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.

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.

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.

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.

Duodenal neuroendocrine neoplasms on enhanced CT: establishing a diagnostic model with duodenal gastrointestinal stromal tumors in the non-ampullary area and analyzing the value of predicting prognosis.

OBJECTIVE: To identify CT features and establish a diagnostic model for distinguishing non-ampullary duodenal neuroendocrine neoplasms (dNENs) from non-ampullary duodenal gastrointestinal stromal tumors (dGISTs) and to analyze overall survival outcomes of all dNENs patients. MATERIALS AND METHODS: This retrospective study included 98 patients with pathologically confirmed dNENs (n = 44) and dGISTs (n = 54). Clinical data and CT characteristics were collected. Univariate analyses and binary logistic regression analyses were performed to identify independent factors and establish a diagnostic model between non-ampullary dNENs (n = 22) and dGISTs (n = 54). The ROC curve was created to determine diagnostic ability. Cox proportional hazards models were created and Kaplan-Meier survival analyses were performed for survival analysis of dNENs (n = 44). RESULTS: Three CT features were identified as independent predictors of non-ampullary dNENs, including intraluminal growth pattern (OR 0.450; 95% CI 0.206-0.983), absence of intratumoral vessels (OR 0.207; 95% CI 0.053-0.807) and unenhanced lesion > 40.76 HU (OR 5.720; 95% CI 1.575-20.774). The AUC was 0.866 (95% CI 0.765-0.968), with a sensitivity of 90.91% (95% CI 70.8-98.9%), specificity of 77.78% (95% CI 64.4-88.0%), and total accuracy rate of 81.58%. Lymph node metastases (HR: 21.60), obstructive biliary and/or pancreatic duct dilation (HR: 5.82) and portal lesion enhancement ≤ 99.79 HU (HR: 3.02) were independent prognostic factors related to poor outcomes. CONCLUSION: We established a diagnostic model to differentiate non-ampullary dNENs from dGISTs. Besides, we found that imaging features on enhanced CT can predict OS of patients with dNENs.

A radiologic diagnostic scoring model based on CT features for differentiating gastric schwannoma from gastric gastrointestinal stromal tumors.

We aimed to further explore the CT features of gastric schwannoma (GS), propose and validate a convenient diagnostic scoring system to distinguish GS from gastric gastrointestinal stromal tumors (GISTs) preoperatively. 170 patients with submucosal tumors pathologically confirmed (GS n=35; gastric GISTs n=135) from Hospital 1 were analyzed retrospectively as the training cohort, and 72 patients (GS=11; gastric GISTs=61) from Hospital 2 were enrolled as the validation cohort. We searched for significant CT imaging characteristics and constructed the scoring system via binary logistic regression and converted regression coefficients to weighted scores. The ROC curves, AUCs and calibration tests were carried out to evaluate the scoring models in both the training cohort and the validation cohort. For convenient assessment, the system was further divided into four score ranges and their diagnostic probability of GS was calculated respectively. Four CT imaging characteristics were ultimately enrolled in this scoring system, including transverse position (2 points), location (5 points), perilesional lymph nodes (6 points) and pattern of enhancement (2 points). The AUC of the scoring model in the training cohort were 0.873 (95% CI, 0.816-0.929) and the cutoff point was 6 points. In the validation cohort, the AUC was 0.898 (95% CI, 0.804-0.957) and the cutoff value was 5 points. Four score ranges were as follows: 0-3 points for very low probability of GS, 4-7 points for low probability; 8-9 points for middle probability; 10-15 points for very high probability. A convenient scoring model to preoperatively discriminate GS from gastric GISTs was finally proposed.

A scoring model for radiologic diagnosis of gastric leiomyomas (GLMs) with contrast-enhanced computed tomography (CE-CT): Differential diagnosis from gastrointestinal stromal tumors (GISTs).

OBJECTIVES: To investigate CT findings and develop a diagnostic score model to differentiate GLMs from GISTs. METHODS: This retrospective study included 109 patients with pathologically confirmed GLMs (n = 46) and GISTs (n = 63) from January 2013 to August 2018 who received CE-CT before surgery. Demographic and radiological features was collected, including lesion location, contour, presence or absence of intralesional necrosis and ulceration, growth pattern, whether the tumor involved EGJ, the long diameter (LD) /the short diameter (SD) ratio, pattern and degree of lesion enhancement. Univariate analyses and multivariate logistic regression analyses were performed to identify independent predictors and establish a predictive model. Independent predictors for GLMs were weighted with scores based on regression coefficients. A receiver operating characteristic (ROC) curve was created to determine the diagnostic ability of the model. Overall score distribution was divided into four groups to show differentiating probability of GLMs from GISTs. RESULTS: Five CT features were the independent predictors for GLMs diagnosis in multivariate logistic regression analysis, including esophagogastric junction (EGJ) involvement (OR, 367.9; 95 % CI, 5.8-23302.8; P =  0.005), absence of necrosis (OR, 11.9; 95 % CI, 1.0-138. 1; P =  0.048) and ulceration (OR, 151.9; 95 % CI, 1.4-16899.6; P =  0.037), degree of enhancement (OR, 9.3; 95 % CI, 3.2-27.4; P <  0.001), and long diameter/ short diameter (LD/SD) ratio (OR,170.9; 95 % CI, 8.4-3493.4; P =  0.001). At a cutoff of 9 points, AUC for this score model was 0.95, with 95.65 % sensitivity, 79.37 % specificity, 77.19 % PPV, 96.15 % NPV and 86.24 % diagnostic accuracy. An increasing trend was showed in diagnostic probability of GLMs among four groups based on the score (P <  0.001). CONCLUSIONS: The newly designed scoring system is reliable and easy-to-use for GLMs diagnosis by distinguishing from GISTs, including EGJ involvement, absence of ulceration and necrosis, mild enhancement and high LD/SD ratio. The overall score of model ranged from 1 to 17 points, which was divided into 4 groups: 1-7 points, 7-10 points, 10-13 points and 13-17 points, with a diagnostic probability of GLMs 0%, 45 %, 83 % and 100 %, respectively.

Radiographic Features and Clinical Factor for Preoperative Prediction in the Bulging Duodenal Papilla With Malignancy.

BACKGROUND: To investigate characteristic clinical and imaging features and establish a scoring system for preoperative prediction of malignancy in the bulging duodenal papilla. METHODS: A total of 147 patients with bulging duodenal papilla (Benign enlargement n = 67; malignant enlargement n = 80) from our hospital between 2010 and 2020 were retrospectively analyzed. We investigated meaningful clinical and CT imaging features and established the score model through logistic regression and weighted. The calibration test, the ROC, AUC, and cut-off points were performed in score model. The model was also divided into three score ranges for convenient clinical evaluation. RESULTS: Three clinical and CT imaging features were finally included in the score model including direct bilirubin (DBil) increase >7 umol/L (3 points), pancreatic duct (PD) dilation >5 mm (2 points), and irregular shape (2 points). The AUCs of the primary predictive model and score model were 0.896 (95% CI, 0.835-0.940) and 0.896 (95% CI, 0.835-0.940), respectively. This scoring system presented with a sensitivity of 78.8% and a specificity of 88.1% when using 2.5 points as cutoff value. Three score ranges were also proposed for convenient clinical use as follows: 0-2 points; 3-4 points; 5-7 points. The number of patients with malignant duodenal papillary enlargement increased with the increasing scores. CONCLUSIONS: We proposed a convenient scoring system to preoperative predict malignancy in the bulging duodenal papilla.

A Non-Invasive Scoring System to Differential Diagnosis of Clear Cell Renal Cell Carcinoma (ccRCC) From Renal Angiomyolipoma Without Visible Fat (RAML-wvf) Based on CT Features.

BACKGROUND: Renal angiomyolipoma without visible fat (RAML-wvf) and clear cell renal cell carcinoma (ccRCC) have many overlapping features on imaging, which poses a challenge to radiologists. This study aimed to create a scoring system to distinguish ccRCC from RAML-wvf using computed tomography imaging. METHODS: A total of 202 patients from 2011 to 2019 that were confirmed by pathology with ccRCC (n=123) or RAML (n=79) were retrospectively analyzed by dividing them randomly into a training cohort (n=142) and a validation cohort (n=60). A model was established using logistic regression and weighted to be a scoring system. ROC, AUC, cut-off point, and calibration analyses were performed. The scoring system was divided into three ranges for convenience in clinical evaluations, and the diagnostic probability of ccRCC was calculated. RESULTS: Four independent risk factors are included in the system: 1) presence of a pseudocapsule, 2) a heterogeneous tumor parenchyma in pre-enhancement scanning, 3) a non-high CT attenuation in pre-enhancement scanning, and 4) a heterogeneous enhancement in CMP. The prediction accuracy had an ROC of 0.978 (95% CI, 0.956-0.999; P=0.011), similar to the primary model (ROC, 0.977; 95% CI, 0.954-1.000; P=0.012). A sensitivity of 91.4% and a specificity of 93.9% were achieved using 4.5 points as the cutoff value. Validation showed a good result (ROC, 0.922; 95% CI, 0.854-0.991, P=0.035). The number of patients with ccRCC in the three ranges (0 to <2 points; 2-4 points; >4 to ≤11 points) significantly increased with increasing scores. CONCLUSION: This scoring system is convenient for distinguishing between ccRCC and RAML-wvf using four computed tomography features.

The prognostic value of multidetector CT features in predicting overall survival outcomes in patients with pancreatic neuroendocrine tumors.

PURPOSE: To assess the prognostic value of multidetector CT in predicting overall survival outcomes in patients with pancreatic neuroendocrine tumors (PNETs). METHOD: Seventy-one patients pathologically diagnosed with PNETs were retrospectively included. The clinical and imaging information was evaluated by two radiologists. The difference between well-differentiated and poorly differentiated PNETs was analyzed. Cox proportional hazards models were created to determine the risk factors for overall survival. Kaplan-Meier survival analyses with log-rank tests were used among different subgroups of patients with PNETs. RESULTS: In the whole cohort, the median survival was 36 months, and the 5-year survival rate was 84.8 %. Patients with poorly differentiated PNETs were more likely to present with symptoms, abnormal tumor markers, larger diameters, irregular shapes, ill-defined margins, invasion into nearby tissues, liver and lymph node metastases, and lower enhancement ratio than those with well-differentiated PNETs (P < 0.05). In the multivariate analysis, lymph node metastases (hazard ratio: 21.52, P = 0.009) and a portal enhancement ratio less than 1.02 (hazard ratio: 30.89, P = 0.024) were significant factors for overall survival. Overall survival decreased with an ill-defined margin, irregular shape, poor differentiation, grade 3 disease, nonfunctional status, abnormal tumor marker levels, invasion into nearby tissues, lymph node and liver metastases, and lower enhancement ratio (log-rank P < 0.05). CONCLUSIONS: Poorly differentiated PNETs were more aggressiveness than well-differentiated PNETs. Lymph node metastases and a portal enhancement ratio < 1.02 were independent prognostic factors for worse overall survival outcomes in patients with PNETs.

Reduced field-of-view diffusion-weighted imaging (DWI) in patients with gastric cancer: Comparison with conventional DWI techniques at 3.0T: A preliminary study.

To evaluate the qualitative image quality and quantitative apparent diffusion coefficient (ADC) value of reduced field-of view (rFOV) and full field-of-view (fFOV) diffusion-weighted imaging (DWI) sequences at 3.0 T in patients with gastric cancer.Fifty-three patients (37 males, 16 females; mean age, 63.3 ±â€Š10.3 years) with 60 lesions with gastric cancer who underwent magnetic resonance (MR) scans, including both rFOV-DWI and fFOV-DWI, were retrospectively analyzed. Two observers subjectively evaluated image quality for both the fFOV-DWI and rFOV-DWI sequences regarding the anatomic details, distortion, lesion conspicuity, artifacts, and overall image quality. The mean ADC values of gastric cancer were calculated. The Wilcoxon test and paired samples t test were used. Interobserver agreement was assessed using kappa statistics.The mean scores based on the 2 observers demonstrated significant differences in image quality in terms of anatomic details, distortion, lesion conspicuity, artifacts and overall image quality at both b values between rFOV-DWI and fFOV-DWI (P < .05) in the whole gastric area. rFOV-DWI yielded significantly better scores in image quality at b = 800 seconds/mm (P < .05) in patients with esophagogastric junction cancers, but there were no significant differences in the gastric corpus and gastric antrum region. The mean tumor ADC values of rFOV-DWI were significantly lower than those of fFOV-DWI (1.237 ±â€Š0.228 × 10-3 mm/second vs 1.683 ±â€Š0.322 × 10-3 mm/second, P < .001).rFOV-DWI yielded significantly better image quality (anatomic details, distortion, lesion conspicuity, artifacts, overall image quality) and more accurate ADC measurements than fFOV-DWI did.

Contrast-enhanced CT imaging for the assessment of lymph node status in patients with colorectal cancer.

The aim of the present study was to identify a novel strategy that predicts the metastatic status of lymph nodes (LNs) in patients diagnosed with colorectal cancer, using detailed characteristics of contrast-enhanced CT scan images. A total of 284 preoperative CT scans derived from patients diagnosed with colorectal cancer at Second Affiliated Hospital, Zhejiang University School of Medicine between January 2013 and July 2018 were retrospectively reviewed. A total of 794 LNs were assessed for size, margins, morphology and subtle internal enhancements in the equilibrium phase. Imaging features were analyzed by two abdominal radiologists (Department of Radiology, Second Affiliated Hospital, Zhejiang University School of Medicine and Departments of Radiology; Shaoxing Second Hospital Departments of Radiology, Shaoxing Second Hospital) in a blind manner. If the conclusions were not concordant, the final score was determined by a senior radiologist who specialized in abdominal radiology for ≥30 years. According to the histopathology results, 27.3% (217/794) of LNs were metastatic (LN+). In addition, LNs >10 mm in size demonstrated sensitivity, specificity, positive predictive values (PPVs) and negative predictive values (NPVs) of 47.0, 80.9, 48.1 and 80.2%, respectively [odds ratio (OR), 3.77; 95% confidence interval (CI), 2.69-5.28]. LNs in the shape of a kidney bean (middle fat depression like kidney) and/or those with an oblong shape were more likely to be metastasis negative LNs (LN-), while lobulated and irregular LNs were more likely to be LN+. In magnified images, internal enhancement characteristics of LN- were defined as homogeneous, spotted, striped and core enhancing. By contrast, rim and heterogeneity enhancement features for LN+ demonstrated sensitivity, specificity, PPVs and NPVs of 46.5, 89.9, 63.5 and 81.7%, respectively (OR, 7.79; 95% CI, 5.33-11.40). The results demonstrated that the internal enhancement features of LNs may be used as a predictor of metastasis. The detailed benign characteristics, such as homogeneity, spotted, striped and core enhancement of LNs may facilitate the identification of LN- in patients with colorectal cancer.

Optimizing prostate cancer accumulating model: combined PI-RADS v2 with prostate specific antigen and its derivative data.

BACKGROUND: To establish a new accumulating model to enhance the accuracy of prostate cancer (PCa) diagnosis by incorporating prostate-specific antigen (PSA) and its derivative data into the Prostate Imaging-Reporting and Data System version 2 (PI-RADS v2). METHODS: A total of 357 patients who underwent prostate biopsy between January 2014 and December 2017 were included in this study. All patients had 3.0 T multiparametric magnetic resonance imaging (MRI) and complete laboratory examinations. PI-RADS v2 was used to assess the imaging. PSA, PSA density (PSAD), the free/total PSA ratio (f/t PSA) and the Gleason score (GS) were classified into four-tiered levels, and optimal weights were pursued on these managed levels to build a PCa accumulating model. A receiver operating characteristic curve was generated. RESULTS: In all, 174 patients (48.7%) had benign prostatic hyperplasia, and 183 (51.3%) had PCa, among whom 149 (81.4%, 149/183) had clinically significant PCa. The established model 6 (PI-RADS v2 + level of PSAD + level of f/t PSA+ level of PSA) had a sensitivity and specificity of 81.4 and 84.5%, respectively, at the cut-off point of 11 in PCa diagnosis. Correspondingly, at the 12 cut-off point, the sensitivity and specificity were 87.7 and 83.0%, respectively, in diagnosing clinically significant PCa. The score of the new accumulating system was significantly different among the defined GS groups (p < 0.001). The mean values and 95% confidence intervals for GS 1-4 groups were 10.20 (9.63-10.40), 12.03 (11.19-12.87), 14.12 (13.60-14.64) and 15.44 (15.09-15.79). CONCLUSIONS: A new PCa accumulating model may be useful in improving the accuracy of the primary diagnosis of PCa and helpful in the clinical decision to perform a biopsy when MRI results are negative.

Relationship between urate within tophus and bone erosion according to the anatomic location of urate deposition in gout: A quantitative analysis using dual-energy CT volume measurements.

The aim of this study was to measure the urate volume within tophus and bone erosion volume using dual-energy computed tomography in patients with tophaceous gout. Furthermore, our study aims to quantitatively analyze the relationship between monosodium urate (MSU) crystal deposition and bone erosion according to the anatomic location of urate deposition.Seventy-seven subjects with chronic gout were positively identified for the presence of urate deposition. Only 27 subjects identified for the presence of urate in contact with bone erosion were included in this study. The urate volumes and associated erosion volumes were measured. The relationships between urate within tophus and bone erosion were separately analyzed according to the anatomic location of urate deposition.Twenty-seven subjects were all male (100%) with a median (interquartile range, IQR) age of 52 (45-61) years. From all the subjects, 103 tophi depositions were identified in contact with bone erosion, including 58/103 tophi that contained an intraosseous component and 45/103 nonintraosseous tophi. Tophi containing intraosseous components were larger than nonintraosseous tophi (urate volume: median [IQR] 45.64 [4.79-250.89] mm vs 19.32 [6.97-46.71] mm, P = .035) and caused greater bone erosion (erosion volume: 249.03 [147.08-845.33] mm vs 69.07 [32.88-111.24] mm, P < .001). Almost all erosion volumes were larger than urate volumes in nonperiarticular tophi, in contrast to most erosion volumes, which were less than urate volumes in the tophi that contained a periarticular component (odds ratio, 95% confidence interval: 74.00, 14.70-372.60; P < .001). Urate volume and erosion volume demonstrated positive correlations in intraosseous tophi, intraosseous-intra-articular-periarticular tophi, and intraosseous-intra-articular tophi (rs = 0.761, rs = 0.695, rs = 0.629, respectively, P < .05).MSU crystal deposition shows a promoting effect on the development of bone erosions in varying degrees, associated with the location of MSU crystals deposited in the joints. The intraosseous tophi contribute the most to bone erosions, followed by intra-articular tophi, and periarticular tophi.

110 Patients with adenosquamous carcinomas of the pancreas (PASC): imaging differentiation of small (≤ 3 cm) versus large (> 3 cm) tumors.

OBJECTIVE: This study examined radiological imaging features of small (≤ 3 cm) and large (> 3 cm) adenosquamous carcinomas of the pancreas (PASC) lesions to better understand the morphology of these lesions. METHODS: Images from 110 patients with pathologically proven PASC (80 males and 30 females, mean age: 62.6 years) were retrospectively reviewed. Two radiologists analyzed images and reached a consensus regarding the following features: location, shape, margins, presence of solid and necrotic components, rim enhancement, density/intensity during the portal venous phase, invasion of surrounding organs, vascular invasion, venous tumor thrombus formation, and enlarged lymph nodes. Differences in the imaging features between the two groups were evaluated with the Chi-square test or Fisher's exact test. RESULTS: There were 41 small PASC lesions (mean age: 60.59 years) and 69 large PASC lesions (63.74 years). Statistical analysis demonstrated significant differences in the location, shape, adjacent organ and vessel invasion, and venous tumor thrombus formation (P < 0.05). Small PASC lesions were more frequently detected in the pancreatic head and had an ovoid shape. There was no significant difference in the presence of solid and necrotic components (P = 0.090), including approximately 3/4 of the lesions with necrosis and 1/4 purely solid lesions, enlarged lymph nodes (P = 0.068) and other features. CONCLUSION: Regardless of the tumor size, 75% of PASC lesions present with central necrosis while 25% are purely solid. Small PASC lesions can be associated with lymph node metastasis at a relatively early stage. Large PASC lesions are likely to invade adjacent tissues and be associated with venous tumor thrombus formation.

Improving the detection rate of prostate cancer in the gray zone of PI-RADS v2 and serum tPSA by using prostate-specific antigen-age volume.

To improve the detection of prostate cancer (PCa) by combining the Prostate Imaging Reporting and Data System version 2 (PI-RADS v2) and prostate-specific antigen-age volume (PSA-AV), especially among those in gray zone with PI-RADS v2 score 3 or serum total prostate-specific antigen (tPSA) 4 to 10 ng/mL.The 357 patients were enrolled in this study. The PI-RADS v2 scoring system was used to represent characteristics on multiparametric magnetic resonance imaging (mpMRI). PI-RADS v2 score 3 or tPSA 4 to 10 ng/mL were defined as the gray zone in detecting PCa. The formula equates to the patient age multiplied by the prostate volume, which is divided by the tPSA level. Univariate and multivariate analyses were done to ascertain significant predictors of prostate cancer.In all, 174 (48.7%) were benign prostatic hyperplasia, 183 (51.3%) had PCa. The results showed that PI-RADS v2, tPSA, and PSA-AV were significant independent predictors of prostate cancer. PI-RADS v2 score ≥4 could detect PCa with rate of 82.1%. Serum tPSA ≥10 ng/mL could detect PCa with rate of 66.2%, PSA density (PSAD) ≥0.15 ng/mL/cc with rate of 62.8%, and PSA-AV ≤250 with rate of 83.5%. Combining with PSA-AV ≤250, patients those with tPSA 4 to 10 ng/mL could improve the detection from 36.0% up to 81%, those with PI-RADS v2 score 3 from 28.6% up to 60.0%.PI-RADS v2 and PSA-AV are faithful variables for detecting PCa. And for patients, those in gray zones of PI-RADS v2 and tPSA, PSA-AV can improve detection rate of PCa.

The "extracapsular cystic" sign in pancreatic serous cystic neoplasms: A clinicopathologic study of 177 patients with cystic pancreatic lesions.

OBJECTIVE: To assess a new imaging feature that we have named the extracapsular cystic sign which can make a constructive contribution towards differentiating serous cystic neoplasms (SCNs) from other pancreatic cystic lesions. MATERIAL AND METHODS: We retrospectively reviewed 177 CTs/MRIs of patients who underwent pancreatic resection of cystic lesions at two institutions from January 2011/2013, to September 2017. For each patient, demographic information, clinical presentation, especially imaging features were carefully investigated by two experienced abdominal radiologists, retrospectively. All statistical analyses were performed using SPSS V.23.0. RESULTS: Twenty-one lesions had extracapsular cystic signs which were newly discovered, 17 (28.3%) of 60 SCNs and 4 (3.4%) (mucinous cystic neoplasm = 1, walled-off necrosis = 2, retention cyst = 1) of 117 Non-SCNs were included, from which indicating that the extracapsular cystic sign was more often detected on SCNs. As for 21 lesions, 86% (n = 18) were females, and mean age at diagnosis was 51.2 years. 71% (n = 15) located in the pancreatic body and tail. Average size was 27.2 mm (23.7-53.4), mean (SD) ratio of biggest daughter cyst to mother cyst was 0.51[0.14] (p = 0.99), average (SD) angle between two of them was 105.5° [14.9] (p = 0.84). The average time interval between last imaging examination and surgery was 8.4 days. CONCLUSIONS: The new sign named the extracapsular cystic sign in SCNs may help differentiate SCNs from other pancreatic cystic lesions. Furthermore, this study supports an original diagnosis for SCNs when the sign of extracapsular cyst appears.