Purpose: To investigate the influence of ROI placement methods and radiologists' experience on diffusion kurtosis imaging (DKI) and intravoxel incoherent motion (IVIM) parameters' diagnostic performance in differentiating benign and malignant lesions based on the mass and non-mass enhancement (NME). Methods: We evaluated 138 lesions in 131 patients retrospectively. The IVIM and DKI parameter values were measured by three radiologists with different experiences independently using two different ROI placement methods. IVIM parameters include diffusion coefficient (ADCstand), true diffusion coefficient (ADCslow), pseudodiffusion coefficient (ADCfast) and perfusion fraction (f). DKI parameters include mean diffusivity (MD) and mean kurtosis (MK). Each radiologist measured the lesions twice with a 3-month interval. We utilized intra-class correlation (ICC) to determine the inter- and intra-reader agreement for mass and NME, respectively. ROC analysis compared the diagnostic performance of parameters between different radiologists, ROI methods, and between mass and NME. Results: In mass lesions, inter- and intra-observer agreement were perfect for all parameters (ICC: 0.800-989). In NME, the inter-observer agreement was substantial to perfect for all parameters(ICC: 0.703-877), the intraobserver agreement of the senior and intermediate radiologists was substantial to perfect(ICC: 0.748-931) and the intra-observer agreement of the junior radiologist was moderate to substantial(ICC: 0.569-784). The diagnostic performance of ADCslow (Z = 2.209, P = 0.023), MD (mean diffusivity) (Z = 2.887, P = 0.004), and MK (mean kurtosis) (Z = 2.080, P = 0.038) in the small ROI measured by the senior radiologist was better than that of the junior radiologist for NME. The diagnostic performance of ADCslow in the large ROI measured by the senior radiologist (Z = 2.281, P = 0.023) and intermediate radiologist (Z = 2.867, P = 0.0041) was better than the junior radiologist for mass lesions. The diagnostic performance of ADCslow, ADCstand, MD, and MK did not show a significant difference between the two ROI placement methods (P > 0.05). Conclusion: The observers' experience can influence the ROI selection and the diagnostic performance of ADCslow, ADCstand, MD, and MK measured using different methods show equal diagnostic performance.

目的:通过影像学对比分析 Ras相互作用蛋白-1(Rasip1)在急性缺血性脑卒中(AIS)病人中的表达及临床应用价值.方法:选取 2019年 1月—2020年 1月首都医科大学附属北京朝阳医院神经内科收治的 AIS病人 97例作为观察组,选取同期无既往心脑血管疾病史的 100名健康体检者为对照组.对比两组一般资料、血清 Rasip1 表达;分析观察组影像学指标与血清 Rasip1 的相关性;受试者工作特征(ROC)曲线评估 Rasip1对于 AIS的预测价值;对比各影像学检查及 Rasip1 对 AIS的诊断效能.结果:观察组病人血清 Rasip1含量明显低于对照组(P＜0.05).检出组脑卒中病灶体积、脑卒中病灶数量、脑皮质病灶数量、血管狭窄、斑块负荷、脑室旁白质信号(PVH)评分、深部脑白质高信号(DWMH)评分、内侧颞叶萎缩(MTLA)评分高于未检出组,血清 Pasip1 水平低于未检出组(P＜0.05).观察组血清 Rasip1水平与表观弥散系数(ADC)值、镜像区脑血流量(CBF)值呈正相关(P＜0.05);与脑卒中病灶数量、脑卒中病灶体积、脑皮质病灶数量、血管狭窄、斑块负荷、PVH评分、DWMH评分、MTLA评分呈负相关(P＜0.05).脑卒中病灶体积、脑卒中病灶数量、脑皮质病灶数量、血清 Rasip1水平是 AIS是否检出的影响因素(P＜0.05).AIS病人中 Rasip1 检测诊断效能显示,AUC为 0.805,灵敏度为 82.00%,特异度为 85.20%.各检测诊断效能最高的为 CT、MRI、Rasip1 三者联合检测.结论:Rasip1在缺血性脑卒中病人的血清含量明显低于健康对照人群,且与脑卒中病灶数量、脑卒中病灶体积及脑皮质层病灶呈负相关.影像学检查联合 Rasip1可有效提升 AIS的诊断准确率.

目的 探讨不同感兴趣区(ROI)放置方法对扩散峰度成像(DKI)及体素内不相干运动(IVIM)模型参数测量的影响及其对乳腺非肿块强化(NME)良恶性鉴别诊断价值的影响.方法 回顾性分析行MR检查表现为NME的患者63例(63个病变),MR检查序列包括动态对比增强磁共振成像(DCE-MRI)、IVIM扫描和DKI扫描.所有恶性病灶和部分良性病灶经外科手术或穿刺病理证实,部分良性病灶观察1年未见变化为标准.采用最小ROI测量法和最大面积ROI测量法,测量病灶的标准扩散系数(ADCstand/ADCstand-max)、慢速扩散系数(ADCslow/ADCslow-max)、快速扩散系数(ADCfast/ADCfast-max)、平均峰度值(MK/MK-max)和平均扩散系数(MD/MD-max).勾画ROI时避开囊肿、血肿或坏死区域.对比乳腺NME良恶性病变之间各参数的统计学差异,绘制受试者工作特征(ROC)曲线,比较2种不同方法所测得参数的曲线下面积(AUC).结果 63个病变中,良性病变33个,恶性病变30个.2种方法所测量的ADCstand、ADCstand-max、ADCslow、ADCslow-max、MK、MK-max、MD、MD-max在良恶性病变之间均有显著统计学差异(P<0.001).ROC曲线结果显示:虽然最小ROI测量法所得的ADCslow AUC最大(0.888),且敏感度和特异度分别为78.8％和93.3％,但是2种方法所测量的ADCstand和ADCstand-max(Z=1.578,P=0.115)、ADCslow和ADCslow-max(Z=1.563,P=0.118)、MK和MK-max(Z=0.384,P=0.701)、MD和MD-max(Z=1.038,P=0.299)的AUC均无显著统计学差异.结论 对于NME病变,ADCstand、ADCslow、MK、MD有较高的AUC,有助于乳腺良恶性病变的诊断,且2种方法所得参数的鉴别诊断效能无明显差异.

目的 探讨分层分类教育方法在放射科住院医师培训中的应用和意义.方法 通过回顾性统计某医院放射科2015年-2019年近5年397位住院医师的培训情况,包括计算每年培训人员总数、各类学生来源数目及占总数百分比.同时计算五年来的递增比例.2017年-2019年近3年根据不同来源的学生分别进行分层分类教学及多种教学模式联合应用,并分别进行出科考试及教学效果评估.结果 发现培训人数逐年递增,专业来源及影像基础参差不齐.培训人员总数从2015年的25人到2019年105人,增长了3.2倍,以非影像专业的临床住院医师和研究生增多明显,从2015年的3人到2019年的50人,以2017年以后增涨幅度最大,最大增长幅度达15倍.针对影像专业及非影像专业住院医师,2017年-2019年通过采取分层分类教学方法达到很好的教学效果,影像专业学生的成绩由良好达到优秀,非影像专业的成绩由及格达到良好.结论 分层分类教育可以解决当前放射科住院医师规范化培养中面临的人员递增、专业水平参差不齐的问题.

雨课堂是将信息技术融入到教学场景中的新型智慧教学工具,能够科学地覆盖课前-课间-课后的每个教学环节,为教学提供完整立体的数据支持.思维导图是表达发散性思维的可视化的思维工具,能够教会学生"如何学习"和"如何思维",在教学中使用思维导图,不仅能够提高学生的学习能力和思维能力,而且有助于实现教师角色及行为的转换,开启培养创新型人才的新的教学模式.在医学影像教学中引入雨课堂和思维导图教学,把雨课堂、思维导图与传统的课堂教学相结合,有利于整合和充分利用优质教学资源,能够促进学科发展、提升教学质量,为医学影像教学改革新供了新思路和新方法.

调查医学生使用学习资源型微信公众号的学习现状,分析其学习中存在的问题及原因并提出相关对策.

目的 了解临床医学专业医学影像学见习课教学中,微课结合翻转课堂教学效果及PBL教学库及问题库的建立及其效果评价.方法 选取某医科大学附属医院2015级和2016级5年制班及5+3班实习生,微课结合翻转课堂教学实验组21人,对照组41人,PBL教学入组21人,通过问卷调查方法和期末考试消化泌尿生殖系统成绩(包括理论考试和技能操作考试)评价微课结合翻转课堂教学效果,通过问卷调查评价PBL教学库、问题库及其教学效果.结果 微课结合翻转课堂及PBL教学对于学生加深对理论知识的掌握,自主学习能力的提升、交流互助能力的提高、分析解决问题能力的提高,归纳总结能力的提升都有较大的帮助,微课结合翻转课堂教学实验组的理论考试成绩(16.0±1.45)和技能操作考试成绩(26.7±2.65)均高于对照组(P<0.05).结论 微课结合翻转课堂及PBL教学均有助于提高教学效果.

目的 探讨不同方法测量扩散峰度成像(DKI)及体素内不相干运动(IVIM)模型DWI参数鉴别诊断乳腺良恶性肿块性病变的价值.方法 收集经病理或随访证实的59例乳腺肿块性病变患者(62个病变).MR检查包括动态增强MRI、IVIM DWI和DKI.分别于动态增强MRI强化最明显处设置ROI,测量其标准扩散系数(ADCstand)、慢速扩散系数(ADCslow)、平均峰度值(mean kurtosis,MK)和平均扩散系数(mean diffusion,MD);于病灶实性部分最大层面沿病变边缘勾画ROI,测量病灶整体的ADCstand-max、ADCslow-max、ADGfast-max、MK-max、MD-max,比较乳腺良恶性病变间各参数的差异,并绘制ROC曲线,比较AUC.结果 62个病变中,良性36个,恶性26个.良恶性病变间ADCstand、ADCstand-max、ADCslow、ADCslow-max、MK、MK-max、MD、MD-max差异均有统计学意义(P均＜0.001).ROC曲线结果显示ADCslow联合MK的AUC最大(0.915),诊断乳腺良恶性病变的敏感度和特异度分别为88.9％和84.6％.ADCstand与ADCstand-max(Z=1.465,P=0.143)、ADCslow与ADCslow-max(Z=1.013,P=0.311)、MK与MK-max(Z=1.021,P=0.307)、MD与MD-max(Z=1.428,P=0.153)间AUC差异均无统计学意义.结论 各DKI和IVIM DWI参数对鉴别乳腺良恶性肿块具有较高诊断价值,不同测量方法之间鉴别诊断效能无明显差异.

放射科作为公共平台科室,满足不同专业、不同层次住院医师的培训要求,是目前住院医师规范化培训工作急需解决的问题.本文通过分析目前临床专业住院医师放射科规范化培训存在的问题,包括培训医师专业不同,各专业放射科培训细则要求不同且不明确,培训医师基础参差不齐,放射科培训时间短,缺乏与临床实际工作密切相关的培训,缺少医学人文教育培训,提出了临床医生放射科培训的教学改革思路,通过建立严格的管理制度,规范公共培训课程,进行以典型病例为中心的教学,培养住院医师的自学能力,加强人文医学教育,达到良好的培训效果.

目的 分析术前CT表现疑似肺癌的肺良性病变的CT特征及患者的临床表现,以提高临床诊断的准确性.方法 2006年6月至2016年12月,2 239例患者在首都医科大学附属北京朝阳医院接受肺部手术并术后病理证实为肺良性病变.其中,术前增强CT存在误诊考虑恶性可能性大的患者为173例(男101例、女72例,平均年龄56.0岁),归属于20种不同疾病,这20种疾病共包括907例肺良性病变(误诊和非误诊).对173例患者的CT及临床特征进行分析.结果 907例肺良性病变术前增强CT容易误诊为恶性病变的病种依次为:肺平滑肌瘤(100.0％)、肺放线菌病(75.0％)、肺隐球菌病(71.4％)、硬化性血管瘤(50.0％)和机化性肺炎(44.2％).173例术前胸部CT误诊为恶性患者,主要临床表现为发热(17.3％)、咳嗽(56.6％)、黄痰(8.7％)、咯血(28.9％)、胸痛(16.2％)、白细胞计数升高(18.5％)及癌胚抗原升高(4.6％).173例胸部CT考虑恶性可能性大的肺部良性病变中,较常见的疾病依次为:肺结核(29.5％)、机化性肺炎(28.9％)、肺错构瘤(6.4％)和肺脓肿(6.4％).173例患者CT多表现为结节或肿块影,70.5％的病灶≤3 cm,病灶有类似肺癌表现,如边缘毛刺(49.1％)、分叶(33.5％)、胸膜凹陷(27.2％)及明显强化(39.3％),同时部分患者具有肿瘤不常见征象,如钙化(12.7％)、中心液化(18.5％)、卫星灶(9.8％)、肺多发结节(42.2％).24.3％患者存在纵隔或肺门淋巴结肿大.结论 CT征象是诊断肺疾病的重要依据,但部分肺良性病变其CT表现有类似肺癌的特征,有时需要动态观察并结合患者临床特征,在影像变化中识别疾病本质.

Objective To evaluate the value of IVIM-DWI and DTI parameters in quantitative analysis and differential diagnosis of invasive breast carcinoma of no special type(NST).Methods We retrospectively analyzed 60 patients (63 lesions)who underwent MR examination in our hospital and all lesions were verified by pathologic results.MR protocol included DCE-MRI,IVIM-DWI using 14b values and DTI.The ADC,ADCslow,ADCfast,f,λ1of lesions were measured and compared by two independent samples t test between the benign lesions and NST.Logistic regression analysis was made using ADC,ADCslow,f,λ1as predictors in detecting and differentiating the NST,ROC analysis was performed to compare diagnostic performance based on the area under the curve(AUC).Results The ADC,ADCslow,ADCfast,f andλ1of NST were (1.49±0.63)×10-3mm2/s,(1.32±0.49)×10-3mm2/s,(25.98±21.84)×10-3mm2/s,0.20±0.13 and (4.98±0.47)×10-3mm2/s,these values of benign lesions were (2.31±0.66)×10-3mm2/s,(2.24±0.65)×10-3mm2/s,(18.71± 12.26)×10-3mm2/s,0.33±0.15 and(5.59±0.59)×10-3mm2/s.All parameters except ADCfast(P=0.271)had significantly statistical differences (P<0.000 1)between NST and benign lesions.The regression model showed that ADCslowwas an independent predictor in NST’s detection.Conclusion The ADC,ADCslow,f andλ1is helpful for differentiation between NST and benign lesions.The regression model is most valuable in NST detection and ADCslowis the preferred index.

Objective: To evaluate the accuracy and sensitivity of computer-aided detection (CAD) for breast calcifed lesions, and the correlation between the accuracy and sensitivity of CAD and the characteristics of calcifed lesions. Methods: Full-feld digital mammography and CAD system of GE Company were used to evaluate 45 mammographically calcifed lesions proven by pathology. The impacts of calcifcation type, distribution and number of pure calcifed lesions on the accuracy and sensitivity of CAD were evaluated. Results: The total accuracy of CAD for calcifed lesions was 73. 3％ (33/45), the sensitivity was 94. 1％ (32/34), and the positive predictive value was 76. 2％ (32/42). The accuracy (42％, 8/19) and sensitivity (88％, 7/8) of CAD for intermediate calcifcation were all lower than those for typical malignant calcifcation (both 96％, 25/26). The accuracy of CAD was signifcantly correlated with classifcation and distribution characteristics of calcifcation (P＜0. 001), but not correlated with calcifcation number (P＞0. 05). The sensitivity of CAD was only signifcant correlated with calcifcation number (P＜0. 05). Conclusion: The accuracy and sensitivity of CAD for pure calcifed lesions of breast in full-feld digital mammography are high, and the same as the positive predictive value. It can be used sufciently in clinic and breast cancer screening.

The medical imaging noviciate class is an important part of the whole teaching process. Through analyzing the problems existing in the practice teaching of the students major in clinical medicine, we made a preliminary attempt of teaching thought reform in the noviciate among students major in clinical medicine. We could improve the students' learning enthusiasm by leading the students to visit radiology department and understand the equipment and working process; In the actual teaching process, we focus on the advantages and limits of the technology, the application range of the technology and the relationship between medical imaging knowledge and other related knowledge; We applied new teaching methods and teaching means to improve the teaching quality, such as make full use of the PACS system, image workstation and electronic medical record system; We also strengthen individual teaching and enforce examination system rigidly, especially strengthening the practical ability.

目的 探讨MSCT双期增强扫描在诊断局灶性自身免疫性胰腺炎(f-AIP)中的价值.方法 对经临床或病理证实的26例f-AIP患者进行MSCT平扫、动脉期及门静脉期扫描.观察病灶动脉期、门静脉期的CT表现,并比较CT值.结果 f-AIP特征性CT表现包括均匀稍低密度灶(n=26)、门静脉期均匀强化(n=26)、鞘膜征(n=19)、胆总管下段狭窄及胰管狭窄(n=9).f-AIP动脉期、门静脉期CT值分别为(60.21士6.03)HU、(87.13±6.06)HU,门静脉期的CT值高于动脉期(t=22.65,P＜0.05).结论 MSCT双期增强扫描在f-AIP诊断中具有重要价值.

目的 探讨动态增强MRI(DCE-MRI)联合DWI对乳腺X线摄影表现为单纯微小钙化病变的诊断价值.方法 回顾性分析行全视野数字化乳腺X线摄影(FFDM)显示为BI-RADS 3～5类单纯微小钙化病变的患者101例(104个病变).对患者均行乳腺FFDM和MR检查.计算病灶ADC值与正常腺体ADC值的比值(nADC值).对病变进行BI-RADS分类.采用ROC曲线计算ADC和nADC鉴别乳腺良、恶性病变的诊断效能;分别计算FFDM、DCE-MRI和DCE-MRI联合nADC值3种方法诊断乳腺良、恶性病变的敏感度和特异度.结果 恶性病变40个,良性病变64个.ADC值及nADC值鉴别乳腺良、恶性病变的ROC曲线下面积分别为0.81和0.89.FFDM归为BI-RADS 3类病变,FFDM、DCE-MRI、DCE-MRI联合nADC值诊断乳腺恶性病变的特异度差异无统计学意义[100％(22/22)、95.45％(21/22)和95.45％(21/22),P=1.00];对BI-RADS 4类病变3种方法诊断的敏感度差异无统计学意义[100％(21/21)、85.71％(18/21)和85.71％(18/21),x2 =1.44,P=0.23],DCE-MRI诊断的特异度明显高于FFDM[66.67％(28/42) vs 0(0/42),x2=16.80,P＜0.01],DCE-MRI联合nADC值诊断的特异度高于DCE-MRI[88.10％(37/42) vs 66.67％,x2=5.51,P=0.02].3种方法均正确诊断BI-RADS 5类病变.结论 对于FFDM检出的微小钙化病变,DCE-MRI联合nADC值有助于检出BI-RADS 4类的恶性病变.

PURPOSETo investigate the correlations of magnetic resonance, perfusion-weighed imaging (PWI) parameters and microvessel density (MVD) in meningioma.METHODS48 patients with pathologically confirmed meningioma (grade I, 38 cases; grade II+III, 10 cases) completed preoperative routine magnetic resonance imaging (MRI) and PWI. The cerebral blood volume (CBV) map of solid tumor region and the mean of maximum relative cerebral blood volume (rCBV) were then calculated. Immunohistochemical staining was performed in all specimens to measure the MVD.RESULTSOn the CBV map, benign meningiomas showed a high perfusion signal, while malignant meningiomas exhibited a slightly higher one. The rCBV of benign meningiomas was 9.61±4.76, which was significantly higher than 3.61±0.25 of malignant meningiomas (t=7.165, p=0.000). The MVD of benign meningioma strips was 21.16 ± 11.32, which was also significantly higher than 10.71 ± 5.53 strips of malignant meningiomas (t=2.325, p=0.026). The correlation analysis showed that the mean of maximum rCBV and MVD of meningiomas had significant positive correlations (r=0.718, p=0.000).CONCLUSIONSThe CBV map of benign meningiomas is different to that of malignant meningiomas, and the mean of maximum rCBV and MVD have significant positive correlations.

OBJECTIVE:To investigate the differential diagnostic value of DTI parameters in breast mass lesions by comparing apparent diffusion coefficient (ADC), fractional aniotropy (FA) and maximum eigenvalue (λ1)of normal glandular tissue, benign lesions and malignant lesions.METHODS:A total of 71 women patients with 74 mass lesions between December 2013 and October 2015 were enrolled from Beijing Chao-Yang Hospital.MRI protocol included dynamic contrast-enhanced MRI (DCE-MRI)and diffusion tentor imaging(DTI) were executed.The ADC, λ1 and FA of lesions and normal glandular tissue were calculated.The ADC, λ1 and FA of lesions were compared by paired t test between the benign/malignant tumors and the contratlateral healthy breast tissue.ROC curve analysis was performed to compare diagnostic performance based on the area under the curve(AUC). The sensitivity and specificity of the DCE-MRI combined with ADC and DCE-MRI combined with λ1 were calculated.RESULTS:The ADC, FA and λ1 values of malignant lesions were (1.09±0.18)×10(-3) mm(2)/s, 0.22±0.02 and(0.97±0.19)×10(-3) mm(2)/s , these values of benign lesions were (1.52±0.19)×10(-3) mm(2)/s, 0.21±0.02 and(1.79±0.19)×10(-3) mm(2)/s, there were statistically significant differences (all P<0.05). Area under the curve of ADC, FA and λ1 were 0.990, 0.605 and 0.978, respectively. The AUC of FA was lower than that of ADC and λ1(P<0.01, <0.01), but there was no difference between the AUC of ADC and that of λ1(P=0.131 6). The sensitivity DCE-MRI combined with ADC and DCE-MRI combined with λ1 was 88.6% vs 97.1%(P=0.353 3), the specificity was 84.6% vs 97.4%(P=0.113 0).CONCLUSION:ADC and λ1 is helpful to differentiate malignant from benign in mass lesions.

PURPOSE:We aimed to evaluate the diagnostic accuracy of a combination of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and apparent diffusion coefficient (ADC) values in lesions that manifest with architectural distortion (AD) on mammography.METHODS:All full-field digital mammography (FFDM) images obtained between August 2010 and January 2013 were reviewed retrospectively, and 57 lesions showing AD were included in the study. Two independent radiologists reviewed all mammograms and MRI data and recorded lesion characteristics according to the BI-RADS lexicon. The gold standard was histopathologic results from biopsies or surgical excisions and results of the two-year follow-up. Receiver operating characteristic curve analysis was carried out to define the most effective threshold ADC value to differentiate malignant from benign breast lesions. We investigated the sensitivity and specificity of FFDM, DCE-MRI, FFDM+DCE-MRI, and DCE-MRI+ADC.RESULTS:Of the 57 lesions analyzed, 28 were malignant and 29 were benign. The most effective threshold for the normalized ADC (nADC) was 0.61 with 93.1% sensitivity and 75.0% specificity. The sensitivity and specificity of DCE-MRI combined with nADC was 92.9% and 79.3%, respectively. DCE-MRI combined with nADC showed the highest specificity and equal sensitivity compared with other modalities, independent of the presentation of calcification.CONCLUSION:DCE-MRI combined with nADC values was more reliable than mammography in differentiating the nature of disease manifesting as primary AD on mammography.

Objective The aim was to evaluate the diagnostic value of MRI in lesions with architectural distortion manifested in mammography. Methods A retrospective analysis of MRI was performed in 60 patients with 61 lesions manifested as architectural distortion in full?field digital mammography (FFDM) and subsequently confirmed by pathology or two year's follow?up, 30 were malignant and 31 were benign. All the patients underwent MRI within 2 weeks of mammography. MRI protocol included conventional MR, DWI and dynamic contrast?enhanced MRI. The breast imaging reporting and data system (BI?RADS) was used as the reference standard. BI?RADS categories 1 to 3 were considered as negative for malignancy and BI?RADS categories 4 to 5 were considered as positive for malignancy. ADCs of suspicious lesion of interest and glandular tissue were calculated. nADC was then calculated using the following formula:nADC=ADC(lesion)/ADC(glandular tissue). ADC and nADC were compared by using t test. ROC analysis was carried out to define the most effective threshold ADC and nADC value to differentiate malignant from benign lesion in the breast. Diagnostic performance of the FFDM, DCE?MRI and DCE?MRI combined nADC were calculated. Results ADC value of malignant and benign lesions was (1.35±0.31)×10?3 mm2/s and (1.07±0.40)×10?3 mm2/s, respectively . nADC values were 0.83±0.17 and 0.59± 0.25, respectively (t values were 2.82 and 4.54, P<0.01). Area under the curve of ADC and nADC were 0.829 and 0.753 respectively. When threshold of ADC was set at 1.19×10?3mm2/s, sensitivity and specificity were 71.0%and 86.7%, respectively. For a nADC value threshold of 0.589, sensitivity and specificity were 93.5%and 76.7%, respectively. Sensitivity, specificity and accuracy with FFDM were 80.0%(24/30), 9.7%(3/31) and 44.3%(27/61), Sensitivity, specificity and accuracy with DCE?MRI were 90.0%(27/30), 41.9%(13/31) and 65.6%(40/61), Sensitivity, specificity and accuracy with DCE?MRI combined nADC were 93.3%(28/30), 77.4%(24/31) and 85.2%(52/61), respectively. Conclusion Sensitivity and specificity with DCE?MRI combined nADC is higher, and DCE?MRI combined nADC values is helpful to differentiate malignant from benign lesions with architectural distortion manifested in FFDM.

目的 探讨乳腺X线摄影与MRI对乳腺原发局部结构扭曲伴微小钙化病变的诊断价值,以及微小钙化形态特点与病变良恶性的关系.方法 回顾性分析56例(57个病变)行全视野数字化乳腺X线摄影(FFDM)且显示为局部结构扭曲病变并行MRI检查的患者资料,将其分为伴微小钙化病变和不伴钙化病变,以病理结果或2年随访观察结果为金标准,分别统计动态增强MRI(DCE-MRI)及FFDM对2类病变诊断的敏感性、特异性.结果 良性病变29个,恶性病变28个;伴钙化病变33个,不伴钙化病变24个.DCE-MRI对局部结构扭曲伴微小钙化病变诊断的敏感性与FFDM相同(87.5％),特异性较FFDM显著提高(58.8％ vs17.6％,P=0.032 4);对不伴钙化病变诊断的敏感性二者无统计学差异(P=0.068 6),特异性有显著提高(0 vs 41.7％,P=0.037 3).点状钙化多出现在良性病变中(P=0.006 6),而其他钙化类型在良恶性病变分布上无统计学差异.结论 DCE-MRI较FFDM对于原发局部结构扭曲伴或不伴微小钙化病变均有较高的鉴别诊断价值.