A clinical and computed tomography-based nomogram to predict the outcome in patients with anterior circulation large vessel occlusion after endovascular mechanical thrombectomy.

PURPOSE: To explore the positive predictors of the clinical outcome in acute ischemic stroke (AIS) patients with anterior circulation large vessel occlusion (ACLVO) after endovascular mechanical thrombectomy (EMT) at a 90-day follow-up, and to establish a nomogram model to predict the clinical outcome. MATERIALS AND METHODS: AIS patients with ACLVO detected by multimodal Computed Tomography imaging who underwent EMT were collected. Patients were divided into the favorable and the unfavorable groups according to the 90-day modified Rankin Scale (mRS) score. Univariate and multivariate analyses were performed to investigate predictors of the favorable outcome (mRS of 0-2). A nomogram model for predicting the clinical outcome after EMT was drawn, and the receiver operating characteristic (ROC) curve was used to evaluate its predictive value. RESULTS: Totally 105 patients including 65 patients in the favorable group and 40 in the unfavorable group were enrolled. Multivariate logistic regression analysis showed that admission National Institute of Health Stroke scale (NIHSS) score [0.858 (95% CI 0.778-0.947)], ACLVO at M2 [20.023 (95% CI 2.204-181.907)] and infarct core (IC) volume [0.943 (95% CI 0.917-0.969)] was positively correlated with favorable outcome. The accuracy of the nomogram model in predicting the outcome was 0.923 (95% CI 0.870-0.976), with a cutoff value of 119.6 points. The area under the ROC curve was 0.848 (95% CI 0.780-0.917; sensitivity, 79.7%; specificity, 90.0%). CONCLUSION: A low Admission NIHSS score, ACLVO at M2, and a small IC volume were positive predictors for favorable outcome. The nomogram model may well predict the outcome in AIS patients with ACLVO after EMT.

Gradient inflammation in the pancreatic stump after pancreaticoduodenectomy: Two case reports and review of literature.

BACKGROUND: Postoperative pancreatic fistula (POPF) contributes significantly to morbidity and mortality after pancreaticoduodenectomy (PD). However, the underlying mechanisms remain unclear. This study explored this pathology in the pancreatic stumps and elucidated the mechanisms of POPF following PD. CASE SUMMARY: Pathological analysis and 16S rRNA gene sequencing were performed on specimens obtained from two patients who underwent complete pancreatectomy for grade C POPF after PD. Gradient inflammation is present in the pancreatic stump. The apoptosis was lower than that in the normal pancreas. Moreover, neutrophil-dominated inflammatory cells are concentrated in the ductal system. Notably, neutrophils migrated through the ductal wall in acinar duct metaplasia-formed ducts. Additionally, evidence indicates that gut microbes migrate from the digestive tract. Gradient inflammation occurs in pancreatic stumps after PD. CONCLUSION: The mechanisms underlying POPF include high biochemical activity in the pancreas, mechanical injury, and digestive reflux. To prevent POPF and address pancreatic inflammation and reflux, breaking the link with anastomotic dehiscence is practical.

Tracheal computed tomography radiomics model for prediction of the Omicron variant of severe acute respiratory syndrome coronavirus 2.

OBJECTIVES: The Omicron variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is highly contagious, fast-spreading, and insidious. Most patients present with normal findings on lung computed tomography (CT). The current study aimed to develop and validate a tracheal CT radiomics model to predict Omicron variant infection. MATERIALS AND METHODS: In this retrospective study, a radiomics model was developed based on a training set consisting of 157 patients with an Omicron variant infection and 239 healthy controls between 1 January and 30 April 2022. A set of morphological expansions, with dilations of 1, 3, 5, 7, and 9 voxels, was applied to the trachea, and radiomic features were extracted from different dilation voxels of the trachea. Logistic regression (LR), support vector machines (SVM), and random forests (RF) were developed and evaluated; the models were validated on 67 patients with the Omicron variant and on 103 healthy controls between 1 May and 30 July 2022. RESULTS: Logistic regression with 12 radiomic features extracted from the tracheal wall with dilation of 5 voxels achieved the highest classification performance compared with the other models. The LR model achieved an area under the curve of 0.993 (95% confidence interval [CI]: 0.987-0.998) in the training set and 0.989 (95% CI: 0.979-0.999) in the validation set. Sensitivity, specificity, and accuracy of the model for the training set were 0.994, 0.946, and 0.965, respectively, whereas those for the validation set were 0.970, 0.952, and 0.959, respectively. CONCLUSION: The tracheal CT radiomics model reliably identified the Omicron variant of SARS-CoV­2, and may help in clinical decision-making in future, especially in cases of normal lung CT findings.

CT target scanning in the diagnosis of solid pseudopapillary tumor of the pancreas.

OBJECTIVE: To discuss the value of computed tomography (CT) iterative reconstruction technique combined with target scanning in the diagnosis of solid pseudopapillary tumor of the pancreas (SPTP). METHODS: The clinical information and CT examination data of 27 patients with SPTP were retrospectively analyzed, and the general condition and CT performance of the patients were observed. The CT image reconstruction algorithm of all patients used iterative reconstruction technique combined with the application of target scanning technique. RESULTS: A total of 27 patients were included in this study, including 6 males and 21 females, aged 14-72 years with a mean age of 39.6 ± 13.6 years. SPTP was more common in young and middle-aged females, with a low level of tumor markers, dominated by cystic-solid tumors. The combination of CT iterative reconstruction technology and targeted scanning revealed the following: the capsule of SPTP was clear and complete, where calcifications were visible, solid components were progressively enhanced, and rare pancreatic and bile duct dilation was seen. Tumors were cystic-solid in 18 of 27 patients with SPTP, of which the solid components showed isodensity or slightly low-density, with calcifications. The solid components and cyst walls were mildly enhanced during the arterial phase, and were progressively enhanced during the parenchymal phase, portal vein phase, and delayed phase, with their enhancement degree lower than that of normal pancreatic parenchyma, and pancreatic and bile duct dilation was rare. There were no statistical differences in tumor location, morphology, growth pattern, integrity of capsule, cystic or solid, calcifications, and enhancement features between the male group and the female group (P > 0.05). CONCLUSION: The iterative reconstruction combined with target scanning clearly displayed the CT features of tumors, helping the diagnosis and clinical treatment of the disease.

Colorectal cancer cell membrane biomimetic ferroferric oxide nanomaterials for homologous bio-imaging and chemotherapy application.

The research of nanomaterials for bio-imaging and theranostic are very active nowadays with unprecedented advantages in nanomedicine. Homologous targeting and bio-imaging greatly improve the ability of targeted drug delivery and enhance active targeting and treatment ability of nanomedicine for the tumor. In this work, lycorine hydrochloride (LH) and magnetic iron oxide nanoparticles coated with a colorectal cancer (CRC) cell membrane (LH-Fe3O4@M) were prepared, for homologous targeting, magnetic resonance imaging (MRI), and chemotherapy. Results showed that the LH-Fe3O4@M and Fe3O4@M intensity at HT29 tumor was significantly higher than that Fe3O4@PEG, proving the superior selectivity of cancer cell membrane-camouflaged nanomedicine for homologous tumors and the MRI effect of darkening contrast enhancement were remarkable at HT29 tumor. The LH-Fe3O4@M exhibited excellent chemotherapy effect in CRC models as well as LH alone and achieved a high tumor ablation rate but no damage to normal tissues and cells. Therefore, our biomimetic system achieved a homologous targeting, bio-imaging, and efficient therapeutic effect of CRC.

Endoscopic and Surgical Management of Non-Metastatic Ampullary Neuroendocrine Neoplasia: A Multi-Institutional Pancreas2000/EPC Study.

INTRODUCTION: Ampullary neuroendocrine neoplasia (NEN) is rare and evidence regarding their management is scarce. This study aimed to describe clinicopathological features, management, and prognosis of ampullary NEN according to their endoscopic or surgical management. METHODS: From a multi-institutional international database, patients treated with either endoscopic papillectomy (EP), transduodenal surgical ampullectomy (TSA), or pancreaticoduodenectomy (PD) for ampullary NEN were included. Clinical features, post-procedure complications, and recurrences were assessed. RESULTS: 65 patients were included, 20 (30.8%) treated with EP, 19 (29.2%) with TSA, and 26 (40%) with PD. Patients were mostly asymptomatic (n = 46; 70.8%). Median tumor size was 17 mm (12-22), tumors were mostly grade 1 (70.8%) and pT2 (55.4%). Two (10%) EP resulted in severe American Society for Gastrointestinal Enterology (ASGE) adverse post-procedure complications and 10 (50%) were R0. Clavien 3-5 complications did not occur after TSA and in 4, including 1 postoperative death (15.4%) of patients after PD, with 17 (89.5%) and 26 R0 resection (100%), respectively. The pN1/2 rate was 51.9% (n = 14) after PD. Tumor size larger than 1 cm (i.e., pT stage >1) was a predictor for R1 resection (p < 0.001). Three-year overall survival and disease-free survival after EP, TSA, and PD were 92%, 68%, 92% and 92%, 85%, 73%, respectively. CONCLUSION: Management of ampullary NEN is challenging. EP should not be performed in lesions larger than 1 cm or with a endoscopic ultrasonography T stage beyond T1. Local resection by TSA seems safe and feasible for lesions without nodal involvement. PD should be preferred for larger ampullary NEN at risk of nodal metastasis.

Rates and Patterns of Recurrence After Microwave Ablation of Colorectal Liver Metastases: A Per Lesion Analysis of 416 Tumors in the Era of 2.45 GHz Generators.

BACKGROUND: For some patients with colorectal liver metastases (CRLMs), surgical resection of all visible disease can lead to long-term survival and even cure. When complete resection is not feasible, microwave ablation (MWA) can help achieve hepatic disease control. As modern 2.45-GHz MWA generators gain popularity, the characteristics of tumors most likely to benefit from this method remain unclear. This study aimed to evaluate local recurrence (LR) rates, patterns of recurrence, and factors contributing to treatment failure after 2.45-GHz MWA of CRLM. METHODS: Patients with CRLM who underwent operative 2.45-GHz MWA between 2011 and 2019 were identified in a prospectively maintained single-institution database. Recurrence outcomes were ascertained for each lesion by imaging review. Factors associated with LR were analyzed. RESULTS: The study enrolled 184 patients bearing 416 ablated tumors. Most of the patients (65.8%) had high clinical risk scores (3-5), and 165 (90%) underwent concurrent liver resection. The median tumor size was 10 mm. After a median follow-up period of 28.8 months, LR was observed in 45 tumors, and the cumulative incidence of LR at 24 months was 10.9% (95% confidence interval [CI], 8.0-14.3%]. In 7%, LR was the first recurrence site, often combined with recurrence elsewhere. The cumulative incidence of LR at 24 months was 6.8% (95% CI 3.8-11.0%) for tumors 10 mm in size or smaller, 12.4% (95% CI 7.8-18.1%) for tumors 11 to 20 mm in size, and 30.2% (95% CI 14.2-48.0%) for tumors larger than 20 mm. In the multivariable analysis, tumors larger than 20 mm with a subcapsular location were significantly associated with increased LR risk. CONCLUSIONS: Treatment of CRLM with 2.45-GHz MWA offers excellent local control at 2 years and is most successful for small tumors deep within the parenchyma.

Replacing secretin-enhanced MRCP with MRI radiomics model based on a fully automated pancreas segmentation for assessing pancreatic exocrine function in chronic pancreatitis.

OBJECTIVES: To develop and validate a radiomics nomogram based on a fully automated pancreas segmentation to assess pancreatic exocrine function. Furthermore, we aimed to compare the performance of the radiomics nomogram with the pancreatic flow output rate (PFR) and conclude on the replacement of secretin-enhanced magnetic resonance cholangiopancreatography (S-MRCP) by the radiomics nomogram for pancreatic exocrine function assessment. METHODS: All participants underwent S-MRCP between April 2011 and December 2014 in this retrospective study. PFR was quantified using S-MRCP. Participants were divided into normal and pancreatic exocrine insufficiency (PEI) groups using the cut-off of 200 µg/L of fecal elastase-1. Two prediction models were developed including the clinical and non-enhanced T1-weighted imaging radiomics model. A multivariate logistic regression analysis was conducted to develop the prediction models. The models' performances were determined based on their discrimination, calibration, and clinical utility. RESULTS: A total of 159 participants (mean age [Formula: see text] standard deviation, 45 years [Formula: see text] 14;119 men) included 85 normal and 74 PEI. All the participants were divided into a training set comprising 119 consecutive patients and an independent validation set comprising 40 consecutive patients. The radiomics score was an independent risk factor for PEI (odds ratio = 11.69; p < 0.001). In the validation set, the radiomics nomogram exhibited the highest performance (AUC, 0.92) in PEI prediction, whereas the clinical nomogram and PFR had AUCs of 0.79 and 0.78, respectively. CONCLUSION: The radiomics nomogram accurately predicted pancreatic exocrine function and outperformed pancreatic flow output rate on S-MRCP in patients with chronic pancreatitis. KEY POINTS: • The clinical nomogram exhibited moderate performance in diagnosing pancreatic exocrine insufficiency. • The radiomics score was an independent risk factor for pancreatic exocrine insufficiency, and every point rise in the rad-score was associated with an 11.69-fold increase in pancreatic exocrine insufficiency risk. • The radiomics nomogram accurately predicted pancreatic exocrine function and outperformed the clinical model and pancreatic flow output rate quantified by secretin-enhanced magnetic resonance cholangiopancreatography on MRI in patients with chronic pancreatitis.

Fully automated magnetic resonance imaging-based radiomics analysis for differentiating pancreatic adenosquamous carcinoma from pancreatic ductal adenocarcinoma.

PURPOSE: To develop and validate an automated magnetic resonance imaging (MRI)-based model to preoperatively differentiate pancreatic adenosquamous carcinoma (PASC) from pancreatic ductal adenocarcinoma (PDAC). METHODS: This retrospective study included patients with surgically resected, histopathologically confirmed PASC or PDAC who underwent MRI between January 2011 and December 2020. According to time of treatment, they were divided into training and validation sets. Automated deep-learning-based artificial intelligence was used for pancreatic tumor segmentation. Linear discriminant analysis was performed with conventional MRI and radiomic features to develop clinical, radiomics, and mixed models in the training set. The models' performances were determined from their discrimination and clinical utility. Kaplan-Meier and log-rank tests were used for survival analysis. RESULTS: Overall, 389 and 123 patients with PDAC (age, 61.37 ± 9.47 years; 251 men) and PASC (age, 61.99 ± 9.82 years; 78 men) were included, respectively; they were split into the training (n = 358) and validation (n = 154) sets. The mixed model showed good performance in the training and validation sets (area under the curve: 0.94 and 0.96, respectively). The sensitivity, specificity, and accuracy were 76.74%, 93.38%, and 89.39% for the training set, respectively, and 67.57%, 97.44%, and 90.26% for the validation set, respectively. The mixed model outperformed the clinical (p = 0.001) and radiomics (p = 0.04) models in the validation set. Log-rank test revealed significantly longer survival in the predicted PDAC group than in the predicted PASC group (p = 0.003), according to the mixed model. CONCLUSION: Our mixed model, which combined MRI and radiomic features, can be used to differentiate PASC from PDAC.

Non-enhanced magnetic resonance imaging-based radiomics model for the differentiation of pancreatic adenosquamous carcinoma from pancreatic ductal adenocarcinoma.

Purpose: To evaluate the diagnostic performance of radiomics model based on fully automatic segmentation of pancreatic tumors from non-enhanced magnetic resonance imaging (MRI) for differentiating pancreatic adenosquamous carcinoma (PASC) from pancreatic ductal adenocarcinoma (PDAC). Materials and methods: In this retrospective study, patients with surgically resected histopathologically confirmed PASC and PDAC who underwent MRI scans between January 2011 and December 2020 were included in the study. Multivariable logistic regression analysis was conducted to develop a clinical and radiomics model based on non-enhanced T1-weighted and T2-weighted images. The model performances were determined based on their discrimination and clinical utility. Kaplan-Meier and log-rank tests were used for survival analysis. Results: A total of 510 consecutive patients including 387 patients (age: 61 ± 9 years; range: 28-86 years; 250 males) with PDAC and 123 patients (age: 62 ± 10 years; range: 36-84 years; 78 males) with PASC were included in the study. All patients were split into training (n=382) and validation (n=128) sets according to time. The radiomics model showed good discrimination in the validation (AUC, 0.87) set and outperformed the MRI model (validation set AUC, 0.80) and the ring-enhancement (validation set AUC, 0.74). Conclusions: The radiomics model based on non-enhanced MRI outperformed the MRI model and ring-enhancement to differentiate PASC from PDAC; it can, thus, provide important information for decision-making towards precise management and treatment of PASC.

Identification of the prognostic, diagnostic, and biological significance of the miR-148a-3p/cathepsin A axis in hepatocellular carcinoma.

A comprehensive analysis of the prognostic, diagnostic, and biological significance of miR-148a-3p and cathepsin A (CTSA) in hepatocellular carcinoma (HCC) was performed using bioinformatics algorithms with The Cancer Genome Atlas (TCGA) data. miR-148a-3p and CTSA gene expression in HCC tissues and nontumor specimens was analyzed using TCGA database with R software. CTSA staining analysis was validated using the Human Protein Atlas database. Prognostic, diagnostic, gene set enrichment, Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and immune infiltration analyses were implemented using the TCGA database with R software. Based on TCGA data and our cohort populations, CTSA expression was significantly elevated in HCC tissues compared with nontumor specimens. A significant negative correlation between miR-148a-3p and CTSA was observed in the TCGA data and our cohort population. Mechanistically, CTSA was a direct gene target of miR-148a-3p. Both CTSA and miR-148a-3p could serve as prognostic and diagnostic indicators in HCC. miR-148a-3p expression was significantly and negatively correlated with the StromalScore, ImmuneScore, and ESTIMATEScore in patients with liver cancer. miR-148a-3p mimic-mediated apoptosis and the inhibition of HCC cell growth and migration were counteracted by CTSA overexpression. The miR-148a-3p/CTSA axis was implicated in immune cell infiltration and carcinogenesis of HCC. miR-148a-3p and CTSA might be prospective molecular targets to enhance the potency of immunotherapy in HCC.

Recurrence After Resection of Pancreatic Cancer: Can Radiomics Predict Patients at Greatest Risk of Liver Metastasis?

BACKGROUND: Liver metastasis (LM) after pancreatic ductal adenocarcinoma (PDAC) resection is common but difficult to predict and has grave prognosis. We combined preoperative clinicopathological variables and quantitative analysis of computed tomography (CT) imaging to predict early LM. METHODS: We retrospectively evaluated patients with PDAC submitted to resection between 2005 and 2014 and identified clinicopathological variables associated with early LM. We performed liver radiomic analysis on preoperative contrast-enhanced CT scans and developed a logistic regression classifier to predict early LM (< 6 months). RESULTS: In 688 resected PDAC patients, there were 516 recurrences (75%). The cumulative incidence of LM at 5 years was 41%, and patients who developed LM first (n = 194) had the lowest 1-year overall survival (OS) (34%), compared with 322 patients who developed extrahepatic recurrence first (61%). Independent predictors of time to LM included poor tumor differentiation (hazard ratio (HR) = 2.30; P < 0.001), large tumor size (HR = 1.17 per 2-cm increase; P = 0.048), lymphovascular invasion (HR = 1.50; P = 0.015), and liver Fibrosis-4 score (HR = 0.89 per 1-unit increase; P = 0.029) on multivariate analysis. A model using radiomic variables that reflect hepatic parenchymal heterogeneity identified patients at risk for early LM with an area under the receiver operating characteristic curve (AUC) of 0.71; the performance of the model was improved by incorporating preoperative clinicopathological variables (tumor size and differentiation status; AUC = 0.74, negative predictive value (NPV) = 0.86). CONCLUSIONS: We confirm the adverse survival impact of early LM after resection of PDAC. We further show that a model using radiomic data from preoperative imaging combined with tumor-related variables has great potential for identifying patients at high risk for LM and may help guide treatment selection.

Distribution of FFRCT in single obstructive coronary stenosis and predictors for major adverse cardiac events: a propensity score matching study.

BACKGROUND: Fractional flow reserve derived from computed tomography (FFRCT) has been demonstrated to improve identification of lesion-specific ischemia significantly compared with coronary computed tomography angiography (CCTA). It remains unclear whether the distribution of FFRCT values in obstructive stenosis between patients who received percutaneous coronary intervention (PCI) or not in routine clinical practice, as well as its association with clinical outcome. This study aims to reveal the distribution of FFRCT value in patients with single obstructive coronary artery stenosis and explored the independent factors for predicting major adverse cardiac events (MACE). METHODS: This was a retrospective study of adults with non-ST-segment elevation acute coronary syndrome undergoing FFRCT assessment by using CCTA data from January 1, 2016 to December 31, 2020. Propensity score matching (PSM) method was used to account for patient selection bias. The risk factors for predicting MACE were evaluated by a Cox proportional hazards regression analysis. RESULTS: Overall, 655 patients with single obstructive (≥ 50%) stenosis shown on CCTA were enrolled and divided into PCI group (279 cases) and conservative group (376 cases) according to treatment strategy. The PSM cohort analysis demonstrated that the difference in history of unstable angina, Canadian Cardiovascular Society Class (CCSC) and FFRCT between PCI group (188 cases) and conservative group (315 cases) was statistically significant, with all P values < 0.05, while the median follow-up time between them was not statistically significant (24 months vs. 22.5 months, P = 0.912). The incidence of MACE in PCI group and conservative group were 14.9% (28/188) and 23.5% (74/315) respectively, P = 0.020. Multivariate analysis of Cox proportional hazards regression revealed that history of unstable angina (adjusted odds ratio (adjOR), 3.165; 95% confidence interval (CI), 2.087-4.800; P < 0.001), FFRCT ≤ 0.8 (OR, 1.632;95% CI 1.095-2.431; P = 0.016), and PCI therapy (OR 0.481; 95% CI 0.305-0.758) were the independent factors for MACE. CONCLUSIONS: History of unstable angina and FFRCT value of ≤ 0.8 were the independent risk factors for MACE, while PCI therapy was the independent protective factor for MACE.

Machine learning radiomics can predict early liver recurrence after resection of intrahepatic cholangiocarcinoma.

BACKGROUND: Most patients recur after resection of intrahepatic cholangiocarcinoma (IHC). We studied whether machine-learning incorporating radiomics and tumor size could predict intrahepatic recurrence within 1-year. METHODS: This was a retrospective analysis of patients with IHC resected between 2000 and 2017 who had evaluable computed tomography imaging. Texture features (TFs) were extracted from the liver, tumor, and future liver remnant (FLR). Random forest classification using training (70.3%) and validation cohorts (29.7%) was used to design a predictive model. RESULTS: 138 patients were included for analysis. Patients with early recurrence had a larger tumor size (7.25 cm [IQR 5.2-8.9] vs. 5.3 cm [IQR 4.0-7.2], P = 0.011) and a higher rate of lymph node metastasis (28.6% vs. 11.6%, P = 0.041), but were not more likely to have multifocal disease (21.4% vs. 17.4%, P = 0.643). Three TFs from the tumor, FD1, FD30, and IH4 and one from the FLR, ACM15, were identified by feature selection. Incorporation of TFs and tumor size achieved the highest AUC of 0.84 (95% CI 0.73-0.95) in predicting recurrence in the validation cohort. CONCLUSION: This study demonstrates that radiomics and machine-learning can reliably predict patients at risk for early intrahepatic recurrence with good discrimination accuracy.

Differentiating prostate cancer from benign prostatic hyperplasia using whole-lesion histogram and texture analysis of diffusion- and T2-weighted imaging.

BACKGROUND: To explore the usefulness of analyzing histograms and textures of apparent diffusion coefficient (ADC) maps and T2-weighted (T2W) images to differentiate prostatic cancer (PCa) from benign prostatic hyperplasia (BPH) using histopathology as the reference. METHODS: Ninety patients with PCa and 112 patients with BPH were included in this retrospective study. Differences in whole-lesion histograms and texture parameters of ADC maps and T2W images between PCa and BPH patients were evaluated using the independent samples t-test. The diagnostic performance of ADC maps and T2W images in being able to differentiate PCa from BPH was assessed using receiver operating characteristic (ROC) curves. RESULTS : The mean, median, 5th, and 95th percentiles of ADC values in images from PCa patients were significantly lower than those from BPH patients (p < 0.05). Significant differences were observed in the means, standard deviations, medians, kurtosis, skewness, and 5th percentile values of T2W image between PCa and BPH patients (p < 0.05). The ADC5th showed the largest AUC (0.906) with a sensitivity of 83.3 % and specificity of 89.3 %. The diagnostic performance of the T2W image histogram and texture analysis was moderate and had the largest AUC of 0.634 for T2WKurtosis with a sensitivity and specificity of 48.9% and 79.5 %, respectively. The diagnostic performance of the combined ADC5th & T2WKurtosis parameters was also similar to that of the ADC5th & ADCDiff-Variance. CONCLUSIONS: Histogram and texture parameters derived from the ADC maps and T2W images for entire prostatic lesions could be used as imaging biomarkers to differentiate PCa and BPH biologic characteristics, however, histogram parameters outperformed texture parameters in the diagnostic performance.

Differentiating T1a-T1b from T2 in gastric cancer lesions with three different measurement approaches based on contrast-enhanced T1W imaging at 3.0 T.

BACKGROUND: To explore the diagnostic value of three different measurement approaches in differentiating T1a-T1b from T2 gastric cancer (GC) lesions. METHODS: A total of 95 consecutive patients with T1a-T2 stage of GC who performed preoperative MRI were retrospectively enrolled between January 2017 and November 2020. The parameters MRI T stage (subjective evaluation), thickness, maximum area and volume of the lesions were evaluated by two radiologists. Specific indicators including AUC, optimal cutoff, sensitivity, specificity, accuracy, positive likelihood ratio (PLR), negative likelihood ratio (NLR), positive predictive value (PPV) and negative predictive value (NPV) of MRI T stage, thickness, maximum area and volume for differentiating T1a-T1b from T2 stage lesions were calculated. The ROC curves were compared by the Delong test. Decision curve analysis (DCA) was used to evaluate the clinical benefit. RESULTS: The ROC curves for thickness (AUC = 0.926), maximum area (AUC = 0.902) and volume (AUC = 0.897) were all significantly better than those of the MRI T stage (AUC = 0.807) in differentiating T1a-T1b from T2 lesions, with p values of 0.004, 0.034 and 0.041, respectively. The values corresponding to the thickness (including AUC, sensitivity, specificity, accuracy, PPV, NPV, PLR and NLR) were all higher than those corresponding to the MRI T stage, maximum area and volume. The DCA curves indicated that the parameter thickness could provide the highest clinical benefit if the threshold probability was above 35%. CONCLUSIONS: Thickness may provide an efficient approach to rapidly distinguish T1a-T1b from T2 stage GC lesions.

Single-Stage Pulmonary Resection via a Combination of Single Hookwire Localization and Video-Assisted Thoracoscopic Surgery for Synchronous Multiple Pulmonary Nodules.

Purpose: To retrospectively analyze the incidence and predictors of complications related to hookwire localization in patients with single and multiple nodules, and to evaluate the usefulness of a single-stage surgical method of single hookwire localization combined with video-assisted thoracoscopic surgery (VATS) in synchronous multiple pulmonary nodules (SMPNs). Methods: A total of 200 patients who underwent computed tomography (CT)-guided hookwire localization and subsequent VATS resection were enrolled in this study. For each patient, only 1 indeterminate nodule was implanted with a hookwire. There were 145 patients in the single-nodule group (Group S) and 55 in the multiple-nodule group (Group M). Univariate and binary logistic regression analyses were used to assess incidence and predictors of complications associated with hookwire localization. Results: The technical success rate of hookwire implantation was 97.5%. The incidence of pneumothorax and hookwire dislodgement was 17.0% and 2.5%, respectively. Binary logistic regression analysis showed that 1 transpleural puncture through the pleura (odds ratio [OR] = 0.433, P = .033) was the only independent protective factor for pneumothorax, and pneumothorax (OR = 26.114, P < .01) was the only independent risk factor for dislodgement. The volume of blood loss during VATS was significantly higher in group M than in group S, and the time of postoperative hospitalization was significantly longer in group M than in group S. About 44 patients in group M with additional 58 nodules without localization had undergone direct surgical resection simultaneously, and bilateral surgery was performed in 13 patients (29.5%). The intrathoracic recurrence rate was 4.8% during follow-up CT. Conclusion: Single-stage surgery via an approach of single hookwire localization combined with VATS is feasible and safe for SMPNs.