Search Results (879)

Background/Objectives: Cardiac sarcoidosis (CS) is an inflammatory cardiomyopathy with a strong clinical impact on patients affected by the disease and a challenging diagnosis. Methods: This comprehensive narrative review evaluates the role of [18F]fluorodesoxyglucose ([18F]FDG) positron emission tomography (PET)-based radiomics and machine learning (ML) analyses in the assessment of CS. Results: The value of [18F]FDG PET-based radiomics and ML has been investigated for the clinical settings of diagnosis and prognosis of patients affected by CS. Even though different radiomics features and ML models have proved their clinical role in these settings in different cohorts, the clear superiority and added value of one of them across different studies has not been demonstrated. In particular, textural analysis and ML showed high diagnostic value for the diagnosis of CS in some papers, but had controversial results in other works, and may potentially provide prognostic information and predict adverse clinical events. When comparing these analyses with the classic semiquantitative evaluation, a conclusion about which method best suits the final objective cannot be drawn with the available references. Different methodological issues are present when comparing different papers, such as image segmentation and feature extraction differences that are more evident. Furthermore, the intrinsic limitations of radiomics analysis and ML need to be overcome with future research developed in multicentric settings with protocol harmonization. Conclusions: [18F]FDG PET-based radiomics and ML show preliminary promising results for CS evaluation, but remain investigational tools since the current evidence is insufficient for clinical adoption due to methodological heterogeneity, small sample sizes, and lack of standardization. Full article

Objective: To evaluate the diagnostic performance of fluorine 18 fluorodeoxyglucose positron emission tomography/magnetic resonance imaging (¹⁸F-FDG PET/MR) in the preoperative staging of hypopharyngeal cancer (HPC), compare it with conventional enhanced computed tomography (CT) and MR, and further explore the prognostic value of its metabolic and diffusion metrics for HPC. Methods: This retrospective study included 33 patients with pathologically confirmed HPC. All patients underwent preoperative ¹⁸F-FDG PET/MR, CT, and MR examination. The staging performance of the three modalities was evaluated using pathological staging as a reference. Additionally, metabolic indicators and diffusion-related parameters from PET/MR were collected to investigate their impact on larynx preservation and survival. Results: PET/MR demonstrated accuracies of 90.9% and 71.4% in the preoperative T and N staging, respectively, significantly higher than those of CT (54.5%, p = 0.001; 42.9%, p = 0.021) and MR (66.7%, p = 0.016; 42.9%, p = 0.021). On the whole, significant differences emerged in the maximum standard uptake value (SUVmax), metabolic tumor volume (MTV), minimum apparent diffusion coefficient (ADCmin), and mean ADC (ADCmean) and combined ratios across different T stages, while SUVmax, mean SUV (SUVmean), total lesion glycolysis (TLG), and MTV varied significantly across different N stages. The ADCmin and ADCmean showed good predictive capability for larynx preservation, with AUCs of 0.857 and 0.920 (p < 0.05), respectively. In Cox multivariate analysis of overall survival, high-level ADCmean (p = 0.004) and low-level TLG/ADCmean (p = 0.022) were significantly associated with better survival. Conclusion: In HPC, ¹⁸F-FDG PET/MR imaging significantly surpasses CT and MR in preoperative diagnostic staging. Its diffusion-related parameters have substantial prognostic value, with high ADC values associated with larynx preservation. ADCmean and TLG/ADCmean are potential prognostic indicators for HPC. Full article

Background: Sclerosing perivascular epithelioid cell tumors (PEComas) are rare mesenchymal neoplasms, typically benign but occasionally exhibiting aggressive behavior. This study reports a case of sclerosing PEComa of the adrenal gland that was treated with robotic partial adrenalectomy, with 13 years of follow-up and a review of the literature. Methods: A 48-year-old woman presented with abdominal pain. Imaging revealed a 10 × 9 cm adrenal mass displacing adjacent structures. MRI and 18F-FDG PET-CT suggested angiomyolipoma. Robotic partial adrenalectomy was performed. Intraoperative frozen section analysis identified the mass as angiomyolipoma, while final histopathology confirmed it as a sclerosing PEComa. Results: This case highlights the advantages of robotic surgery in the management of large adrenal tumors, allowing complete tumor removal while preserving functional adrenal tissue. The extended 13-year follow-up is significant, given the potential for recurrence or malignant transformation reported in other cases. A literature review identified 39 reported cases of sclerosing PEComas, with few documenting long-term outcomes. Conclusions: This is a documented case of robotic partial adrenalectomy for sclerosing PEComa. The findings support robotic surgery as a safe effective approach for managing this rare tumor, with excellent functional and oncological results. Extended follow-up reinforces the tumor’s benign behavior and the importance of long-term monitoring in PEComas. Full article

Background/Objectives: The purpose of this study is to determine the added value of 18F-FDG PET/CT scan in pediatric LCH compared to other imaging modalities (CT and MRI) at initial staging, during assessment of disease reactivation, and after treatment. Methods: This is a retrospective study of children diagnosed with LCH between 1 June 2007 and 8 December 2022 who met the inclusion criteria. 18F-FDG PET CT imaging was compared to CT and/or MRI when available. The interclass correlation coefficient (ICC) was used to assess the agreement between methods. p-Values of less than 0.05 were considered statistically significant. Results: A total of 39 children had undergone 18F-FDG PET/CT studies. Median (range) age at presentation was 10 years (1.3–17 y), with a female-to-male ratio of 0.7:1. Excellent concordance (ICC = 1; p < 0.0001) between 18F-FDG PET/CT and other imaging methods was found. Median SUVmax of the positive FDG-avid lesions at initial staging was 2.7 [range 1.3–16.7]. Conclusions: 18F-FDG PET/CT has been shown to be complementary to diagnostic CT and MRI, with the advantage of demonstrating additional metabolic information at initial staging, during assessment of disease reactivation, and to assess interval changes post therapy. These preliminary findings warrant further investigation. Full article

Fever of unknown origin (FUO) and inflammation of unknown origin (IUO) remain complex diagnostic challenges due to their heterogeneous presentations and broad differential diagnoses. FUO was first described by Petersdorf and Beeson in 1961 and later redefined by Durack and Street, while IUO was introduced more recently by Vanderschueren et al. in 2009. Despite thorough investigations, a significant proportion of patients remain without a clear diagnosis, often resulting in prolonged hospital stays and increased healthcare costs. In recent years, [¹⁸F]FDG PET/CT has emerged as a valuable tool in the diagnostic workup of FUO and IUO, offering both metabolic and anatomical insights in a single scan. This review evaluates the diagnostic utility of [¹⁸F]FDG PET/CT, based on an analysis of 55 studies encompassing 6681 patients. The scan was found to be clinically helpful in 59% of cases, with diagnostic contributions from both true-positive and true-negative findings. Negative scans were frequently associated with spontaneous symptom resolution and fewer unnecessary interventions. However, differences in study design and definitions of diagnostic value make it difficult to compare results across studies. Overall, [¹⁸F]FDG PET/CT has proven to be a useful tool in the evaluation of FUO and IUO, and future research should focus on standardizing how its clinical benefit is measured and directly comparing its effectiveness with conventional imaging in well-designed prospective studies. Full article

Immune checkpoint inhibitors (ICIs) and tyrosine kinase inhibitors (TKIs) have revolutionized cancer therapy, substantially improving survival across a broad range of malignancies. However, these agents are associated with a unique profile of endocrine immune-related adverse events (irAEs), including thyroiditis, hypophysitis, adrenalitis, and pancreatitis, which differ significantly from the toxicities seen with conventional chemotherapy. These complications often arise unpredictably during treatment and may result in irreversible hormone deficiencies requiring lifelong replacement, underscoring the importance of early detection. ¹⁸F-fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT) has emerged as a valuable tool not only for oncologic staging and response assessment but also for detecting metabolic changes in endocrine organs. PET/CT can identify irAEs before the appearance of clinical symptoms or biochemical abnormalities. Emerging evidence suggests that the presence of endocrine irAEs identified by ¹⁸F-FDG PET/CT may correlate with improved treatment response and survival, possibly reflecting enhanced immune activation. This comprehensive review discusses the role of ¹⁸F-FDG PET/CT in the early recognition of therapy-induced endocrine toxicities, facilitating timely intervention through hormone replacement or immunosuppressive therapy while minimizing unnecessary treatment interruptions. Effective integration of metabolic imaging with clinical and laboratory evaluation requires coordinated multidisciplinary collaboration among oncologists, endocrinologists, and nuclear medicine physicians to optimize outcomes and reduce endocrine-related morbidity in the era of precision oncology. Full article

Objectives: Evaluation of the predictive potential of pre-CAR-T [¹⁸F]FDG PET/CT in Diffuse Large B-Cell Lymphoma (DLBCL) patients concerning Cytokine Release Syndrome (CRS) and Immune Effector Cell-associated Neurotoxicity Syndrome (ICANS). Methods: Eighteen DLBCL patients (mean age: 60 ± 12 years) who underwent pre-therapeutic [¹⁸F]FDG-PET/CT and CAR-T cell therapy were retrospectively included. Median follow-up time was ten months (IQR6-16) after CAR-T cell infusion. Age, sex, serum lactate dehydrogenase (LDH), interleukin-6 (IL-6), C-reactive protein (CRP), and modified Endothelial Activation and Stress Index (mEASIX) were obtained. Potential occurrence of CRS/ICANS and the SUV_max were evaluated. Pearson and Spearman correlations, group comparisons (Mann–Whitney U-test) and the odds ratio (OR) were calculated. P values below 0.05 were defined as statistically significant and 95%-confidence intervals (CI) were calculated. Results: Pre-therapeutic SUV_max correlated positively with LDH (r = 0.5; p = 0.02), with the grade of CRS (r = 0.5; p = 0.03) and with the grade of ICANS (r = 0.6; p = 0.01). Appearance of ICANS was significantly correlated with pre-therapeutic SUV_max (p = 0.03; U = 7.0; Z = −2.2). Using ROC analysis and Youden’s index, an SUV_max threshold of 17 (AUC: 0.865; p < 0.01) was defined. Patients exceeding a pre-therapeutic SUV_max of 17 had a significantly higher risk of CRS grade > 1 (OR = 22; CI 2, 314; p = 0.03) and ICANS grade > 1 (OR = 18; CI 1, 271; p = 0.04). Conclusions: Pre-therapeutic SUV_max may be a useful marker for identifying DLBCL patients at risk for CRS and ICANS. Full article

Background/Objectives: Electrochemotherapy (ECT) has emerged as a promising locoregional treatment modality for patients with cutaneous and subcutaneous melanoma metastases. While systemic therapies have improved overall disease control, effective local tumor management remains crucial, particularly in oligometastatic or symptomatic disease. This pilot study investigates the role of metabolic imaging with [¹⁸F]FDG PET/CT to assess tumor metabolism in melanoma patients undergoing ECT, building on prior evidence that PET offers valuable functional information beyond anatomical changes detected by conventional imaging. Methods: This retrospective study included 11 patients with histologically confirmed melanoma and cutaneous or subcutaneous metastases treated with ECT. [¹⁸F]FDG PET/CT scans were performed either before ECT, after ECT, or both. Metabolic response was assessed by measuring the tracer uptake (SUV_max) of the ten hottest lesions. Morphological changes were evaluated using CT. Local progression-free survival was determined. Results: A total of 66 lesions were analyzed. Patients with PET/CT only after ECT showed significantly higher SUV_max and lesion size compared to those imaged before treatment (mean SUV_max: 9.9 ± 11.2 vs. 10.3 ± 5.5; p = 0.034). Progression-free survival differed significantly based on pre-ECT SUV_max values (χ² = 3.90; p = 0.048). Among two patients with follow-up imaging, one showed new lesions on CT with only mild FDG uptake, while the other developed newly FDG-avid metastases after ECT. Conclusions: FDG PET/CT provides valuable information on tumor viability and treatment response in melanoma patients undergoing ECT, demonstrated by significant differences in metabolic activity between lesions imaged before and after treatment. The lack of longitudinal intra-individual imaging limits definitive conclusions about the direct metabolic effects of ECT. Full article

We aimed to establish non-invasive diagnostic models comparable to pathology testing and explore reliable digital imaging biomarkers to classify diffuse large B-cell lymphoma (DLBCL) and invasive ductal carcinoma (IDC). Our study enrolled 386 breast nodules from 279 patients with DLBCL and IDC, which were pathologically confirmed and underwent ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) positron emission tomography/computed tomography (PET/CT) examination. Patients from two centers were separated into internal and external cohorts. Notably, we introduced 2.5D deep learning and machine learning to extract features, develop models, and discover biomarkers. Performances were assessed using the area under curve (AUC) and confusion matrix. Additionally, the Shapley additive explanation (SHAP) and local interpretable model-agnostic explanations (LIME) techniques were employed to interpret the model. On the internal cohort, the optimal model PT_TDC_SVM achieved an accuracy of 0.980 (95% confidence interval (CI): 0.957–0.991) and an AUC of 0.992 (95% CI: 0.946–0.998), surpassing the other models. On the external cohort, the accuracy was 0.975 (95% CI: 0.913–0.993) and the AUC was 0.996 (95% CI: 0.972–0.999). The optimal imaging biomarker PET_LBP-2D_gldm_DependenceEntropy demonstrated an average accuracy of 0.923/0.937 on internal/external testing. Our study presented an innovative automated model for DLBCL and IDC, identifying reliable digital imaging biomarkers with significant potential. Full article

Background/Objectives: Endometrial cancer (EC) is the most common gynecological tumor in developed countries, and presents a wide variety of histological and molecular characteristics that make its treatment increasingly complex. In recent years, advances in molecular imaging, particularly with [¹⁸F]FDG-PET/CT and PET/MRI, have changed clinicians’ management of diagnosis, treatment planning, and prognosis of EC. Methods: In this narrative review, a search was conducted for current evidence on the role of [¹⁸F]FDG-PET/CT and PET/MRI throughout the treatment of EC, focusing on their diagnostic performance, clinical relevance, and prognostic implications. Their use in areas such as initial staging, treatment monitoring, recurrence detection, and individualized risk assessment was also discussed. Results: [¹⁸F]FDG-PET/CT is effective in detecting lymph node and distant metastases, while [¹⁸F]FDG-PET/MRI offers greater accuracy for T and N staging. In addition, [¹⁸F]FDG-PET/CT provides early metabolic indicators of therapeutic response and facilitates differentiation between viable tumors and post-treatment changes. Radiomics-derived parameters have shown promising associations with tumor aggressiveness and lymphovascular invasion and survival, supporting their role as prognostic imaging biomarkers. In addition, the use of non-FDG radiotracers, as well as predictive models based on machine learning, can further refine preoperative stratification and treatment planning in certain subtypes of EC. Conclusions: Molecular imaging enhances the accuracy of TNM staging in EC. The incorporation of molecular imaging biomarkers into daily clinical practice could significantly improve personalized decision-making in EC. However, large prospective studies are needed to confirm their efficacy. Full article

Background: Despite its central role in pediatric pre-surgical evaluation of drug-resistant focal epilepsy, conventional analog ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) PET/CT (aPET) systems often yield modest epileptogenic zone (EZ) detection rates (~50–60%). Silicon photomultiplier–based digital PET/CT (dPET) promises enhanced image quality, but its performance in pediatric epilepsy remains untested. Methods: We retrospectively analyzed 22 children (mean age 11.5 ± 2.6 years) who underwent interictal brain ¹⁸F-FDG PET/CT: 11 on an analog system (Discovery ST, 2018–2019) and 11 on a digital system (Biograph Vision 450, 2020–2021). Three blinded nuclear medicine physicians independently scored EZ localization and image quality (4-point scale); post-surgical histology and ≥1-year clinical follow-up served as reference. Results: The EZ was correctly identified in 8/11 analog scans (72.7%) versus 10/11 digital scans (90.9%). Average image quality was significantly higher with dPET (3.0 ± 0.9 vs. 2.1 ± 0.9; p < 0.05), and inter-reader agreement improved from good (ICC = 0.63) to excellent (ICC = 0.91). Conclusions: Our preliminary findings suggest that dPET enhances image clarity and reader consistency, potentially improving localization accuracy in pediatric epilepsy presurgical workups. Full article

Objective: We evaluated the feasibility of a machine-learning (ML) model based on clinical features and radiomics from [¹⁸F]FDG PET/CT images to differentiate between infected and non-infected intracavitary vascular grafts and endografts (iVGEI). Methods: Three ML models were developed: one based on pre-treatment criteria to diagnose a vascular graft infection (“MAGIC-light features”), another using radiomics features from diagnostic [¹⁸F]FDG-PET scans, and a third combining both datasets. The training set included 92 patients (72 iVGEI-positive, 20 iVGEI-negative), and the external test set included 20 iVGEI-positive and 12 iVGEI-negative patients. The abdominal aorta and iliac arteries in the PET/CT scans were automatically segmented using SEQUOIA and TotalSegmentator and manually adjusted, extracting 96 radiomics features. The best-performing models for the MAGIC-light features and PET-radiomics features were selected from 343 unique models. Most relevant features were combined to test three final models using ROC analysis, accuracy, sensitivity, and specificity. Results: The combined model achieved the highest AUC in the test set (mean ± SD: 0.91 ± 0.02) compared with the MAGIC-light-only model (0.85 ± 0.06) and the PET-radiomics model (0.73 ± 0.03). The combined model also achieved a higher accuracy (0.91 vs. 0.82) than the diagnosis based on all the MAGIC criteria and a comparable sensitivity and specificity (0.70 and 1.00 vs. 0.76 and 0.92, respectively) while providing diagnostic information at the initial presentation. The AUC for the combined model was significantly higher than the PET-radiomics model (p = 0.02 in the bootstrap test), while other comparisons were not statistically significant. Conclusions: This study demonstrated the potential of ML models in supporting diagnostic decision making for iVGEI. A combined model using pre-treatment clinical features and PET-radiomics features showed high diagnostic performance and specificity, potentially reducing overtreatment and enhancing patient outcomes. Full article

Lung cancer is one of the most common cancers and the leading cause of cancer-related death worldwide. Despite advancements, the overall survival rate for lung cancer remains between 10% and 20% in most countries. However, recent progress in diagnostic tools and therapeutic strategies has led to meaningful improvements in survival outcomes, highlighting the growing importance of personalized management based on accurate disease assessment. ¹⁸F-fluorodeoxyglucose positron emission tomography/computed tomography (FDG PET/CT) has become essential in the management of lung cancer, serving as a key imaging modality for initial diagnosis, staging, treatment response assessment, and follow-up evaluation. Recent developments in radiomics and artificial intelligence (AI), including machine learning and deep learning, have revolutionized the analysis of complex imaging data, enhancing the diagnostic and predictive capabilities of FDG PET/CT in lung cancer. However, the limitations of FDG, including its low specificity for malignancy, have driven the development of novel oncologic radiotracers. One such target is fibroblast activation protein (FAP), a type II transmembrane glycoprotein that is overexpressed in activated cancer-associated fibroblasts within the tumor microenvironment of various epithelial cancers. As a result, FAP-targeted radiopharmaceuticals represent a novel theranostic approach, offering the potential to integrate PET imaging with radioligand therapy (RLT). In this review, we provide a comprehensive overview of FDG PET/CT in lung cancer, along with recent advances in AI. Additionally, we discuss FAP-targeted radiopharmaceuticals for PET imaging and their potential application in RLT for the personalized management of lung cancer. Full article

Hydrogen-rich water (HRW) has shown neuroprotective effects in acute brain injury, but its role in chronic radiation-induced brain injury (RIBI) remains unclear. This study investigated the long-term efficacy of HRW in mitigating cognitive impairment and neuronal damage caused by chronic RIBI. Fifty male Sprague Dawley rats were randomly divided into five groups: control, irradiation (IR), IR with memantine, IR with HRW, and IR with combined treatment. All but the control group received 20 Gy whole-brain X-ray irradiation, followed by daily interventions for 60 days. Behavioral assessments, histopathological analyses, oxidative stress measurements, ¹⁸F-FDG PET/CT imaging, transcriptomic sequencing, RT-qPCR, Western blot, and serum ELISA were performed. HRW significantly improved anxiety-like behavior, memory, and learning performance compared to the IR group. Histological results revealed that HRW reduced neuronal swelling, degeneration, and loss and enhanced dendritic spine density and neurogenesis. PET/CT imaging showed increased hippocampal glucose uptake in the IR group, which was alleviated by HRW treatment. Transcriptomic and molecular analyses indicated that HRW modulated key genes and proteins, including CD44, CD74, SPP1, and Wnt1, potentially through the MIF, Wnt, and SPP1 signaling pathways. Serum CD44 levels were also lower in treated rats, suggesting its potential as a biomarker for chronic RIBI. These findings demonstrate that HRW can alleviate chronic RIBI by preserving neuronal structure, reducing inflammation, and enhancing neuroplasticity, supporting its potential as a therapeutic strategy for radiation-induced cognitive impairment. Full article

Background and Purpose: Stratification based on specific image biomarkers applicable in clinical settings could help optimize treatment outcomes for recurrent non-small cell lung cancer patients. For this purpose, we aimed to determine the clinical impact of positive delta changes (any difference above zero > 0) between baseline [¹⁸F]FDG PET/CT metrics before the first treatment course and reirradiation. Material/Methods: Forty-seven patients who underwent thoracic reirradiation with curative intent at our institute between 2013 and 2021 met the inclusion criteria. All patients had histologically verified NSCLC, ECOG (Eastern Cooperative Oncology Group) ≤ 2, and underwent [¹⁸F]FDG PET/CT for initial staging and re-staging before primary radiotherapy and reirradiation, respectively. The time interval between radiation treatments was at least nine months. Quantitative metabolic volume and intensity parameters were measured before first irradiation and before reirradiation, and the difference above zero (>0; delta change) between them was statistically correlated to locoregional control (LRC), progression-free survival (PFS), and overall survival (OS). Results: Patients were followed for a median time of 33 months after reirradiation. The median OS was 21.8 months (95%-CI: 16.3–27.3), the median PFS was 12 months (95%-CI: 6.7–17.3), and the median LRC was 13 months (95%-CI: 9.0–17.0). Multivariate analysis revealed that the delta changes in SULpeak, SUVmax, and SULmax of the lymph nodes significantly impacted OS (SULpeak p = 0.017; SUVmax p = 0.006; SULmax p = 0.006), PFS (SULpeak p = 0.010; SUVmax p = 0.009; SULmax p = 0.009), and LRC (SULpeak p < 0.001; SUVmax p = 0.003; SULmax p = 0.003). Conclusions: Delta changes in SULpeak, SUVmax, and SULmax of the metastatic lymph nodes significantly impacted all clinical endpoints (OS, PFS and LRC) in recurrent NSCLC patients treated with reirradiation. Hence, these imaging biomarkers could be helpful with regard to patient selection in this challenging clinical situation. Full article