Superparamagnetic Iron Oxide-Erastin-Polyethylene Glycol Nanotherapeutic Platform: A Ferroptosis-Based Approach for the Integrated Diagnosis and Treatment of Nasopharyngeal Cancer.

Erastin can induce ferroptosis in tumor cells as an effective small molecule inhibitor. However, its application is hampered by a lack of water solubility. This study investigated the effects of superparamagnetic iron oxide (SPIO)-erastin-polyethylene glycol (PEG) nanoparticles prepared by loading SPIO-PEG nanoparticles with erastin on ferroptosis. SPIO-erastin-PEG nanoparticles exhibited square and spherical shapes with good dispersibility. The zeta potential and hydrodynamic size of SPIO-erastin-PEG were measured as (-37.68 ± 2.706) mV and (45.75 ± 18.88) nm, respectively. On T2-weighted imaging, the nanosystem showed significant contrast enhancement compared to no-enhancement magnetic resonance imaging (MRI). SPIO-erastin-PEG induced ferroptosis by increasing reactive oxygen species and iron content and promoting the accumulation of lipid peroxides and the degradation of glutathione peroxidase 4. Pharmacokinetic experiments revealed a half-life of 1.25 ± 0.05 h for the SPIO-erastin-PEG solution in circulation. Moreover, significant antitumorigenic effects of SPIO-erastin-PEG have been demonstrated in 5-8F cells and mouse-bearing tumors. These results indicated that the synthesized SPIO-erastin-PEG nanoplatform could induce ferroptosis effects in vitro and in vivo while exhibiting favorable physical characteristics. This approach may provide a new strategy for theranostic nanoplatform for nasopharyngeal cancer.

MRI-based random survival Forest model improves prediction of progression-free survival to induction chemotherapy plus concurrent Chemoradiotherapy in Locoregionally Advanced nasopharyngeal carcinoma.

BACKGROUND: The present study aimed to explore the application value of random survival forest (RSF) model and Cox model in predicting the progression-free survival (PFS) among patients with locoregionally advanced nasopharyngeal carcinoma (LANPC) after induction chemotherapy plus concurrent chemoradiotherapy (IC + CCRT). METHODS: Eligible LANPC patients underwent magnetic resonance imaging (MRI) scan before treatment were subjected to radiomics feature extraction. Radiomics and clinical features of patients in the training cohort were subjected to RSF analysis to predict PFS and were tested in the testing cohort. The performance of an RSF model with clinical and radiologic predictors was assessed with the area under the receiver operating characteristic (ROC) curve (AUC) and Delong test and compared with Cox models based on clinical and radiologic parameters. Further, the Kaplan-Meier method was used for risk stratification of patients. RESULTS: A total of 294 LANPC patients (206 in the training cohort; 88 in the testing cohort) were enrolled and underwent magnetic resonance imaging (MRI) scans before treatment. The AUC value of the clinical Cox model, radiomics Cox model, clinical + radiomics Cox model, and clinical + radiomics RSF model in predicting 3- and 5-year PFS for LANPC patients was [0.545 vs 0.648 vs 0.648 vs 0.899 (training cohort), and 0.566 vs 0.736 vs 0.730 vs 0.861 (testing cohort); 0.556 vs 0.604 vs 0.611 vs 0.897 (training cohort), and 0.591 vs 0.661 vs 0.676 vs 0.847 (testing cohort), respectively]. Delong test showed that the RSF model and the other three Cox models were statistically significant, and the RSF model markedly improved prediction performance (P < 0.001). Additionally, the PFS of the high-risk group was lower than that of the low-risk group in the RSF model (P < 0.001), while comparable in the Cox model (P > 0.05). CONCLUSION: The RSF model may be a potential tool for prognostic prediction and risk stratification of LANPC patients.

MRI-Based Back Propagation Neural Network Model as a Powerful Tool for Predicting the Response to Induction Chemotherapy in Locoregionally Advanced Nasopharyngeal Carcinoma.

BACKGROUND: Pretreatment individualized assessment of tumor response to induction chemotherapy (ICT) is a need in locoregionally advanced nasopharyngeal carcinoma (LANPC). Imaging method plays vital role in tumor response assessment. However, powerful imaging method for ICT response prediction in LANPC is insufficient. PURPOSE: To establish a robust model for predicting response to ICT in LANPC by comparing the performance of back propagation neural network (BPNN) model with logistic regression model. STUDY TYPE: Retrospective. POPULATION: A total of 286 LANPC patients were assigned to training (N = 200, 43.8 ± 10.9 years, 152 male) and testing (N = 86, 43.5 ± 11.3 years, 57 male) cohorts. FIELD STRENGTH/SEQUENCE: T2 -weighted imaging, contrast enhanced-T1 -weighted imaging using fast spin echo sequences at 1.5 T scanner. ASSESSMENT: Predictive clinical factors were selected by univariate and multivariate logistic models. Radiomic features were screened by interclass correlation coefficient, single-factor analysis, and the least absolute shrinkage selection operator (LASSO). Four models based on clinical factors (Modelclinic ), radiomics features (Modelradiomics ), and clinical factors + radiomics signatures using logistic (Modelcombined ), and BPNN (ModelBPNN ) methods were established, and model performances were compared. STATISTICAL TESTS: Student's t-test, Mann-Whitney U-test, and Chi-square test or Fisher's exact test were used for comparison analysis. The performance of models was assessed by area under the receiver operating characteristic (ROC) curve (AUC) and Delong test. P < 0.05 was considered statistical significance. RESULTS: Three significant clinical factors: Epstein-Barr virus-DNA (odds ratio [OR] = 1.748; 95% confidence interval [CI], 0.969-3.171), sex (OR = 2.883; 95% CI, 1.364-6.745), and T stage (OR = 1.853; 95% CI, 1.201-3.052) were identified via univariate and multivariate logistic models. Twenty-four radiomics features were associated with treatment response. ModelBPNN demonstrated the highest performance among Modelcombined , Modelradiomics , and Modelclinic (AUC of training cohort: 0.917 vs. 0.808 vs. 0.795 vs. 0.707; testing cohort: 0.897 vs. 0.755 vs. 0.698 vs. 0.695). CONCLUSION: A machine-learning approach using BPNN showed better ability than logistic regression model to predict tumor response to ICT in LANPC. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 2.

A functional liver imaging score for preoperative prediction of liver failure after hepatocellular carcinoma resection.

OBJECTIVES: Posthepatectomy liver failure (PHLF) is a challenging complication after resection to treat hepatocellular carcinoma (HCC), and it is associated with high mortality. Preoperative prediction of PHLF may improve patient subsequent and reduce such mortality. This study examined whether a functional liver imaging score (FLIS) based on preoperative gadoxetic acid-enhanced magnetic resonance imaging (MRI) could predict PHLF. MATERIALS AND METHODS: The study included 502 patients who underwent preoperative gadoxetic acid-enhanced MRI, followed by HCC resection. Significant preoperative predictors of PHLF were identified using logistic regression analysis. The ability of FLIS to predict PHLF was evaluated using receiver operating characteristic curves, and its predictive power was compared to that of the model for end-stage liver disease (MELD) score, albumin-bilirubin (ALBI) score, and indocyanine green 15-min retention rate (ICG-R15). RESULTS: In multivariate analysis, PHLF was independently associated with FLIS (OR 0.452, 95% CI 0.361 to 0.568, p < 0.001) and major resection (OR 1.898, 95% CI 1.057 to 3.408, p = 0.032). FLIS was associated with a higher area under the receiver operating characteristic curve (0.752) than the MELD score (0.557), ALBI score (0.609), or ICG-R15 (0.605) (all p < 0.05). Patients with FLIS ≤ 4 who underwent major resection were at 9.4-fold higher risk of PHLF than patients with lower FLIS who underwent minor resection. CONCLUSION: FLIS is an independent predictor of PHLF, and it may perform better than the MELD score, ALBI score, and ICG-R15 clearance. We propose treating elevated FLIS and major resection as risk factors for PHLF. KEY POINTS: • A functional liver imaging score can independently predict posthepatectomy liver failure in patients with HCC. • The score may predict such failure better than MELD and ALBI scores and ICG-R15. • Patients with scores ≤ 4 who undergo major hepatic resection may be at nearly tenfold higher risk of posthepatectomy liver failure.

Preoperative normalized iodine concentration derived from spectral CT is correlated with early recurrence of hepatocellular carcinoma after curative resection.

OBJECTIVES: To investigate whether normalized iodine concentration (NIC) correlates with tumor microvessel density and early recurrence in patients with HCC. MATERIALS AND METHODS: We included 71 patients with surgically resected single HCC in this prospective study who underwent preoperative spectral CT between November 2014 and June 2016. Two observers independently measured the NIC in the arterial phase (AP) and portal venous phase (PVP). The relationship between NIC and microvessel density was evaluated. Univariate and multivariate logistic regression was performed to evaluate independent predictors of early recurrence. RESULTS: Early recurrence occurred in 28 of 71 patients (39.4%) during the 2-year follow-up. NIC-AP positively correlated with microvessel density for the two observers (r = 0.593 and 0.527). Based on multivariate analysis, independent risk factors for early HCC recurrence were tumor size (odds ratio, 1.200; p = 0.043) and NIC-AP (odds ratio, 2.522; p = 0.005). For the two observers, areas under the receiver operating characteristic curve for predicting early HCC recurrence were 0.719 and 0.677. Early recurrence rates were significantly higher among patients with NIC-AP values higher than the optimal cutoff than among those with values below the cutoff. CONCLUSION: Normalized iodine concentration in the arterial phase from spectral CT reflects tumor-derived angiogenesis and is a potential predictive biomarker for early recurrence of hepatocellular carcinoma. KEY POINTS: • Normalized iodine concentration in the arterial phase positively correlated with microvessel density of hepatocellular carcinoma. • In the patients with hepatocellular carcinoma, tumor size and normalized iodine concentration in the arterial phase were independent risk factors for early hepatocellular carcinoma recurrence. • Early hepatocellular carcinoma recurrence rates were significantly higher when normalized iodine concentration in the arterial phase values was above the optimal cutoff.

Polyethylene glycol-coated ultrasmall superparamagnetic iron oxide nanoparticles-coupled sialyl Lewis X nanotheranostic platform for nasopharyngeal carcinoma imaging and photothermal therapy.

BACKGROUND: Nasopharyngeal carcinoma (NPC) is a type of head and neck malignant tumor with a high incidence in specific regional distribution, and its traditional therapies face some challenges. It has become an urgent need to seek new therapeutic strategies without or with low toxicity and side effects. At present, more and more researchers has been attracting attention by nanotheranostic platform. Therefore, our team synthesized the polyethylene glycol-coated ultrasmall superparamagnetic iron oxide nanoparticles-coupled sialyl Lewis X (USPIO-PEG-sLex) nanotheranostic platform with high temperature pyrolysis. RESULTS: The USPIO-PEG-sLex nanoparticles had excellent photothermal conversion property, and the temperature of USPIO-PEG-sLex nanoparticles solution increased with its concentration and power density of near-infrared (NIR) on 808 nm wavelengths. Five USPIO-PEG-sLex nanoparticles with different concentrations of 0 mg/ml, 0.025 mg/ml, 0.05 mg/ml, 0.1 mg/ml and 0.2 mg/ml were prepared. The biological toxicity results showed that the viability of NPC 5-8F cells is related to the concentration of USPIO-PEG-sLex nanoparticles and the culture time (P < 0.001). The results of photothermal therapy (PTT) in vitro indicated that the viability of 5-8F cells decreased significantly with the concentration of USPIO-PEG-sLex nanoparticles increases (P < 0.001), and the viability of NPC 5-8F cells were 91.04% ± 5.20%, 77.83% ± 3.01%, 73.48% ± 5.55%, 59.50% ± 10.98%, 17.11% ± 3.14%, respectively. The USPIO-PEG-sLex nanoparticles could target the tumor area, and reduce the T2* value of tumor tissue. The T2* values of tumor pre- and post-injection were 30.870 ± 5.604 and 18.335 ± 4.351, respectively (P < 0.001). In addition, USPIO-PEG-sLex nanoparticles as a photothermal agent for PTT could effectively inhibit tumor progression. The ratio of volume change between tail vein injection group, control group, nanoparticles without laser irradiation group and blank group after 5 treatments were 3.04 ± 0.57, 5.80 ± 1.06, 8.09 ± 1.96, 7.89 ± 2.20, respectively (P < 0.001). CONCLUSIONS: Our synthesized USPIO-PEG-sLex nanotheranostic platform, and it may be become a new strategy for the treatment of NPC.

Value of Diffusion-Weighted Imaging Combined with Susceptibility-Weighted Imaging in Differentiating Benign from Malignant Parotid Gland Lesions.

BACKGROUND The aim of this study was to investigate the diagnostic value of diffusion-weighted imaging (DWI) in combination with susceptibility-weighted imaging (SWI) for differentiating benign parotid gland lesions from malignant ones. MATERIAL AND METHODS This retrospective study was approved by the Ethics Committee of our hospital. A total of 36 patients (26 benign cases and 10 malignant cases) were confirmed by surgical pathology. The apparent diffusion coefficient (ADC), normalized ADC (ADCNormalized), intratumoral susceptibility signals (ITSS), and morphological characteristics were analyzed with SPSS 19.0 software. RESULTS The mean ADC values of parotid gland lesions was not different between malignant and benign lesions (P=0.07), while the differences between ADCNormalized (P=0.026) and ITSS grading (P=0.014) were statistically significant. Logistic regression analysis identified use of ADCNormalized and ITSS as the only independent predictor of malignant lesions (odds ratio 0.038; 95% confidence interval 0.001~0.988; P=0.011) and (odds ratio 4.867; 95% confidence interval 1.442~16.423; P=0.049), respectively. The optimum threshold of the ADCNormalized values was -0.45%, ITSS grade was 2, the corresponding areas under the receiver operating characteristic curve (AUC) were 0.750 and 0.787 respectively, and the combination of the 2 was 0.846. CONCLUSIONS DWI integrated with SWI can significantly improve the diagnostic efficacy in distinguishing benign from malignant parotid lesions.

Non-enhanced MRI in combination with color Doppler flow imaging for improving diagnostic accuracy of parotid gland lesions.

PURPOSE: To determine the value of non-enhanced MRI in combination with color Doppler flow imaging (CDFI) for differentiating malignant parotid tumors from benign ones. METHODS: This retrospective study analyzed 51 parotid gland lesions (39 benign and 12 malignant) in 51 patients who underwent preoperative CDFI as well as non-enhanced MRI including T1-weighted, T2-weighted, and diffusion-weighted imaging (DWI). Degrees of intratumor vascularity were categorized into four grades basing on CDFI findings. The relationships between the lesion and its adjacent external carotid artery and retromandibular vein were inspected on T1-weighted and T2-weighted images. Apparent diffusion coefficient (ADC) values were calculated from diffusion-weighted images, and were used to classify the parotid gland lesions with and without reference to the CDFI findings. The classification results were compared using the McNemar test. Sensitivity, specificity, and accuracy percentages were calculated when the non-enhanced MRI/CDFI findings were used to differentiate benign lesions from malignant ones. RESULTS: The diagnostic accuracy (96.1 vs 82.4%) was significantly improved when ADCs were used together with CDFI findings for classifying parotid gland lesions compared to when ADCs were used alone. Pleomorphic adenomas had the highest ADCs. The ADC thresholds were 1.425 × 10-3 mm2/s for differentiating pleomorphic adenomas from carcinomas, 0.999 × 10-3 mm2/s for differentiating pleomorphic adenomas from other benign lesions, and 0.590 × 10-3 mm2/s for differentiating benign lesions other than pleomorphic adenomas from lymphomas. CONCLUSION: Combining CDFI with non-enhanced MRI can improve the diagnostic accuracy of MRI for classifying parotid gland lesions.

Targeted Delivery of Active Sites by Oxygen Vacancy-Engineered Bimetal Silicate Nanozymes for Intratumoral Aggregation-Potentiated Catalytic Therapy.

Biodegradable silicate nanoconstructs have aroused tremendous interest in cancer therapeutics due to their variable framework composition and versatile functions. Nevertheless, low intratumoral retention still limits their practical application. In this study, oxygen vacancy (OV)-enriched bimetallic silicate nanozymes with Fe-Ca dual active sites via modification of oxidized sodium alginate and gallic acid (GA) loading (OFeCaSA-V@GA) were developed for targeted aggregation-potentiated therapy. The band gap of silica markedly decreased from 2.76 to 1.81 eV by codoping of Fe3+ and Ca2+, enabling its excitation by a 650 nm laser to generate reactive oxygen species. The OV that occurred in the hydrothermal synthetic stage of OFeCaSA-V@GA can anchor the metal ions to form an atomic phase, offering a massive fabrication method of single-atom nanozymes. Density functional theory results reveal that the Ca sites can promote the adsorption of H2O2, and Fe sites can accelerate the dissociation of H2O2, thereby realizing a synergetic catalytic effect. More importantly, the targeted delivery of metal ions can induce a morphological transformation at tumor sites, leading to high retention (the highest retention rate is 36.3%) of theranostic components in tumor cells. Thus, this finding may offer an ingenious protocol for designing and engineering highly efficient and long-retention nanodrugs.

Precision USPIO-PEG-SLex Nanotheranostic Agent Targeted Photothermal Therapy for Enhanced Anti-PD-L1 Immunotherapy to Treat Immunotherapy Resistance.

Background: The anti-Programmed Death-Ligand 1 (termed aPD-L1) immune checkpoint blockade therapy has emerged as a promising treatment approach for various advanced solid tumors. However, the effect of aPD-L1 inhibitors limited by the tumor microenvironment makes most patients exhibit immunotherapy resistance. Methods: We conjugated the Sialyl Lewis X with a polyethylene glycol-coated ultrasmall superparamagnetic iron oxide (USPIO-PEG) to form UPS nanoparticles (USPIO-PEG-SLex, termed UPS). The physicochemical properties of UPS were tested and characterized. Transmission electron microscopy and ICP-OES were used to observe the cellular uptake and targeting ability of UPS. Flow cytometry, mitochondrial membrane potential staining, live-dead staining and scratch assay were used to verify the in vitro photothermal effect of UPS, and the stimulation of UPS on immune-related pathways at the gene level was analyzed by sequencing. Biological safety analysis and pharmacokinetic analysis of UPS were performed. Finally, the amplification effect of UPS-mediated photothermal therapy on aPD-L1-mediated immunotherapy and the corresponding mechanism were studied. Results: In vitro experiments showed that UPS had strong photothermal therapy ability and was able to stimulate 5 immune-related pathways. In vivo, when the PTT assisted aPD-L1 treatment, it exhibited a significant increase in CD4+ T cell infiltration by 14.46-fold and CD8+ T cell infiltration by 14.79-fold, along with elevated secretion of tumor necrosis factor-alpha and interferon-gamma, comparing with alone aPD-L1. This PTT assisted aPD-L1 therapy achieved a significant inhibition of both primary tumors and distant tumors compared to the alone aPD-L1, demonstrating a significant difference. Conclusion: The nanotheranostic agent UPS has been introduced into immunotherapy, which has effectively broadened its application in biomedicine. This photothermal therapeutic approach of the UPS nanotheranostic agent enhancing the efficacy of aPD-L1 immune checkpoint blockade therapy, can be instructive to address the challenges associated with immunotherapy resistance, thereby offering potential for clinical translation.

Chinese expert consensus on imaging diagnosis of drug-resistant pulmonary tuberculosis.

Tuberculosis (TB) remains one of the major infectious diseases in the world with a high incidence rate. Drug-resistant tuberculosis (DR-TB) is a key and difficult challenge in the prevention and treatment of TB. Early, rapid, and accurate diagnosis of DR-TB is essential for selecting appropriate and personalized treatment and is an important means of reducing disease transmission and mortality. In recent years, imaging diagnosis of DR-TB has developed rapidly, but there is a lack of consistent understanding. To this end, the Infectious Disease Imaging Group, Infectious Disease Branch, Chinese Research Hospital Association; Infectious Diseases Group of Chinese Medical Association of Radiology; Digital Health Committee of China Association for the Promotion of Science and Technology Industrialization, and other organizations, formed a group of TB experts across China. The conglomerate then considered the Chinese and international diagnosis and treatment status of DR-TB, China's clinical practice, and evidence-based medicine on the methodological requirements of guidelines and standards. After repeated discussion, the expert consensus of imaging diagnosis of DR-PB was proposed. This consensus includes clinical diagnosis and classification of DR-TB, selection of etiology and imaging examination [mainly X-ray and computed tomography (CT)], imaging manifestations, diagnosis, and differential diagnosis. This expert consensus is expected to improve the understanding of the imaging changes of DR-TB, as a starting point for timely detection of suspected DR-TB patients, and can effectively improve the efficiency of clinical diagnosis and achieve the purpose of early diagnosis and treatment of DR-TB.

Apparent diffusion coefficient ratio between axillary lymph node with primary tumor to detect nodal metastasis in breast cancer patients.

PURPOSE: To evaluate the ratios of apparent diffusion coefficient (ADC) calculated from diffusion weighted imaging (DWI) between axillary lymph nodes with primary breast tumor lesions in the detection of axillary lymph nodes metastasis in breast cancer patients. MATERIALS AND METHODS: A total of 36 patients with breast tumors and their axillary lymph nodes were included in this study for MR image scan. The ADC values were calculated using DW-MR imaging software. The ADC values and the ADC ratios of axillary lymph nodes in patients with primary breast lesion were compared among benign and metastatic axillary lymph nodes. All the diagnosis were confirmed by histopathological examination. RESULTS: The mean ADC value of metastatic lymph nodes was significantly lower than those of benign lymph nodes (0.787 × 10(-3) mm(2)/s ± 0.145 versus 1.043 × 10(-3) mm(2)/s ± 0.257) (P < 0.05). In addition, ADC ratio of metastatic lymph nodes with breast lesion was significantly lower than those of benign lymph nodes with breast tumor lesions (0.986 ± 0.17 versus 1.375 ± 0.417) (P < 0.05). Once the ADC ratio was fixed at 0.889 × 10(-3) mm(2)/s, the sensitivity, specificity, and accuracy were 82.22%, 82.35% and 82.28%, respectively. The cutoff of ADC ratio was at 1.097 × 10(-3) mm(2)/s, the sensitivity, specificity, and accuracy can be up to 84.44%, 88.24%, and 86.08%. CONCLUSION: ADC value and ADC ratio could be used as a reliable parameter to detect the axillary lymph nodes metastasis in breast cancer patients, and ADC ratio has a higher accuracy.

Meta-analysis of diffusion-weighted magnetic resonance imaging in detecting prostate cancer.

PURPOSE: The objective of this study was to determine the diagnostic performance of quantitative diffusion-weighted magnetic resonance imaging in detection of prostate cancer. METHODS: A comprehensive search was performed for English articles published before May 2012 that fulfilled the following criteria: patients had histopathologically proved prostate cancer; diffusion-weighted imaging (DWI) was performed for the detection of prostate cancer, and data for calculating sensitivity and specificity were included. Methodological quality was assessed by using the quality assessment of diagnostic studies instrument. Publication bias analysis, homogeneity, inconsistency index, and threshold effect were performed by STATA version 12. RESULTS: Of 119 eligible studies, 12 with 1637 malignant and 4803 benign lesions were included. There was notable heterogeneity beyond threshold effect and publication bias. The sensitivity and specificity with 95% confidence interval (CI) estimates of DWI on a per-lesion basis were 77% (CI, 0.76-0.84) and 84% (CI, 0.78-0.89), respectively, and the area under the curve of summary receiver operating characteristic curve was 0.88 (CI, 0.85-0.90). The overall positive and negative likelihood ratios with 95% CI were 4.93 (3.39-7.17) and 0.278 (0.19-0.39), respectively. CONCLUSIONS: Quantitative DWI has a relative sensitivity and specificity to distinguish malignant from benign in prostate lesions. However, large-scale randomized control trials are necessary to assess its clinical value because of nonuniformed diffusion gradient b factor, diagnosis threshold, and small number of studies.

A three-gene signature reveals changes in the tumor immune microenvironment in the progression from NAFLD to HCC.

Hepatocellular carcinoma (HCC) is one of the most dangerous malignant tumors. The incidence rates of obesity related NAFLD and NASH are increasing year by year, and they are the main risk factors for HCC at present. Finding the mechanism of malignant transformation of NAFLD and NASH is helpful for early prevention and diagnosis. In this study, we performed differential analysis using NAFLD data, NASH data, and HCC data to identify crossover differential genes. Then, using the clinical data of TCGA, a prognostic risk prediction model of three genes (TEAD4, SOCS2, CIT) was constructed, and survival analysis and receiver operating characteristic curves were drawn. The prognostic model was validated using ICGC, GSE116174 and GSE54236 datasets. In addition, we assessed immune status and function in high- and low-risk populations using a prognostic model. Moreover, we assessed the expression of CIT in clinical samples and HCC cell lines and validated its role in HCC development. Our study elucidates the important role of the tumor immune microenvironment in the development of NAFLD/NASH to HCC, deepens the understanding of the pathogenesis of NAFLD/NASH development to HCC, and is helpful for clinical management and decision-making.

Diagnostic value of a CT-based radiomics nomogram for discrimination of benign and early stage malignant ovarian tumors.

BACKGROUND: This study aimed to identify the diagnostic value of models constructed using computed tomography-based radiomics features for discrimination of benign and early stage malignant ovarian tumors. METHODS: The imaging and clinicopathological data of 197 cases of benign and early stage malignant ovarian tumors (FIGO stage I/II), were retrospectively analyzed. The patients were randomly assigned into training data set and validation data set. Radiomics features were extracted from images of plain computed tomography scan and contrast-enhanced computed tomography scan, were then screened in the training data set, and a radiomics model was constructed. Multivariate logistic regression analysis was used to construct a radiomic nomogram, containing the traditional diagnostic model and the radiomics model. Moreover, the decision curve analysis was used to assess the clinical application value of the radiomics nomogram. RESULTS: Six textural features with the greatest diagnostic efficiency were finally screened. The value of the area under the receiver operating characteristic curve showed that the radiomics nomogram was superior to the traditional diagnostic model and the radiomics model (P < 0.05) in the training data set. In the validation data set, the radiomics nomogram was superior to the traditional diagnostic model (P < 0.05), but there was no statistically significant difference compared to the radiomics model (P > 0.05). The calibration curve and the Hosmer-Lemeshow test revealed that the three models all had a great degree of fit (All P > 0.05). The results of decision curve analysis indicated that utilization of the radiomics nomogram to distinguish benign and early stage malignant ovarian tumors had a greater clinical application value when the risk threshold was 0.4-1.0. CONCLUSIONS: The computed tomography-based radiomics nomogram could be a non-invasive and reliable imaging method to discriminate benign and early stage malignant ovarian tumors.

Regional lymph node density-based nomogram predicts prognosis in nasopharyngeal carcinoma patients without distant metastases.

BACKGROUND: Nasopharyngeal carcinoma (NPC) is a relatively common type of cancer in Southern China, with local recurrence or distant metastases even after radical treatment; consequently, it is critical to identify the patients at higher risk for these events beforehand. This study aimed to assess the prognostic value of regional lymph node density (RLND) associated nomograms in NPC and to evaluate the utility of nomograms in risk stratification. METHODS: A total of 610 NPC patients without distant metastases (425 in the training and 185 in the validation cohort) were enrolled. The MRI-identified nodal features and clinical characteristics were documented, and the RLND was calculated. Cox analyses were conducted to identify prognostic-associated factors. Nomograms were generated based on the multivariate analysis results. The predictive accuracy and discriminative ability of the nomogram models were determined using the concordance index (C-index), receiver operating characteristic (ROC) curve, and calibration curve; the results were compared with those of the tumor-node-metastasis (TNM) classification. Decision curve analysis (DCA) and C-index were used to assess the prognostic effect and added discriminative ability of RLND. We also estimated the optimal RLND-based nomogram score cut-off values for survival prediction. RESULTS: RLND was an independent predictor of overall survival (OS) and disease-free survival (DFS), with hazard ratios of 1.36 and 1.30, respectively. RLND was utilized in the construction of nomograms, alongside other independent prognostic factors. The RLND-based nomogram models presented a more effective discriminative ability than the TNM classification for predicting OS (C-index, 0.711 vs. 0.680) and DFS (C-index, 0.681 vs. 0.669), with favorable calibration and consistency. The comparison of C-index values between the nomogram models with and without RLND provided substantiation of the crucial role RLND plays in these models. DCA confirmed the satisfactory clinical practicability of RLND. Moreover, the nomograms were used to categorize the patients into three groups (high-, middle-, and low-risk), and the Kaplan-Meier curves showed significant differences in prognosis between them (p < 0.05). These results were verified in the validation cohort. CONCLUSION: RLND stands as a robust prognostic factor in NPC. The RLND-based nomograms excel in predicting survival, surpassing the TNM classification.

A Clinical-Radiomics Nomogram Based on Magnetic Resonance Imaging for Predicting Progression-Free Survival After Induction Chemotherapy in Nasopharyngeal Carcinoma.

Purpose: This paper aimed to establish and verify a radiomics model based on magnetic resonance imaging (MRI) for predicting the progression-free survival of nasopharyngeal carcinoma (NPC) after induction chemotherapy (IC). Materials and Methods: This cohort consists of 288 patients with clinical pathologically confirmed NPC, which was collected from January 2015 to December 2018. All NPC patients were randomly divided into two cohorts: training (n=202) and validation (n=86). Radiomics features from the MRI images of NPC patients were extracted and selected before IC. The patients were classified into high- and low-risk groups according to the median of Radscores. The significant imaging features and clinical variables in the univariate analysis were constructed for progression-free survival (PFS) using the multivariate Cox regression model. A survival analysis was performed using Kaplan-Meier with log-rank test and then each model's stratification ability was evaluated. Results: Epstein-Barr virus (EBV) DNA before treatment was an independent predictor for PFS (p < 0.05). Based on the pyradiomic platform, we extracted 1,316 texture parameters in total. Finally, 16 texture features were used to build the model. The clinical radiomics-based model had good prediction capability for PFS, with a C-index of 0.827. The survival curve revealed that the PFS of the high-risk group was poorer than that of the low-risk group. Conclusion: This research presents a nomogram that merges the radiomics signature and the clinical feature of the plasma EBV DNA load, which may improve the ability of preoperative prediction of progression-free survival and facilitate individualization of treatment in NPC patients before IC.

The accuracy of computed tomographic perfusion in detecting recurrent nasopharyngeal carcinoma after radiation therapy.

OBJECTIVES: To assess the diagnostic accuracy of computed tomographic (CT) perfusion technique in discriminating recurrent nasopharyngeal carcinoma (NPC) after radiation therapy. METHODS: Forty-eight patients with a pathologic finding as reference standards were divided into 2 groups, recurrent and nonrecurrent NPCs. Perfusion parameters blood flow (BF), blood volume (BV), permeability surface (PS), and mean transit time were statistically analyzed. A receiver operating characteristic curve was used to study whether CT perfusion parameters could aid in detecting recurrent NPC. RESULTS: Blood flow, BV, and PS values between recurrent NPC (n = 27) and nonrecurrent NPC (n = 21) were 526.8 (168.1) versus 312.1 (214.4) mL/100 g per minute, 35.1 (23.6) versus 9.2 (8.0) (ml/100 g), and 53.4 (34.3) versus 17.6 (14.7) mL/100 g per minute, respectively. There was a significant difference between these 2 groups (P < 0.01). Mean transit time values in these 2 groups were 3.5 (2.0) versus 4.3 (2.7) seconds; there was no statistical difference. To optimize sensitivity and specificity, BF, BV, and PS threshold values for differentiating between recurrent and nonrecurrent NPCs were 537.20 mL/100 g per minute, 37.18 (ml/100 g), and 57.34 mL/100 g per minute, respectively. According to threshold values of BF, BV, and PS, sensitivity and specificity for distinguishing recurrent and nonrecurrent NPCs were 92.6% and 76.2%, 96.3% and 81%, and 81.5% and 61.9%, respectively. CONCLUSIONS: The CT perfusion technique may be helpful to find patients with recurrent NPC after radiation therapy.

Peritumoral edema in preoperative magnetic resonance imaging is an independent prognostic factor for hepatocellular carcinoma.

BACKGROUND: Peritumoral edema is an independent prognostic risk factor for malignant tumors. Therefore, assessment of peritumoral edema in preoperative magnetic resonance imaging (MRI) may provide better prognostic information in patients with hepatocellular carcinoma (HCC). AIM: To determine whether peritumoral edema in preoperative MRI is a prognostic factor for HCC. METHODS: A retrospective analysis of 90 patients with HCC confirmed by surgical pathology was performed. All patients' peritumoral edema in preoperative MRI was reviewed by two radiologists. The association of disease recurrence with peritumoral edema and clinicopathological features was assessed using the Cox proportional hazards model. Interobserver agreement for evaluating peritumoral edema was determined using Cohen's κ coefficient. RESULTS: Recurrence and non-recurrence after an average 20.8 month follow-up was 25.6% (23/90) and 74.4% (67/90), respectively. The ratio of peritumoral edema of 90 patients with HCC in preoperative MRI was 35.6% (32/90). In univariate Cox regression analysis, peritumoral edema [hazard ratio (HR) 11.08, P < 0.001], tumor diameter (HR 4.12, P = 0.001), microvascular invasion (HR 2.78, P = 0.020), gender (HR 0.29, P = 0.006), cirrhosis (HR 2.45, P = 0.049), ascites syndrome (HR 2.83, P = 0.022), aspartate aminotransferase(AST)/alanine aminotransferase(ALT) (HR 5.07, P = 0.003) were indicators for HCC recurrence. In multivariate Cox regression analysis, the tumor diameter (HR 2.53, P = 0.032) and peritumoral edema (HR 8.71, P < 0.001) were independent prognostic factors of HCC. The sensitivity, specificity, positive predictive value and negative predictive value of peritumoral edema and tumor diameter were 82.6%&60.9%, 80.6%&77.6%, 59.4%&48.3%, and 93.1%&85.3%, respectively. CONCLUSION: Peritumoral edema in preoperative MRI may be considered as a biomarker of prognostic information for patients with HCC.

Ultrasmall superparamagnetic nanoparticles targeting E-selectin: synthesis and effects in mice in vitro and in vivo.

Purpose: We developed a contrast agent for targeting E-selectin expression. We detected the agent using magnetic resonance imaging (MRI) in vivo in nude mice that had undergone nasopharyngeal carcinoma (NPC) metastasis. Methods: Sialyl Lewis X (sLeX) was conjugated with ultrasmall superparamagnetic iron oxide (USPIO) nanoparticles. Hydrodynamic size, polydispersity index, and ζ-potential of USPIO-polyethylene glycol (PEG) nanoparticles and USPIO-PEG-sLeX nanoparticles were measured. Component changes in nanoparticles of USPIO, USPIO-PEG, and USPIO-PEG-sLeX were analyzed by thermogravimetric analysis and Fourier-transform infrared spectroscopy. A model of NPC metastasis to inguinal lymph nodes in nude mice was used to investigate characteristics of the USPIO-PEG-sLeX nanoparticles in vivo. We investigated the ability of the T2* value, change in T2* value (ΔT2* value), and enhancement rate (ER) to assess accumulation of USPIO-PEG-sLeX nanoparticles quantitatively in mice of a metastasis group and control group. Four MRI scans were undertaken for each mouse. The first scan (t0) was done before administration of USPIO-PEG-sLeX nanoparticles (0.1 mL) via the tail vein. The other scans were carried out at 0 (t1), 1 (t2), and 2 hours (t3) postinjection. The mean optical density was used to reflect E-selectin expression. Results: sLeX was labeled onto USPIO successfully. In vivo, there were significant interactions between the groups and time for T2* values after administration of USPIO-PEG-sLeX nanoparticles. Six parameters (T2* at t2, ΔT2* at t1, ΔT2* at t2, ER at t1, ER at t2, and ER at t3) were correlated with the mean optical density. Conclusion: USPIO-PEG-sLeX nanoparticles can be used to assess E-selectin expression quantitatively. Use of such molecular probes could enable detection of early metastasis of NPC, more accurate staging, and treatment monitoring.