肺部病灶~（18）F-FDG PET-CT显像与CT引导下穿刺活检结果对比分析

目的：探讨不同大小病灶18F-FDG PET-CT的显像特点与同层面CT引导下穿刺活检结果的关系。方法：回顾性研究经过18F-FDG PET-CT及CT引导下穿刺活检两种检查的病例,通过统计病灶的大小、病理、穿刺取材部位的放射性浓聚程度、SUVmax来分析不同大小病灶18F-FDG PET-CT的显像特点与同层面CT引导下穿刺活检结果的关系。结果：69例患者,共穿刺74个病灶,71个病灶测得SUVmax,放射性浓聚程度不同的病灶其穿刺敏感性、病灶大小的分布情况有显著性差异（P〈0.05）,≤3 cm组病灶放射性均匀浓聚率高,≥5 cm组放射性均匀浓聚率低（P〈0.05）,≤3 cm的均匀浓聚的恶性病灶其SUVmax低于〉3 cm组（P〈0.05）,良恶性病灶SUVmax无显著性差异（P〉0.05）。结论：不同大小的病灶在18F-FDG PET-CT上放射性浓聚程度不同,反映了病灶生物学特性的空间差异,进而影响穿刺活检的准确率。     

非小细胞肺癌EGFR表达与^18F-FDG-PET SUVmax值的相关性研究

目的：探讨非小细胞肺癌组织中EGFR蛋白在的表达与PET-CT检测的SUVmax的相关性。方法：临床收集30例非小细胞肺癌患者,每一病例首先行PET-CT检查,然后行CT导引下活检穿刺,同一病灶取2个穿刺部位,分别为肿瘤组织内SUVmax值2.5-5区域及SUVmax〉5区域,采用免疫组化方法检测检测30例非小细胞肺癌肿瘤内部不同部位EGFR表达。结果：EGFR蛋白表达、SUVmax值在不同年龄、性别、病理类型中表达的差异无统计学意义（P均〉0.05）。EGFR蛋白表达、SUVmax值在不同的肿瘤直径、临床分期组表达差异有统计学意义（P均〈0.05）。NSCLC肿块SUVmax值与组织EGFR表达呈显著正相关（P〈0.05）。结论：NSCLC组织SUV值与组织EGFR表达有显著相关性,可以为非小细胞肺癌的放疗提供指导。     

非小细胞肺癌EGFR 表达与18F-FDG-PET SUVmax 值 的相关性研究

目的:探讨非小细胞肺癌组织中EGFR蛋白在的表达与PET-CT检测的SUVmax的相关性。方法:临床收集30例非小细胞肺癌患者,每一病例首先行PET-CT检查,然后行CT导引下活检穿刺,同一病灶取2个穿刺部位,分别为肿瘤组织内SUVmax值2.5-5区域及SUVmax>5区域,采用免疫组化方法检测检测30例非小细胞肺癌肿瘤内部不同部位EGFR表达。结果:EGFR蛋白表达、SUVmax值在不同年龄、性别、病理类型中表达的差异无统计学意义(P均>0.05)。EGFR蛋白表达、SUVmax值在不同的肿瘤直径、临床分期组表达差异有统计学意义(P均<0.05)。NSCLC肿块SUVmax值与组织EGFR表达呈显著正相关(P<0.05)。结论:NSCLC组织SUV值与组织EGFR表达有显著相关性,可以为非小细胞肺癌的放疗提供指导。     

直径小于1 cm孤立性肺结节的18F-FDG PET/CT诊断研究进展

孤立性肺结节的鉴别诊断一直是胸部影像学的研究热点。早期且准确地鉴别肺内小结节的良恶性,对于患者治疗方案的确定以及随访情况的评估均具有重要的临床意义。~(18)F-FDG PET/CT在鉴别诊断恶性肿瘤方面具有明显优于其他传统检查的高特异性和高敏感性,其公认的恶性肿瘤的诊断阈值是最大化标准摄取值(maximum standard uptake value, SUVmax)为2.5,然而部分临床数据显示一些直径小于1 cm的恶性肺结节的SUVmax数值小于2.5。因此在早期研究中,~(18)F-FDG PET/CT在诊断直径较小的肺结节的其临床价值仍存在争议。为了尽量降低SUVmax的测量误差,提高~(18)F-FDG PET/CT诊断的准确率,衍生出了许多SUVmax辅助诊断方法以及优化的重建算法、放射性显像剂的联合应用等手段。本文将对~(18)F-FDG PET/CT鉴别诊断直径小于1 cm孤立性肺结节的研究进展进行综述。     

肿瘤/肝脏比值在~(18)F-FDG符合线路SPECT/CT显像在肺癌诊断中的价值

目的:探讨18F-FDG符合线路SPECT/CT显像在肺癌病灶的检测能力以及肿瘤/肝脏比值对肺部良恶性病灶及胸部小病灶诊断的临床价值。方法:回顾性分析2011年6月至2013年4月期间于西安交通大学第一附属医院行18F-FDG符合线路SPECT/CT显像的肺癌疑诊患者41例CT测量肺部原发病灶最大直径4.16±2.81厘米(最小直径1.3厘米,最大直径16厘米),以病理结果作为判断标准,通过t检验及接受者操作特征曲线(receiver operating characteristic,ROC)研究18F-FDG符合线路SPECT/CT显像对肺部病灶、肺及纵膈小病灶的诊断价值。结果:18F-FDG符合线路SPECT/CT显像肺部良恶性病灶的肿瘤/肌肉(T/N)、肿瘤/肝脏(T/L)比值差异均具有显著统计学意义(P0.01),T/L比值在肺部良恶性病灶和肺及纵膈最大横径小于3 cm的病灶ROC曲线的曲线下面积分别为0.857、0.810,均大于T/N比值相应的ROC曲线下面积(分别为0.825、0.760)。T/N=3.5为界值时,诊断肺部病灶的灵敏度为90%,特异度为71.4%,准确度为0.614;诊断最大横径小于3 cm病灶的灵敏度为70%,特异度为80%,准确度为0.50。T/L=2.3时诊断肺部病灶的灵敏度为80%,特异度为85.7%,准确度为0.657。T/L=1.6时诊断最大横径小于3 cm病灶的灵敏度为90%,特异度为80%,准确度为0.70。结论:T/N=3.5为界值时,对于肺部病灶及肺及最大横径小于3 cm病灶良恶性的鉴别能力较好。T/L比值对于肺部良恶性病灶和肺及纵膈最大横径小于3 cm的病灶诊断价值均高于传统常用的T/N比值,具有较高的准确性,可以良好的应用于18F-FDG符合线路SPECT/CT显像对肺癌的诊断中。     

CT引导下经皮肺穿刺并发症的高危因素分析

目的:探讨CT引导下经皮肤肺穿刺并发症发生的高危因素.方法:回顾分析93例因肺部肿块行CT引导下经皮肤肺穿刺患者,对其性别、吸烟史、病灶大小、肿块类型、组织学分型、穿刺时体位、进针位置、进针角度和进针深度等因素与穿刺后并发症的相关性进行分析.结果:单因素分析显示吸烟史、病灶大小、肿块类型和进针深度在有并发症患者和无并发症的患者之间存在显著性差异(P＜0.05),多因素分析显示病灶大小、肿块类型和进针深度在两组患者间存在显著性差异(P＜0.05).结论:病灶大小、肿块类型和进针深度为CT引导下经皮肺穿刺并发症出现的高危因素.     

超声引导经皮肺肿块穿刺活检在临床诊断中的应用

应用超声引导经皮自动穿刺活检术对79例经X线及CT检查发现肺部肿块患者进行穿刺活检,分析患者穿刺活检二维声像图特征,彩色血流信息特征,病灶内造影剂增强情况,穿刺活检成功率及并发症情况,探讨超声引导经皮肺肿块穿刺活检在肺肿块病变临床诊断中的应用价值。结果发现:实验组79例患者中,周围型肿块73例,中央型肿块伴肺实变6例,恶性病变60例,良性病变19例。恶性病变病灶回声类型、病灶最大径线、Adler血量分级、病灶内造影剂均匀性与良性病变同类指标比较具有显著差异性(p0.05)。可见:超声引导经皮肺肿块穿刺活检是安全可靠,简便易行的方法,其良、恶性病变二维声像图特征,彩色血流信息特征,病灶内造影剂增强情况差异显著,在肺周围型肿块及伴实变中央型肿块患者的病理分型诊断中具有重要的应用价值。     

MRI与CT检查对老年多发性脑梗死患者诊断价值、预后及满意度的影响

摘要 目的：分析磁共振（MRI）与计算机断层扫描（CT）检查对老年多发性脑梗死患者诊断价值、预后及满意度的影响。方法：选择2017年1月至2019年2月我院收治的老年多发性脑梗死患者141例,其中接受MRI检查的患者68例作为MRI组,接受CT检查的患者73例作为CT组,比较两组患者多发性脑梗死的检出情况、检出的病灶数量、病灶大小及检查所需时间,并比较患者预后情况及检查满意率。结果：MRI组发病<24 h检出率、总检出率高于CT组（P＜0.05）。MRI组检出的病灶数量显著高于CT组,病灶显著小于CT组,检查所需时间显著短于CT组（P＜0.05）。MRI组患者病残率及死亡率均低于CT组（P＜0.05）。MRI组患者总满意率显著高于CT组（P＜0.05）。结论：与CT相比,MRI对老年多发性脑梗死诊断价值更高,检出的病灶数量更多,有利于降低患者病残率和死亡率,且患者满意度更高。     

超声引导下18针与20针穿刺活检对甲状腺结节的诊断效果比较

摘要 目的：比较超声引导下18针与20针穿刺活检对甲状腺结节的诊断效果。方法：选取我院超声科2018.8.6-2020.9.30共收治的167例甲状腺结节患者作为研究对象,将患者分为18针穿刺组（n=86）和20针穿刺组（n=81）,分别对两组患者应用超声引导下18针和20针穿刺活检,比较不确定结果的发生率,包括非诊断性或异型性/滤泡性病变的未确定显著性,恶性肿瘤的诊断性能在最终诊断的结节中进行评估。比较两组并发症发生率及超声引导下的核心针穿刺活检标本产率。结果：对比20针穿刺组和18针穿刺组患者的临床特征发现,两组患者性别、年龄、结节大小、结节形状、方位、回声强度、表现和钙化情况对比无明显差异（P＜0.05）;在20针穿刺组中43个结节和18针穿刺组中46个结节最终确诊。恶性结节的比例在两组之间没有显著差异。在最终诊断分析中,20针穿刺组有38个结节,18针穿刺组中有40个结节。在20针穿刺组,38个结节包括6个非诊断结果、18个不典型/滤泡性病变（未确定显著性）和14个滤泡性肿瘤。在18针穿刺组中,40个结节包括1个非诊断结果,22个不典型/滤泡性病变未确定的显著性,17个滤泡性肿瘤;18针穿刺组的未确诊率（包括非诊断结果和未发现显著性的异型性/滤泡性病变）较低（29.1 % vs 37.0 %）,尽管这一差异在统计学上没有显著性（P＞0.05）。然而,18针穿刺组的非诊断性结果发生率（1.2 % vs 8.6 %;P＜0.05）显著低于20针穿刺组。两组的不典型/滤泡性病变的发生率（27.8 % vs 28.4 %）相似。20针穿刺组的CNB显示出更高的敏感性（75.0 % vs 66.7 %）,更高的阴性预测值（NPV;83.9 % vs 75.9 %）和更高的准确率（78.3 % vs 74.4 %）,虽然结果没有达到统计显著性。两组的特异性（81.8 % vs 80.8 %）和阳性预测值（PPV;两者均为100 %）相似;18针穿刺组和20针穿刺组患者的并发症发生率对比无明显差异（P＞0.05）。结论：18针芯针活检对甲状腺结节的诊断较20针更有效,且不增加并发症情况,安全性好,值得临床应用推广。     

99mTc标记BmK CT及其胶质瘤荷瘤裸鼠的SPECT成像研究

目的:通过放射性核素~(99m)Tc标记BmK CT多肽制备靶向胶质瘤的显像剂,探讨~(99m)?Tc-BmK CT用于胶质瘤显像的可行性。方法:采用BmK CT多肽游离的氨基与DTPA酸酐反应得到BmK CT-DTPA,经99m Tc标记后通过柱层析分离纯化制备~(99m)?Tc-BmK CT。测定标记物在PBS溶液和血清中不同时间点放射性化学纯度,评价BmK CT-~(99m)?Tc体外稳定性。新西兰白兔耳缘静脉注射~(99m)Tc-BmK CT进行SPECT显像,观察不同时间点体内的放射性分布。皮下胶质瘤裸鼠经尾静脉注射~(99m)Tc-BmK CT,观察不同时间点肿瘤的摄取情况;注射后4 h处死裸鼠,分离肿瘤和主要器官进行离体SPECT显像,并用勾画感兴趣区法分析相对放射性计数。结果:~(99m)Tc标记BmK CT多肽标记率大于80%,经柱层析分离纯化后放射性化学纯度大于99%。标记物在PBS和血清稳定性良好,6 h内放射性化学纯度均大于95%,12 h内放射性化学纯度大于90%。正常白兔SPECT显像表明~(99m)Tc-BmK CT主要浓聚在肝脏、脾脏和肾脏,软组织持续显影微弱,甲状腺区及胃肠未见核素浓聚;显像剂主要通过泌尿系统排泄,24 h肾脏与肝脏显影接近。胶质瘤裸鼠SPECT显像表明,注射后4 h肿瘤显像清楚,ROI分析结果显示肿瘤/肌肉比4.26±0.25,标记物在肿瘤内代谢缓慢,8 h肿瘤部位仍有较高摄取。结论:本研究成功制备了~(99m)Tc标记BmK CT多肽,标记物主要被肝、脾和肾摄取,经泌尿系统排泄;~(99m)Tc-BmK CT能够在皮下胶质瘤中浓聚,注射后4 h肿瘤显影清晰,瘤内代谢缓慢,有潜力成为一种新型胶质瘤分子探针。     

Intérêt de la scintigraphie pulmonaire de perfusion dans les dilatations des bronches de l’enfant

IntroductionBronchiectasis is a chronic disease of the lungs by repeated respiratory infection. An early and adequate diagnosis and management reduce the morbidity and mortality of this disease. The aim of this study is to emphasize the importance of the combination of Computer Tomography (CT) and lung perfusion scan (SPP) in the diagnosis and therapeutic approach.Materials and methodsForty-three children were referred in the nuclear medicine department with a clinical diagnosis of bronchiectasis; they underwent a CT and a SPP.Results and conclusionBy analyzing the results of the SPP and CT separately, we conclude that there is no significant difference between the two investigations. The combination of the two explorations provides a gain in most surgical therapeutic orientation.     

7例肺类癌的CT影像报道及文献复习

目的:分析肺类癌的CT影像表现,结合文献复习以提高对该病的认识。方法:回顾性分析7例经病理证实的肺类癌的CT表现,其中3例行胸部CT平扫检查,4例行胸部CT平扫及增强扫描。结果:7例患者中有6例为典型类癌,1例为非典型类癌。6例典型类癌中:1例为微瘤型类癌,表现为右侧肺门旁支气管扩张、结石及条片状影;1例为硬化性血管瘤合并类癌,表现为右侧肺门旁肿块,边缘较光整,伴晕征;2例为右侧肺门旁肿块,边缘光整,明显强化,伴有邻近支气管扩张或支气管粘液嵌塞、远端伴阻塞性肺不张或肺炎改变;2例表现为肺内孤立小结节,边缘光整,无强化。1例非典型类癌表现为不均匀强化的右肺门旁肿块,伴右肺门、纵隔淋巴结转移。结论:肺类癌的CT影像表现多样,典型病例的CT表现具有一定的特征性。     

高分辨率CT与常规CT检查对肺小结节及早期肺癌诊断价值的对比研究

目的:对比高分辨率电子计算机断层扫描(CT)与常规CT检查对肺小结节及早期肺癌的诊断价值。方法:将2018年6月2020年1月我院收治的肺小结节及早期肺癌患者94例纳入研究。以随机数字表法将其分为观察组及对照组,每组各47例,对照组实施常规CT检查,观察组则实施高分辨率CT检查。比较两组CT肿瘤征象情况(主要包括毛刺征、分叶征、棘突征、钙化征、空泡征、支气管征、胸膜凹陷征、血管集束征),CT扫描图像质量,诊断肺小结节及早期肺癌的效能。结果:观察组各项CT肿瘤征象人数占比均高于对照组(P<0.05)。观察组CT扫描图像质量优良率为97.87%(46/47),高于对照组的72.34%(34/47)(P<0.05)。高分辨率CT诊断早期肺癌的灵敏度及准确度、特异度分别为96.67%(29/30)、95.74%(45/47)、94.12%(16/17),高于常规CT检查的74.19%(23/31)、74.47%(35/47)、75.00%(12/16)。结论:高分辨率CT检查对肺小结节及早期肺癌诊断价值显著高于常规CT检查,可作为临床肺小结节及早期肺癌诊断的有效影像学手段,值得临床应用。     

Deep learning for predicting subtype classification and survival of lung adenocarcinoma on computed tomography

ObjectivesThe subtype classification of lung adenocarcinoma is important for treatment decision. This study aimed to investigate the deep learning and radiomics networks for predicting histologic subtype classification and survival of lung adenocarcinoma diagnosed through computed tomography (CT) images.MethodsA dataset of 1222 patients with lung adenocarcinoma were retrospectively enrolled from three medical institutions. The anonymised preoperative CT images and pathological labels of atypical adenomatous hyperplasia, adenocarcinoma in situ, minimally invasive adenocarcinoma, invasive adenocarcinoma (IAC) with five predominant components were obtained. These pathological labels were divided into 2-category classification (IAC; non-IAC), 3-category and 8-category. We modeled the classification task of histological subtypes based on modified ResNet-34 deep learning network, radiomics strategies and deep radiomics combined algorithm. Then we established the prognostic models in lung adenocarcinoma patients with survival outcomes. The accuracy (ACC), area under ROC curves (AUCs) and C-index were primarily performed to evaluate the algorithms.ResultsThis study included a training set (n = 802) and two validation cohorts (internal, n = 196; external, n = 224). The ACC of deep radiomics algorithm in internal validation achieved 0.8776, 0.8061 in the 2-category, 3-category classification, respectively. Even in 8 classifications, the AUC ranged from 0.739 to 0.940 in internal set. Further, we constructed a prognosis model that C-index was 0.892(95% CI: 0.846–0.937) in internal validation set.ConclusionsThe automated deep radiomics based triage system has achieved the great performance in the subtype classification and survival predictability in patients with CT-detected lung adenocarcinoma nodules, providing the clinical guide for treatment strategies.     

Identification of pathological subtypes of early lung adenocarcinoma based on artificial intelligence parameters and CT signs

Objective: To explore the value of quantitative parameters of artificial intelligence (AI) and computed tomography (CT) signs in identifying pathological subtypes of lung adenocarcinoma appearing as ground-glass nodules (GGNs). Methods: CT images of 224 GGNs from 210 individuals were collected retrospectively and classified into atypical adenomatous hyperplasia (AAH)/adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA), and invasive adenocarcinoma (IAC) groups. AI was used to identify GGNs and to obtain quantitative parameters, and CT signs were recognized manually. The mixed predictive model based on logistic multivariate regression was built and evaluated. Results: Of the 224 GGNs, 55, 93, and 76 were AAH/AIS, MIA, and IAC, respectively. In terms of AI parameters, from AAH/AIS to MIA, and IAC, there was a gradual increase in two-dimensional mean diameter, three-dimensional mean diameter, mean CT value, maximum CT value, and volume of GGNs (all P<0.0001). Except for the CT signs of the location, and the tumor–lung interface, there were significant differences among the three groups in the density, shape, vacuolar signs, air bronchogram, lobulation, spiculation, pleural indentation, and vascular convergence signs (all P<0.05). The areas under the curve (AUC) of predictive model 1 for identifying the AAH/AIS and MIA and model 2 for identifying MIA and IAC were 0.779 and 0.918, respectively, which were greater than the quantitative parameters independently (all P<0.05). Conclusion: AI parameters are valuable for identifying subtypes of early lung adenocarcinoma and have improved diagnostic efficacy when combined with CT signs.     

Assessment of regional non-linear tissue deformation and air volume change of human lungs via image registration

We evaluate the non-linear characteristics of the human lung via image registration-derived local variables based on volumetric multi-detector-row computed tomographic (MDCT) lung image data of six normal human subjects acquired at three inflation levels: 20% of vital capacity (VC), 60% VC and 80% VC. Local variables include Jacobian (ratio of volume change) and maximum shear strain for assessment of lung deformation, and air volume change for assessment of air distribution. First, the variables linearly interpolated between 20% and 80% VC images to reflect deformation from 20% to 60% VC are compared with those of direct registration of 20% and 60% VC images. The result shows that the linearly-interpolated variables agree only qualitatively with those of registration (P<0.05). Then, a quadratic (or linear) interpolation is introduced to link local variables to global air volumes of three images (or 20% and 80% VC images). A sinusoidal breathing waveform is assumed for assessing the time rate of change of these variables. The results show significant differences between two-image and three-image results (P<0.05). The three-image results for the whole lung indicate that the peak of the maximum shear rate occurs at about 37% of the maximum volume difference between 20% and 80% VC, while the peaks for the Jacobian and flow rate occur at 50%. This is in agreement with accepted physiology whereby lung tissues deform more at lower lung volumes due to lower elasticity and greater compliance. Furthermore, the three-image results show that the upper and middle lobes, even in the recumbent, supine posture, reach full expansion earlier than the lower lobes.     

Dose warping performance in deformable image registration in lung

PurposeIt is unclear that spatial accuracy can reflect the impact of deformed dose distribution. In this study, we used dosimetric parameters to compare an in-house deformable image registration (DIR) system using NiftyReg, with two commercially available systems, MIM Maestro (MIM) and Velocity AI (Velocity).MethodsFor 19 non-small-cell lung cancer patients, the peak inspiration (0%)-4DCT images were deformed to the peak expiration (50%)-4DCT images using each of the three DIR systems, which included computation of the deformation vector fields (DVF). The 0%-gross tumor volume (GTV) and the 0%-dose distribution were also then deformed using the DVFs. The agreement in the dose distributions for the GTVs was evaluated using generalized equivalent uniform dose (gEUD), mean dose (D_mean), and three-dimensional (3D) gamma index (criteria: 3 mm/3%). Additionally, a Dice similarity coefficient (DSC) was used to measure the similarity of the GTV volumes.ResultsD_mean and gEUD demonstrated good agreement between the original and deformed dose distributions (differences were generally less than 3%) in 17 of the patients. In two other patients, the Velocity system resulted in differences in gEUD of 50.1% and 29.7% and in D_mean of 11.8% and 4.78%. The gamma index comparison showed statistically significant differences for the in-house DIR vs. MIM, and MIM vs. Velocity.ConclusionsThe finely tuned in-house DIR system could achieve similar spatial and dose accuracy to the commercial systems. Care must be taken, as we found errors of more than 5% for D_mean and 30% for gEUD, even with a commercially available DIR tool.