Li Huo

Introduction: Somatostatin receptor 2 (SSTR2) has important diagnostic and therapeutic implications in neuroendocrine tumors, but studies on its expression and clinical significance in medullary thyroid carcinoma (MTC) remain limited with inconsistent findings. Methods: SSTR2 expression was evaluated in 75 MTC patients using two scoring methods: the percentage of positive tumor cells and the H-score. Its associations with clinicopathological features were then analyzed. These results were derived from both manual assessment by pathologists and validated using an automated digital analysis platform. Results: Of 75 cases, 61.3% (46) were SSTR2-positive (>5% positive cells), with a median manual H-score of 0.15 (range 0–2.7). A higher manual H-score was associated with octreotide scintigraphy positivity (P = 0.019). Within SSTR2-positive cases, lymph node metastasis decreased from low to high expression (80.0% vs. 73.3% vs. 27.3%, P = 0.015), and the median manual H-score was lower in high-grade than in low-grade tumors (0.00 vs. 0.25, P = 0.010). In univariate analysis, patients with non-high SSTR2 expression (≤50% positive cells) had higher odds of elevated calcitonin at final follow-up (OR 4.17, P = 0.047). Digital and manual assessments showed directionally consistent clinicopathological associations, and the digital H-score correlated strongly with the manual H-score (Spearman ρ = 0.778, P < 0.001). Conclusion: SSTR2 expression in MTC varies widely between patients. High SSTR2 expression appears associated with reduced tumor aggressiveness and a higher likelihood of biochemical cure.

The comprehensive knowledge of how the distinct physical decay characteristics of each radionuclide shape their image quality performance is essential for

This study aims to investigate the prevalence, pattern, physiological basis, and influencing factors of sympathetic ganglia uptake on [¹⁸F]AlF-NOTA-LM3 PET/CT. [¹⁸F]AlF-NOTA-LM3 PET/CT images from 101 patients were retrospectively reviewed to evaluate the presence of sympathetic ganglia uptake. Clinical data and normal-organ uptake were investigated to identify influencing factors. Uptake patterns were compared between sympathetic ganglia and metastatic lymph nodes. Immunohistochemical (IHC) staining for SSTR2 was performed on a stellate ganglion and other specimens. Positive sympathetic ganglia were observed in 76.2% (77/101) of patients on [¹⁸F]AlF-NOTA-LM3 PET/CT. 76.2% (77/101), 33.7% (34/101), 23.8% (24/101), 32.7% (33/101) of patients exhibited positive stellate, thoracic, celiac, and sacral ganglia, respectively. Sympathetic ganglia uptake was associated with higher pituitary, adrenal gland, small-intestinal uptake, and lower tumor burden. Sympathetic ganglia generally exhibited a bilateral symmetric distribution and significantly lower uptake than lymph node metastases (SUVmax: 2.29 ± 0.67 vs. 14.52 ± 14.29; P < 0.001). An SUVmax cutoff of 3.45 differentiated sympathetic ganglia from metastatic lymph nodes with an accuracy of 95.9% and an AUC of 0.967. IHC revealed moderate SSTR2 expression in the membrane and cytoplasm of a subset of stellate ganglionic neurons and in neurons of both the myenteric and submucosal plexuses of duodenum. Sympathetic ganglia uptake on SSTR PET/CT is a common physiological finding, featured by symmetric distribution and faint uptake. Histopathology confirming SSTR2-positive ganglionic neurons provides the biological basis for this uptake.

To evaluate the comparative prognostic utility of next‐generation flow cytometry (NGF) and dual‐tracer PET/CT in measuring minimal residual disease (MRD), this prospective real‐world study enrolled 118 newly diagnosed multiple myeloma (NDMM) patients. Patients underwent post‐treatment assessment using NGF (sensitivity 10 ⁻⁵ ) and dual‐tracer PET/CT using ¹¹ C‐acetate (AC‐PET) and ¹⁸ F‐FDG. While AC‐PET showed a numerically higher detection rate compared to FDG‐PET in paired analyses ( n = 45), a significant discordance was observed between imaging and immunophenotypic assessment. NGF detected MRD in 38.2% of paired cases compared to 11.8% by AC‐PET; however, AC‐PET uniquely identified metabolic activity in extramedullary sites for two NGF‐negative patients, highlighting the value of functional imaging in resolving spatial heterogeneity. In the landmark survival analysis ( n = 104), NGF positivity was identified as a robust independent predictor for inferior progression‐free survival (HR 2.21, 95% CI 1.01–4.81; p = 0.046) and overall survival (HR 4.97, 95% CI 1.23–20.01; p = 0.026), transcending baseline risk stratifications. Furthermore, longitudinal monitoring revealed that patients achieving sustained MRD negativity experienced significantly superior outcomes compared to those with transient negativity or persistent disease. These findings establish NGF as the standard prognostic biomarker for MM, while AC‐PET serves as a critical complementary tool for detecting extramedullary escape, supporting a risk‐adapted MRD strategy that integrates molecular depth with metabolic imaging.

Fibroblast activation plays a key role in plaque instability and coronary artery disease (CAD) progression. In-stent restenosis (ISR) remains a major complication after percutaneous coronary intervention (PCI), increasing the risk of major adverse cardiovascular events (MACEs). This study primarily aimed to investigate whether coronary [¹⁸F]AlF-NOTA-FAPI-04 uptake is associated with major adverse cardiovascular events (MACEs) in symptomatic post-PCI patients, and secondarily to explore its ability to differentiate ISR from in-stent non-restenosis (ISnR) and to evaluate longitudinal changes under lipid-lowering therapy. In this prospective single-centre observational cohort study, we enrolled symptomatic CAD patients with a history of PCI A total of 76 symptomatic CAD patients (30 with acute coronary syndrome [ACS] and 46 with stable coronary syndrome [SCS]) underwent FAPI PET/CT imaging. Twenty-two non-CVD individuals served as controls. Coronary SUV_max and TBR were measured. The primary endpoint was the occurrence of MACEs, while the secondary endpoint was changes in FAPI uptake on follow-up PET/CT. The effects of Lipid-lowering therapy(LLT) on coronary FAPI uptake were also evaluated. FAPI uptake was significantly higher in ACS (SUV_max: 4.06 ± 1.81, TBR: 4.51 ± 2.20) than in SCS (SUV_max: 2.47 ± 1.82, TBR: 2.89 ± 2.23, P < 0.05). ISR plaques exhibited markedly elevated FAPI uptake (SUV_max: 4.06 ± 1.91, TBR: 4.69 ± 2.25) compared to ISnR plaques (SUV_max: 1.69 ± 0.72, TBR: 1.88 ± 0.91, P < 0.0001). Exploratory analyses suggested a trend toward higher MACE risk with elevated uptake, but survival differences were not significant. FAPI PET/CT enables non-invasive assessment of fibroblast-driven plaque activity, particularly in ISR, and identifies high-risk coronary plaques linked to MACEs. While LLT did not significantly modify fibroblast activity in the short term, further studies are needed to explore its long-term effects on plaque stability. (FAPI-PLAQUE Study, NCT06280287).

Distinguishing indolent from clinically significant prostate cancer (csPCa) in biopsy-naïve men remains a diagnostic challenge, often leading to unnecessary biopsies. This study aimed to develop and externally validate an interpretable multimodal model integrating ¹⁸F-PSMA PET/CT, mpMRI, and clinical variables to predict csPCa and optimize biopsy decision-making. This multicenter retrospective study analyzed 302 biopsy-naïve patients derived from a prospective multicenter cohort. Radiomic features were extracted from ¹⁸F-PSMA PET and mpMRI. A dual-level region-of-interest (ROI) strategy was used to capture lesion and whole-gland features. To prevent overfitting, the optimal radiomics signature was derived from the intersection of four machine learning (ML) selection algorithms, while clinical features were selected via logistic regression. Eight ML models were trained and tested with ten-fold cross-validation. A Fusion model, combining radiomics and clinical variables, was evaluated against clinical and single-modality models using AUC, decision curve analysis (DCA), and clinical impact curves (CIC). Additionally, SHapley Additive exPlanations (SHAP) values elucidated feature contributions. The Fusion model demonstrated robust diagnostic efficacy, achieving AUCs of 0.92 in both the internal (95% CI: 0.85-0.97) and external (95% CI: 0.83-0.99) validation cohorts. In the PI-RADS 3 subgroup, the model outperformed standard clinical assessments, yielding an excellent AUC of 0.97 (sensitivity 95.0%, specificity 86.5%). Clinically, risk stratification utilizing the Fusion model could avoid 82.9%, 75.0%, and 72.2% of unnecessary biopsies across the three cohorts, while maintaining low missed-diagnosis rates of 4.0%, 9.5%, and 6.1%, respectively. Furthermore, SHAP analysis identified PET-derived intensity and textural features as the dominant predictors, underscoring the indispensable added value of ¹⁸F-PSMA PET. This interpretable Fusion model integrating ¹⁸F-PSMA PET/CT and mpMRI demonstrated superior diagnostic performance for csPCa compared to standard clinical assessment. This approach shows potential as an effective non-invasive triage tool to support biopsy decision-making, with the potential to reduce unnecessary biopsies while maintaining oncological safety.

To investigate the diagnostic value of PET/MR fusion images for the noninvasive prediction of IDH status using various fusion strategies. This retrospective study involved 45 patients with histopathologically confirmed gliomas who underwent preoperative integrated 18F-FET PET/MR from May 2023 to August 2024. Image fusion was performed by combining PET and the IVIM-derived α map using three commonly used fusion algorithms: discrete wavelet transform (DWT), Laplacian pyramid (LP), and ratio-of-low-pass pyramid (RP). PET parameters and first-order histogram features were extracted from 18F-FET PET, IVIM α map, and fused images. A support vector machine (SVM) classifier with a radial basis function (RBF) kernel was used for classification. Model performance was evaluated through stratified cross-validation, with the area under the receiver operating characteristic curve (AUC) as the main metric. All three fusion-based models outperformed single-modality models and the combined model baseline. Specifically, the LP-based fusion model showed an improved AUC of 0.790 (95% CI: 0.783-0.798); the RP-based fusion model achieved the highest AUC of 0.820 (95% CI: 0.813-0.828); and the DWT-based fusion model reached an AUC of 0.814 (95% CI: 0.806-0.821), with the highest sensitivity at 0.747. Additionally, the parameter analyses demonstrated that the fusion performance was highly sensitive to the weighting strategy across frequency bands. Optimized fusion weights are critical to realize the full benefit of PET/MR image fusion. Integrated ¹⁸F-FET PET/MR image fusion offers a promising alternative to traditional multimodal analysis. Its application in individualized treatment and precision medicine is highly promising.