A CT-based nomogram established for differentiating gastrointestinal heterotopic pancreas from gastrointestinal stromal tumor: compared with a machine-learning model.

OBJECTIVE: To identify CT features and establish a nomogram, compared with a machine learning-based model for distinguishing gastrointestinal heterotopic pancreas (HP) from gastrointestinal stromal tumor (GIST). MATERIALS AND METHODS: This retrospective study included 148 patients with pathologically confirmed HP (n = 48) and GIST (n = 100) in the stomach or small intestine that were less than 3 cm in size. Clinical information and CT characteristics were collected. A nomogram on account of lasso regression and multivariate logistic regression, and a RandomForest (RF) model based on significant variables in univariate analyses were established. Receiver operating characteristic (ROC) curve, mean area under the curve (AUC), calibration curve and decision curve analysis (DCA) were carried out to evaluate and compare the diagnostic ability of models. RESULTS: The nomogram identified five CT features as independent predictors of HP diagnosis: age, location, LD/SD ratio, duct-like structure, and HU lesion/pancreas A. Five features were included in RF model and ranked according to their relevance to the differential diagnosis: LD/SD ratio, HU lesion/pancreas A, location, peritumoral hypodensity line and age. The nomogram and RF model yielded AUC of 0.951 (95% CI: 0.842-0.993) and 0.894 (95% CI: 0.766-0.966), respectively. The DeLong test found no statistically significant difference in diagnostic performance (p > 0.05), but DCA revealed that the nomogram surpassed the RF model in clinical usefulness. CONCLUSION: Two diagnostic prediction models based on a nomogram as well as RF method were reliable and easy-to-use for distinguishing between HP and GIST, which might also assist treatment planning.

Recent Advances in Well-Designed Therapeutic Nanosystems for the Pancreatic Ductal Adenocarcinoma Treatment Dilemma.

Pancreatic ductal adenocarcinoma (PDAC) is a highly malignant tumor with an extremely poor prognosis and low survival rate. Due to its inconspicuous symptoms, PDAC is difficult to diagnose early. Most patients are diagnosed in the middle and late stages, losing the opportunity for surgery. Chemotherapy is the main treatment in clinical practice and improves the survival of patients to some extent. However, the improved prognosis is associated with higher side effects, and the overall prognosis is far from satisfactory. In addition to resistance to chemotherapy, PDAC is significantly resistant to targeted therapy and immunotherapy. The failure of multiple treatment modalities indicates great dilemmas in treating PDAC, including high molecular heterogeneity, high drug resistance, an immunosuppressive microenvironment, and a dense matrix. Nanomedicine shows great potential to overcome the therapeutic barriers of PDAC. Through the careful design and rational modification of nanomaterials, multifunctional intelligent nanosystems can be obtained. These nanosystems can adapt to the environment's needs and compensate for conventional treatments' shortcomings. This review is focused on recent advances in the use of well-designed nanosystems in different therapeutic modalities to overcome the PDAC treatment dilemma, including a variety of novel therapeutic modalities. Finally, these nanosystems' bottlenecks in treating PDAC and the prospect of future clinical translation are briefly discussed.

Quantitative analysis of enhanced CT in differentiating well-differentiated pancreatic neuroendocrine tumors and poorly differentiated neuroendocrine carcinomas.

OBJECTIVE: To identify quantitative CT features for distinguishing well-differentiated pancreatic neuroendocrine tumors (PNETs) from poorly differentiated pancreatic neuroendocrine carcinomas (PNECs). MATERIALS AND METHODS: Seventeen patients with PNECs and 131 patients with PNETs confirmed by biopsy or surgery were retrospectively included. General demographic (sex, age) and CT quantitative parameters (arterial/portal absolute enhancement, arterial/portal relative enhancement ratio, arterial/portal enhancement ratio) were collected. Univariate and multivariate logistic regression analyses were performed to confirm independent variables for differentiating PNECs from PNETs. Receiver operating characteristic (ROC) curves for each quantitative parameter were generated to determine their diagnostic ability. RESULTS: PNECs had a much lower mean arterial/portal absolute enhancement value (19.5 ± 11.0 vs. 78.8 ± 47.2; 28.1 ± 15.8 vs. 77.0 ± 39.4), arterial/portal relative enhancement ratio (0.57 ± 0.36 vs. 2.03 ± 1.31; 0.80 ± 0.52 vs. 1.99 ± 1.13), and arterial/portal enhancement ratio (0.62 ± 0.27 vs. 1.22 ± 0.49; 0.74 ± 0.19 vs. 1.21 ± 0.36) than PNETs (all p < 0.001). After multivariable analysis, arterial absolute enhancement (odds ratio [OR]: 0.96, 95% confidence interval [CI]: 0.93, 0.99) and portal absolute enhancement (OR: 0.96, 95% CI: 0.92, 0.99) were independent factors for differentiating PNECs from PNETs. For each quantitative parameter, arterial lesion enhancement yielded the highest diagnostic performance, with an area under the curve (AUC) of 0.922 (95% CI: 0.867-0.960), followed by portal absolute enhancement. CONCLUSIONS: Arterial/portal absolute enhancements were independent predictors with good diagnostic accuracy for differentiating between PNETs and PNECs. Quantitative parameters of enhanced CT can distinguish PNECs from PNETs. KEY POINTS: • PNECs were hypovascular and had a much lower enhanced CT attenuation in both arterial and portal phases than well-differentiated PNETs. • Quantitative parameters derived from enhanced CT can be used to distinguish PNECs from PNETs. • Arterial absolute enhancement and portal absolute enhancement were independent predictive factors for differentiating between PNETs and PNECs.

Ultra-thin layered double hydroxide-mediated photothermal therapy combine with asynchronous blockade of PD-L1 and NR2F6 inhibit hepatocellular carcinoma.

BACKGROUND: The efficacy of immune checkpoint blockade (ICB), in the treatment of hepatocellular carcinoma (HCC), is limited due to low levels of tumor-infiltrating T lymphocytes and deficient checkpoint blockade in this immunologically "cool" tumor. Thus, combination approaches are needed to increase the response rates of ICB and induce synergistic antitumor immunity. METHODS: Herein, we designed a pH-sensitive multifunctional nanoplatform based on layered double hydroxides (LDHs) loaded with siRNA to block the intracellular immune checkpoint NR2F6, together with the asynchronous blockade surface receptor PD-L1 to induce strong synergistic antitumor immunity. Moreover, photothermal therapy (PTT) generated by LDHs after laser irradiation modified an immunologically "cold" microenvironment to potentiate Nr2f6-siRNA and anti-PD-L1 immunotherapy. Flow cytometry was performed to assess the immune responses initiated by the multifunctional nanoplatform. RESULTS: Under the slightly acidic tumor extracellular environment, PEG detached and the re-exposed positively charged LDHs enhanced tumor accumulation and cell uptake. The accumulated siRNA suppressed the signal of dual protumor activity in both immune and H22 tumor cells by silencing the NR2F6 gene, which further reduced the tumor burden and enhanced systemic antitumor immunity. The responses include enhanced tumor infiltration by CD4+ helper T cells, CD8+ cytotoxic T cells, and mature dendritic cells; the significantly decreased level of immune suppressed regulator T cells. The therapeutic responses were also attributed to the production of IL-2, IFN-γ, and TNF-α. The prepared nanoparticles also exhibited potential magnetic resonance imaging (MRI) ability, which could serve to guide synergistic immunotherapy treatment. CONCLUSIONS: In summary, the three combinations of PTT, NR2F6 gene ablation and anti-PD-L1 can promote a synergistic immune response to inhibit the progression of primary HCC tumors and prevent metastasis. This study can be considered a proof-of-concept for the targeting of surface and intracellular immune checkpoints to supplement the existing HCC immunotherapy treatments.

Extracellular matrix modulating enzyme functionalized biomimetic Au nanoplatform-mediated enhanced tumor penetration and synergistic antitumor therapy for pancreatic cancer.

BACKGROUND: Excessive extracellular matrix (ECM) deposition in pancreatic ductal adenocarcinoma (PDAC) severely limits therapeutic drug penetration into tumors and is associated with poor prognosis. Collagen is the most abundant matrix protein in the tumor ECM, which is the main obstacle that severely hinders the diffusion of chemotherapeutic drugs or nanomedicines. METHODS: We designed a collagenase-functionalized biomimetic drug-loaded Au nanoplatform that combined ECM degradation, active targeting, immune evasion, near-infrared (NIR) light-triggered drug release, and synergistic antitumor therapy and diagnosis into one nanoplatform. PDAC tumor cell membranes were extracted and coated onto doxorubicin (Dox)-loaded Au nanocages, and then collagenase was added to functionalize the cell membrane through lipid insertion. We evaluated the physicochemical properties, in vitro and in vivo targeting, penetration and therapeutic efficacy of the nanoplatform. RESULTS: Upon intravenous injection, this nanoplatform efficiently targeted the tumor through the homologous targeting properties of the coated cell membrane. During penetration into the tumor tissue, the dense ECM in the PDAC tissues was gradually degraded by collagenase, leading to a looser ECM structure and deep penetration within the tumor parenchyma. Under NIR irradiation, both photothermal and photodynamic effects were produced and the encapsulated chemotherapeutic drugs were released effectively, exerting a strong synergistic antitumor effect. Moreover, this nanoplatform has X-ray attenuation properties that could serve to guide and monitor treatment by CT imaging. CONCLUSION: This work presented a unique and facile yet effective strategy to modulate ECM components in PDAC, enhance tumor penetration and tumor-killing effects and provide therapeutic guidance and monitoring.

Self-amplification of oxidative stress with tumour microenvironment-activatable iron-doped nanoplatform for targeting hepatocellular carcinoma synergistic cascade therapy and diagnosis.

BACKGROUND: Hepatocellular carcinoma is insensitive to many chemotherapeutic agents. Ferroptosis is a form of programmed cell death with a Fenton reaction mechanism. It converts endogenous hydrogen peroxide into highly toxic hydroxyl radicals, which inhibit hepatocellular carcinoma progression. METHODS: The morphology, elemental composition, and tumour microenvironment responses of various organic/inorganic nanoplatforms were characterised by different analytical methods. Their in vivo and in vitro tumour-targeting efficacy and imaging capability were analysed by magnetic resonance imaging. Confocal microscopy, flow cytometry, and western blotting were used to investigate the therapeutic efficacy and mechanisms of complementary ferroptosis/apoptosis mediated by the nanoplatforms. RESULTS: The nanoplatform consisted of a silica shell doped with iron and disulphide bonds and an etched core loaded with doxorubicin that generates hydrogen peroxide in situ and enhances ferroptosis. It relied upon transferrin for targeted drug delivery and could be activated by the tumour microenvironment. Glutathione-responsive biodegradability could operate synergistically with the therapeutic interaction between doxorubicin and iron and induce tumour cell death through complementary ferroptosis and apoptosis. The nanoplatform also has a superparamagnetic framework that could serve to guide and monitor treatment under T2-weighted magnetic resonance imaging. CONCLUSION: This rationally designed nanoplatform is expected to integrate cancer diagnosis, treatment, and monitoring and provide a novel clinical antitumour therapeutic strategy.

Development of a Novel Multiparametric MRI Radiomic Nomogram for Preoperative Evaluation of Early Recurrence in Resectable Pancreatic Cancer.

BACKGROUND: In pancreatic cancer, methods to predict early recurrence (ER) and identify patients at increased risk of relapse are urgently required. PURPOSE: To develop a radiomic nomogram based on MR radiomics to stratify patients preoperatively and potentially improve clinical practice. STUDY TYPE: Retrospective. POPULATION: We enrolled 303 patients from two medical centers. Patients with a disease-free survival ≤12 months were assigned as the ER group (n = 130). Patients from the first medical center were divided into a training cohort (n = 123) and an internal validation cohort (n = 54). Patients from the second medical center were used as the external independent validation cohort (n = 126). FIELD STRENGTH/SEQUENCE: 3.0T axial T1 -weighted (T1 -w), T2 -weighted (T2 -w), contrast-enhanced T1 -weighted (CET1 -w). ASSESSMENT: ER was confirmed via imaging studies as MRI or CT. Risk factors, including clinical stage, CA19-9, and radiomic-related features of ER were assessed. In addition, to determine the intra- and interobserver reproducibility of radiomic features extraction, the intra- and interclass correlation coefficients (ICC) were calculated. STATISTICAL TESTS: The area under the receiver-operator characteristic (ROC) curve (AUC) was used to evaluate the predictive accuracy of the radiomic signature in both the training and test groups. The results of decision curve analysis (DCA) indicated that the radiomic nomogram achieved the most net benefit. RESULTS: The AUC values of ER evaluation for the radiomics signature were 0.80 (training cohort), 0.81 (internal validation cohort), and 0.78 (external validation cohort). Multivariate logistic analysis identified the radiomic signature, CA19-9 level, and clinical stage as independent parameters of ER. A radiomic nomogram was then developed incorporating the CA19-9 level and clinical stage. The AUC values for ER risk evaluation using the radiomic nomogram were 0.87 (training cohort), 0.88 (internal validation cohort), and 0.85 (external validation cohort). DATA CONCLUSION: The radiomic nomogram can effectively evaluate ER risks in patients with resectable pancreatic cancer preoperatively, which could potentially improve treatment strategies and facilitate personalized therapy in pancreatic cancer. LEVEL OF EVIDENCE: 4 Technical Efficacy: Stage 4 J. Magn. Reson. Imaging 2020;52:231-245.

Grade 3 Pancreatic Neuroendocrine Tumors on MDCT: Establishing a Diagnostic Model and Comparing Survival Against Pancreatic Ductal Adenocarcinoma.

OBJECTIVE. The purpose of this study is to establish a diagnostic model for differentiating grade 3 (G3) pancreatic neuroendocrine tumors (PNETs) from pancreatic ductal adenocarcinomas (PDACs) and to analyze survival outcomes. MATERIALS AND METHODS. Twenty patients with G3 PNETs and 58 patients with PDACs confirmed by surgery or biopsy were retrospectively included. Demographic and radiologic information was collected. Univariate analyses and binary logistic regression analyses were performed to identify independent factors and establish a diagnostic model. An ROC curve was created to determine diagnostic ability. Kaplan-Meier survival analysis was performed. RESULTS. Patients with G3 PNETs were more likely to present with normal carbohydrate antigen (CA) 19-9 levels, normal pancreatic ducts, and round tumors with well-defined margins and higher portal enhancement ratios than were patients with PDAC (p < 0.05). After multivariate analysis, a normal CA 19-9 level (odds ratio, 0.0125; 95% CI, 0.0008-0.2036), round tumor shape (odds ratio, 0.0143; 95% CI, 0.0004-0.5461), and pancreatic duct dilation of 4 mm or less (odds ratio, 17.9804; 95% CI, 1.0098-320.1711) were independent predictors of G3 PNETs. The AUC of the ROC curve was 0.916, and sensitivity and specificity were 90.0% and 81.0%, respectively. Furthermore, patients with G3 PNETs had better overall survival than patients with PDACs. Among patients in the G3 PNET subgroup, patients with liver or lymph node metastases had worse overall survival than patients without metastases. CONCLUSION. A diagnostic model was established to differentiate G3 PNETs from PDACs. A normal CA 19-9 level, round tumor shape, and pancreatic duct dilation of 4 mm or less were factors that were strongly predictive of G3 PNET.

A prognostic nomogram in patients with distant metastasis of pancreatic neuroendocrine tumors: a population-based study.

Aim: Prognostic factors in patients with distant metastatic pancreatic neuroendocrine tumors (PNETs) remain uncertain. The purpose of our study is to establish a nomogram to predict survival outcomes in patients with metastatic PNETs. Methods: A total of 878 patients diagnosed with PNETs in the Surveillance, Epidemiology and End Results database between 2004 and 2016 were retrospectively identified. The Kaplan-Meier survival analysis with log-rank test was used to analyze survival outcomes. The nomogram was established after a univariate and multivariate Cox analysis. Results: The independent prognostic variables, including age, tumor grade and primary site surgery were applied to develop a nomogram. The original concordance index was 0.773 (95% CI: 0.751-0.795), and the bias-corrected concordance index was 0.769 (95% CI: 0.748-0.791). The internal calibration curves showed well consistency and veracity in predicting cancer-specific survival probabilities. Conclusion: A nomogram was constructed and verified to predict survival outcomes in patients with distant-stage PNETs.

Polysialic-Acid-Based Micelles Promote Neural Regeneration in Spinal Cord Injury Therapy.

Spinal cord injury (SCI) routinely causes the immediate loss and disruption of neurons followed by complicated secondary injuries, including inflammation, oxidative stress, and dense glial scar formation. Inhibitory factors in the lesion scar and poor intrinsic neural regeneration capacity restrict functional recovery after injury. Minocycline, which has neuroprotective activity, can alleviate secondary injury, but the long-term administration of this drug may cause toxicity. Polysialic acid (PSA) is a large cell-surface carbohydrate that is critical for central nervous system development and is capable of promoting precursor cell migration, axon path finding, and synaptic remodeling; thus, PSA plays a vital role in tissue repair and regeneration. Here, we developed a PSA-based minocycline-loaded nanodrug delivery system (PSM) for the synergistic therapy of spinal cord injury. The prepared PSM exerted marked anti-inflammatory and neuroprotective activities both in vitro and in vivo. The administration of PSM could significantly protect neurons and myelin sheaths from damage, reduce the formation of glial scar, recruit endogenous neural stem cells to the lesion site, and promote the regeneration of neurons and the extension of long axons throughout the glial scar, thereby largely improving the locomotor function of SCI rats and exerting a superior therapeutic effect. The findings might provide a novel strategy for SCI synergistic therapy and the utilization of PSA in other central nervous system diseases.

Visual targeted therapy of hepatic cancer using homing peptide modified calcium phosphate nanoparticles loading doxorubicin guided by T1 weighted MRI.

Effective treatment and real-time monitoring of hepatic cancer are essential. A multifunctional calcium phosphate nanoparticles loading chemotherapeutic agent doxorubicin and magnetic resonance imaging contrast agent diethylenetriaminepentaacetic acid gadolinium (A54-CaP/Gd-DTPA/DOX) was developed for visual targeted therapy of hepatic cancer via T1-weighted MRI in real-time. A54-CaP/Gd-DTPA/DOX exhibited a higher longitudinal relaxivity (6.02 mM-1 s-1) than commercial MR contrast agent Gd-DTPA (3.3765 mM-1 s-1). The DOX release from the nanoparticles exhibited a pH dependent behavior. The cellular uptake results showed that the internalization of A54-CaP/Gd-DTPA/DOX into BEL-7402 cells was1.9-fold faster than that of HepG2 cells via A54 binding. In vivo experiments presented that A54-CaP/Gd-DTPA/DOX had higher distribution and longer retention time in tumor tissue than CaP/Gd-DTPA/DOX and free DOX, and also displayed great antitumor efficacy (95.38% tumor inhibition rate) and lower toxicity. Furthermore, the Gd-DTPA entrapped in the nanoparticles could provide T1-weighted MRI for real-time monitoring the progress of tumor treatment.

A preoperative nomogram predicts prognosis of up front resectable patients with pancreatic head cancer and suspected venous invasion.

BACKGROUND: Pancreatic head adenocarcinoma is commonly diagnosed at an advanced stage when adjacent vascular invasion is present. This study aimed to establish a preoperative prognostic nomogram for patients who underwent attempted curative resectional surgery for pancreatic head cancer with suspected peripancreatic venous invasion. METHODS: Data on all consecutive patients were retrospectively collected from 2012 to 2016 at four academic institutions. The demographic and radiological parameters were analyzed using univariate and multivariate Cox regression analyses. The final nomogram was established using the concordance Harrell's C-indices and calibration curves from data obtained in three institutions and validated in the cohort of patients coming from the fourth institution. RESULTS: The nomogram was constructed using data from 178 patients while the validation cohort consisted of 61 patients. Age, length of tumor contact, peripancreatic venous abnormalities and lymph node staging were independent factors of overall survival. The nomogram showed good probabilities of survival on calibration curves. The C-index of the model in predicting overall survival (OS) was 0.824 for the validation cohort. CONCLUSIONS: The nomogram accurately predicted OS in patients with pancreatic head cancer with suspected peripancreatic venous invasion after attempted curative pancreatic resectional surgery.

Overactivation of corticotropin-releasing factor receptor type 1 and aquaporin-4 by hypoxia induces cerebral edema.

Cerebral edema is a potentially life-threatening illness, but knowledge of its underlying mechanisms is limited. Here we report that hypobaric hypoxia induces rat cerebral edema and neuronal apoptosis and increases the expression of corticotrophin releasing factor (CRF), CRF receptor type 1 (CRFR1), aquaporin-4 (AQP4), and endothelin-1 (ET-1) in the cortex. These effects, except for the increased expression of CRF itself, could all be blocked by pretreatment with an antagonist of the CRF receptor CRFR1. We also show that, in cultured primary astrocytes: (i) both CRFR1 and AQP4 are expressed; (ii) exogenous CRF, acting through CRFR1, triggers signaling of cAMP/PKA, intracellular Ca(2+), and PKCε; and (iii) the up-regulated cAMP/PKA signaling contributes to the phosphorylation and expression of AQP4 to enhance water influx into astrocytes and produces an up-regulation of ET-1 expression. Finally, using CHO cells transfected with CRFR1(+) and AQP4(+), we show that transfected CRFR1(+) contributes to edema via transfected AQP4(+). In conclusion, hypoxia triggers cortical release of CRF, which acts on CRFR1 to trigger signaling of cAMP/PKA in cortical astrocytes, leading to activation of AQP4 and cerebral edema.

To identify important MRI features to differentiate hepatic mucinous cystic neoplasms from septated hepatic cysts based on random forest.

OBJECTIVE: To identify important MRI features to differentiate hepatic mucinous cystic neoplasms (MCN) from septated hepatic cysts (HC) using random forest and compared with logistic regression algorithm. METHODS: Pathologically diagnosed hepatic cysts and hepatic MCNs with pre-operative contrast-enhanced MRI in our hospital from 2010 to 2023 were collected and only septated lesions on enhanced MRI were enrolled. A total of 21 septated HC and 18 MCNs were included in this study. Eighteen MRI features were analyzed and top important features were identified based on random forest (RF) algorithm. The results were evaluated by the prediction performance of a RF model combining the important features and compared with the performance of the logistic regression (LR) algorithm. Finally, for each identified feature, diagnostic probability, sensitivity, and specificity were calculated and compared. RESULTS: Four variables, i.e., the septation arising from wall without indentation, multiseptate, intracapsular cyst sign, and solitary lesion were extracted as top important features with significance for MCNs by the random forest algorithm. The RF model using these variables had an AUC of 0.982 (0.95CI, 0.950-1.000), compared with the LR model based on two identified features with AUC of 0.931 (0.95CI, 0.846-1.000), p = 0.202. Among the four important features, multiseptate had the highest specificity (95.2%) and good sensitivity (72.2%, lower than the septation from wall without indentation, 94.4%) to diagnose MCNs. CONCLUSION: Four out of 18 MRI features were extracted as reliably important factors to differ hepatic MCNs from septated HC. The combination of these four features in a RF model could achieve satisfactory diagnostic efficacy.

Clinical and CT Quantitative Features for Predicting Liver Metastases in Patients with Pancreatic Neuroendocrine Tumors: A Study with Prospective/External Validation.

RATIONALE AND OBJECTIVES: We aimed to evaluate clinical characteristics and quantitative CT imaging features for the prediction of liver metastases (LMs) in patients with pancreatic neuroendocrine tumors (PNETs). METHODS: Patients diagnosed with pathologically confirmed PNETs were included, 133 patients were in the training group, 22 patients in the prospective internal validation group, and 28 patients in the external validation group. Clinical information and quantitative features were collected. The independent variables for predicting LMs were confirmed through the implementation of univariate and multivariate logistic analyses. The diagnostic performance was evaluated by conducting receiver operating characteristic curves for predicting LMs in the training and validation groups. RESULTS: PNETs with LMs demonstrated significantly larger diameter and lower arterial/portal tumor-parenchymal enhancement ratio, arterial/portal absolute enhancement value (AAE/PAE value) (p < 0.05). After multivariate analyses, A high level of tumor marker (odds ratio (OR): 5.32; 95% CI, 1.54-18.35), maximum diameter larger than 24.6 mm (OR: 7.46; 95% CI, 1.70-32.72), and AAE value ≤ 51 HU (OR: 4.99; 95% CI, 0.93-26.95) were independent positive predictors of LMs in patients with PNETs, with area under curve (AUC) of 0.852 (95%CI, 0.781-0.907). The AUCs for prospective internal and external validation groups were 0.883 (95% CI, 0.686-0.977) and 0.789 (95% CI, 0.602-0.916), respectively. CONCLUSION: Tumor marker, maximum diameter and absolute enhancement value in arterial phase were independent predictors with good predictive performance for the prediction of LMs in patients with PNETs. Combining clinical and quantitative features may facilitate the attainment of good predictive precision in predicting LMs.

Galactosylated chitosan oligosaccharide nanoparticles for hepatocellular carcinoma cell-targeted delivery of adenosine triphosphate.

Nanoparticles composed of galactosylated chitosan oligosaccharide (Gal-CSO) and adenosine triphosphate (ATP) were prepared for hepatocellular carcinoma cell-specific uptake, and the characteristics of Gal-CSO/ATP nanoparticles were evaluated. CSO/ATP nanoparticles were prepared as a control. The average diameter and zeta potential of Gal-CSO/ATP nanoparticles were 51.03 ± 3.26 nm and 30.50 ± 1.25 mV, respectively, suggesting suitable properties for a drug delivery system. Subsequently, the cytotoxicity of Gal-CSO/ATP nanoparticles were examined by the methyl tetrazolium (MTT) assay, and the half maximal inhibitory concentration (IC50) values were calculated with HepG2 (human hepatocellular carcinoma cell line) cells. The results showed that the cytotoxic effect of nanoparticles on HepG2 cells was low. In the meantime, it was also found that the Gal-CSO/ATP nanoparticles could be uptaken by HepG2 cells, due to expression of the asialoglycoprotein receptor (ASGP-R) on their surfaces. The presented results indicate that the Gal-CSO nanoparticles might be very attractive to be used as an intracellular drug delivery carrier for hepatocellular carcinoma cell targeting, thus warranting further in vivo or clinical investigations.

[Breast cancer subtypes based on ER/PR and Her2 expression: comparison of MR imaging features].

OBJECTIVE: To evaluate the magnetic resonance (MR) imaging findings of breast cancer subtypes based on the profiles of ER/PR and Her2. METHODS: A retrospective study was conducted for 267 breast cancer subjects between February 2007 and January 2011. Clinicopathologic features and MR imaging findings of four subtypes were compared. The Chi-square (χ(2)) test, Fisher's exact test and χ(2) section method were employed for categorical variables. RESULTS: MR imaging findings:Patients with segment or linear enhancement type accounted for 25.6% in ER/PR(+), Her2(+) subtype group and 36.1% in ER/PR(-), Her2(+) subtype, no significant difference existed between them (χ(2) = 1.112, P = 0.641). But they were significantly higher than ER/PR(+), Her2(-) subtype group and ER/PR(-), Her2(-) subtype group (χ(2) = 32.793, P < 0.001; χ(2) = 14.565, P < 0.001). ER/PR(-), Her2(-) subtype patients accounted for 14.6% of the total breast cancer patients (39/267). Subjects with ER/PR(-), Her2(-) subtype were more likely to present unifocal (91.7%, 33/36) and mass type lesion (92.3%, 36/39). The mass type lesions in ER/PR(-), Her2(-) subtype group were more likely to showed smooth margin [58.3% (21/36), P < 0.001], very high intratumoral signal and peripheral hyperintense pattern on fat suppression T2-weighted imaging (P < 0.001) and early rim enhancement [81.5% (29/36), P < 0.001]. No significantly difference of four subtypes were found on number of mass, mass shape and pattern at dynamic enhancement imaging (χ(2) = 1.413, P = 0.713; χ(2) = 8.423, P = 0.204; χ(2) = 4.657, P = 0.540). CONCLUSION: Segment or linear enhancement type is characterized by MR imaging. Early rim enhanced mass is ER/PR(-), Her2(-) breast cancer. The most important characteristics of MR imaging include a smooth edge of breast mass, very high intratumoral signal on fat suppression T2-weighted imaging and peripheral hyperintense pattern.

Compare image quality of T2-weighted imaging with different phase acceleration factors.

Previous studies demonstrated that adjusting the phase acceleration (PA) factors could influence image quality. To improve image quality and decrease respiratory artifacts of lesions in the liver on T2-weighted image by adjusting PA factor and number of excitation (NEX). Sixty consecutive patients with hepatic lesions were enrolled in this prospective research between May 2020 and June 2020. All patients had 3.0T magnetic resonance imaging with 4 sequences (combining PA factors and NEXs, the former was 2 and 3, the latter were 1.5 and 2, respectively, with the same other scanning parameters). Two readers used 5-point quality scales to assess image quality. The signal intensity was measured by drawing regions of interest in the liver, spleen, and background on the T2-weighted imaging. Artifacts, overall image impression, and vascular conspicuity were better when the PA factor was 3 than 2. Artifacts and vascular conspicuity were better when NEX was 2 than 1.5. PA factor 3 and NEX 2 got a higher score in 5-point quality scales and less scan time than the other 3 sequences. Meanwhile, the signal-to-noise ratio of PA factor 3 and NEX 2 was best among these 4 sequences. PA factor and NEX could influence the imaging quality and lesion-to-hepatic contrast in detecting hepatic lesions on T2-weighted images. PA factor 3 and NEX 2 may have a positive effect in the clinic, especially for those with irregular respiration, as it decreased artifacts and reduced scan time.

KRAS mutation status between left- and right-sided colorectal cancer: are there any differences in computed tomography?

PURPOSE: To investigate the differences in clinicopathological and imaging features according to KRAS mutation status in left- and right-sided colorectal cancer. METHOD: A total of 157 patients with pathologically proven colorectal cancer and preoperative contrast-enhanced multidetector CT examinations were enrolled. According to the tumor location and KRAS status, they were divided into two groups: the left-sided colorectal cancer (LCC) group (wild type, mutant type) and the right-sided colorectal cancer (RCC) group (wild type, mutant type). Clinicopathological and imaging features were recorded in each group. The imaging observation indicators included short axis diameter (SAD), longitudinal tumor length (LTL), tumor shape, pericolic fat stranding, bowel stenosis, intratumoral low-density range, enhancement pattern, and bowel obstruction. Univariate and multivariate logistic regression analyses were performed to compare the difference in KRAS mutation status between groups. RESULTS: In the LCC group, SAD, tumor shape, degree of pericolic fat stranding, and bowel obstruction were significant indicators for predicting KRAS status (P < 0.05). In the RCC group, CA19-9, SAD, and intratumoral low-density range were significant indicators for predicting KRAS status (P < 0.05.). The area under the curve (AUC) of the combination image indicators in the LCC group was 0.802 [cutoff point 0.372, 95% confidence interval (CI) 0.718-0.888, sensitivity 85.4%, specificity 72.0%]. The AUC in the RCC group was 0.828 (cutoff point 0.647, 95% CI 0.726-0.931, sensitivity 79.5%, specificity 75.0%). CONCLUSION: The CT imaging features associated with KRAS mutation status in the LCC and RCC groups were different. The combination of tumor location and imaging features can help to further improve the predictive value of KRAS status.