatic Rotating Estimation), that was validated on 18F-FDG data acquired on a ECAT EXACT HR+ scanner. Here, we extend that initial work by externally validating STARE using within-subject data acquired with both a Siemens Biograph mCT scanner and a portable Brain Biosciences CerePET scanner. MethodsPerformance was assessed by comparing regional net influx rates (Ki) estimated using STARE and the standard blood-based Patlak approach. Twenty participants underwent 60-minute 18F-FDG scans, on two different days, once in each scanner. The time-stability of both STARE- and Patlak-based Ki estimates was evaluated by applying each method to the first 20 (STARE only), 30, 40, and 50 minutes of data. ResultsSTARE demonstrated high correlation with Patlak Ki estimates across both scanner types, particularly in the Biograph mCT (r = 0.93), with lower correlation in the CerePET (r = 0.71). In the Biograph dataset, STARE provided reliable Ki estimates at all evaluated scan durations (20 minutes and above), while in the CerePET dataset, only the 50-minute duration yielded STARE Ki estimates that were not significantly different from the full 60 minutes. The Patlak approach provided Ki estimates at 40 minutes scan duration and above that did not differ from the 60-min scan results in both datasets. ConclusionSTARE is a viable, noninvasive alternative to traditional blood-based quantification of dynamic 18F-FDG PET data, facilitating shorter, blood-free acquisition. This advancement could make dynamic 18F-FDG PET imaging more accessible and comfortable for patients, promoting broader clinical adoption.

BackgroundDistinguishing individuals with cognitive decline (CD), including early Alzheimers disease, from cognitively normal (CN) individuals is essential for improving diagnostic accuracy and enabling timely intervention. Positron emission tomography (PET) captures functional brain alterations associated with CD, but its broader application is often limited by cost and radiation exposure. To enhance the clinical utility of PET while addressing data limitations, we propose a multi-representational learning framework that leverages both imaging data and region-level quantification in a data-efficient manner. MethodsVoxel-level features were extracted using convolutional neural networks (CNN) or principal component analysis networks (PCANet) from [{superscript 1}F]FDG PET imaging. Region-level features were derived from standardized uptake value ratio measurements across predefined brain regions and processed using a deep neural network (DNN). These voxel- and region-level information are integrated through direct concatenation. For final prediction, different machine learning models and ensemble technique were applied. The models were trained and validated using 5-fold cross-validation on PET scans from 252 participants in the Alzheimers Disease Neuroimaging Initiative (ADNI), comprising 118 CN and 134 CD subjects. Additional correlation analysis and disease classification comparison with the Mini-Mental State Examination (MMSE) were also performed. ResultsIn 5-fold cross-validation, CNN, PCANet, and DNN models achieved classification accuracies of 0.69 {+/-} 0.04, 0.69 {+/-} 0.06, and 0.82 {+/-} 0.06, respectively. The integrated DNN-CNN model using direct concatenation yielded the highest accuracy (0.87 {+/-} 0.05), with a 6.10% improvement in accuracy and reduced standard deviation relative to the DNN-only model. Moreover, there were an increase of 14.29% in Recall (0.77 to 0.88) and an increase of 7.32% in F1-Score (0.82 to 0.88). Moreover, the model output showed a significant level of relation with MMSE, and it outperformed the MMSE-based classification in accuracy, recall, and f1, except precision. ConclusionCombining PET imaging with region-level quantification and deep learning improves diagnostic performance over single-feature based models. Notably, fusion-based approaches enhanced sensitivity to cognitive decline. This multimodal strategy offers a more data-efficient and accurate approach for classifying cognitive decline and supports broader PET application in clinical settings.

Aim/IntroductionDifferentiating malignant from inflammatory uptake on 18F-FDG PET/CT remains a major diagnostic challenge, as standardized uptake value (SUV) lacks specificity. Dynamic acquisitions with Patlak analysis can separate metabolized from unmetabolized tracer, potentially improving discrimination. We evaluated whether short-duration dynamic FDG PET/CT with Patlak parametric imaging provides complementary information beyond SUV for distinguishing malignancy from inflammation. Materials and MethodsTwenty-seven patients undergoing oncologic PET/CT (breast, lung, or gastrointestinal cancer) were included, yielding 96 lesions (69 malignant, 27 inflammatory). Short dynamic acquisitions (20 min) were motion-corrected and analysed to generate influx rate (Ki) and distribution volume (Vd) maps. Lesions were segmented on SUV images (40% SUVmax), and radiomic features were extracted from SUV, Ki, and Vd maps. Exploratory data analysis, linear modelling, and dimensionality reduction assessed separability. A Random Forest classifier was trained with crossvalidation, integrating Synthetic Minority Oversampling (SMOTE) to address class imbalance. An independent validation cohort of 15 lesions (13 inflammatory, 2 malignant) was tested. ResultsMalignant lesions showed higher SUVmean (5.8 vs. 2.8 g/ml) and Ki (1.95 vs. 0.75 ml/min/100ml), whereas inflammatory lesions demonstrated higher Vd (44.7 vs. 35.1%). No single feature provided reliable thresholds. Logistic regression achieved 89% accuracy but suffered from quasi-separation, confirming limited linear discriminability. Random Forest classification yielded robust performance (cross-validated AUC-ROC 0.876; AUC-PR 0.948). With G-mean thresholding, inflammation was detected with high recall (0.93) but recall for malignancy was lower (0.74). Feature importance highlighted SUV and Ki variance, as well as Ki/ Vd ratios, as strongest predictors. In the external validation set, accuracy reached 0.80, with inflammation reliably identified (precision 0.85, recall 0.85). ConclusionShort dynamic Patlak imaging combined with machine learning improves the characterization of malignant versus inflammatory uptake beyond SUV alone. By decomposing FDG up-take into metabolized (Ki) and unmetabolized (Vd) fractions, this approach provides physiologically meaningful separation of tracer behaviour. While sensitivity for malignancy requires further optimization, our findings establish a reproducible framework for future more extensive research on clinical interpretation of parametric imaging in oncologic PET.

Radionuclides used for imaging and therapy can show high molecular specificity in the body with appropriate targeting ligands. We hypothesized that local energy delivered by molecularly targeted radionuclides could chemically activate prodrugs at disease sites while avoiding activation in off-target sites of toxicity. As proof-of-principle, we tested whether this strategy of "RAdionuclide induced Drug Engagement for Release" (RAiDER) could locally deliver combined radiation and chemotherapy to maximize tumor cytotoxicity while minimizing exposure to activated chemotherapy in off-target sites. MethodsWe screened the ability of radionuclides to chemically activate a model radiation-activated prodrug consisting of the microtubule destabilizing monomethyl auristatin E caged by a radiation-responsive phenyl azide ("caged-MMAE") and interpreted experimental results using the radiobiology computational simulation suite TOPAS-nBio. RAiDER was evaluated in syngeneic mouse models of cancer using fibroblast activation protein inhibitor (FAPI) agents 99mTc-FAPI-34 and 177Lu-FAPI-04, the prostate-specific membrane antigen (PSMA) agent 177Lu-PSMA-617, combined with caged-MMAE or caged-exatecan. Biodistribution in mice, combined with clinical dosimetry, estimated the relationship between radiopharmaceutical uptake in patients and anticipated concentrations of activated prodrug using RAiDER. ResultsRAiDER efficiency varied by 250-fold across radionuclides (99mTc>177Lu>64Cu>68Ga>223Ra>18F), yielding up to 1.22{micro}M prodrug activation per Gy of exposure from 99mTc. Computational simulations implicated low-energy electron-mediated free radical formation as driving prodrug activation. Clinically relevant radionuclide concentrations chemically activated caged-MMAE restored its ability to destabilize microtubules and increased its cytotoxicity by up to 600-fold compared to non-irradiated prodrug. Mice treated with 99mTc-FAPI-34 and caged-MMAE accumulated up to 3000x greater concentrations of activated MMAE in tumors compared to other tissues. RAiDER with 99mTc-FAPI-34 or 177Lu-FAPI-04 delayed tumor growth, while monotherapies did not (P<0.03). Clinically-guided dosimetry suggests sufficient radiation doses can be delivered to activate therapeutically meaningful levels of prodrug. ConclusionThis proof-of-concept study shows that RAiDER is compatible with multiple radionuclides commonly used in nuclear medicine and has the potential to improve the efficacy of radiopharmaceutical therapies to treat cancer safely. RAiDER thus shows promise as an effective strategy to treat disseminated malignancies and broadens the capability of radiopharmaceuticals to trigger diverse biological and therapeutic responses. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=136 SRC="FIGDIR/small/606075v1_ufig1.gif" ALT="Figure 1"> View larger version (33K): org.highwire.dtl.DTLVardef@18aef37org.highwire.dtl.DTLVardef@5f36eforg.highwire.dtl.DTLVardef@10fa0ccorg.highwire.dtl.DTLVardef@105c416_HPS_FORMAT_FIGEXP M_FIG C_FIG

Multimodal Positron Emission Tomography/Computed Tomography (PET/CT) plays a key role in the diagnosis, staging, restaging, treatment response assessment, and radiotherapy planning of malignant tumors. The complementary nature of high-resolution anatomic CT and high sensitivity/specificity molecular PET imaging provides accurate assessment of disease status [14] In oncology, 18-fluorodeoxyglucose (FDG) PET/CT is the most widely used method to identify and analyze metabolically active tumors. In particular, FDG uptake allows for more accurate detection of both nodal and distant forms of metastatic disease. Accurate quantification and staging of tumors is the most important prognostic factor for predicting the survival of patients and for designing personalized patient management plans. [8,3] Analyzing PET/CT quantitatively by experienced medical imaging experts/radiologists is timeconsuming and error-prone. Automated quantitative analysis by deep learning algorithms to segment tumor lesions will enable accurate feature extraction, tumor staging, radiotherapy planning, and treatment response assessment. The AutoPET Challenge 2022 provided an opensource platform to develop and benchmark deep learning models for automated PET lesion segmentation by providing large open-source wholebody FDG-PET/CT data. Using the multimodal PET/CT data from 900 subjects with 1014 studies provided by the AutoPET MICCAI 2022 Challenge, we applied fivefold cross-validation on residual UNETs to automatically segment lesions. We then utilized the output from adaptive ensemble highly contributive models as the final segmentation. Our method achieved a 10th ranking with a dice score of 0.5541 in the heldout test dataset (N=150 studies).

Accurate quantification of tau binding from 18F-PI-2620 PET requires kinetic modeling and an input function. Here, we implemented a non-invasive Image-derived input function (IDIF) derived using the state-of-the-art total-body uEXPLORER PET/CT scanner to quantify tau binding and tracer delivery rate from 18F-PI-2620 in the brain. Additionally, we explored the impact of scan duration on the quantification of kinetic parameters. Total-body PET dynamic data from 15 elderly participants were acquired. Time-activity curves from the grey matter regions of interest (ROIs) were fitted to the two-tissue compartmental model (2TCM) using a subject-specific IDIF derived from the descending aorta. ROI-specific kinetic parameters were estimated for different scan durations ranging from 10 to 90 minutes. Logan graphical analysis was also used to estimate the total distribution volume (VT). Differences in kinetic parameters were observed between ROIs, including significant reduction in tracer delivery rate (K1) in the medial temporal lobe. All kinetic parameters remained relatively stable after the 60-minute scan window across all ROIs, with K1 showing high stability after 30 minutes of scan duration. Excellent correlation was observed between VT estimated using 2TCM and Logan plot analysis. This study demonstrated the utility of IDIF with total-body PET in investigating 18F-PI-2620 kinetics in the brain.

BackgroundDysfunction of cyclic nucleotide phosphodiesterase 7 (PDE7) has been associated with excess intracellular cAMP concentrations, fueling pathogenic processes that are implicated in neurodegenerative disorders. The aim of this study was to develop a suitable PDE7-targeted positron emission tomography (PET) probe that allows non-invasive mapping of PDE7 in the mammalian brain. MethodsBased on a spiro cyclohexane-1,4-quinazolinone scaffold with known inhibitory properties towards PDE7, we designed and synthesized a methoxy analog that was suitable for carbon-11 labeling. Radiosynthesis was conducted with the respective desmethyl precursor using [11C]MeI. The resulting PET probe, codenamed [11C]26, was evaluated by cell uptake studies, ex vivo biodistribution and radiometabolite studies, as well as in vivo PET experiments in rodents and nonhuman primates (NHP). ResultsTarget compound 26 and the corresponding phenolic precursor were synthesized in 2-3 steps with overall yields of 49.5% and 12.4%, respectively. An inhibitory constant (IC50) of 31 nM towards PDE7 was obtained and no significant interaction with other PDE isoforms were observed. [11C]26 was synthesized in high molar activities (170 - 220 GBq/{micro}mol) with radiochemical yields of 34{+/-}7%. In vitro cell uptake of [11C]26 was 6-7 folds higher in PDE7 overexpressing cells, as compared to the controls, whereas an in vitro specificity of up to 90% was measured. Ex vivo metabolite studies revealed a high fraction of intact parent in the rat brain (98% at 5 min and 75% at 30 min post injection). Considerable brain penetration was further corroborated by ex vivo biodistribution and PET imaging studies - the latter showing heterogenic brain uptake. While marginal specific binding was observed by PET studies in rodents, a moderate, but dose-dependent, blockade was observed in the NHP brain following pretreatment with non-radioactive 26. ConclusionIn this work, we report on the preclinical evaluation of [11C]26 (codename [11C]P7-2104), a PDE7-targeted PET ligand that is based on a spiroquinazolinone scaffold. [11C]26 displayed promising in vitro performance characteristics, a moderate degree of specific binding in PET studies with NHP. Accordingly, [11C]26 will serve as a valuable lead compound for the development of a new arsenal of PDE7-targeted probes with potentially improved in vivo specificity.

The synaptic vesicle protein SV2C, predominantly found in the basal ganglia, has been associated with Parkinsons disease through genetic studies. It plays a crucial role in regulating dopamine release and has been shown to be disrupted in PD animal models and brain tissues from PD patients. In the context of PD-related synaptopathy, SV2C may serve as a potential imaging target for monitoring disease progression and response to treatment. [18F]UCB-F is a radioligand binding to SV2C developed by UCB. Preliminary autoradiography and PET studies in rats showed that [18F]UCB-F displays a brain distribution consistent with the expression of SV2C in vitro but does not display any specific binding in vivo. This study was therefore designed to further investigate the affinity and selectivity of [18F]UCB-F for SV2C and to examine the in vitro and in vivo properties of the radioligand in non-human primates. In vitro binding studies were performed to measure the affinity of UCB-F to SV2A, SV2B, and SV2C. Insilico modeling was used to assess the binding mode and energy of UCB-F. Autoradiography studies on rat and non-human primate (NHP) brain tissues were performed to confirm that [18F]UCB-F showed similar distribution in rat and NHP tissue. Finally, PET studied in NHPs were performed to examine the in vivo pharmacokinetic properties of [18F]UCB-F. [18F]UCB-F was successfully synthesized from the corresponding precursor with high yield. Autoradiography on brain slices from rats and NHPs demonstrated specific binding of [18F]UCB-F in the pallidum, striatum, substantia nigra, and brainstem, consistent with the known brain expression of SV2C. In NHPs, [18F]UCB-F rapidly crossed the blood-brain barrier, reaching peak uptake values of 2.8 %ID in NHP1 and 2.1 %ID in NHP2 at 4 minutes post-injection. The tracer wasrapidly washed out from the brain, with no clear regional distribution. Radiometabolite analysis revealed the formation of only more polar radiometabolites, with approximately 15% of unchanged radioligand remaining in plasma at 15 minutes post-injection. In vitro and in-silico studies demonstrated that the affinity of [18F]UCB-F decreased by approximately one factor of magnitude with increase of temperature from 4{degrees} to 37{degrees} C. This temperature-related decrease of the affinity for SV2C together with rapid in vivo radiometabolism might explain the discrepancy between in vitro and in vivo performance of [18F]UCB-F. Overall, these findings suggest that [18F]UCB-F is not a suitable PET radioligand for imaging SV2C. Further research is needed to identify alternative candidates with improved in vivo stability and brain retention.

ObjectivesDisialoganglioside 2 (GD2), overexpressed by cancers such as melanoma and neuroblastoma, is a tumor antigen for targeted therapy. The delivery of conventional IgG antibody technologies targeting GD2 is limited clinically by its co-expression on nerves that contributes to toxicity presenting as severe neuropathic pain. To improve the tumor selectivity of current GD2-targeting approaches, a next-generation bispecific antibody targeting GD2 and B7-H3 (CD276) was generated. MethodsDifferential expression of human B7-H3 (hB7-H3) was transduced into GD2+ B78 murine melanoma cells and confirmed by flow cytometry. We assessed the avidity and selectivity of our GD2-B7-H3 targeting bispecific antibodies (INV34-6, INV33-2, and INV36-6) towards GD2+/hB7-H3- B78 cells relative to GD2+/hB7-H3+ B78 cells using flow cytometry and competition binding assays, comparing results an anti-GD2 antibody (dinutuximab, DINU). The bispecific antibodies, DINU, and a non-targeted bispecific control (bsAb CTRL) were conjugated with deferoxamine for radiolabeling with Zr-89 (t1/2 = 78.4 h). Using positron emission tomography (PET) studies, we evaluated the in vivo avidity and selectivity of the GD2-B7-H3 targeting bispecific compared to bsAb CTRL and DINU using GD2+/hB7-H3+ and GD2+/hB7-H3- B78 tumor models. ResultsFlow cytometry and competition binding assays showed that INV34-6 bound with high avidity to GD2+/hB7-H3+ B78 cells with high avidity but not GD2+/hB7-H3+ B78 cells. In comparison, no selectivity between cell types was observed for DINU. PET in mice bearing the GD2+/hB7-H3- and GD2+/hB7-H3+ B78 murine tumor showed similar biodistribution in normal tissues for [89Zr]Zr-Df-INV34-6, [89Zr]Zr-Df-bsAb CTRL, and [89Zr]Zr-Df-DINU. Importantly, [89Zr]Zr-Df-INV34-6 tumor uptake was selective to GD2+/hB7-H3+ B78 over GD2+/hB7-H3- B78 tumors, and substantially higher to GD2+/hB7-H3+ B78 than the non-targeted [89Zr]Zr-Df-bsAb CTRL control. [89Zr]Zr-Df-DINU displayed similar uptake in both GD2+ tumor models, with uptake comparable to [89Zr]Zr-Df-INV34-6 in the GD2+/hB7-H3+ B78 model. ConclusionThe GD2-B7-H3 targeting bispecific antibodies successfully improved selectivity to cells expressing both antigens. This approach should address the severe toxicities associated with GD2-targeting therapies by reducing off-tumor GD2 binding in nerves. Continued improvements in bispecific antibody technologies will continue to transform the therapeutic biologics landscape. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=114 SRC="FIGDIR/small/595624v2_ufig1.gif" ALT="Figure 1"> View larger version (44K): org.highwire.dtl.DTLVardef@11afee9org.highwire.dtl.DTLVardef@1558607org.highwire.dtl.DTLVardef@1d23d6eorg.highwire.dtl.DTLVardef@1bf1d63_HPS_FORMAT_FIGEXP M_FIG C_FIG

Immunotherapies, especially the checkpoint inhibitors such as anti-PD-1 antibodies, have transformed cancer treatment by enhancing immune systems capability to target and kill cancer cells. However, predicting immunotherapy response remains challenging. 18F-AraG is a molecular imaging tracer targeting activated T cells, which may facilitate therapy response assessment by non-invasive quantification of immune cell activity within tumor microenvironment and elsewhere in the body. The aim of this study was to obtain preliminary data on total-body pharmacokinetics of 18F-AraG, as a potential quantitative biomarker for immune response evaluation. MethodsThe study consisted of 90-min total-body dynamic scans of four healthy subjects and one non-small cell lung cancer (NSCLC) patient, scanned before and after anti-PD-1 immunotherapy. Compartmental modeling with Akaike information criterion model selection were employed to analyze tracer kinetics in various organs. Additionally, seven sub-regions of the primary lung tumor and four mediastinal lymph nodes were analyzed. Practical identifiability analysis was performed to assess reliability of kinetic parameter estimation. Correlations of SUVmean, SUVR (tissue-to-blood ratio), and Logan plot slope (KLogan) with total volume-of-distribution (VT) were calculated to identify potential surrogates for kinetic modeling. ResultsStrong correlations were observed between KLogan and SUVR values with VT, suggesting that they can be used as promising surrogates for VT, especially in organs with low blood-volume fraction. Moreover, the practical identifiability analysis suggests that the dynamic 18F-AraG PET scans could potentially be shortened to 60 minutes, while maintaining quantification accuracy for all organs-of-interest. The study suggests that although 18F-AraG SUV images can provide insights on immune cell distribution, kinetic modeling or graphical analysis methods may be required for accurate quantification of immune response post-therapy. While SUVmean showed variable changes in different sub-regions of the tumor post-therapy, the SUVR, KLogan, and VT showed consistent increasing trends in all analyzed sub-regions of the tumor with high practical identifiability. ConclusionOur findings highlight the promise of 18F-AraG dynamic imaging as a non-invasive biomarker for quantifying the immune response to immunotherapy in cancer patients. The promising total-body kinetic modeling results also suggest potentially wider applications of the tracer in investigating the role of T cells in the immunopathogenesis of diseases.

The traditional design of PET target engagement studies is based on a baseline scan and one or more scans after drug administration. We here evaluate an alternative design in which the drug is administered during an on-going scan (i.e., a displacement study). This approach results both in lower radiation exposure and lower costs. Existing kinetic models assume steady state. This condition is not present during a drug displacement and consequently, our aim here was to develop kinetic models for analysing PET displacement data. We modified existing compartment models to accommodate a time-variant increase in occupancy following the pharmacological in-scan intervention. Since this implies the use of differential equations that cannot be solved analytically, we developed instead one approximate and one numerical solution. Through simulations, we show that if the occupancy is relatively high, it can be estimated without bias and with good accuracy. The models were applied to PET data from six pigs where [11C]UCB-J was displaced by intravenous brivaracetam. The dose-occupancy relationship estimated from these scans showed good agreement with occupancies calculated with Lassen plot applied to baseline-block scans of two pigs. In summary, the proposed models provide a framework to determine target occupancy from a single displacement scan.

BackgroundBispecific antibodies exploiting receptor-mediated transcytosis offer a promising strategy to overcome limited blood-brain barrier permeability in Alzheimers disease (AD) therapy and imaging. Lecanemab-Fab8D3 (Lec-Fab8D3), a bispecific anti-amyloid beta (A{beta}) antibody engineered for enhanced brain delivery, holds potential as a companion immunoPET imaging diagnostic with the novel lecanemab immunotherapy. This study aimed to compare three radionuclides--zirconium-89 (89Zr), copper-64 (64Cu), and iodine-124 (124I)--for PET imaging with Lec-Fab8D3 to study its in vivo brain distribution and evaluate its potential as an AD companion diagnostic. MethodsLec-Fab8D3 was conjugated to DFO* or NODAGA for 89Zr and 64Cu radiolabeling, respectively, or directly radioiodinated with 124I. PET imaging was performed in the Tg-ArcSwe mouse model of A{beta} pathology and wild-type (WT) littermates at multiple time points post administration of the radiolabeled antibody, followed by ex vivo biodistribution, autoradiography, and A{beta} quantification to assess brain uptake, specificity, and distribution of the radiolabeled Lec-Fab8D3. ResultsRadiolabeled Lec-Fab8D3 variants showed retained binding properties with high radiochemical purity and yields. PET imaging demonstrated cortical brain uptake of all three tradiotracers in Tg-ArcSwe mice, with [89Zr]Zr-DFO*-Lec-Fab8D3 and [124I]I-Lec-Fab8D3 showing the best discrimination between Tg-ArcSwe and WT mice at 48-72 h post-injection. The highest absolute brain retention, combined with a lower brain-to-cerebellum ratio, was observed in both Tg-ArcSwe and WT mice that received the radiometal-labeled (89Zr and 64Cu) antibody, likely due to the residualizing nature of radiometals. Ex vivo analyses confirmed PET findings, and immunostaining demonstrated co-localization of Lec-Fab8D3 with A{beta} deposits. ConclusionsImmunoPET imaging with bispecific Lec-Fab8D3 enables specific detection of brain A{beta} pathology in an AD mouse model. 89Zr was superior to 64Cu due to a more compatible half-life, while 124I displayed higher regional contrast than both radiometals, despite lower overall brain signal. The combined findings from radiometal- and iodine-based immunoPET will enhance our understanding of intra-brain distribution of bispecific antibodies. Furthermore, this highlights the importance of the choice of radiolabeling strategy and how it will impact the outcome of immunoPET with bispecific A{beta} antibodies.

BackgroundGadolinium-based contrast agents (GBCAs) have recognized limitations for accurate delineation of brain tumor margins and perfusion assessment in neuro-oncology. Nanoparticle contrast agents (NP-CAs), particularly ultrasmall superparamagnetic iron oxides (USPIOs), may overcome these limitations by providing delayed uptake and tissue characterization. MethodsWe systematically searched PubMed, Embase, Scopus, Web of Science, and trial registries on July 2025 for human neuro-oncology studies using NP-CAs. The primary outcome was the change in relative cerebral blood volume ({Delta}rCBV) compared with that of GBCA imaging at prespecified time points. The secondary outcomes were the contrast-to-noise ratio (CNR), signal-to-noise ratio (SNR), reader-rated margin delineation, and safety. Two reviewers independently extracted the data and assessed the risk of bias via tools from the Joanna Briggs Institute. Random effects meta-analysis was performed when [&ge;]3 comparable datasets were available; otherwise, the results were synthesized narratively. ResultsSix studies met the inclusion criteria. Agents included ferumoxtran-10, ferumoxytol, and ferumoxides, with intravenous doses ranging from 0.56-7.00 mg Fe/kg. The pooled common-effect mean dose was 4.65 mg/kg. Across heterogeneous designs, NP-CAs consistently enhanced margin delineation and perfusion metrics: ferumoxtran-10 produced sharp, persistent T2/T2* rims beyond T1-GBCA enhancement, and ferumoxytol-based DSC (Dynamic Susceptibility Contrast) yielded a higher rCBV with reduced leakage effects. No serious adverse events were reported; infusion reactions were rare and inconsistently defined. ConclusionsCompared with GBCA, NP-CAs, particularly USPIOs, improve brain tumor margin visualization and perfusion assessment. However, methodological heterogeneity and small sample sizes limit certainty. Standardized protocols for dosing, acquisition, and safety monitoring, alongside biopsy-validated prospective trials, are needed before clinical adoption.

CD47/SIRP immune axis is of substantial clinical interest for innate cancer immunotherapy. Development on this axis has largely focused on monoclonal antibody agents and combination therapy strategies. Clinical use is challenging due to dose limiting side effects and severe anemia. Better understanding of the whole-body dynamics of CD47/SIRP can be used to improve the developmental and therapeutic strategies targeting this axis. Herein, we developed anti-CD47 and anti-SIRP radiotracers with good yields and stability. CD47/SIRP biodistribution showed consistent whole-body results in healthy and colorectal cancer (CT26) allograft mice, demonstrating significant uptake in normal organs liver and spleen in addition to tumor accumulation of these agents. Enhancing immunogenicity via low-dose radiotherapy had no impact on over-all biodistribution but caused small, significant changes for anti-SIRP tumor uptake. Antibody PEGylation of the anti-SIRP tracer was further able to modify the whole-body distribution and reduce splenic uptake. These findings suggest that SIRP targeted agents may benefit from co-therapies and drug delivery systems to optimize tumor uptake. Our work highlights the importance of in vivo molecular imaging in addition to in vitro and ex vivo assays when evaluating therapeutic designs.

Cerenkov (or Cherenkov) luminescence occurs when charged particles exceed the phase velocity of a given medium. Cerenkov has gained interest in preclinical space as well as in clinical trials for optical visualization of numerous radionuclides. However, Cerenkov intensity has to be inferred from alternative databases with energy emission spectra, or theoretical fluence estimates. Here we present the largest experimental dataset of Cerenkov emitting isotopes recorded using the IVIS optical imaging system. We report Cerenkov measurements spanning orders of magnitude normalized to the activity concentration for 21 Cerenkov emitting isotopes, covering electron, alpha, beta minus, and positron emissions. Isotopes measured include Carbon-11, Fluorine-18, Phosphorous-32, Scandium-47, Copper-64, Copper-67, Gallium-68, Arsenic-72, Bromine-76, Yttrium-86, Zirconium-89, Yttrium-90, Iodine-124, Iodine-131, Cerium-134, Lutetium-177, Lead-203, Lead-212, Radium-223, Actinium-225, and Thorium-227. We hope this updating resource will serve as a rank ordering for comparing isotopes for Cerenkov luminescence in the visible window and serve as a rule of thumb for comparing Cerenkov intensities in vitro and in vivo. MethodsAll Cerenkov emitting radionuclides were either produced at Memorial Sloan Kettering Cancer Center (Carbon-11, 11C; Fluorine-18, 18F; Iodine-124, 124I), from commercial sources such as Perkin Elmer (Phosphorous-32, 32P; Yttrium-90, 90Y), Bayer (Radium-223, 223Ra, Xofigo), 3D-Imaging (Zirconium-89, 89Zr), Nuclear Diagnostic Products (Iodine-131, 131I), or from academic collaborators at Washington University at St. Louis (Copper-64, 64Cu), University of Wisconsin (Bromine-76, 76Br), MD Anderson Cancer Center (Yttrium-86, 86Y), Brookhaven National Laboratory (Arsenic-72, 72As; Thorium-227, 227Th), or Oak Ridge National Laboratory (Cerium-134, 134Ce, Actinium-225, 225Ac), and Viewpoint Molecular Targeting (Lead-203, 203Pb; Lead 212, 212Pb). All isotopes were diluted in triplicate on a black bottomed corning 96 well plate to several activity concentrations ranging from 0.1-250 Ci in 100-200 L of Phosphate Buffered Saline. Cerenkov imaging was acquired on a single Perkin-Elmer Spectrum In-Vivo Imaging System (IVIS) at field of view c with exposures ranging up to 15 minutes or lower provided no part of the image intensity was saturated, or that the activity significantly changed during the exposure. Experimental radiances on the IVIS were calculated from regions of interest drown over each 96 well, and then normalized for the activity present in the well, and the volume the isotope was diluted into.

Plasma pharmacokinetic (PK) data is required as an input function for graphical analysis (e.g., Patlak plot) of single positron emission computed tomography/computed tomography (SPECT/CT) and positron emission tomography/CT (PET/CT) data to evaluate tissue influx rate of radiotracers. Dynamic heart imaging data is often used as a surrogate of plasma PK. However, accumulation of radiolabel (representing both intact and degraded tracer) in the heart tissue may interfere with accurate prediction of plasma PK from the heart data. Therefore, we developed a compartmental model, which involves forcing functions to describe intact and degraded radiolabeled proteins in plasma and their accumulation in heart tissue, to deconvolve plasma PK of 125I-amyloid beta 40 (125I-A{beta}40) and 125I-insulin from their dynamic heart imaging data. The three-compartment model was shown to adequately describe the plasma concentration-time profile of intact/degraded proteins and the heart radioactivity time data obtained from SPECT/CT imaging for both tracers. The model was successfully applied to deconvolve the plasma PK of both tracers from their naive datasets of dynamic heart imaging. In agreement with our previous observations made by conventional serial plasma sampling, the deconvolved plasma PK of 125I-A{beta}40 and 125I-insulin in young mice exhibited lower area under the curve (AUC) than the aged mice. Further, Patlak plot parameters (Ki) extracted using deconvolved plasma PK as input function successfully recapitulated age-dependent blood-to-brain influx kinetics changes for both 125I-A{beta}40 and 125I-insulin. Therefore, the compartment model developed in this study provides a novel approach to deconvolve plasma PK of radiotracers from their noninvasive dynamic heart imaging. This method facilitates the application of preclinical SPECT or PET imaging data to characterize distribution kinetics of tracers where simultaneous plasma sampling is not feasible.