European Journal of Nuclear Medicine and Molecular Imaging

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.

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.

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.

Background and Purpose: 2-[18F] fluoro-2-deoxy-D-glucose positron emission tomography (static PET) has mixed specificity and sensitivity in targeting epileptic zones in the noninvasive stage of epilepsy surgery evaluations. We compared the signal quality of static PET compared to a method of interictal dynamic PET (iD-PET). Materials and Methods: We calculated the signal quality of static PET and iD-PET obtained from a cohort of patients with focal epilepsy. We developed a Bayesian regional estimated signal quality (BRESQ) technique to objectively compare signal-to-noise ratios (SNRs) by region of interest (ROI) within subjects. Results: Adjusted for ROI size and neighboring regions, iDPET was superior to sPET with probability >95% in 8/36 regions; >90% in 21/36 regions; >80% in 29/36 regions. The top five regions with the largest adjusted SNR differences (greatest magnitude of iDPET superiority) were the Temporal Mesial (Left and Right), Occipital Lateral (Left and Right), and the Left Frontal Inferior Base. Conclusions: We found that iDPET yielded a superior SNR in most ROI. BRESQ offers a scalable and generalizable method to quantify signal quality between brain mapping modalities.

Background/ObjectivesDevelopability assessment is a critical step in advancing antibody-based molecules toward clinical application. This evaluation typically begins during clinical candidate selection and continues throughout all modifications of the molecule during development. It is guided by the target product profile, which includes the intended administration route and regimen, formulation parameters, and process conditions encountered during manufacturing, storage, and delivery. While developability testing is well established for conventional therapeutic antibodies, strategies for assessing single-domain antibodies (sdAbs) and their conjugates remain underexplored. Here we present a strategy to test the developability of sdAbs as a case study for two clinical candidates intended as precursors for the production of diagnostic tracers for clinical imaging. MethodsAssays were developed to evaluate chemical and thermodynamic stability, target binding affinity and capacity, and chelation efficiency ("chelatability"). Accelerated stability studies were conducted for both unconjugated sdAbs and their chelator conjugated forms following incubation at two pH conditions, at multiple time points, and after twelve freeze-thaw cycles to simulate process conditions and long-term storage. Analytical assays were applied stepwise in a hierarchical approach to minimized experimental effort and material consumption. Candidates exhibiting critical developability features were selectively addressed by assays with increasing precision. ResultsA tailored panel of analytical assays optimized for low molecular weight proteins was established and applied to the two clinical candidates, identifying instability hotspots as well as potential mitigation strategies. Successful engineering of a candidate with an initially critical developability profile was achieved. ConclusionThis study demonstrates the implementation of a structured developability assessment strategy for sdAb conjugates. The approach integrates physicochemical and functional stability evaluations, supporting robust candidate selection, formulation development, and method optimization for this class of molecules.

BackgroundAlthough deep learning models have improved individual PET analysis, image processing and quantification tasks, end-to-end automation from raw DICOM to quantitative clinical reporting remains limited, particularly in heterogeneous real-world settings. MethodsAs a proof-of-concept, an autonomous large language model (LLM)-orchestrated multi-tool agent for end-to-end PET/CT interpretation was developed. A reasoning-based text LLM selected appropriate series from raw DICOM, coordinated registration and SUV conversion, invoked segmentation and detection tools, generated maximum-intensity projections, called a vision-enabled LLM for interpretation, and synthesized structured draft reports. The system was retrospectively evaluated in 170 patients undergoing baseline FDG PET/CT for lung cancer staging, using expert reports as reference. ResultsThe agent successfully completed the full end-to-end workflow from raw DICOM selection to structured draft report generation without human intervention in all 170 examinations. Primary tumor detection achieved 100% sensitivity. For nodal involvement, sensitivity was 84.8% and specificity was 39.4%, whereas distant metastasis detection showed 70.2% sensitivity and 65.0% specificity. Discrepancy analysis of 58 nodal and 57 metastatic mismatch cases revealed systematic false-positive findings related to reactive or physiologic uptake and false-negative findings involving small-volume or anatomically atypical metastases. ConclusionLLM-orchestrated PET/CT agents can enable workflow-level automation from raw DICOM to quantification and structured draft reporting under real-world conditions. Although primary tumor detection was highly reliable, nodal and metastatic assessment revealed systematic limitations, supporting a collaborative role with continued expert oversight in complex clinical scenarios.

BackgroundQuantitative cerebral blood flow (CBF) measured with [15O]water positron emission tomography (PET) is the reference standard for quantifying brain perfusion. However, clinical interpretation of individual CBF measurements is limited by the absence of large normative datasets accounting for physiological variability across the adult lifespan. Long-axial field-of-view PET enables high-sensitivity quantitative [15O]water perfusion imaging without arterial blood sampling, allowing normative characterization of cerebral perfusion at unprecedented scale. The aim of this study was to establish normative and covariate-adjusted models of cerebral blood flow across the adult lifespan using total-body [15O]water PET. MethodsQuantitative CBF measurements were obtained in 302 neurologically healthy adults (age 21-86 years) using total-body [15O]water PET. Linear mixed-effects models were used to evaluate the effects of age, sex, body mass index (BMI), and blood hemoglobin concentration on CBF and to generate normative prediction models across the adult lifespan. Between-subject and within-subject variability were estimated from repeated scans in a subset of participants (n=51). ResultsMean grey matter CBF was 46.1 mL/(min*dL), with substantial inter-individual variability but high within-subject reproducibility (intraclass correlation coefficients 0.78-0.89). Advancing age was associated with a decline in CBF of approximately 7% per decade (p_FDR < 10-12). Higher BMI was associated with lower CBF (approximately -6% per 10 kg/m2; p_FDR < 0.01). Women exhibited higher CBF than men (approximately 7.5%), but this difference was largely explained by lower blood hemoglobin concentration in women. Covariate-adjusted models were used to generate normative predictions and prediction intervals describing expected CBF across adulthood. ConclusionThis study establishes a normative database of quantitative cerebral blood flow across the adult lifespan using high-sensitivity [15O]water PET. Age, BMI, and hemoglobin are major determinants of inter-individual variability in CBF. The resulting generative models provide a quantitative reference framework for interpreting cerebral perfusion measurements and may enable automated detection of abnormal brain perfusion in clinical PET imaging.

It has been hypothesized that effective cellular internalization is required for the retention of 225Ac daughter radionuclides. The complex decay chain of 225Ac and recoil-mediated release of daughters, particularly 213Bi (half-life (t1/2) = 46 min), raise concerns about redistribution that may reduce tumor absorbed dose (TAD) and increase off-target radiation exposure. Because somatostatin receptor subtype 2 (SSTR2) antagonists such as SSO110 are not internalized, it has been proposed that the daughter radionuclides are less effectively retained compared to internalizing agonists such as DOTA-TATE. We therefore performed a direct and quantitative comparison of daughter radionuclide redistribution following administration of [225Ac]Ac-SSO110 and [225Ac]Ac-DOTA-TATE. MethodsBiodistribution and 213Bi redistribution were evaluated in Balb/c nude mice bearing NCI-H69 small cell lung cancer xenografts. Repeated gamma counting combined with bi-exponential modeling was used to quantify 225Ac and 213Bi activity in tumor, blood, bone marrow, kidneys, liver, and intestines up to 96 h post-injection. TAD was calculated with and without accounting for experimentally-derived 213Bi redistribution. Real-time in vitro binding assays were conducted to characterize cellular retention of [225Ac]Ac-SSO110. Results[225Ac]Ac-SSO110 demonstrated higher tumor uptake and prolonged retention compared with [225Ac]Ac-DOTA-TATE, resulting in a 1.9-fold higher tumor-to-kidney ratio at 96 h and a 2.8-fold higher TAD. Redistribution of 213Bi from tumor was minimal and comparable between agonist and antagonist, with maximum tumor loss of 3.5% for [225Ac]Ac-SSO110 and 2% for [225Ac]Ac-DOTA-TATE. Accounting for daughter redistribution reduced TAD by less than 5% for both radioconjugates. No sustained 213Bi accumulation was observed in blood, kidneys, or liver, and only minimal activity was detected in bone marrow and intestines. Real-time binding studies demonstrated sustained cell-associated {beta}- signal following incubation with [225Ac]Ac-SSO110. ConclusionReceptor-mediated internalization is not required for effective retention of 225Ac daughter radionuclides. Despite negligible internalization, [225Ac]Ac-SSO110 achieved superior TAD and higher tumor-to-kidney ratio without increased daughter redistribution compared with the internalizing agonist [225Ac]Ac-DOTA-TATE. These findings question the necessity of internalization for daughter retention and support further evaluation of antagonist-based 225Ac radioligand therapy.

Peritoneal micrometastases (micromets) remain a major barrier to durable cytoreduction in ovarian and other intra-abdominal cancers, because lesions can be difficult to visualize and are often resistant to systemic therapy. Liposomal doxorubicin (Dox) improves pharmacokinetics but can be limited by slow intratumoral release. Porphyrin-phospholipid (PoP) liposomes enable near-infrared light-triggered release of Dox (chemophototherapy (CPT)), creating an opportunity for intraoperative, fluorescence-guided treatment planning and monitoring. Here, we evaluate a laparoscopic fluorescence imaging platform for quantifying light-triggered drug delivery in 2D monolayers and 3D spheroid cluster models. Dox fluorescence increased linearly with administered LC-Dox-PoP concentration in both SCC2095sc and SKOV-3 cultures (R2 = 0.97-0.98 in 2D; R2 = 0.98 in spheroid clusters over 1-9 {micro}g/mL). Laparoscope-derived fluorescence measurements agreed with standard well-plate reader measurements (R2 = 0.89-0.96). Porphyrin fluorescence provided stronger, complementary contrast for localizing spheroid constructs and decreased after activation light exposure, consistent with photobleaching during triggered release. Together, these results support a quantitative imaging framework for fluorescence-guided monitoring of light-triggered liposomal drug release, with potential to inform individualized CPT dosimetry for peritoneal micrometastases. These findings in SCC2095sc (oral squamous cell carcinoma) additionally suggest relevance of fluorescence-guided CPT for head and neck/oral cancer, where localized post-resection adjuvant treatment may improve control of residual disease.

BackgroundPlasma biomarkers demonstrate strong within-cohort performance for identifying cerebral amyloid pathology, but their real-world clinical utility depends on generalization across populations and assay platforms. The impact of cross-cohort deployment on clinically actionable metrics such as negative predictive value (NPV) remains poorly characterized. ObjectiveTo evaluate the performance and portability of plasma biomarker-based machine learning models for amyloid PET prediction across independent cohorts, with emphasis on calibration and clinically relevant predictive values. MethodsData from ADNI (n=885) and A4 (n=822) were analyzed. Machine learning models were trained within each cohort to predict amyloid PET status and continuous amyloid burden (centiloids). Performance was assessed using ROC AUC, accuracy, R{superscript 2}, and RMSE. Cross-cohort generalizability was evaluated using bidirectional transfer without retraining. Calibration, predictive values, and decision curve analysis were used to assess clinical utility. ResultsWithin-cohort discrimination was high (AUC up to 0.913 in ADNI and 0.870 in A4), with moderate performance for centiloid prediction (R{superscript 2} up to 0.628 and 0.535, respectively). Cross-cohort deployment resulted in modest attenuation of AUC ([~]4-7%) but substantially greater degradation in clinically actionable performance. NPV declined from 0.831 to 0.644 under ADNI[-&gt;]A4 transfer ([~]19 percentage points) despite preserved discrimination. Calibration analyses demonstrated systematic probability misestimation, and decision curve analysis showed reduced net clinical benefit. Biomarker distribution differences across cohorts were consistent with dataset shift. ConclusionPlasma biomarker models retain discrimination across cohorts but exhibit clinically meaningful degradation in predictive value under deployment. Calibration instability and prevalence differences critically affect NPV, highlighting the need for cross-cohort validation, calibration assessment, and assay harmonization before clinical implementation.

Autoradiography provides microscale mapping of radionuclide distributions, a promising approach to complement nuclear medicine imaging for small-scale radiopharmaceutical therapy (RPT) research. However, quantitative protocols for {beta}-emitters remain under-established compared to those for -emitters. In this work, the ionizing-radiation quantum imaging detector (iQID) digital autoradiography system was characterized and calibrated specifically for the theranostic {beta}-emitter 177Lu. Spatial resolution, detection efficiency, background and minimum detectable activity, and depth dependence were characterized and compared to Geant4 Monte Carlo simulations. A methodology for converting count rates to activity was established, yielding a high linear response (range from 0 to 300 Bq). To validate the system for realistic measurement scenarios, cross-modality benchmarking was performed using a custom stacked multi-layer virtual water phantom to compare iQID performance with preclinical {micro}SPECT/CT. The iQID system demonstrated an effective spatial resolution of [~]43 {micro}m for 177Lu and achieved total activity estimates of (0.194 {+/-} 0.022) MBq, agreeing within 2% with the dispensed reference (0.197 {+/-} 0.015) MBq. Crucially, iQID exhibited superior quantitative accuracy for small-scale features (0.8 mm to 2.5 mm diameters), resolving activity concentrations in regions where {micro}SPECT/CT performance was severely limited by partial volume effects. This study establishes a validated framework for quantitative 177Lu digital autoradiography, laying the groundwork for accurate activity estimation in ex vivo tissue samples.

PURPOSEGlycolytic production of HDO from the metabolism of perdeuterated glucose provides a means for metabolic imaging with 2H MRI. The present study compared HDO production from a cost-efficient [2,3,4,6,6-2H5]glucose with [2H7]glucose in vitro and in vivo. METHODS2H NMR spectroscopy was performed to measure glucose consumption, lactate, and HDO production in the SFxL glioblastoma cell line. In vivo studies in healthy mice using 2H magnetic resonance spectroscopy were performed at 11.1 T after administering a bolus of either metabolic contrast agent. In vivo metabolite levels were quantified using unlocalized and slice-selective localized spectra. RESULTSOur in vitro results demonstrated similar glucose consumption and HDO production kinetics, although significant differences in lactate labeling were observed. The in vivo study showed comparable glucose consumption and HDO production kinetics following tail-vein bolus administration of either metabolic contrast agent, while lactate was not detected in the brain. CONCLUSION[2,3,4,6,6-2H5]glucose shows comparable HDO production to [2H7]glucose, while offering lower cost and reduced spectral complexity. These findings place [2,3,4,6,6-2H5]glucose as an alternative to [2H7]glucose for HDO-based DMI studies.

Affibodies are remarkably stable three-helix bundle proteins that can be engineered to selectively bind target proteins. When combined with radioactive metals, they serve as imaging agents or cancer therapeutics, depending on the metal used. Traditionally, this involves bifunctional linkers that attach large chelators to the affibody via reactive groups. Here, we present an alternative approach that eliminates the need for such linkers by burying the metal within the core of the affibody, surrounded by its three helices. A simple engineered triple cysteine motif, with one cysteine in each helix, stably binds Bi(III), Pb(II), In(III) and Ga(III), which are commonly used in imaging and radiotherapy. Quantitative metal uptake is instantaneous at room temperature and physiological pH, and all metal-affibody complexes remain fully intact for one week at 4 {degrees}C. All retain their metal cargo when challenged with cellular concentrations of glutathione, while only the bismuth-affibody complex withstands a challenge with 100 equivalents of strong chelators, even over two weeks. We demonstrate selective uptake and retention of 213Bi, a promising isotope for targeted alpha therapy.

BACKGROUNDSteno-occlusive diseases of the internal carotid artery (ICA) or middle cerebral artery (MCA) can lead to hemodynamic impairment, yet conventional imaging often fails to reflect metabolic dysfunction. Integrated positron emission tomography and magnetic resonance imaging (PET/MRI) allows simultaneous assessment of cerebral blood flow (CBF) and glucose metabolism. This study compared baseline perfusion and metabolic characteristics between patients receiving medical therapy or extracranial-intracranial (EC-IC) bypass surgery. METHODSThis retrospective study enrolled 34 patients with unilateral ICA/MCA stenosis or occlusion confirmed by digital subtraction angiography. All patients underwent 18F-FDG PET/MRI before treatment. Glucose metabolism was quantified using the cerebral metabolic rate of glucose (CMRGlu) from dynamic PET and the standard uptake value ratio (SUVR) from static PET. CBF was measured using three-dimensional arterial spin labeling with post-labeling delays of 2.0 and 2.5 seconds. Perfusion and metabolic parameters were compared across vascular territories. RESULTSBaseline clinical characteristics and long-term outcomes did not differ between groups (all P>0.05). Cerebral blood flow was similar across all arterial territories and post-labeling delays, with no hemispheric asymmetry detected (all P>0.05). In contrast, glucose metabolism was significantly lower in the surgical group, with reduced CMRGlu in the ischemic middle cerebral artery (23.58{+/-}7.46 vs 18.82{+/-}5.04mol/100g-1/min-1, P=0.037) and anterior cerebral artery territories (26.37{+/-}8.76 vs 20.71{+/-}5.78mol/100g-1/min-1, P=0.034). No differences were observed in the posterior cerebral artery or in SUVR across all regions (all P>0.05). CONCLUSIONSDespite similar perfusion profiles, the surgical group demonstrated lower glucose metabolism, suggesting that metabolic imaging may aid in identifying patients who could benefit from revascularization.

Somatostatin receptor 2 (SSTR2) is highly expressed in neuroendocrine tumors including small cell lung cancer (SCLC) and represents a validated target for peptide receptor radionuclide therapy. The SSTR2 agonist [177Lu]Lu-DOTA-TATE is clinically approved, however, treatment resistance and relapse occur. The SSTR2 antagonist SSO110 (DOTA-JR11, OPS201) demonstrates higher tumor uptake and longer retention than DOTA-TATE both pre-clinically and clinically. We performed a systemic head-to-head comparison of SSO110 labeled with various radionuclides of distinct emission characteristics to identify the optimal radionuclide for SSO110 and to compare antagonist with agonist performance. MethodsSSO110 was radiolabeled with 177Lu, 161Tb, 212Pb, and 225Ac. Biodistribution was assessed in AR42J and NCI-H69 xenograft models. Therapeutic efficacy of single and fractionated [212Pb]Pb-SSO110 was compared with [177Lu]Lu-SSO110 in NCI-H69 tumors. Single-dose efficacy of 225Ac-, 161Tb-, and 177Lu-labeled SSO110 was evaluated in both models. [{superscript 2}{superscript 2}Ac]Ac-DOTA-TATE served as agonist comparator. Tumor growth, survival, safety parameters, and tumor absorbed doses were analyzed. ResultsAll SSO110 radioconjugates demonstrated comparable biodistribution with high tumor uptake and favorable tumor-to-kidney ratios. In NCI-H69 tumors, [212Pb]Pb-SSO110 induced dose-dependent tumor growth delay but did not improve anti-tumor efficacy compared with [177Lu]u-SSO110 under single or fractionated regimens. [161Tb]Tb-SSO110 showed efficacy comparable to [177Lu]Lu-SSO110 in NCI-H69 model and significantly improved tumor growth delay in high-SSTR2-expressing AR42J tumors. Across both models, [225Ac]Ac-SSO110 demonstrated the highest therapeutic potency, inducing durable tumor regression and 100% survival at clinically relevant activities. [225Ac]Ac-SSO110 also outperformed the agonist comparator [225Ac]Ac-DOTA-TATE. Dosimetry analysis revealed a 63-fold higher tumor absorbed dose per injected administered activity for [225Ac]Ac-SSO110 compared with [212Pb]Pb-SSO110. All treatments were well tolerated without significant renal or hepatic toxicity. ConclusionTherapeutic efficacy of SSTR2-targeted peptide receptor radionuclide therapy appears to benefit from alignment between radionuclide physical half-life and ligand tumor residence time. Among the radionuclides evaluated, [225Ac]Ac-SSO110 demonstrated the most pronounced and durable anti-tumor efficacy, outperforming [161Tb]Tb-SSO110, [177Lu]Lu-SSO110, and the short-lived -emitter [212Pb]Pb-SSO110. These findings support clinical investigation of [225Ac]Ac-SSO110 in SSTR2-positive malignancies.

Cardiac fibrosis is a key contributor to cardiomyopathy after myocardial infarction (MI). Existing imaging techniques can detect established fibrotic changes; however, they lack sensitivity for ongoing collagen turnover--a dynamic process involving the denaturation of collagen triple helix. Molecular imaging of this process could enhance risk assessment and aid in the development of anti-fibrotic treatments. This study aimed to evaluate 99mTc-(HE)-(GPO), a radiotracer designed to target denatured collagen, as a biomarker of collagen turnover after MI. Methods99mTc-(HE)-(GPO) incorporates glycine-proline-hydroxyproline (GPO) repeats and can hybridize with denatured single- or double-stranded collagen. MI was induced in mice by ligation of the left anterior descending artery; sham-operated animals served as controls. At 2 weeks post-MI, animals underwent myocardial perfusion imaging or contrast-enhanced CT to detect the infarct zone, followed by SPECT/CT imaging using 99mTc-(HE)-(GPO) or a control scrambled tracer. Tracer uptake was quantified in vivo and ex vivo with gamma counting and autoradiography. Different aspects of fibrosis were examined by tissue analysis, along with autoradiography with a matrix metalloproteinase-targeted radiotracer, 99mTc-RYM1. Tracer binding was also assessed in human cardiac tissue through ex vivo autoradiography. Results99mTc-(HE)-(GPO) SPECT/CT revealed significantly higher tracer uptake in the infarct zone of MI mice compared to the remote zone and sham controls (P < 0.0001 for both). Tracer uptake was confirmed by autoradiography, which showed a strong correlation between SPECT and autoradiography (R = 0.81, P < 0.01). The scrambled tracer exhibited minimal cardiac uptake, demonstrating the specificity of 99mTc-(HE)-(GPO) signal. Denatured collagen staining and 99mTc-RYM1 autoradiography showed similar patterns as ex vivo 99mTc-(HE)-(GPO) autoradiography, while the ratio of denatured collagen to procollagen in the infarct zone significantly increased from day 3 to 2 weeks post-MI. Finally, 99mTc-(HE)-(GPO) bound to human fibrotic (but not normal) cardiac tissue. Conclusion99mTc-(HE)-(GPO) enables non-invasive detection of denatured collagen as a marker of collagen remodeling in vivo, offering a promising tool for assessing fibrotic remodeling after MI. Collagen, procollagen, and denatured collagen, along with MMP activation, exhibit distinct patterns, and their combined imaging may provide a comprehensive molecular fingerprint of cardiac fibrosis, advancing personalized management of cardiomyopathy.

The accumulation of tau tangles and A{beta} plaques are prominent neuropathologies that characterize Alzheimers disease (AD) and Down Syndrome (DS). Continuous developments of PET tracers as biomarkers can be supported by autoradiography to validate effectiveness and accuracy of binding properties that elucidate the pathophysiology of DSAD and AD. This in vitro comparative study evaluates [125I]IPPI binding to tau and [125I]IBETA binding to A{beta} plaques in the frontal cortex (FCX) and temporal cortex (TCX) of postmortem human brain slices of AD (n=5), DSAD (n=5), and cognitively normal (CN) (n=5) cases. With anti-tau and anti-A{beta} immunostains confirming the presence of tau and A{beta} plaques, [125I]IPPI and [125I]IBETA binding in autoradiographic images were significantly higher in DSAD and AD gray matter (GM) compared to CN. When comparing DSAD with AD, FCX and TCX GM binding was similar throughout DSAD and AD except in FCX GM where there was 48% more [125I]IPPI binding in DSAD than AD. In vitro drug inhibition studies revealed that [125I]IPPI binding was significantly inhibited with increasing harmine concentrations (IC50=115{+/-}40 nM) in DSAD FCX and TCX but KuFal194 minimally inhibited [125I]IPPI binding in the same cases. The GM/white matter ratios for DSAD ([125I]IPPI=4.1, [125I]IBETA=2.9) and AD ([125I]IPPI=4.2, [125I]IBETA=2.6) were significantly greater than CN ([125I]IPPI=1.3, [125I]IBETA=1.2). A positive correlation between [125I]IPPI and [125I]IBETA binding suggests a synergistic relationship between tau and A{beta} plaque in DSAD and AD pathology. This study demonstrates that [125I]IPPI and [125I]IBETA may serve as novel radiotracers in both DSAD and AD to continue diagnostic investigations in vivo.

Gene therapy using adeno-associated virus (AAV) vectors shows promise for cancer treatment through molecular intervention, yet achieving sufficient and targeted delivery to brain tumors via systemic administration remains limited by the biological barriers. Here, we investigate whether microbubble-enhanced focused ultrasound (MB-FUS) improves targeted delivery of systemically administered AAV9 to orthotopic gliomas, using quantitative PET imaging of 64Cu-radiolabeled AAV9 vectors and fluorescent reporter expression to assess biodistribution and functional efficacy. At 21 hours after injection, 64Cu-AAV9 accumulation was 3.2-fold higher in FUS-treated tumors compared to non-FUS-treated tumors (n=3, p=0.004). Quantitative PCR analysis of tumor tissue at the same timepoint confirmed a 6.4-fold increase in genome copies in FUS-treated tumors (p=0.0003). The enhanced vector delivery translated to a 5.3-fold increase in optical reporter protein expression in FUS-treated compared to control tumors (p=0.0002) at 17 days post-treatment. These results establish that MB-FUS enables spatially-targeted AAV delivery with quantifiable enhancement in both acute vector biodistribution and downstream transgene expression. The integration of radiolabeled AAV with PET imaging provides a non-invasive methodology for real-time assessment of vector delivery and optimization of treatment protocol for brain cancer gene therapy. HighlightsO_LIMB-FUS enables targeted systemic AAV delivery to brain tumors. C_LIO_LIMB-FUS enhanced vector delivery translates to increased transgene expression in gliomas. C_LIO_LIPET imaging of radiolabeled AAV allows non-invasive tracking of gene therapy vectors. C_LIO_LIReal-time imaging validates spatially-controlled gene delivery for brain cancer. C_LI

Besides immunotherapy, inhibitors of the DNA damage response (DDR) are currently one of the most promising contributors to improved cancer therapy. They exploit elevated replicative stress in cancer cells and often rely on synthetic lethality with existing gene deficiencies or between targeted pathways. In view of the absence of reliable histological biomarkers for replicative stress, this study examined [18F]-fluorothymidine (FLT) positron emission tomography (PET) as alternative or complementary approach to predict treatment response to DDR inhibitors. Using orthotopic and syngeneic triple negative breast cancer mouse models and treatment with combined AZD6738 and AZD1775 (inhibiting ATR and Wee1, respectively) this study found that: a) Sequential [18F]FLT-PET in the early phase of treatment was able to predict ATR/Wee1 inhibitor treatment efficacy, whereas b) [18F]FLT tumor uptake at onset of therapy was unable to predict treatment outcome, despite c) [18F]FLT tumor uptake positively correlating with Ki-67 staining, the clinically used proliferation marker. Importantly, non-invasive monitoring of changes in tumor biology by [18F]FLT-PET predicted which tumor model responds to combined AZD6738/AZD1775 treatment and established a quantitative correlation in [18F]FLT tumor uptake with tumor shrinkage in individual responders. Since the inhibitors AZD6738 and AZD1775 are already in phase I/II clinical trials, this knowledge could soon be translated into the clinic. To our knowledge this is the first study to correlate non-invasive PET imaging with treatment efficacy of DDR inhibitors. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=100 SRC="FIGDIR/small/710900v1_ufig1.gif" ALT="Figure 1"> View larger version (31K): org.highwire.dtl.DTLVardef@1e18b7eorg.highwire.dtl.DTLVardef@8d306corg.highwire.dtl.DTLVardef@1663a21org.highwire.dtl.DTLVardef@7261c2_HPS_FORMAT_FIGEXP M_FIG C_FIG