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《Diagnostic and interventional imaging》2020,101(12):821-830
PurposeTo compare morphological imaging features and CT texture histogram parameters between grade 3 pancreatic neuroendocrine tumors (G3-NET) and neuroendocrine carcinomas (NEC).Materials and methodsPatients with pathologically proven G3-NET and NEC, according to the 2017 World Health Organization classification who had CT and MRI examinations between 2006-2017 were retrospectively included. CT and MRI examinations were reviewed by two radiologists in consensus and analyzed with respect to tumor size, enhancement patterns, hemorrhagic content, liver metastases and lymphadenopathies. Texture histogram analysis of tumors was performed on arterial and portal phase CT images. images. Morphological imaging features and CT texture histogram parameters of G3-NETs and NECs were compared.ResultsThirty-seven patients (21 men, 16 women; mean age, 56 ± 13 [SD] years [range: 28-82 years]) with 37 tumors (mean diameter, 60 ± 46 [SD] mm) were included (CT available for all, MRI for 16/37, 43%). Twenty-three patients (23/37; 62%) had NEC and 14 patients (14/37; 38%) had G3-NET. NECs were larger than G3-NETs (mean, 70 ± 51 [SD] mm [range: 18 - 196 mm] vs. 42 ± 24 [SD] mm [range: 8 - 94 mm], respectively; P = 0.039), with more tumor necrosis (75% vs. 33%, respectively; P = 0.030) and lower attenuation on precontrast (30 ± 4 [SD] HU [range: 25-39 HU] vs. 37 ± 6 [SD] [range: 25-45 HU], respectively; P = 0.002) and on portal venous phase CT images (75 ± 18 [SD] HU [range: 43 - 108 HU] vs. 92 ± 19 [SD] HU [range: 46 - 117 HU], respectively; P = 0.014). Hemorrhagic content on MRI was only observed in NEC (P = 0.007). The mean ADC value was lower in NEC ([1.1 ± 0.1 (SD)] × 10−3 mm2/s [range: (0.91 - 1.3) × 10−3 mm2/s] vs. [1.4 ± 0.2 (SD)] × 10−3 mm2/s [range: (1.1 - 1.6) × 10−3 mm2/s]; P = 0.005). CT histogram analysis showed that NEC were more heterogeneous on portal venous phase images (Entropy-0: 4.7 ± 0.2 [SD] [range: 4.2-5.1] vs. 4.5 ± 0.4 [SD] [range: 3.7-4.9]; P = 0.023).ConclusionPancreatic NECs are larger, more frequently hypoattenuating and more heterogeneous with hemorrhagic content than G3-NET on CT and MRI. 相似文献
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《Diagnostic and interventional imaging》2020,101(9):555-564
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%. 相似文献
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《Diagnostic and interventional imaging》2020,101(6):335-345
This article was designed to provide a pediatric cardiac computed tomography angiography (CCTA) expert panel consensus based on opinions of experts of the Société Française d’Imagerie Cardiaque et Vasculaire diagnostique et interventionnelle (SFICV) and of the Filiale de Cardiologie Pédiatrique Congénitale (FCPC). This expert panel consensus includes recommendations for indications, patient preparation, CTA radiation dose reduction techniques, and post-processing techniques. The consensus was based on data from available literature (original papers, reviews and guidelines) and on opinions of a group of specialists with extensive experience in the use of CT imaging in congenital heart disease. In order to reach high potential and avoid pitfalls, CCTA in children with congenital heart disease requires training and experience. Moreover, pediatric cardiac CCTA protocols should be standardized to acquire optimal images in this population with the lowest radiation dose possible to prevent unnecessary radiation exposure. We also provided a suggested structured report and a list of acquisition protocols and technical parameters in relation to specific vendors. 相似文献
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目的 评价中老年人社会资本量表的信效度,探索其在不同健康状况的中老年人群间的区分度。方法 针对已编制的中老年人社会资本量表,采用多阶段分层随机抽样方法,在四川省成都市及泸州市共抽取1 367名50岁及以上中老年居民进行问卷调查。运用Cronbach’s α系数、Pearson相关系数、t检验、探索性因子分析等方法评价量表的信度和效度。结果 1 367名中老年调查对象的社会资本量表总Cronbach’s α系数为0.67,各维度条目与总分的相关系数在0.30~0.79之间,具有良好的信度;探索性因子分析表明,14个条目提取出5个特征根大于1的因子,累积方差贡献率为68.84%;现患慢性疾病的中老年病例组人群的个人社会资本得分、家庭社会资本得分、社团社会资本得分、社区社会资本得分及社会资本总得分均低于未患病的对照人群组,宏观社会资本得分高于对照人群组,且差异均有统计学意义 (均 P<0.01),提示该量表具有较好的区分度。结论 中老年人社会资本量表具有较好的信度和效度,且对不同健康状况的50岁及以上中老年人中有较好的区分度。 相似文献
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《Clinical neurophysiology》2021,132(12):3104-3115
ObjectiveWe aimed to establish an objective neurophysiological test protocol that can be used to assess the somatosensory nervous system.MethodsIn order to assess most fiber subtypes of the somatosensory nervous system, repetitive stimuli of seven different modalities (touch, vibration, pinprick, cold, contact heat, laser, and warmth) were synchronized with the electroencephalogram (EEG) and applied on the cheek and dorsum of the hand and dorsum of the foot in 21 healthy subjects and three polyneuropathy (PNP) patients. Latencies and amplitudes of the modalities were assessed and compared. Patients received quantitative sensory testing (QST) as reference.ResultsWe found reproducible evoked potentials recordings for touch, vibration, pinprick, contact-heat, and laser stimuli. The recording of warm-evoked potentials was challenging in young healthy subjects and not applicable in patients. Latencies were shortest within Aβ-fiber-mediated signals and longest within C-fibers. The test protocol detected function loss within the Aβ-fiber and Aδ-fiber-range in PNP patients. This function loss corresponded with QST findings.ConclusionIn this pilot study, we developed a neurophysiological test protocol that can specifically assess most of the somatosensory modalities. Despite technical challenges, initial patient data appear promising regarding a possible future clinical application.SignificanceEstablished and custom-made stimulators were combined to assess different fiber subtypes of the somatosensory nervous system using modality-specific evoked potentials. 相似文献
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