BACKGROUND: Limited data exist on the significance of PET imaging and quantitative PET parameters in primary central nervous system (CNS) lymphoma due to its relative rarity. This study was conducted to investigate the prognostic value of a novel internal standardization indicator, the pontine-white matter (PW) score, in primary CNS lymphoma patients undergoing post-treatment 18F-FDG PET/CT and PET/MR imaging.
METHODS: From January 2014 to December 2022, eligible patients with primary CNS lymphoma who underwent post-treatment PET imaging were enrolled. Using the FDG uptake of the pons and white matter as an internal reference, the PW score was graded based on the metabolism of the post-therapeutic lesion for each patient, and its associations with patients\' prognosis were investigated.
RESULTS: In total, 41 patients with post-treatment PET/CT and 49 patients with post-treatment PET/MR imaging were enrolled. ROC curve analysis indicated that the PW score possessed robust discriminative ability in distinguishing patients with worse outcomes. Furthermore, a higher PW score was significantly correlated with and identified as an independent prognostic indicator for, worse prognosis in both the PET/CT and PET/MR cohorts.
CONCLUSIONS: The study demonstrated that the PW score was an effective prognostic indicator for identifying post-treatment primary CNS lymphoma patients with worse outcomes.

BACKGROUND: To 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).
METHODS: We 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.
RESULTS: The 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.
CONCLUSIONS: The 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.

BACKGROUND: Developing biomarkers for early stage AD patients is crucial. Glucose metabolism measured by 18F-FDG PET is the most common biomarker for evaluating cellular energy metabolism to diagnose AD. Arterial spin labeling (ASL) MRI can potentially provide comparable diagnostic information to 18F-FDG PET in patients with neurodegenerative disorders. However, the conclusions about the diagnostic performance of AD are still controversial between 18F-FDG PET and ASL. This study aims to compare quantitative cerebral blood flow (CBF) and glucose metabolism measured by 18F-FDG PET diagnostic values in patients with Alzheimer\'s disease (AD) and amnestic mild cognitive impairment (aMCI) using integrated PET/MR.
RESULTS: Analyses revealed overlapping between decreased regional rCBF and 18F-FDG PET SUVR in patients with AD compared with NC participants in the bilateral parietotemporal regions, frontal cortex, and cingulate cortex. Compared with NC participants, patients with aMCI exclusively demonstrated lower 18F-FDG PET SUVR in the bilateral temporal cortex, insula cortex, and inferior frontal cortex. Comparison of the rCBF in patients with aMCI and NC participants revealed no significant difference (P > 0.05). The ROC analysis of rCBF in the meta-ROI could diagnose patients with AD (AUC, 0.87) but not aMCI (AUC, 0.61). The specificity of diagnosing aMCI has been improved to 75.56% when combining rCBF and 18F-FDG PET SUVR.
CONCLUSIONS: ASL could detect similar aberrant patterns of abnormalities compared to 18F-FDG PET in patients with AD compared with NC participants but not in aMCI. The diagnostic efficiency of 18F-FDG-PET for AD and aMCI patients remained higher to ASL. Our findings support that applying 18F-FDG PET may be preferable for diagnosing AD and aMCI.

More than half of patients with tuberous sclerosis complex (TSC) suffer from drug-resistant epilepsy (DRE), and resection surgery is the most effective way to control intractable epilepsy. Precise preoperative localization of epileptogenic tubers among all cortical tubers determines the surgical outcomes and patient prognosis. Models for preoperatively predicting epileptogenic tubers using 18F-FDG PET images are still lacking, however. We developed noninvasive predictive models for clinicians to predict the epileptogenic tubers and the outcome (seizure freedom or no seizure freedom) of cortical tubers based on 18F-FDG PET images.
Forty-three consecutive TSC patients with DRE were enrolled, and 235 cortical tubers were selected as the training set. Quantitative indices of cortical tubers on 18F-FDG PET were extracted, and logistic regression analysis was performed to select those with the most important predictive capacity. Machine learning models, including logistic regression (LR), linear discriminant analysis (LDA), and artificial neural network (ANN) models, were established based on the selected predictive indices to identify epileptogenic tubers from multiple cortical tubers. A discriminating nomogram was constructed and found to be clinically practical according to decision curve analysis (DCA) and clinical impact curve (CIC). Furthermore, testing sets were created based on new PET images of 32 tubers from 7 patients, and follow-up outcome data from the cortical tubers were collected 1, 3, and 5 years after the operation to verify the reliability of the predictive model. The predictive performance was determined by using receiver operating characteristic (ROC) analysis.
PET quantitative indices including SUVmean, SUVmax, volume, total lesion glycolysis (TLG), third quartile, upper adjacent and standard added metabolism activity (SAM) were associated with the epileptogenic tubers. The SUVmean, SUVmax, volume and TLG values were different between epileptogenic and non-epileptogenic tubers and were associated with the clinical characteristics of epileptogenic tubers. The LR model achieved the better performance in predicting epileptogenic tubers (AUC = 0.7706; 95% CI 0.70-0.83) than the LDA (AUC = 0.7506; 95% CI 0.68-0.82) and ANN models (AUC = 0.7425; 95% CI 0.67-0.82) and also demonstrated good calibration (Hosmer‒Lemeshow goodness-of-fit p value = 0.7). In addition, DCA and CIC confirmed the clinical utility of the nomogram constructed to predict epileptogenic tubers based on quantitative indices. Intriguingly, the LR model exhibited good performance in predicting epileptogenic tubers in the testing set (AUC = 0.8502; 95% CI 0.71-0.99) and the long-term outcomes of cortical tubers (1-year outcomes: AUC = 0.7805, 95% CI 0.71-0.85; 3-year outcomes: AUC = 0.8066, 95% CI 0.74-0.87; 5-year outcomes: AUC = 0.8172, 95% CI 0.75-0.87).
The 18F-FDG PET image-based LR model can be used to noninvasively identify epileptogenic tubers and predict the long-term outcomes of cortical tubers in TSC patients.

Early diagnosis of Anti-N-methyl-D-aspartate receptor (anti-NMDAR) encephalitis with non-invasive imaging modalities benefiting is crucial to guarantee prompt treatments decision-making and good prognosis for patients. The present study aimed to explore the correlation of MRI features with brain metabolism characteristics of 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) and to describe the metabolic patterns in Anti-N-methyl-D-aspartate receptor (anti-NMDAR) encephalitis at acute and subacute phases. Twenty-four patients with anti-NMDAR encephalitis confirmed by serum and/or CSF tests at acute and subacute phases, 9 females and 15 males, with an age range of 6-80 years, were enrolled in this retrospective study as encephalitis group. 18F-FDG PET and MRI findings of all patients were investigated and interpreted with visual analysis. Chi-square test was performed to compare the diagnostic sensitivity between MRI and PET. Independent sample t-test was used to compare the standardized uptake value ratio (SUVR) of each ROI between the encephalitis group and control group, which consisted of 24 healthy volunteers of the same age and gender.
There was no statistical difference in the diagnostic sensitivity between FDG PET (23/24, 95.83%) and MRI (18/24, 75.00%) in anti-NMDAR encephalitis patients (P > 0.05). Three categories of abnormalities shown on T2 FLAIR, including shallow of sulci and swelling of brain tissue, increased signal in the sulci, increased signal on brain gray matter or adjacent white matter presented hypermetabolism on PET, excepting increased signal in brain linear structure with hypometabolism of the basal ganglia on PET. We identified 19 brain regions with hypermetabolism and 16 brain regions with hypometabolism that exhibited statistically significant changes in SUVRs between anti-NMDAR encephalitis group and control group (FDR P < 0.05).
Anteroposterior glucose metabolism gradient (frontal-temporal/parietal-occipital) is proved to be a typical pattern of anti-NMDAR encephalitis at the acute and subacute phases in both visual and statistical testing. Interestingly, the pattern is also commonly found in the anterior and posterior portions of the parietal lobe and cingular cortex, which may be a potential indicator for the diagnosis of this disorder. In addition, MRI is an important and reliable neuroimaging modality to assist in the correct evaluation of activity changes on individual 18F-FDG PET.

OBJECTIVE: Progressive supranuclear palsy (PSP) involves a variety of visual symptoms that are thought to be partially caused by structural abnormalities of the retina. However, the relationship between retinal structural changes, disease severity, and intracranial alterations remains unknown. We investigated distinct retinal thinning patterns and their relationship with clinical severity and intracranial alterations in a PSP cohort.
METHODS: We enrolled 19 patients with PSP (38 eyes) and 20 age-matched healthy controls (40 eyes). All of the participants underwent peripapillary and macular optical coherence tomography. Brain 11C-2β-carbomethoxy-3β-(4-fluorophenyl) tropane (11C-CFT) and 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography imaging were also performed in patients with PSP. We investigated the association between retinal thickness changes and clinical features, striatal dopamine transporter availability, and cerebral glucose metabolism.
RESULTS: The peripapillary retinal nerve fiber layer (pRNFL) and macula were significantly thinner in patients with PSP than in controls. The thickness of the superior sector of the pRNFL demonstrated a significant negative relationship with the Movement Disorder Society-Unified Parkinson\'s Disease Rating Scale part III and Hoehn and Yahr staging scale scores. A significant negative correlation was found between outer inferior macular thickness and disease duration. Outer temporal macular thickness was positively correlated with Montreal Cognitive Assessment scores. In PSP, lower outer temporal macular thickness was also positively correlated with decreased dopamine transporter binding in the caudate.
CONCLUSIONS: The pRNFL and macular thinning may be candidate markers for monitoring disease severity. Additionally, macular thinning may be an in vivo indicator of nigrostriatal dopaminergic cell degeneration in PSP patients.

Metabolic reprogramming that senses brain homeostasis imbalances is necessary to drive detrimental microglial polarization, and specific targeting of this process contributes to the flexible control of pathological inflammatory responses in Alzheimer\'s disease (AD), displaying distinctive therapeutic benefits. Herein, glutathione-functionalized gold nanocages loaded with the immunosuppressant fingolimod hydrochloride are developed as brain-targeted and microglia-located immunometabolic reprogramming nanomodulators (GAF NPs) for AD management. By virtue of glutathione-mediated transport properties, this nanomodulator can cross the blood-brain barrier and localize to microglia in AD lesions. Through blocking Akt/mTOR/HIF-1α signaling pathways, GAF NPs not only promote the dominated metabolic shift from glycolysis to oxidative phosphorylation under immune activation but also inhibit transporter-mediated glucose overconsumption by microglia. Correlation analysis based on real-time bioenergetic assessment and 18F-labeled fluorodeoxyglucose (FDG) PET reveals that brain glucose utilization and metabolism restored by GAF NP treatment can serve as a sensitive and effective indicator for microglial M1 to M2 polarization switching, ultimately alleviating neuroinflammation and its derived neurodegeneration as well as ameliorating cognitive decline in AD mice. This work highlights a potential nanomedicine aimed at modifying mTOR-mediated immunometabolic reprogramming to halt energy deprivation-induced AD progression.

Our objective was to compare the diagnostic performance of 68Ga-labeled fibroblast activation protein (FAP) inhibitor (FAPI) and 18F-labeled FDG PET/CT in diagnosing lymphomas and to characterize the influence of FAP and glycolytic markers on tracer uptake by involved lesions. Methods: Participants with different lymphoma subtypes who were prospectively recruited from May 2020 to December 2021 underwent 68Ga-FAPI and 18F-FDG PET/CT. Immunohistochemistry was performed to evaluate FAP, hexokinase 2, and glucose transporter 1 (GLUT1) expression, and the paired-samples t test and Wilcoxon signed-rank test were used to compare parameters. The correlation between the immunochemistry results and tracer uptake was determined by the Spearman rank correlation coefficient. Results: In total, 186 participants (median age, 52 y [interquartile range, 41-64 y]; 95 women) were included. Dual-tracer imaging produced 3 types of imaging profiles. 18F-FDG PET possessed a higher staging accuracy (98.4%) than 68Ga-FAPI PET (86.0%). In 5,980 lymphoma lesions, 18F-FDG PET/CT detected more nodal (4,624 vs. 2,196) and extranodal (1,304 vs. 845) lesions than 68Ga-FAPI PET/CT. Additionally, 52 68Ga-FAPI-positive/18F-FDG-negative lesions and 2,939 68Ga-FAPI-negative/18F-FDG-positive lesions were observed. In many lymphoma subtypes, semiquantitative evaluation revealed no significant differences in SUVmax or target-to-liver ratios between 68Ga-FAPI and 18F-FDG PET/CT (P > 0.05). Interestingly, GLUT1 and hexokinase 2 were overexpressed both in lymphoma cells and in the tumor microenvironment, whereas FAP was expressed only in stromal cells. FAP and GLUT1 expression correlated positively with 68Ga-FAPI SUVmax (r = 0.622, P = 0.001) and 18F-FDG SUVmax (r = 0.835, P < 0.001), respectively. Conclusion: 68Ga-FAPI PET/CT was inferior to 18F-FDG PET/CT in diagnosing lymphomas with low FAP expression. However, the former may supplement the latter and help reveal the molecular profile of lymphomas.

UNASSIGNED: Evaluation of the correlation between 18F-fluorodeoxyglucose-positron emission tomography (18F-FDG PET) and cognitive function in first-diagnosed and untreated Parkinson\'s disease (PD) patients.
UNASSIGNED: This cross-sectional study included 84 first diagnosed and untreated PD patients. The individuals were diagnosed by movement disorder experts based on the 2015 MDS Parkinson\'s disease diagnostic criteria. The patients also underwent 18F-FDG PET scans and clinical feature assessments including the Montreal Cognitive Assessment (MoCA) scale. Glucose metabolism rates were measured in 26 brain regions using region of interest (ROI) and pixel-wise analyses with displayed Z scores. The cognitive function was assessed by professionals using the MoCA scale, which covers five cognitive domains. Spearman\'s linear correlation and linear regression models were used to compare the correlations between 18F-FDG metabolism in each brain region and cognitive domain, using SPSS 25.0 software.
UNASSIGNED: The results indicated a positive correlation between executive function and glucose metabolism in the lateral prefrontal cortex of the left hemisphere (p = 0.041). Additionally, a positive correlation between memory function and glucose metabolism in the right precuneus (p = 0.014), right lateral occipital cortex (p = 0.017), left lateral occipital cortex (p = 0.031), left primary visual cortex (p = 0.008), and right medial temporal cortex (p = 0.046). Further regression analysis showed that for every one-point decrease in the memory score, the glucose metabolism in the right precuneus would decrease by 0.3 (B = 0.30, p = 0.005), the glucose metabolism in the left primary visual cortex would decrease by 0.25 (B = 0.25, p = 0.040), the glucose metabolism in the right lateral occipital cortex would decrease by 0.38 (B = 0.38, p = 0.012), and the glucose metabolism in the left lateral occipital cortex would decrease by 0.32 (B = 0.32, p = 0.045).
UNASSIGNED: This study indicated that cognitive impairment in PD patients mainly manifests as changes in executive function, visual-spatial function and memory functions, while glucose metabolism mainly decreases in the frontal and posterior cortex. Further analysis shows that executive function is related to glucose metabolism in the left lateral prefrontal cortex. On the other hand, memory ability involves changes in glucose metabolism in a more extensive brain region. This suggests that cognitive function assessment can indirectly reflect the level of glucose metabolism in the relevant brain regions.

[This corrects the article DOI: 10.3389/fimmu.2023.1151967.].