A Pilot First-in-Human Study of Embrace,a Polyethylene Glycol-Based Liquid Embolic Agent,in the Embolization of Malignant and Benign Hypervascular Tumors

PurposeTo investigate the safety and efficacy of an aqueous polyethylene glycol-based liquid embolic agent, Embrace Hydrogel Embolic System (HES), in the treatment of benign and malignant hypervascular tumors.Materials and MethodsA prospective, single-arm, multicenter study included 8 patients, 5 males and 3 females, with a median age of 58.5 years (30–85 years), who underwent embolization in 8 tumors between October 2019 and May 2020. Technical success was defined as successful delivery of HES to the index vessel, with disappearance of >90% of the targeted vascular enhancement or, for portal vein embolization, occlusion of the portal branches to the liver segments for future resection. The volume of HES administered, ease of use (5 point Likert scale), administration time, and adverse events (AEs) were recorded. Evaluation was performed at 7, 30, and 90 days via clinical assessment and blood testing, and follow-up imaging was performed at 30 days.ResultsEight patients were enrolled, and 10 embolizations were performed in 8 lesions. Tumors included hepatocellular carcinoma (n = 4), renal angiomyolipoma (n = 3), and intrahepatic cholangiocarcinoma (n = 1). Technical success was 100%, and the average ease of use was 3.3 ± 1.0 SD. The HES delivery time was 1–28 minutes (median, 16.5 minutes), and the HES volume injected was 0.4–4.0 mL (median, 1.3 mL). All patients reached 30-day follow-up with imaging, and 6 patients reached 90-day follow-up. There were 3 serious AEs in 2 patients that were unrelated to the embolic agent.ConclusionHES resulted in a 100% embolization technical success rate. The product ease of use was acceptable, and no target vessel recanalization was noted on follow-up imaging at 30 days.     

食管癌高、低发区食管鳞癌患者生存及其影响因素分析

目的 探讨食管癌高、低发区食管鳞癌患者的生存状况及其影响因素。方法 收集38 741例经病理学证实为食管鳞癌患者的资料，其中，高发区患者23 273例（60.1%），低发区15 468例（39.9%）。所有患者均行食管癌根治术。运用卡方检验分析不同临床病理特征患者的组间差异，Kaplan-Meier法绘制不同临床病理特征患者的生存曲线并用Log rank进行检验。多因素Cox比例风险回归模型法分析影响生存的主要因素。结果 低发区男性患者所占比例高于高发区（P<0.001），低发区诊断年龄≥50岁食管癌患者所占比例高于高发区（P<0.001）。高发区食管鳞癌患者的整体生存优于低发区患者（P<0.001）。Cox比例风险回归模型综合分析结果表明：高低发区、性别、确诊年龄、肿瘤部位、分化程度、TNM分期和肿瘤家族史均是影响食管鳞癌患者生存的独立因素。结论 高发区食管鳞癌患者整体生存优于低发区；低发区是食管鳞癌患者预后差的独立危险因素。     

Radiomics model based on preoperative gadoxetic acid-enhanced MRI for predicting liver failure

BACKGROUND Postoperative liver failure is the most severe complication in cirrhotic patients with hepatocellular carcinoma(HCC) after major hepatectomy. Current available clinical indexes predicting postoperative residual liver function are not sufficiently accurate.AIM To determine a radiomics model based on preoperative gadoxetic acid-enhanced magnetic resonance imaging for predicting liver failure in cirrhotic patients with HCC after major hepatectomy.METHODS For this retrospective study, a radiomics-based model was developed based on preoperative hepatobiliary phase gadoxetic acid-enhanced magnetic resonance images in 101 patients with HCC between June 2012 and June 2018. Sixty-one radiomic features were extracted from hepatobiliary phase images and selected by the least absolute shrinkage and selection operator method to construct a radiomics signature. A clinical prediction model, and radiomics-based model incorporating significant clinical indexes and radiomics signature were built using multivariable logistic regression analysis. The integrated radiomics-based model was presented as a radiomics nomogram. The performances of clinical prediction model, radiomics signature, and radiomics-based model for predicting post-operative liver failure were determined using receiver operating characteristics curve, calibration curve, and decision curve analyses.RESULTS Five radiomics features from hepatobiliary phase images were selected to construct the radiomics signature. The clinical prediction model, radiomics signature, and radiomics-based model incorporating indocyanine green clearance rate at 15 min and radiomics signature showed favorable performance for predicting postoperative liver failure(area under the curve: 0.809-0.894). The radiomics-based model achieved the highest performance for predicting liver failure(area under the curve: 0.894; 95%CI: 0.823-0.964). The integrated discrimination improvement analysis showed a significant improvement in the accuracy of liver failure prediction when radiomics signature was added to the clinical prediction model(integrated discrimination improvement = 0.117, P =0.002). The calibration curve and an insignificant Hosmer-Lemeshow test statistic(P = 0.841) demonstrated good calibration of the radiomics-based model. The decision curve analysis showed that patients would benefit more from a radiomics-based prediction model than from a clinical prediction model and radiomics signature alone.CONCLUSION A radiomics-based model of preoperative gadoxetic acid–enhanced MRI can be used to predict liver failure in cirrhotic patients with HCC after major hepatectomy.     

肝癌组织LncRNA TINCR表达水平对术后长期生存的影响

目的 探讨肝癌组织中LncRNA TINCR 表达水平对术后长期生存的影响。方法 回顾性分析2013 年4 月～2016 年2 月间在本院接受手术治疗的157 例肝细胞肝癌患者的临床资料。RT-PCR 法检测肝癌标本内LncRNA TINCR 表达水平，采用ROC 曲线和Kaplan-Meier 法分析LncRNA TINCR 表达水平对肝癌术后长期生存的影响。结果 肝癌组织LncRNA TINCR 表达水平对术后长期生存预测的曲线下面积（AUC）为0.812，特异度为73.77%，灵敏度为79.17%，最佳判读值为1.89（P＜0.0001）。根据ROC 曲线分析结果，将肝癌组织LncRNA TINCR 相对表达水平大于1.89 的93 例（59.24%）患者纳入高表达组，而肝癌组织LncRNA TINCR 相对表达水平小于或等于1.89的64 例（40.76%）患者纳入低表达组。Kaplan－Meier 法生存分析发现高表达组术后3 年内有76 例患者死亡，3 年总生存率为18.28%（17/93）；低表达组术后3 年内有20 例患者死亡，3 年总生存率为68.75%（44/64），低表达组3 年总生存率明显优于高表达组（P＜0.0001，两组间死亡风险比为3.7534，95%可信区间为2.5158～5.6000）。结论 肝癌组织LncRNA TINCR 表达水平与肝癌术后长期生存显著相关，LncRNA TINCR 表达水平升高则预示着预后不佳。     

Papillary thyroid carcinoma with a high tumor mutation burden has a poor prognosis

BackgroundTumor mutation burden (TMB) as a prognostic marker for immunotherapy has shown prognostic value in many cancers. However, there is no systematic investigation on TMB in papillary thyroid carcinoma (PTC).MethodsBased on the somatic mutation data of 487 PTC patients from The Cancer Genome Atlas (TCGA), TMB was calculated, and we classified the samples into high-TMB (H-TMB) and low-TMB (L-TMB) groups. Bioinformatics methods were used to explore the characteristics and potential mechanism of TMB in PTC.ResultsHigh TMB predicts shorter progression-free survival (PFS) (P < 0.001). TMB was positively correlated with age, stage, tumor size, metastasis, the male sex and tall cell PTC. Compared to the L-TMB group, the H-TMB group presented with lower immune cell infiltration, a higher proportion of tumor-promoting immune cells (M0 macrophages, activated dendritic cells and monocytes) and a lower proportion of antitumor immune cells (M1 macrophages, CD8⁺ T cells and B cells). Additionally, the characteristics displayed by different TMB groups were not driven by critical driver mutations such as BRAF and RAS.ConclusionsPTC patients with high TMB have a worse prognosis. By stratifying PTC patients according to their TMB, advanced PTC patients who are candidates for immunotherapy could be selected.     

Risk for Upgrade to Malignancy After Breast Core Needle Biopsy Diagnosis of Lobular Neoplasia: A Systematic Review and Meta-Analysis

PurposeLobular neoplasia (LN) detected on breast core needle biopsy is frequently managed with surgical excision because of concern for undersampled malignancy. The authors performed a systematic review and meta-analysis to estimate the risk for upgrade to malignancy in the setting of imaging-concordant classic LN diagnosed on core biopsy.MethodsPubMed and Embase were searched for original articles published from 1998 to 2020 that reported rates of upgrade to malignancy for classic LN, including atypical lobular hyperplasia (ALH) and classic lobular carcinoma in situ (LCIS). Two reviewers extracted study data and assessed the following quality criteria: exclusion of variant LCIS, exclusion of imaging-discordant lesions, and outcome reporting for ≥70% of lesions. For studies meeting all criteria, pooled risks for upgrade to any malignancy (invasive carcinoma or ductal carcinoma in situ) and invasive malignancy for all LN, ALH, and LCIS were estimated using random-effects models.ResultsFor 65 full-text articles included in the review, the risk for upgrade to any malignancy ranged from 0% to 45%. Among the 16 studies that met all quality criteria for the meta-analysis, pooled risks for upgrade to any malignancy were 3.1% (95% confidence interval [CI], 1.8%-5.2%) for all LN, 2.5% (95% CI, 1.6%-3.9%) for ALH, and 5.8% (95% CI, 2.9%-11.3%) for LCIS. Risks for upgrade to invasive malignancy were 1.3% (95% CI, 0.7%-2.4%) for all LN, 0.4% (95% CI, 0.0%-4.2%) for ALH, and 3.5% (95% CI, 2.0%-5.9%) for LCIS.ConclusionsThe risk for upgrade to malignancy for LN found on breast biopsy is low. Imaging surveillance can likely be offered as an alternative to surgical management for LN, particularly for ALH.     

Optimal combination of antiangiogenic therapy for hepatocellular carcinoma

The success of sorafenib in prolonging survival of patients with hepatocellular carcinoma (HCC) makes therapeutic inhibition of angiogenesis a component of treatment for HCC. To enhance therapeutic efficacy, overcome drug resistance and reduce toxicity, combination of antiangiogenic agents with chemotherapy, radiotherapy or other targeted agents were evaluated. Nevertheless, the use of antiangiogenic therapy remains suboptimal regarding dosage, schedule and duration of therapy. The issue is further complicated by combination antiangiogenesis to other cytotoxic or biologic agents. There is no way to determine which patients are most likely respond to a given form of antiangiogenic therapy. Activation of alternative pathways associated with disease progression in patients undergoing antiangiogenic therapy has also been recognized. There is increasing importance in identifying, validating and standardizing potential response biomarkers for antiangiogenesis therapy for HCC patients. In this review, biomarkers for antiangiogenesis therapy including systemic, circulating, tissue and imaging ones are summarized. The strength and deficit of circulating and imaging biomarkers were further demonstrated by a series of studies in HCC patients receiving radiotherapy with or without thalidomide.     

The Effect of Helicobacter pylori on Gastric Cancer Treated with Adjuvant Chemotherapy After Curative Resection

Helicobacter pylori has been associated with diverse pathologies of varying severity. We investigated the H. pylori infection status and its association with the pathologic features and clinical outcomes in stage III gastric cancer patients treated with adjuvant therapy after curative resection. Between 2004 and 2009, the records of 76 consecutive patients were retrospectively reviewed. H. pylori infection was confirmed by examination of pathological specimen. The relationship between H. pylori and the clinicopathological features was analyzed by Fisher exact test, Student’s t test, and Kaplan-Meier method. Of the 76 patients, 16 patients (21.1 %) were confirmed for H. pylori infection. The median age was 59 years. Twenty-three patients received chemotherapy and remainder received chemoradiotherapy. H. pylori status did not correlate with the clinicopathologic features. It was greater in non-neoplastic tissue than the tumor tissue (21.1 vs 7.9 %). Median follow-up was 21 months. During this period, 88.2 % patients had experienced tumor recurrence, and 85.5 % patients had died. Recurrence was observed in 87.5 % patients and in 88.3 % patients in H. pylori-positive and H. pylori-negative patients, respectively (P = 0.92). Disease-free survival was 28.4 ± 7.9 months and overall survival was 31.5 ± 7.4 months in H. pylori-positive patients compared with 28.3 ± 3.7 and 33.2 ± 3.4 months, respectively, in H. pylori-negative patients. H. pylori infection status did not have effect on the overall or disease-free survival (p = 0.85 and P = 0.86), respectively. H. pylori status might not be useful as a prognostic and predictive factor for clinical outcomes.     

Differentiating autoimmune pancreatitis from pancreatic ductal adenocarcinoma with CT radiomics features

PurposeThe purpose of this study was to determine whether computed tomography (CT)-based machine learning of radiomics features could help distinguish autoimmune pancreatitis (AIP) from pancreatic ductal adenocarcinoma (PDAC).Materials and MethodsEighty-nine patients with AIP (65 men, 24 women; mean age, 59.7 ± 13.9 [SD] years; range: 21–83 years) and 93 patients with PDAC (68 men, 25 women; mean age, 60.1 ± 12.3 [SD] years; range: 36–86 years) were retrospectively included. All patients had dedicated dual-phase pancreatic protocol CT between 2004 and 2018. Thin-slice images (0.75/0.5 mm thickness/increment) were compared with thick-slices images (3 or 5 mm thickness/increment). Pancreatic regions involved by PDAC or AIP (areas of enlargement, altered enhancement, effacement of pancreatic duct) as well as uninvolved parenchyma were segmented as three-dimensional volumes. Four hundred and thirty-one radiomics features were extracted and a random forest was used to distinguish AIP from PDAC. CT data of 60 AIP and 60 PDAC patients were used for training and those of 29 AIP and 33 PDAC independent patients were used for testing.ResultsThe pancreas was diffusely involved in 37 (37/89; 41.6%) patients with AIP and not diffusely in 52 (52/89; 58.4%) patients. Using machine learning, 95.2% (59/62; 95% confidence interval [CI]: 89.8–100%), 83.9% (52:67; 95% CI: 74.7–93.0%) and 77.4% (48/62; 95% CI: 67.0–87.8%) of the 62 test patients were correctly classified as either having PDAC or AIP with thin-slice venous phase, thin-slice arterial phase, and thick-slice venous phase CT, respectively. Three of the 29 patients with AIP (3/29; 10.3%) were incorrectly classified as having PDAC but all 33 patients with PDAC (33/33; 100%) were correctly classified with thin-slice venous phase with 89.7% sensitivity (26/29; 95% CI: 78.6–100%) and 100% specificity (33/33; 95% CI: 93–100%) for the diagnosis of AIP, 95.2% accuracy (59/62; 95% CI: 89.8–100%) and area under the curve of 0.975 (95% CI: 0.936–1.0).ConclusionsRadiomic features help differentiate AIP from PDAC with an overall accuracy of 95.2%.