Standardized Uptake Value Research Articles

Role of PET/CT in improving the cost effectiveness of nimotuzumab in nasopharyngeal carcinoma.

This study aims to use the maximum standardised uptake value (SUVmax) of 18F-fluorodeoxyglucose positron emission tomography to improve the cost effectiveness of nimotuzumab (NTZ) in locoregionally advanced nasopharyngeal carcinoma (LA-NPC). Two hundred and forty-eigh patients with LA-NPC, who met the inclusion criteria, were recruited from January 2012 to June 2019. The survival differences and independent factors were assessed using the Kaplan-Meier method and by Cox proportional hazards regression analysis. A cost effectiveness analysis was performed. The optimal cut-off value for SUVmax was 12.92. Multivariable analysis indicated a prognostic significance of overall survival (OS) for the NTZ treatment (p = 0.023) and SUVmax (p = 0.014). The exploratory subgroup survival analysis revealed that LA-NPC patients with SUVmax > 12.92 treated with concurrent chemoradiotherapy (CCRT) and NTZ had a significantly improved 3-year OS compared to patients treated with CCRT alone (96.2 vs 73.2%, p = 0.047). Furthermore, the treatment cost for NTZ was $6,317.61. This incurred an additional cost of $274.68 for every 1% increase in OS. For patients with LA-NPC with SUVmax > 12.92, the addition of NTZ to CCRT can improve OS and is cost effective.

Prognostic significance of fludeoxyglucose positron emission tomography delta radiomics following bridging therapy in patients with large B-cell lymphoma undergoing CAR T-cell therapy.

Bridging radiation therapy (bRT) is increasingly being utilized prior to chimeric antigen receptor (CAR) T-cell therapy for large B-cell lymphoma (LBCL). It is unknown how the extent of cytoreduction during bRT impacts outcomes. We retrospectively reviewed patients with LBCL treated with bRT followed by CAR T-cell therapy. Metabolic tumor volume (MTV), maximum standardized uptake value (SUVmax), SUVmean, and total lesion glycolysis (TLG) were extracted from F18-fluorodeoxyglucose positron emission tomography (PET) scans acquired prior to bRT and between completion of bRT and CAR T-cell infusion. Delta radiomics based on changes of these values were then calculated. The association between delta radiomics and oncologic outcomes [progression-free survival (PFS), freedom from distant progression (FFDP), and local control (LC)] were then examined. Thirty-three sites across 23 patients with LBCL were irradiated. All metabolically active disease was treated in 10 patients. Following bRT, median overall decreases (including unirradiated sites) in MTV, SUVmax, SUVmean, and TLG were 22.2 cc (63.1%), 8.9 (36.8%), 3.4 (31.1%), and 297.9 cc (75.8%), respectively. Median decreases in MTV, SUVmax, SUVmean, and TLG in irradiated sites were 15.6 cc (91.1%), 17.0 (74.6%), 6.8 (55.3%), and 157.0 cc (94.6%), respectively. Median follow-up was 15.2 months. A decrease in SUVmax of at least 54% was associated with improved PFS (24-month PFS: 83.3% vs. 28.1%; p = 0.037) and FFDP (24-month FFDP: 100% vs. 62.4%; p < 0.001). A decrease in MTV of at least 90% was associated with improved FFDP (24-month FFDP: 100% vs. 62.4%; p < 0.001). LC was improved in sites with decreases in SUVmax of at least 71% (24-month LC: 100% vs. 72.7%; p < 0.001). Decreases of MTV by at least 90% (100% vs. 53.3%; p = 0.038) and TLG by at least 95% (100% vs. 56.3%; p = 0.067) were associated with an improved complete response rate. bRT led to substantial reductions in MTV, SUVmax, SUVmean, and TLG. The relative extent of these decreases correlated with improved outcomes after CAR T-cell infusion. Prospective cohorts should validate the value of interim PET following bRT for quantifying changes in disease burden and associated prognosis.

Visual reading for [18F]Florzolotau Tau PET scans in progressive supranuclear palsy.

The identification of tau accumulation within living brains holds significant potential in facilitating accurate diagnosis of progressive supranuclear palsy (PSP). While visual assessment is frequently employed, standardized methods for tau positron emission tomography (PET) specifically in PSP are absent. We aimed to develop a visual reading algorithm dedicated to the evaluation of [18F]Florzolotau PET in PSP. 148 PSP and 30 healthy volunteers were divided into a development set (for the establishment of the reading rules; n = 89) and a testing set (for the validation of the reading rules; n = 89). For differential diagnosis, 55 α-synucleinopathies were additionally included into the testing set. The visual reading method was established by an experienced assessor (Reader 0) and was then validated by Reader 0 and two additional readers on regional and overall binary manners. A positive binding in both midbrain and globus pallidus/putamen regions was characterized as a PSP-like pattern, whereas any other pattern was classified as non-PSP-like. Reader 1 (94.4%) and Reader 2 (93.8%) showed excellent agreement for the overall binary determination against Reader 0. The regional binary determinations of midbrain and globus pallidus/putamen showed excellent agreement among readers (kappa > 0.80). The overall binary evaluation demonstrated reproducibility of 86.1%, 94.4% and 77.8% for three readers. The visual reading algorithm showed high agreement with regional standardized uptake value ratios and clinical diagnoses. Through the application of the suggested visual reading algorithm, [18F]Florzorotau PET imaging demonstrated a robust performance for the imaging diagnosis of PSP.

Predicting regional tau accumulation with machine learning‐based tau‐PET and advanced radiomics

AbstractINTRODUCTIONAlzheimer's disease is partially characterized by the progressive accumulation of aggregated tau‐containing neurofibrillary tangles. Although the association between accumulated tau, neurodegeneration, and cognitive decline is critical for disease understanding and clinical trial design, we still lack robust tools to predict individualized trajectories of tau accumulation. Our objective was to assess whether brain imaging biomarkers of flortaucipir‐positron emission tomography (PET), in combination with clinical and genomic measures, could predict future pathological tau accumulation.METHODSWe quantified the disease profile of participants (N = 276) using a comprehensive set of descriptors, including clinical/demographic (age, diagnosis, amyloid status, sex, race, ethnicity), genetic (apolipoprotein E [APOE]‐ε4), and flortaucipir‐PET imaging measures (regional flortaucipir standardized uptake value ratio [SUVr] and comprehensive radiomic texture features extracted from Automated Anatomical Labeling template regions). We trained an AdaBoost machine learning algorithm in a 2:1 split train‐test configuration to derive a prognostic index that (i) stratifies individualized brain regions including global (AD‐signature region) and lobar regions (frontal, occipital, parietal, temporal) into stable/slow‐ and fast‐progressors based on future tau accumulation, and (ii) forecasts individualized regional annualized‐rate‐of‐change in flortaucipir‐PET SUVr. Further, we developed an adaptive model incorporating flortaucipir‐PET measurements from the baseline and intermediate timepoints to predict annualized‐rate‐of‐change.RESULTSIn binary classification for predicting stable/slow‐ versus fast‐progressors, the area‐under‐the‐receiver‐operating‐characteristic curve was 0.86 in the AD‐signature region and 0.83, 0.82, 0.84, and 0.83 in frontal, occipital, parietal, and temporal regions, respectively. The trained models successfully predicted annualized‐rate‐of‐change of flortaucipir‐PET regional flortaucipir SUVr in AD‐signature and lobar regions (Pearson‐correlation [R]: AD‐signature = 0.73; frontal = 0.73; occipital = 0.71; parietal = 0.70; temporal = 0.69). The models’ performance in predicting annualized‐rate‐of‐change slightly increased when imaging features from intermediate timepoints were used in the adaptive setting (R: AD‐signature = 0.79; frontal = 0.87; occipital = 0.83; parietal = 0.74; temporal = 0.82).DISCUSSIONTaken together, our results propose a robust approach to predict future tau accumulation that may improve the ability to enroll, stratify, and gauge efficacy in clinical trial participants.Highlights Machine learning predicts the future rate of tau accumulation in Alzheimer's disease. Tau prediction in lobar/global regions benefits from diverse multimodal features. This prognostic index can serve as a sensitive tool for patient stratification.

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.

EP.07G.05 Maximum Standardized Uptake Value and Cell-Free DNA to Predict Adjuvant Therapy in Resectable Non-Small Cell Lung Cancer

EP.07G.05 Maximum Standardized Uptake Value and Cell-Free DNA to Predict Adjuvant Therapy in Resectable Non-Small Cell Lung Cancer

Outcomes for high-risk defining events in follicular lymphoma following frontline immunochemotherapy

Progression of follicular lymphoma (FL) or transformation (tFL) within 24 months of immunochemotherapy (ICT) represent high-risk defining events (HRDE) with poor overall survival (OS). We examined baseline clinical characteristics, imaging and outcomes for patients experiencing HRDE in an international retrospective cohort of newly diagnosed FL patients requiring ICT. We defined HRDE groups as: relapse or progression of FL within 24 months (FL24); Early TFL (transformation <24 months of ICT); Late TFL (transformation >24 months of ICT). 433 patients were categorised: reference FL n=352 (no HRDE), FL24 n=43, Early TFL n=29, or Late TFL n=9. Chemotherapy regimens included bendamustine (63%), CHOP (27%) or CVP (10%); 85% received rituximab/15% obinutuzumab and 48% received maintenance therapy. Compared to the reference FL group, OS from HRDE was inferior for FL24 (HR 3.93, 95% CI 2.14-7.23), Early TFL (HR 8.16, 95% CI 4.38-15.2) and Late TFL (HR 8.23, 95% CI 3.18-21.25). OS from HRDE was inferior for Early TFL compared to FL24 (HR 2.08, 95% CI 1.02-4.21). In multivariable analysis, baseline performance status, elevated lactate dehydrogenase, elevated beta-2-microglobulin and grade 3A were associated with Early TFL. Clinical characteristics were not able to differentiate Early TFL from FL24. Standardised uptake value max was higher in Early TFL but not FL24 compared to reference FL. Early TFL and FL24 represent different HRDEs in FL after ICT and are associated with inferior OS. Distinguishing between early TFL and FL24 is important for biomarker development, management and to develop and interpret clinical trials in this area of unmet need.

Maximum standardised uptake value of positron emission tomography as a predictor of oesophageal cancer outcomes

ObjectivesThis study aimed to analyse the value of pre-operative 18F-fluorodeoxyglucose positron emission tomography (PET)-computed tomography that can predict tumour pathological complete response, tumour histology grade, overall survival, and recurrence-free survival in patients with locally advanced oesophageal squamous cell carcinoma who underwent neoadjuvant chemoradiotherapy (NCRT) followed by surgery.MethodsWe retrospectively reviewed the cases of patients with locally advanced oesophageal squamous cell carcinoma undergoing NCRT followed by surgery. Patients who did not undergo PET within 3 months of surgery were excluded. We set a pre-operative PET maximum standardised uptake value (SUVmax) of > 5 as the threshold and classified the patients into two groups. We analysed the tumour response and histology grade, and compared the overall survival and recurrence-free survival between the two groups.ResultsThis cohort included 92 patients with oesophageal squamous cell carcinoma who underwent NCRT followed by surgery; 49 patients had a pre-operative PET SUVmax < 5, and 43 patients had a pre-operative PET SUVmax > 5. The patients’ pre-operative PET SUVmax correlated with tumour histology, ypT stage, and tumour response. Patients with a pre-operative SUVmax < 5 had better 2-year-overall survival (78% vs. 62%, P < 0.05) and 2-year recurrence-free survival (62% vs. 34%, P < 0.05) than those with a pre-operative SUV > 5.ConclusionsPre-operative SUVmax may be useful to predict tumour response, survival, and recurrence in patients with locally advanced oesophageal squamous cell carcinoma who undergo NCRT followed by surgery.

The relationship between sarcopenia and metabolic parameters of 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) and the prognostic value of sarcopenia in early-stage non-small cell lung cancer.

Patients with lung cancer face a heightened risk of developing sarcopenia. Despite this known risk, the impact of sarcopenia on the long-term prognosis of lung cancer patients, specifically concerning progression-free survival (PFS) and overall survival (OS), remains unclear. The primary objective of our study was to examine the correlation between metabolic parameters derived from 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) and sarcopenia, as well as the prognostic value of sarcopenia in patients with surgically resected early-stage non-small cell lung cancer (NSCLC). In this retrospective cross-sectional study, we analyzed 187 NSCLC patients who underwent 18F-FDG PET/CT at the First Affiliated Hospital of Soochow University between March 2019 and October 2023. Patients were divided into two groups based on the presence (n=46) or absence (n=141) of sarcopenia. The correlation between sarcopenia, metabolic parameters, and patient characteristics was evaluated using chi-square and Mann-Whitney U tests. Survival analyses, including PFS and OS, were conducted using Kaplan-Meier analysis and Cox proportional hazards regression. Based on sarcopenia, metabolic parameters and patient characteristics, patients were classified into high-risk (n=28), intermediate-risk (n=121), and low-risk (n=38) groups. Our analysis identified gender, body mass index (BMI), psoas Hounsfield unit (HU), and maximum standardized uptake value of the psoas major muscle (SUVmax-Muscle) as independent predictors of sarcopenia (P<0.05 for all). A nomogram model, utilizing these parameters, was constructed to predict sarcopenia. Survival analysis further demonstrated that total lesion glycolysis [hazard ratio (HR) =2.499; 95% confidence interval (CI): 2.014-3.267; P=0.016], sarcopenia (HR =3.323; 95% CI: 1.748-6.316; P<0.001), and programmed death ligand-1 (PD-L1) expression (HR =0.093; 95% CI: 0.012-0.698; P=0.021) emerged as independent predictors of OS in early-stage NSCLC. Notably, patients categorized as high-risk, characterized by elevated total lesion glycolysis, presence of sarcopenia, and PD-L1 positivity, exhibited a significantly poorer prognosis compared to the intermediate-risk (P<0.05) and low-risk groups (P<0.05). Our findings indicated an inverse relationship between SUVmax-Muscle or psoas HU with the incidence of sarcopenia in NSCLC patients. Additionally, total lesion glycolysis, sarcopenia, and PD-L1 expression were identified as independent prognostic factors for OS in early-stage NSCLC. The risk stratification model, incorporating total lesion glycolysis, sarcopenia, and PD-L1 expression, assumed a pivotal role in guiding personalized therapy decisions and post-treatment monitoring.

Clinicopathologic and genomic features associated with brain metastasis after resection of lung adenocarcinoma

ObjectiveTo identify clinicopathologic and genomic features associated with brain metastasis after resection of lung adenocarcinoma (LUAD) and to evaluate survival after brain metastasis. MethodsPatients who underwent complete resection of stage I-IIIA LUAD between 2011 and 2020 were included. A subset of patients had broad-based panel next-generation sequencing performed on their tumors. Fine-Gray models for the development of brain metastasis were constructed, with death without brain metastasis as a competing risk. ResultsA total of 2660 patients were included. The median duration of follow-up was 71 months (95% confidence interval [CI], 69-73 months). The cumulative incidence of brain metastasis at 10 years was 9.8%. Among patients who developed a brain metastasis, the median time from surgery to brain metastasis was 21 months (interquartile range, 10-42 months). Higher maximum standardized uptake value of the primary tumor, neoadjuvant therapy, lymphovascular invasion, and stage III disease were associated with the development of brain metastasis. Among patients who underwent next-generation sequencing, a multivariable analysis identified neoadjuvant therapy, pathologic stage, and TP53 mutations as associated with development of brain metastasis. The median survival after brain metastasis was 18 months (95% CI, 13-24 months). Better performance status, lack of extracranial metastasis, stereotactic radiosurgery, and targeted therapy were associated with better survival after brain metastasis. ConclusionsBrain metastasis is common after complete resection of LUAD and often occurs within 2 years. Markers of aggressive tumor biology, including higher maximum standardized uptake value, lymphovascular invasion, and TP53 mutations, and neoadjuvant therapy are associated with brain metastasis.

73 - Residual/recurrent nasopharyngeal carcinoma and nasopharyngeal lymphoma: Dual-parameters differentiation based on apparent diffusion coefficient and standardized uptake value of 18F-FDG PET/MRI

73 - Residual/recurrent nasopharyngeal carcinoma and nasopharyngeal lymphoma: Dual-parameters differentiation based on apparent diffusion coefficient and standardized uptake value of 18F-FDG PET/MRI

Establishing a predictive model for tumor mutation burden status based on 18F-FDG PET/CT and clinical features of non-small cell lung cancer patients.

Tumor mutation burden (TMB) has emerged as a promising biomarker for immune checkpoint inhibitors (ICI) response, but its detection through whole exome sequencing (WES) is costly and invasive. This study aims to establish a predictive model for TMB using baseline metabolic parameters (MPs) of 18F-fluorodeoxyglucose (FDG) uptake on positron emission tomography/computed tomography (PET/CT) and clinical features in non-small cell lung cancer (NSCLC) patients, potentially offering a non-invasive and cost-effective method to predict TMB status. A total of 223 NSCLC patients with baseline 18F-FDG PET/CT scans and TMB detection results were retrospectively enrolled from January 2019 to September 2023, and were divided into two groups: TMB-high (≥4 mutations/Mb, 96 patients) and TMB-low (<4 mutations/Mb, 127 patients). Twelve clinical features and five PET parameters were assessed. Univariate analysis was conducted in all patients to reveal the preliminary associations between variables and TMB status. All patients were randomly divided into a training set (n=135) and a validation set (n=88). Feature selection was performed using lasso regression and logistic regression analyses. A predictive model and nomogram were established with the features selected above. Decision curve analysis (DCA) was performed to assess the clinical utility of the developed model. Two clinical features and two PET parameters were identified through lasso regression and logistic regression analysis including pathology type, cancer antigen 125 (CA125) level, maximum standardized uptake value (SUVmax), and metabolic tumor volume (MTV). The predictive model exhibited an area under the curve (AUC) of 0.822 [95% confidence interval (CI), 0.751-0.894], and internal validation yielded an AUC of 0.822 (95% CI, 0.731-0.912). The model was well-calibrated. The developed nomogram, incorporating the four selected variables, showed promising potential in evaluating TMB status in NSCLC patients. In this study, a predictive model combining 18F-FDG PET/CT and clinical features of NSCLC patients effectively distinguished between TMB-high and TMB-low status. The nomogram generated from this model holds significant promise for predicting TMB status, offering valuable insights for clinical decision-making.

End-to-end [18F]PSMA-1007 PET/CT radiomics-based pipeline for predicting ISUP grade group in prostate cancer.

To develop an end-to-end radiomics-based pipeline for the prediction of International Society of Urological Pathology grade group (ISUP GG) in prostate cancer (PCa). This retrospective study includes 356 patients (241 in training set and 115 in independent test set) with histopathologically confirmed PCa who underwent [18F]PSMA-1007 PET/CT scan. Patients were classified into two groups according to their ISUP GG (1-3 vs. 4-5). Radiomics features were extracted from the whole, automatically segmented prostate on PET/CT images, 30 models were constructed by combining 6 feature selection algorithms and 5 machine learning classifiers. The clinical model incorporated age, total prostate-specific antigen (tPSA), maximum standardized uptake value (SUVmax), and prostate volume. The predictive performance of the models was evaluated using the area under the receiver operating characteristic curve (AUC), balanced accuracy (bAcc), and decision curve analysis (DCA). The best-performing radiomics model significantly outperformed clinical model (AUC 0.879 ± 0.041 vs. 0.799 ± 0.051, bAcc 0.745 ± 0.074 vs. 0.629 ± 0.045). On an external independent test set, best-performing radiomics model perform better than clinical model, with an AUC of 0.861 vs. 0.750, p = 0.002 (Delong), and bAcc of 0.764 vs. 0.582, p = 0.043 (McNemar). The learning curve, calibration curve and DCA demonstrated goodness-of-fit and improved benefits in clinical practice. The end-to-end radiomics-based pipeline is an effective non-invasive tool to predict ISUP GG in PCa.

Lymph nodes rather than pleural metabolic activity in 18F-FDG PET/CT correlates with malignant pleural effusion recurrence in advanced non-small cell lung cancer.

Frequently recurrent malignant pleural effusion (MPE) significantly hampers the life quality of advanced non-small cell lung cancer (NSCLC) patients. We aimed to explore the effects of progression patterns and local intervention on MPE recurrence and apply fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) to establish a predictive model for MPE recurrence in NSCLC. We retrospectively recruited two cohorts of patients including treatment-naïve NSCLC diagnosed with MPE at the onset and receiving PET/CT scanning, as well as those with MPE and undergoing first-line epidermal growth factor receptor (EGFR)-tyrosine kinase inhibitor (TKI) treatment. Pleural maximum standardized uptake value (SUVmax), metabolic tumor burden (MTV), total lesion glycolysis (TLG), and uptake patterns as well as SUVmax of lymph nodes (LN) were extracted. The primary outcome was MPE recurrence defined as re-accumulation of cytologically proven ipsilateral MPE. Step-wise multivariate Cox regression was used to identify candidate variables. Cox regression analysis and random survival forest were applied to establish models. A total of 148 treatment-naïve patients with EGFR-TKI treatment and MPE were recruited during the median follow-up period of 683 days, with 69 (46.6%) and 35 (23.6%) witnessing MPE recurrence at least once and twice. Intrapleural perfusion therapy at first recurrence was a protective factor for the second MPE recurrence (P=0.006), while intrapleural perfusion therapy at baseline could not benefit the first MPE recurrence (P=0.14). Conversely, prior systemic progression indicative of the change of systemic treatment was a protective factor for time to the first MPE recurrence (P<0.001); instead, the change of systemic treatment at the first MPE recurrence was not associated with second MPE recurrence (P=0.53). In another cohort with treatment-naïve NSCLC patients with MPE and PET/CT scanning, 103 patients regardless of the actionable mutation status were recruited during the median follow-up period of 304 days. Multivariate analysis suggested that the LN SUVmax >4.50 g/mL [hazard ratio (HR), 2.54; P=0.01], female gender (HR, 0.40; P=0.01), bone metastases (HR, 3.16; P=0.001), and systemic treatment (targeted therapy vs. chemotherapy: HR, 0.32; P=0.002; immunotherapy therapy vs. chemotherapy: HR, 0.99; P=0.97) could collectively indicate MPE recurrence with an optimal 300-day area under the curve (AUC) of 0.83. For patients with actionable mutation, LN SUVmax >4.50 g/mL (P=0.02) could forecast MPE recurrence independently. In summary, LN rather than pleural metabolic activity or uptake patterns could predict MPE recurrence for patients with or without targeted therapy. We should re-consider the application of intrapleural perfusion treatment for first-onset MPE and prompt it more at the moment of recurrent MPE. Promisingly, we could probably apply the non-invasive tool to identify the risk factors for MPE recurrence.

18F-FDG PET/CT biomarkers as predictors of long term outcomes and survival rates in patients with high risk malignant pulmonary masses/nodules treated with stereotactic ablative radiotherapy.

Stereotactic ablative body radiotherapy (SABR) is a standard treatment option for patients with malignant pulmonary masses (including primary and metastatic lesions) who are unfit for surgery or who are medically operable but refuse surgery. Flourine-18 flurodeoxyglucose positron emission tomography (18F-FDG PET) volumetric metabolic parameters, i.e., metabolic tumour volume (MTV) and total lesion glycolysis (TLG) play an important role in assessing the biological characteristics of some tumours and its role as potential prognostic factors has also been introduced. The aim of this retrospective study is to assess the value of baseline metabolic volumetric parameters as prognostic imaging biomarkers in patients with pulmonary masses/nodules treated with SABR. 70 patients were included in this retrospective study (39 male and 31 female, age range 47-91years, mean 76years). Standardized uptake value (SUVmax), SUVmean, MTV and TLG for all the patients were calculated on baseline 18F-FDG PET/CT. Patient outcome was divided into 3 categories free of disease, stable disease and disease progression. There was no significant statistical difference in the SUVmax and SUVmean in all the three categories. Mean SUVmax ranges from 7.13 to 8.08 with its highest value in the stable disease and lowest value in the progressive disease categories. Similarly, the average SUVmean was 4.9 in the free of disease category and 4.68 in the progressive disease category. MTV and TLG were low in the free of disease and the highest in progressive disease. MTV increased from 2.25 cm3 in free of disease category to 3.23 cm3 and 7.29 cm3 in stable disease and progressive disease, respectively. TLG has increased from 11.7 in the disease-free survival category to 18.77 and 40.39 in the stable and progressive disease, respectively. Patients with low MTV had longer overall survival (OS) than patients with high MTV (37months versus 27months, p value = 0. 0018). In addition, OS was longer in patients with low TLG (36months versus 24months, p value = 0.016). TLG and MTV are more useful than SUVmax and SUVmean for predicting outcome, OS and progression-free survival (PFS) in patients receiving SABR. The TLG and MTV measurement on 18F-FDG PET imaging may be routinely recommended in baseline 18F-FDG PET/CT prior to SABR.

Predicting standardized uptake value of brown adipose tissue from CT scans using convolutional neural networks.

The standard method for identifying active Brown Adipose Tissue (BAT) is [18F]-Fluorodeoxyglucose ([18F]-FDG) PET/CT imaging, which is costly and exposes patients to radiation, making it impractical for population studies. These issues can be addressed with computational methods that predict [18F]-FDG uptake by BAT from CT; earlier population studies pave the way for developing such methods by showing some correlation between the Hounsfield Unit (HU) of BAT in CT and the corresponding [18F]-FDG uptake in PET. In this study, we propose training convolutional neural networks (CNNs) to predict [18F]-FDG uptake by BAT from unenhanced CT scans in the restricted regions that are likely to contain BAT. Using the Attention U-Net architecture, we perform experiments on datasets from four different cohorts, the largest study to date. We segment BAT regions using predicted [18F]-FDG uptake values, achieving 23% to 40% better accuracy than conventional CT thresholding. Additionally, BAT volumes computed from the segmentations distinguish the subjects with and without active BAT with an AUC of 0.8, compared to 0.6 for CT thresholding. These findings suggest CNNs can facilitate large-scale imaging studies more efficiently and cost-effectively using only CT.

Better survival with lobectomy versus sublobar resection in patients with hypermetabolic c-stage IA lung cancer on positron emission tomography/computed tomography.

The clinical trial showed that sublobar resection was not inferior to lobectomy in terms of disease-free survival in patients with peripherally located non-small-cell lung cancer ≤2 cm. However, it is not clear whether sublobar resection is indicated for all types of c-stage IA lung cancer. The purpose of this study was to clarify whether sublobar resection is indicated for c-stage IA hypermetabolic lung cancer. Patients with c-stage IA lung cancer who underwent F-18 fluorodeoxyglucose positron emission tomography/computed tomography and lobectomy or sublobar resection were assessed. Of these, patients who had a maximum standardized uptake value ≥3.0 on positron emission tomography/computed tomography were evaluated. We compared survival rates after lobectomy versus sublobar resection. Propensity score matching was performed to balance patient characteristics between groups. Between April 2004 and March 2023, 723 patients underwent lobectomy or sublobar resection and had a maximum standardized uptake value ≥3.0 on positron emission tomography/computed tomography. Lobectomy and sublobar resection were performed in 532 (73.6%) and 191 (26.4%) patients, respectively. Both the 5-year overall and disease-free survival rates were worse after sublobar resection compared with lobectomy (62.3% vs 79.9% and 53.9% vs 70.3%, respectively). After propensity score matching, the 5-year overall and disease-free survival rates remained worse after sublobar resection compared with lobectomy (60.7% vs 75.2% and 51.6% vs 67.7%, respectively). Patients with c-stage IA hypermetabolic lung cancer with standardized uptake value ≥3.0 on positron emission tomography/computed tomography had a worse prognosis after sublobar resection than after lobectomy.

Assessing osteoporosis and bone mineral density through 18F-NaF uptake at lumbar spine.

The use of 18F-Sodium fluoride (NaF) PET/CT is established in the detection of metastatic bone disease, yet its utility in osteoporosis remains underexplored. This research aims to assess the variations in 18F-NaF uptake among individuals with differing bone mineral density (BMD) and to examine the relationship between 18F-NaF uptake and BMD. In this retrospective study, 199 patients (average age 56 ± 6, comprising 52 males and 147 females) with a history of cancer were analyzed. Each participant underwent both 18F-NaF PET/CT and lumbar dual-energy X-ray absorptiometry (DXA) scans within a span of 7days. Based on DXA outcomes, patients and their lumbar vertebrae were categorized into normal BMD, osteopenia, and osteoporosis groups. The lumbar 18F-NaF uptake across these groups were compared, and to explore the association between lumbar standardized uptake values (SUV) values and BMD. The efficacy of 18F-NaF uptake in diagnosing osteoporosis or osteopenia was also evaluated. Analysis was conducted using Mann-Whitney U tests, Spearman regression, and receiver operating characteristic (ROC) curve analysis through GraphPad Prism 10.0. A total of 796 lumbar vertebrae from 199 patients were measured. It was observed that osteoporotic patients had significantly lower 18F-NaF uptake than those with osteopenia and normal BMD across the L1-L4 lumbar vertebrae (P < 0.0001). In a vertebra-based analysis, normal BMD vertebrae exhibited the highest maximum SUV(SUVmax) compared to osteopenic (8.13 ± 1.28 vs. 6.61 ± 1.01, P < 0.0001) and osteoporotic vertebrae (8.13 ± 1.28 vs. 4.82 ± 1.01, P < 0.0001). There was a positive correlation between lumbar 18F-NaF uptake and BMD across all vertebrae, with correlation coefficients exceeding 0.5 (range: 0.57-0.8). The area under the ROC curve values were notably high, at 0.96 for osteoporosis and 0.83 for osteopenia diagnosis. This study demonstrates distinct 18F-NaF uptake patterns among individuals with varying BMD levels, with a positive correlation between 18F-NaF uptake and BMD. These findings highlight the potential of 18F-NaF PET/CT as a supportive diagnostic method in the management of osteoporosis.

Clinical value of 18F-FDG PET/CT in patients with newly diagnosed acute leukemia.

To explore the correlation between semi-quantitative parameters of 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) scans findings and the clinical features of patients with acute leukemia (AL), as well as to evaluate the clinical utility of 18F-FDG PET/CT in the management of AL. A retrospective study was conducted with 44 patients newly diagnosed with acute leukemia (AL) at Zhongnan Hospital of Wuhan University between January 2019 and August 2024. Multivariate analysis revealed that age at diagnosis of AL (odds ratio [OR]: 0.888, P < 0.01) and percentage of blasts in the peripheral blood (PB) (OR: 1.061, P < 0.05) were independent predictors of the appearance of active extramedullary disease (EMD). Kaplan-Meier survival analysis for patients with EMD(+) indicated that those with organ infiltration beyond the lymph nodes experienced markedly reduced overall survival (OS) compared to those without such infiltration (157 days and 806 days, respectively). Furthermore, in the AL subgroup with EMD, the ratio of the maximum standardized uptake value (SUVmax) in the bone marrow (BM) to SUVmax of the liver emerged as an independent prognostic factor for OS (Hazard ratio [HR]: 2.372; 95% confidence interval [CI]: 1.079-5.214, P < 0.05). 18F-FDG PET/CT offers the benefits of being non-invasive and highly sensitive for the thorough evaluation of disease status in patients newly diagnosed with AL. Furthermore, the SUVmax BM/liver ratio is of significant clinical importance for prognosticating outcomes in patients with AL presenting EMD.

Do Tau Deposition and Glucose Metabolism Dissociate in Alzheimer's Disease Trajectory?

Tau aggregation demonstrates close associations with hypometabolism in Alzheimer's disease (AD), although differing pathophysiological processes may underlie their development. To establish whether tau deposition and glucose metabolism have different trajectories in AD progression and evaluate the utility of global measures of these pathological hallmarks in predicting cognitive deficits. 279 participants with amyloid-β (Aβ) status, and T1-weighted MRI scans, were selected from the Alzheimer's Disease Neuroimaging Initiative (http://adni.loni.usc.edu). We created the standard uptake value ratio images using Statistical Parametric Mapping 12 for [18F]AV1451-PET (tau) and [18F]FDG-PET (glucose metabolism) scans. Voxel-wise group and single-subject level SPM analysis evaluated the relationship between global [18F]FDG-PET and [18F]AV1451-PET depending on the Aβ status. Linear models assessed whether tau deposition or glucose metabolism better predicted clinical progression. There was a dissociation between global cerebral glucose hypometabolism and global tau load in amyloid-positive AD and amyloid-negative mild cognitive impairment (MCI) (p > 0.05). Global hypometabolism was only associated with global cortical tau in amyloid-positive MCI. Voxel-level single subject tau load better predicted neuropsychological performance, Alzheimer's disease assessment scale-cognitive (ADAS-Cog) 13 score, and one-year change compared with regional and global hypometabolism. A dissociation between tau pathology and glucose metabolism at a global level in AD could imply that other pathological processes influence glucose metabolism. Furthermore, as tau is a better predictor of clinical progression, these processes may have independent trajectories and require independent consideration in the context of therapeutic interventions.