High Capacitive Performance of N,O-Codoped Carbon Aerogels Synthesized via a One-Step Chemical Blowing and In Situ Activation Process.

Biomass and its derivatives, with their renewable characteristics, cost-effectiveness, and controllable structural and compositional properties, are promising precursors for carbon materials. Herein, N,O-codoped carbon aerogels were synthesized by carbonization and zinc nitrate activation of histidine. The specific surface area (SSA) was markedly increased with the addition of zinc nitrate, and the maximum value achieved 853 m2 g-1 for ZHC-11 obtained with the molar ratio of 1:1 between histidine and zinc nitrate. The D/G-band intensity ratio increased from 1.55 for the histidine-derived control sample HC to 1.65 for ZHC-11, indicating the enhancement of amorphous feature. The nitrogen content increased from 6.5% for HC to 1.60 for ZHC-11. The optimized microstructure and enriched heteroatom doping are beneficial to the capacitance performance. The optimum electrode exhibited 234.1 F g-1 at 0.1 A g-1 and maintained 116.5 F g-1 at 60 A g-1 in a three-electrode system. In particular, the symmetric supercapacitor showed 121.9 F g-1 and 19.5 Wh kg-1 at 0.2 A g-1. This research offers guidance on the cost-effective synthesis of carbon materials for supercapacitors, while also providing novel insights to realize the complete utilization of biomass derivatives.

Bimolecular Salt Strategy Enhances Heteroatom Doping and Porosity Optimization of Porous Carbon for Supercapacitors.

The incompatibility between electrolyte ions and electrode pore sizes, coupled with the extensive use of activators and dopants, significantly restricts the fabrication of porous carbon materials. Consequently, developing environmentally sustainable and efficient methodologies that exploit the intrinsic properties and pretreatment of materials to facilitate self-activation and self-doping becomes crucial. In this study, potassium histidine and magnesium histidine molecular salts were synthesized as precursors, enabling specific ion activation and bimetallic template-directed tunable porosity through a one-step carbonization process. Notably, the ratio of bimolecular salts significantly influenced the porous structure of carbon, the properties of heteroatoms, and the electrochemical performance. By optimizing the ratio, the porous carbon materials exhibited high accessibility to electrolyte ions and effective ion/electron transport channels. Consequently, the optimal sample (NOSPC-2) achieved a high specific capacitance of 318 F g-1 at 0.1 A g-1 and a good capacitance retention rate of 98.8% after 50,000 cycles at 5 A g-1. In addition, NOSPC-2 also boasted high energy density and power density, reaching 22 Wh kg-1 and 25 kW kg-1, respectively. This research represents a significant stride in advancing preparation technologies for small molecule derived porous carbon materials, providing valuable insights for the rational design of carbon electrode materials for capacitive energy storage.

High Capacitance Performance N, O Codoped Carbon Foams Synthesized via an All-In-One Step Carbonization of Molecular Salt Strategy.

The preparation of porous carbon is constrained by the extensive use and detrimental impact of activators and dopants. Therefore, developing green and efficient strategies that leverage the intrinsic properties and pretreatment of the materials to achieve self-activation and self-doping is particularly crucial for porous carbon materials. Herein, potassium histidine was utilized as the molecular salt precursor, attaining the efficient and streamlined preparation of porous carbon through a one-step carbonization process that enables self-activation, self-doping, and self-templating. More interestingly, the carbonization temperature significantly impacts the porous structure of the molecular salt precursors, the properties of the heteroatoms, and electrochemical performance. The designed electrodes exhibit high accessibility to electrolyte ions and effective ion-electron transport channels. Therefore, the optimal carbon material (KHis800) has an excellent mass-specific capacitance of 305.2 F g-1 at 0.2 A g-1, and a high capacitance retention rate of 115.6% (50,000 cycles at 5 A g-1). Notably, KHis800 also shows a maximum energy density of 19.6 Wh kg-1. This research is dedicated to exploring a more efficient preparation method for porous carbon material via molecular salts, offering insights for the sustainable development of carbon materials.

N/O Co-doped Porous Carbon with Controllable Porosity Synthesized via an All-in-One Step Method for a High-Rate-Performance Supercapacitor.

A green and economical methodology to fabricate carbon-based materials with suitable pore size distributions is needed to achieve rapid electrolyte diffusion and improve the performance of supercapacitors. Here, a method combining in situ templates with self-activation and self-doping is proposed. By variation of the molar ratio of magnesium folate and potassium folate, the pore size distribution was effectively adjusted. The optimal carbon materials (Kx) have a high specific surface area (1021-1676 m2 g-1) and hierarchical pore structure, which significantly promotes its excellent capacitive properties. Notably, K2 shows an excellent mass specific capacitance of 233 F g-1 at 0.1 A g-1. It still retained 113 F g-1 at 55 A g-1. The assembled symmetric supercapacitor exhibited an outstanding cyclic stability. It maintains 100% capacitance after 100 000 cycles at 10 A g-1. The symmetric supercapacitor demonstrated a maximum power density of 99.8 kW kg-1. This study focuses on the preparation of layered pore structures to provide insights into the sustainable design of carbon materials.

Can the preoperative CT-based deep learning radiomics model predict histologic grade and prognosis of chondrosarcoma?

BACKGROUND AND PURPOSE: Computed tomography (CT) and biopsy may be insufficient for preoperative evaluation of the grade and outcome of patients with chondrosarcoma. The aim of this study was to develop and validate a CT-based deep learning radiomics model (DLRM) for predicting histologic grade and prognosis in chondrosarcoma (CS). METHODS: A multicenter 211 (training cohort/ test cohort, 127/84) CS patients were enrolled. Radiomics signature (RS), deep learning signature (DLS), and DLRM incorporating radiomics and deep learning features were developed for predicting the grade. Kaplan-Meier survival analysis was used to assess the association of the model-predicted grade with recurrence-free survival (RFS). Model performance was evaluated with the area under the receiver operating characteristic curve (AUC) and the Harrell's concordance index (C-index). RESULTS: The DLRM (AUC, 0.879; 95 % confidence interval [CI], 0.802-0.956) outperformed (z = 2.773, P=0.006) the RS (AUC, 0.715;95 % CI, 0.606-0.825) in predicting grade in the test cohort. RFS showed significant differences (log-rank test, P<0.05) between low-grade and high-grade patients stratified by DLRM. The DLRM achieved a higher C-index (0.805; 95 % CI, 0.694-0.916) than the RS (0.692, 95 % CI, 0.540-0.844) did in predicting RFS for CS patients in the test cohort. CONCLUSION: The DLRM can accurately predict the histologic grade and prognosis in CS.

Simultaneous determination of three tyrosine kinase inhibitors and three triazoles in human plasma by LC-MS/MS: applications to therapeutic drug monitoring and drug-drug interaction studies.

Tyrosine kinase inhibitors (TKIs) and triazole antifungals are the first-line drugs for treating chronic myeloid leukemia (CML) and fungal infections, respectively, but both suffer from large exposure differences and narrow therapeutic windows. Moreover, these two types of drugs are commonly used together in CML patients with fungal infections. Multiple studies and guidelines have suggested the importance of therapeutic drug monitoring (TDM) of TKIs and triazoles. Currently, methods for the simultaneous determination of both types of drugs are limited. We developed a simple, rapid, and reliable liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for simultaneous quantification of three commonly used TKIs (imatinib, dasatinib, and nilotinib) and three commonly used triazoles (voriconazole, itraconazole, and posaconazole) in human plasma. The analytes were eluted on a Welch XB-C18 analytical column (50 × 2.1 mm, 5 µm) at 0.7 mL/min, using a gradient elution of 10 mM ammonium formate (A) and methanol-acetonitrile-isopropanol (80:10:10, v/v/v) containing 0.2 % formic acid (B) with a total analysis time of 3.5 min. The calibration curves were linear over the range from 20 to 4000 ng/mL for imatinib and nilotinib, from 2 to 400 ng/mL for dasatinib, and from 50 to 10,000 ng/mL for voriconazole, itraconazole, and posaconazole. Selectivity, accuracy, precision, recovery, matrix effect, and stability all met the validation requirements. The method was successfully used for TDM in CML patients who co-treated with both TKIs and triazoles. Drug-drug interaction analysis between TKIs and triazoles showed that a significant positive correlation was observed between imatinib and voriconazole, as well as dasatinib and voriconazole. Therefore, this method can be well applied in clinical TDM for patients receiving TKIs, triazoles, or both simultaneously.

Development and validation of a liquid chromatography-tandem mass spectrometry method for the determination of polymixin B1, B2, ile-B1, E1, and E2 in human plasma and its clinical pharmacokinetic application.

Polymyxin B (PB) and Polymyxin E (PE, also called colistin) are used as the last treatment resort for multidrug-resistant Gram-negative bacterial infections. The nephrotoxicity and neurotoxicity of polymyxins limit their clinical use, and guidelines recommend therapeutic drug monitoring (TDM) to optimize efficacy and reduce toxicity. However, there are limited analytical methods available for the determination of PB and PE. This study aimed to develop a simple and robust liquid chromatography with tandem mass spectrometry (LC-MS/MS) analytical method for determining the main compounds of PB and PE, namely PB1, PB2, ile-PB1, PE1, and PE2, in human plasma and to investigate of their pharmacokinetics in critically ill patients with the use of PB and PE, respectively. Plasma PB1, PB2, ile-PB1, PE1, and PE2 were chromatographically separated on a Welch LP-C18 column and detected using electrospray ionization mode coupled with multiple reaction monitoring. The calibration curve showed acceptable linearity over 20-10,000 ng/mL for PB1, PE1, and PE2 and 10-5000 ng/mL for PB2 and ile-PB1 in the plasma, respectively. After validation following approved guidelines, this method was successfully applied for PB and PE pharmacokinetic analysis and TDM in critically ill patients. Additionally, the composition of PB1, PB2, ile-PB1, PE1, and PE2 remains unchanged from 0 to 12 h after entering the patient's body.

Radiomics nomogram based on CT radiomics features and clinical factors for prediction of Ki-67 expression and prognosis in clear cell renal cell carcinoma: a two-center study.

OBJECTIVES: To develop and validate a radiomics nomogram combining radiomics features and clinical factors for preoperative evaluation of Ki-67 expression status and prognostic prediction in clear cell renal cell carcinoma (ccRCC). METHODS: Two medical centers of 185 ccRCC patients were included, and each of them formed a training group (n = 130) and a validation group (n = 55). The independent predictor of Ki-67 expression status was identified by univariate and multivariate regression, and radiomics features were extracted from the preoperative CT images. The maximum relevance minimum redundancy (mRMR) and the least absolute shrinkage and selection operator algorithm (LASSO) were used to identify the radiomics features that were most relevant for high Ki-67 expression. Subsequently, clinical model, radiomics signature (RS), and radiomics nomogram were established. The performance for prediction of Ki-67 expression status was validated using area under curve (AUC), calibration curve, Delong test, decision curve analysis (DCA). Prognostic prediction was assessed by survival curve and concordance index (C-index). RESULTS: Tumour size was the only independent predictor of Ki-67 expression status. Five radiomics features were finally identified to construct the RS (AUC: training group, 0.821; validation group, 0.799). The radiomics nomogram achieved a higher AUC (training group, 0.841; validation group, 0.814) and clinical net benefit. Besides, the radiomics nomogram provided a highest C-index (training group, 0.841; validation group, 0.820) in predicting prognosis for ccRCC patients. CONCLUSIONS: The radiomics nomogram can accurately predict the Ki-67 expression status and exhibit a great capacity for prognostic prediction in patients with ccRCC and may provide value for tailoring personalized treatment strategies and facilitating comprehensive clinical monitoring for ccRCC patients.

The status of nuclear medicine in China: the first official national survey.

AIM/INTRODUCTION: The National Nuclear Medicine Quality Control Center of China conducted the first official survey to investigate the nationwide situation of nuclear medicine in 2020. The survey aimed to unveil the current nuclear medicine situation and its quality control in China. MATERIALS AND METHODS: The web-based survey was conducted and the data was collected via the National Clinical Improvement System (NCIS) of China from 1st April to 31st May 2021. RESULTS: A total of 808 institutes across 30 provinces responded to the national survey. For human resources, there are 4460 physicians, 3077 technologists, 339 physicists, and 309 radiochemists. There are 887 single-photon imaging instruments, including 823 SPECT or SPECT/CT, and 365 PET instruments including 314 PET/CT. Six hundred twenty-four institutes perform SPECT examinations and 319 institutes perform PET examinations. 60% of SPECT scans are bone scintigraphy. A total of 97% of PET scans use an [18F]F-FDG tracer. Furthermore, 587 institutes provide radionuclide therapy services but only 280 institutes have admission rooms. The top three radionuclide therapies are [131I] therapy of hyperthyroidism with 546 institutes, [89Sr] therapy of bone metastasis with 400 institutes, and [131I] therapy of differentiated thyroid cancer with 286 institutes. Finally, for the frequency of equipment quality control per year, there are about 67 times self-test within the department for SPECT instruments and 111 times for PET instruments on average in each province. There are about three failures of SPECT and five failures of PET on average per year in each province. There are 408 institutes (of 624 SPECT institutes) performing quality control of SPECT radiopharmaceuticals, 216 (of 319) for PET radiopharmaceuticals, and 373 (of 587) for radionuclide therapy. CONCLUSION: These results of the first official survey towards current status of nuclear medicine in China are the foundation for the establishment of the quality control management system.

Small animal PET imaging with the 68Ga-labeled pH (low) insertion peptide-like peptide YJL-4 in a triple-negative breast cancer mouse model.

BACKGROUND: The aim of this study was to prepare a novel 68Ga-labeled pH (low) insertion peptide (pHLIP)-like peptide, YJL-4, and determine its value for the early diagnosis of triple-negative breast cancer (TNBC) via in vivo imaging of tumor-bearing nude mice. The novel peptide YJL-4 was designed using a template-assisted method and synthesized by solid-phase peptide synthesis. After modification with the chelator 1,4,7­triazacyclononane-N,N',N″-triacetic acid (NOTA), the peptide was labeled with 68Ga. Then, the biodistribution of 68Ga-YJL-4 in tumor-bearing nude mice was investigated, and the mice were imaged by small animal positron emission tomography (PET). RESULTS: The radiochemical yield and radiochemical purity of 68Ga-YJL-4 were 89.5 ± 0.16% and 97.95 ± 0.06%, respectively. The biodistribution of 68Ga-YJL-4 in tumors (5.94 ± 1.27% ID/g, 6.72 ± 1.69% ID/g and 4.54 ± 0.58% ID/g at 1, 2 and 4 h after injection, respectively) was significantly greater than that of the control peptide in tumors at the corresponding time points (P < 0.01). Of the measured off-target organs, 68Ga-YJL-4 was highly distributed in the liver and blood. The small animal PET imaging results were consistent with the biodistribution results. The tumors were visualized by PET at 2 and 4 h after the injection of 68Ga-YJL-4. No tumors were observed in the control group. CONCLUSIONS: The novel pHLIP family peptide YJL-4 can adopt an α-helical structure for easy insertion into the cell membrane in an acidic environment. 68Ga-YJL-4 was produced in high radiochemical yield with good stability and can target TNBC tissue. Moreover, the strong concentration of radioactive 68Ga-YJL-4 in the abdomen does not hinder the imaging of early TNBC.

Sex Differences in Coronary Inflammation and Atherosclerosis Phenotypes in Response to Imaging Marker of Stress-Related Neural Activity.

BACKGROUND: Sex-specific differences in coronary phenotypes in response to stress have not been elucidated. This study investigated the sex-specific differences in the coronary computed tomography angiography-assessed coronary response to mental stress. METHODS: This retrospective study included patients with coronary artery disease and without cancer who underwent resting 18F-fluorodexoyglucose positron emission tomography/computed tomography and coronary computed tomography angiography within 3 months. 18F-flourodeoxyglucose resting amygdalar uptake, an imaging biomarker of stress-related neural activity, coronary inflammation (fat attenuation index), and high-risk plaque characteristics were assessed by coronary computed tomography angiography. Their correlation and prognostic values were assessed according to sex. RESULTS: A total of 364 participants (27.7% women and 72.3% men) were enrolled. Among those with heightened stress-related neural activity, women were more likely to have a higher fat attenuation index (43.0% versus 24.0%; P=0.004), while men had a higher frequency of high-risk plaques (53.7% versus 39.3%; P=0.036). High amygdalar 18F-flourodeoxyglucose uptake (B-coefficient [SE], 3.62 [0.21]; P<0.001) was selected as the strongest predictor of fat attenuation index in a fully adjusted linear regression model in women, and the first-order interaction term consisting of sex and stress-related neural activity was significant (P<0.001). Those with enhanced imaging biomarkers of stress-related neural activity showed increased risk of major adverse cardiovascular event both in women (24.5% versus 5.1%; adjusted hazard ratio, 3.62 [95% CI, 1.14-17.14]; P=0.039) and men (17.2% versus 6.9%; adjusted hazard ratio, 2.72 [95% CI, 1.10-6.69]; P=0.030). CONCLUSIONS: Imaging-assessed stress-related neural activity carried prognostic values irrespective of sex; however, a sex-specific mechanism linking psychological stress to coronary plaque phenotypes existed in the current hypothesis-generating study. REGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifier: NCT05545618.

Clinical value of [18F]AlF-NOTA-FAPI-04 PET/CT for assessing early-stage liver fibrosis in adult liver transplantation recipients compared with chronic HBV patients.

AIMS: To investigate the clinical value and performance of [18F]AlF-NOTA-FAPI-04 PET/CT in assessing early-stage liver fibrosis in liver transplantation (LT) recipients. METHODS: A prospective study including 17 LT recipients and 12 chronic Hepatitis B (CHB) patients was conducted. All patients received liver biopsy, transient elastography (TE), and [18F]AlF-NOTA-FAPI-04 PET/CT. On [18F]AlF-NOTA-FAPI-04 PET/CT scans, the liver parenchyma's maximum standardized uptake values (SUVmax) were measured. The receiver operating characteristic (ROC) curve analysis was applied to determine the diagnostic efficacy of [18F]AlF-NOTA-FAPI-04 PET/CT in early-stage liver fibrosis (S1-S2) compared with the diagnostic performance of TE. RESULTS: Among those 29 patients enrolled in this study, 15(51.7%) had fibrosis S0, 10(34.5%) had S1, and 4(13.8%) had S2, respectively. The SUVmax of patients with early-stage liver fibrosis was significantly higher than those without liver fibrosis in LT recipients and CHB patients (P = 0.004, P = 0.02). In LT recipients, a SUVmax cut-off value of 2.0 detected early-stage liver fibrosis with an AUROC of 0.92 (P = 0.006), and a liver stiffness measurements (LSM) score cut-off value of 8.2 kPa diagnosed early-stage liver fibrosis with an AUROC of 0.80 (P = 0.012). In CHB patients, a SUVmax cut-off value of 2.7 detected early-stage liver fibrosis with an AUROC of 0.94 (P < 0.001) and an LSM scores cut-off value of 8.4 kPa diagnosed early-stage liver fibrosis with an AUROC of 0.91 (P < 0.001). CONCLUSION: [18F]AlF-NOTA-FAPI-04 PET/CT could be applied to evaluate early-stage liver fibrosis in LT recipients and CHB patients properly, with the potential additional advantages in monitoring and predicting complications after LT.

Development and validation of a clinic-radiological model to predict tumor spread through air spaces in stage I lung adenocarcinoma.

OBJECTIVES: Tumor spread through air spaces (STAS) is associated with poor prognosis and impacts surgical options. We aimed to develop a user-friendly model based on 2-[18F] FDG PET/CT to predict STAS in stage I lung adenocarcinoma (LAC). MATERIALS AND METHODS: A total of 466 stage I LAC patients who underwent 2-[18F] FDG PET/CT examination and resection surgery were retrospectively enrolled. They were split into a training cohort (n = 232, 20.3% STAS-positive), a validation cohort (n = 122, 27.0% STAS-positive), and a test cohort (n = 112, 29.5% STAS-positive) according to chronological order. Some commonly used clinical data, visualized CT features, and SUVmax were analyzed to identify independent predictors of STAS. A prediction model was built using the independent predictors and validated using the three chronologically separated cohorts. Model performance was assessed using ROC curves and calculations of AUC. RESULTS: The differences in age (P = 0.009), lesion density subtype (P < 0.001), spiculation sign (P < 0.001), bronchus truncation sign (P = 0.001), and SUVmax (P < 0.001) between the positive and negative groups were statistically significant. Age ≥ 56 years [OR(95%CI):3.310(1.150-9.530), P = 0.027], lesion density subtype (P = 0.004) and SUVmax ≥ 2.5 g/ml [OR(95%CI):3.268(1.021-1.356), P = 0.005] were the independent factors predicting STAS. Logistic regression was used to build the A-D-S (Age-Density-SUVmax) prediction model, and the AUCs were 0.808, 0.786 and 0.806 in the training, validation, and test cohorts, respectively. CONCLUSIONS: STAS was more likely to occur in older patients, in solid lesions and higher SUVmax in stage I LAC. The PET/CT-based A-D-S prediction model is easy to use and has a high level of reliability in diagnosing.

Ct-based intratumoral and peritumoral radiomics for predicting prognosis in osteosarcoma: A multicenter study.

PURPOSE: To evaluate the performance of CT-based intratumoral, peritumoral and combined radiomics signatures in predicting prognosis in patients with osteosarcoma. METHODS: The data of 202 patients (training cohort:102, testing cohort:100) with osteosarcoma admitted to the two hospitals from August 2008 to February 2022 were retrospectively analyzed. Progression free survival (PFS) and overall survival (OS) were used as the end points. The radiomics features were extracted from CT images, three radiomics signatures（RSintratumoral, RSperitumoral, RScombined）were constructed based on intratumoral, peritumoral and combined radiomics features, respectively, and the radiomics score (Rad-score) were calculated. Kaplan-Meier survival analysis was used to evaluate the relationship between the Rad-score with PFS and OS, the Harrell's concordance index (C-index) was used to evaluate the predictive performance of the radiomics signatures. RESULTS: Finally, 8, 6, and 21 features were selected for the establishment of RSintratumoral, RSperitumoral, and RScombined, respectively. Kaplan-Meier survival analysis confirmed that the Rad-scores of the three RSs were significantly correlated with the PFS and OS of patients with osteosarcoma. Among the three radiomics signatures, RScombined had better predictive performance, the C-index of PSF prediction was 0.833 in the training cohort and 0.814 in the testing cohort, the C-index of OS prediction was 0.796 in the training cohort and 0.764 in the testing cohort. CONCLUSIONS: CT-based intratumoral, peritumoral and combined radiomics signatures can predict the prognosis of patients with osteosarcoma, which may assist in individualized treatment and improving the prognosis of osteosarcoma patients.

Low 18F-fluorodeoxyglucose dose positron emission tomography assisted by a deep-learning image-denoising technique in patients with lymphoma.

Background: Patients with lymphoma receive multiple positron emission tomography/computed tomography (PET/CT) exams for monitoring of the therapeutic response. With PET imaging, a reduced level of injected fluorine-18 fluorodeoxyglucose ([18F]FDG) activity can be administered while maintaining the image quality. In this study, we investigated the efficacy of applying a deep learning (DL) denoising-technique on image quality and the quantification of metabolic parameters and Deauville score (DS) of a low [18F]FDG dose PET in patients with lymphoma. Methods: This study retrospectively enrolled 62 patients who underwent [18F]FDG PET scans. The low-dose (LD) data were simulated by taking a 50% duration of routine-dose (RD) PET list-mode data in the reconstruction, and a U-Net-based denoising neural network was applied to improve the images of LD PET. The visual image quality score (1 = undiagnostic, 5 = excellent) and DS were assessed in all patients by nuclear radiologists. The maximum, mean, and standard deviation (SD) of the standardized uptake value (SUV) in the liver and mediastinum were measured. In addition, lesions in some patients were segmented using a fixed threshold of 2.5, and their SUV, metabolic tumor volume (MTV), and tumor lesion glycolysis (TLG) were measured. The correlation coefficient and limits of agreement between the RD and LD group were analyzed. Results: The visual image quality of the LD group was improved compared with the RD group. The DS was similar between the RD and LD group, and the negative (DS 1-3) and positive (DS 4-5) results remained unchanged. The correlation coefficients of SUV in the liver, mediastinum, and lesions were all >0.85. The mean differences of SUVmax and SUVmean between the RD and LD groups, respectively, were 0.22 [95% confidence interval (CI): -0.19 to 0.64] and 0.02 (95% CI: -0.17 to 0.20) in the liver, 0.13 (95% CI: -0.17 to 0.42) and 0.02 (95% CI: -0.12 to 0.16) in the mediastinum, and -0.75 (95% CI: -3.42 to 1.91), and -0.13 (95% CI: -0.57 to 0.31) in lesions. The mean differences in MTV and TLG were 0.85 (95% CI: -2.27 to 3.98) and 4.06 (95% CI: -20.53 to 28.64) between the RD and LD groups. Conclusions: The DL denoising technique enables accurate tumor assessment and quantification with LD [18F]FDG PET imaging in patients with lymphoma.

Synthesis and Preliminary Study of 99mTc-Labeled HYNIC-FAPi for Imaging of Fibroblast Activation Proteins in Tumors.

Fibroblast activation protein (FAP) is an emerging target for cancer diagnosis. Different types of FAP inhibitor (FAPI)-based radiotracers have been developed and applied for tumor imaging. However, few FAPI tracers for single photon emission computed tomography (SPECT) imaging have been reported. SPECT imaging is less expensive and more widely distributed than positron emission tomography (PET), and thus, 99mTc-labeled FAPIs would be more available to patients in developing regions. Herein, we developed a FAPI-04-derived radiotracer, HYNIC-FAPi-04 (HFAPi), for SPECT imaging. 99mTc-HFAPi, with a radiochemical purity of >98%, was prepared using a kit formula within 30 min. The specificity of 99mTc-HFAPi for FAP was validated by a cell binding assay in vitro and SPECT/CT imaging in vivo. The binding affinity (Kd value) of 99mTc-HFAPi for human FAP and murine FAP was 4.49 and 2.07 nmol/L, respectively. SPECT/CT imaging in HT1080-hFAP tumor-bearing mice showed the specific FAP targeting ability of 99mTc-HFAPi in vivo. In U87MG tumor-bearing mice, 99mTc-HFAPi had a higher tumor uptake compared with that of HT1080-hFAP and 4T1-mFAP tumor models. Interestingly, 99mTc-HFAPi showed a relatively high uptake in some murine joints. 99mTc-HFAPi accumulated in tumor lesions with a high tumor-to-background ratio. A preliminary clinical study was also performed in breast cancer patients. Additionally, 99mTc-HFAPi exhibited an advantage over 18F-FDG in the detection of lymph node metastatic lesions in breast cancer patients, which is helpful in improving treatment strategies. In short, 99mTc-HFAPi showed excellent affinity and specificity for FAP and is a promising SPECT radiotracer for (re)staging and treatment planning of breast cancers.

Intratumoral and peritumoral CT radiomics in predicting prognosis in patients with chondrosarcoma: a multicenter study.

OBJECTIVE: To evaluate the efficacy of the CT-based intratumoral, peritumoral, and combined radiomics signatures in predicting progression-free survival (PFS) of patients with chondrosarcoma (CS). METHODS: In this study, patients diagnosed with CS between January 2009 and January 2022 were retrospectively screened, and 214 patients with CS from two centers were respectively enrolled into the training cohorts (institution 1, n = 113) and test cohorts (institution 2, n = 101). The intratumoral and peritumoral radiomics features were extracted from CT images. The intratumoral, peritumoral, and combined radiomics signatures were constructed respectively, and their radiomics scores (Rad-score) were calculated. The performance of intratumoral, peritumoral, and combined radiomics signatures in PFS prediction in patients with CS was evaluated by C-index, time-dependent area under the receiver operating characteristics curve (time-AUC), and time-dependent C-index (time C-index). RESULTS: Eleven, 7, and 16 features were used to construct the intratumoral, peritumoral, and combined radiomics signatures, respectively. The combined radiomics signature showed the best prediction ability in the training cohort (C-index, 0.835; 95%; confidence interval [CI], 0.764-0.905) and the test cohort (C-index, 0.800; 95% CI, 0.681-0.920). Time-AUC and time C-index showed that the combined signature outperformed the intratumoral and peritumoral radiomics signatures in the prediction of PFS. CONCLUSION: The CT-based combined signature incorporating intratumoral and peritumoral radiomics features can predict PFS in patients with CS, which might assist clinicians in selecting individualized surveillance and treatment plans for CS patients. CRITICAL RELEVANCE STATEMENT: Develop and validate CT-based intratumoral, peritumoral, and combined radiomics signatures to evaluate the efficacy in predicting prognosis of patients with CS. KEY POINTS: • Reliable prognostic models for preoperative chondrosarcoma are lacking. • Combined radiomics signature incorporating intratumoral and peritumoral features can predict progression-free survival in patients with chondrosarcoma. • Combined radiomics signature may facilitate individualized stratification and management of patients with chondrosarcoma.

99mTc-Labeled FAPI SPECT Imaging in Idiopathic Pulmonary Fibrosis: Preliminary Results.

AIM: Idiopathic pulmonary fibrosis (IPF) is associated with a poor prognosis, presenting the most aggressive form of interstitial lung diseases (ILDs). Activated fibroblasts are crucial for pathological processes. Fibroblast activation protein (FAP) inhibitor (FAPI) tracers would be promising imaging agents for these diseases. The purpose of this study was to evaluate a 99mTc-labeled FAPI tracer, 99mTc-HFAPI imaging in IPF patients. METHODS: Eleven IPF patients (nine males and two females; age range 55-75 year) were included in this pilot study. 99mTc-HFAPI serial whole-body scintigraphy at 5 min, 20 min, 40 min, 1 h, 2 h, 3 h, 4 h, and 6 h was acquired for dynamic biodistribution and dosimetry estimation in seven representative patients. SPECT/CT tomography fusion imaging of the chest region was performed in all patients at 4 h post-injection, which was considered as the optimal acquisition time. Dosimetry was calculated using OLINDA/EXM software (version 2.0; HERMES Medical Solutions). The quantified or semi-quantified standardized uptake values (SUVs) and lesion-to-background ratios (LBRs) of affected lung parenchyma were also calculated. The high-resolution CT (HRCT) stage was determined with visual evaluation, and the total HRCT score of each patient was measured using a weighting factor formula. Pulmonary function tests (PFTs) were recorded as well. Then, the relationships between the 99mTc-HFAPI results, disease extent on HRCT, and PFT results were investigated. RESULTS: Normal physiological uptake of 99mTc-HFAPI was observed mainly in the liver, intestinal tract, pancreas, gallbladder, and to a lesser extent in the spleen, kidneys, and thyroid, with no apparent retention in the blood circulation at the late time point. The mean injected activity of 99mTc-HFAPI was 813.4 MBq (range 695.6-888.0 MBq). No subjective side effects were noticed. The average whole-body effective dose was 0.0041 mSv/MBq per patient. IPF patients exhibited elevated pulmonary 99mTc-HFAPI uptake in abnormal lung regions, which was correlated with fibrotic regions on HRCT. Among different HRCT stage groups, both SUVmax and LBR showed significant differences (p < 0.001). The higher HRCT stage demonstrated significantly higher SUVmax and LBR. A linear correlation between 99mTc-HFAPI uptake and total HRCT score was observed for SUVmax (r = 0.7839, F = 54.41, p = 0.0094) and LBR (r = 0.7402, F = 56.33, p = 0.0092). 99mTc-HFAPI uptake also had moderate correlations with PFT results. CONCLUSIONS: Our preliminary data show that the 99mTc-HFAPI SPECT imaging is a promising new imaging modality in IPF patients. Investigations of its clinical value in monitoring disease progression and treatment response are needed in the future.

A preoperative CT-based deep learning radiomics model in predicting the stage, size, grade and necrosis score and outcome in localized clear cell renal cell carcinoma: A multicenter study.

BACKGROUND AND PURPOSE: The Stage, Size, Grade and Necrosis (SSIGN) score is the most commonly used prognostic model in clear cell renal cell carcinoma (ccRCC) patients. It is a great challenge to preoperatively predict SSIGN score and outcome of ccRCC patients. The aim of this study was to develop and validate a CT-based deep learning radiomics model (DLRM) for predicting SSIGN score and outcome in localized ccRCC. METHODS: A multicenter 784 (training cohort/ test 1 cohort / test 2 cohort, 475/204/105) localized ccRCC patients were enrolled. Radiomics signature (RS), deep learning signature (DLS), and DLRM incorporating radiomics and deep learning features were developed for predicting SSIGN score. Model performance was evaluated with area under the receiver operating characteristic curve (AUC). Kaplan-Meier survival analysis was used to assess the association of the model-predicted SSIGN with cancer-specific survival (CSS). Harrell's concordance index (C-index) was calculated to assess the CSS predictive accuracy of these models. RESULTS: The DLRM achieved higher micro-average/macro-average AUCs (0.913/0.850, and 0.969/0.942, respectively in test 1 cohort and test 2 cohort) than the RS and DLS did for the prediction of SSIGN score. The CSS showed significant differences among the DLRM-predicted risk groups. The DLRM achieved higher C-indices (0.827 and 0.824, respectively in test 1 cohort and test 2 cohort) than the RS and DLS did in predicting CSS for localized ccRCC patients. CONCLUSION: The DLRM can accurately predict the SSIGN score and outcome in localized ccRCC.

A CT-based deep learning radiomics nomogram outperforms the existing prognostic models for outcome prediction in clear cell renal cell carcinoma: a multicenter study.

OBJECTIVES: To develop and validate a CT-based deep learning radiomics nomogram (DLRN) for outcome prediction in clear cell renal cell carcinoma (ccRCC), and its performance was compared with the Stage, Size, Grade, and Necrosis (SSIGN) score, the University of California, Los Angeles, Integrated Staging System (UISS), the Memorial Sloan-Kettering Cancer Center (MSKCC), and the International Metastatic Renal Cell Database Consortium (IMDC). METHODS: A multicenter of 799 localized (training/ test cohort, 558/241) and 45 metastatic ccRCC patients were studied. A DLRN was developed for predicting recurrence-free survival (RFS) in localized ccRCC patients, and another DLRN was developed for predicting overall survival (OS) in metastatic ccRCC patients. The performance of the two DLRNs was compared with that of the SSIGN, UISS, MSKCC, and IMDC. Model performance was assessed with Kaplan-Meier curves, time-dependent area under the curve (time-AUC), Harrell's concordance index (C-index), and decision curve analysis (DCA). RESULTS: In the test cohort, the DLRN achieved higher time-AUCs (0.921, 0.911, and 0.900 for 1, 3, and 5 years, respectively), C-index (0.883), and net benefit than SSIGN and UISS in predicting RFS for localized ccRCC patients. The DLRN provided higher time-AUCs (0.594, 0.649, and 0.754 for 1, 3, and 5 years, respectively) than MSKCC and IMDC in predicting OS for metastatic ccRCC patients. CONCLUSIONS: The DLRN can accurately predict outcomes and outperformed the existing prognostic models in ccRCC patients. CLINICAL RELEVANCE STATEMENT: This deep learning radiomics nomogram may facilitate individualized treatment, surveillance, and adjuvant trial design for patients with clear cell renal cell carcinoma. KEY POINTS: • SSIGN, UISS, MSKCC, and IMDC may be insufficient for outcome prediction in ccRCC patients. • Radiomics and deep learning allow for the characterization of tumor heterogeneity. • The CT-based deep learning radiomics nomogram outperforms the existing prognostic models in ccRCC outcome prediction.