CT鉴别诊断原发性与继发性肺淋巴瘤

目的 观察CT鉴别诊断原发性肺淋巴瘤(PPL)与继发性肺淋巴瘤(SPL)的价值。方法 回顾性分析接受胸部CT平扫的28例PPL(PPL组)及27例SPL(SPL组)患者,其中18例PPL及16例SPL接受增强扫描,观察病变CT表现;采用单因素分析及多因素logistic回归分析其CT平扫相关征象,筛选鉴别PPL与SPL的独立预测因素,并绘制受试者工作特征(ROC)曲线,评估各指标单独及联合鉴别诊断效能。结果 PPL及SPL均可表现为肺结节、肿块或实变。PPL多为分布于肺外周的单发病变,可见支气管充气征伴扩张;SPL常为多发病变,多伴纵隔/肺门淋巴结肿大及胸腔积液(P均＜0.05)。接受增强CT的18例PPL与16例SPL之间,病变强化方式差异有统计学意义(P=0.04),强化程度及是否存在血管造影征差异均无统计学意义(P均＞0.05)。病变数目、充气支气管征伴扩张及胸腔积液是鉴别PPL与SPL的独立预测因素,其鉴别PPL与SPL的曲线下面积(AUC)分别为0.74、0.68、0.69,三者联合诊断的AUC为0.91。结论 CT所见病变数目、充气支气管征伴扩张及胸腔积液有助于鉴别PPL及SPL。     

基于增强CT影像组学鉴别胸腺瘤组织学分型

目的 观察基于增强CT影像组学鉴别胸腺瘤组织学分型的价值。方法 回顾性分析226例经病理证实的胸腺瘤患者,按7∶3比例将其分为训练集(n=159)及测试集(n=67);利用最大相关最小冗余(mRMR)及最小绝对收缩和选择算子(LASSO)算法筛选最佳影像组学特征,构建鉴别胸腺瘤组织学分型的影像组学模型;以单因素及多因素logistic回归分析筛选鉴别胸腺瘤组织学分型相关的临床及CT表现,构建临床模型和联合影像组学特征及临床、CT特征的影像组学列线图。绘制受试者工作特征(ROC)曲线,计算曲线下面积(AUC),评价3种模型鉴别胸腺瘤组织学分型的效能并比较其差异,评价影像组学列线图的临床价值。结果 最终基于增强动脉期及静脉期CT筛选出19个最佳影像组学特征,以建立影像组学模型。临床模型由患者年龄、重症肌无力、病灶CT表现形态、侵犯邻近组织及动脉期CT值构成。训练集中,影像组学列线图及影像组学模型区分低危组胸腺瘤与高危组胸腺瘤的AUC (0.91、0.89)均高于临床模型(0.79,Z=3.62、2.49,P均＜0.05),而影像组学列线图与影像组学模型AUC差异无统计学意义(Z=1.54,P=0.12);3种模型在测试集中的AUC差异均无统计学意义(P均＞0.05)。阈值概率为0.1~1.0时,影像组学列线图的临床获益均大于临床模型及影像组学模型。结论 基于增强CT影像组学模型和基于临床、CT表现及影像组学特征的影像组学列线图均有利于鉴别胸腺瘤组织学分型,后者临床获益更高。     

肾血管平滑肌脂肪瘤自发性破裂危险因素

目的 观察肾血管平滑肌脂肪瘤(RAML)自发性破裂的危险因素。方法 纳入151例接受超选择性栓塞的RAML患者,根据治疗前CT或血管造影是否可见对比剂外溢将其分为破裂组(n=45)及未破裂组(n=106);比较组间患者基本资料及肿瘤影像学表现的差异,以多因素logistic回归分析观察RAML破裂的独立危险因素,构建风险预测模型并以列线图可视化;绘制受试者工作特征(ROC)曲线,评价以各危险因素及模型判断RAML破裂的效能。结果 组间肿瘤最大径、瘤内动脉瘤最大径＞5 mm占比差异均有统计学意义(P均＜0.05)。ROC曲线分析结果显示,以6.32 cm为截断值,根据肿瘤最大径判断RAML破裂的曲线下面积(AUC)为0.684。多因素logistic分析显示,单发肿瘤、直径较大及瘤内动脉瘤最大径≥5 mm(OR=0.37、1.14、5.69,P均＜0.05)是RAML破裂的独立危险因素;以之构建的预测RAML破裂风险模型预测RAML破裂的AUC为0.776,且模型校准曲线与理想曲线的重合度尚可。结论 单发病灶、肿瘤较大且存在≥5 mm的瘤内动脉瘤是RAML自发性破裂的独立危险因素。     

SPECT联合血清脂联素鉴别诊断甲状腺良、恶性结节

目的 分析SPECT联合血清脂联素鉴别诊断甲状腺良、恶性结节的效能。方法 回顾性分析815例单发甲状腺结节患者,术前均接受甲状腺SPECT显像及血清脂联素水平检测;以术后病理结果为金标准,采用受试者工作特征(ROC)曲线评估SPECT、血清脂联素及二者联合鉴别诊断甲状腺良、恶性结节的效能。结果 815枚甲状腺结节中,良性结节777枚(良性组),恶性结节38枚(恶性组),其血清脂联素水平分别为(12.65±1.45)ng/ml及(6.28±0.94)ng/ml,组间差异有统计学意义(P＜0.001)。SPECT正确诊断恶性结节30枚、良性结节582枚,其鉴别诊断甲状腺良、恶性结节的曲线下面积(AUC)为0.783。以8.95 ng/ml为血清脂联素的截断点,正确诊断恶性甲状腺结节27例、良性544例,其AUC为0.723。SPECT联合血清脂联素正确诊断26例恶性、653例良性甲状腺结节, AUC为0.901。结论 SPECT联合血清脂联素鉴别诊断甲状腺良、恶性结节的效能较高。     

CT鉴别诊断造血干细胞移植后胃肠道移植物抗宿主病与机会性感染性肠炎

目的 观察CT鉴别诊断造血干细胞移植(HSCT)后胃肠道移植物抗宿主病(GI-GVHD)与机会性感染性肠炎的价值。方法 回顾性分析59例HSCT后出现胃肠道症状且经内窥镜下组织活检病理确诊GI-GVHD(GI-GVHD组,n=31)或机会性感染性肠炎(机会性感染性肠炎组,n=28)患者,观察其CT表现差异。结果 GI-GVHD组CT显示肠壁增厚、肠壁强化、肠管积气及肠外CT表现肠周淋巴结增生、胆囊炎、膀胱炎或膀胱出血率均高于机会性感染性肠炎组(P均＜0.05),而CT显示多灶性肠壁炎症及肠系膜水肿率组间差异均无统计学意义(P均＞0.05)。结论 CT有助于鉴别诊断HSCT后GI-GVHD与机会性感染性肠炎。     

光谱CT多参数定量分析对乳腺肿块良恶性的鉴别价值

背景与目的 乳腺肿瘤是妇女常见疾病之一,准确判断乳腺肿瘤的良恶性是精准治疗的前提,本文旨在探讨双层探测器光谱CT多参数定量分析鉴别乳腺肿块良恶性的价值。方法 回顾性分析经病理证实,且行光谱CT双期增强扫描的25例乳腺肿块患者（31个病灶）资料,比较良、恶性组双期40 keV虚拟单能量图（VMI_{40 keV}）CT值及强化增值（?CT）、碘浓度（IC）及标准化碘浓度（NIC）、光谱曲线斜率（K）、有效原子序数（Z_eff）的差异。采用受试者工作特征（ROC）曲线分析比较各参数鉴别乳腺肿块良恶性的诊断效能。结果 乳腺恶性肿瘤动脉期VMI_{40 keV} ?CT及双期VMI_{40 keV} CT值、IC、NIC、K、Z_eff均大于良性肿瘤,差异均有统计学意义（均P<0.05）。动脉期各参数的曲线下面积（AUC）均高于静脉期,其中动脉期VMI_{40 keV} ?CT的AUC最大,AUC为0.899（95% CI=0.737~0.978）,阈值为35.75 HU时,其鉴别乳腺肿块良恶性的敏感度、特异度、阳性预测值、阴性预测值分别为100.0%、81.8%、75.0%、100.0%。结论 双层探测器光谱CT多参数定量分析可有效鉴别乳腺肿块的良恶性,动脉期诊断效能高于静脉期,其中VMI_{40 keV} ?CT的诊断能力最佳。     

MRI鉴别诊断卵巢颗粒细胞瘤与卵泡膜纤维瘤

目的 观察MRI鉴别诊断卵巢颗粒细胞瘤（OGCT）与卵泡膜纤维瘤（OTF）的价值。方法 回顾性分析37例OGCT（OGCT组）与74例OTF（OTF组）女性,比较其MRI参数;行多因素logistic回归分析,观察各参数单独及联合鉴别诊断OGCT与OTF的效能。结果 组间病灶囊实性分型,囊变程度、囊区最大径,实性部分T2WI信号、强化程度、表观弥散系数（ADC）,以及是否合并蜂窝征/奶酪征、有无肿瘤内血管及出血差异均有统计学意义（P均＜0.05）。其中,囊变程度、ADC及是否合并蜂窝征/奶酪征为MRI鉴别OGCT与OTF的影响因素,其鉴别OGCT与OTF的曲线下面积（AUC）分别为0.834、0.868及0.744,而三者联合的AUC为0.934,大于其单一AUC（P均＜0.05）。结论 病灶囊变程度、实性部分ADC及是否合并蜂窝征/奶酪征等MRI特征有助于鉴别OGCT与OTF。     

CT影像组学联合CT特征预测肺亚实性结节侵袭性

目的 观察CT影像组学联合CT特征预测肺亚实性结节侵袭性的价值。方法 回顾性分析170例肺亚实性结节患者资料,包括6例非典型腺瘤样增生(AAH)、12例原位腺癌(AIS)、58例微浸润性腺癌(MIA)及94例浸润性腺癌(IAC),将AAH、AIS和MIA归为非侵袭组、IAC归为侵袭组。按7∶3比例将患者分为训练集(n=119,含5例AAH、9例AIS、36例MIA及69例IAC)和验证集(n=51,含1例AAH、3例AIS、22例MIA及25例IAC)。采用单因素及logistic回归分析训练集患者一般资料及病灶CT表现,筛选预测肺亚实性结节侵袭性的独立危险因素并建立CT模型;基于训练集提取及筛选病灶最佳影像组学特征,以之构建影像组学模型。基于CT模型及影像组学模型构建联合模型,并以列线图将其可视化。绘制受试者工作特征(ROC)曲线,计算曲线下面积(AUC),基于验证集评估各模型诊断效能;以校准曲线评价联合模型的校准程度。结果 CT所示结节长径和最大CT值为预测肺亚实性结节为IAC的CT相关独立危险因素,以之构建CT模型。基于训练集筛选出6个最佳影像组学特征并构建影像组学模型。CT模型、影像组学模型及联合模型预测验证集肺亚实性结节侵袭性的AUC分别为0.772、0.785及0.869;联合模型的AUC高于CT模型(Z=2.336,P=0.019)而与影像组学模型差异无统计学意义(Z=1.925,P=0.054),其预测结果与实际结果的一致性较高。结论 CT影像组学联合CT特征可有效预测肺亚实性结节侵袭性。     

三维能量多普勒超声联合MR弥散加权成像鉴别FIGO ⅠA、ⅠB及ⅡA期宫颈癌

目的 分析三维能量多普勒超声(3D-PDU)联合MR弥散加权成像(DWI)术前鉴别国际妇产联盟(FIGO)ⅠA、ⅠB及ⅡA期宫颈癌的价值。方法 回顾性分析60例经术后病理确诊宫颈癌患者的术前宫颈3D-PDU及DWI,其中FIGO分期ⅠA期19例(ⅠA期组),ⅠB期26例(ⅠB期组),ⅡA期15例(ⅡA期组)。比较各组病灶相关血管参数血管形成指数(VI)、血流指数(FI)、血管形成-血流指数(VFI)及DWI参数表观弥散系数(ADC)和指数ADC (eADC)的差异;以logistic回归及受试者工作特征(ROC)曲线评价3D-PDU、DWI及二者联合鉴别FIGO ⅠA、ⅠB及ⅡA期宫颈癌的效能。结果 FIGO ⅠA、ⅠB及ⅡA期宫颈癌中,随分期级别提高,VI、FI及VFI均逐渐升高,ADC逐渐降低而eADC逐渐升高(P均＜0.05)。3D-PDU、DWI及二者联合鉴别宫颈癌FIGO ⅠA、ⅠB及ⅡA期宫颈癌模型,即logit (PRE)_3D-PDU、logit (PRE)_DWI及logit (PRE)_联合中,logit (PRE)_联合模型判断宫颈癌FIGO分期的曲线下面积(AUC)为0.89,大于logit (PRE)_3D-PDU及logit (PRE)_DWI(0.78、0.75,Z＝4.73、3.55,P均＜0.05),其诊断敏感度及特异度亦均高于logit (PRE)_3D-PDU及logit (PRE)_DWI(P均＜0.05)。结论 三维能量多普勒超声联合DWI可于术前有效鉴别FIGO ⅠA、ⅠB及ⅡA期宫颈癌。     

血管内介入治疗缺血性脑卒中后脑内高密度影与出血转化的关系

目的 采用双源CT量化评价经血管内介入治疗缺血性脑卒中(CIS)后脑内高密度影,探讨其与出血转化的关系。方法 回顾性分析167例CIS患者经介入治疗后即刻颅脑双能量CT资料,根据术后24~72 h CT平扫或MR检查结果分为出血组(n=42)及无出血组(n=125),比较组间患者临床资料、脑内新发高密度影CT值及其体积的差异,分析影响出血转化的因素,评价CT参数与出血转化的相关性;绘制受试者工作特征曲线,评价各指标判断出血转化的效能。结果 出血组患者高血脂比例低于无出血组(P<0.05);出血组新发高密度影占比、高密度影的最大CT值、平均CT值及其体积均大于无出血组(P均<0.001)。高血脂病史为出血转化的保护因素(P<0.05);新发高密度影最大CT值、平均CT值及其体积为出血转化的危险因素(P均<0.001),且均与出血转化呈正相关(P均<0.001),以之判断血管内介入治疗CIS后患者发生出血转化的曲线下面积(AUC)分别为0.950、0.910及0.888,联合应用新发高密度影最大CT值+体积、平均CT值+体积及最大CT值+平均CT值+体积判断发生出血转化的AUC分别为0.944、0.923及0.941。结论 血管内介治疗CIS后即刻CT显示缺血区新发高密度影的最大CT值、平均CT值及其体积均与术后出血相关。     

CT鉴别诊断胃神经内分泌癌与胃腺癌

目的观察CT鉴别诊断胃神经内分泌癌(GNEC)与胃腺癌(GC)的效能。方法回顾性分析经病理确诊的62例GNEC(GNEC组)和70例GC(GC组)患者,手术或活检前7天内均接受腹部增强CT检查,对比组间临床资料及CT特征。针对差异有统计学意义的CT特征进行Logistic回归分析,并绘制受试者工作特征(ROC)曲线,分析CT特征对鉴别GNEC与GC的效能。结果组间肿瘤边界、囊变/坏死和肝转移以及肿瘤厚径、静脉-动脉期强化率差异均有统计学意义(P均0.05)。肿瘤边界、厚径、囊变/坏死、肝转移及强化特点可作为独立预测因素鉴别GNEC与GC(P均0.05)。ROC曲线结果显示,以上述参数单独鉴别GNEC与GC的曲线下面积(AUC)分别为0.63、0.69、0.65、0.62、0.63,各参数联合鉴别诊断的AUC可达0.83。结论 CT特征可用于鉴别GNEC与GC。     

CT影像组学模型鉴别诊断肺淋巴瘤与肺浸润性黏液腺癌

目的观察CT影像组学模型鉴别诊断肺淋巴瘤与肺浸润性黏液腺癌(PIMA)的价值。方法回顾性分析经病理证实的34例肺淋巴瘤(淋巴瘤组)及64例PIMA患者(PIMA组),按7∶3比例将其随机分入训练集和验证集。于胸部CT纵隔窗图像上沿病灶边缘手动勾画三维容积感兴趣区(VOI),提取影像组学特征参数。以最小冗余最大相关、LASSO十折交叉验证进行特征降维,以多因素Logistic回归分别构建影像组学标签、影像学特征模型及二者融合的个体化预测模型(以列线图表示)。采用受试者工作特征(ROC)曲线评价各模型对肺淋巴瘤与PIMA的鉴别效能,以决策曲线分析(DCA)综合评价模型的临床效用价值。结果共获得15个影像组学参数用于构建影像组学标签;ROC曲线结果显示其鉴别训练集肺淋巴瘤与PIMA的AUC=0.84,验证集AUC=0.77。以空气支气管征、支气管扩张及胸腔积液构建影像学特征模型,训练集AUC=0.85,验证集AUC=0.81;融合列线图对训练集AUC=0.95,验证集AUC=0.92;列线图具有更高的临床效用价值。结论基于CT征象、影像组学标签构建的个体化预测模型可有效鉴别肺淋巴瘤与PIMA。     

Predictive value of renal tumor contour irregularity score in pathological T3a upstaging of clinical T1 renal cell carcinoma: A multi-institutional study

PurposeTo explore the predictive value of renal tumor contour irregular degree (CID) in pathological T3a upstaging of clinical T1 renal cell carcinoma (RCC).Materials and methodsWe performed a retrospective multi-institutional review of 1,487 patients with clinical T1N0M0 RCC between January 2009 and June 2019. Kaplan-Meier survival curve and Cox regressions were used to analyze the prognostic factors of disease-free survival (DFS). Logistic regressions were performed to determine predictors of pathological T3a upstaging in clinical T1 RCC.ResultsAmong 1,487 patients with cT1 RCC, 96 (6.5%) were pathological T3a upstaging. Multivariable logistic regression analysis showed that age (odds ratio [OR] = 1.022, 95% confidence interval [CI] = 1.001–1.042, P = 0.036), tumor maximum diameter(OR = 1.242, 95% CI = 1.042-–1.480, P = 0.015) and CID (OR = 1.067, 95% CI = 1.051–1.083, P < 0.001) were independent predictors of pathological T3a upstaging. The area under the curve (AUC) of the prediction model that included the CID was 0.846, while the AUC of the prediction model that did not include CID was only 0.741, the difference was statistically significant (P < 0.001). Kaplan-Meier survival curve showed that patients with pathological T3a upstaging had significantly worse DFS than patients without pathological T3a upstaging (P < 0.001). Multivariable Cox analysis showed that pathological T3a upstaging (HR = 1.836, 95% CI = 1.013–3.329, P = 0.002) is an independent prognostic factor for DFS in patients with cT1N0M0 RCC.ConclusionsThe predictive model of CID combined with tumor maximum diameter and age significantly improved the ability to predict pathological T3a upstaging in clinical T1 RCC, compared with the prediction model of tumor maximum diameter combined with age. The predictive model of CID combined with tumor maximum diameter and age may be applicable to patients considering partial vs. radical nephrectomy.     

Pretreatment differentiation of renal cell carcinoma subtypes by CT: the influence of different tumor enhancement measurement approaches

Purpose

We conducted a retrospective study to evaluate the influence of different tumor enhancement measurement approaches on the ability of computed tomography (CT) to differentiate between solid forms of clear cell renal cell carcinoma (RCC), other RCC histologic subtypes and oncocytomas. Different RCC subtypes have a diverse range of malignant potential; consequently, the information about RCC subtype obtained using minimally invasive imaging method before the treatment could allow the more accurate therapy planning. Differentiation of ccRCCs from oncocytomas is important because oncocytomas are usually benign tumors which could be treated conservatively.

Methods

CT images of 113 patients with 118 solid renal tumors were evaluated. The imaging protocol consisted pre-contrast and post-contrast images during the arterial and nephrographic phases. Renal tumor attenuation values were measured using region of interest covering as much of the solid enhancing tumor tissue as possible. Tumor attenuation values and tumor enhancement ratios were correlated with histologic subtype. One hundred of tumors were diagnosed as clear cell RCC, nine as non-clear cell RCC and nine as oncocytoma.

Results

Tumor attenuation values of >74 HU on the arterial phase scans significantly correlated with clear cell RCC (Az 0.73). The tumor-to-aorta enhancement ratios calculated on tumor attenuation values measured on the arterial phase scans had a cutoff value of >0.29, which significantly correlated with clear cell RCC (Az 0.79). All ROC curves for differentiating the clear cell RCC from oncocytomas have area under the curve too small (0.5 or less) to have chose cutoff value with sensitivity and specificity that could be applied in clinical work.

Conclusion

Enhancement measurements of renal carcinomas on CT images in the arterial phase can be used as an auxiliary method in the pretreatment differentiation of solid forms of the most frequent RCC subtypes in patients not suitable for core biopsy but who are suitable for minimally invasive treatment methods and/or targeted therapy.     

Translocation renal cell carcinomas in adults: a single-institution experience

Translocation renal cell carcinoma is a newly recognized subtype of renal cell carcinoma (RCC) with chromosomal translocations involving TFE3 (Xp11.2) or, less frequently, TFEB (6p21). Xp11 translocation RCC was originally described as a pediatric neoplasm representing 20% to 40% of pediatric RCCs, with a much lower frequency in the adult population. TFEB translocation RCC is very rare, with approximately 10 cases reported in the literature. Here, we describe the clinicopathologic features of adult translocation RCC from a single institution. Using tissue microarray, immunohistochemistry, cytogenetic examination, and fluorescence in situ hybridization, we identified 6 (～5%) cases of TFE3 translocation RCC and 1 (<1%) case of TFEB translocation RCC in 121 consecutive adult RCC cases between 2001 and 2009. Our results suggest that weak TFE3 staining of a significant proportion of RCC cases may be because of expression of the full-length TFE3 protein rather than the chimeric fusion protein resulting from chromosomal translocation.     

A case of xp11.2 translocation renal cell carcinoma

Xp11.2/TFE3 translocation renal cell carcinoma (RCC), a recently classified distinct subtype, is a rare tumor that usually affects children and adolescents. The morphology and biological behavior are not widely recognized, Xp11.2 translocation RCC is suggestive of early metastases despite the small tumor size. The definitive diagnosis requires the evidence of several different reciprocal translocations involving the TFE3 gene located on chromosome Xp11.2. Here, we present a case of Xp11.2 translocation RCC in an 18-yearold male. He was referred to our hospital because of a right renal tumor with macroscopic hematuria and right flank colic. The radiographic evaluation including magnetic resonance imaging (MRI) suggested it to be a typical papillary renal cell carcinoma or benign renal tumor. He underwent laparoscopic nephrectomy against the repeat symptom in spite of small tumor (3.5 cm in diameter). The immunohistochemical study revealed nuclear staining for TFE3 protein in the cancer cells. The urologic and radiologic outcomes were satisfactory after more than 1 year of follow-up.     

肾母细胞瘤过表达基因和WT1基因在肾癌组织中转录水平的定量研究

目的 研究肾癌组织中肾母细胞瘤过表达基因（NOV）及WT1基因mRNA定量表达水平及意义。方法 肾癌组织标本57例。男40例，女17例，平均年龄65岁。T139例、T213例、T3a5例；G114例、G223例、G320例。应用实时RT—PCR方法定量检测癌组织及36例癌旁正常肾组织中NOV和WT1的mRNA表达，并对2种基因表达水平进行相关性分析。结果 肾癌组织NOVmRNA表达水平中位值（1．17）显著低于癌旁正常组织（4．32，P〈0．05），乳头状肾癌组织表达量（2．67）显著高于透明细胞癌（1．06，P〈0．05），G．肿瘤表达量（4．61）显著高于G2～G3肿瘤（1．11，P〈0．05）。NOV表达与肿瘤分期、大小等无显著相关。WT1mRNA在肾癌组织中的表达水平中位值（0．13）显著低于癌旁正常组织（1．93，P〈0．05），WT1表达与肿瘤分期、分级、组织类型等均无关。NOVmRNA与WT1mRNA表达水平无明显相关。结论 NOV基因与肾癌的发生和分化相关。WT1在肾癌组织中表现为低表达。NOV表达是否受WT1的调节尚需进一步研究。