腰椎椎弓崩裂CT征象的临床诊断价值

目的分析腰椎椎弓峡部裂的CT表现,探讨各个征象的诊断价值和意义.方法自可疑椎弓峡部裂脊椎的椎弓根的上缘至下一个椎弓根上缘,层厚2～3mm连续扫描.结果86例中发生L5椎弓峡部裂51例,L4者33例,L3,者2例.各种CT征象发现率为:环裂征91%,椎体前移征85%,双椎体征50%,椎管拉长征45%,双关节面征38%,葫芦征26%,游移征15%,磨旋征6%.结论环裂征是该病的特征性表现;双关节面征及葫芦征发现率较低,但特异性较高.椎管拉长征具有一定诊断价值,其它征象无论其发现率大小,均是该病的继发改变,不能作为确诊的直接依据.     

Philips Bucky DiagnostTS X线机的数字化改造

采用友通公司的方案，对PhilipsX线机进行了数字化改造，改造后的系统增加了数字化X线平板探测器、控制盒和DR影像工作站，使摄片更加方便快捷，为临床诊断提供了更高质量的图像。     

慢性中耳炎及其并发症的高分辨率CT表现

目的 分析慢性中耳炎及其并发症的高分辨率CT表现。方法 回顾性分析50例(60耳)慢性中耳炎患者的高分辨率CT表现,其中两例行MRI增强检查,并与手术所见及病理诊断对照。结果 鼓室腔内见软组织影52耳,听小骨受累51耳,鼓室、乳突内硬化斑形成14耳,面神经鼓室段受累5耳,迷路瘘1耳,骨化性迷路炎2耳。结论 高分辨率CT对诊断慢性中耳炎及其并发症以及指导临床治疗具有重要价值。     

翼管在内镜经鼻颅底手术中的标志作用

目的通过影像学和解剖学方法进行研究以明确翼管在鼻内镜经鼻颅底手术中的价值并为临床提供参考。方法选23具尸头行冠状位及轴位高分辨CT扫描,观察翼管及其与周围结构的关系,并测量相关距离。选其中3具经过动脉灌注的尸头,分别采用经上颌窦、经鼻至翼腭窝-海绵窦入路进行鼻内镜下的解剖学研究。结果高分辨CT能够清晰显示翼管形态、走行及其与周围结构的关系。所有翼管均位于颈内动脉管水平段或其以下层面。鼻内镜解剖与相应的影像学提示相同,翼管内容恒定地指向颈内动脉前膝;翼管和圆孔之间的距离标定了一个手术门户。结论翼管是内镜经鼻颅底手术的一个重要解剖标志,作为骨性管道,高分辨CT可以清晰显示翼管。     

乳腺癌分期诊断中SPECT—CT同机图像融合技术的探讨

目的将SPECT-CT同机图像融合技术，应用于^99mTc—MIBI乳腺癌亲肿瘤显像，探讨对乳腺癌术前TNM分期的临床价值。方法对10例怀疑已发生淋巴或血行转移的乳腺癌患者，完成^99mTc—MIBI乳腺癌亲肿瘤显像及SPECT-CT同机图像融合处理，并进行图像评价。以术后与活检的病理结果作为参照标准。结果19例乳腺癌中，1例浸润性导管癌检查呈假阴性；18例阳性病例中，发生腋窝淋巴结转移10例，腋窝淋巴结伴锁骨上淋巴结转移3例，胸骨旁淋巴结转移2例，漏检2例，未发生淋巴结转移1例；本组中有2例肿瘤侵犯乳腺后间隙，有3例发生胸壁转移。经SPECT--CT同机图像融合处理后，完成了对所有阳性病例淋巴结的分组，并对肿瘤侵犯深部胸肌及胸壁转移，提供定位诊断信息。结论SPECT--CT同机图像融合技术，应用于^99mTc—MIBI乳腺癌亲肿瘤显像，对乳腺癌的术前TNM分期具有一定的临床应用价值。     

高原地区首例新型冠状病毒肺炎CT诊断分析并文献复习

目的 回顾性分析高原地区首例新型冠状病毒肺炎的CT影像特征及临床表现,以提高对该病的认识.方法 回顾性分析高原地区1例确诊新型冠状病毒患者的CT影像及临床资料并进行文献复习.结果 患者患病过程中早期、进展期及转归期的CT表现较为典型,与内地文献报道无明显差异,但诊断时应与高原性病种相互鉴别.结论 新型冠状病毒肺炎的诊断...     

深度学习重建算法在腹部CT成像中应用的体模研究

目的 探讨不同辐射剂量下深度学习图像重建算法（DLIR）相对于常规迭代重建算法（ASIR-V）对腹部体模CT图像质量的改善价值。方法 根据管电压设置100 kV组与120 kV组,每组按照容积剂量指数（CTDI_vol）不同（2、4、6、8、10、15 mGy）分为6组进行常规扫描,获得基于滤波反投影（FBP）算法的CT图像,并使用不同权重迭代重建算法（ASIR-V 50%、80%、100%）及不同等级深度学习重建算法（DLIR-L、DLIR-M、DLIR-H）进行图像重建,共获得84组图像。对比分析不同重建方式下各CTDI_vol组图像各部位CT值、噪声、信噪比（SNR）、对比噪声比（CNR）及主观评分的变化规律。图像质量主观评分比较采用Kruskal-Wallis H检验,客观指标和辐射剂量比较采用单因素方差分析及配对样本t检验。结果 同一管电压下,各CTDI_vol组不同重建条件下各部位的噪声、SNR、CNR差异均有统计学意义（F=415.39、315.30,P<0.001）,且ASIR-V 50%与DLIR-L图像的噪声、SNR、CNR差异无统计学意义（P>0.05）;主观评分之间差异均有统计学意义（100 kV组：H=13.47,P=0.036;120 kV组：H=12.99,P=0.043）,且两名医师的主观评分一致性较高（Kappa>0.70）,其中DLIR-H图像质量评分最高,DLIR-M与ASIR-V 50%图像质量主观评分基本一致;100 kV组图像质量主观评分整体较120 kV略高。以CTDI_vol为15 mGy组ASIR-V 50%图像作为参照,在满足诊断需求的前提下,低中高等级的DLIR可以分别降低辐射剂量超过30%、70%、85%。结论 DLIR算法不仅能够显著降低图像噪声、提高图像质量,而且可以在满足诊断需求的前提下有效降低辐射剂量;推荐临床应用100 kV结合中、高等级DLIR行腹部低剂量CT扫描。     

Imaging update on soft tissue sarcoma

Soft tissue sarcomas (STS) are rare tumours presenting as soft tissue lumps. Ultrasound is often the primary modality for the initial assessment, with MRI the mainstay for lesion characterisation. PET/CT along with other emerging MRI sequences are used in certain situations as an adjunct and problem solving tool in STS staging and assessment of disease recurrence. Recent advances include the promise of whole body MRI, hybrid PET/MRI, diffusion weighted imaging, dynamic contrast enhanced MRI and advances in artificial intelligence. This article discusses current concepts in extremity STS imaging and highlights recent advances.     

Elaboración de modelos predictivos de la gravedad y la mortalidad en pacientes con COVID-19 que acuden al servicio de urgencias,incluida la radiografía torácica

ObjectivesTo develop prognosis prediction models for COVID-19 patients attending an emergency department (ED) based on initial chest X-ray (CXR), demographics, clinical and laboratory parameters.MethodsAll symptomatic confirmed COVID-19 patients admitted to our hospital ED between February 24th and April 24th 2020 were recruited. CXR features, clinical and laboratory variables and CXR abnormality indices extracted by a convolutional neural network (CNN) diagnostic tool were considered potential predictors on this first visit. The most serious individual outcome defined the three severity level: 0) home discharge or hospitalization ≤ 3 days, 1) hospital stay >3 days and 2) intensive care requirement or death. Severity and in-hospital mortality multivariable prediction models were developed and internally validated. The Youden index was used for the optimal threshold selection of the classification model.ResultsA total of 440 patients were enrolled (median 64 years; 55.9% male); 13.6% patients were discharged, 64% hospitalized, 6.6% required intensive care and 15.7% died. The severity prediction model included oxygen saturation/inspired oxygen fraction (SatO2/FiO2), age, C-reactive protein (CRP), lymphocyte count, extent score of lung involvement on CXR (ExtScoreCXR), lactate dehydrogenase (LDH), D-dimer level and platelets count, with AUC-ROC = 0.94 and AUC-PRC = 0.88. The mortality prediction model included age, SatO2/FiO2, CRP, LDH, CXR extent score, lymphocyte count and D-dimer level, with AUC-ROC = 0.97 and AUC-PRC = 0.78. The addition of CXR CNN-based indices did not improve significantly the predictive metrics.ConclusionThe developed and internally validated severity and mortality prediction models could be useful as triage tools in ED for patients with COVID-19 or other virus infections with similar behaviour.     

Hallazgos iniciales en la radiografía de tórax como predictores de empeoramiento en la infección pulmonar por SARS-CoV-2. Correlación en 265 pacientes

Background and aimsWe aimed to analyze the relationship between the initial chest X-ray findings in patients with severe acute respiratory syndrome due to infection with SARS-CoV-2 and eventual clinical worsening and to compare three systems of quantifying these findings.Material and methodsThis retrospective study reviewed the clinical and radiological evolution of 265 adult patients with COVID-19 attended at our center between March 2020 and April 2020. We recorded data related to patients’ comorbidities, hospital stay, and clinical worsening (admission to the ICU, intubation, and death). We used three scoring systems taking into consideration 6 or 8 lung fields (designated 6 A, 6 B, and 8) to quantify lung involvement in each patient's initial abnormal chest X-ray and to classify its severity as mild, moderate, or severe, and we compared these three systems. We also recorded the presence of alveolar opacities and linear opacities (fundamentally linear atelectasis) in the first chest X-ray with pathologic findings.ResultsIn the χ2 analysis, moderate or severe involvement in the three classification systems correlated with hospital admission (p = 0.009 in 6 A, p = 0.001 in 6 B, and p = 0.001 in 8) and with death (p = 0.02 in 6 A, p = 0.01 in 6 B, and p = 0.006 in 8). In the regression analysis, the most significant associations were 6 B with alveolar involvement (OR 2.3; 95%CI 1.1.–4.7; p = 0.025;) and 8 with alveolar involvement (OR 2.07; 95% CI 1.01.–4.25; p = 0.046). No differences were observed in the ability of the three systems to predict clinical worsening by classifications of involvement in chest X-rays as moderate or severe.ConclusionModerate/severe extension in the three chest X-ray scoring systems evaluating the extent of involvement over 6 or 8 lung fields and the finding of alveolar opacities in the first abnormal X-ray correlated with mortality and the rate of hospitalization in the patients studied. No significant difference was found in the predictive ability of the three classification systems proposed.