European Journal of Nuclear Medicine and Molecular Imaging最新文献

Purpose: Noninvasive angiogenesis visualization is essential for evaluating tumor proliferation, progression, invasion, and metastasis. This study aimed to translate the heterodimeric PET tracer [⁶⁸Ga]Ga-HX01, which targets integrin αvβ3 and CD13 in neovascularization, into phase I clinical study.

Methods: This study enrolled 12 healthy volunteers (phase Ia) and 10 patients with malignant tumors (phase Ib). The subjects in phase Ia were divided into low-dose (0.05 mCi/kg) and high-dose (0.1 mCi/kg) groups. For phase Ia subjects, PET/CT images, blood and urine samples were collected to analyze the biodistribution, pharmacokinetics, radiation dosimetry, and safety of [⁶⁸Ga]Ga-HX01. For phase Ib patients, PET/MR scans were performed at 30 ± 5 and 60 ± 5 min after injection. The safety and preliminary diagnostic value of [⁶⁸Ga]Ga-HX01 were assessed.

Results: In phase Ia study, [⁶⁸Ga]Ga-HX01 was distributed and metabolized similarly in two dosage groups as the highest accumulations in kidneys and urine. It possessed quick renal excretion and blood clearance with an elimination half-life (T_1/2) of 28.92 ± 3.97 min. The total effective dose was 2.14 × 10^- 2 mSv/MBq. In phase Ib study, [⁶⁸Ga]Ga-HX01 clearly detected the lesions per patient, and found a total of 59 lesions with varying uptake levels. For safety evaluation, no serious adverse events were observed during the examination.

Conclusion: [⁶⁸Ga]Ga-HX01 has proved to be a translational radiopharmaceutical with reliable security, favorable pharmacokinetics, and the ability to visualize tumors. The preliminary results in malignancy patients warrant further investigation of [⁶⁸Ga]Ga-HX01 in monitoring antiangiogenic therapy of patients with malignancies.

Clinical trial registration: ClinicalTrials.gov, NCT06416774. Registered 11 May, 2024.

Introduction: Bacterial infections pose major challenges in medicine. To guide effective infection treatment, faster and more accurate diagnostic modalities are needed. Bacteria-targeted molecular imaging can meet these needs. The present study was aimed at the in vivo evaluation of two ¹⁸F-vancomycin-based PET tracers, for detection of deep-seated Gram-positive bacterial infections. These tracers were bench-marked against the current standard of care, [¹⁸F]FDG.

Methods: The potential of [¹⁸F]BODIPY-FL-vancomycin and [¹⁸F]PQ-VE1-vancomycin ([4+2]photocycloadduct of 9,10-phenanthrenequinone-vancomycin and [¹⁸F]fluorinated vinyl ether) to distinguish bacterial infections from sterile inflammation was evaluated in a murine myositis model. Tracer specificity was assessed by infecting mice either with the Gram-positive bacterium Staphylococcus aureus (n = 12) or the Gram-negative bacterium Escherichia coli (n = 12). The contralateral leg was injected with Cytodex beads to induce sterile inflammation, or with phosphate-buffered saline for control. In parallel, mice were imaged with [¹⁸F]FDG (n = 12). Dynamic positron emission tomography (PET) measurements, biodistribution analyses, and immunohistopathology were performed to determine tracer distribution and bacterial burden.

Results: Both ¹⁸F-vancomycin-PET tracers accumulated at sites of infection, but not at sites of sterile inflammation, in contrast to [¹⁸F]FDG. The tracers exhibited distinct biodistribution profiles, with [¹⁸F]BODIPY-FL-vancomycin being cleared more rapidly. Both ¹⁸F-vancomycin-PET tracers displayed significant target to non-target ratios of 2.95 for [¹⁸F]BODIPY-FL-vancomycin and 1.48 for [¹⁸F]PQ-VE1-vancomycin.

Conclusion: Vancomycin-based PET is a potentially attractive approach to distinguish Gram-positive bacterial infections from sterile inflammation.

Purpose

The role of fibroblast activation protein (FAP)-targeted imaging in systemic vasculitis is currently unclear. We aimed to evaluate the clinical value of fluorine-18-labeled FAP inhibitor 42 ([¹⁸F]FAPI-42) in patients with systemic vasculitis and to compare with [¹⁸F]fluorodeoxyglucose (FDG) imaging.

Methods

Patients with systemic vasculitis who underwent dual-tracer PET/CT([¹⁸F]FDG and [¹⁸F]FAPI) imaging from September 2020 to March 2022 were retrospectively analyzed. Positive lesions are defined as vascular/extravascular lesions with increased tracer uptake above surrounding background, which cannot be attributed to the physiologic biodistribution of the radiotracer. The vascular/extravascular lesion detection rate and semiquantitative values (SUVmax, TBR_blood and TBR_liver) of [¹⁸F]FAPI and [¹⁸F]FDG were compared, and the correlation between the extent and range of tracer uptake and levels of inflammatory markers was investigated.

Results

Thirty patients (13 males and 17 females; mean age, 52.5 ± 17.2 years) with systemic vasculitis were included (17 large vessel vasculitis, 10 anti-neutrophil cytoplasmic antibody-associated vasculitis, 2 Behcet’s disease and 1 polyarteritis nodosa). [¹⁸F]FDG PET/CT had positive findings in 93.3% (28/30) of patients, while [¹⁸F]FAPI PET/CT had positive findings in all patients (100%, P = 0.500). Compared with [¹⁸F]FDG PET/CT, [¹⁸F]FAPI PET/CT detected more lesions (161/168 vs. 145/168, P = 0.005), and more extensive vascular involvement in 60% (18/30) of patients. Although SUVmax did not differ significantly between [¹⁸F]FAPI and [¹⁸F]FDG (median, 5.94 vs. 5.46, P = 0.517), [¹⁸F]FAPI had higher TBR_liver (median, 9.59 vs. 3.15, P < 0.001) and TBR_blood (median, 5.45 vs. 4.20, P = 0.006). The total number of positive lesions in FAPI PET/CT show a moderate correlation with erythrocyte sedimentation rate (r_s =0.478, P = 0.008) and C-reactive protein (r_s =0.486, P = 0.006). After treatment, follow-up FAPI PET/CT of 6 patients showed decreased SUVmax, TBR and number of detected lesions, paralleling the clinical remission.

Conclusion

[¹⁸F]FAPI PET/CT imaging is a promising imaging modality for the diagnosis and therapeutic monitoring of systemic vasculitis.

Purpose

Deep convolutional neural networks (CNN) hold promise for assisting the interpretation of dopamine transporter (DAT)-SPECT. For improved communication of uncertainty to the user it is crucial to reliably discriminate certain from inconclusive cases that might be misclassified by strict application of a predefined decision threshold on the CNN output. This study tested two methods to incorporate existing label uncertainty during the training to improve the utility of the CNN sigmoid output for this task.

Methods

Three datasets were used retrospectively: a “development” dataset (n = 1740) for CNN training, validation and testing, two independent out-of-distribution datasets (n = 640, 645) for testing only. In the development dataset, binary classification based on visual inspection was performed carefully by three well-trained readers. A ResNet-18 architecture was trained for binary classification of DAT-SPECT using either a randomly selected vote (“random vote training”, RVT), the proportion of “reduced” votes ( “average vote training”, AVT) or the majority vote (MVT) across the three readers as reference standard. Balanced accuracy was computed separately for “inconclusive” sigmoid outputs (within a predefined interval around the 0.5 decision threshold) and for “certain” (non-inconclusive) sigmoid outputs.

Results

The proportion of “inconclusive” test cases that had to be accepted to achieve a given balanced accuracy in the “certain” test case was lower with RVT and AVT than with MVT in all datasets (e.g., 1.9% and 1.2% versus 2.8% for 98% balanced accuracy in “certain” test cases from the development dataset). In addition, RVT and AVT resulted in slightly higher balanced accuracy in all test cases independent of their certainty (97.3% and 97.5% versus 97.0% in the development dataset).

Conclusion

Making between-readers-discrepancy known to CNN during the training improves the utility of their sigmoid output to discriminate certain from inconclusive cases that might be misclassified by the CNN when the predefined decision threshold is strictly applied. This does not compromise on overall accuracy.

Purpose

Radiomics has revolutionized clinical research by enabling objective measurements of imaging-derived biomarkers. However, the true potential of radiomics necessitates a comprehensive understanding of the biological basis of extracted features to serve as a clinical decision support. In this work, we propose an end-to-end framework for the in silico simulation of [¹⁸F]FLT PET imaging process in Pancreatic Ductal Adenocarcinoma, accounting for the biological characterization of tissues (including perfusion and fibrosis) on tracer delivery. We thus establish a direct association between radiomics features and the underlying biological properties of tissues.

Methods

We considered 4 immunohistochemically stained Whole Slide Images of pancreatic tissue of one healthy control and three patients with PDAC and/or precursor lesions. From marker-specific images, tissue-depending diffusivity properties were estimated and computational domains were built to simulate the [¹⁸F]FLT spatial-temporal uptake exploiting Partial Differential Equations and Finite Elements Method. Consequently, we simulated the imaging process obtaining surrogated PET images for the considered patients, and we performed image-derived features extraction from PET images to be mapped with biological properties via correlation estimation.

Results

The framework captured the phenotypic differences and generated Time Activity Curves reflecting the underlying tissue composition. Image-derived biomarkers were ranked in view of their association with biological characteristics of the tissue, unveiling their molecular correlative. Moreover, we showed that the proposed pipeline could serve as a digital phantom to optimize the image acquisition for lesion detection.

Conclusions

This innovative framework holds the potential to enhance interpretability and reliability of radiomics, fostering the adoption in personalized nuclear medicine and patient care.