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Malignant liver tumors have a high incidence and mortality rate. Therefore, it is of great significance to promptly learn about tumor advancement status through relevant examinations for patients' follow-up, diagnosis, and therapy as well as the improvement of the five-year survival rate. The primary lesions and intrahepatic metastases of malignant liver tumors have been better demonstrated in the clinical study with the use of various isotope-labeled fibroblast activating protein inhibitors because of their low uptake in liver tissues and high tumor/background ratio, which provides a new method for early diagnosis, precise staging, and radionuclide therapy. In light of this context, a review of the research progress of fibroblast-activating protein inhibitors for the diagnosis of liver malignant tumors is presented.
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Humans , Positron Emission Tomography Computed Tomography , Carcinoma, Hepatocellular , Liver NeoplasmsABSTRACT
Aim To investigate whether resveratrol (Resveratrol, Res) induces cardiomyocyte protection by increasing intracellular zinc ion and its possible signal mechanism. Methods H9c2 cells were routinely cultured and 2-deoxyglucose (2-DG) was used to establish an endoplasmic reticulum stress (ERS) model. The experiment was randomly divided into control group, 2-DG group, Res +2-DG group, TPEN + Res + 2-DG group and 3-MA + Res +2-DG group. Cell viability was detected by MTT and CCK-8; the expression levels of ERS molecular chaperone proteins glucose-regulated protein 78 (GRP78), glucose-regulated protein 94 (GRP94) and autophagy proteins LC3 II / I, p62 and p-AMPK were detected by Western blot; the expression of LC3 protein was measured by cellular immunofluorescence; the mitochondrial membrane potential (Aijjm) and the intracellular zinc ion level were measured by laser scanning confocal microscope. Results Compared with the control group, 2-DG reduced cell activity and resveratrol inhibited the changes caused by 2-DG, which was reversed by zinc chelator TPEN. 2-DG increased GRP78 and GRP94 expression and resveratrol inhibited the protein changes caused by 2-DG, which was reversed by TPEN. 2-DG increased the expression of LC3 II / I, p-AMPK and decreased the expression of p62, and resveratrol promoted the effect of 2-DG. 2-DG increased the fluorescence intensity of LC3, and resveratrol enhanced the effect of 2-DG, which was reversed by TPEN and 3-MA. 2-DG reduced the red fluorescence intensity of mitochondrial TMRE and green fluorescence intensity of intracellular zinc ions, and resveratrol inhibited these changes caused by 2-DG, which was also reversed by TPEN and 3-MA. The above differences were all statistically significant (P < 0. 05). Conclusion Resveratrol increases intracellular zinc to promote ERS-induced autophagy and prevent the mPTP opening in H9c2 cardiac cells.
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Tumor cells have unique metabolic programming that is biologically distinct from that of corresponding normal cells. Resetting tumor metabolic programming is a promising strategy to ameliorate drug resistance and improve the tumor microenvironment. Here, we show that carboxyamidotriazole (CAI), an anticancer drug, can function as a metabolic modulator that decreases glucose and lipid metabolism and increases the dependency of colon cancer cells on glutamine metabolism. CAI suppressed glucose and lipid metabolism utilization, causing inhibition of mitochondrial respiratory chain complex I, thus producing reactive oxygen species (ROS). In parallel, activation of the aryl hydrocarbon receptor (AhR) increased glutamine uptake via the transporter SLC1A5, which could activate the ROS-scavenging enzyme glutathione peroxidase. As a result, combined use of inhibitors of GLS/GDH1, CAI could effectively restrict colorectal cancer (CRC) energy metabolism. These data illuminate a new antitumor mechanism of CAI, suggesting a new strategy for CRC metabolic reprogramming treatment.
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Objective To investigate the effect of phenformin combined with hexokinase inhibitor 2-deoxyglucose (2-DG) on the treatment of triple-negative breast cancer cell lines 4T1 and MDA-MB-231. Methods Following treatment with phenformin, 2-DG or phenformin combined with 2-DG on 4T1 and MDA-MB-231 cells for 48 h, the cell proliferation in each group was detected by SRB and the apoptosis of cells was detected by flow cytometry. The concentration of glucose and lactic acid in cell culture supernatant was detected by ELISA. The activity of mitochondrial respiratory chain complex Ⅰ was detected by FlexStation3 and the mitochondrial oxygen consumption (OCR) was assayed with the Seahorse X Fe Analyzer. Results The hexokinase expression (4.6±0.17,3.73±0.21), glucose consumption (356±31，397±42) μg/105 cells , Lactic acid concentration (5.59±0.52, 7.83±0.78) μmol/L in the supernatant of 4T1 and MDA-MB-231 cells in Phenformin group were higher than that in control group ( 1±0.15，1±0.12 ) , ( 289±25，301±32) μg/105cells , ( 2.37±0.18，4.01±0.45) μmol/L (P < 0.01). Even if the dose was reduced by 90%, the cell viability of phenformin combined with 2-DG group (64.63±2.28, 51.97±2.29) % was still higher than that of phenformin group (86.70±1.83, 85.53±1.46) % (P<0.001). The combination of the two drugs significantly promoted the apoptosis of 4T1 and MDA-MB-231. In addition, compared with the phenformin group (5.59±0.52, 7.83±0.78) μmol/L, the phenformin combined with 2-DG group (3.46±0.37, 5.18±0.62) μmol/L cell lactic acid production also greatly reduced (P<0.01). Compared with the phenformin or 2-DG single-drug group, the phenformin combined with 2-DG group can significantly inhibit the growth rate of tumors in tumor-bearing mice (P<0.01). The median survival time of tumor-bearing mice in the phenformin combined with 2-DG group was 72.5 d, which was higher than that in the phenformin group 57 d and 2-DG group 55.5 d (P<0.01). Conclusion Hexokinase inhibitor 2-DG significantly enhances the therapeutic effects of phenformin on triple-negative breast cancer cells.
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@#Primary malignant melanoma of the esophagus (PMME) is an exceptionally rare condition, representing a mere 0.1 to 0.2% of esophageal cancers, and accounting for just 0.1 to 0.5% of all melanomas. This case involves a 39 -year-old Filipino male who sought medical attention after an episode of choking. Subsequently, endoscopy with biopsy revealed a mass in the distal third of the esophagus, ultimately diagnosed as PMME based on histopathology and immunohistochemistry. FDG-PET/CT scan revealed a hypermetabolic distal esophageal mass and a confluent upper paratracheal lymphadenopathy. He was initially treated with Pembrolizumab, Nivolumab, and Ipilimumab immunotherapy. However, post-treatment FDG PET/CT scans unveiled metabolic progression of the esophageal mass with new hypermetabolic cervical lymph nodes, necessitating a shift to carboplatin and paclitaxel chemotherapy. After two cycles, there was a notable metabolic regression of the mass and paratracheal node with metabolic resolution of the cervical lymph node. An additional 2 cycles of chemotherapy were given, aimed to further reduce the size of the tumor, however, a succeeding follow-up study revealed metabolic progression of the mass. Surgical resection of both the esophageal mass and paratracheal nodes became imperative. The aggressive characteristics, metastasis at early diagnosis, and lack of effective treatment have contributed to the poor prognosis of PMME. Total esophagectomy is the preferred method of treatment. Chemotherapy and immunotherapy may be used in advanced diseases but with variable efficacy. The utilization of FDG PET/CT scans plays a crucial role in both the initial staging and the ongoing assessment of treatment response in patients diagnosed with PMME. This advanced imaging modality offers valuable insights into the extent of the disease and aids clinicians in evaluating the effectiveness of the chosen therapeutic interventions. Given the rarity and challenges associated with PMME, a multidisciplinary approach integrating surgical, medical, and imaging strategies is essential for comprehensive patient care.
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Melanoma , Positron-Emission Tomography , Fluorodeoxyglucose F18 , ImmunotherapyABSTRACT
Objective:To assess the value of 18F-fluorodeoxyglucose (FDG) PET/MR parameters and their changes in predicting and evaluating the curative effect in patients with locally advanced rectal cancer before and after neoadjuvant chemoradiotherapy (NCRT). Methods:From June 2017 to June 2020, 13 patients (9 males, 4 females; age (52.2±13.2) years) with locally advanced rectal cancer confirmed pathologically and underwent NCRT in Chinese PLA General Hospital were retrospectively enrolled. All patients performed the first PET/MR within one month before NCRT and the second PET/MR within one month before operation. PET/MR parameters including maximum standardized uptake value (SUV max), mean standardized uptake value (SUV mean), metabolic tumor volume (MTV) 2.5, total lesion glycolysis (TLG), minimum apparent diffusion coefficient (ADC min), and their changing percentage (Δ) before and after NCRT were collected. Patients were divided into pathologically complete remission (pCR) group and non-pCR group or response group and non-response group according to the postoperative pathological results as the gold standard. Mann-Whitney U test and logistic regression analysis were used for data analysis. The cut-off values of related parameters and their diagnostic efficiencies were determined by receiver operating characteristic (ROC) curve analysis. Results:Of 13 patients, 5 reached pCR and 8 had histological reaction (response). There were no significant differences in parameters (SUV max, SUV mean, MTV 2.5, TLG, ADC min) between different groups before treatment ( U values: 8.00-19.00, all P>0.05). There were significant differences in SUV max, SUV mean, MTV 2.5, TLG and ΔADC min between pCR group and non-pCR group after treatment ( U values: 0.00-6.00, all P<0.05), but only SUV max was correlated with pCR after treatment (odds ratio ( OR)=0.335, 95% CI: 0.123-0.917, P=0.033). The area under curve (AUC) was 0.95 and the cut-off value of SUV max was 3.055, with the sensitivity of 100%, the specificity of 80.0% and the accuracy of 92.3%. There were significant differences in SUV max, SUV mean, TLG, ADC min, ΔSUV max and ΔADC min between the response group and non-response group after treatment ( U values: 0.00-6.00, all P<0.05), but only ΔSUV max was correlated with the response results ( OR=2.022, 95% CI: 1.100-4.130, P=0.048). The AUC was 0.90 and the cut-off value of ΔSUV max was 69.0%, with the sensitivity of 87.5%, the specificity of 80.0% and the accuracy of 84.6%. Conclusions:PET/MR has high accuracy in evaluating NCRT for locally advanced rectal cancer. SUV max is an independent predictor of pCR after treatment, while ΔSUV max is an independent predictor of histological reaction (response).
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Objective:To explore the diagnostic value of 18F-fluorodeoxyglucose (FDG) PET/MR imaging for liver metastasis. Methods:A retrospective analysis of 75 cases (46 males, 29 females; age (58.9±14.3) years) with suspected liver metastases from January 2020 to October 2020 in Ruijin Hospital were performed. All patients underwent PET/MR and enhanced upper abdominal CT scans. Diagnostic efficacies of enhanced CT, PET, MR and PET/MR for liver metastases (based on lesions and patients respectively) were calculated and compared (McNemar test).Results:A total of 306 liver lesions were detected in 75 patients, of which 179 lesions in 45 patients were confirmed as liver metastases through follow-up or pathology. In lesion-based analysis, the sensitivities of enhanced CT, PET, MR and PET/MR were 74.9%(134/179), 60.3%(108/179), 98.9%(177/179) and 100%(179/179), with specificities of 96.9%(123/127), 100%(127/127), 92.9%(118/127) and 92.1%(117/127), respectively. The diagnostic efficacy of PET/MR was significantly higher than that of enhanced CT and PET ( χ2 values: 51.000 and 81.000, both P<0.001), but there was no statistical difference between PET/MR and MR ( χ2=2.000, P=0.368). In patient-based analysis, the sensitivities of enhanced CT, PET, MR and PET/MR were 82.2%(37/45), 84.4%(38/45), 95.6%(43/45) and 100%(45/45), with specificities of 86.7%(26/30), 100%(30/30), 70.0%(21/30) and 70.0%(21/30), respectively. The diagnostic efficacies of enhanced CT and PET were statistically different from PET/MR ( χ2 values: 13.000 and 16.000, both P<0.05), but there was no statistical difference between MR and PET/MR ( χ2=2.000, P=0.368). Conclusions:Compared with enhanced CT, PET and MR, 18F-FDG PET/MR has a higher detective rate for liver metastases. The overall diagnostic efficacy of 18F-FDG PET/MR is better than enhanced CT and PET alone, but similar to MR.
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Objective:To evaluate the value of PET/MR multiple parameters before treatment and MR-intravoxel incoherent motion (IVIM) parameters 4 weeks after concurrent chemoradiotherapy (CCRT) in predicting the prognosis of cervical cancer patients 6 months after treatment.Methods:From September 2017 to March 2019, 58 cervical cancer patients (age: 35-78 years) performed CCRT in Shengjing Hospital of China Medical University were retrospectively enrolled. PET/MR was performed before treatment, and MR-IVIM was performed at the end of the fourth week of treatment and 6 months after treatment. Patients were divided into complete response (CR) group and non-CR group according to the response evaluation criteria in solid tumors (RECIST). PET imaging parameters (maximum standardized uptake value (SUV max), metabolic tumor volume (MTV), total lesion glycolysis (TLG)), MR-IVIM parameters (slow diffusion coefficient (D), fast diffusion coefficient (D *), perfusion fraction (F), gross tumor volume (GTV), diffusion volume (DV)) before (referred to as 1) and after (at the end of the fourth week; referred to as 2) treatment and their percentage changes (ΔD, ΔD *, ΔF, ΔGTV, ΔDV) were measured. The parameters of PET and MR-IVIM were analyzed by the receiver operating characteristic (ROC) curve analysis. Multiple logistic regression was used to establish the combination prediction model of parameters before treatment and all parameters before and after treatment (Combination1 and Combination2 respectively), and the two models were compared by Delong test. Results:Of 58 patients, 37(63.79%) were CR, and 21 (36.21%) were non-CR. MTV (area under curve (AUC)=0.764, P<0.01), TLG (AUC=0.719, P<0.01), GTV 1 (AUC=0.761, P<0.01) and DV 1 (AUC=0.785, P<0.01) before treatment had positive effects on the treatment response, and the valuable parameters after treatment were D 2 (AUC=0.683, P<0.01), GTV 2 (AUC=0.861, P<0.01), DV 2 (AUC=0.891, P<0.01), ΔD (AUC=0.723, P<0.01), ΔGTV (AUC=0.768, P<0.01) and ΔDV (AUC=0.865, P<0.01). The best prediction model before treatment was DV 1 (Combination1; AUC=0.785, P=0.004). The best prediction model for all parameters before and after treatment was the combination pre-treatment of MTV, DV 2 and ΔD (Combination2; AUC=0.965, P<0.001). Combination2 was superior to Combination1 ( z=2.982, P=0.003). Conclusion:In evaluating the early prognosis of cervical cancer patients treated with CCRT, DV 1 has good predictive potential before treatment, while the combination of pre-treatment MTV with post-treatment DV 2 and ΔD has superior joint predictive potential and can provide help for patients′ personalized treatment.
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Objective:To investigate the value of multiple parameters and the combined model based on 18F-fluorodeoxyglucose (FDG) PET/MR in the differential diagnosis of benign and malignant pancreatic tumors. Methods:A total of 76 patients (50 males, 26 females, age (45.2±18.0) years) with clinically suspected pancreatic tumor who underwent PET/MR between December 2012 and September 2020 in First Medical Center of Chinese PLA General Hospital were retrospectively selected. All patients had definitive diagnoses. PET/MR sequences included T 1 weighted imaging (WI; convention and contrast enhancement), T 2WI, diffusion weighted imaging (DWI) and 18F-FDG PET sequences. Morphological characteristics and scores of lesions in MRI were evaluated. Parameters including parameters of PET and DWI, as well as parameters derived from histogram analysis of apparent diffusion coefficient (ADC) and standardized uptake value (SUV) (maximum (max), minimum (min), mean, median, standard deviation (SD), skewness, kurtosis, entropy) were measured. Independent-sample t test or Mann-Whitney U test were used for data analysis. PET/MR combined model was measured based on logistic regression analysis. Receiver operating characteristic (ROC) curve analysis was used to calculate the differential diagnosis efficacy of PET/MR multiparameters and combined model for benign and malignant lesions. Results:Among 76 patients, 55 were malignant and 21 were benign. (1) Visual evaluation. The main manifestations of pancreatic cancer were unclear margin, abnormal internal MR signal and enhancement, decreased ADC signal and increased radioactive uptake. The main manifestations of benign tumor lesions of pancreas were clear margin, even signal and enhancement, no reduction of ADC, decreased radioactive uptake. (2) Diagnostic efficacy. Multiparameter model established based on logistic regression analysis included SUV max, SUV SD, ADC entropy and ADC skewness. The efficiency of differential diagnosis for benign and malignant pancreatic tumors were shown as follows: multiparametric diagnostic model>ADC entropy>MR score>SUV max>SUV SD>ADC skewness. The multiparametric diagnostic model had the best diagnosis efficiency with the area under curve (AUC) of 0.86, the sensitivity of 69.1%(38/55), and the specificity of 100%(21/21) ( z=-8.73, P<0.001). Conclusions:MR score and multiple quantitative parameters obtained from 18F-FDG PET/MR can be used to differentiate benign and malignant pancreatic tumors. Compared with independent parameter of PET/MR, multiparametric model can further improve the diagnostic efficiency.
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Objective:To explore the accuracy of 18F-fluorodeoxyglucose (FDG) PET/MR in preoperative localization of refractory epilepsy patients with conventional MRI negative. Methods:From August 2016 to December 2018, 57 refractory epilepsy patients (36 males, 21 females, age (24.0±10.3) years) with conventional MRI negative who underwent surgery in Xuanwu Hospital were retrospectively enrolled. All patients received interictal 18F-FDG PET/MR before surgery and the epileptogenic foci were determined by using visual and semi-quantitative methods. Patients were followed up for 1 year and the surgical outcome was evaluated according to Engel classification. The sensitivity, specificity and accuracy of 18F-FDG PET/MR in locating epileptogenic foci were calculated according to surgical resection and followed-up results as the " gold standard" . Results:Of 57 patients, 51(89.5%, 51/57) showed single or multiple hypo-metabolism focus on 18F-FDG PET/MR, and 6(10.5%, 6/57) showed no abnormal metabolism changes. The microstructure abnormality was found in 18 patients (31.6%, 18/57) on 18F-FDG PET/MR images. Follow-up results were obtained from 46 patients, and 84.8%(39/46) with seizure improvement (Engel Ⅰ-Ⅲ). The sensitivity, specificity and accuracy of 18F-FDG PET/MR in preoperative localization of epileptic foci was 90.0%(27/30), 3/16 and 65.2%(30/46), respectively. Conclusion:18F-FDG PET/MR is helpful for the detection of epileptic foci in patients with MRI-negative refractory epilepsy, and can provide reliable information for further surgical treatment.
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Objective:To explore the potential value of interim 18F-fluorodeoxyglucose (FDG) PET/CT combined with B-cell lymphoma-2 (Bcl-2)/MYC protein dual expression (DE) status in the prognostic stratification for patients with primary gastrointestinal diffuse large B-cell lymphoma (PGI-DLBCL). Methods:Forty-six patients (21 males, 25 females; age 20-83 years) with newly diagnosed PGI-DLBCL from June 2012 to May 2019 in Nanjing Drum Tower Hospital were enrolled in this retrospective study. Immunohistochemistry for Bcl-2 and MYC protein expression was performed. All patients underwent baseline and interim (after 2-4 cycles of cyclophosphamide, doxorubicin, vincristine, prednisone, and rituximab (R-CHOP) regimen) 18F-FDG PET/CT scans for assessment. Interim 18F-FDG PET/CT results were determined based on Deauville 5-point scale (DS) and changing rate of maximum standardized uptake value (ΔSUV max%) in 18F-FDG PET/CT images. Kaplan-Meier survival analysis, Cox proportional hazards regression model (single factor, multiple factors analysis) were used to analyze the prognosis (3-year progression free survival (PFS) and overall survival (OS) rates). Results:Patients were followed up for 6-84 months, and 14 showed disease progression and 9 died. The PFS rate and OS rate were 69.6% and 80.4%, respectively. DE, DS as well as ΔSUV max% were significant predictors of PFS (hazard ratio ( HR) values: 3.280, 5.120, 9.167, all P<0.05); lactate dehydrogenase (LDH), MYC protein expression, DS and ΔSUV max% were significant predictors of OS ( HR values: 4.091, 9.618, 7.697, 11.151, all P<0.05). Multivariate analysis revealed that DS and ΔSUV max% were independent predictors of PFS and OS ( HR values: 4.370-9.244, all P<0.05). In the DS negative (-) group, patients with DE positive (+ ) had lower PFS and OS rates than those with DE- (PFS rate: 50.0% vs 88.9%; OS rate: 66.7% vs 96.3%; χ2 values: 6.050, 4.966, both P<0.05). In ΔSUV max%<90% group, patients with DE+ had lower PFS rate than those with DE- (12.5% vs 68.8%; χ2=6.649, P=0.01). Conclusions:Interim PET/CT analysis using DS and ΔSUV max% is able to predict survival in PGI-DLBCL patients. The combination of DS, ΔSUV max% and DE can risk-stratify PGI-DLBCL patient more effectively.
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Objective:To explore the influence of time of flight (TOF) and point spread function (PSF) on PET/CT image quality and standardized uptake value (SUV) based on a phantom study.Methods:PET/CT imaging were performed using Jaszczak phantom and International Electrotechnical Commission (IEC) body phantom respectively, and conventional clinical imaging protocol (3 min/bed) was used for three consecutive imaging. The ordered subsets expectation maximization (OSEM), OSEM+ TOF, OSEM+ PSF and OSEM+ TOF+ PSF were used to reconstruct the raw data respectively. The differences of image resolution, image uniformity, contrast, signal to noise ratio (SNR) and SUV among different reconstruction algorithms were compared by using one-way analysis of variance and the least significant difference (LSD) t test. The correlations between SNR, mean SUV (SUV mean), maximum SUV (SUV max) and the sphere diameter were analyzed by Pearson correlation analysis. Results:The minimum image resolution for the hot column was 6.4 mm by OSEM and OSEM+ PSF reconstruction, while it was 4.8 mm by OSEM+ TOF and OSEM+ TOF+ PSF reconstruction. The contrast was significantly better by OSEM+ TOF ((78.56±1.21)%) and OSEM+ TOF+ PSF ((78.85±1.17)%) reconstruction than that by OSEM reconstruction ((73.44±1.47)%; F=61.068, t values: 9.503, 10.018, both P<0.001). The maximum and minimum nonuniformity percentages were significantly better for images reconstructed with OSEM+ PSF than those reconstructed with OSEM ( F values: 10.286, 27.630, t values: -2.599, 7.698, both P<0.05). In IEC phantom imaging, the SNR and SUV max of hot sphere were higher by OSEM+ PSF and OSEM+ TOF+ PSF reconstruction than those by OSEM reconstruction (SNR: (98.99±34.76)%, (98.29±28.66)%, (73.64±26.05)%; F=5.712, t values: 3.209, 3.412, both P<0.05; SUV max: 8.96±2.72, 9.28±2.17, 8.01±2.21; F=3.931, t values: 2.154, 2.863, both P<0.05), but there was no significant difference between OSEM+ TOF and OSEM reconstruction ( t values: 0.297, 0.272, both P>0.05). Among the four reconstruction methods, the SNR and SUV mean increased with the increase of the sphere diameter ( r values: 0.913-0.963, all P<0.05), but SUV max in images reconstructed with OSEM+ PSF and OSEM+ TOF+ PSF had no significant correlations with the sphere diameter ( r values: 0.496, 0.614, both P>0.05). Conclusions:Under specific acquisition and reconstruction conditions, TOF mainly improves image resolution and contrast, while PSF mainly improves image uniformity and SNR. The combination of the two method can obtain better image quality and significantly improve the SUV of hot lesions.
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Objective:To investigate the segmentation methods of pancreatic ductal adenocarcinoma (PDAC) tumor regions in 18F-fluorodeoxyglucose (FDG) PET/CT images, as well as their impact on radiomic features-based pathological grade prediction. Methods:A total of 72 patients (46 males, 26 females, age range: 25-87 years) with pathologically confirmed PDAC and a preoperative 18F-FDG PET/CT scan in Peking Union Medical College Hospital between September 2010 and January 2016 were enrolled retrospectively. The cohort of patients was classified as well differentiated group and non-well differentiated group based on the pathological grade of PDAC, and patients were divided into training set and validation set in the ratio of 3∶1 randomly. Two physicians performed manual contours in the tumor region (referred as region of interest (ROI)_M1 and ROI_M2) and semi-automatic ROIs based on standardized uptake value (SUV) gradient edge search (referred as ROI_G) and 40% threshold applied to the maximum SUV (SUV max; referred as ROI_S) were drawn. The four types of segmentation results were compared in terms of volume and Dice similarity coefficient (DSC). Shape, first-order, and texture features were extracted from PET/CT original and preprocessed images, and the interclass correlation coefficient (ICC) was used to assess each feature′s consistency across all segmentations. Kruskal-Wallis rank sum test, independent-sample t test or z test were used to analyze the data. The area under the receiver operating characteristic curve was used to assess model accuracy, and cross validation was used to assess generalization ability. Results:There were 55 patients in the training set (14 well differentiated cases and 41 non-well differentiated cases) and 17 patients in the validation set (4 well differentiated cases and 13 non-well differentiated cases). A total of 44 selected features were predictive of the pathological grade of PDAC among 20 feature groups. There was significant difference among the volumes of ROI_M1, ROI_M2, ROI_G and ROI_S (10.29(4.01, 19.43), 9.34(4.26, 17.27), 11.86(5.52, 19.74) and 15.08(9.62, 27.44) cm 3; H=18.641, P<0.05). The degree of contour coincidence and feature consistency between ROI_M1 and ROI_M2 were both higher (DSC=0.86 (0.76, 0.90), ICC=0.86 (0.74, 0.94)). Compared to manual contours, the degree of contour coincidence and feature consistency of ROI_G (DSC: 0.86(0.75, 0.91), 0.91(0.85, 0.96); ICC: 0.87(0.72, 0.94), 0.94(0.88, 0.98)) were better. There was no statistically significant difference in model accuracy or generalization ability between ROI_M1 and ROI_G ( z=1.052, t=0.712, both P>0.05). The accuracy of ROI_M2 was better than ROI_G ( z=3.031, P=0.002), but the generalization ability of ROI_M2 was insufficient ( t=3.086, P=0.012). Conclusions:Although the manual contour prediction models are highly accurate, their performance are unstable. Semi-automatic contouring based on gradient can achieve comparable accuracy to manual contouring, and the model′s generalization ability is stronger.
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Objective:To explore the value of radiomics based on 18F-fluorodeoxyglucose (FDG) PET/CT in predicting the Children′s Oncology Group (COG) risk stratification of neuroblastoma (NB). Methods:From March 2018 to November 2019, the 18F-FDG PET/CT images of 125 NB children (51 males, 74 females, age: 0.5-10.5 years) confirmed pathologically in Beijing Friendship Hospital were retrospectively analyzed. According to the COG classification, patients were divided into high-risk group and non-high-risk group (including low- and intermediate-risk). Imaging radiomics features were extracted from PET and CT images and screened. Logistic regression was used to build the first model based on radiomics features (R_model) and calculate radiomics score (Rad_score), then build the second model (RD_model) based on Rad_score and demographic features and at last build the third model (RDC_modle) based on Rad_score, demographic features and clinical features. The receiver operating characteristic (ROC) curve was used to evaluate the predictive efficacy of these models. Results:The training set contained 94 NB cases (63 high-risk cases, 31 non-high-risk cases), and the validation set contained 31 NB cases (21 high-risk cases, 10 non-high-risk cases). Four radiomics features were obtained by screening, of which two features were based on CT images and the other two features were based on PET images. The area under the curves (AUCs) of the R_model, RD_model and RDC_model in training or validation set were 0.91, 0.94, 0.98 or 0.86, 0.92, 0.95, respectively. The accuracies of the R_model, RD_model and RDC_model in training or validation set were 86%(81/94), 89%(84/94), 93%(87/94) or 84%(26/31), 84%(26/31), 87%(27/31), respectively.Conclusions:Radiomics based on 18F-FDG PET/CT can accurately predict the COG risk stratification of NB. Prediction model of radiomics features combined with demographic and clinical characteristics can further improve the accuracy of predicting NB COG risk stratification, which can help personalized and precise therapy protocol management in NB.
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Objective:To investigate the value of baseline 18F-fluorodeoxyglucose (FDG) PET/CT radiomics features in predicting the prognosis of non-small cell lung cancer (NSCLC) before treatment. Methods:From January 2016 to August 2018, a total of 300 patients with solitary NSCLC (189 males, 111 females, age (62.3±9.0) years) who underwent 18F-FDG PET/CT imaging before treatment in Fourth Hospital of Hebei Medical University were retrospectively analyzed. According to the ratio of 7∶3 (R language), 300 patients were randomly divided into training group ( n=210) and validation group ( n=90). LIFEx software package was used to extract the PET and CT radiomics features of primary focus in 300 NSCLC patients. The least absolute shrinkage and selection operator (LASSO) algorithm combined with Cox proportional hazard regression model were used to select radiomics features and clinical features for predicting overall survival (OS) and progression-free survival (PFS) in training group. Then radiomics model, clinical model and complex model which integrated the two were established and the radiomics score (Rad-score), clinical score and complex score of each patient were calculated. Data of validation group was used to validate each training model. Efficiencies of each model in predicting the prognosis of patients with NSCLC were further evaluated by the concordance index (C-index), and a nomogram was developed based on the best prediction model. Results:In training group, the C-indices of predicting OS and PFS in NSCLC patients of radiomics model were 0.762 and 0.724 respectively, which were 0.834 and 0.780 respectively in clinical model, and were 0.842 and 0.787 respectively in complex model. Cox multivariate analysis showed that both Rad-score and complex score were independent prognostic factors for OS (hazard ratio ( HR): 1.804, 9.996, 95% CI: 1.023-3.184, 4.582-21.808, both P<0.05) and PFS ( HR: 1.771, 5.627, 95% CI: 1.138-2.756, 3.429-9.234, both P<0.05). Conclusions:Pre-treatment 18F-FDG PET/CT radiomics can predict OS and PFS of NSCLC patients. The complex model based on the combination of radiomics and clinical model is effective in predicting the prognosis of NSCLC patients, and the nomogram of complex model is simple and convenient to assist clinical decision-making.
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Objective:To explore the predictive value of 18F-fluorodeoxyglucose (FDG) PET/CT radiomics for the programmed death ligand-1 (PD-L1) expression level in lung adenocarcinoma patients. Methods:A total of 101 patients (43 males, 58 females; median age 60 years) with histologically confirmed lung adenocarcinoma who received pre-treatment 18F-FDG PET/CT from January 2017 to January 2019 in Peking University Cancer Hospital were included retrospectively. There were 44 patients with positive PD-L1 by immunohistochemical assays, and 57 with PD-L1 negative. Patients were assigned to a training set ( n=71) and a validation set ( n=30). Clinical data, PET/CT radiomics parameters, conventional metabolic parameters, and observed CT characteristics of these patients were included in the models. The filter method and embedded method were used in feature selection. Models based on logistic regression, random forest, XGBoost and Light Gradient Boosting Machine (LightGBM) were trained and evaluated, and the optimal parameters to predict the PD-L1 expression as well as the area under curve (AUC) were attained. Results:All models had predictive ability in the prediction of PD-L1 expression, while LightGBM was more powerful than the others, with the precision for positive and negative predictions of 0.85 and 0.76, respectively. Incorporating clinical data and data derived from thin-section CT images (clinical data+ CT) into the LightGBM, the precision, recall and F1-score for positive and negative patients were 0.71, 0.67, 0.69 and 0.69, 0.73, 0.72, respectively, with the accuracy of 0.70 and the AUC of 0.79. As for clinical data+ PET, the precision, recall and F1-score for positive and negative patients were 0.79, 0.73, 0.76 and 0.75, 0.80, 0.77, respectively, with the accuracy of 0.77 and the AUC of 0.80. As for clinical data+ CT+ PET, the precision, recall and F1-score for positive and negative patients were 0.85, 0.73, 0.79 and 0.76, 0.87, 0.81, respectively, with the accuracy of 0.80 and the AUC of 0.83. Features with significant importance in the model (clinical data+ CT+ PET) were as follows: maximum standardized uptake value (SUV max), peak of standardized uptake value (SUV peak), CT_shape_Maximum2DDiameterSlice, PET_shape_Elongation, PET_gray level co-occurrence matrix (GLCM)_Correlation, etc. Conclusions:Incorporating clinical data, PET/CT radiomics features and conventional metabolic parameters, the PD-L1 expression can be effectively predicted, which help to assist the selection of patients who may benefit from the immunotherapy.
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Objective:To explore the predictive values for mutation subtypes of epidermal growth factor receptor (EGFR) in patients with lung adenocarcinoma (LUAD) based on machine learning and 18F-fluorodeoxyglucose (FDG) PET/CT images. Methods:18F-FDG PET/CT images and pathological data of 238 patients with LUAD (126 patients (54 males, 72 females, median age 62 years) with EGFR mutation; 112 patients (68 males, 44 females, median age 61 years) with wild-type EGFR)) were retrospectively collected at Tianjin Medical University Cancer Institute and Hospital between April 2016 and May 2020. Volumes of interest (VOI) of PET and CT images were delineated respectively and three-dimensional-based and two-dimensional-based radiomics features were extracted from VOIs. Three machine learning classifiers of K-nearest neighbor (KNN), support vector machine (SVM) and Adaboost were trained in training set with CT, PET and fusion PET/CT radiomics features respectively. Well trained classifiers were tested in test set. Each predictive model was evaluated by using the receiver operating characteristic (ROC) curve. Results:A total of 126 patients were EGFR mutation including 3 patients with 18 exon mutation, 6 patients with 20 exon mutation, 42 patients with 19 exon mutation, and 75 patients with 21 exon mutation. Finally, patients with 18 exon mutation and 20 exon mutation were removed due to the scale was too small to be trained adequately by machine learning classifiers. Predictive performance of mean PET/CT feature-based model (Adaboost: area under curve (AUC)=0.87, 95% CI: 0.75-0.99) in EGFR mutation subtypes was better than PET feature-based model (Adaboost: AUC=0.64, 95% CI: 0.46-0.83; z=2.04, P<0.05) and CT feature-based model (Adaboost: AUC=0.64, 95% CI: 0.45-0.83; z=2.06, P<0.05). There was no statistical difference between predictive performance of mean PET/CT feature-based model (SVM: AUC=0.76, 95% CI: 0.56-0.96) and PET/CT concatenation feature-based model (SVM: AUC=0.75, 95% CI: 0.59-0.92; z=1.14, P>0.05). Conclusion:Machine learning and 18F-FDG PET/CT radiomics features can provide predictive value for EGFR mutation subtypes in patients with LUAD.
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Objective:To explore the clinical significance of different metabolic parameters measured by 18F-fluorodeoxyglucose (FDG) PET/CT in predicting the effectiveness of chemotherapy in advanced lung adenocarcinoma patients. Methods:A set of metabolic parameters of PET/CT and clinical characteristics which were detected from 127 patients (70 males, 57 females, age (56.8±10.1) years) with advanced lung adenocarcinoma treated with at least two cycles of chemotherapy in Hainan Cancer Hospital between August 2017 and June 2019 were retrospectively analyzed. The effects of those parameters on patients′ survival were analyzed by receiver operating characteristic (ROC) curve, Kaplan-Meier method (log-rank test) and Cox proportional hazards model.Results:Maximum standardized uptake value (SUV max), metabolic tumor volume 30% (MTV 30), and total lesion glycolysis 30% (TLG 30) had larger areas under the curve (0.581, 0.606 and 0.693 respectively) compared with other imaging parameters, and the optimal cut-off values were 10.12, 20.21 cm 3 and 81.25 g respectively. Kaplan-Meier univariate and Cox analyses synergistically showed that clinical stage (hazard ratio ( HR)=0.293(95% CI: 0.190-0.451), P<0.001), smoking ( HR=0.732(95% CI: 0.605-0.885), P=0.001), and MTV 30 ( HR=1.555(95% CI: 1.078-2.242), P=0.018) had significant predictive value for progression-free survival (PFS). Stratified analysis showed that smoking and MTV 30>20.21 cm 3 were independent prognostic factors for poor PFS in patients with advanced lung adenocarcinoma receiving chemotherapy ( HR=0.738(95% CI: 0.611-0.893), P=0.002; HR=1.502(95% CI: 1.037-2.177), P=0.032). Conclusions:Clinical stage, smoking and MTV 30 are independent prognostic factors of PFS in patients with advanced lung adenocarcinoma receiving chemotherapy. MTV 30≤20.21 cm 3 is expected to be an image biomarker for predicting survival and selecting patients with advanced lung adenocarcinoma who are more likely to benefit from chemotherapy.
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Objective:To improve the quality of 18F-fluorodeoxyglucose (FDG) PET images at different acquisition times through deep learning (DL) PET image reconstruction methods. Methods:A total of 45 patients (20 males, 25 females; age (52.0±13.6) years) with malignant tumors and PET/CT scans from September 2020 to October 2020 in the Department of Nuclear Medicine of the First Hospital of Shanxi Medical University were included in this retrospective study. The short acquisition time 30 s/bed PET images from the raw list mode were selected as the input of DL model. DL image reconstruction model, based on the Unet algorithm, was trained to output imitated PET images with full dose standard acquisition time (3 min). The image quality evaluation and quantitative analysis were carried out for four groups of images: DL images, 30 s, 90 s, and 120 s images, respectively. The quality of PET images in four groups was evaluated using the five-point method. Liver background activities, lesions quantification parameters (maximum standardized uptake value (SUV max), mean standardized uptake value (SUV mean), standard deviation (SD), signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR)), and first-order texture features (skewness, kurtosis, uniformity, entropy) were measured. Kappa test, χ2 test and one-way analysis of variance (least significant difference t test) were used for data analysis. Results:The image quality scores between four groups were highly consistent ( Kappa=0.799, P<0.001). The number of patients with scores≥3 in DL, 30 s, 90 s and 120 s groups were 6, 4, 7 and 8, respectively ( χ2=125.47, P<0.001). The liver SD of DL group was significantly lower than that of 30 s group (0.26±0.07 vs 0.43±0.11; F=3.58, t=-7.91, P<0.05). The liver SNR of DL group was higher than that of 30 s group (11.04±4.36 vs 5.41±1.41; F=10.22, t=5.40, P<0.05). The liver SD and SNR of DL group were similar to those of 90 s group (0.39±0.16, 8.46±3.34; t values: -0.87 and 2.17, both P>0.05). In 18 tumor lesions with high uptake, SNR and CNR of DL group were significantly higher than those of 30 s group (60.21±29.26 vs 38.38±16.54, 22.26±15.85 vs 15.41±9.51; F values: 13.09 and 7.05; t values: 5.20 and 4.04, both P<0.001). There were statistically significant differences among four groups in the first-order texture features ( F values: 4.30-9.65, all P<0.05), but there was no significant difference between DL group and 120 s group ( t values: from -1.25 to 0.15, all P>0.05). Conclusion:DL reconstruction model can improve the quality of short-frame PET images, which meets the needs of clinical diagnosis, efficacy evaluation and radiomics research.
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Objective:To analyze the differences in 18F-fluorodeoxyglucose (FDG) PET/CT imaging and preoperative localization between patients with temporal lobe epilepsy (TLE) and extratemporal epilepsy (ETLE) caused by focal cortical dysplasia (FCD). Methods:From April 2015 to August 2018, a total of 71 patients (45 males, 26 females, age (24.3±9.1) years) with refractory epilepsy who underwent 18F-FDG PET/CT imaging before surgery and confirmed as FCD by pathology in Xuanwu Hospital were retrospectively analyzed. Patients were divided into TLE and ETLE groups based on pathological results. 18F-FDG PET/CT images were analyzed qualitatively and compared with the operation result, then region of interest (ROI) was used to calculate the asymmetry index (AI), and evaluated the hypometabolism of every cerebral region by |AI| semi-quantitatively. Engle classification were followed-up after surgery. Independent-sample t test and χ2 test were used to analyze data. Results:Of 71 FCD patients, 35 were TLE and 36 were ETLE. The onset age of ETLE patients were younger than TLE patients ((10.1±6.5) vs (14.9±9.7) years; t=2.48, P=0.02). In TLE group, 54.29%(19/35) were completely consistent with the operation results, and 42.86%(15/35) showed hypometabolized brain regions in extratemporal lobe. In ETLE group, 27.78%(10/36) were completely consistent with the operation results, and 47.22%(17/36) showed hypometabolized brain regions in temporal lobe. There were significant differences in the lateral accuracy and positioning accuracy of 18F-FDG PET/CT between TLE and ETLE patients (97.14%(34/35) vs 75.00%(27/36), 54.29%(19/35) vs 27.78%(10/36); χ2 values: 7.19, 6.27, both P<0.05). There was no significant difference in |AI| values between the brain regions of TLE and ETLE patients ( z values: from -1.25 to -0.06, all P>0.05). Conclusion:The lateral accuracy and positioning accuracy of 18F-FDG PET/CT in TLE patients are better than that in ETLE patients.