Differentiating autoimmune pancreatitis from pancreatic ductal adenocarcinoma with CT radiomics features

PurposeThe purpose of this study was to determine whether computed tomography (CT)-based machine learning of radiomics features could help distinguish autoimmune pancreatitis (AIP) from pancreatic ductal adenocarcinoma (PDAC).Materials and MethodsEighty-nine patients with AIP (65 men, 24 women; mean age, 59.7 ± 13.9 [SD] years; range: 21–83 years) and 93 patients with PDAC (68 men, 25 women; mean age, 60.1 ± 12.3 [SD] years; range: 36–86 years) were retrospectively included. All patients had dedicated dual-phase pancreatic protocol CT between 2004 and 2018. Thin-slice images (0.75/0.5 mm thickness/increment) were compared with thick-slices images (3 or 5 mm thickness/increment). Pancreatic regions involved by PDAC or AIP (areas of enlargement, altered enhancement, effacement of pancreatic duct) as well as uninvolved parenchyma were segmented as three-dimensional volumes. Four hundred and thirty-one radiomics features were extracted and a random forest was used to distinguish AIP from PDAC. CT data of 60 AIP and 60 PDAC patients were used for training and those of 29 AIP and 33 PDAC independent patients were used for testing.ResultsThe pancreas was diffusely involved in 37 (37/89; 41.6%) patients with AIP and not diffusely in 52 (52/89; 58.4%) patients. Using machine learning, 95.2% (59/62; 95% confidence interval [CI]: 89.8–100%), 83.9% (52:67; 95% CI: 74.7–93.0%) and 77.4% (48/62; 95% CI: 67.0–87.8%) of the 62 test patients were correctly classified as either having PDAC or AIP with thin-slice venous phase, thin-slice arterial phase, and thick-slice venous phase CT, respectively. Three of the 29 patients with AIP (3/29; 10.3%) were incorrectly classified as having PDAC but all 33 patients with PDAC (33/33; 100%) were correctly classified with thin-slice venous phase with 89.7% sensitivity (26/29; 95% CI: 78.6–100%) and 100% specificity (33/33; 95% CI: 93–100%) for the diagnosis of AIP, 95.2% accuracy (59/62; 95% CI: 89.8–100%) and area under the curve of 0.975 (95% CI: 0.936–1.0).ConclusionsRadiomic features help differentiate AIP from PDAC with an overall accuracy of 95.2%.     

Stress Testing Versus CT Angiography in Patients With Diabetes and Suspected Coronary Artery Disease

Background

The optimal noninvasive test (NIT) for patients with diabetes and stable symptoms of coronary artery disease (CAD) is unknown.

How accurate is atherosclerosis imaging by coronary computed tomography angiography?

Invasive coronary plaque imaging such as intravascular ultrasound and optical coherence tomography has been widely used to observe culprit or non-culprit coronary atherosclerosis, as well as optimize stent sizing, apposition and deployment. Coronary computed tomographic angiography (CTA) is non-invasively available to assess coronary artery disease (CAD) and has become an appropriate strategy to evaluate patients with suspected CAD. Given recent technologies, semi-automated plaque software is available to identify coronary plaque stenosis, volume and characteristics and potentially allows to be used for the assessment of more details of plaque information, progression and future risk as a surrogate tool of the invasive imaging modalities. This review article aims to focus on various evidence in coronary plaque imaging by coronary CTA and describes how accurate coronary CTA can classify coronary atherosclerosis.     

肝门胆管癌的动态增强CT诊断

目的评价螺旋CT对肝门胆管癌的诊断价值。方法13例肝门胆管癌行螺旋CT平扫及动态增强扫描,并与手术及病理对照分析。结果11例平扫表现为肝门区低密度软组织肿块;2例表现为肝门区胆管不规则增厚,管腔狭窄。增强扫描13例有延迟强化。结论螺旋CT扫描对肝门胆管癌的诊断具有重要意义。     

高分辨率CT对颞部疾病的检查价值

目的：探讨高分辨率CT（HRCT）对颞部疾病的检查价值。方法：对43例颞部疾病患者行常规CT和高分辨率CT（HRCT）检查所获图像对比分析，并讨论HRCT的检查技术和图像后处理。结果：HRCT对病变的显示率及病变引起骨质破坏的程度，病变边缘，轮廓的显示均明显优于常规CT，尤其能清楚显示常规CT难以显示的中耳及内耳的细微结构，结论：高分辨率CT是颞部疾病的首选检查方法，使用高分辨率CT对颞部疾病的检查给临床提供更多，更准确的诊断信息。     

鼻部源性突眼的CT分析

目的：为了提高对鼻部源性突眼的认识。材料和方法：本文19例鼻部源性突眼，其中鼻咽癌7例，鼻咽纤维血管瘤2例，鼻腔纤维血管瘤、恶性肉芽肿和嗅神经母细胞瘤各1例，上颌窦癌和软骨肉瘤各2例，上颌窦恶性肉芽肿、纤维肉瘤和恶性纤维组织细胞瘤各1例，全部病例均作轴位CT扫描，12例加作增强扫描，详细分析了它们CT表现。结果：源于鼻咽的放疗前鼻咽癌和纤维血管瘤，其病变主要位于鼻咽腔和咽旁，后者显著增强并有钙斑，与前者不同；源于上颌窦的肿瘤，病变占据上颌窦的全部或大部分，软骨肉瘤有钙斑且无强化，易与其它肿瘤区别，它们破坏上颌窦顶部进入眼眶；鼻腔嗅神经母细胞瘤在鼻腔和筛窦形成肿块，破坏筛骨眶板侵入眼眶。结论：根据CT所见，可判断突眼原因。     

New insights on COPD imaging via CT and MRI

Multidetector-row computed tomography (MDCT) can be used to quantify morphological features and investigate structure/function relationship in COPD. This approach allows a phenotypical definition of COPD patients, and might improve our understanding of disease pathogenesis and suggest new therapeutical options. In recent years, magnetic resonance imaging (MRI) has also become potentially suitable for the assessment of ventilation, perfusion and respiratory mechanics. This review focuses on the established clinical applications of CT, and novel CT and MRI techniques, which may prove valuable in evaluating the structural and functional damage in COPD.     

血糖水平对18F-FDG PET/CT图像质量的影响

目的 研究血糖水平对18F-脱氧葡萄糖(FDG) PET/CT图像质量的影响.方法 80例行体格检查或评价肿瘤性质的受检者,按空腹血糖水平分为9组(组间距为1mmol/L),第1组为血糖正常组,即血糖＜6.0mmol/L(10例);第2～9组血糖水平高于正常,分别为6.0～6.9mmol/L(11例),7.0～7.9mmol/L(13例),8.0～8.9mmol/L(11例),9.0～9.9mmol/L(11例),10.0～10.9mmol/L(8例),11.0～11.9mmol/L(6例),12.0～12.9mmol/L(5例),≥13.0mmol/L(5例).受检者做完PET/CT检查后,图像质量由2位有经验的医师独立判断.同时根据肝不同层面的标准摄取值(SUV)最大值(SUVmax)及SUV平均值(SUVavg)分别计算肝图像噪声.采用SPSS 12.0软件进行统计学处理.结果 (1)9组之间图像质量评分、肝噪声差异有统计学意义(P均＜0.05).将第2～9组图像质量评分、肝噪声分别与第1组进行比较,第2～7组与第1组差异无统计学意义(P均＞0.05);第8,9组与第1组比较差异有统计学意义(P均＜0.05),且评分低于第1组.(2)血糖水平与图像质量评分呈负相关(r=-0.52,P＜0.05);血糖水平与肝噪声呈正相关(SUVmax、SUVavgr值分别为0.33和0.60,P均＜0.05);SUVavg所算噪声与血糖水平的相关性优于SUVmax.结论 图像质量随血糖水平的升高而下降,血糖＜12.0mmol/L时与血糖正常者PET/CT图像质量差异无统计学意义,但当血糖水平≥12.0mmol/L时图像质量将显著下降.