Imaging of the brain-heart axis: prognostic value in a European setting.

BACKGROUND AND AIMS: Increasing data suggest that stress-related neural activity (SNA) is associated with subsequent major adverse cardiovascular events (MACE) and may represent a therapeutic target. Current evidence is exclusively based on populations from the U.S. and Asia where limited information about cardiovascular disease risk was available. This study sought to investigate whether SNA imaging has clinical value in a well-characterized cohort of cardiovascular patients in Europe. METHODS: In this single-centre study, a total of 963 patients (mean age 58.4 ± 16.1 years, 40.7% female) with known cardiovascular status, ranging from 'at-risk' to manifest disease, and without active cancer underwent 2-[18F]fluoro-2-deoxy-D-glucose positron emission tomography/computed tomography between 1 January 2005 and 31 August 2019. Stress-related neural activity was assessed with validated methods and relations between SNA and MACE (non-fatal stroke, non-fatal myocardial infarction, coronary revascularization, and cardiovascular death) or all-cause mortality by time-to-event analysis. RESULTS: Over a maximum follow-up of 17 years, 118 individuals (12.3%) experienced MACE, and 270 (28.0%) died. In univariate analyses, SNA significantly correlated with an increased risk of MACE (sub-distribution hazard ratio 1.52, 95% CI 1.05-2.19; P = .026) or death (hazard ratio 2.49, 95% CI 1.96-3.17; P < .001). In multivariable analyses, the association between SNA imaging and MACE was lost when details of the cardiovascular status were added to the models. Conversely, the relationship between SNA imaging and all-cause mortality persisted after multivariable adjustments. CONCLUSIONS: In a European patient cohort where cardiovascular status is known, SNA imaging is a robust and independent predictor of all-cause mortality, but its prognostic value for MACE is less evident. Further studies should define specific patient populations that might profit from SNA imaging.

Evaluation of the 2023 Duke-International Society of Cardiovascular Infectious Diseases Criteria in a Multicenter Cohort of Patients With Suspected Infective Endocarditis.

BACKGROUND: Since publication of Duke criteria for infective endocarditis (IE) diagnosis, several modifications have been proposed. We aimed to evaluate the diagnostic performance of the Duke-ISCVID (International Society of Cardiovascular Infectious Diseases) 2023 criteria compared to prior versions from 2000 (Duke-Li 2000) and 2015 (Duke-ESC [European Society for Cardiology] 2015). METHODS: This study was conducted at 2 university hospitals between 2014 and 2022 among patients with suspected IE. A case was classified as IE (final IE diagnosis) by the Endocarditis Team. Sensitivity for each version of the Duke criteria was calculated among patients with confirmed IE based on pathological, surgical, and microbiological data. Specificity for each version of the Duke criteria was calculated among patients with suspected IE for whom IE diagnosis was ruled out. RESULTS: In total, 2132 episodes with suspected IE were included, of which 1101 (52%) had final IE diagnosis. Definite IE by pathologic criteria was found in 285 (13%), 285 (13%), and 345 (16%) patients using the Duke-Li 2000, Duke-ESC 2015, or the Duke-ISCVID 2023 criteria, respectively. IE was excluded by histopathology in 25 (1%) patients. The Duke-ISCVID 2023 clinical criteria showed a higher sensitivity (84%) compared to previous versions (70%). However, specificity of the new clinical criteria was lower (60%) compared to previous versions (74%). CONCLUSIONS: The Duke-ISCVID 2023 criteria led to an increase in sensitivity compared to previous versions. Further studies are needed to evaluate items that could increase sensitivity by reducing the number of IE patients misclassified as possible, but without having detrimental effect on specificity of Duke criteria.

Quantitative brain [18F]FDG PET beyond normal blood glucose levels.

Introduction SUV measurements from static brain [18F]FDG PET acquisitions are a commonly used tool in preclinical research, providing a simple alternative for kinetic modelling, which requires complex and time-consuming dynamic acquisitions. However, SUV can be severely affected by the animal handling and preconditioning protocols, primarily by those that may induce changes in blood glucose levels (BGL). Here, we aimed at developing and investigating the feasibility of SUV-based approaches for a wide range of BGL far beyond normal values, and consequently, to develop and validate a new model to generate standardized and reproducible SUV measurements for any BGL. Material and methods We performed dynamic and static brain [18F]FDG PET acquisitions in 52 male Sprague-Dawley rats sorted into control (n = 10), non-fasting (n = 14), insulin-induced hypoglycemia (n = 12) and glucagon-induced hyperglycemia (n = 16) groups. Brain [18F]FDG PET images were cropped, aligned and co-registered to a standard template to calculate whole-brain and regional SUV. Cerebral Metabolic Rate of Glucose (CMRglc) was also estimated from 2-Tissue Compartment Model (2TCM) and Patlak plot for validation purposes. Results Our results showed that BGL=100±6 mg/dL can be considered a reproducible reference value for normoglycemia. Furthermore, we successfully established a 2nd-degree polynomial model (C1=0.66E-4, C2=-0.0408 and C3=7.298) relying exclusively on BGL measures at pre-[18F]FDG injection time, that characterizes more precisely the relationship between SUV and BGL for a wide range of BGL values (from 10 to 338 mg/dL). We confirmed the ability of this model to generate corrected SUV estimations that are highly correlated to CMRglc estimations (R2= 0.54 2TCM CMRgluc and R2= 0.49 Patlak CMRgluc). Besides, slight regional differences in SUV were found in animals from extreme BGL groups, showing that [18F]FDG uptake is mostly directed toward central regions of the brain when BGLs are significantly decreased. Conclusion Our study successfully established a non-linear model that relies exclusively on pre-scan BGL measurements to characterize the relationship between [18F]FDG SUV and BGL. The extensive validation confirmed its ability to generate SUV-based surrogates of CMRglu along a wide range of BGL and it holds the potential to be adopted as a standard protocol by the preclinical neuroimaging community using brain [18F]FDG PET imaging.

Evaluation of the Therapeutical Effect of Matricaria Chamomilla Extract vs. Galantamine on Animal Model Memory and Behavior Using 18F-FDG PET/MRI.

The memory-enhancing activity of Matricaria chamomilla hydroalcoholic extract (MCE) is already being investigated by behavioral and biochemical assays in scopolamine-induced amnesia rat models, while the effects of scopolamine (Sco) on cerebral glucose metabolism are examined as well. Nevertheless, the study of the metabolic profile determined by an enriched MCE has not been performed before. The present experiments compared metabolic quantification in characteristic cerebral regions and behavioral characteristics for normal, only diseased, diseased, and MCE- vs. Galantamine (Gal)-treated Wistar rats. A memory deficit was induced by four weeks of daily intraperitoneal Sco injection. Starting on the eighth day, the treatment was intraperitoneally administered 30 min after Sco injection for a period of three weeks. The memory assessment comprised three maze tests. Glucose metabolism was quantified after the 18F-FDG PET examination. The right amygdala, piriform, and entorhinal cortex showed the highest differential radiopharmaceutical uptake of the 50 regions analyzed. Rats treated with MCE show metabolic similarity with normal rats, while the Gal-treated group shows features closer to the diseased group. Behavioral assessments evidenced a less anxious status and a better locomotor activity manifested by the MCE-treated group compared to the Gal-treated group. These findings prove evident metabolic ameliorative qualities of MCE over Gal classic treatment, suggesting that the extract could be a potent neuropharmacological agent against amnesia.

18F-FDG PET/CT for early prediction of pathological complete response in breast cancer neoadjuvant therapy: a retrospective analysis.

BACKGROUND: Neoadjuvant treatment has been developed as a systematic approach for patients with early breast cancer and has resulted in improved breast-conserving rate and survival. However, identifying treatment-sensitive patients at the early phase of therapy remains a problem, hampering disease management and raising the possibility of disease progression during treatment. METHODS: In this retrospective analysis, we collected 2-deoxy-2-[F-18] fluoro-d-glucose (18F-FDG) positron emission tomography (PET)/computed tomography (CT) images of primary tumor sites and axillary areas and reciprocal clinical pathological data from 121 patients who underwent neoadjuvant treatment and surgery in our center. The univariate and multivariate logistic regression analyses were performed to investigate features associated with pathological complete response (pCR). An 18F-FDG PET/CT-based prediction model was trained, and the performance was evaluated by receiver operating characteristic curves (ROC). RESULTS: The maximum standard uptake values (SUVmax) of 18F-FDG PET/CT were a powerful indicator of tumor status. The SUVmax values of axillary areas were closely related to metastatic lymph node counts (R = 0.62). Moreover, the early SUVmax reduction rates (between baseline and second cycle of neoadjuvant treatment) were statistically different between pCR and non-pCR patients. The early SUVmax reduction rates-based model showed great ability to predict pCR (AUC = 0.89), with all molecular subtypes (HR+HER2-, HR+HER2+, HR-HER2+, and HR-HER2-) considered. CONCLUSION: Our research proved that the SUVmax reduction rate of 18F-FDG PET/CT contributed to the early prediction of pCR, providing rationales for utilizing PET/CT in NAT in the future.

Individual-specific metabolic network based on 18F-FDG PET revealing multi-level aberrant metabolisms in Parkinson's disease.

Metabolic network analysis in Parkinson's disease (PD) based on 18F-FDG PET has revealed PD-related metabolic patterns. However, alterations at the systemic metabolic network level and at the connection level between different brain regions still remain unknown. This study aimed to explore metabolic network alterations at multiple network levels among PD patients using an individual-specific metabolic network (ISMN) approach. 18F-FDG-PET images of patients with PD (n = 34) and healthy subjects (n = 47) were collected. Healthy subjects were further separated into reference group (n = 28) and control group (n = 19) randomly. Standardized uptake value normalized by lean body mass ratio (SULr) maps was calculated from the PET images. ISMNs were constructed based on SULr maps for PD patients and controls with reference to the reference group. Comparisons of nodal and edge features were performed between PD and control groups. Correlation analysis was conducted between multilevel network properties and clinical scales in PD group. A linear classifier was trained based on nodal or edge features to distinguish PD from controls. The distance from each patient's ISMN to the group-level difference network showed a negative correlation with Hoehn and Yahr stage (r = -0.390, p = .023). Eight nodes from ISMN were identified which exhibited significantly increased nodal degree in PD patients compared to controls (p < .05). Eleven edges were observed which demonstrated significant distinctions in Z-score values in comparisons to the control group (p < .05). Furthermore, the nodal and edge features showed comparable performances in PD diagnosis compared to the traditional SULr values, with area under the receiver operating characteristic curve larger than 0.91. The proposed ISMN approach revealed systemic metabolic deviations, as well as nodal and edge distinctions in PD, which might be supplementary to the existing findings on PD-related metabolic patterns.

Prognostic value of hypermetabolic bone sarcoidosis observed by 18F-fluorodeoxyglucose positron emission tomography.

OBJECTIVES: Sarcoidosis is a multisystemic granulomatosis diagnosed mainly in young adults.18F-fluorodeoxyglucose (18F-FDG) positron emission tomography-computed tomography (PET-CT) is useful in sarcoidosis cases to search for a biopsiable site or assess disease activity.18F-FDG PET-CT can reveal bone hypermetabolism in sarcoidosis patients, even in the absence of osteoarticular symptoms. The aim of this study was to describe metabolic bone involvement in sarcoidosis patients and to evaluate its prognostic impact. METHODS: This was an observational, comparative, retrospective, monocentric study. Inclusion criteria were a confirmed diagnosis of sarcoidosis according to the World Association of Sarcoidosis and Other Granulomatous Diseases (WASOG) criteria and at least one 18F-FDG PET-CT scan during follow-up. Metabolic bone involvement of sarcoidosis was defined as focal bone hypermetabolism with no argument for a differential diagnosis of bone 18F-FDG uptake. Patients with and without bone involvement were compared. RESULTS: Among the 175 included patients, 32 (18%) had metabolic bone involvement of sarcoidosis. The metabolic bone involvement was mainly axial and mostly without bone abnormalities on CT. Metabolic bone involvement was associated with intrathoracic and extrathoracic lymph node involvement and with a higher number of organs involved. Patients with metabolic bone involvement more frequently received corticosteroids, methotrexate and tumor necrosis factor (TNF)-α inhibitors and a higher number of treatments. Relapse of sarcoidosis occurred sooner in patients with metabolic bone involvement. CONCLUSION: These results suggest that metabolic bone involvement is associated with more diffuse and more severe sarcoidosis.

Advances in the diagnosis of myocarditis in idiopathic inflammatory myopathies: an overview of diagnostic tests.

Cardiac involvement in idiopathic inflammatory myopathies (IIM) purports to worse clinical outcomes, and therefore early identification is important. Research has focused on blood biomarkers and basic investigations such as ECG and echocardiography, which have the advantage of wide availability and low cost but are limited in their sensitivity and specificity. Imaging the myocardium to directly look for inflammation and scarring has therefore been explored, with a number of new methods for doing this gaining wider research interest and clinical availability. Cardiovascular magnetic resonance (CMR) with contemporary multiparametric mapping techniques and late gadolinium enhancement imaging, is an extremely valuable and increasingly used non-invasive imaging modality for the diagnosis of myocarditis. The recently updated CMR-based Lake Louise Criteria for the diagnosis of myocarditis incorporate the newer T1 and T2 mapping techniques, which have greatly improved the diagnostic accuracy for IIM myocarditis.18F-FDG-PET/CT is a well-utilized imaging modality in the diagnosis of malignancies in IIM, and it also has a role for the diagnosis of myocarditis in multiple systemic inflammatory diseases. Endomyocardial biopsy, however, remains the gold standard technique for the diagnosis of myocarditis and is necessary for the diagnosis of specific cases of myocarditis. This article provides an overview of the important tests and imaging modalities that clinicians should consider when faced with an IIM patient with potential myocarditis.

18F-FDG PET/CT Radiomics-Based Multimodality Fusion Model for Preoperative Individualized Noninvasive Prediction of Peritoneal Metastasis in Advanced Gastric Cancer.

PURPOSE: This study was designed to develop and validate a machine learning-based, multimodality fusion (MMF) model using 18F-fluorodeoxyglucose (FDG) PET/CT radiomics and kernelled support tensor machine (KSTM), integrated with clinical factors and nuclear medicine experts' diagnoses to individually predict peritoneal metastasis (PM) in advanced gastric cancer (AGC). METHODS: A total of 167 patients receiving preoperative PET/CT and subsequent surgery were included between November 2006 and September 2020 and were divided into a training and testing cohort. The PM status was confirmed via laparoscopic exploration and postoperative pathology. The PET/CT signatures were constructed by classic radiomic, handcrafted-feature-based model and KSTM self-learning-based model. The clinical nomogram was constructed by independent risk factors for PM. Lastly, the PET/CT signatures, clinical nomogram, and experts' diagnoses were fused using evidential reasoning to establish the MMF model. RESULTS: The MMF model showed excellent performance in both cohorts (area under the curve [AUC] 94.16% and 90.84% in training and testing), and demonstrated better prediction accuracy than clinical nomogram or experts' diagnoses (net reclassification improvement p < 0.05). The MMF model also had satisfactory generalization ability, even in mucinous adenocarcinoma and signet ring cell carcinoma which have poor uptake of 18F-FDG (AUC 97.98% and 89.71% in training and testing). CONCLUSIONS: The 18F-FDG PET/CT radiomics-based MMF model may have significant clinical implications in predicting PM in AGC, revealing that it is necessary to combine the information from different modalities for comprehensive prediction of PM.

Sex-specific differences in myocardial glucose metabolic rate in non-diabetic, pre-diabetic and type 2 diabetic subjects.

BACKGROUND: Evidence has shown that women with type 2 diabetes (T2DM) have a higher excess risk for cardiovascular disease (CVD) than men with T2DM. Subjects with either T2DM or prediabetes exhibit myocardial insulin resistance, but it is still unsettled whether sex-related differences in myocardial insulin resistance occur in diabetic and prediabetic subjects. METHODS: We aimed to evaluate sex-related differences in myocardial glucose metabolic rate (MRGlu), assessed using dynamic PET with 18F-FDG combined with euglycemic-hyperinsulinemic clamp, in subjects with normal glucose tolerance (NGT; n = 20), prediabetes (n = 11), and T2DM (n = 26). RESULTS: Women with prediabetes or T2DM exhibited greater relative differences in myocardial MRGlu than men with prediabetes or T2DM when compared with their NGT counterparts. As compared with women with NGT, those with prediabetes exhibited an age-adjusted 35% lower myocardial MRGlu value (P = 0.04) and women with T2DM a 74% lower value (P = 0.006), respectively. Conversely, as compared with men with NGT, men with T2DM exhibited a 40% lower myocardial MRGlu value (P = 0.004), while no significant difference was observed between men with NGT and prediabetes. The statistical test for interaction between sex and glucose tolerance on myocardial MRGlu (P < 0.0001) was significant suggesting a sex-specific association. CONCLUSIONS: Our data suggest that deterioration of glucose homeostasis in women is associated with a greater impairment in myocardial glucose metabolism as compared with men. The sex-specific myocardial insulin resistance could be an important factor responsible for the greater effect of T2DM on the excess risk of cardiovascular disease in women than in men.

End of induction [18F]FDG PET is prognostic for progression-free survival and overall survival in follicular lymphoma patients enrolled in the FOLL12 trial.

PURPOSE: To evaluate the reliability of the Deauville score (DS) in therapy response assessment and to define the prognostic value of the metabolic response of end of induction (EOI) [18F]FDG PET (PET) in follicular lymphoma patients. METHODS: Adult patients with untreated grade 1-3a FL/ stage II-IV enrolled in the multicentre, prospective, phase III FOLL12 trial (NCT02063685) were randomized to receive standard immunochemotherapy followed by rituximab maintenance (standard arm) versus standard immunochemotherapy followed by response-adapted post-induction management (experimental arm). Baseline and EOI PET were mandatory for the study. All PET scans were centralized on the WIDEN® platform and classified according to DS in a blind independent central review. DS1-3 was considered negative (CMR), whereas DS4-5 was considered positive (not CMR). The primary endpoint was PFS. The main secondary endpoint was overall survival (OS). RESULTS: Overall, 807 follicular lymphoma patients-52% women, 89% stage III-IV disease, 40% with a high-risk FLIPI-2 score (3-5)-were enrolled in the study; 729 (90.4%) baseline and EOI PET were available for the analysis. EOI PET was positive (DS4-5) in 88/729 (12.1%) cases. Overall inter-reviewer agreement on PET pos/neg result was 0.92, while agreement on positive and negative cases was 0.77 and 0.94, respectively. The median follow-up was 69 months; 247 events were registered in the 5-yr follow-up, with a 5-yr PFS of 67% (95%CI: 63%-70%). The 5-yr PFS rate for PET neg (DS1-3) and PET pos (DS4-5) patients was 71% (95%CI: 67%-75%) and 36% (95%CI: 25%-46%), respectively, with HR 3.49 (95%CI: 2.57-4.72). Five-year PFS was worse as DS increased, with 74% (70%-78%), 58% (48%-67%; HR 1.71; p = 0.001)] and 36% (25%-46%; HR 3.88; p < 0.001) in DS1-2, DS3 and DS4-5, respectively. EOI PET maintained its prognostic value in both the standard and experimental arms. In the whole population, 5-yr OS was 94% (95%CI: 92%-96%), with 96% (95%CI: 94-97) and 82% (95%CI: 72%-89%) in EOI PET negative (DS1-3) and positive (DS4-5), respectively (HR 4.48; p < 0.001). When DS was associated with FLIPI-2, patients with DS3 or DS1-2 with high FLIPI-2 (3-5) experienced worse OS than patients with DS1-2 and low FLIPI-2 (1-2) (p = 0.003). CONCLUSION: This study shows that DS is a reliable prognostic tool to evaluate EOI PET in follicular lymphoma patients, with prognostic value maintained both in the standard and experimental arms, making metabolic imaging a robust tool to assess response in FL. Moreover, although preliminary, this study provides further information on DS3 patients, who are considered as CMR but show a less favourable PFS than DS1-2 patients.

[18F]FDG PET/CT for prognosis and toxicity prediction of diffuse large B-cell lymphoma patients with chimeric antigen receptor T-cell therapy.

PURPOSE: Chimeric antigen receptor (CAR) T-cell therapy has been confirmed to benefit patients with relapsed and/or refractory diffuse large B-cell lymphoma (DLBCL). It is important to provide precise and timely predictions of the efficacy and toxicity of CAR T-cell therapy. In this study, we evaluated the value of [18F]fluorodeoxyglucose positron emission tomography/computed tomography ([18F]FDG PET/CT) combining with clinical indices and laboratory indicators in predicting outcomes and toxicity of anti-CD19 CAR T-cell therapy for DLBCL patients. METHODS: Thirty-eight DLBCL patients who received CAR T-cell therapy and underwent [18F]FDG PET/CT within 3 months before (pre-infusion) and 1 month after CAR T-cell infusion (M1) were retrospectively reviewed and regularly followed up. Maximum standardized uptake value (SUVmax), total lesion glycolysis (TLG), metabolic tumor volume (MTV), clinical indices, and laboratory indicators were recorded at pre-infusion and M1 time points, and changes in these indices were calculated. Progression-free survival (PFS) and overall survival (OS) were as endpoints. Based on the multivariate Cox regression analysis, two predictive models for PFS and OS were developed and evaluated the efficiency. Pre-infusion indices were subjected to predict the grade of cytokine release syndrome (CRS) resulting from toxic reactions. RESULTS: For survival analysis at a median follow-up time of 18.2 months, patients with values of international prognostic index (IPI), SUVmax at M1, and TLG at M1 above their optimal thresholds had a shorter PFS (median PFS: 8.1 months [IPI ≥ 2] vs. 26.2 months [IPI < 2], P = 0.025; 3.1 months [SUVmax ≥ 5.69] vs. 26.8 months [SUVmax < 5.69], P < 0.001; and 3.1 months [TLG ≥ 23.79] vs. 26.8 months [TLG < 23.79], P < 0.001). In addition, patients with values of SUVmax at M1 and ∆SUVmax% above their optimal thresholds had a shorter OS (median OS: 12.6 months [SUVmax ≥ 15.93] vs. 'not reached' [SUVmax < 15.93], P < 0.001; 32.5 months [∆SUVmax% ≥ -46.76] vs. 'not reached' [∆SUVmax% < -46.76], P = 0.012). Two novel predictive models for PFS and OS were visualized using nomogram. The calibration analysis and the decision curves demonstrated good performance of the models. Spearman's rank correlation (rs) analysis revealed that the CRS grade correlated strongly with the pre-infusion SUVmax (rs = 0.806, P < 0.001) and moderately with the pre-infusion TLG (rs = 0.534, P < 0.001). Multinomial logistic regression analysis revealed that the pre-infusion value of SUVmax correlated with the risk of developing a higher grade of CRS (P < 0.001). CONCLUSION: In this group of DLBCL patients who underwent CAR T-cell therapy, SUVmax at M1, TLG at M1, and IPI were independent risk factors for PFS, and SUVmax at M1 and ∆SUVmax% for OS. Based on these indicators, two novel predictive models were established and verified the efficiency for evaluating PFS and OS. Moreover, pre-infusion SUVmax correlated with the severity of any subsequent CRS. We conclude that metabolic parameters measured using [18F]FDG PET/CT can identify DLBCL patients who will benefit most from CAR T-cell therapy, and the value before CAR T-cell infusion may predict its toxicity in advance.

Targeting Fn14 as a therapeutic target for cachexia reprograms the glycolytic pathway in tumour and brain in mice.

PURPOSE: Cachexia is a complex syndrome characterized by unintentional weight loss, progressive muscle wasting and loss of appetite. Anti-Fn14 antibody (mAb 002) targets the TWEAK receptor (Fn14) in murine models of cancer cachexia and can extend the lifespan of mice by restoring the body weight of mice. Here, we investigated glucose metabolic changes in murine models of cachexia via [18F]FDG PET imaging, to explore whether Fn14 plays a role in the metabolic changes that occur during cancer cachexia. METHODS: [18F]FDG PET/MRI imaging was performed in cachexia-inducing tumour models versus models that do not induce cachexia. SUVaverage was calculated for all tumours via volume of interest (VOI) analysis of PET/MRI overlay images using PMOD software. RESULTS: [18F]FDG PET imaging demonstrated increased tumour and brain uptake in cachectic versus non-cachectic tumour-bearing mice. Therapy with mAb 002 was able to reduce [18F]FDG uptake in tumours (P < 0.05, n = 3). Fn14 KO tumours did not induce body weight loss and did not show an increase in [18F]FDG tumour and brain uptake over time. In non-cachectic mice bearing Fn14 KO tumours, [18F]FDG tumour uptake was significantly lower (P < 0.01) than in cachectic mice bearing Fn14 WT counterparts. As a by-product of glucose metabolism, l-lactate production was also increased in cachexia-inducing tumours expressing Fn14. CONCLUSION: Our results demonstrate that Fn14 receptor activation is linked to glucose metabolism of cachexia-inducing tumours.

Identifying the primary tumour in patients with cancer of unknown primary (CUP) using [18F]FDG PET/CT: a systematic review and individual patient data meta-analysis.

PURPOSE: In this systematic review and individual patient data (IPD) meta-analysis, we analysed the diagnostic performance of [18F]FDG PET/CT in detecting primary tumours in patients with CUP and evaluated whether the location of the predominant metastatic site influences the diagnostic performance. METHODS: A systematic literature search from January 2005 to February 2024 was performed to identify articles describing the diagnostic performance of [18F]FDG PET/CT for primary tumour detection in CUP. Individual patient data retrieved from original articles or obtained from corresponding authors were grouped by the predominant metastatic site. The diagnostic performance of [18F]FDG PET/CT in detecting the underlying primary tumour was compared between predominant metastatic sites. RESULTS: A total of 1865 patients from 32 studies were included. The largest subgroup included patients with predominant bone metastases (n = 622), followed by liver (n = 369), lymph node (n = 358), brain (n = 316), peritoneal (n = 70), lung (n = 67), and soft tissue (n = 23) metastases, leaving a small group of other/undefined metastases (n = 40). [18F]FDG PET/CT resulted in pooled detection rates to identify the primary tumour of 0.74 (for patients with predominant brain metastases), 0.54 (liver-predominant), 0.49 (bone-predominant), 0.46 (lung-predominant), 0.38 (peritoneal-predominant), 0.37 (lymph node-predominant), and 0.35 (soft-tissue-predominant). CONCLUSION: This individual patient data meta-analysis suggests that the ability of [18F]FDG PET/CT to identify the primary tumour in CUP depends on the distribution of metastatic sites. This finding emphasises the need for more tailored diagnostic approaches in different patient populations. In addition, alternative diagnostic tools, such as new PET tracers or whole-body (PET/)MRI, should be investigated.

Outcome prediction based on [18F]FDG PET/CT in patients with pleural mesothelioma treated with ipilimumab and nivolumab +/- UV1 telomerase vaccine.

PURPOSE: The introduction of immunotherapy in pleural mesothelioma (PM) has highlighted the need for effective outcome predictors. This study explores the role of [18F]FDG PET/CT in predicting outcomes in PM treated with immunotherapy. METHODS: Patients from the NIPU trial, receiving ipilimumab and nivolumab +/- telomerase vaccine in second-line, were included. [18F]FDG PET/CT was obtained at baseline (n = 100) and at week-5 (n = 76). Metabolic tumour volume (MTV) and peak standardised uptake value (SUVpeak) were evaluated in relation to survival outcomes. Wilcoxon rank-sum test was used to assess differences in MTV, total lesion glycolysis (TLG), maximum standardised uptake value (SUVmax) and SUVpeak between patients exhibiting an objective response, defined as either partial response or complete response according to the modified Response Criteria in Solid Tumours (mRECIST) and immune RECIST (iRECIST), and non-responders, defined as either stable disease or progressive disease as their best overall response. RESULTS: Univariate Cox regression revealed significant associations of MTV with OS (HR 1.36, CI: 1.14, 1.62, p < 0.001) and PFS (HR 1.18, CI: 1.03, 1.34, p = 0.02), while multivariate analysis showed a significant association with OS only (HR 1.35, CI: 1.09, 1.68, p = 0.007). While SUVpeak was not significantly associated with OS or PFS in univariate analyses, it was significantly associated with OS in multivariate analysis (HR 0.43, CI: 0.23, 0.80, p = 0.008). Objective responders had significant reductions in TLG, SUVmax and SUVpeak at week-5. CONCLUSION: MTV provides prognostic value in PM treated with immunotherapy. High SUVpeak was not associated with inferior outcomes, which could be attributed to the distinct mechanisms of immunotherapy. Early reductions in PET metrics correlated with treatment response. STUDY REGISTRATION: The NIPU trial (NCT04300244) is registered at clinicaltrials.gov. https://classic. CLINICALTRIALS: gov/ct2/show/NCT04300244?cond=Pleural+Mesothelioma&cntry=NO&draw=2&rank=4.

EANM guidelines on the use of [18F]FDG PET/CT in diagnosis, staging, prognostication, therapy assessment, and restaging of plasma cell disorders.

We provide updated guidance and standards for the indication, acquisition, and interpretation of [18F]FDG PET/CT for plasma cell disorders. Procedures and characteristics are reported and different scenarios for the clinical use of [18F]FDG PET/CT are discussed. This document provides clinicians and technicians with the best available evidence to support the implementation of [18F]FDG PET/CT imaging in routine practice and future research.

Multicentric development and evaluation of [18F]FDG PET/CT and CT radiomic models to predict regional and/or distant recurrence in early-stage non-small cell lung cancer treated by stereotactic body radiation therapy.

PURPOSE: To develop machine learning models to predict regional and/or distant recurrence in patients with early-stage non-small cell lung cancer (ES-NSCLC) after stereotactic body radiation therapy (SBRT) using [18F]FDG PET/CT and CT radiomics combined with clinical and dosimetric parameters. METHODS: We retrospectively collected 464 patients (60% for training and 40% for testing) from University Hospital of Liège and 63 patients from University Hospital of Brest (external testing set) with ES-NSCLC treated with SBRT between 2010 and 2020 and who had undergone pretreatment [18F]FDG PET/CT and planning CT. Radiomic features were extracted using the PyRadiomics toolbox®. The ComBat harmonization method was applied to reduce the batch effect between centers. Clinical, radiomic, and combined models were trained and tested using a neural network approach to predict regional and/or distant recurrence. RESULTS: In the training (n = 273) and testing sets (n = 191 and n = 63), the clinical model achieved moderate performances to predict regional and/or distant recurrence with C-statistics from 0.53 to 0.59 (95% CI, 0.41, 0.67). The radiomic (original_firstorder_Entropy, original_gldm_LowGrayLevelEmphasis and original_glcm_DifferenceAverage) model achieved higher predictive ability in the training set and kept the same performance in the testing sets, with C-statistics from 0.70 to 0.78 (95% CI, 0.63, 0.88) while the combined model performs moderately well with C-statistics from 0.50 to 0.62 (95% CI, 0.37, 0.69). CONCLUSION: Radiomic features extracted from pre-SBRT analog and digital [18F]FDG PET/CT outperform clinical parameters in the prediction of regional and/or distant recurrence and to discuss an adjuvant systemic treatment in ES-NSCLC. Prospective validation of our models should now be carried out.

Prognostic value of baseline and interim [18F]FDG PET metabolic parameters in pediatric Hodgkin's lymphoma.

BACKGROUND: Hodgkin lymphoma (HL) in pediatric populations has a high survival rate but poses risks for long-term morbidities. Although [18F]fluoro­2­deoxy­2­d­glucose positron emission tomography ([18F]FDG PET) scans offer potential for improved risk stratification, the definitive prognostic value of quantitative [18F]FDG PET parameters remains unclear for pediatric HL. METHODS: A single-center, retrospective study included pediatric patients diagnosed with HL between 2016 and 2023 treated according to EuroNet-PHL-C1 and DAL/GPOH-HD protocols. Patients underwent baseline and interim PET/CT scans after two chemotherapy cycles. Event-free survival (EFS) was the primary endpoint, Deauville score was the secondary endpoint. Quantitative [18F]FDG PET parameters included SUVmax, metabolic tumor volume (MTV) and total lesion glycolysis (TLG) that were evaluated using two segmentation methods (SUV 2.5, 41% SUVmax). Survival outcomes were assessed using Cox regression analysis. RESULTS: A total of 115 patients (50 males, median age 14.2 years) were studied, with a median follow-up period of 35 months. During this period, 16 cases (13.9%) of relapse or progression were noted. Baseline and interim MTV 2.5, MTV 41%, TLG 2.5, and TLG 41%, along with interim SUVmax, were significantly associated with worse EFS and correlated with post-treatment Deauville scores. In multivariable analysis, interim MTV 2.5 > 0 ml (adj. hazard ratio, HR: 3.89, p = 0.009) and interim TLG 41% ≥ 30 g (adj. HR: 7.98, p = 0.006) were independent risk factors for EFS. CONCLUSION: Baseline and interim [18F]FDG PET parameters can serve as significant prognostic indicators for EFS and treatment response in pediatric HL. These quantitative measures could enhance individualized, risk-adapted treatment strategies for children and adolescents with HL.

Baseline [18F]FDG PET/CT and MRI first-order breast tumor features do not improve pathological complete response prediction to neoadjuvant chemotherapy.

PURPOSE: To verify the ability of pretreatment [18F]FDG PET/CT and T1-weighed dynamic contrast-enhanced MRI to predict pathological complete response (pCR) after neoadjuvant chemotherapy (NAC) in breast cancer (BC) patients. METHODS: This retrospective study includes patients with BC of no special type submitted to baseline [18F]FDG PET/CT, NAC and surgery. [18F]FDG PET-based features reflecting intensity and heterogeneity of tracer uptake were extracted from the primary BC and suspicious axillary lymph nodes (ALN), for comparative analysis related to NAC response (pCR vs. non-pCR). Multivariate logistic regression was performed for response prediction combining the breast tumor-extracted PET-based features and clinicopathological features. A subanalysis was performed in a patients' subsample by adding breast tumor-extracted first-order MRI-based features to the multivariate logistic regression. RESULTS: A total of 170 tumors from 168 patients were included. pCR was observed in 60/170 tumors (20/107 luminal B-like, 25/45 triple-negative and 15/18 HER2-enriched surrogate molecular subtypes). Higher intensity and higher heterogeneity of [18F]FDG uptake in the primary BC were associated with NAC response in HER2-negative tumors (immunohistochemistry score 0, 1 + or 2 + non-amplified by in situ hybridization). Also, higher intensity of tracer uptake was observed in ALN in the pCR group among HER2-negative tumors. No [18F]FDG PET-based features were associated with pCR in the other subgroup analyses. A subsample of 103 tumors was also submitted to extraction of MRI-based features. When combined with clinicopathological features, neither [18F]FDG PET nor MRI-based features had additional value for pCR prediction. The only significant predictors were estrogen receptor status, HER2 expression and grade. CONCLUSION: Pretreatment [18F]FDG PET-based features from primary BC and ALN are not associated with response to NAC, except in HER2-negative tumors. As compared with pathological features, no breast tumor-extracted PET or MRI-based feature improved response prediction.

Artificial intelligence-based, volumetric assessment of the bone marrow metabolic activity in [18F]FDG PET/CT predicts survival in multiple myeloma.

PURPOSE: Multiple myeloma (MM) is a highly heterogeneous disease with wide variations in patient outcome. [18F]FDG PET/CT can provide prognostic information in MM, but it is hampered by issues regarding standardization of scan interpretation. Our group has recently demonstrated the feasibility of automated, volumetric assessment of bone marrow (BM) metabolic activity on PET/CT using a novel artificial intelligence (AI)-based tool. Accordingly, the aim of the current study is to investigate the prognostic role of whole-body calculations of BM metabolism in patients with newly diagnosed MM using this AI tool. MATERIALS AND METHODS: Forty-four, previously untreated MM patients underwent whole-body [18F]FDG PET/CT. Automated PET/CT image segmentation and volumetric quantification of BM metabolism were based on an initial CT-based segmentation of the skeleton, its transfer to the standardized uptake value (SUV) PET images, subsequent application of different SUV thresholds, and refinement of the resulting regions using postprocessing. In the present analysis, ten different uptake thresholds (AI approaches), based on reference organs or absolute SUV values, were applied for definition of pathological tracer uptake and subsequent calculation of the whole-body metabolic tumor volume (MTV) and total lesion glycolysis (TLG). Correlation analysis was performed between the automated PET values and histopathological results of the BM as well as patients' progression-free survival (PFS) and overall survival (OS). Receiver operating characteristic (ROC) curve analysis was used to investigate the discrimination performance of MTV and TLG for prediction of 2-year PFS. The prognostic performance of the new Italian Myeloma criteria for PET Use (IMPeTUs) was also investigated. RESULTS: Median follow-up [95% CI] of the patient cohort was 110 months [105-123 months]. AI-based BM segmentation and calculation of MTV and TLG were feasible in all patients. A significant, positive, moderate correlation was observed between the automated quantitative whole-body PET/CT parameters, MTV and TLG, and BM plasma cell infiltration for all ten [18F]FDG uptake thresholds. With regard to PFS, univariable analysis for both MTV and TLG predicted patient outcome reasonably well for all AI approaches. Adjusting for cytogenetic abnormalities and BM plasma cell infiltration rate, multivariable analysis also showed prognostic significance for high MTV, which defined pathological [18F]FDG uptake in the BM via the liver. In terms of OS, univariable and multivariable analysis showed that whole-body MTV, again mainly using liver uptake as reference, was significantly associated with shorter survival. In line with these findings, ROC curve analysis showed that MTV and TLG, assessed using liver-based cut-offs, could predict 2-year PFS rates. The application of IMPeTUs showed that the number of focal hypermetabolic BM lesions and extramedullary disease had an adverse effect on PFS. CONCLUSIONS: The AI-based, whole-body calculations of BM metabolism via the parameters MTV and TLG not only correlate with the degree of BM plasma cell infiltration, but also predict patient survival in MM. In particular, the parameter MTV, using the liver uptake as reference for BM segmentation, provides solid prognostic information for disease progression. In addition to highlighting the prognostic significance of automated, global volumetric estimation of metabolic tumor burden, these data open up new perspectives towards solving the complex problem of interpreting PET scans in MM with a simple, fast, and robust method that is not affected by operator-dependent interventions.