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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
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
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 exploring the uptake of fibroblast activation protein (FAP) inhibitor (FAPI) in pancreatic cancer through 68Ga-FAPI-04 PET/CT imaging, and provide a basis for the FAP-targeted imaging of pancreatic cancer. Methods:Pancreatic cancer-patient-derived tumor xenograft (PDX) mouse models ( n=8) were developed, then 68Ga-FAPI-04 and 18F-FDG microPET/CT imaging were performed (4 in each group). The differences of percentage activity of injection dose per gram of tissue (%ID/g) of 68Ga-FAPI-04 and 18F-FDG were analyzed by independent-sample t test. 68Ga-FAPI-04 and 18F-FDG PET/CT imaging were performed in 5 patients (4 males, 1 female, age: 46-74 (63.0±11.9) years) with pancreatic cancer, and the maximum standardized uptake value (SUV max) of 68Ga-FAPI-04 and 18F-FDG in primary pancreatic cancer and the SUV max ratio of liver metastases to liver tissue were compared by paired t test. Results:MicroPET/CT imaging showed that 68Ga-FAPI-04 was obviously uptaken at all time points in the tumor of PDX mice. The uptake of 68Ga-FAPI-04 in PDX mice 60 min after injection was significantly higher than that of 18F-FDG ((6.58±0.44) and (4.29±0.13) %ID/g; t=4.152, P=0.008 9). PET/CT showed that the SUV max of 68Ga-FAPI-04 in pancreatic cancer was significantly higher than that of 18F-FDG (16.82±3.08 and 5.14±2.20; t=6.893, P=0.000 1) and the SUV max ratio of liver metastases to liver tissue of 68Ga-FAPI-04 was also significantly higher than that of 18F-FDG (4.57±1.47 and 1.30±0.16; t=3.803, P=0.019 1). Conclusion:68Ga-FAPI-04 can be highly uptaken in pancreatic cancer, suggesting that FAP can be a potential target for PET/CT imaging of pancreatic cancer.
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18F-fluorodeoxyglucose(FDG) PET/MR has been more and more widely used in non-small cell lung cancer (NSCLC). Compared with PET/CT, PET/MR has more advantages, such as higher contrast resolution of soft tissues, less radiation dose and providing physicians with more functional parameters. This article summarizes the application status of 18F-FDG PET/MR in NSCLC in terms of diagnosis, staging, restaging, and prognosis.
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Objective:To investigate 18F-fluorodeoxyglucose (FDG) PET/CT imaging manifestations and digestive endoscopy of gastric mucosa-associated lymphoid tissue (MALT) lymphoma and evaluate whether maximum standardized uptake value (SUV max) can reflect the tumor proliferation activity and diagnose the diffuse large B cell transformation. Methods:18F-FDG PET/CT of 36 untreated histologically confirmed gastric MALT lymphoma patients (19 males, 17 females, age (46.4±18.1) years) between December 2012 and January 2019 in Nanjing Drum Tower Hospital were reviewed retrospectively. A positive or negative PET was defined based on visual analysis. 18F-FDG uptake above surrounding tissues in the regions of interest defined by the nuclear physician was considered positive, while negative was definited if the 18F-FDG uptake below surrounding tissues. Types of uptake included focal uptake and diffuse uptake. The characteristic findings of 18F-FDG PET/CT and digestive endoscopy (3 types: chronic gastritis-like type, depressed type and protruding type) in the consecutive patients were evaluated. The region of interest was drawn and the maximum standardized uptake value (SUV max) was measured. One-way analysis of variance and the least siginficant difference t test were used to compare the SUV max of 3 types of lesions and Mann-Whitney U test was used for comparison of SUV max between lesions with/without diffuse large B cell transformation. The correlation between SUV max and Ki-67 was assessed by Spearman rank correlation analysis. Receiver operating characteristic (ROC) curve analysis was performed to calculate the optimal cut-off value for the diagnosis of diffuse large B cell transformation. Results:Positive 18F-FDG PET/CT were found in 15 patients and the diagnostic accuracy was 41.7%(15/36). 18F-FDG uptake results were positive for all protruding tumors (5/5) mainly with focal uptake (4/5), but only 4/16 for chronic gastritis-like type tumors and 6/15 for depressed type tumors. SUV max of protruding type tumors (10.7±6.4) was significantly higher than chronic gastritis-like type tumors (2.1±0.8) and depressed type tumors (2.7±1.4; F=13.010, all P<0.05). SUV max (2.7(1.8, 5.0)) was associated with Ki-67 (10%(15%, 40%); rs=0.345, P=0.039). SUV max of tumors with diffuse large B cell transformation in 36 patients was significantly higher than that with no transformation (9.4(3.1, 14.8) vs 2.3(1.7, 3.9); z=-3.044, P=0.002), and the cut-off value of SUV max was 6.5 (area under the curve: 0.788, P=0.011). Conclusions:18F-FDG PET may be a useful method for evaluating protruding type gastric MALT lymphoma but not appropriate for chronic gastritis-like type or depressed type tumors. SUV max may be a useful biomarker for tumor proliferation activity and can be used for diffuse large B cell transformation diagnosis in gastric MALT lymphoma patients.
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Objective:To explore the role of 18F-fluorodeoxyglucose (FDG) PET/CT in early detection of therapy-associated cardiotoxicity (TACT) in lymphoma patients and to analyze the diagnostic efficacy of different evaluation criteria. Methods:Consecutive patients between November 2009 to October 2018 in Peking University Cancer Hospital were retrospectively enrolled. All patients underwent standard chemotherapy. Myocardial uptake of 18F-FDG pre- and post-treatment were analyzed by visual interpretation and semi-quantitative (maximum standardized uptake value, SUV max) methods. The value of pre-treatment SUV max-heart -post-treatment SUV max-heart (ΔSUV max), %ΔSUV max, and post-treatment SUV max-heart/SUV max-mediastinum, SUV max-heart/SUV max-liver and SUV max-heart/SUV max-background(left gluteal muscle) ratios were calculated. Receiver operating characteristic (ROC) curve analysis was performed to determine optimal cut-off values of those PET/CT imaging criteria for evaluating early TACT of lymphoma, taking electrocardiogram (ECG) positive as the end point. Independent-sample t test and χ2 test were performed. Results:A total of 274 patients (median age was 36-year old), with the male-to-female ratio of 1.85∶1, were included, and 78.1%(214/274) of them had non-Hodgkin′s lymphoma (NHL). After treatment, 55.1%(151/274)of the patients had high myocardial uptake of 18F-FDG (compared with liver uptake), 20.4%(56/274) of them had moderate myocardial uptake (between liver uptake and blood-pool uptake), and 24.5%(67/274) were with equal uptake (less than blood-pool uptake). There were significant differences in myocardial uptake between ECG-positive group ( n=71) and ECG-negative group ( n=203) ( SUV max: 7.77±4.06 vs 5.91±3.04; t=4.045, P<0.01). ROC curves showed that optimal thresholds of post-treatment SUV max-heart, Δ SUV max-heart, %ΔSUV max-heart, and post-treatment SUV max-heart/SUV max-mediastinum, SUV max-heart/SUV max-liver and SUV max-heart/SUV max-background ratios were 9.4, 4.8, 1.4, 5.0, 2.3, 7.0 respectively. The corresponding areas under the curves (AUC) were 0.653, 0.637, 0.612, 0.655, 0.649 and 0.650, respectively. The sensitivity, specificity, positive predictive value, negative predictive value and accuracy of post-treatment SUV max-heart/SUV max-background ratio were 40.85%(29/71), 82.76%(168/203), 45.31%(29/64), 80.00%(168/210) and 71.90%(197/274). Conclusion:18F-FDG PET/CT can early detect TACT in patients with lymphoma, and if using 7.0 as the threshold of post-treatment SUV max-heart/SUV max- background ratio, the specificity and negative predictive value of 18F-FDG PET/CT for early prediction of TACT are up to 80%.
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Objective:To compare the diagnostic efficacy of 68Ga-prostate specific membrane antigen (PSMA)-11 PET/CT and 18F-fluorodeoxyglucose (FDG) PET/CT in TNM staging before radical prostatectomy. Methods:From July 2018 to December 2019, a total of 67 patients ((67.5±6.8) years) with prostate cancer diagnosed pathologically by radical surgery in Renji Hospital, School of Medicine, Shanghai Jiao Tong University were retrospectively enrolled. All patients underwent 68Ga-PSMA-11 PET/CT and 18F-FDG PET/CT whole-body scans before surgery. Results of PET/CT were compared with pathological diagnosis after surgery to compare the diagnostic efficiencies of 68Ga-PSMA-11 PET/CT and 18F-FDG PET/CT for preoperative TNM staging ( χ2 test). The differences of the maximum standardized uptake value (SUV max) in primary lesions between 2 imaging methods were compared by Mann-Whitney U test. Patients were divided into low-risk, intermediate-risk and high-risk for stratified analysis. Results:Among 67 patients, 9 were with low-risk, 19 were with intermediate-risk, 39 were with high-risk. For T staging, 59 (88.06%, 59/67) patients showed positive results by 68Ga-PSMA-11 PET/CT imaging, with median SUV max of 13.80(7.30, 22.40) for 67 patients; 31(46.27%, 31/67) patients showed positive results in 18F-FDG PET/CT imaging, with median SUV max of 4.00(3.10, 5.60) ( U=62, P<0.05). Stratifed analysis showed that the detection rate of 68Ga-PSMA-11 PET/CT was higher than that of 18F-FDG PET/CT in intermediate-risk patients (17/19 vs 6/19; χ2=4.920, P<0.05). Among 67 patients, 10 were diagnosed as N1 stage based on the pathological results. The sensitivities, specificities, accuracies, positive predictive values and negative predictive values of 68Ga-PSMA-11 PET/CT and 18F-FDG PET/CT for detecting positive regional lymph nodes were 6/10, 87.72%(50/57), 83.58%(56/67), 6/13, 92.59%(50/54) and 4/10, 89.47%(51/57), 82.09%(55/67), 4/10, 89.47%(51/57), respectively. 68Ga-PSMA-11 PET/CT detected 15 patients (22.39%, 15/67) with M1 stage, and 18F-FDG PET/CT identified 9 patients (13.43%, 9/67; χ2=35.436, P<0.05). Conclusions:As for T staging, the detection rate of 68Ga-PSMA-11 PET/CT in the intermediate-risk group is better than 18F-FDG PET/CT. In N and M staging, the detection rates of 68Ga-PSMA-11 PET/CT are higher than those of 18F-FDG PET/CT.
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Objective:To investigate whether the intratumoral heterogeneity measured by preoperative 18F-fluorodeoxyglucose (FDG) PET/CT could predict regional lymph node metastasis (LNM) in patients with clinical (c)N0 colorectal cancer. Methods:A total of 70 patients with cN0 colorectal cancer were consecutively enrolled from January 2012 to December 2019. All patients underwent 18F-FDG PET/CT followed by radical resection of colorectal cancer within one month. Whether the regional LNM existed was confirmed pathologically. Volume of interest (VOI) was drawn with the threshold of the standardized uptake value (SUV) of 2.5. The area under the cumulative SUV histograms curve (AUC-CSH) of the primary lesion was calculated by PMOD software, as well as the maximum SUV (SUV max), metabolic tumor volume (MTV) and total lesion glycolysis (TLG). Differences of AUC-CSH and metabolic parameters between groups were compared by using independent-sample t test and Mann-Whitney U test. Whether AUC-CSH was the independent predictor of regional LNM was analyzed with multivariate logistic regression model. The receiver operating characteristic (ROC) curve was used to evaluate the predictive value of AUC-CSH. Results:Among 70 patients with cN0 colorectal cancer, 16(22.9%) patients were pathologically confirmed to have regional LNM. The AUC-CSH of metastasis group was significantly lower than that of non-metastasis group (0.372±0.089 vs 0.464±0.121; t=2.831, P=0.006). There were no significant differences in SUV max(21.0±9.6 vs 23.9±10.9), MTV (33.0(20.8, 50.2) vs 28.3(16.0, 47.1) cm 3) and TLG (203.3(117.2, 467.5) vs 184.5(105.6, 434.3) g) of the primary tumor between those two groups( t=0.980, U values: 0.517, 0.028, all P>0.05). The multivariate logistic regression analysis showed AUC-CSH was the independent predictor of regional lymph node matastasis (odds ratios ( OR)=5.04, 95% CI: 1.37-18.60, P=0.015). The ROC curve analysis showed the area under the curve of AUC-CSH was 0.73 (95% CI: 0.59-0.86, P=0.006). When the cut-off value of AUC-CSH was 0.409, the sensitivity and specificity of predicting regional LNM was 12/16 and 66.7%(36/54), respectively. Conclusions:The intratumoral heterogeneity of primary tumor is strongly associated with regional LNM in cN0 colorectal cancer. AUC-CSH measured by preoperative 18F-FDG PET/CT has a potential in prediction of regional LNM in patients with cN0 colorectal cancer.
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Gaucher′s disease (GD) is a lysosomal storage disease, and the etiology of GD is the decreased activity of glucocerebrosidase, which leads to the accumulation of glucocerebroside in the lysosomes of macrophages. Because GD is rare and lacks specific clinical manifestations, it is easy to be misdiagnosed, which delays the best time for treatment. Early diagnosis, clinical evaluation, and regular monitoring of the disease have important clinical significance for enzyme replacement therapy in patients with GD. Recent studies have found that radionuclide imaging is playing an increasingly important role in the diagnosis and treatment of GD. This article introduces the application of radionuclide imaging in the diagnosis and management of GD.
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Objective:To investigate the value of 18F-fluorodeoxyglucose (FDG) PET imaging in evaluating the 18F-FDG influx rate of lungs and its relationship with parameters of pulmonary hemodynamics in patients with pulmonary arterial hypertension related to congenital heart disease (PAH-CHD). Methods:From January 2018 to June 2019, a total of 16 PAH-CHD patients (6 males, 10 females, age (29.2±10.6) years) and 22 health controls who received physical examinations (8 males, 14 females, age (45.4±3.8) years) in Fuwai Hospital were respectively enrolled. All cases underwent dynamic 18F-FDG PET imaging for whole lung 18F-FDG influx rate (presented as Ki). Right heart catheterization was performed to evaluate pulmonary hemodynamic parameters such as pulmonary vascular resistance (PVR), mean pulmonary vascular pressure (mPAP) in PAH-CHD patients after imaging within one week. Independent-sample t test was used to compare Ki of 2 groups, and Pearson correlation analysis was used to analyze the relationship between Ki and PVR, mPAP in PAH-CHD patients. Results:Ki of the lungs was significantly higher in PAH-CHD patients than that in controls ((0.000 6±0.000 3) vs (0.000 4±0.000 3) ml·g -1·min -1; t=2.15, P=0.038). Ki was not correlated with PVR ((10.86±4.45) Wood units) or mPAP ((69.75±18.93) mmHg; 1 mmHg=0.133 kPa) in PAH-CHD patients ( r values: 0.202 and 0.006, both P>0.05). Conclusions:Pulmonary vascular remodeling can lead the increasing lung 18F-FDG uptake in patients with PAH-CHD. 18F-FDG PET may have the ability in monitoring and evaluating pulmonary vascular remodeling in PAH-CHD.
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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.
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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 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 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 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 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 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 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.