Intracranial atherosclerotic stenosis (ICAS) is a major cause of ischemic stroke, but current diagnostic indices such as stenotic percentage (SP) and relative cerebral blood flow (rCBF) have limitations. SP lacks functional relevance, and rCBF cannot confirm whether stenosis causes ischemia. We propose a non-invasive method to assess ischemic stroke by computing cerebral fractional flow (cFF), defined as the ratio of distal to inlet pressure across the stenosis. Using cerebrovascular generation algorithms and the Desikan-Killiany atlas, we built 66 personalized whole-brain hemodynamic models to calculate cFF and rCBF, diagnosing ischemia at rCBF ≤ 0.48. cFF showed a stronger correlation with rCBF than SP (r = 1.00 vs. 0.71, p < 0.001). ROC analysis identified a diagnostic threshold of 0.56, yielding 98.48

Background We aimed to construct and validate a radiomics prediction model based on preoperative T2-weighted MRI for prognosis and chemosensitivity prediction in patients with glioma. Methods A total of 576 glioma patients were enrolled in this study. The training and validation group included 324 patients and 127 patients respectively with preoperative MRI image data, tumor transcriptome sequencing data and clinical information. The prospective validation group consisted of 125 patients with preoperative MRI image data and clinical information. The radiomics prediction model was constructed based on the prognostic relevant radiomic features of glioma patients in the training group. The radiomics prediction model was validated inpatients of retrospective and prospective validation groups. Functional annotation of radiomic features was performed by pearson correlation analysis of biological process scores and radiomic features values of patients in the training group and validated by transcriptome sequencing, single cell sequencing, reactive oxygen species detection and endoplasmic reticulum stress detection of tumors of patients in retrospective and prospective validation groups. Results The radiomics prediction model, which consisted of 17 radiomic features, showed highly predictive stability in overall survival and progression-free survival prediction. Compared with patients who underwent postoperative radiotherapy alone, only patients in the high-risk group benefited from postoperative chemoradiotherapy. The prognostic relevant radiomic features were closely related to immune response, reactive oxygen species metabolism and endoplasmic reticulum stress of glioma cells in silico and in vitro. Conclusions The radiomics prediction model serves as a non-invasive tool to predict prognosis and temozolomide chemosensitivity of glioma patients based on preoperative T2-weighted MRI.

Magnetic resonance imaging (MRI), with its characteristics of no radiation, high soft tissue resolution, and multi-parameter imaging, has irreplaceable advantages in the diagnosis and assessment of various diseases. In clinical practice, MRI image quality and imaging speed are limited by software and hardware. Some patients (such as those with poor tolerance, infants, and critically ill patients) often cannot endure the long MR imaging time, resulting in low image quality, severe artifacts, and even imaging failure. MR imaging time is constrained by factors such as image resolution, signal-to-noise ratio, and contrast. Filling the k-space and converting k-space data into MR images through algorithms (such as Fourier transform) is the core of the MRI principle. The k-space undersampling is the basis for rapid MR data acquisition and can effectively save imaging time. Optimizing algorithms is the key to ensuring image reconstruction quality and speed. Clinically, methods such as appropriately shortening the TR time, reducing the number of phase-encoding steps, optimizing the kspace filling trajectory, partial Fourier acquisition, and parallel imaging (PI) technology can all shorten the MR imaging time to a certain extent. However, shortening the MR imaging time through such methods often sacrifices the spatial resolution or signal-to-noise ratio of the image, which is not expected in clinical diagnosis. At the same time, the acceleration effect of such methods is often limited, either with insignificant acceleration or a significant decline in MR image quality when the acceleration is too high. The application and development of compressed sensing (CS) technology have improved the speed of MR imaging to a certain extent and ensured the quality of MR imaging to a certain extent, but its acceleration ability also has limitations, especially in sparse sampling methods and denoising models. Therefore, how to quickly and high-quality reconstruct noisy sparse k-space data into MR images remains a major challenge in the MRI field. In recent years, artificial intelligence, especially deep learning methods, have demonstrated great potentials in the field of MRI and have made a lot of significant breakthroughs, primarily involving the acquisition of magnetic resonance data, various filling methods of k-space, various image reconstruction algorithms, various image segmentation approaches, and auxiliary diagnosis on a variety of diseases. In order to better clarify the development of artificial intelligence in accelerating MRI, this article focuses on summarizing the clinical applications of artificial intelligence in k-space filling and image reconstruction. Under-sampling of the magnetic resonance signals and a variety of algorithms for achieving magnetic resonance image reconstruction are emphatically discussed. Furthermore, this article has listed the difficulties faced by artificial intelligence in accelerating MRI and the future directions. This is helpful for radiologic technologists and radiologists to better understand, use and further develop the artificial intelligence-based acceleration technology on MRI, which will ensure that the quality of all the magnetic resonance images meets the clinical diagnostic requirements while achieving a fast MRI. Meanwhile, it is beneficial to patients who suffer from claustrophobia, poor tolerance, critical conditions, and infants who cannot tolerate a long duration of MRI.

Background: Shortening the acquisition time of brain three-dimensional T2 fluid-attenuated inversion recovery (3D T2 FLAIR) by using acceleration techniques has the potential to reduce motion artifacts in images and facilitate clinical application. This study aimed to assess the image quality of brain 3D T2 FLAIR accelerated by artificial intelligence-assisted compressed sensing (ACS) in comparison to 3D T2 FLAIR accelerated by parallel imaging (PI). Methods: In this prospective cohort study, 102 consecutive participants, including both healthy individuals and those with suspected brain diseases, were recruited and underwent both ACS- and PI-3D T2 FLAIR scans with a 3.0-Tesla magnetic resonance imaging system from February 2023 to October 2023 in Beijing Tiantan Hospital, Capital Medical University. Quantitative assessment involved white matter (WM) and gray matter (GM) signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR), whole-image sharpness, and tumor volume. Qualitative assessment included the scoring of overall image quality, GM-WM border sharpness, and diagnostic confidence in lesion detection. Results: ACS-3D T2 FLAIR exhibited a shorter acquisition time compared to PI-3D T2 FLAIR (105 vs. 320 seconds). ACS-3D T2 FLAIR, compared to PI-3D T2 FLAIR, demonstrated a significantly higher CNRWM/GM (4.613 +/- 1.547 vs. 4.160 +/- 1.552; P<0.001), and sharpness (0.413 +/- 0.049 vs. 0.396 +/- 0.034; P<0.001), while no significant differences were found for the overall image quality ratings (P=0.063) or GM-WM border sharpness ratings (P=0.125). A good agreement on tumor volume was achieved between ACS-3D T2 FLAIR and PI-3D T2 FLAIR images (intraclass correlation coefficient =0.999; 0.998-1.000; P<0.001). Images acquired with ACS demonstrated nearly equivalent diagnostic confidence to those obtained with PI Conclusions: The ACS technique offers a substantial reduction in scanning time for brain 3D T2 FLAIR compared to PI while maintaining good image quality and equivalent diagnostic confidence.

Background Deep learning reconstruction (DLR) with denoising has been reported as potentially improving the image quality of magnetic resonance imaging (MRI). Multi-modal MRI is a critical non-invasive method for tumor detection, surgery planning, and prognosis assessment; however, the DLR on multi-modal glioma imaging has not been assessed. Purpose To assess multi-modal MRI for glioma based on the DLR method. Material and Methods We assessed multi-modal images of 107 glioma patients (49 preoperative and 58 postoperative). All the images were reconstructed with both DLR and conventional reconstruction methods, encompassing T1-weighted (T1W), contrast-enhanced T1W (CE-T1), T2-weighted (T2W), and T2 fluid-attenuated inversion recovery (T2-FLAIR). The image quality was evaluated using signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and edge sharpness. Visual assessment and diagnostic assessment were performed blindly by neuroradiologists. Results In contrast with conventionally reconstructed images, (residual) tumor SNR for all modalities and tumor to white/gray matter CNR from DLR images were higher in T1W, T2W, and T2-FLAIR sequences. The visual assessment of DLR images demonstrated the superior visualization of tumor in T2W, edema in T2-FLAIR, enhanced tumor and necrosis part in CE-T1, and fewer artifacts in all modalities. Improved diagnostic efficiency and confidence were observed for preoperative cases with DLR images. Conclusion DLR of multi-modal MRI reconstruction prototype for glioma has demonstrated significant improvements in image quality. Moreover, it increased diagnostic efficiency and confidence of glioma.

Objective To explore the correlation between amide proton transfer imaging(APTw)and the Ki67 proliferation index of glioma and analyze the accuracy of the predicting model.Methods 63 glioma patients from Beijing Tiantan Hospital were accepted APTw imaging within 2 weeks before surgery,and 59 glioma patients were finally included.The patients were divided into two groups according to immunohistochemistry results:low proliferation group(cell proliferation index<20%,n= 39)and high proliferation group(cell proliferation index 20%,n=20),and the mean APTw signal intensities of gliomas were measured.The correlaction between APTw signal intensity and Ki67 proliferation index was evaluated by Pearson test.The differences of mean APTw signal intensity between two proliferation groups were evaluated by Mann-Whitney U test.The predicting model by mean APTw signal intensity as an imaging biomarker was established,and then ROC curve was drawn to assess their diagnostic performance.Finally,the cut-off value of the APTw signal intensity for this model was obtained by Yuden index.Result There was a positivity correlaction between APTw signal intensity and Ki67 proliferation index(r=0.629,P<0.001),and there was a significant difference between two proliferation groups(Z=4.539,P<0.001).The AUC for predicting model was 0.863(95%CI:0.770-0.956),with sensitivity of 1,and specificity of 0.718.Youden index showed the cut-off value was 2.55.Conclusion APTw signal intensity can be served as an imaging biomarker for the predicting model of glioma Ki-67 proliferation level,which has a good diagnostic effectiveness and good sensitivity;When the mean APTw signal intensity is greater than 2.55,the glioma prefers high proliferation level,otherwise,the glioma prefers low proliferation level.

Extracorporeal membrane oxygenation (ECMO) is a life support system used in the treatment of severe respiratory and circulatory failure. High shear stress caused by the high rotational speed of centrifugal blood pumps can cause hemolysis and platelet activation, which are among the major factors leading to the complications of the ECMO system. In this study, a novel blood pump named rotary displacement blood pump (RDBP), which can considerably reduce rotational speed and shear stress while ensuring the normal pressure flow relationship, was proposed. We employed computational fluid dynamics (CFD) analysis to investigate the performance of RDBP under adult ECMO support operating conditions (5 L/min with 350 mmHg). The efficiency and H-Q curves of the RDBP were calculated to evaluate its hydraulic performance, and pressure, flow patterns, and shear stress distribution were analyzed to estimate the hemodynamic characteristics in the pump. In addition, the modified index of hemolysis (MIH) was calculated for the RDBP based on a Eulerian approach. The hydraulic efficiency of the RDBP was 47.28%. The velocity distribution of flow field in the pump was relatively uniform. Most of the liquid (more than 75%) in the pump was exposed to low scale shear stress (<1 Pa), which was close to normal physiological conditions. The gap area was the main distribution location of high scale shear stress. The high wall shear stress (>9 Pa) volume fraction of the RDBP was small and located in the boundary areas between the rotor's edge and the housing. The MIH value of the RDBP was 9.87 ± 0.93 (mean ± SD). The RDBP can achieve better hydraulic efficiency and hemodynamic performance at lower rotational speed. The design of this novel pump is expected to provide a new direction for developing a blood pump for ECMO.

Objective Venous-arterial venous extracorporeal membrane oxygenation (V-AV ECMO), as a new clinical application of ECMO, showed great clinical application potential in the treatment of patients with combined cardiopulmonary failure. Given the complicated cannulation strategy of V-AV ECMO, its influence on the hemodynamics of the human circulatory system remained unclear. Methods In this paper, a fluid–structure interaction was used to study the effect of V-AV ECMO oxygenated blood shunt ratio on right atrial recirculation and tricuspid valve (TV) blood oxygen saturation. In this study, the right atrium, superior vena cava supplying cannulae and inferior vena cava draining cannulae model of a specific patient was constructed. Seven cases with shunt ratio of 12.50%, 18.75%, 25.00%, 31.25%, 37.50%, 43.75% and 50.00% were designed. Results The streamline diagram and velocity contour of oxygenated blood, recirculation fraction (RF), correlation of three variables (shunt ratio, RF, and oxygen saturation), and the oxygen saturation of blood at the TV were extracted for the study. Study results showed that, first, as the shunt ratio increased, the RF of the seven cases was 14.64%, 29.87%, 33.85%, 40.12%, 40.40%, 40.02%, and 38.09%. Second, with the increase of the shunt ratio, oxygen saturation of blood at the TV in seven cases was 82.1%, 82.5%, 83.3%, 83.3%, 84.0%, 84.6%, and 85.3%. Conclusions In this study, the shunt ratio had a strong correlation with the RF and oxygen saturation of blood at the TV. As the shunt ratio increased, the RF initially increased and then stabilized. However, oxygen saturation of blood at the TV would increase with the increase of the shunt ratio, but the degree of increase was small. This research provided useful information for surgeons and operators using V-AV ECMO.

虽然我国新型冠状病毒肺炎疫情防控取得较大阶段性成果,但是全球范围内新型冠状病毒肺炎疫情仍处于持续大流行阶段.我国仍然面临"外防输入、内防反弹"的防控压力,当前处于新型冠状病毒肺炎疫情防控常态化阶段.影像学检查,特别是CT检查依然是新型冠状病毒肺炎筛查、诊断和疗效评估的重要临床检查手段之一,方舱式应急CT已经成为隔离区对新型冠状病毒肺炎确诊患者进行CT检查的主要专用设备.本文拟探讨首都医科大学附属北京地坛医院在新型冠状病毒肺炎疫情防控常态化情况下隔离区方舱CT的临床应用,重点阐述隔离区方舱CT的布局、智能化系统的有效应用以及对影像技师的挑战,旨在总结有效经验,以期指导临床实际工作.

Objective:To compare the image quality between virtual mono-energetic images (VMIs) with different keV and conventional images in intracranial CT angiography (CTA) using dual-layer spectral detector CT (SDCT).Methods:The clinical and imaging data of 80 patients who underwent intracranial CTA utilizing the SDCT in Radiology Department of Beijing Tiantan Hospital, Capital Medical University from April 2020 to March 2021 were retrospectively analyzed. CT values of the intracranial arteries, their contrast to noise ratio (CNR) compared to the corpus callosum, overall image quality, and difficulty degree of volume rendering (VR) for the intracranial artery were compared between the VMIs (40-90 keV, interval of 10 keV) and the conventional images. Friedman test was used for the statistical analysis.Results:With the decrease of the energy level (from 90 keV to 40 keV), CT values of the arteries increased significantly (C7 segment of the internal carotid artery: 242.16-1090.28 HU; the basilar artery: 217.17-1021.79 HU), while CT value of the corpus callosum increased slightly (29.30-37.76 HU). Performance of the CNR and the overall image quality on the lower-energy (40-60 keV) images were significantly better than those on the conventional images (P<0.05), meanwhile, VR of the arteries on the lower-energy (40-60 keV) images was easier than that on the conventional images (P<0.05).Conclusion:Visualization of the intracranial arteries on the lower-energy (40-60 keV) images was better than that on the conventional images, and VR of the intracranial arteries on the lower-energy (40-60 keV) images was easier than that on the conventional images when utilizing the dual-layer SDCT.

目的 探索双层探测器光谱CT利用50 keV低能级图像对挽救颅内冠状动脉CT血管造影(CT Angiography,CTA)扫描失败的可行性.方法 回顾性分析在我院光谱CT上行颅内CTA扫描失败的31例患者的临床和影像资料.比较50 keV图像与常规图像上血管的CT值及相对于胼胝体的对比噪声比(Contrast to Noise Ratio,CNR)、可诊断性评分、血管容积重建(Volume Rendering,VR)难易程度.统计分析采用Wilcoxon检验进行分析.结果 50 keV图像上颅内血管CT值[如颈内动脉C7段为(388.39±131.08)HU、基底动脉为(376.34±114.57)HU]均高于常规图像[如颈内动脉C7段为(202.61±53.60)HU、基底动脉为(196.18±50.22)HU],差异具有统计学意义(P<0.05).50 keV图像上颅内血管CNR(如颈内动脉C7段为43.15±23.07、基底动脉为24.22±14.17)均大于常规图像(如颈内动脉C7段为19.45±9.37、基底动脉为15.90±6.98),差异具有统计学意义(P<0.05).50 keV低能级扫描可提高图像的诊断价值,且诊断评分≥2的例数比常规图像明显增加.50 keV低能级图像更易进行血管多级分支的VR.结论 利用双层探测器光谱CT 50keV低能级图像的优势可挽救部分颅内CTA扫描失败的情况.

Background:Although aortic valve reconstruction has become an alternative treatment for aortic valve disease, the design of the geometric parameters of the reconstructed leaflet still mainly depends on the experience of doctors. The present study investigates the effects of the height of the leaflets on the performance and biomechanical states of the reconstructed aortic valve.Methods:This numerical study was carried out using the finite element approach and the lattice Boltzmann method. The dynamic and biomechanical characteristics of the leaflets were evaluated by using the finite element approach, while the blood flow in the aortic sinus was evaluated by applying the lattice Boltzmann method. Three types of leaflets with different heights were designed. Then the dynamic characteristics, stress distribution, and effective orifice area (EOA) of the aortic valve and flow pattern were calculated as the indicators.Results:The results demonstrated that the height of the leaflets could indeed regulate the performance and the biomechanical states of the aortic valve. The rapid valve opening times of the 3 types of leaflets gradually reduced along with the decrease of the height ratio (HR_0.8: 120 ms vs. HR_1.0: 68 ms vs. HR_1.2: 31 ms), while the rapid valve closing times (RVCTs) of the 3 types of leaflets were similar to each other (approximately 75 ms). Moreover, the radial displacement of the leaflet at the fully open time increased along with the decrease of the HR of the leaflets (HR_0.8: 8 mm vs. HR_1.0: 6 mm vs. HR_1.2: 4 mm). In addition, the stress level of the leaflets also increased with the increase of the height of the leaflets (max stress, HR_0.8: 0.5 MPa, vs. HR_1.0: 1.1 MPa, vs. HR_1.2: 1.8 MPa). Similarly, the low velocity region near the ascending aortic wall and the wall shear stress (WSS) level on the ventricular side of the leaflets also increased along with the increase of the HR of the leaflets.Conclusions:In short, the height of the leaflets mainly affects the opening performance of the reconstructed aortic leaflets. The HR of the reconstructed leaflets for adults should be less than 1.0 to balance the opening and closing performance of aortic leaflets.

目的 对比分析基于压缩感知(compressed sensing,CS)技术的3D液体衰减反转恢复(fluid-attenuated inversion-recovery,FLAIR)序列与常规2D-FLAIR序列对脑白质病变的成像质量.材料与方法 前瞻性纳入首都医科大学附属北京天坛医院40例同时行头部CS 3D-FLAIR序列和2D-FLAIR序列扫描的脑白质病患者.客观分析图像的信噪比(signal-to-noise ratio,SNR)和对比噪声比(contrast noise ratio,CNR),并由2名经验丰富的诊断医师对图像整体质量和脑白质病灶个数进行评估.利用Wilcoxon秩和检验进行统计分析.结果CS技术可以将3D-FLAIR序列的采集时间缩短到与2D-FLAIR序列相当.CS 3D-FLAIR序列和2D-FLAIR序列图像的SNR和CNR差异无统计学意义(Z=-1.18,P=0.24;Z=-1.92,P=0.14).CS 3D-FLAIR序列的图像整体质量评分和显示脑白质病灶个数显著优于2D-FLAIR序列(Z=-3.99,P<0.001;Z=-3.75,P=0.006).CS 3D-FLAIR序列对第四脑室层面的搏动伪影具有抑制作用.结论 扫描时长相当的情况下,CS 3D-FLAIR序列图像整体质量好,可抑制搏动伪影,比2D-FLAIR序列更利于脑白质病变的检出,建议临床推广应用.

Subtyping relapsing–remitting multiple sclerosis (RRMS) patients may help predict disease progression and triage patients for treatment. We aimed to subtype RRMS patients by structural MRI and investigate their clinical significances. 155 relapse-remitting MS (RRMS) and 210 healthy controls (HC) were retrospectively enrolled with structural 3DT1, diffusion tensor imaging (DTI) and resting-state functional MRI. Z scores of cortical and deep gray matter volumes (CGMV and DGMV) and white matter fractional anisotropy (WM-FA) in RRMS patients were calculated based on means and standard deviations of HC. We defined RRMS as “normal” (− 2 < z scores of both GMV and WM-FA), DGM (z scores of DGMV < − 2), and DGM-plus types (z scores of DGMV and [CGMV or WM-FA] < − 2) according to combinations of z scores compared to HC. Expanded disability status scale (EDSS), cognitive and functional MRI measurements, and conversion rate to secondary progressive MS (SPMS) at 5-year follow-up were compared between subtypes. 77 (49.7%) patients were “normal” type, 37 (23.9%) patients were DGM type and 34 (21.9%) patients were DGM-plus type. 7 (4.5%) patients who were not categorized into the above types were excluded. DGM-plus type had the highest EDSS. Both DGM and DGM-plus types had more severe cognitive impairment than “normal” type. Only DGM-plus type showed decreased functional MRI measures compared to HC. A higher conversion ratio to SPMS in DGM-plus type (55%) was identified compared to “normal” type (14%, p < 0.001) and DGM type (20%, p = 0.005). Three MRI-subtypes of RRMS were identified with distinct clinical and imaging features and different prognosis.

Background: The impact of myelin oligodendrocyte glycoprotein antibody disease (MOGAD) on brain structure and function is unknown. Objectives: The aim of this study was to study the multimodal brain MRI alterations in MOGAD and to investigate their clinical significance. Methods: A total of 17 MOGAD, 20 aquaporin-4 antibody seropositive neuromyelitis optica spectrum disorders (AQP4 + NMOSD), and 28 healthy controls (HC) were prospectively recruited. Voxel-wise gray matter (GM) volume, fractional anisotropy (FA), mean diffusivity (MD), and degree centrality (DC) were compared between groups. Clinical associations and differential diagnosis were determined using partial correlation and stepwise logistic regression. Results: In comparison with HC, MOGAD had GM atrophy in frontal and temporal lobe, insula, thalamus, and hippocampus, and WM fiber disruption in optic radiation and anterior/posterior corona radiata; DC decreased in cerebellum and increased in temporal lobe. Compared to AQP4 + NMOSD, MOGAD presented lower GM volume in postcentral gyrus and decreased DC in cerebellum. Hippocampus/parahippocampus atrophy associated with Expanded Disability Status Scale (R = -0.55, p = 0.04) and California Verbal Learning Test (R = 0.62, p = 0.031). The differentiation of MOGAD from AQP4 + NMOSD achieved an accuracy of 95% using FA in splenium of corpus callosum and DC in occipital gyrus. Conclusion: Distinct structural and functional alterations were identified in MOGAD. Hippocampus/parahippocampus atrophy associated with clinical disability and cognitive impairment.

Purpose H3K27M-mutant associated brainstem glioma (BSG) carries a very poor prognosis. We aimed to predict H3K27M mutation status by amide proton transfer weighted (APTw) imaging and radiomic features. Methods Eighty-one BSG patients with APTw imaging at 3T MRI and known H3K27M status were retrospectively studied. APTw values (mean, median and max) and radiomic features within manually delineated 3D tumor masks were extracted. Comparison of APTw measures between H3K27M-mutant and wildtype groups was conducted by two-sample Student’s T/Mann-Whitney U test and receiver operating characteristic curve (ROC) analysis. H3K27M-mutant prediction using APTw-derived radiomics was conducted using a machine-learning algorithm (Support Vector Machine) in randomly selected train (n=64) and test (n=17) sets. Sensitivity analysis with additional random splits of train and test sets, 2D tumor masks and other classifiers were conducted. Finally, a prospective cohort including 29 BSG patients was acquired for validation of the radiomics algorithm.

Purpose H3K27M-mutant associated brainstem glioma (BSG) carries a very poor prognosis. We aimed to predict H3K27M mutation status by amide proton transfer weighted (APTw) imaging and radiomic features. Methods Eighty-one BSG patients with APTw imaging at 3T MRI and known H3K27M status were retrospectively studied. APTw values (mean, median and max) and radiomic features within manually delineated 3D tumor masks were extracted. Comparison of APTw measures between H3K27M-mutant and wildtype groups was conducted by two-sample Student’s T/Mann-Whitney U test and receiver operating characteristic curve (ROC) analysis. H3K27M-mutant prediction using APTw-derived radiomics was conducted using a machine-learning algorithm in randomly selected train (n=64) and test (n=17) sets. Sensitivity analysis with additional random splits of train and test sets, 2D tumor masks and other classifiers were conducted. Finally, a prospective cohort including 29 BSG patients was acquired for validation of the radiomics algorithm. Results BSG patients with H3K27M-mutant were younger and had higher max APTw values than those with wildtype. APTw-derived radiomic measures reflecting tumor heterogeneity could predict H3K27M mutation status with an accuracy of 0.88, sensitivity of 0.92 and specificity of 0.80 in the test set. Sensitivity analysis confirmed the predictive ability (accuracy range: 0.71-0.94). In the independent prospective validation cohort, the algorithm reached an accuracy of 0.86, sensitivity of 0.88 and specificity of 0.85 for predicting H3K27M-mutation status. Conclusion BSG patients with H3K27M-mutant had higher max APTw values than those with wildtype. APTw-derived radiomics could accurately predict a H3K27M-mutant status in BSG patients.

To assess the diagnostic efficacy of magnetic resonance imaging (MRI) in the differential diagnosis between well-differentiated hepatocellular carcinomas (WD-HCCs) and high-grade dysplastic nodules (HGDNs) in cirrhotic liver. From January 2012 to April 2018, we retrospectively analyzed 91 cirrhotic nodules (HGDN, n = 31, WD-HCC, n = 60) which were confirmed by surgery or pathology. Each patient underwent gadobenate dimeglumine-enhanced hepatic MRI. The MRI characteristics and enhancement effects were calculated and analyzed. Hyperintensity on diffusion-weighted imaging (DWI), the typical enhancement pattern and hypo-intensity on T1-Weighted imaging (T1WI)were showed with statistically significant difference between WD-HCCs and HGDNs in cirrhotic live (P = 0.002, 0.008, 0.002, respectively). And high signal intensity (SI) on DWI (sensitivity, 66.7%, specificity, 67.7%) was the most specific feature to differentiated WD-HCCs from HGDNs. The combination of DWI and the dynamic enhancement pattern improved the differentiation of WD-HCCs from HGDNs(specificity 83.9%). DWI is the most specific technique to differentiate WD-HCCs from HGDNs. The combination of DWI and the typical dynamic enhancement pattern can improve the differentiation of WD-HCCs from HGDNs. Pre-enhanced T1WI, as well as a capsule, provides additional diagnostic values.

目的:研究iDose4迭代重建算法不同迭代水平在人类获得性免疫缺陷综合征(AIDS)合并耶氏肺孢子菌肺炎(PJP)患者胸部低剂量CT扫描中的效能对比.方法:应用飞利浦iCT对16例AIDS合并PJP患者分别行常规剂量和低剂量胸部CT平扫.常规剂量组的DRI指数设置为30;低剂量组的DRI指数设置为10.管电压均采用120 kV.常规剂量组采用FPB重建算法,低剂量组采用iDose4(L2,L4,L6)重建算法.测量不同扫描方案下图像的客观噪声值(SD),记录不同扫描方案下CT容积剂量指数(CTDI vol)、剂量长度乘积(DLP)并计算有效剂量(ED).比较不同扫描方案下的辐射剂量、图像的客观指标(图像噪声)及主观指标(图像质量主观评分)的差异.结果:低剂量扫描条件下,LD_iDose4_L2组、LD_iDose4_L4组及LD_iDose4_L6图像噪声值分别为:12.41、10.13和8.01,LD_iDose4_L6组的图像噪声值与SD_FPB组(8.51)相比,差异无统计学意义.肺窗视图下,LD-iDose4_L2组、LD-iDose4_L4组CT图像质量主观评分均在3分以上,满足了诊断需求,以LD_iDose4_L2组显示最好.纵隔窗视图下,低剂量组各组主观评分均在3分以上,均满足了诊断需求,其中以LD_iDose4_L6组得分最高.低剂量组与常规组的ED值大小分别为6.18和2.28,差异均具有统计学意义(P<0.05),低剂量组的有效剂量较常规剂量组降低了63.11％.结论:iDose4迭代重建在AIDS合并PJP患者胸部CT病变及解剖结构的显示上具有明显的优势,能够在大幅降低辐射剂量的情况下得到满足诊断需要的CT图像.低剂量扫描条件下,iDose 4迭代重建迭代水平级别越高,降噪的能力越强,图像噪声值越小.但就图像总体质量而言,肺窗视图下,图像质量以LD_iDose4_L2组显示最好;纵隔窗视图下,图像质量以LD_iDose4_L6组显示最好.

目的 分析颅脑MRI扫描时所产生伪影的类型及原因,选择合适的方法 消除或减少伪影,以提高颅脑MRI扫描的图像质量.方法 回顾性收集80例颅脑MRI扫描时产生伪影的图像并归类,统计不同类型伪影的例数,分析可能原因,采用合理方法消除或减少伪影.结果 所收集的80例颅脑MRI伪影分为设备伪影、患者伪影和外源性伪影三大类,其中设备伪影8例(包括线圈故障2例,卷褶伪影6例),患者伪影52例(包括自主运动伪影24例,血管搏动伪影15例,植入器械伪影13例),外源性伪影20例(包括射频干扰12例,外源性辅助装置伪影7例、呕吐物所致伪影1例).结论 行颅脑MR扫描时,多种因素易导致图像产生伪影,选择合理的方法,可避免或减少颅脑MR扫描时伪影的产生;修正合理的扫描参数及定期维护以及患者的良好配合均有助于避免和消除设备伪影、改善运动伪影.