Background/Objectives: Immune checkpoint blockade targeting the PD-1/PD-L1 axis is a standard treatment for urothelial carcinoma (UC), but 20–30% of patients develop resistance. The underlying mechanisms, particularly regarding tumor microenvironment metabolic reprogramming, remain unclear. Methods: We performed single-cell RNA sequencing on pre-treatment tumors from eight pembrolizumab-treated UC patients (three responders, five non-responders). Bioinformatic analyses included cell clustering, pathway enrichment, and cell–cell communication, validated using public datasets. Functional experiments involved SGPL1 knockdown in MB49 cells and a syngeneic PD-1-resistant murine model (MB49-R5). Results: Responders exhibited a higher proportion of infiltrating T-cells. Unexpectedly, CD4+ subsets, rather than CD8+ cells, were numerically enriched in responders. However, all T-cell subsets in responders demonstrated enhanced oxidative phosphorylation-dominant metabolic activity. Enhanced macrophage–T-cell crosstalk was observed, with macrophages exhibiting M1-like polarization driven by CD4+ T-cell-derived IFN-γ and CD40L signaling. In contrast, non-responders displayed dominant tumor-derived MIF–CD74 signaling and M2 polarization. Integration of public datasets identified SGPL1 as a key metabolic regulator associated with poor prognosis and reduced immune activation. Functional experiments demonstrated that SGPL1 knockdown inhibited tumor proliferation and restored anti-PD-1 sensitivity, accompanied by increased T-cell infiltration. Conclusions: T-cell metabolic activation drives anti-PD-1 responses in UC, and CD4+ T-cell-mediated M1 polarization and tumor-intrinsic SGPL1 crucially shape therapeutic outcomes, highlighting SGPL1 as a candidate metabolic target to overcome PD-1 resistance.

Relapsed refractory primary central nervous system lymphoma (R/R PCNSL) has no recognized optimal therapy due to its grave prognosis and high mortality. This report describes a 69-year-old patient with primary central nervous system lymphoma (PCNSL) who rapidly relapsed after achieving complete remission (CR) on first-line treatment and subsequently received treatment with glofitamab to achieve CR again. Grade 1 cytokine release syndrome was observed and there were no fatal side effects. However, limited reports on glofitamab therapy are applied for relapsed and refractory PCNSL. Further ex vivo data demonstrated that glofitamab drove T cell activation and killing ability against lymphoma cells. Our study suggested that glofitamab may be a viable option for relapsed PCNSL patients.

Abstract A 68-year-old man with chest tightness underwent cardiac blood perfusion imaging on total-body 13N-NH3 PET/CT. Incidentally, mildly increased 13N-NH3 activity was observed in the left side of the body of the tongue. Pathological diagnosis proved to be mucosal squamous cell carcinoma.

Background Previous studies have demonstrated that delayed [ 68 Ga]Ga-PSMA PET/CT imaging improves lesion detection compared to early [ 68 Ga]Ga-PSMA PET/CT in patients with prostate cancer. However, the sole use of delayed [ 68 Ga]Ga-PSMA PET/CT has been limited due to the insufficient number of photons obtained with standard PET/CT scanners. The combination of early and delayed [ 68 Ga]Ga-PSMA standard PET/CT may be considered, and it is challenging to incorporate into a high-demand clinical setting. Long field-of-view (LFOV) PET/CT scanners have higher sensitivity compared to standard PET/CT. However, it remains unknown whether the image quality of solitary delayed [ 68 Ga]Ga-PSMA LFOV PET/CT imaging is adequate to satisfy clinical diagnostic requirements. Therefore, the purpose of this study was to evaluate the image quality of delayed [ 68 Ga]Ga-PSMA LFOV PET/CT and examine the feasibility of utilizing delayed [ 68 Ga]Ga-PSMA LFOV PET/CT imaging alone in patients with prostate cancer. Methods The study sample consisted of 56 prostate cancer patients who underwent [ 68 Ga]Ga-PSMA-11 LFOV PET/CT scanning between December 2020 and July 2021. All patients were subjected to early LFOV PET/CT imaging at 1-h post-injection as well as delayed LFOV PET/CT imaging at 3-h post-injection using [ 68 Ga]Ga-PSMA-11. The image quality and diagnostic efficiency of solitary delayed [ 68 Ga]Ga-PSMA-11 LFOV PET/CT imaging was analyzed. Results The results showed that delayed [ 68 Ga]Ga-PSMA-11 LFOV PET/CT yielded satisfactory image quality that fulfilled clinical diagnostic benchmarks. Compared to early imaging, delayed [ 68 Ga]Ga-PSMA-11 LFOV PET/CT demonstrated heightened lesion SUVmax values (11.0 [2.3–193.6] vs. 7.0 [2.0–124.3], P < 0.001) and superior tumor-to-background ratios (3.3 [0.5–62.2] vs. 1.7 [0.3–30.7], P < 0.001). Additionally, delayed [ 68 Ga]Ga-PSMA-11 LFOV PET/CT detected supplementary lesions in 14 patients (25%) compared to early imaging, resulting in modifications to disease staging and management plans. Conclusions In summary, the findings indicate that the image quality of delayed [ 68 Ga]Ga-PSMA-11 LFOV PET/CT is satisfactory for meeting clinical diagnostic prerequisites. The use of solitary delayed [ 68 Ga]Ga-PSMA-11 LFOV PET/CT imaging in prostate cancer simplifies the examination protocol and improves patient compliance, compared to [ 68 Ga]Ga-PSMA-11 standard PET/CT which necessitates both early and delayed imaging.

Purpose A small number of patients diagnosed with multiple myeloma (MM) by bone marrow aspiration reported as being disease-free on 18 F-FDG PET/CT. We aim to evaluate the diagnostic value of radiomics approach in patients with MM who were negative by visual analysis. Materials and methods Thirty-three patients judged negative by visual analysis were assigned to the MM group. Contemporaneous 31 disease-free patients served as the control group. 70% of the whole data set was used as training set (23 from MM group and 22 from control group) and 30% as testing set (10 from MM group and 9 from control group). Axial skeleton volumes were automatically segmented and high-dimensional imaging features were extracted from PET and CT. The unsupervised machine learning method was used to filter and reduce the dimensions of the extracted features. Random forest was used to construct the prediction model and then validated with 10-fold cross-validation and evaluated on the independent testing set. Results One thousand seven hundred two quantitative features were extracted from PET and CT. Of those, three first-order and one high-order imaging features were uncorrelated. With the cross-validation on the training group, the sensitivity, specificity, accuracy and area under the curve of random forest were 0.850, 0.792, 0.818 and 0.894, respectively. On the independent testing set, the accuracy of the model was 0.850 and the area under the curve was 0.909. Conclusion Radiomic analysis based on 18 F-FDG PET/CT using machine learning model provides a quantitative, objective and efficient mechanism for diagnosing patients with MM who were negative by visual analysis.

Dynamic positron emission tomography (PET) images can reveal the distribution of tracers in the organism and the dynamic processes involved in biochemical reactions, and it is widely used in clinical practice. Despite the high effectiveness of dynamic PET imaging in studying the kinetics and metabolic processes of radiotracers. Pro-longed scan times can cause discomfort for both patients and medical personnel. This study proposes a dynamic frame prediction method for dynamic PET imaging, reduc-ing dynamic PET scanning time by applying a multi-module deep learning framework composed of reversible and irreversible modules. The network can predict kinetic parameter images based on the early frames of dynamic PET images, and then generate complete dynamic PET images. In validation experiments with simulated data, our network demonstrated good predictive performance for kinetic parameters and was able to reconstruct high-quality dynamic PET images. Additionally, in clinical data experiments, the network exhibited good generalization performance and attached that the proposed method has promising clinical application prospects.

OBJECTS:To evaluate the prognostic value of radiomics features extracted from 18F-FDG-PET/CT images and integrated with clinical characteristics and conventional PET/CT metrics in newly diagnosed multiple myeloma (NDMM) patients. METHODS:We retrospectively reviewed baseline clinical information and 18F-FDG-PET/CT imaging data of MM patients with 18F-FDG-PET/CT. Multivariate Cox regression models involving different combinations were constructed, and stepwise regression was performed: (1) radiomics features of PET/CT alone (Rad Model); (2) Using clinical data (including clinical/laboratory parameters and conventional PET/CT metrics) only (Cli Model); (3) Combination radiomics features and clinical data (Cli-Rad Model). Model performance was evaluated by C-index and Net Reclassification Index (NRI). RESULTS:Ninety-eight patients with NDMM who underwent 18F-FDG-PET/CT between 2014 and 2019 were included in this study. Combining radiomics features from PET/CT with clinical data showed higher prognostic performance than models with radiomics features or clinical data alone (C-index 0.790 vs. 0.675 vs. 0.736 in training cohort; 0.698 vs. 0.651 vs. 0.563 in validation cohort; AUC 0.761, sensitivity 56.7%, specificity 85.7%, p < 0.05 in training cohort and AUC 0.650, sensitivity 80.0%, specificity78.6%, p < 0.05 in validation cohort) When clinical data was combined with radiomics, an increase in the performance of the model was observed (NRI > 0). CONCLUSIONS:Radiomics features extracted from the PET and CT components of baseline 18F-FDG-PET/CT images may become an effective complement to provide prognostic information; therefore, radiomics features combined with clinical characteristic may provide clinical value for MM prognosis prediction.

Fibroblast activation protein inhibitor (FAPI) is an ideal diagnostic and therapeutic target in malignant tumors. However, the knowledge of kinetic modeling and parametric imaging of 68Ga-FAPI is limited. Purpose: The purpose of this study was to explore the pharmacokinetics of 68Ga-FAPI-04 PET/CT in pancreatic cancer and gastric cancer and to conduct parametric imaging of dynamic total-body data compared with SUV imaging. Methods: Dynamic total-body 68Ga-FAPI-04 PET/CT was performed on 13 patients. The lesion time-activity curves were fitted by 3-compartment models and multigraphical models. The kinetics parameters derived from the 2-tissue reversible compartment model (2T4K) and multigraphical models were analyzed. Parametric [Formula: see text] imaging was generated using the 2T4K and Logan models, and their performances were evaluated compared with SUV images. Results: 2T4K had the lowest Akaike information criterion value, and its fitting curves matched excellently with the origin time-activity curves. Visual assessment revealed that the [Formula: see text](2T4K) images and [Formula: see text](Logan with spatial constraint [SC]) images both showed less image noise and higher lesion conspicuity compared with SUV images. Objective image quality assessment demonstrated that parametric [Formula: see text](2T4K) images and parametric [Formula: see text](Logan with SC) images had a 5.0-fold and 5.0-fold higher average signal-to-noise ratio and 3.6-fold and 4.1-fold higher average contrast-to-noise ratio compared with conventional SUV images, respectively. In addition, no significant differences in signal-to-noise ratio and contrast-to-noise of pathologic lesions were observed between parametric [Formula: see text](2T4K) images and parametric [Formula: see text](Logan with SC) images (all P > 0.05). Conclusions: The 2T4K model was the preferred compartment model. Total-body parametric imaging of 68Ga-FAPI-04 PET yielded superior quantification beyond SUV with enhanced lesion contrast, which may serve as a promising imaging method to make an early diagnosis, to better reflect tumor characterization, or to allow evaluation of treatment response. [Formula: see text](2T4K) images are comparable in image quality and consistent to [Formula: see text](Logan with SC) images in lesions conspicuity; however, [Formula: see text](Logan with SC) images presented an appealing alternative to [Formula: see text](2T4K) images because of their simplicity.

Serving as targeting ligands, aptamers have shown promise in precision medicine. However, the lack of knowledge of the biosafety and metabolism patterns in the human body largely impeded aptamers' clinical translation. To bridge this gap, here we report the first-in-human pharmacokinetics study of protein tyrosine kinase 7 targeted SGC8 aptamer via in vivo PET tracking of gallium-68 (68Ga) radiolabeled aptamers. The specificity and binding affinity of a radiolabeled aptamer, named 68Ga[Ga]-NOTA-SGC8, were maintained as proven in vitro. Further preclinical biosafety and biodistribution evaluation confirmed that aptamers have no biotoxicity, potential mutation risks, or genotoxicity at high dosage (40 mg/kg). Based on this result, a first-in-human clinical trial was approved and carried out to evaluate the circulation and metabolism profiles, as well as biosafety, of the radiolabeled SGC8 aptamer in the human body. Taking advantage of the cutting-edge total-body PET, the aptamers' distribution pattern in the human body was acquired in a dynamic fashion. This study revealed that radiolabeled aptamers are harmless to normal organs and most of them are accumulated in the kidney and cleared from the bladder via urine, which agrees with preclinical studies. Meanwhile, a physiologically based pharmacokinetic model of aptamer was developed, which could potentially predict therapeutic responses and plan personalized treatment strategies. This research studied the biosafety and dynamic pharmacokinetics of aptamers in the human body for the first time, as well as demonstrated the capability of novel molecular imaging fashion in drug development.

Coffee is an important commercial product that arose various quality issues. Different techniques have been applied to detect coffee quality. This review focused on the recent updates in the detection methods of coffee from a targeted versus nontargeted perspective. This review introduced case studies of the current research progresses on targeted and nontargeted detection approaches. Their merits and demerits were evaluated as an analysis of coffee quality. The targeted approach, including liquid chromatography (LC), gas chromatography (GC), thin-layer chromatography (TLC), and capillary electrophoresis (CE), evaluates the quality of coffee by specific markers, whereas the nontargeted approach tests whether the sample is abnormal, without prior knowledge of what caused the abnormality, usually coupled with chemometrics. The nontargeted techniques commonly involve LC, GC, nuclear magnetic resonance (NMR), infrared spectroscopy (IR), ultraviolet-visible spectroscopy (UV-Vis), laser-induced breakdown spectroscopy (LIBS), and mass spectrometry (MS). This work may provide guidance for resolving most aspects of the quality problems in coffee, such as adulterant detection, species identification, and geographical origin discrimination.

BACKGROUND Conventional short-axis PET typically utilizes multi-bed multi-pass acquisition to produce quantitative whole-body dynamic images and cannot record all the uptake information simultaneously, resulting in errors when fitting the time-activity curves (TACs) and calculating radiation doses. PURPOSE The aim of this study is to evaluate the 13 N-ammonia biodistribution and the internal radiation doses using a 194 cm long total-body PET/CT scanner (uEXPLORER), and make a comparison with the previous short-axis PET results. METHODS Ten subjects (age 40-74 years) received 13 N-NH3 injection (418.1-670.81 MBq) and were under a dynamic scan for about 60 min with using a 3-dimensional whole-body protocol. ROIs were drawn visually on 11 major organs (brain, thyroid, gallbladder, heart wall, kidneys, liver, pancreas, spleen, lungs, bone marrow, and urinary bladder content) for each subject. TACs were generated using Pmod and the absorbed radiation doses were calculated using Olinda 2.2. To compare with the conventional PET/CT, five points were sampled on uEXPLORER's TACs to mimic the result of a short-axis PET/CT (15 cm axial FOV, consisted of 9 or 10 bed positions). Then the TACs were obtained using the multi-exponential fitting method, and the residence time and radiation dose were also calculated and compared with uEXPLORER. RESULTS The highest absorbed organ doses were the pancreas, thyroid, spleen, heart wall, and kidneys for the male. For the female, the first five highest absorbed organ dose coefficients were the pancreas, heart wall, spleen, lungs, and kidneys. The lowest absorbed dose was found in red marrow both for male and female. The simulated short-axis PET can fit TACs well for the gradually-changed uptake organs but typically underestimated for the rapid-uptake organs during the first-10 min, resulting in errors in the calculated radiation dose. CONCLUSION uEXPLORER PET/CT can measure 13 N-ammonia's TACs simultaneously in all organs of the whole body, which can provide more accurate biodistribution and radiation dose estimation compared with the conventional short-axis scanners.

IntroductionAs one of the staple foods for the world’s major populations, the safety of wheat is critical in ensuring people’s wellbeing. However, mildew is one of the prevalent safety issues that threatens the quality of wheat during growth, production, and storage. Due to the complex nature of the microbial metabolites, the rapid identification of moldy wheat is challenging.MethodsIn this research, identification of moldy wheat samples was studied using ultra-performance liquid chromatography - quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS) coupled with chemometrics. The non-targeted PCA model for identifying moldy wheat from normal wheat was established by using previously established compounds database of authentic wheat samples. The partial least squares-discriminant analysis (PLS-DA) was performed.Results and discussionBy optimizing the model parameters, correct discrimination of the moldy wheat as low as 5% (w/w) adulteration level could be achieved. Differential biomarkers unique to moldy wheat were also extracted to identify between the moldy and authentic wheat samples. The results demonstrated that the chemical information of wheat combined with the existing PCA model could efficiently discriminate between the constructed moldy wheat samples. The study offered an effective method toward screening wheat safety.

Background: Total variation regularized expectation maximization (TVREM) reconstruction algorithm on the image quality of gallium (68GA) prostate-specific membrane antigen-11 ([68Ga]Ga-PSMA-11) total-body positron emission tomography/computed tomography (PET/CT). Methods: Images of a phantom with small hot sphere inserts and the total-body PET/CT scans of 51 prostate cancer patients undergoing [68Ga]Ga-PSMA-11 were reconstructed using TVREM with 5 different penalization factors between 0.09 and 0.45 and for 20-, 40-, 60-, 120-, and 300-second acquisition, respectively. As a comparison, the same data were also reconstructed using the ordered subset expectation maximization (OSEM) with 3 iterations, 20 subsets, and 300 second acquisition. The contrast recovery coefficients (CRC) and background variability (BV) of the phantom, the tumor-to-background ratios (TBR), the contrast recovery (CR) ratio, the image noise of the liver, and maximum standard uptake value (SUVmax) of the lesions were calculated to evaluate the image quality. The clinical performance of the images was evaluated by 2 radiologists with a 5-point scale (1-poor, 5-excellent). Results: The TVREM reconstructions groups fwith 120 second acquisition and the penalization of 0.27 to 0.45 showed the best performance in terms of CR, TBR, image noise, and the gain of SUVmax compared to that obtained in the OSEM 300 second group. Even the image noise of the TVREM 120 second group with a penalization factor of 0.27 and 0.36 was comparable to the OSEM 300 second group; the lesions’ SUVmax increased by 28% whereas the image noise decreased by 5% and 14%, respectively. The TVREM 120 second group with a penalization factor of 0.36 (5.00±0.00) had the highest qualitative score that equaled OSEM and TVREM for the 300 second (P>0.05) group. Conclusions: Our study has shown the potential of the TVREM reconstruction algorithm with optimized penalization factors to achieve comparable [68Ga]Ga-PSMA-11 total-body PET/CT image quality with a shorter acquisition time, compared with the conventional OSEM reconstruction algorithm.

Background PD-L1 promotes glycolysis in tumour cells. We observed a correlation between high PD-L1 expression and high 18 F-FDG uptake in patients with pancreatic ductal adenocarcinoma (PDAC) in a previous study. This study aims to determine the usefulness of 18 F-FDG PET/CT for evaluating the PD-L1 status in PDAC and to elucidate its rationality by integrated analyses. Methods For bioinformatics analysis, WGCNA, GSEA and TIMER were applied to analyse the pathways and hub genes associated with PD-L1 and glucose uptake. 18 F-FDG uptake assay was used to determine the glucose uptake rate of PDAC cells in vitro. Related genes expression were verified by RT-PCR and western blot. A retrospective analysis was performed on 47 patients with PDAC who had undergone 18 F-FDG PET/CT. Maximum standardised uptake values (SUV max ) were determined. The usefulness of SUV max for evaluating PD-L1 status was determined by receiver operating characteristic (ROC) curve analysis. Results Bioinformatics analysis showed that several signalling pathways are associated with both PD-L1 expression and tumour glucose uptake, among which JAK-STAT may be an important one. By in vitro experiments, the regulatory role of PD-L1 on glucose uptake was demonstrated, and its dependency on the JAK-STAT pathway was also verified by the rescue study. The SUV max of PD-L1-positive patients was significantly higher than PD-L1-negative in tumour cells (TCs) (6.1 ± 2.3 vs. 11.1 ± 4.2; P < 0.001), and in tumour-infiltrating immune cells (TIICs) (6.4 ± 3.2 vs. 8.4 ± 3.5; P < 0.001). In a multivariate analysis, SUV max was significantly associated with PD-L1 expression in TCs and TIICs ( P < 0.001 and P = 0.018, respectively). Using SUV max cut-off values of 8.15 and 7.75, PD-L1 status in TCs and TIICs could be predicted with accuracies of 91.5% and 74.5%, respectively. Conclusion Higher 18 F-FDG uptake by PDAC is associated with elevated PD-L1 expression. JAK-STAT is an important pathway that mediates PD-L1 to promote glucose uptake in PDAC.

[68Ga]Ga-FAPI-04 (gallium-68-labeled fibroblast activation protein inhibitor-04) PET/CT has been widely used in diagnosing malignant tumors. Total-body PET/CT has a long axial field of view and provides higher sensitivity compared to traditional PET/CT. However, whether the reduced injected dose of [68Ga]Ga-FAPI-04 could obtain qualified imaging has not been evaluated. To explore the effect of half-dose [68Ga]Ga-FAPI-04 on image quality and tumor detectability in oncology patients. A total of twenty-seven patients with tumors or clinically suspected tumors were included, and all patients were scanned with total-body PET/CT after an injected dose of 0.84–1.14 MBq/kg [68Ga]Ga-FAPI-04. All patients obtained superior image quality with 300 s original acquisition time. Images were reconstructed using 180 s, 120 s, 60 s, 40 s, 30 s, 20 s scanning duration by ordered subset expectation maximization algorithm. The subjective image quality of all patients in each time group was scored using 5-point Likert scale. Mediastinal blood pool, liver, spleen, and muscle were analyzed as background using semi-quantitative parameters maximum standardized uptake values (SUVmax), mean standardized uptake values (SUVmean), standard deviation (SD), and signal to noise ratio (SNR). The lesion detection rate, SUVmax, and tumor-to-background ratio (TBR) were calculated for tumors confirmed by pathology. The subjective image quality score decreased with the shortening of scanning time; however, both 180 s and 120 s images met the diagnostic requirements in terms of overall quality, lesion conspicuity, and image noise. The SUVmax of background increased with the reduction of scanning time, while the SUVmean was relatively stable. With the shortening of scanning time, the SD gradually increased, and the SNR gradually decreased, which was consistent with subjective image quality scores. In 180 s and 120 s images, all 11 primary lesions and 79 metastatic lesions were detected. The SUVmax of tumor focus showed an increasing trend as same as the background. Compared with 300 s, the TBR muscle had no statistical difference in 180 s and 120 s. Half-dose [68Ga]Ga-FAPI-04 in total-body PET/CT imaging can shorten the acquisition time to 120 s with acceptable subjective image quality and 100

PURPOSE:Multiple myeloma (MM) is a malignant disease characterized by the secretion of monoclonal immunoglobulins and has a high demand for amino acids. [11C]methionine total-body PET is capable of noninvasive dynamic monitoring of radiotracer in vivo, thus providing a way to reveal the dynamic changes of myeloma metabolism. This study aims to analyze the metabolic process of [11C]methionine based on kinetic modeling, and to preliminary reveal its application value in MM.METHODS:Dynamic total-body [11C]methionine PET/CT was conducted with uEXPLORER in 12 subjects (9 MM patients and 3 controls). The tissue time activity curves (TACs) of organs and bone marrows were extracted. Model fitting of TACs was operated using PMOD Kinetic Modeling. After validation by Goodness of fit (GOF), the reversible two-tissue compartment model (2T4k) was used to further analysis. R software was used to analyze the correlation between kinetic parameters and clinical indicators.RESULTS:The 2T4k has passed the criterion of GOF and was used to fit the data of 0-20 minutes. The [11C]methionine net uptake rate (Ki) was significantly higher in the MM lesions than in the non-myeloma controls (control: 0.040±0.007 mL/g/min, MM: 0.171±0.108 mL/g/min, p=0.009). The Ki values were found to be correlated with M protein levels in MM patients. MM patients with t(4;14) translocations had an elevated k4 value compared with t(4;14) negative patients.CONCLUSION:MM lesions have a propensity for uptake of [11C]methionine. The serum levels of M protein are correlated with [11C]methionine uptake rate in myeloma. Metabolic classification based on the k4 value may be a promising strategy for risk stratification in MM.

ABSTRACT:A 68-year-old man with chest tightness underwent cardiac blood perfusion imaging on total-body 13 N-NH 3 PET/CT. Incidentally, mildly increased 13 N-NH 3 activity was observed in the left side of the body of the tongue. Pathological diagnosis proved to be mucosal squamous cell carcinoma.

Metabolic reprogramming is a hallmark of tumors. Tumors own unique metabolic patterns in different stages of their occurrence and development. The stable isotope metabolic flux analysis technology uses stable isotope to trace the metabolites in tumors and crystallize tumor metabolism network. Stable isotope metabolic flux analysis is a useful tool for studying tumor metabolism, which can determine the nutritional sources, find the metabolic liabilities, confirm the metabolic pattern of tumors, and discover new mechanisms of tumor metabolic reprogramming, thus providing theoretical bases for imaging, diagnosis, treatment and evaluation of tumor. This article reviews the applications of stable isotope flux analysis in tumor metabolic reprogramming.