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.     

肿瘤免疫检查点抑制剂相关的肝毒性

肿瘤免疫检查点抑制剂治疗为肿瘤患者带来生存获益的同时,也面临了许多挑战,例如免疫介导的肝毒性的发生。深入了解免疫检查点抑制剂治疗肿瘤过程中导致肝损伤的发生情况、可能机制、危险因素等,有助于更好地临床管理。     

Utility of Tissue Similarity Maps Based on Relative Cerebral Blood Volume for Grading Gliomas as Validated by Histological Results

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死亡结构域相关蛋白及其在宫颈病变中的研究进展

宫颈癌对妇女健康构成严重威胁,人乳头瘤病毒感染与宫颈病变及宫颈癌的发生密切相关。关于宫颈癌发生发展的机制仍在研究中。近年研究发现一种多功能核蛋白,即死亡结构域相关蛋白(death domain associated protein,Daxx),其与细胞内蛋白或病毒蛋白相互作用,参与调节细胞凋亡、转录调控、抗病毒等细胞活动,在不同途径中发挥不同的生理或病理作用。通过对Daxx功能及其作用机制的研究有助于进一步阐明宫颈癌发生发展的机制,有助于发现新的预防和治疗方法。综述Daxx的一般特性和研究现况及其在宫颈病变的研究进展。     

利用CNV-seq技术产前诊断Pallister-Killian综合征胎儿一例

应用拷贝数变异测序(copy number variation sequencing,CNV-seq)技术鉴别来源不明的胎儿标记染色体,明确其遗传物质的来源,并探讨此技术在产前诊断中的应用价值。讨论Pallister-Killian综合征(Pallister-Killian syndrome,PKS)的临床特征及遗传学特点,提高对此类罕见染色体疾病的认识。该病例因在妊娠中期超声发现胎儿异常而行羊水穿刺进行CNV-Seq检测,同时分析胎儿和父母的核型。羊水CNV-Seq结果示该样本12号染色体p13.33-p11.1处检测到拷贝数为3.5、片段大小为34.70 Mb的嵌合重复区域;羊水染色体核型结果为47,XY,+i(12)(p10)[58]/46,XX[42],综合上述结果考虑为PKS。通过结合超声结果,综合应用染色体G显带核型分析和CNV-seq技术能准确确认染色体异常片段来源,在产前有效诊断PKS患者。     

D6S1043、D12S391基因座与主动攻击行为的关联研究

目的:探讨D6S1043、D12S391基因座的基因多态性对主动攻击行为的影响。方法:应用聚合酶链反应技术结合毛细管电泳法对114例男性主动攻击行为者(研究组)及120名健康男性(对照组)进行D6S1043、D12S391基因座的基因型及等位基因检测,分析D6S1043、D12S391基因座多态性与主动攻击行为的相关性。结果:研究组D6S1043基因座中12~19基因型频率(13.16%)明显高于对照组(1.67%)(P0.05);两组等位基因频率差异无统计学意义;两组D12S391基因座的基因型及等位基因频率差异无统计学意义。结论:D6S1043基因座中12~19基因型可能主动攻击行为有关。