Background: Aortic stenosis (AS) induces myocardial remodeling and fibroblast activation, yet modifiable biomarkers capable of capturing active fibrogenesis and predicting post-transcatheter aortic valve implantation (TAVI) recovery are currently scarce. Fibroblast activation protein (FAP)-targeted PET serves as a noninvasive tool to visualize activated fibroblasts in vivo. We evaluated a time-robust, blood-pool-normalized myocardial [68Ga]Ga-FAPI PET imaging biomarker that reflects AS burden and predicts outcomes after TAVI.
Methods: Nineteen patients with severe symptomatic AS underwent [68Ga]Ga-FAPI-04 PET/CT at 60, 70, and 120 min. Using an in-house semi-automatic pipeline, the left ventricular (LV) myocardium was segmented, and regions of elevated fibroblast activity (EFM) were delineated using a blood-pool-anchored, time-point-specific threshold. We quantified myocardial SUVmean, blood-pool SUVmean, and a normalized myocardium-to-blood index, TBR(EFM), and assessed associations with N-terminal pro-brain natriuretic peptide (NT-proBNP) and left-ventricular ejection fraction (LVEF). One-year outcomes (n = 11) were assessed using a predefined composite clinical response.
Results: Blood-pool SUVmean declined from 60 to 120 min, whereas myocardial SUVmean decreased less, yielding stable TBR(EFM) across time points (60/70/120 min: 2.2 ± 0.8, 2.1 ± 0.9, 2.3 ± 0.9; ANOVA p = 0.596). By contrast, myocardial SUVmean fell from 3.8 ± 0.7 (60 min) to 2.1 ± 0.9 (120 min; p < 0.001). TBR(EFM) correlated with NT-proBNP at all time-points (60 min r = 0.65, p = 0.007; 120 min r = 0.72, p = 0.003), whereas SUVmean did not (60 min p = 0.576; 120 min p = 0.109). Baseline TBR(EFM) was significantly lower in one-year responders than non-responders (1.7 ± 0.2 vs. 2.9 ± 0.9; p = 0.013), with separation present at each time point (p < 0.05). Higher baseline TBR(EFM) associated with lower reductions in NT-proBNP at one year (p < 0.05).
Conclusions: Myocardial [68Ga]Ga-FAPI TBR may provide a time-robust index of active fibroblast signaling that relates to myocardial hemodynamic stress and stratifies one-year clinical response after TAVI. A single 60-minute acquisition with TBR quantification may be sufficient for myocardial [68Ga]Ga-FAPI assessment. These hypothesis-generating findings require validation in larger, multicenter cohorts.
Peptide receptor radionuclide therapy (PRRT) has established itself as a pivotal component in the management of advanced, somatostatin receptor (SSTR)-positive neuroendocrine tumours (NETs). The NETTER-1 phase III trial demonstrated that [177Lu]Lu-DOTATATE significantly prolongs progression-free survival (PFS) and improves quality of life in patients with midgut NETs refractory to somatostatin analogues, leading to regulatory approval by both EMA (2017) and FDA (2018). The recent NETTER-2 phase III trial further extended these findings by supporting the first-line use of PRRT in Grade 2 and 3 gastroentero-pancreatic (GEP)-NETs (Ki-67 ≥ 10 ≤ 55%). Beyond standard β-emitting therapy, several developments are reshaping the field: the clinical adoption of SSTR antagonists such as radiolabelled JR-11 and LM3, targeted α-particle-emitting therapies (225Ac, 212Pb, 213Bi) for resistant disease, and rational combination strategies with chemotherapy, DNA-repair inhibitors, and immunotherapy. Parallel innovation in radiopharmaceutical chemistry has yielded new peptide ligands, including cholecystokinin-2 receptor (CCK2R)-targeted compounds such as DOTA-MGS5, which show promise for rare NETs such as medullary thyroid carcinoma (MTC) and small-cell lung cancer (SCLC). This review summarises clinical evidence, translational advances, and future perspectives for PRRT as a cornerstone of precision nuclear oncology. Emphasis is placed on expanding indications, integrating α-emitters, improving safety and dosimetry, and developing novel theragnostic ligands that enable personalised treatment strategies for NETs patients.
Purpose: Accurate diagnosis of hepatocellular carcinoma (HCC) remains a clinical challenge. Glypican-3 (GPC3) is highly expressed in HCC but not in normal liver tissue, making it a promising target for PET-based molecular imaging, which may complement existing approaches for HCC diagnosis. In this study, we developed a new GPC3-targeted immunoPET radiotracer for noninvasive visualization of GPC3 expression and conducted a first-in-human, proof-of-concept evaluation in patients with HCC to assess its clinical feasibility.
Methods: An anti-GPC3 antigen-binding fragment (Fab) was generated under Good Manufacturing Practice conditions and labeled with Gallium-68 (68Ga) to obtain [68Ga]Ga-aGPC3-Fab. In vitro assays, small-animal PET/CT scans, and ex vivo biodistribution experiments were conducted to examine its GPC3 targeting ability. Five patients with radiologically suspected or diagnosed HCC were enrolled in a pilot clinical study and underwent [68Ga]Ga-aGPC3-Fab PET imaging. Radiotracer uptake in tumor and non-tumor tissues was quantitatively analyzed.
Results: [68Ga]Ga-aGPC3-Fab was synthesized with high radiochemical purity and demonstrated strong affinity and efficient internalization in GPC3-positive cells. It enabled clear tumor visualization in both subcutaneous and orthotopic GPC3-positive HCC mouse models. All five patients tolerated the PET procedure well, with no adverse effects. [68Ga]Ga-aGPC3-Fab successfully detected intrahepatic metastases approximately 1 cm in diameter with high imaging contrast, including lesions that missed on magnetic resonance imaging.
Conclusion: [68Ga]Ga-aGPC3-Fab demonstrated a favorable safety profile and enabled effective visualization of GPC3-positive lesions. It may serve as a complementary approach to conventional imaging to improve the diagnostic accuracy of HCC.
Clinical trial registration: ClinicalTrials.gov, NCT06383520. Registered on April 25, 2024 ( https://clinicaltrials.gov/study/NCT06383520 ).
Purpose: SUV4.0-based thresholding is widely used for baseline [¹⁸F]FDG PET-based metabolic tumor volume (MTV) assessment in diffuse large B-cell lymphoma (DLBCL), but its suitability at interim and end-of-treatment (EoT) PET, when residual uptake is heterogeneous and tumor-to-background contrast is lower, is uncertain. We aimed to define a lesion-adaptive decision rule approach for selecting the optimal segmentation method based on lesion-level features and treatment phase and, exploratorily, to compare its performance with ML-based selection models.
Methods: A total of 598 lesions from 33 DLBCL patients (HOVON-84 trial) were segmented at baseline, interim, and EoT [¹⁸F]FDG PET/CT using six semi-automated methods: SUV2.5, SUV4.0, 41%max, A50peak, MV2, and MV3. Segmentation quality was independently rated for each lesion by two observers (scale 1-5; 3 = preferred), with adjudication by a third reviewer. The influence of lesional SUVpeak, tumor-to-background ratio (TBRpeak), background uptake (SUVbg), treatment phase, and location on segmentation quality was assessed. Over six million rule-based combinations of key features were evaluated to derive a lesion-adaptive decision rule for preferred method selection. Exploratorily, ML classifiers were trained and compared with the decision-rule strategy.
Results: Segmentation quality varied across lesions and methods. SUVpeak, TBRpeak, and SUVbg were key predictors of method performance. The final lesion-adaptive rule, applying SUV4.0 if SUVpeak > 8, MV3 if SUVbg > 0.8, and otherwise MV2, achieved a lesion-wise accuracy of 0.82 for preferred method selection, matching the best-performing ML models. Versus SUV4.0 alone (benchmark), the Decision Rule improved lesion-level MTV agreement with the reference (ρ = 0.85 vs. 0.82 vs. best ML ρ = 0.81) and reduced the proportion of lesions with > 10% MTV deviation (46.2% vs. 63.5%; best ML 50.2%). Total-MTV agreements with the reference were uniformly high across all strategies (all ρ ≥ 0.94), with modest gains for the decision rule at interim and EoT PET.
Conclusion: A straightforward decision-rule approach using SUVpeak and SUVbg successfully selects the preferred method for individual DLBCL lesions across treatment phases and matches ML performance with greater simplicity and clinical applicability. Although supervision remains necessary, this approach helps address the current gap in segmentation methodology for interim and EoT PET, where SUV4.0 may not always be appropriate.
Purpose: Prostate-specific membrane antigen (PSMA) PET/CT is recognized as the most accurate imaging modality for staging of patients with intermediate and high-risk prostate cancer (PCa). PSMA PET/CT has also shown potential in the local (T) staging of primary PCa. The purpose of this study was to explore the value of quantitative PSMA PET/CT parameters in addition to the standard visual assessment for local T-stage classification in a large single-center retrospective cohort.
Methods: Sequential intermediate- and high-risk primary PCa patients who underwent staging PSMA PET/CT prior to robot-assisted radical prostatectomy were included. Visual assessment of T-stage (miT-stage) was performed alongside quantitative analysis of PSMA PET/CT parameters, including SUVmax, SUVpeak, tumor volume (PSMA-vol), total lesion PSMA expression (PSMA-TL), and tumor longest capsule contact (LCC). The pathological tumor stage derived from radical prostatectomy specimens served as the reference standard. Univariable and multivariable logistic regression analyses were performed to develop clinical risk models for predicting pT3-stage disease.
Results: A total of 223 evaluable patients with PSMA-positive primary PCa were included. Univariable analyses of individual imaging parameters yielded AUCs of 0.53-0.63 for pT3a, 0.64-0.74 for ≥ pT3b, and 0.59-0.69 for overall ≥ pT3-stage. In multivariable analyses, LCC was the sole independent predictor for pT3a stage; miT-stage, LCC, and PSMA-vol were independent predictors for ≥ pT3b-stage; and LCC together with PSMA-vol were independent predictors for overall ≥ pT3-stage. Clinical risk models incorporating these predictors achieved AUCs of 0.62 for pT3a, 0.79 for ≥ pT3b, and 0.70 for ≥ pT3-stage.
Conclusion: Quantitative parameters derived from PSMA PET/CT scans provide additional diagnostic accuracy for detecting extraprostatic tumor extension, particularly for ≥ pT3b-stage disease, outperforming visual assessment (miT-stage) alone.
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