The in vivo processes underlying neural stem cell (NSC) transplantation for ischemic stroke remain unclear, primarily due to the lack of effective in vivo monitoring and evaluation approaches. Therefore, we systematically investigated the in vivo mechanisms of NSC transplantation by positron emission tomography (PET) on a rat model with ischemic stroke. NSCs were generated from human induced pluripotent stem cells (hiPSCs), and their neuronal differentiation potential was assessed in vitro. After transplantation into rats with photothrombotic stroke, neurological function was evaluated using the cylinder test and forelimb placing test. 18F-FDG, 18F-SynVesT-1 and 18F-DPA-714 PET were used to monitor brain metabolism, synaptic density, and glial reactivity in vivo. And correlations among the results of in vivo experiments were analyzed. Neuronal differentiation, maturation and synaptic connection of transplanted NSCs were investigated, while changes of glial reactivity were explored. NSCs derived from hiPSCs exhibited high neuronal differentiation potential in vitro. After NSC transplantation, neurological function of rats with ischemic stroke was recovered, while transplanted NSCs differentiated into neurons and established synaptic connections in the rat brain. In vivo brain metabolism and synaptic density were both restored, revealed by 18F-FDG and 18F-SynVesT-1 PET imaging and highly correlated with behavioral recovery. In vivo glial reactivity was higher at 8 weeks after NSC transplantation in 18F-DPA-714 PET imaging, mainly induced by microglial M2 polarization, which promotes neurological function recovery. Our findings suggest PET molecular imaging can systematically monitor the brain metabolism, synaptic density and glial reactivity, providing effective in vivo monitoring and evaluation approaches for NSC transplantation in ischemic stroke.
Cardiac sympathetic imaging with iodine-labeled metaiodobenzylguanidine (MIBG) is clinically relevant for assessing autonomic dysfunction and arrhythmic risk in heart failure. The development of positron-emitting 124I-MIBG and new-generation PET/CT systems, particularly long axial field-of-view (LAFOV) scanners, may improve image quality and regional defect assessment while enabling protocol optimization. This study compared simulated cardiac 124I-MIBG image quality and lesion detectability across three PET/CT generations, analog standard axial field-of-view (SAFOV), digital SAFOV, and LAFOV, and explored the potential for acquisition-time and activity reduction. An anthropomorphic torso phantom with cardiac insert was prepared to simulate physiologic 124I-MIBG biodistribution. Two configurations were studied: a pathological model with a transmural defect (TD) and a non-transmural defect (NTD), and a normal model with homogeneous myocardial uptake. Acquisitions were performed on three PET/CT systems: analog SAFOV (Biograph mCT), digital SAFOV (Biograph Vision Edge 600), and LAFOV (Biograph Vision Quadra). List-mode data were acquired for 10 min and reconstructed to simulate 1-, 5-, and 10-min acquisitions, yielding nine datasets. Qualitative assessment included lesion detectability and overall image quality scored on 5-point Likert scales by two experienced readers. Quantitative analysis included signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). Exploratory pairwise Wald-type comparisons were performed using propagated measurement uncertainty. LAFOV PET/CT showed the best qualitative and quantitative performance overall. Lesion detectability was highest on LAFOV at all acquisition times, with digital SAFOV intermediate and analog SAFOV lowest. Image quality likewise favored LAFOV, especially at 5 and 10 min. In the pathological phantom, SNR increased from 25.9 to 75.1 on LAFOV, from 18.7 to 41.8 on digital SAFOV, and from 15.5 to 17.1 on analog SAFOV. At 10 min, exploratory uncorrected pairwise comparisons showed nominally higher SNR on LAFOV than on analog SAFOV PET/CT (75.1 vs 17.1, p = 0.028). For the transmural defect, CNR also increased most on LAFOV, with a nominally higher value versus analog SAFOV at 10 min (67.6 vs 14.5, p = 0.044). By contrast, for the low-contrast non-transmural defect, CNR was numerically higher on LAFOV at longer acquisition times, but the absolute inter-scanner differences were smaller and did not reach statistical significance. LAFOV PET/CT provides superior image quality and lesion detectability for simulated cardiac 124I-MIBG imaging and supports shorter acquisitions and potentially lower administered activity. However, the advantage was most pronounced for high-contrast transmural defects, whereas the benefit for low-contrast non-transmural defects was less robust. Reliable detection of subtle partial innervation defects remains challenging and requires dedicated clinical validation.
We aimed to evaluate the diagnostic performance of ¹⁸F-FDG PET/CT-derived radiomics-based machine learning models for differentiating malignant from benign pancreatic lesions, to compare these models with two sequential stages of visual assessment, and to assess whether incorporation of clinician judgement as a model input provides additional diagnostic gain. In this retrospective single-centre study, 853 consecutive patients who underwent ¹⁸F-FDG PET/CT between April 2009 and February 2025 for known or suspected pancreatic lesions were screened, and 466 were included in the final analysis. Final diagnosis was established by histopathology (76.9%) or clinico-radiological follow-up (23.1%). Diagnostic performance was assessed within a five-stage framework consisting of two visual assessment stages and three progressively expanded machine-learning stages. The visual stages comprised first-look assessment based on PET/CT images alone and comprehensive second-look assessment integrating available clinical, laboratory, and multimodal imaging data. The machine-learning stages comprised a hybrid PET + CT radiomics model, an integrated model additionally incorporating clinical, laboratory, semiquantitative PET, and imaging-derived variables, and a human-radiomics synergistic model including the clinician's second-look binary judgement as an input feature. PET-only and CT-only radiomics models were also evaluated as unimodal comparators. Radiomic features were extracted after manual three-dimensional segmentation using 3D Slicer/PyRadiomics, and Random Forest was selected as the final classifier. Of 466 lesions, 336 (72.1%) were malignant and 130 (27.9%) were benign. First-look visual assessment achieved 93.5% sensitivity, 49.2% specificity, and 81.1% accuracy. Comprehensive second-look assessment improved performance to 97.9% sensitivity, 76.9% specificity, and 92.0% accuracy. Among radiomics-based models, the hybrid PET + CT model outperformed unimodal approaches, achieving 91.1% sensitivity, 66.7% specificity, and 86.8% accuracy. The integrated model did not improve overall accuracy beyond the hybrid model. The human-radiomics synergistic model achieved the highest sensitivity (98.7%) and overall accuracy (93.3%), whereas comprehensive second-look assessment retained slightly higher specificity and NPV. ¹⁸F-FDG PET/CT radiomics-based machine learning models improved specificity beyond routine first-look visual PET interpretation, approaching the performance of comprehensive second-look visual assessment without requiring additional clinical data. Incorporation of clinician judgement further increased sensitivity, although comprehensive second-look visual assessment by an experienced reader retained the highest specificity and NPV among all approaches. These findings support a complementary, decision-support role for radiomics-based models alongside, rather than in place of, expert visual assessment.
Conventional ex vivo molecular assessment of nodal specimens lacks three-dimensional (3D) spatial context, making localisation of tracer-avid sentinel nodes (SNs) within large en bloc inguinal lymph node dissection (ILND) specimens challenging. We evaluated the technical feasibility of combining light detection and ranging (LiDAR)-registered freehand SPECT (fhSPECT) with near-infrared (NIR) fluorescence imaging for spatially augmented localisation of hybrid tracer uptake in solitary SNs and SNs residing within ILND specimens. Fourteen patients with penile cancer (25 cN0 groins; 3 cN1 groins) underwent radio- and fluorescence-guided lymph node (LN) surgery following preoperative lymphoscintigraphy and SPECT/CT. Resected specimens underwent conventional ex vivo assessment, followed by LiDAR-registered fhSPECT with co-registered NIR-fluorescence imaging. These 3D models were compared with conventional ex vivo assessments, preoperative imaging, and histopathological outcomes. In total, 40 solitary tracer-avid LNs and 3 ILND specimens underwent ex vivo assessment. LiDAR/fhSPECT localised radioactive hotspots in 38/40 solitary LNs, consistent with conventional gamma probe assessment, while both conventional and LiDAR-registered NIR-fluorescence imaging detected fluorescent signal in all 40 LNs. Among the 3 ILND procedures, preoperative SPECT/CT identified 6 tracer-avid hotspots within the anatomical resection template. Conventional gamma probe and NIR-fluorescence detected only 4 and 5 hotspots, respectively, whereas LiDAR/fhSPECT localised all 6 hotspots in the corresponding resected specimens. Histopathology identified 6 tumour-positive LNs, all of which were hybrid tracer-avid and effectively localised by LiDAR/fhSPECT. LiDAR-registered 3D surface mapping provided anatomical context to radioactive and fluorescent molecular imaging signals, enabling localisation of tracer-avid LNs in complex ex vivo ILND specimens. These findings support the feasibility of spatially augmented localisation of hybrid tracer uptake and warrant validation in larger studies.
Congenital heart disease (CHD) patients are at increased risk of developing infective endocarditis, particularly following placement of prosthetic valves, stents, and vascular conduits. As compared to studies of infective endocarditis in adults, there is limited data on use of FDG PET/CT for evaluation of pediatric CHD patients. The primary aim of this study is to determine the value of FDG PET/CT for detecting infective endocarditis in a cohort of pediatric and young adult patients with complex CHD, with a secondary aim of demonstrating the feasibility of obtaining adequate dietary preparation in these complex patients. Single center retrospective review of patients undergoing 18F-FDG PET/CT for suspected endocarditis between April 2014 and October 2025. Patients were identified in a search of the radiology report database. The accuracy of FDG PET/CT was determined based on a combination of clinical outcomes, surgical findings, microbiology and pathology. 67 patients accounted for the 75 examinations meeting inclusion criteria. Median age was 21 (IQR 15-26) years. The most common underlying diagnosis was Tetralogy of Fallot (n = 27). Implanted devices were present in 62/67 patients; 53/67 patients had more than 1 implanted device. RV/PA conduit (n = 48) and Melody valve (n = 27) were the most common implants. 50 of 75 (67%) examinations were positive by FDG PET/CT criteria. Sensitivity was 95.9%; specificity was 88.5%, with an overall accuracy of 93.3%. 73% of examinations had adequate suppression of myocardial FDG uptake. 18F-FDG PET/CT is sensitive and accurate for detecting infective endocarditis in the CHD population. With proper instruction, adequate dietary preparation can be successfully accomplished in pediatric patients of varying ages and co-morbidities.
This study aimed to synthesise diagnostic evidence comparing a novel myocardial perfusion radiotracer [¹⁸F]flurpiridaz PET with SPECT myocardial perfusion imaging (MPI) in detecting coronary artery disease (CAD). A systematic search to Feb 2026 was conducted in Web of Science, Scopus, PubMed, and the Cochrane Library. Studies comparing [¹⁸F]flurpiridaz PET with SPECT/MPI were screened. Primary outcomes were sensitivity and specificity using invasive coronary angiography as the reference standard. Secondary outcomes included image quality and radiation dose. Out of 558 studies, 28 publications were fully screened, and three trials comparing [¹⁸F]flurpiridaz PET with [⁹⁹ᵐTc]Tc-sestamibi/tetrofosmin SPECT were identified (1476 patients). For ≥ 50% stenosis, pooled sensitivity/specificity were 76% (95% CI 71-81%)/71% (63-78%) for flurpiridaz PET and 61% (53-69%)/76% (60-86%) for SPECT; for ≥ 70% stenosis, values were 87% (77-94%)/63% (52-73%) versus 73% (62-81%)/72% (50-87%), respectively. In patients with BMI ≥30kg/m², sensitivity/specificity were 74% (68-78%)/73% (64-80%) for flurpiridaz PET and 61% (49-72%)/75% (56-88%) for SPECT. In women, sensitivity/specificity were 73% (57-84%)/76% (70-81%) for flurpiridaz PET versus 50% (29-70%)/78% (60-90%) for SPECT. Rest and stress image quality favoured flurpiridaz PET (RR1.29[1.19-1.41] and 1.14[1.11-1.17], both p<0.00001) with superior image quality and lower radiation dose. This first meta-analysis suggests higher sensitivity of [¹⁸F]flurpiridaz PET vs SPECT MPI with significantly lower radiation dose and improved image quality. [¹⁸F]flurpiridaz is especially useful for assessing women and patients with high BMI, given its superior sensitivity and comparable subgroup specificity. However, findings should be interpreted cautiously due to the limited number of studies.
To investigate the sources of variability in Centiloid (CL) calculations, particularly the influence of image reconstruction and reference region selection, and to examine the relationship between baseline CL scores, visual interpretation and subsequent disease progression. 162 aMCI patients who underwent amyloid PET at a single center were retrospectively analyzed. Visual assessment was performed by two nuclear medicine physicians and Centiloid scoring was determined using syngo.MI Neurology Cortical Analysis, using different reference regions (RR) and image reconstruction settings. The CL values were compared against visual interpretation, using a ROC analysis. The value of CL in predicting the onset of Alzheimer's dementia was assessed. The use of the whole cerebellum as RR provided the most robust and consistent CL values across reconstruction methods. The RR was critical in the case of flutemetamol, as CL varied in more than 20 units between pons and whole cerebellum. Visual classifications and CL values showed strong concordance (area under the ROC curve: 0.9786) and the CL cut-off value that maximized agreement with visual reading was 28 CL. During follow-up, 49% of patients progressed to AD dementia and CL-based amyloid positivity was a significant predictor of progression. Standardized CL quantification using the whole cerebellum as RR enhances the reliability of amyloid PET interpretation across tracers and reconstruction settings. CL values strongly correlate with visual assessment and are predictive of clinical progression. These findings suggest the potential utility of CL quantification in both clinical and research settings.
Imaging in heart transplantation is rapidly evolving from a primarily descriptive tool to a central component of predictive, precision-based graft surveillance. This review summarizes current and emerging roles of non-invasive imaging across the continuum of post-transplant care. Starting from the traditional use of imaging modalities such as echocardiography, computed tomography, magnetic resonance, nuclear imaging techniques, the focus is centered on the most recent evidence on the established techniques and the more recent advances, delineating gaps, and future directions towards routine clinical implementation. Overall, the review supports a paradigm shift in which multimodal, quantitative, and AI-enabled "precision imaging" could become integral to tailoring surveillance strategies, guiding therapy, and optimizing long-term outcomes for heart transplant recipients.
Fibroblast activation protein-targeted radionuclide therapy (FAP-TRT) shows promise across multiple cancers, but clinical responses remain variable. Here, we aim to investigate how the presence, abundance, and spatial organisation of FAP-expressing cancer-associated fibroblasts (CAFs) relative to tumour cells influence the efficacy of FAP-TRT, to further optimisation. Spatial heterogeneity of FAP expression and radioligand uptake was assessed in human pancreatic ductal adenocarcinoma (PDAC) tissues using immunofluorescence and autoradiography with [1⁶1 Tb]Tb-FAPI-46. Mechanistic studies were conducted in vitro using PSN-1 tumour cells and FAP-expressing CAFs in 2D cultures and 3D spheroids, including mono- and co-culture systems with defined tumour-to-CAF ratios and spatial configurations. Cellular uptake and nuclear absorbed dose were quantified, and radiobiological effects were evaluated using DNA damage (γH2AX), clonogenic survival, spheroid growth, and cytokine profiling. PDAC tissues exhibited pronounced spatial heterogeneity in FAP expression and radioligand uptake. In vitro, uptake alone did not predict absorbed dose or biological response. In 2D models, [1⁶1 Tb]Tb-FAPI-46 did not significantly reduce clonogenic survival or increase DNA damage response. In 3D spheroids, FAP-TRT induced dose-dependent DNA damage and growth inhibition. Mixed tumour-CAF spheroids showed more uniform DNA damage and stronger growth suppression than layered models. CAF-containing models attenuated tumour-cell DNA damage and growth inhibition compared to models without CAFs (P < 0.001), associated with increased IL-6 and TGF-β secretion. FAP-expressing CAFs have a dual, context-dependent role in FAP-TRT, enhancing tumour irradiation through crossfire while also limiting tumour control potentially through radioligand partitioning towards the stromal compartment and CAF-derived paracrine signalling. These findings identify spatial organisation and CAF radiobiology as key determinants of FAP-TRT efficacy.
Gastric-type endocervical adenocarcinoma (GAS) is an aggressive, non-HPV-associated cervical adenocarcinoma that is often difficult to recognize preoperatively. This study aimed to characterize the integrated PET/CT phenotype of GAS and evaluate whether morphological, metabolic, serological, and explainable machine-learning features could support its differentiation from squamous cell carcinoma (SCC) and usual-type endocervical adenocarcinoma (UEA). This retrospective study included 144 patients with histologically confirmed cervical cancer who underwent pretreatment 18 F-FDG PET/CT, including 22 with GAS, 82 with SCC, and 40 with UEA. Clinical characteristics, serum tumor markers, PET/CT-derived morphological features, metabolic parameters, and dissemination-related variables were collected. Intergroup differences were assessed using appropriate statistical tests. Five machine-learning models were developed for histological differentiation, and model performance was evaluated using ROC analysis, classification metrics, calibration assessment, and decision curve analysis. SHAP analysis was used to interpret feature contributions. GAS demonstrated a distinctive PET/CT phenotype characterized by diffuse infiltrative growth, cystic morphology, intrauterine fluid accumulation, relatively lower FDG uptake, CA19-9 positivity, and more frequent distant and peritoneal metastasis. The median cervical lesion SUVmax was lower in GAS than in SCC and UEA, and similar trends were observed for liver-normalized and blood pool-normalized SUV ratios. Despite its relatively low metabolic activity, GAS showed more aggressive dissemination-related features. Among the machine-learning models, tree-based ensemble models showed better exploratory discriminative performance than Logistic Regression and multilayer perceptron. SHAP analysis indicated that growth pattern, cystic morphology, intrauterine fluid, cervical lesion SUVmax, liver SUV ratio, blood pool ratio, CA19-9, and SCC antigen were the main contributors to model prediction. GAS exhibits a recognizable PET/CT phenotype characterized by a descriptive metabolic-morphological mismatch, namely relatively low primary-tumor FDG uptake despite aggressive infiltrative morphology and metastatic dissemination. Integrated assessment of PET/CT morphology, metabolic parameters, tumor markers, and dissemination patterns may help raise preoperative suspicion of GAS and guide further pathological work-up. Explainable machine learning may serve as a complementary tool for feature integration, but external validation is required before clinical implementation.
Receptor tyrosine kinase-like orphan receptor 1 (ROR1) is an attractive molecular target for anti-tumor therapies undergoing late-stage clinical development. Quantitative imaging of ROR1 expression could enable identification of patients likely to respond to such treatments. This study aimed to assess the feasibility of specific in vivo imaging of ROR1 using radiolabeled affibody molecules. The affibody molecule ZROR1:A10, with high affinity for human (4 nM) and murine (2 nM) ROR1, was labeled with indium-111 using a DOTA chelator. In vitro binding specificity, affinity, and cellular processing were evaluated using a panel of ROR1-expressing cell lines. The affibody [111In]In-DOTA-Zcov19s, which does not bind ROR1, served as a nonspecific control. The biodistribution of [111In]In-DOTA-ZROR1:A10 and [111In]In-DOTA-Zcov19s was measured in immunodeficient mice bearing ROR1-positive tumors, with ROR1-negative Ramos xenografts used as an additional specificity control. [111In]In-DOTA-ZROR1:A10 bound specifically to ROR1-expressing cells, with significantly higher uptake than [111In]In-DOTA-Zcov19s. The apparent equilibrium dissociation constant for ROR1 binding in vitro was 1-4 nM. Tumor uptake of [111In]In-DOTA-ZROR1:A10 in MDA-MB-468 xenografts was saturable and significantly (p < 0.05) higher than in Ramos tumors, as well as higher than uptake of the control affibody. At 4 h post‑injection of 1 µg (50 µg/kg), tumor‑to‑blood, tumor‑to‑bone, and tumor‑to‑muscle ratios were 14 ± 6, 19 ± 6, and 11 ± 1, respectively. Micro-SPECT/CT imaging clearly visualized ROR1‑positive tumors and discriminated them from ROR1‑negative xenografts. The preclinical evaluation shows that visualization of ROR1-expressing tumors using a radiolabeled affibody molecule is feasible.
This study aimed to externally validate the P-Score, a composite scoring system combining PI-RADS and PRIMARY score, for its diagnostic accuracy in detecting clinically significant (ISUP ≥ 2) and higher-grade (ISUP ≥ 3) prostate cancer (PCa). 230 biopsy-naïve men with suspected PCa were prospectively enrolled in the DEPROMP trial and underwent multiparametric MRI and [68Ga]Ga-DKFZ-PSMA-11 PET/CT. Lesions were assessed using PI-RADS v2.1, the PRIMARY score, and the derived P-Score. Targeted biopsies were guided by imaging findings, and histopathology served as the reference standard. Diagnostic performance was evaluated using receiver operating characteristic curve analyses and DeLong's test to compare the area under the curve (AUC) between scoring systems. For clinically significant PCa (ISUP ≥ 2), no significant difference in diagnostic performance was observed between the P-Score (AUC 0.796) and PI-RADS (AUC 0.804; p = 0.72), whereas the P-Score significantly outperformed the PRIMARY score (AUC 0.730; p < 0.001). Similarly, for detection of ISUP ≥ 3 disease, no significant difference in diagnostic performance was observed between the P-Score (AUC 0.840) and PI-RADS (AUC 0.830; p = 0.66). In the PI-RADS 3 subgroup, diagnostic performance remained limited, with AUCs of 0.573 (95% CI: 0.407-0.739) for the P-Score and 0.556 (95% CI: 0.389-0.722) for the PRIMARY score. Overall, the P-Score demonstrated robust diagnostic performance across disease categories and showed comparable accuracy to PI-RADS. The P-Score demonstrated diagnostic performance comparable to PI-RADS in this external validation cohort. While providing a standardized framework integrating anatomical and molecular imaging findings, further studies are warranted to determine whether it has a role in selected clinical scenarios and prospective research settings.
This study evaluated the imaging performance, tumor retention, and therapeutic potential of two new FAPI homodimers, DOTAGA.Glu2.(FAPI)2 and DOTAGA.PEG2.Glu.(FAPI)2, specifically designed to improve FAP-targeted tumor retention. DOTAGA.Glu2.(FAPI)2 and DOTAGA.PEG2.Glu.(FAPI)2 were radiolabeled with gallium-68 and lutetium-177. In vitro studies included lipophilicity, protein binding, saturation binding, internalization and externalization using FAP+ CAFs. In vivo evaluation in PC3-mice comprised biodistribution, metabolic stability, blood and organ clearance, PET/SPECT/CT imaging, and autoradiography. Therapeutic efficacy was assessed using fractionated radioligand therapy with [177Lu]Lu-DOTAGA.Glu2.(FAPI)2, as monotherapy or combined with everolimus. All radioligands showed > 99% radiochemical purity, high FAP affinity (Kd: 0.9-1.5 nM), hydrophilic profiles (LogDoctanol/PBS ≤-3), and low protein binding (< 10%). They exhibited high internalization and low externalization (~ 20% for [177Lu]Lu-DOTAGA.Glu2.(FAPI)2 and ~ 35% for [177Lu]Lu-DOTAGA.PEG2.Glu.(FAPI)2). The 68Ga-labeled radiotracers displayed sustained tumor uptake up to 3 h p.i. (> 14%I.A./g) with increasing tumor-to-organ ratios. For the 177Lu-labeled analogues the initial uptake was comparable (~ 15%I.A./g at 4 h p.i.), with [177Lu]Lu-DOTAGA.Glu2.(FAPI)2, showing even improved retention compared to [177Lu]Lu-DOTAGA.PEG2.Glu.(FAPI)2 (4.2 ± 0.5 vs. 1.2 ± 0.02%I.A./g at 96 h). Blood clearance was rapid and biphasic, with faster kinetics for DOTAGA.Glu2.(FAPI)2. For the same compound, tumor half-life was significantly prolonged (44.5 vs. 19 h), resulting in 2-fold higher tumor exposure (AUC: 971 ± 74 vs. 542 ± 28%I.A.×h/g). Imaging confirmed high tumor-to-background ratios, while autoradiography revealed heterogeneous intratumoral FAP distribution. Fractionated therapy significantly inhibited tumor growth and improved survival, further enhanced by everolimus. DOTAGA.Glu2.(FAPI)2 demonstrates superior tumor retention, favorable pharmacokinetics, and enhanced therapeutic efficacy, supporting its potential for clinical translation.
To evaluate lesion detection patterns and the risk-stratification value of paired 68Ga-PSMA-11 and 18F-FDG PET/CT in patients with post-prostatectomy biochemical recurrence (BCR) and negative conventional imaging, and to explore the hypothesis-generating biological context of dual-tracer phenotypes using public single-cell transcriptomic data. This retrospective single-center study included patients with post-prostatectomy BCR who underwent paired 68Ga-PSMA-11 and 18F-FDG PET/CT within 14 days and had negative conventional imaging within 1 month before PET/CT. Overall dual-tracer PET positivity was defined as at least 1 positive lesion on either tracer. Among patients with PET-detectable disease on either tracer, phenotypes were classified as PSMA+/FDG-, PSMA+/FDG+, or PSMA-/FDG+. Public single-cell RNA sequencing data were analyzed to assess the relationship between FOLH1 expression and glycolytic activity. Among 58 included patients, 21 (36.2%) had at least one positive lesion on either tracer. Overall dual-tracer PET positivity increased across PSA strata and with a greater number of prespecified risk features (both P for trend < 0.001). Older age and higher PSA at PET were independently associated with overall dual-tracer PET positivity. Among patients with PET-detectable disease on either tracer, FDG-avid disease was associated with pathologic stage ≥pT3, pathologic N1 disease, recurrence within 3 years after radical prostatectomy, and PSA doubling time ≤ 6 months. In the public single-cell cohort, FOLH1 expression and glycolytic activity showed only a weak association. Paired 68Ga-PSMA-11 and 18F-FDG PET/CT revealed heterogeneity beyond lesion detection in patients with post-prostatectomy BCR and negative conventional imaging. Among patients with PET-detectable disease on either tracer, FDG-avid disease was enriched for adverse clinicopathologic features, and public single-cell transcriptomic analysis provided hypothesis-generating biological context for divergent dual-tracer phenotypes.
CAR T-cell therapy has changed the management of relapsed/refractory (R/R) Diffuse large B-cell lymphoma (DLBCL). Fluorodeoxyglucose Positron Emission Tomography Computed Tomography (PET/CT) plays a central role in lymphoma response assessment, but its prognostic use remains insufficiently standardized in this setting. Patients from the French DESCAR-T registry treated in third line or beyond with commercial anti-CD19 CAR T-cells in real-life, and having centrally reviewed PET/CT before infusion, and at one month (M1) or three months (M3) post-infusion were included. For each visit, Total Metabolic Tumor Volume (TMTV) and SUVmax were measured. Deauville score (DS) and response according to 2014 Lugano classification were registered on follow-up PET/CT. Optimal TMTV cut-offs at baseline, M1 and M3 follow-up for progression-free survival (PFS) and overall survival (OS) and the prognostic impact of DS at M1 and M3 were determined. A total of 212 R/R DLBCL patients were analysed. Baseline median SUVmax was 16.4 and median TMTV 41.3 cm3. A baseline TMTV cut-off of 30 cm3 significantly stratified patients for PFS and OS, in both univariate and multivariate analysis, along with LDH. Complete metabolic response (DS 1-3) at M1 was significantly associated with better PFS M1 and OS M1 than DS4-5 (for PFS M1: median of 21.8 vs 1.8 vs months; p < 0.0001; for OS M1: median not reached versus median of 6.3 months; p < 0.0001). DS5 identified patients with the worst outcomes (for PFS M1: median of 0.1 month and for OS M1: median of 4.5 months). Similarly, at M3 DS1-3 was associated with a better outcome than DS4-5, and patients with DS5 had the worst outcome. In patients without complete metabolic response residual TMTV provided additional prognostic value. Baseline TMTV and metabolic response assessed by DS, together with residual TMTV on follow-up PET/CT, are strong prognostic biomarkers in R/R DLBCL patients treated with anti-CD19 CAR T-cells.
Radioligand therapy (RLT) delivers radionuclides, such as Lutetium-177 (177Lu), to selectively target cancer cells. Despite the favourable clinical outcomes of 177Lu-based RLT, complete cure remains infrequent. A comprehensive understanding of its mode of action (MoA) is essential for strategic design of novel combination approaches that could improve therapeutic responses. DNA damage response (DDR) markers were profiled by immunofluorescence in cancer cell lines treated with DOTA-chelated 177Lu ([177Lu]Lu-DOTA). Multiple DDR-deficient isogenic cell lines and DDR inhibitors were screened in viability assays with [177Lu]Lu-DOTA to identify sensitizers. 177Lu-RLT combination with an inhibitor of the non-homologous end joining (NHEJ) core factor DNA-PK, and its effect on viability and cell death, were further characterised in vitro and in vivo. [177Lu]Lu-DOTA treatment induced multiple DDR biomarkers indicative of DNA double-strand break (DSB) repair and genomic instability. Viability assays performed with DDR-deficient isogenic models and DDR inhibitors demonstrated that loss of DSB repair through NHEJ elicits the strongest sensitisation to [177Lu]Lu-DOTA. Consistently, DNA-PK inhibition strongly sensitised PSMA-positive prostate cancer cells to [177Lu]Lu-PSMA-617, exacerbated apoptosis and cell cycle arrest and improved efficacy in vivo, demonstrating good tolerability. These results provide novel mechanistic insights into 177Lu-based RLT and pinpoint NHEJ as a key pathway for the repair of 177Lu-induced DNA damage. DNA-PK inhibition strongly sensitises cancer cells to 177Lu-based RLT and results in stronger potentiation compared with other tested DDR inhibitor combinations, warranting the clinical exploration of 177Lu-based RLT and DNA-PK inhibitor (DNA-PKi) combination.
Corticobasal syndrome (CBS) is a clinically defined phenotype with different underlying neuropathological substrates most commonly the 4-repeat tauopathy corticobasal degeneration (CBD). 2-[18F] fluoro-2-deoxy-D-glucose Positron Emission Tomography ([18F]FDG-PET) studies have described regional metabolic abnormalities but detailed subcortical and cerebellar structures involvement is less known and metabolic connectivity remains unexplored. This study combined voxel-based, region-of-interest (ROI) analyses and connectivity approaches to further characterize metabolic alterations and to provide a network-level framework in CBS. Thirty-nine CBS patients underwent [18F]FDG-PET at two sites, with images flipped to align the most affected hemisphere; 99 controls were drawn from a national normative database. Voxel-based SPM method and ROIs analysis were performed. Thirty-six bilateral cortical and subcortical regions of interest were processed to perform interregional correlation and network-based analyses within five functional networks. Pairwise Spearman correlations were computed from normalized regional signals. Group differences were assessed at regional and network levels using Fisher-transformed correlations, Cohen's q, permutation testing (10,000 iterations), and graph-theoretical metrics (node strength, clustering coefficient; threshold ρ > 0.25). CBS patients showed asymmetric hypometabolism predominantly in frontal, parietal, and temporal cortices, caudate and thalamus of the predominantly affected hemisphere, with additional contralateral involvement, notably in the cerebellum and caudate. Metabolic connectivity analyses revealed widespread intra- and inter-network disconnection, particularly involving frontal, parietal, and sensorimotor cortices, and thalamo-cortical pathways, with significant lateralization toward the affected hemisphere. Graph analysis showed decreased cortical node strength with relative increases in subcortical hubs and mixed changes in clustering coefficients, suggesting network reorganization. This first [18F]FDG-PET metabolic connectivity study in CBS demonstrates asymmetric and bilateral regional hypometabolism, widespread and lateralized network disconnection, and subcortical reorganization. These findings reflect both degenerative, functional and compensatory mechanisms and highlight metabolic connectivity as a sensitive marker of network-level alterations in neurodegenerative disease.
The management of treatment-refractory meningioma in patients with previous surgical resection and radiation therapy remains challenging due to the lack of effective systemic treatment options. Therefore, novel therapeutic applications, such as peptide receptor radionuclide therapy (PRRT) targeting somatostatin receptors, may offer a promising therapeutic strategy. We aimed to assess the lesion-based tumour-absorbed dose and efficacy of PRRT with [90Y]Y-DOTATOC in patients with treatment-refractory meningioma. In this study, 10 patients with therapy-refractory meningioma were retrospectively included. All patients received systemic [90Y]Y-DOTATOC therapy following prior surgical resection and radiation therapy. In total, 21 lesions were assessed morphologically by contrast-enhanced MRI and [68Ga]Ga-DOTATOC PET/CT both before and after therapy. All patients underwent dosimetry with [111In]In-DOTATOC prior to [90Y]Y-DOTATOC therapy. Treatment response was evaluated according to RANO bidimensional and volumetric criteria. Overall survival (OS) was defined from the first PRRT cycle until death. The median cumulative activity administered per patient was 3804 MBq (IQR, 3140-4050 MBq), with a median of 3 cycles (range: 1-7). On lesion-based analysis following PRRT, response assessment was available in 19/21 (91.5%) lesions. Among these, tumour stabilisation according to RANO criteria was observed in 7/19 (36.8%) lesions, with a median cumulative tumour-absorbed dose of 52.7 Gy. Morphological tumour progression was noted in 12/19 (63.2%) lesions, with a median cumulative tumour-absorbed dose of 43.8 Gy. The difference in tumour-absorbed doses between morphologically stable and progressive lesions according to RANO criteria was not statistically significant (P = 0.82). Values for SUVmax and SUVmean from pretherapeutic [68Ga]Ga-DOTATOC PET/CT significantly correlated with the tumour-absorbed doses (P = 0.018 for SUVmax, P = 0.021 for SUVmean, respectively). Post-therapeutic [68Ga]Ga-DOTATOC PET/CT demonstrated an increase in SUVmax in 19/21 (90.5%) lesions (median: 40.8%, range: 13.0% - 101.2%). The median OS in the whole cohort was 23.0 months (95% CI 12.5-33.5 months). Our preliminary results indicate no significant difference in tumour-absorbed doses between morphologically stable lesions and those with progressive disease, as defined by the RANO criteria. However, lesion-based analysis revealed a significant correlation between pretherapeutic [68Ga]Ga-DOTATOC PET/CT uptake and tumour-absorbed doses following [90Y]Y-DOTATOC therapy. These findings suggest that baseline PET/CT may serve as a valuable tool for estimating cumulative tumour-absorbed dose and guiding the optimal cumulative activity of PRRT.
To evaluate stage-dependent performance of same-session [18F]FDG PET/contrast-enhanced CT (PET/ceCT) for initial breast cancer staging and PET/ceCT-detected relapse patterns during follow-up. This retrospective single-centre study included a primary staging cohort with one index PET/ceCT per patient and a longitudinal cohort of follow-up/restaging examinations. PET/ceCT-derived endpoints were assessed against clinically adjudicated reference standards established through multidisciplinary team review, pathology when available and follow-up imaging. SUVmax and ceCT lesion diameter were analysed as exploratory biomarkers. The staging cohort included 116 patients. Baseline stage was evaluable in 106 patients: 65 had cN-positive disease, 9 had cT3-4 cN0 disease and 32 had cT1-2 cN0 disease. Overall nodal staging performance showed sensitivity 64.8%, specificity 88.9%, PPV 92.0%, NPV 56.1% and accuracy 72.9%. In cT3-4 and/or cN-positive disease, PET-positive nodal findings had a PPV of 100%. Baseline M-stage assessment was limited by the low number of clinically confirmed M1 cases. SUVmax correlated with Ki-67 (rho = 0.322, p = 0.003, q = 0.022). The longitudinal cohort included 176 patients and 429 examinations. In 311 adjudicated examinations, restaging performance for disease progression showed sensitivity 100%, specificity 93.5%, PPV 97.3%, NPV 100% and accuracy 98.1%. First confirmed relapse was multiorgan/multisystem in 48/82 patients and visceral-only in 15/82; visceral conversion occurred in 5/16 patients with initial bone-only or nodal/locoregional relapse. Same-session [18F]FDG PET/ceCT showed greatest baseline utility in higher-risk breast cancer and was useful for longitudinal characterization of relapse phenotype and metastatic evolution.
Fever of unknown origin (FUO) remains diagnostically challenging because of heterogeneous causes, non-specific clinical manifestations, and overlapping imaging findings. We developed and validated FUO-PETMamba, a PET maximum-intensity-projection (MIP)-based artificial intelligence framework for AI-assisted aetiological classification of FUO. This retrospective multicentre study included 681 patients with FUO who underwent baseline [18 F]FDG PET/CT, comprising one development cohort (n = 355) and two independent external validation cohorts (n = 195 and n = 131). FUO-PETMamba is a weakly supervised framework analysing PET MIP images generated from PET data. Model performance was assessed by discrimination, calibration, decision curve analysis (DCA). Attention-based visual explanations were generated using attention mechanisms and gradient-based activation mapping. A reader study assessed the potential assistive effect of model-predicted probabilities on physicians with different PET/CT experience. In the development cohort, FUO-PETMamba achieved AUCs of 0.838 for malignancy, 0.851 for infection, 0.914 for autoimmune disease, and 0.788 for miscellaneous causes. Corresponding AUCs were 0.809, 0.815, 0.805, and 0.849 in external validation cohort 1, and 0.808, 0.772, 0.701, and 0.927 in external validation cohort 2, respectively. Calibration and decision curve analysis suggested potential clinical benefit for the major aetiological categories, although performance varied across cohorts and classes. The miscellaneous category should be interpreted cautiously because of limited case numbers and low positive predictive value and F1 scores. In the reader study, AI assistance improved diagnostic accuracy for junior and intermediate physicians, whereas changes in senior-physician performance were variable. Post hoc attention-based visualisations highlighted clinically plausible hypermetabolic patterns and served as qualitative explanatory aids. FUO-PETMamba provides a PET MIP-based AI-assisted diagnostic support framework for aetiological classification of FUO across multicentre cohorts and may help reduce experience-dependent diagnostic variability after prospective validation.