18F-FDG Positron Emission Tomography Research Articles

Standardized Ketogenic Dietary Preparation for Metabolic PET Imaging in Suspected and Known Cardiac Sarcoidosis

Abstract Aims A major limitation of cardiac positron emission tomography (PET) with F18-fluorodeoxyglucose (F18-FDG) for the evaluation of cardiac sarcoidosis (CS) is associated with physiologic myocardial glucose uptake. The optimal dietary protocol to suppress physiologic myocardial F18-FDG uptake is not well-established. We aimed to evaluate the diagnostic performance of a novel dietary preparation using a ketone-based infant formula. Methods and Results Between 2018 and 2021, consecutive studies using a ketogenic dietary preparation were identified (n=198). The rate of non-diagnostic studies due to failure to suppress myocardial glucose was 7.1% (n= 14) with a similar incidence in diabetics (n= 6, 8.1%). Among studies reported to have no inflammation (N= 137), 130 studies (66%) had mean myocardial SUV less than or equal to mean blood pool SUV. Conclusion Patient preparation with a ketone-based infant formula resulted in low rate of inappropriate myocardial glucose suppression in patients undergoing F18-FDG cardiac PET to evaluate cardiac sarcoidosis.

Abstract PS05-01: Accuracy and safety of fibroblast activation protein inhibitor (FAPI) PET/CT in diagnosis of axillary lymph node metastasis in early breast cancer patients: a prospective cohort study (PFB-01&02 study)

Abstract Background Axillary lymph node (ALN) is the most common metastatic site of breast cancer (BC) and the status of ALN determines the staging, treatment and prognosis for BC patients. Traditional imaging techniques, including ultrasound (US), mammography, MRI, and 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET) were still unsatisfactory to evaluate the status of ALN non-invasively. Fibroblast activation protein (FAP) is highly expressed in cancer-associated fibroblasts and FAP inhibitor (FAPI) PET has been found quite promising in BC. Well-designed prospective large cohort study concerning the diagnostic performance and safety profile of FAPI PET/CT in detection of ALN metastasis of BC is still lacking. Furthermore, FAPI could be radio-labeled with different radio-nuclides including 68Ga and 18F, and there is yet no data concerning the 18F-labeled FAPI in BC. In this study, we investigated the accuracy of FAPI (both 68Ga-FAPI-04 and Al18F-FAPI-04) PET/CT in newly diagnosed BC patients for assessing ALN metastasis. We also compared the diagnostic performance of FAPI PET/CT with that of 18F-FDG PET/CT and US. Methods This prospective study was approved by the Peking Union Medical College Hospital Ethics Committee and was registered online at NIH ClinicalTrials.gov (NCT05574907, NCT05574920). The inclusion criteria were as follows: (1) age 18-80 years old; (2) newly diagnosed BC confirmed by biopsy or with BI-RADS category 4C or 5 lesions by US. The exclusion criteria were as follows: (1) pregnancy or lactation; (2) patients unwilling to undergo PET/CT scans. All patients received biopsy or surgery on breast lesion and ALN. Patients received FAPI and 18F-FDG PET/CT after enrollment. The safety profile of FAPI PET was monitored after injection using the Common Terminology Criteria for Adverse Events. Two experienced nuclear medicine physicians, who were blinded to the pathological diagnosis and other imaging results, assessed the PET/CT images. It was defined as visually positive if the radioactive uptake of the ALN was higher than that of the adjacent normal tissue. The sensitivity, specificity, accuracy, positive predictive value (PPV), and negative predictive value (NPV) were calculated for each diagnostic test. The McNemar test was applied to compare the differences of sensitivity and specificity between FAPI PET/CT, 18F-FDG PET/CT, and US. All statistical tests were performed two-sided, and P< 0.05 was considered statistically significant. Results In total, 113 patients (27-79 years old, median age 66) were enrolled. 53 patients underwent 68Ga-FAPI-04 PET/CT, and the other 60 patients underwent Al18F-FAPI-04 PET/CT. All patients underwent 18F-FDG PET/CT and US. A total of 53/113 (46.9%) patients were finally diagnosed with ALN metastasis. The sensitivity, specificity, accuracy, PPV, and NPV were 90.6%, 90.0%, 90.3%, 88.9%, and 91.5% for FAPI PET/CT, 84.9%, 73.3%, 78.8%, 73.8%, and 84.6% for 18F-FDG PET/CT, 83.0%, 76.7%, 79.6%, 75.9%, and 83.6% for US, respectively (Table 1). The specificity of FAPI PET/CT was significantly higher than that of 18F-FDG PET/CT (P < 0.05) and US (P < 0.05). The sensitivity of FAPI PET/CT was higher than that of 18F-FDG PET/CT (P= 0.45) and US (P= 0.29). There was no significant difference of sensitivity and specificity between 18F-FDG PET/CT and US (P > 0.05). The sensitivity, specificity, accuracy, PPV, and NPV were 92.0%, 92.9%, 92.5%, 92.0%, and 92.9% for 68Ga-FAPI-04 PET/CT, and 89.3%, 87.5%, 88.3%, 86.2%, and 90.3% for Al18F-FAPI-04 PET/CT, respectively (Table 2). The 68Ga-FAPI-04 PET/CT and Al18F-FAPI-04 PET/CT procedures were well tolerated in all patients. The only adverse event was injection pain in 12/53 (22.6%) patients injected with 68Ga-FAPI-04, and 7/69 (10.1%) patients injected with Al18F-FAPI-04, which might relate to the ethanol in the imaging agent. Conclusion The FAPI PET/CT outperformed 18F-FDG PET/CT and US in the diagnosis of ALN metastasis among early breast cancer patients. The 68Ga-FAPI-04 and Al18F-FAPI-04 PET/CT have similar diagnostic performance. The FAPI PET/CT procedures were well tolerated in all patients. Table 1 Diagnostic performance of FAPI PET/CT, 18F-FDG PET/CT, and ultrasound in the diagnosis of ALN metastasis Table 2 Diagnostic performance of 68Ga-FAPI-04 and Al18F-FAPI-04 PET/CT in diagnosis of ALN metastasis Citation Format: Bo Pan, Zhixin Hao, Chao Ren, Lifan Zhang, Yidong Zhou, Qiang Sun, Li Huo. Accuracy and safety of fibroblast activation protein inhibitor (FAPI) PET/CT in diagnosis of axillary lymph node metastasis in early breast cancer patients: a prospective cohort study (PFB-01&02 study) [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PS05-01.

Vision transformer to differentiate between benign and malignant slices in 18F-FDG PET/CT

Fluorine-18-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET)/computed tomography (CT) is widely used for the detection, diagnosis, and clinical decision-making in oncological diseases. However, in daily medical practice, it is often difficult to make clinical decisions because of physiological FDG uptake or cancers with poor FDG uptake. False negative clinical diagnoses of malignant lesions are critical issues that require attention. In this study, Vision Transformer (ViT) was used to automatically classify 18F-FDG PET/CT slices as benign or malignant. This retrospective study included 18F-FDG PET/CT data of 207 (143 malignant and 64 benign) patients from a medical institute to train and test our models. The ViT model achieved an area under the receiver operating characteristic curve (AUC) of 0.90 [95% CI 0.89, 0.91], which was superior to the baseline Convolutional Neural Network (CNN) models (EfficientNet, 0.87 [95% CI 0.86, 0.88], P < 0.001; DenseNet, 0.87 [95% CI 0.86, 0.88], P < 0.001). Even when FDG uptake was low, ViT produced an AUC of 0.81 [95% CI 0.77, 0.85], which was higher than that of the CNN (DenseNet, 0.65 [95% CI 0.59, 0.70], P < 0.001). We demonstrated the clinical value of ViT by showing its sensitive analysis of easy-to-miss cases of oncological diseases.

Predictive value of CT and 18F-FDG PET/CT features on spread through air space in lung adenocarcinoma

BackgroundLung adenocarcinoma, a leading cause of cancer-related mortality, demands precise prognostic indicators for effective management. The presence of spread through air space (STAS) indicates adverse tumor behavior. However, comparative differences between 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography(PET)/computed tomography(CT) and CT in predicting STAS in lung adenocarcinoma remain inadequately explored. This retrospective study analyzes preoperative CT and 18F-FDG PET/CT features to predict STAS, aiming to identify key predictive factors and enhance clinical decision-making.MethodsBetween February 2022 and April 2023, 100 patients (108 lesions) who underwent surgery for clinical lung adenocarcinoma were enrolled. All these patients underwent 18F-FDG PET/CT, thin-section chest CT scan, and pathological biopsy. Univariate and multivariate logistic regression was used to analyze CT and 18F-FDG PET/CT image characteristics. Receiver operating characteristic curve analysis was performed to identify a cut-off value.ResultsSixty lesions were positive for STAS, and 48 lesions were negative for STAS. The STAS-positive was frequently observed in acinar predominant. However, STAS-negative was frequently observed in minimally invasive adenocarcinoma. Univariable analysis results revealed that CT features (including nodule type, maximum tumor diameter, maximum solid component diameter, consolidation tumor ratio, pleural indentation, lobulation, spiculation) and all 18F-FDG PET/CT characteristics were statistically significant difference in STAS-positive and STAS-negative lesions. And multivariate logistic regression results showed that the maximum tumor diameter and SUVmax were the independent influencing factors of CT and 18F-FDG PET/CT in STAS, respectively. The area under the curve of maximum tumor diameter and SUVmax was 0.68 vs. 0.82. The cut-off value for maximum tumor diameter and SUVmax was 2.35 vs. 5.05 with a sensitivity of 50.0% vs. 68.3% and specificity of 81.2% vs. 87.5%, which showed that SUVmax was superior to the maximum tumor diameter.ConclusionThe radiological features of SUVmax is the best model for predicting STAS in lung adenocarcinoma. These radiological features could predict STAS with excellent specificity but inferior sensitivity.

End-of-treatment 18[F]-FDG PET can predict early progression in patients receiving bendamustine-rituximab for follicular lymphoma in first relapse: a prospective West Japan hematology Study Group (W-JHS) NHL01 trial.

Response determined by 18[F]-fluoro-2-deoxy-D-glucose (18F-FDG) positron emission tomography (PET)-CT after induction therapy can predict progression-free survival (PFS) in follicular lymphoma (FL). However, little prospective research has examined the significance of PET after second-line therapy. We conducted a prospective multicenter phase II trial (W-JHS NHL01) of bendamustine plus rituximab (BR) without rituximab maintenance for FL in first relapse. This study aimed to evaluate the usefulness of end-of-treatment (EOT)-PET for predicting PFS in FL patients in first relapse. EOT-PET examinations were performed between 6 and 8weeks from the start of the last BR cycle. The primary endpoint was 1-year PFS. Key secondary endpoints were overall response rate (ORR), complete response rate (CRR), and 1-year overall survival (OS). Seventy-five patients were enrolled, and 8 were excluded from analysis. ORR was 86.6% and CRR was 59.7%. One-year PFS was 88.9% (95% confidence interval [CI] 80.7-94.3%) and 1-year OS in 75 patients was 97.3% (95% CI 89.6-99.3%). One-year PFS was significantly inferior in EOT-PET-positive patients (n = 9) compared with PET-negative patients (n = 58) (77.8% vs. 93.1%; p = 0.02). We confirmed that EOT-PET after second-line BR therapy could predict early progression in FL patients in first relapse.

Regional pulmonary perfusion, blood volume, and their relationship change in experimental early ARDS

Regional pulmonary perfusion (Q) has been investigated using blood volume (Fb) imaging as an easier-to-measure surrogate. However, it is unclear if changing pulmonary conditions could affect their relationship. We hypothesized that vascular changes in early acute respiratory distress syndrome (ARDS) affect Q and Fb differently. Five sheep were anesthetized and received lung protective mechanical ventilation for 20 h while endotoxin was continuously infused. Using dynamic 18F-FDG and 13NN Positron Emission Tomography (PET), regional Fb and Q were analysed in 30 regions of interest (ROIs) and normalized by tissue content (Fbn and Qn, respectively). After 20 h, the lung injury showed characteristics of early ARDS, including gas exchange and lung mechanics. PET images of Fbn and Qn showed substantial differences between baseline and lung injury. Lung injury caused a significant change in the Fbn-Qn relationship compared to baseline (p < 0.001). The best models at baseline and lung injury were Fbn = 0.32 + 0.690Qn and Fbn = 1.684Qn–0.538Qn2, respectively. Endotoxine-associated early ARDS changed the relationship between Fb and Q, shifting from linear to curvilinear. Effects of endotoxin exposure on the vasoactive blood flow regulation were most likely the key factor for this change limiting the quantitative accuracy of Fb imaging as a surrogate for regional Q.

Detection of HER2 expression using 99mTc-NM-02 nanobody in patients with breast cancer: a non-randomized, non-blinded clinical trial

Background99mTc radiolabeled nanobody NM-02 (99mTc-NM-02) is a novel single photon emission computed tomography (SPECT) probe with a high affinity and specificity for human epidermal growth factor receptor 2 (HER2). In this study, a clinical imaging trial was conducted to investigate the relationship between 99mTc-NM-02 uptake and HER2 expression in patients with breast cancer.MethodsThirty patients with pathologically confirmed breast cancer were recruited and imaged with both 99mTc-NM-02 SPECT/computed tomography (CT) and 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET)/CT. According to the treatment conditions before recruitment, patients were divided into two groups, the newly diagnosed group (n = 24) and the treated group (n = 6). The maximal standard uptake value (SUVmax) of 18F-FDG and SUVmax and mean SUV (SUVmean) of 99mTc-NM-02 in the lesions were determined to analyze the relationship with HER2 expression.ResultsNo meaningful relationship was observed between 18F-FDG uptake and HER2 expression in 30 patients with breast cancer. 99mTc-NM-02 uptake was positively correlated with HER2 expression in the newly diagnosed group, but no correlation was observed in the treated group. 99mTc-NM-02 uptake in HER2-positive lesions was lower in those with effective HER2-targeted therapy compared with the newly diagnosed group. 99mTc-NM-02 SPECT/CT detected brain and bone metastases of breast cancer with a different imaging pattern from 18F-FDG PET/CT. 99mTc-NM-02 showed no non-specific uptake in inflamed tissues and revealed intra- and intertumoral HER2 heterogeneity by SPECT/CT imaging in 9 of the 30 patients with breast cancer.Conclusions99mTc-NM-02 SPECT/CT has the potential for visualizing whole-body HER2 overexpression in untreated patients, making it a promising method for HER2 assessment in patients with breast cancer.Trial registrationNCT04674722, Date of registration: December 19, 2020.

Clinical feasibility study of early 30-minute dynamic FDG-PET scanning protocol for patients with lung lesions

PurposeThis study aimed to evaluate the clinical feasibility of early 30-minute dynamic 2-deoxy-2-[18F]fluoro-D-glucose (18F-FDG) positron emission tomography (PET) scanning protocol for patients with lung lesions in comparison to the standard 65-minute dynamic FDG-PET scanning as a reference.MethodsDynamic 18F-FDG PET images of 146 patients with 181 lung lesions (including 146 lesions confirmed by histology) were analyzed in this prospective study. Dynamic images were reconstructed into 28 frames with a specific temporal division protocol for the scan data acquired 65 min post-injection. Ki images and quantitative parameters Ki based on two different acquisition durations [the first 30 min (Ki-30 min) and 65 min (Ki-65 min)] were obtained by applying the irreversible two-tissue compartment model using in-house Matlab software. The two acquisition durations were compared for Ki image quality (including visual score analysis and number of lesions detected) and Ki value (including accuracy of Ki, the value of differential diagnosis of lung lesions and prediction of PD-L1 status) by Wilcoxon’s rank sum test, Spearman’s rank correlation analysis, receiver operating characteristic (ROC) curve, and the DeLong test. The significant testing level (alpha) was set to 0.05.ResultsThe quality of the Ki-30 min images was not significantly different from the Ki-65 min images based on visual score analysis (P > 0.05). In terms of Ki value, among 181 lesions, Ki-65 min was statistically higher than Ki-30 min (0.027 ± 0.017 ml/g/min vs. 0.026 ± 0.018 ml/g/min, P < 0.05), while a very high correlation was obtained between Ki-65 min and Ki-30 min (r = 0.977, P < 0.05). In the differential diagnosis of lung lesions, ROC analysis was performed on 146 histologically confirmed lesions, the area under the curve (AUC) of Ki-65 min, Ki-30 min, and SUVmax was 0.816, 0.816, and 0.709, respectively. According to the Delong test, no significant differences in the diagnostic accuracies were found between Ki-65 min and Ki-30 min (P > 0.05), while the diagnostic accuracies of Ki-65 min and Ki-30 min were both significantly higher than that of SUVmax (P < 0.05). In 73 (NSCLC) lesions with definite PD-L1 expression results, the Ki-65 min, Ki-30 min, and SUVmax in PD-L1 positivity were significantly higher than that in PD-L1 negativity (P < 0.05). And no significant differences in predicting PD-L1 positivity were found among Ki-65 min, Ki-30 min, and SUVmax (AUC = 0.704, 0.695, and 0.737, respectively, P > 0.05), according to the results of ROC analysis and Delong test.ConclusionsThis study indicates that an early 30-minute dynamic FDG-PET acquisition appears to be sufficient to provide quantitative images with good-quality and accurate Ki values for the assessment of lung lesions and prediction of PD-L1 expression. Protocols with a shortened early 30-minute acquisition time may be considered for patients who have difficulty with prolonged acquisitions to improve the efficiency of clinical acquisitions.

Nuclear Medicine Imaging Tools in Fever of Unknown Origin: Time for a Revisit and Appropriate Use Criteria.

Fever of unknown origin (FUO) is a clinical conundrum for patients and clinicians alike, and imaging studies are often performed as part of the diagnostic workup of these patients. Recently, the Society of Nuclear Medicine and Molecular Imaging convened and approved a guideline on the use of nuclear medicine tools for FUO. The guidelines support the use of 2-18F-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET)/computed tomography (CT) in adults and children with FUO. 18F-FDG PET/CT allows detection and localization of foci of hypermetabolic lesions with high sensitivity because of the 18F-FDG uptake in glycolytically active cells that may represent inflammation, infection, or neoplasia. Clinicians should consider and insurers should cover 18F-FDG PET/CT when evaluating patients with FUO, particularly when other clinical clues and preliminary studies are unrevealing.

Identifying G6PC3 as a Potential Key Molecule in Hypoxic Glucose Metabolism of Glioblastoma Derived from the Depiction of 18F-Fluoromisonidazole and 18F-Fluorodeoxyglucose Positron Emission Tomography.

Glioblastoma is the most aggressive primary brain tumor, characterized by its distinctive intratumoral hypoxia. Sequential preoperative examinations using fluorine-18-fluoromisonidazole (18F-FMISO) and fluorine-18-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET) could depict the degree of glucose metabolism with hypoxic condition. However, molecular mechanism of glucose metabolism under hypoxia in glioblastoma has been unclear. The aim of this study was to identify the key molecules of hypoxic glucose metabolism. Using surgically obtained specimens, gene expressions associated with glucose metabolism were analyzed in patients with glioblastoma (n = 33) who underwent preoperative 18F-FMISO and 18F-FDG PET to identify affected molecules according to hypoxic condition. Tumor in vivo metabolic activities were semiquantitatively evaluated by lesion-normal tissue ratio (LNR). Protein expression was confirmed by immunofluorescence staining. To evaluate prognostic value, relationship between gene expression and overall survival was explored in another independent nonoverlapping clinical cohort (n = 17) and validated by The Cancer Genome Atlas (TCGA) database (n = 167). Among the genes involving glucose metabolic pathway, mRNA expression of glucose-6-phosphatase 3 (G6PC3) correlated with 18F-FDG LNR (P = 0.03). In addition, G6PC3 mRNA expression in 18F-FMISO high-accumulated glioblastomas was significantly higher than that in 18F-FMISO low-accumulated glioblastomas (P < 0.01). Protein expression of G6PC3 was consistent with mRNA expression, which was confirmed by immunofluorescence analysis. These findings indicated that the G6PC3 expression might be facilitated by hypoxic condition in glioblastomas. Next, we investigated the clinical relevance of G6PC3 in terms of prognosis. Among the glioblastoma patients who received gross total resection, mRNA expressions of G6PC3 in the patients with poor prognosis (less than 1-year survival) were significantly higher than that in the patients who survive more than 3 years. Moreover, high mRNA expression of G6PC3 was associated with poor overall survival in glioblastoma, as validated by TCGA database. G6PC3 was affluently expressed in glioblastoma tissues with coincidentally high 18F-FDG and 18F-FMISO accumulation. Further, it might work as a prognostic biomarker of glioblastoma. Therefore, G6PC3 is a potential key molecule of glucose metabolism under hypoxia in glioblastoma.

Exceptionally Rare Isolated Thyroidal Metastasis of Pulmonary Carcinosarcoma: A Tale of 18F-FDG-positive Thyroid Nodule.

Pulmonary carcinosarcomas (PCS) are uncommon and aggressive malignant tumors with epithelial and mesenchymal components and have a worse prognosis than other non-small-cell lung cancers. Metastases of non-thyroidal malignancies to the thyroid are rare. We reported a unique case of isolated thyroidal metastasis of PCS and discussed 18F-fluorodeoxyglucose (18F-FDG) positivity in incidentally found thyroid nodules on 18F-FDG positron emission tomography scan.

Using tumor habitat-derived radiomic analysis during pretreatment 18F-FDG PET for predicting KRAS/NRAS/BRAF mutations in colorectal cancer

BackgroundTo investigate the association between Kirsten rat sarcoma viral oncogene homolog (KRAS) / neuroblastoma rat sarcoma viral oncogene homolog (NRAS) /v-raf murine sarcoma viral oncogene homolog B (BRAF) mutations and the tumor habitat-derived radiomic features obtained during pretreatment 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) in patients with colorectal cancer (CRC).MethodsWe retrospectively enrolled 62 patients with CRC who had undergone 18F-FDG PET/computed tomography from January 2017 to July 2022 before the initiation of therapy. The patients were randomly split into training and validation cohorts with a ratio of 6:4. The whole tumor region radiomic features, habitat-derived radiomic features, and metabolic parameters were extracted from 18F-FDG PET images. After reducing the feature dimension and selecting meaningful features, we constructed a hierarchical model of KRAS/NRAS/BRAF mutations by using the support vector machine. The convergence of the model was evaluated by using learning curve, and its performance was assessed based on the area under the receiver operating characteristic curve (AUC), calibration curve, and decision curve analysis. The SHapley Additive exPlanation was used to interpret the contributions of various features to predictions of the model.ResultsThe model constructed by using habitat-derived radiomic features had adequate predictive power with respect to KRAS/NRAS/BRAF mutations, with an AUC of 0.759 (95% CI: 0.585–0.909) on the training cohort and that of 0.701 (95% CI: 0.468–0.916) on the validation cohort. The model exhibited good convergence, suitable calibration, and clinical application value. The results of the SHapley Additive explanation showed that the peritumoral habitat and a high_metabolism habitat had the greatest impact on predictions of the model. No meaningful whole tumor region radiomic features or metabolic parameters were retained during feature selection.ConclusionThe habitat-derived radiomic features were found to be helpful in stratifying the status of KRAS/NRAS/BRAF in CRC patients. The approach proposed here has significant implications for adjuvant treatment decisions in patients with CRC, and needs to be further validated on a larger prospective cohort.

The Role of PET Imaging in Patients with Prion Disease: A Literature Review.

Prion diseases are rare, rapidly progressive, and fatal incurable degenerative brain disorders caused by the misfolding of a normal protein called PrPC into an abnormal protein called PrPSc. Their highly variable clinical presentation mimics various degenerative and non-degenerative brain disorders, making diagnosis a significant challenge for neurologists. Currently, definitive diagnosis relies on post-mortem examination of nervous tissue to detect the pathogenic prion protein. The current diagnostic criteria are limited. While structural magnetic resonance imaging (MRI) remains the gold standard imaging modality for Creutzfeldt-Jakob disease (CJD) diagnosis, positron emission tomography (PET) using 18fluorine-fluorodeoxyglucose (18F-FDG) and other radiotracers have demonstrated promising potential in the diagnostic assessment of prion disease. In this context, a comprehensive and updated review exclusively focused on PET imaging in prion diseases is still lacking. We review the current value of PET imaging with 18F-FDG and non-FDG tracers in the diagnostic management of prion diseases. From the collected data, 18F-FDG PET mainly reveals cortical and subcortical hypometabolic areas in prion disease, although fails to identify typical pattern or laterality abnormalities to differentiate between genetic and sporadic prion diseases. Although the rarity of prion diseases limits the establishment of a definitive hypometabolism pattern, this review reveals some more prevalent 18F-FDG patterns associated with each disease subtype. Interestingly, in both sporadic and genetic prion diseases, the hippocampus does not show significant glucose metabolism alterations, appearing as a useful sign in the differential diagnosis with other neurodegenerative disease. In genetic prion disease forms, PET abnormality precedes clinical manifestation. Discordant diagnostic value for amyloid tracers among different prion disease subtypes was observed, needing further investigation. PET has emerged as a potential valuable tool in the diagnostic armamentarium for CJD. Its ability to visualize functional and metabolic brain changes provides complementary information to structural MRI, aiding in the early detection and confirmation of CJD.

Development and validation of a 18F-FDG PET/CT radiomics nomogram for predicting progression free survival in locally advanced cervical cancer: a retrospective multicenter study

BackgroundThe existing staging system cannot meet the needs of accurate survival prediction. Accurate survival prediction for locally advanced cervical cancer (LACC) patients who have undergone concurrent radiochemotherapy (CCRT) can improve their treatment management. Thus, this present study aimed to develop and validate radiomics models based on pretreatment 18Fluorine-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET)-computed tomography (CT) images to accurately predict the prognosis in patients.MethodsThe data from 190 consecutive patients with LACC who underwent pretreatment 18F-FDG PET-CT and CCRT at two cancer hospitals were retrospectively analyzed; 176 patients from the same hospital were randomly divided into training (n = 117) and internal validation (n = 50) cohorts. Clinical features were selected from the training cohort using univariate and multivariate Cox proportional hazards models; radiomic features were extracted from PET and CT images and filtered using least absolute shrinkage and selection operator and Cox proportional hazard regression. Three prediction models and a nomogram were then constructed using the previously selected clinical, CT and PET radiomics features. The external validation cohort that was used to validate the models included 23 patients with LACC from another cancer hospital. The predictive performance of the constructed models was evaluated using receiver operator characteristic curves, Kaplan Meier curves, and a nomogram.ResultsIn total, one clinical, one PET radiomics, and three CT radiomics features were significantly associated with progression-free survival in the training cohort. Across all three cohorts, the combined model displayed better efficacy and clinical utility than any of these parameters alone in predicting 3-year progression-free survival (area under curve: 0.661, 0.718, and 0.775; C-index: 0.698, 0.724, and 0.705, respectively) and 5-year progression-free survival (area under curve: 0.661, 0.711, and 0.767; C-index, 0.698, 0.722, and 0.676, respectively). On subsequent construction of a nomogram, the calibration curve demonstrated good agreement between actually observed and nomogram-predicted values.ConclusionsIn this study, a clinico-radiomics prediction model was developed and successfully validated using an independent external validation cohort. The nomogram incorporating radiomics and clinical features could be a useful clinical tool for the early and accurate assessment of long-term prognosis in patients with LACC patients who undergo concurrent chemoradiotherapy.

Strategies for deep learning-based attenuation and scatter correction of brain 18 F-FDG PET images in the image domain.

Attenuation and scatter correction is crucial for quantitative positron emission tomography (PET) imaging. Direct attenuation correction (AC) in the image domain using deep learning approaches has been recently proposed for combined PET/MR and standalone PET modalities lacking transmission scanning devices or anatomical imaging. In this study, different input settings were considered in the model training to investigate deep learning-based AC in the image space. Three different deep learning methods were developed for direct AC in the image space: (i) use of non-attenuation-corrected PET images as input (NonAC-PET), (ii) use of attenuation-corrected PET images with a simple two-class AC map (composed of soft-tissue and background air) obtained from NonAC-PET images (PET segmentation-based AC [SegAC-PET]), and (iii) use of both NonAC-PET and SegAC-PET images in a Double-Channel fashion to predict ground truth attenuation corrected PET images with Computed Tomography images (CTAC-PET). Since a simple two-class AC map (generated from NonAC-PET images) can easily be generated, this work assessed the added value of incorporating SegAC-PET images into direct AC in the image space. A 4-fold cross-validation scheme was adopted to train and evaluate the different models based using 80 brain 18 F-Fluorodeoxyglucose PET/CT images. The voxel-wise and region-wise accuracy of the models were examined via measuring the standardized uptake value (SUV) quantification bias in different regions of the brain. The overall root mean square error (RMSE) for the Double-Channel setting was 0.157±0.08 SUV in the whole brain region, while RMSEs of 0.214±0.07 and 0.189±0.14 SUV were observed in NonAC-PET and SegAC-PET models, respectively. A mean SUV bias of 0.01±0.26% was achieved by the Double-Channel model regarding the activity concentration in cerebellum region, as opposed to 0.08±0.28% and 0.05±0.28% SUV biases for the network that uniquely used NonAC-PET or SegAC-PET as input, respectively. SegAC-PET images with an SUV bias of -1.15±0.54%, served as a benchmark for clinically accepted errors. In general, the Double-Channel network, relying on both SegAC-PET and NonAC-PET images, outperformed the other AC models. Since the generation of two-class AC maps from non-AC PET images is straightforward, the current study investigated the potential added value of incorporating SegAC-PET images into a deep learning-based direct AC approach. Altogether, compared with models that use only NonAC-PET and SegAC-PET images, the Double-Channel deep learning network exhibited superior attenuation correction accuracy.

Utility of 18F-FDG PET/CT for differential diagnosis between IgG4-related lymphadenopathy and angioimmunoblastic T-cell lymphoma

To explore the utility of the 2-[18F]-fluoro-2-deoxy-d-glucose (18F-FDG) positron-emission tomography (PET)/computed tomography (CT) in the differential diagnosis of IgG4-related lymphadenopathy (IgG4-RLAD) and angioimmunoblastic T-cell lymphoma (AITL). Retrospective analysis of 18F-FDG PET/CT imaging findings in clinically diagnosed IgG4-RLAD and AITL cases was undertaken to record the distribution, morphological characteristics, and imaging features of the affected lymph nodes, as well as FDG uptake of the spleen and bone marrow. Standardised uptake values normalised to lean body mass were evaluated for maximum (SULmax), average (SULavg), and peak values (SULpeak). Univariate and multivariate logistic regression was used to screen for statistically significant imaging findings to discriminate IgG4-RLAD from AITL. Twenty-two cases of IgG4-RLAD (17 men, five women, median age 49.5 years) and 22 cases of AITL (16 men, six women, median age 55 years) were finally included in the analysis. There were no AITL patients with involvement of a single lymph node region. AITL patients had more involvement of the different nodal regions except cervical and pelvic nodal regions. A practical assessment method based on a combination of SULpeak-LN/SULavg-liver, SULpeak-spleen, and the number of involved nodal regions, improved the performance for differential diagnosis between both groups with an overall classification accuracy of 90.9%. 18F-FDG PET/CT is a useful tool for distinguishing AITL from IgG4-RLAD, and it can also help determine the optimal biopsy site for suspected cases of IgG4-RLAD or AITL, reduce the need for re-biopsy procedures, and enable physicians to develop timely treatment strategies.

One-tenth-activity total-body positron emission tomography versus full-activity imaging in patients with a complex of hepatic malignant tumors: a retrospective study.

The value of ultra-low-activity 2-[18F]-fluoro-2-deoxy-D-glucose (18F-FDG) positron emission tomography (PET) imaging in patients with hepatic malignancies remains unclear. A cross-sectional study was conducted from April 2019 to May 2021 in Zhongshan Hospital, Fudan University. A total of 49 patients with hepatic malignancies, including hepatocellular carcinoma (HCC) (n=13) or intrahepatic cholangiocarcinoma (ICC) (n=36), underwent 60-min dynamic PET imaging, with 15 undergoing full-activity 18F-FDG and 34 undergoing ultra-low-activity 18F-FDG. The kinetic metrics (K1-k3, and Ki) of tumors were calculated and compared between the activity groups. Another 54 patients (27 each group) with hepatic malignancies, including HCC (n=9), ICC (n=34), and metastases (n=11), underwent static imaging. Image qualities were compared between the groups in terms of 5-point Likert scores (with a score ≥3 fulfilling the clinical requirement), the mean standardized uptake value (SUVmean), the standard deviation of standardized uptake value (SUVSD), and the signal-to-noise ratio (SNR) of the liver; the SUVmean of blood pool and muscle; and the tumor-to-liver ratio (TLR), tumor-to-blood ratio (TBR), and tumor-to-muscle ratio (TMR) of lesions. Intergroup comparisons were performed using Chi-squared test for categorical variables and the Student's t-test or the Mann-Whitney test for continuous variables depending on the normality of variables. There was a nonsignificant difference in the kinetic metrics (K1-k3 and Ki) of tumors between the activity groups. In static imaging, 1-min full-activity (F1) and 8-min ultra-low-activity (L8) images obtained image-quality scores >3 and were thus selected for intergroup comparisons. Nonsignificant differences in SUVmean of liver, blood pool, and muscle were identified between F1 and L8 images (P=0.641, P=0.542, and P=0.073, respectively) although the liver SNR was slightly higher in F1 (13.10 vs. 11.31; P=0.003). Lesion detectability was 98.5% and 100% for F1 and L8 images, respectively, but there were no significant differences in TLR, TBR, or TMR between the groups. The results of this single-center study indicate that the performance of ultra-low-activity PET imaging is comparable to that of full-activity imaging in patients with hepatic malignancies.

Correlation between 18F-FDG PET-derived parameters and quantitative pathological characteristics of soft tissue sarcoma.

18F-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET) has been widely used for evaluating patients with soft tissue sarcoma (STS). However, uncertainties and overlap among individuals may be observed, and the relevance of these findings remains to be further explored. The present study was aimed at investigating the correlation between PET metabolic parameters and quantitative pathological characteristics in STS. We retrospectively collected 39 patients with STS who underwent 18F-FDG PET/computed tomography (CT) examination before treatment. Metabolic parameters including the maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV), total lesion glycolysis (TLG), and intratumoral FDG uptake heterogeneity (IFH) were measured. Histological grading was performed according to the French Federation of Cancer Centers grading system. Continuous staining of tissue sections and digital quantitative analysis methods were used, the characteristics of tumor nucleated cells were observed through hematoxylin-eosin staining, and the expression of CD163, CD68, CD8, and CD4 in tumor tissues was determined by immunohistochemistry (IHC), then the correlation between FDG metabolic parameters and the above quantitative pathological characteristics in patients with STS were evaluated. The SUVmax of 18F-FDG PET/CT in STS was positively correlated with the total nuclear area (r=0.355, P=0.027). SUVmax was also positively correlated with the expression levels of CD163, CD68, CD8, and CD4 (r=0.582, 0.485, 0.343, and 0.324, with P<0.001, 0.002, 0.032, and 0.044, respectively), but was not significantly correlated with cell count and mean nuclear area (all P>0.05). However, MTV, TLG, and IFH were not significantly correlated with the above quantitative pathological characteristics. Further multivariate logistic regression analysis indicated that only CD163 expression and histological grade were independently correlated with SUVmax. Moreover, SUVmax remained positively correlated with CD163 expression in the low-grade STS (r=0.820, P=0.001) and high-grade STS groups (r=0.430, P=0.028). 18F-FDG uptake was positively correlated with the quantitative pathological features of soft tissue tumors. SUVmax may be a meaningful method reflecting the level of M2 macrophage infiltration and may provide additional valuable information for preclinical evaluation of STS.

Multiparametric hippocampal signatures for early diagnosis of Alzheimer's disease using 18F-FDG PET/MRI Radiomics.

This study aimed to explore the utility of hippocampal radiomics using multiparametric simultaneous positron emission tomography (PET)/magnetic resonance imaging (MRI) for early diagnosis of Alzheimer's disease (AD). A total of 53 healthy control (HC) participants, 55 patients with amnestic mild cognitive impairment (aMCI), and 51 patients with AD were included in this study. All participants accepted simultaneous PET/MRI scans, including 18F-fluorodeoxyglucose (18F-FDG) PET, 3D arterial spin labeling (ASL), and high-resolution T1-weighted imaging (3D T1WI). Radiomics features were extracted from the hippocampus region on those three modal images. Logistic regression models were trained to classify AD and HC, AD and aMCI, aMCI and HC respectively. The diagnostic performance and radiomics score (Rad-Score) of logistic regression models were evaluated from 5-fold cross-validation. The hippocampal radiomics features demonstrated favorable diagnostic performance, with the multimodal classifier outperforming the single-modal classifier in the binary classification of HC, aMCI, and AD. Using the multimodal classifier, we achieved an area under the receiver operating characteristic curve (AUC) of 0.98 and accuracy of 96.7% for classifying AD from HC, and an AUC of 0.86 and accuracy of 80.6% for classifying aMCI from HC. The value of Rad-Score differed significantly between the AD and HC (p < 0.001), aMCI and HC (p < 0.001) groups. Decision curve analysis showed superior clinical benefits of multimodal classifiers compared to neuropsychological tests. Multiparametric hippocampal radiomics using PET/MRI aids in the identification of early AD, and may provide a potential biomarker for clinical applications.

Brain metabolic network covariance and aging in a mouse model of Alzheimer's disease.

Alzheimer's disease (AD), the leading cause of dementia worldwide, represents a human and financial impact for which few effective drugs exist to treat the disease. Advances in molecular imaging have enabled assessment of cerebral glycolytic metabolism, and network modeling of brain region have linked to alterations in metabolic activity to AD stage. We performed 18 F-FDG positron emission tomography (PET) imaging in 4-, 6-, and 12-month-old 5XFAD and littermate controls (WT) of both sexes and analyzed region data via brain metabolic covariance analysis. The 5XFAD model mice showed age-related changes in glucose uptake relative to WT mice. Analysis of community structure of covariance networks was different across age and sex, with a disruption of metabolic coupling in the 5XFAD model. The current study replicates clinical AD findings and indicates that metabolic network covariance modeling provides a translational tool to assess disease progression in AD models.