Radiomic features from computed tomography to differentiate invasive pulmonary adenocarcinomas from non-invasive pulmonary adenocarcinomas appearing as part-solid groundglass nodules

Objective:We aim to investigate radiomic imaging features extracted in computed tomography(CT)images to differentiate invasive pulmonary adenocarcinomas(IPAs)from non-IPAs appearing as part-solid ground-glass nodules(GGNs),and to incorporate significant radiomic features with other clinically-assessed features to develop a diagnostic nomogram model for IPAs.Methods:This retrospective study was performed,with Institutional Review Board approval,on 88 patients with a total of 100 part-solid nodules(56 IPAs and 44 non-IPAs)that were surgically confirmed between February 2014and November 2016 in the First Affiliated Hospital of China Medical University.Quantitative radiomic features were computed automatically on 3D nodule volume segmented from arterial-phase contrast-enhanced CT images.A set of regular risk factors and visually-assessed qualitative CT imaging features were compared with the radiomic features using logistic regression analysis.Three diagnostic models,i.e.,a basis model using the clinical factors and qualitative CT features,a radiomics model using significant radiomic features,and a nomogram model combining all significant features,were built and compared in terms of receiver operating characteristic(ROC)curves.Decision curve analysis was performed for the nomogram model to explore its potential clinical benefit.Results:In addition to three visually-assessed qualitative imaging features,another three quantitative features selected from hundreds of radiomic features were found to be significantly(all P<0.05)associated with IPAs.The diagnostic nomogram model showed a significantly higher performance[area under the ROC curve(AUC)=0.903]in differentiating IPAs from non-IPAs than either the basis model(AUC=0.853,P=0.0009)or the radiomics model(AUC=0.769,P<0.0001).Decision curve analysis indicates a potential benefit of using such a nomogram model in clinical diagnosis.Conclusions:Quantitative radiomic features provide additional information over clinically-assessed qualitative features for differentiating IPAs from non-IPAs appearing as GGNs,and a diagnostic nomogram model including all these significant features may be clinically useful in preoperative strategy planning.

Role of positron emission tomography-computed tomography in non-small cell lung cancer

Lung cancer is the leading cause of cancer-related mortality worldwide. Non-small cell carcinoma and small cell carcinoma are the main histological subtypes and constitutes around 85% and 15% of all lung cancer respectively. Multimodality treatment plays a key role in the successful management of lung cancer depending upon the histological subtype, stage of disease, and performance status. Imaging modalities play an important role in the diagnosis and accurate staging of the disease, in assessing the response to neoadjuvant therapy, and in the follow-up of the patients. Last decade has witnessed voluminous upsurge in the use of positron emission tomography-computed tomography(PET-CT); role of PET-CT has widened exponentially in the management of lung cancer. The present article reviews the role of 18-fluoro-deoxyglucose PET-CT in the management of non small cell lung cancer with emphasis on staging of the disease and the assessment of response to neoadjuvant therapy based on available literature.

A correlation of computed tomography perfusion and histopathology in tumor edges of hepatocellular carcinoma

BACKGROUND： The peripheral morphologic characteristics of hepatocellular carcinoma （HCC） reflect tumor growth patterns. Computed tomography （CT） perfusion is a new method to analyze hemodynamic changes in tissues. We assessed the relationship between CT perfusion and histopathologic findings in the periphery of HCC lesions. METHODS： Non-contrast CT, enhanced dual-phase CT, and CT perfusion were performed on 77 subjects （47 patients and 30 controls）. Based on the imaging findings of enhanced dual- phase CT, the tumor edges were classified into three types： type Ⅰ （sharp）; type Ⅱ （blurry）; and type Ⅲ （mixed）. The CT perfusion parameters included hepatic blood flow, hepatic arterial fraction, hepatic arterial perfusion, and hepatic portal perfusion. The tissue sections from resected specimens were subjected to routine hematoxylin and eosin staining and immunohistochemical staining for CD34. The correlations between microvessel density （MVD） and the CT perfusion parameters were analyzed using Pearson＇s product-moment correlation coefficient. Changes in the perfusion parameters in tumor edges of different tumor types were evaluated. RESULTS： Type Ⅰ （sharp）： the pathologic findings showed fibrous connective tissue capsules in the tumor edges, and an MVD 〈30/ram2. Type Ⅱ （blurry）： the histology showed that the edges were clear with no capsules and an MVD 〉30/ram2. Type Ⅲ （mixed）： the pathology was similar to that of types I and II, and an MVD 〉30/mm~. Hepatic blood flow, hepatic arterial fraction, hepatic arterial perfusion, and hepatic portal perfusion were significantly increased in the tumor edges of HCC patients compared to those of the controls （P〈0.05）. The correlation between CT perfusion parameters and MVD was higher in blurry tumor edges of type II than in those of types Ⅰ or Ⅲ. CONCLUSION： CT perfusion imaging of tumor edges may be helpful in revealing histopathological features, and indirectly reflect angiogenic changes of HCCs.

Can visceral fat parameters based on computed tomography be used to predict occult peritoneal metastasis in gastric cancer?

BACKGROUND The preoperative prediction of peritoneal metastasis(PM)in gastric cancer would prevent unnecessary surgery and promptly indicate an appropriate treatment plan.AIM To explore the predictive value of visceral fat(VF)parameters obtained from preoperative computed tomography(CT)images for occult PM and to develop an individualized model for predicting occult PM in patients with gastric carcinoma(GC).METHODS A total of 128 confirmed GC cases(84 male and 44 female patients)that underwent CT scans were analyzed and categorized into PM-positive(n=43)and PM-negative(n=85)groups.The clinical characteristics and VF parameters of two regions of interest(ROIs)were collected.Univariate and stratified analyses based on VF volume were performed to screen for predictive characteristics for occult PM.Prediction models with and without VF parameters were established by multivariable logistic regression analysis.RESULTS The mean attenuations of VF_(ROI 1)and VF_(ROI 2)varied significantly between the PM-positive and PMnegative groups(P=0.044 and 0.001,respectively).The areas under the receiver operating characteristic curves(AUCs)of VF_(ROI 1)and VF_(ROI 2)were 0.599 and 0.657,respectively.The mean attenuation of VF_(ROI 2)was included in the final prediction combined model,but not an independent risk factor of PM(P=0.068).No significant difference was observed between the models with and without mean attenuation of VF(AUC:0.749 vs 0.730,P=0.339).CONCLUSION The mean attenuation of VF is a potential auxiliary parameter for predicting occult PM in patients with GC.

Role of positron emission tomography in primary carcinoma ex pleomorphic adenoma of the bronchus: A case report

BACKGROUND Primary carcinoma ex pleomorphic adenoma arising from the tracheobronchial system is rarely reported.CASE SUMMARY We present a patient with primary carcinoma ex pleomorphic adenoma of the bronchus and review the associated literature for further comparison,including age,clinical manifestations,and diagnostic process.This patient had no history of neoplasms of the salivary gland.CONCLUSION Positron emission tomography played an important role in the staging work-up of primary carcinoma of ex pleomorphic adenoma.Long-term follow-up was necessary for further prognosis analysis.

The ^(18)F-FDG uptake in non small cell lung carcinoma correlates with the DNA-grading of malignancy

In order to evaluate correlation of glucose metabolism and DNA ploidity of tumors, the uptake of 18F-Deoxyglucose (FDG) by PET prior to surgery and the DNA cotent and DNA-grading of malignancy (DNA-MG) of Schiff-stained nuclei obtained from fresh tumor fragments by means of image cytometry were studied, and thereafter the correlation between standardized uptake value (SUV) and (DNA-MG) was analysed in forty-nine patients with histologically proven non-small cell lung carcinoma (NSCLC). As a result of the DNA histograms of these 49 patients, 46 (93.88%) were aneuploid and only 3(6.12%) were tetraploid. A linear correlation of the SUV versus the (DNA-MG) (r=0.336, p=0.024) was found, demonstrating that 18F-FDG PET as a non-invasive metabolic imaging technique, may also provide inforrnation correlated to malignant DNA patterns which may be valuable in malignant differentiation and prognostic prediction.

Application of computed tomography-based radiomics in differential diagnosis of adenocarcinoma and squamous cell carcinoma at the esophagogastric junction

BACKGROUND The biological behavior of carcinoma of the esophagogastric junction(CEGJ)is different from that of gastric or esophageal cancer.Differentiating squamous cell carcinoma of the esophagogastric junction(SCCEG)from adenocarcinoma of the esophagogastric junction(AEG)can indicate Siewert stage and whether the surgical route for patients with CEGJ is transthoracic or transabdominal,as well as aid in determining the extent of lymph node dissection.With the development of neoadjuvant therapy,preoperative determination of pathological type can help in the selection of neoadjuvant radiotherapy and chemotherapy regimens.AIM To establish and evaluate computed tomography(CT)-based multiscale and multiphase radiomics models to distinguish SCCEG and AEG preoperatively.METHODS We retrospectively analyzed the preoperative contrasted-enhanced CT imaging data of single-center patients with pathologically confirmed SCCEG(n=130)and AEG(n=130).The data were divided into either a training(n=182)or a test group(n=78)at a ratio of 7:3.A total of 1409 radiomics features were separately extracted from two dimensional(2D)or three dimensional(3D)regions of interest in arterial and venous phases.Intra-/inter-observer consistency analysis,correlation analysis,univariate analysis,least absolute shrinkage and selection operator regression,and backward stepwise logical regression were applied for feature selection.Totally,six logistic regression models were established based on 2D and 3D multi-phase features.The receiver operating characteristic curve analysis,the continuous net reclassification improvement(NRI),and the integrated discrimination improvement(IDI)were used for assessing model discrimination performance.Calibration and decision curves were used to assess the calibration and clinical usefulness of the model,respectively.RESULTS The 2D-venous model(5 features,AUC:0.849)performed better than 2D-arterial(5 features,AUC:0.808).The 2D-arterial-venous combined model could further enhance the performance(AUC:0.869).The 3D-venous model(7 features,AUC:0.877)performed better than 3D-arterial(10 features,AUC:0.876).And the 3D-arterial-venous combined model(AUC:0.904)outperformed other single-phase-based models.The venous model showed a positive improvement compared with the arterial model(NRI>0,IDI>0),and the 3D-venous and combined models showed a significant positive improvement compared with the 2D-venous and combined models(P<0.05).Decision curve analysis showed that combined 3D-arterial-venous model and 3D-venous model had a higher net clinical benefit within the same threshold probability range in the test group.CONCLUSION The combined arterial-venous CT radiomics model based on 3D segmentation can improve the performance in differentiating EGJ squamous cell carcinoma from adenocarcinoma.

Lung squamous cell carcinoma presenting as rare clustered cystic lesions:A case report and review of literature

BACKGROUND Lung cancer is the leading cause of cancer-related death.Early diagnosis is critical to improving a patient’s chance of survival.However,lung cancer associated with cystic airspaces is often misdiagnosed or underdiagnosed due to the absence of clinical symptoms,poor imaging specificity,and high risk of biopsy-related complications.CASE SUMMARY We report an unusual case of cancer in a 55-year-old man,in which the lesion evolved from a small solitary thin-walled cyst to lung squamous cell carcinoma(SCC)with metastases in both lungs.The SCC manifested as rare clustered cystic lesions,detected on chest computed tomography.There were air-fluid levels,compartments,and bronchial arteries in the cystic lesions.Additionally,there was no clear extrathoracic metastasis.After chemotherapy,the patient achieved a partial response,type I respiratory failure was relieved,and the lung lesions became a clustered thin-walled cyst.CONCLUSION Pulmonary cystic lesions require regular imaging follow-up.Lung SCC should be a diagnostic consideration in cases of thin-walled cysts as well as multiple clustered cystic lesions.

能谱CT定量参数联合动脉期碘基图影像组学特征在肺鳞癌与肺腺癌鉴别诊断中的价值

目的基于能谱电子计算机断层扫描(computed tomography,CT)定量参数联合动脉期碘基图影像组学特征构建诺模图模型,探讨能谱CT在肺鳞癌(lung squamous cell carcinoma,LUSC)与肺腺癌(lung adenocarcinoma,LUAD)鉴别诊断中的临床应用价值。方法收集术前行能谱CT增强检查、经病理活检或手术证实的肺癌患者89例,其中LUAD组38例,LUSC组51例。分析LUAD组和LUSC组患者在60keV动脉期单能量图像中病灶水浓度、碘浓度(iodine concentration,IC)、标准化碘浓度(normalizediodineconcentration,NIC)、CT值、能谱曲线斜率(K)、有效原子序数(effective-Z,Eff-Z)及标准化有效原子序数(normalized effective-Z,NEff-Z)。采用Logistic回归分析构建LUAD和LUSC基于能谱CT特征的鉴别诊断模型。应用ITKSnap软件提取动脉期碘基图影像组学特征;采用组内相关系数(intraclass correlation coemcient,ICC)、递归特征消除(recursive featureelimination,RFE)和最小绝对收缩和选择算子(least absolute shrinkage and selection operator,LASSO)对影像组学特征进行降维、筛选,采用Logistic回归构建基于影像组学特征的诊断模型,并计算该模型的影像组学评分(radiomics score,Rad-score),以多因素Logistic回归分析筛选出的能谱CT定量参数与Rad-score构建联合模型,并绘制诺模图。应用受试者工作特征(receiveroperatingcharacteristic,ROC)曲线、Delong检验、校正曲线、Hosmer-Lemeshow检验及临床决策曲线(decision curve analysis,DCA)对能谱CT模型、影像组学模型和诺莫图模型进行效能评价。结果LUAD组和LUSC组患者IC、NIC、CT值、K及NEff-Z比较差异均有统计学意义(P均<0.05)。多因素Logistic回归分析结果显示,IC、NIC及NEff-Z为独立影响因素,基于此构建能谱CT模型预测LUAD和LUSC的效能曲线下面积(areaunderthecurve,AUC)为0.768,准确率、灵敏度、特异度分别为70.73%、76.92%和67.86%;影像组学特征经降维后共筛选出的有意义特征有5个,一阶特征2个、二阶特征2个和形状特征1个,影像组学模型预测LUAD和LUSC的效能AUC为0.848,准确率、灵敏度、特异度分别为80.50%、83.33%和75.00%;诺莫图模型预测LUAD和LUSC的效能AUC为0.912,准确率、灵敏度、特异度分别为85.00%、92.31%和85.71%。经Delong检验显示,诺莫图模型AUC均明显高于影像组学模型和能谱CT模型(P均<0.05)。Hosmer-Lemeshow检验结果显示,能谱CT模型、影像组学模型及诺莫图模型的拟合度均良好(χ^(2)值分别为8.592、6.591、6.686,P值分别为0.378、0.581、0.570)。校准曲线分析显示,诺莫图模型预测LUAD和LUSC的预测概率曲线与理想曲线更接近,优于影像组学模型和能谱CT模型;DCA分析结果显示,诺莫图模型的AUC最大,均高于影像组学模型和能谱CT模型,临床净收益更高。结论基于能谱CT定量参数联合动脉期碘基图影像组学特征构建的诺模图模型在LUSC与LUAD鉴别诊断中具有潜在应用价值。

肺鳞癌误诊为肺脓肿的CT影像学表现

目的 分析肺鳞癌误诊为肺脓肿的计算机断层扫描(CT)影像学特征,以提高对肺鳞癌的认识及诊断正确率。方法 选择2017年12月至2022年12月于河南科技大学第一附属医院收治的112例曾经误诊为肺脓肿的肺鳞癌患者和同期确诊为肺脓肿的80例患者作为研究对象,前者为肺鳞癌组,后者为肺脓肿组,均接受CT平扫和增强扫描。比较两组患者的临床表现、病程和CT下病变主体及周围病灶的影像学特征。结果 肺鳞癌组患者病程长于肺脓肿组(P<0.05),肺鳞癌组CT表现为空洞伴液平患者占比低于肺脓肿组(P<0.05),空洞壁厚>15 mm患者占比高于肺脓肿组(P<0.05);肺鳞癌组CT病灶周围形态表现为边缘模糊患者占比低于肺脓肿组(P<0.05)。抗感染后,肺鳞癌组病灶缩小的患者占比低于肺脓肿组(P<0.05),病灶无变化的患者占比高于肺脓肿组(P<0.05)。两组临床表现差异无统计学意义(P>0.05)。结论 相比于肺脓肿,肺鳞癌患者CT下较少出现空洞伴液平、病灶边缘模糊特征,多表现为空洞壁厚>15 mm、抗感染后病灶无变化,这些CT影像学特征对于肺鳞癌和肺脓肿的鉴别诊断具有重要意义。

术前CT在诊断非小细胞肺癌脏层胸膜浸润中的应用价值

目的:探讨术前CT在诊断非小细胞肺癌(NSCLC)脏层胸膜浸润(VPI)中的应用价值。方法:回顾性纳入489例经手术病理证实的NSCLC患者的资料,按收集时间分为训练集362例和验证集127例,2个数据集根据弹力纤维染色结果各分为VPI组和无VPI组。训练集中,VPI组57例,无VPI组305例;验证集中,VPI组15例,无VPI组112例。总结VPI组和无VPI组病理特征、临床资料及CT征象,通过单因素分析和二元logistic回归分析,筛选出VPI的独立风险因素并构建联合模型;采用ROC曲线比较各模型的诊断效能。结果:在训练集中,VPI组与无VPI组在结节类型、空气支气管征、胸膜接触类型、实性接触长度、长径、短径、最小CT值(CT_(min)值)和平均CT值(CT_(mean)值)之间差异均有统计学意义(均P<0.05)。经多因素logistic回归分析剔除混杂因素,筛选出实性接触长度和胸膜接触类型为鉴别VPI的独立风险因素(均P<0.01),实性接触长度的最佳截断值为8.5 mm,敏感度为80.7%,特异度为55.4%。在训练集中,由单因素分析中差异有统计学意义的特征所建立的模型1、由2个独立风险因素建立的模型2和实性接触长度3种模型的AUC分别为0.775、0.755和0.734;在验证集中,模型1、模型2和实性接触长度3种模型的AUC分别为0.789、0.740和0.682。3种模型间在训练集及验证集中差异均无统计学意义(均P>0.05)。结论:实性接触长度和胸膜接触类型可作为鉴别VPI的独立风险因素,可为临床术前决策提供影像学依据。

基于PET/CT不同勾画方法测量非小细胞肺癌原发灶代谢体积的差异性研究

目的:探讨基于PET/CT不同勾画方法对非小细胞肺癌(NSCLC)代谢参数测量的影响及可重复性分析。方法:回顾性分析79例经病理确诊的NSCLC患者资料,测量原发灶最大标准化摄取值(SUVmax),采取自适应迭代算法(AIA)、固定阈值法(以2.5、3、4为阈值)及相对阈值法(以40%、50%为阈值)测量肿瘤代谢体积(MTV)及糖酵解总量(TLG),比较不同勾画方法所获代谢参数的差异,并分析2位医师测量一致性。结果:不同勾画方法所测MTV差异有统计学意义(χ^(2)=14.759,P=0.011),而TLG差异无统计学意义(χ^(2)=3.013,P=0.698)。对于固定阈值法和相对阈值法,阈值越高,测得的MTV和TLG越小,其中相对阈值法测得的MTV和TLG较小。不同勾画方法测得的SUVmax、MTV和TLG可重复性均非常高。2位医师测量的SUVmax、MTV及TLG的一致性均极强(均ICC>0.99)。不同勾画方法中相对阈值法(以40%为阈值)无需手动调整次数占比最大,为18.32%,其勾画准确率最高,为91.14%,差异有统计学意义(χ^(2)=11.748,P=0.038)。结论:不同勾画方法测得的MTV、TLG的重复性非常高,但测得的MTV之间存在差异,其中以40%为阈值的勾画方法无需手动调整的次数最多,勾画准确率为91.14%,建议在临床工作中使用。

瘤内与瘤周CT影像组学模型结合临床及常规CT特征鉴别肺原位腺癌与微浸润性腺癌

目的观察基于平扫CT瘤内及瘤周影像组学模型联合临床及常规CT特征鉴别肺原位腺癌(AIS)与微浸润性腺癌(MIA)的价值。方法回顾性分析180例孤立性AIS及180例孤立性MIA肺结节患者,随机将其中各160例纳入训练集(n=320)、各20例纳入测试集(n=40)。以训练集AIS与MIA间差异有统计学意义的临床及常规CT特征构建临床模型;勾画瘤内(CTi)及包含瘤周2 mm(CTi+p2mm)、4 mm(CTi+p4mm)ROI,提取并筛选其影像组学特征,分别以之构建CTi模型、CTi+p2mm模型及CTi+p4mm模型;绘制受试者工作特征(ROC)曲线,计算曲线下面积(AUC),评价各模型效能,遴选预测测试集MIA效能最佳者,联合临床及常规CT特征构建联合模型,观察临床模型、最佳影像组学模型及联合模型的AUC、校准度及净收益。结果训练集内,相比AIS,MIA结节直径较大、密度不均匀、伴血管穿行结节占比较高(P均<0.05)。CTi+p2mm模型鉴别测试集MIA与AIS效能最高(AUC=0.838,P<0.05);以之结合临床及常规CT特征构建的联合模型鉴别诊断效能更佳(AUC=0.867,P<0.05)。联合模型的校准度及0.60~0.90阈值概率区间的临床净收益较高。结论基于平扫CT构建的瘤内和瘤周2 mm ROI影像组学模型能有效鉴别肺MIA与AIS,联合临床及常规CT特征可进一步提高模型鉴别效能。

肺癌椎体转移瘤影像学特征与原发灶组织学的相关性研究

目的 探讨肺癌椎体转移瘤患者CT、MRI影像特征与原发灶组织学类型的关系。方法 回顾性分析2019年1月-2022年12月收治的103例肺癌椎体转移瘤临床资料,其中腺癌37例、鳞癌31例、小细胞癌19例、大细胞癌16例,分析CT、MRI特征与原发灶组织学类型的关系。结果 103例肺癌椎体转移瘤受累椎体以胸椎多见(65例,63.11%),37例(35.92%)单节段转移,23例(22.33%)双节段转移,43例(41.75%)多节段转移。原发灶不同组织学类型患者椎体转移瘤部位、受累节段、椎体骨折、椎管受累、椎旁肿物、常规MRI信号表现、增强MRI强化特点、椎间盘膨出、腰椎退行性病变情况比较差异无统计学意义(P>0.05);鳞癌骨质改变类型以混合型为主,腺癌骨质改变类型以溶骨型、成骨型为主,鳞癌与腺癌骨质改变类型比较差异有统计学意义(P<0.05);小细胞癌出现脊髓受压、其他脏器转移患者多于腺癌、鳞癌、大细胞癌(P<0.05);腺癌、鳞癌有胸腔积液患者多于小细胞癌、大细胞癌(P<0.05)。结论 骨质改变类型、脊髓受压、其他脏器转移、胸腔积液情况与肺癌椎体转移患者原发灶组织学类型有关,腺癌和鳞癌患者更易发生椎体转移,采用CT、MRI检查可相互弥补,准确识别以上特征,可为临床判断原发灶组织学类型、筛选肺癌椎体转移高风险人群等提供参考。

MSCT诊断原发性肺腺泡细胞癌临床案例分析

腺泡细胞癌(ACC)是一种涎腺上皮源性恶性肿瘤,主要发生于涎腺,而肺内原发腺泡细胞癌极其罕见。由于临床发病率非常低,相关文献报道少,临床医生对其认识不足,容易误诊而延误患者治疗。本文报道1例经手术病理证实的原发性肺腺泡细胞癌,并结合相关文献,总结本病的MSCT影像表现以及MSCT在本病诊疗中的价值,以提高对该病的认识和影像诊断水平。

CT纹理分析评估非小细胞肺癌ALK基因状态的价值

目的:探讨CT纹理分析对非小细胞肺癌(NSCLC)患者的间变性淋巴瘤激酶(ALK)基因状态的预测价值。方法:回顾性收集54例经病理证实的NSCLC患者,其中ALK基因变异者18例,未变异者36例。采用Omni-Kinetics软件对肺癌患者治疗前的增强CT图像进行纹理分析,比较纹理参数在ALK基因变异与未变异组间的差异。采用受试者工作特征(ROC)曲线评估纹理参数的预测效能。结果:ALK变异组中的Mean、Entropy、Grey Level Nonuniformity显著高于未变异组(P=0.003、0.021、0.030),Energy、Sphericity显著低于未变异组(P=0.002、0.030)。CT各纹理参数预测ALK基因状态的ROC曲线下面积(AUC)值在0.673~0.796,CT纹理参数联合后,其AUC值提高至0.853,灵敏度为0.711,特异度为0.972。结论:CT纹理分析可用于预测NSCLC患者的ALK基因突变状态,有望为ALK基因状态的诊断提供辅助信息。

非小细胞肺癌CT动态增强扫描定量参数与病理类型及靶向治疗远期预后的关系分析

目的:探讨非小细胞肺癌(NSCLC)CT动态增强扫描定量参数与病理类型及靶向治疗远期预后的关系。方法:回顾性分析116例NSCLC患者的临床资料。所有患者均予以作用于表皮生长因子受体(EGFR)的靶向药物治疗,于治疗前和治疗后1个月行CT动态增强扫描,获取定量参数[灌注值、强化峰值(PH)、肿块强化达到峰值时间(Tp)],并根据患者存活情况,分为死亡组(30例)和存活组(86例),分析灌注值、PH、Tp与病理类型及靶向治疗远期预后的关系。结果:治疗前,不同病理类型患者CT动态增强扫描定量参数比较,差异均无统计学意义(均P>0.05)。治疗后,灌注值、PH水平下降,Tp更大(均P<0.05)。治疗后,与死亡组比较,存活组灌注值、PH水平更低,Tp更大(P<0.05)。ROC曲线显示,灌注值预测NSCLC患者远期预后的AUC和截点值分别为0.822、0.19 mL·min^(-1)·mL^(-1),PH预测的AUC和截点值分别为0.780、57.61 HU,Tp预测的AUC和截点值分别为0.741、89.92 s;三者联合预测的AUC为0.960,高于单一参数预测(P<0.05)。结论:NSCLC患者CT动态增强扫描定量参数与病理类型无关,与靶向治疗远期预后密切相关。

Multiphase hepatic scans with multirow- detector helical CT in detection of hypervascular hepatocellular carcinoma

BACKGROUND: Multirow-detector helical CT (MDCT) allows faster Z-axis coverage and improves longitudinal re- solution to scan the entire liver. This study was to evaluate the value of multiphase hepatic CT scans using MDCT in diagnosing hypervascular hepatocellular carcinoma (HCC). METHODS: Multiphase hepatic CT scans in 40 patients were carried out with a Marconi Mx8000 MDCT scanner. The scans of early arterial phase (EAP), late arterial phase (LAP) and portal venous phase (PVP) were started at 21, 34 and 85 seconds after injection of contrast medium, re- spectively. The number of detected lesions was calculated in each phase. The density of the liver and tumor was great- er than 1 cm for HCC, and the density of the liver and tumor in each phase was statistically calculated. RESULTS: A total of 61 lesions were found in the 40 pa- tients , and lesions greater than 1 cm were seen in 47 cases. The density differences between the liver and tumor were statistically significant (P<0.05) at the LAP and EAP and between the LAP, EAP and PVP. In the 61 lesions, the de- tectability in the EAP, LAP and the double arterial phases (DAP) was 32%, 87%, and 94%, respectively. Significant difference was found between the LAP plus PVP and the EAP plus PVP; but no significant difference was observed between the DAP plus PVP and the LAP plus PVP. CONCLUSIONS: The utility of MDCT scan in the liver has optimized the protocol of arterial phase scan. MDCT is possible to scan the entire liver in a real arterial phase and it is very valuable in the detection of small HCC.

Correlation between Calcified Liver Metastases and Histopathology of Primary Colorectal Carcinoma in Chinese

The study examined the association between calcified liver metastases and the histopathology of the primary colorectal carcinoma in Chinese.The clinical,pathological and CT data were retrospectively analyzed in 210 patients (mean age:54.2 years) with liver metastases from colorectal carcinoma.Plain CT scanning and contrast-enhanced scanning were performed in all the patients.For the contrast-enhanced examination,iohexol was injected by using a high pressure syringe at a flow rate of 2.5-3.0 mL/s.The arterial phase lasted approximately 25 s and the portal venous phase about 60 s.All patients had no history of chronic liver diseases and had never received interventional treatments.χ 2-test was used to analyze the rate of calcification in the liver metastasis from colorectal cancer of different differentiation degrees.Among the 210 cases of liver metastases,22 patients (10.5%) were found to have calcified liver metastases on CT scan.Two patients with calcified liver metastasis received lumpectomy and developed calcification in recurrent tumors.Another two patients had calcification in newly developed tumor masses.And the calcification in the newly developed masses was similar to that of their primary counterparts in terms of morphology and distribution.On the enhanced CT scan,the tumors exhibited no enhancement during hepatic arterial phase and showed slight rim enhancement during portal venous scan in the 22 cases.The calcification became obscure on contrast-enhanced scans.Histopathologically,the primary tumors were well-differentiated adenocarcinoma in 6 cases,moderately-differentiated adenocarcinoma in 10,poorly-differentiated adenocarcinoma in 4 and mucinous adenocarcinoma in 2 among the 22 cases.No statistical correlation was noted between the incidence of calcified liver metastasis and the pathological subtypes and differentiation degrees of the primary colorectal carcinoma.It was concluded that calcified liver metastases may result from colorectal adenocarcinomata of different differentiation degrees or mucinous adenocarcinomata in Chinese population.There is no correlation between calcification of liver metastases and the pathological subtype of the primary colorectal carcinoma in Chinese,which is different from the findings that calcified metastases were associated with colorectal mucinous adenocarcinoma in other ethnic groups.

The diagnostic rules of peripheral lung cancer preliminary study based on data mining technique

Objective： To discuss the clinical and imaging diagnostic rules of peripheral lung cancer by data mining technique, and to explore new ideas in the diagnosis of peripheral lung cancer, and to obtain early-stage technology and knowledge support of computer-aided detecting （CAD）. Methods： 58 cases of peripheral lung cancer confirmed by clinical pathology were collected. The data were imported into the database after the standardization of the clinical and CT findings attributes were identified. The data was studied comparatively based on Association Rules （AR） of the knowledge discovery process and the Rough Set （RS） reduction algorithm and Genetic Algorithm（GA） of the generic data analysis tool （ROSETTA）, respectively. Results： The genetic classification algorithm of ROSETTA generates 5 000 or so diagnosis rules. The RS reduction algorithm of Johnson＇s Algorithm generates 51 diagnosis rules and the AR algorithm generates 123 diagnosis rules. Three data mining methods basically consider gender, age, cough, location, lobulation sign, shape, ground-glass density attributes as the main basis for the diagnosis of peripheral lung cancer. Conclusion： These diagnosis rules for peripheral lung cancer with three data mining technology is same as clinical diagnostic rules, and these rules also can be used to build the knowledge base of expert system. This study demonstrated the potential values of data mining technology in clinical imaging diagnosis and differential diagnosis.