[To promote the clinical application of PET/MRI in oncology].

PET/MRI integrates anatomical, functional and metabolic information, and is increasingly used in the field of clinical oncology, including early diagnosis of disease, local staging, detection of systemic metastases, evaluation of treatment efficacy and prognosis. In addition to fine anatomical structure, MRI multiparametric imaging can also provide functional information of the lesion. Combined with metabolic information of PET, MRI multiparametric imaging can better evaluate the benign and maligant lesions, tumor grade and extent of invasion, and identify tumor recurrence and radiation necrosis. The development of new PET tracers, optimization of MRI sequences and examination paths, combined with high-throughput image quantitative analysis methods, radiomics, artificial intelligence and other new technologies will further promote the application of PET/MRI in oncology.

[Predictive performance for prognosis of aneurysmal subarachnoid hemorrhage with ventricular hemorrhage by imaging combined with clinical and laboratory quantitative index model].

Objective: To explore the predictive performance of image quantitative index model, clinical-laboratory index model and image-clinical multi-dimensional fusion model in predicting the prognosis of patients with aneurysmal subarachnoid hemorrhage (aSAH) with intraventricular hemorrhage (IVH). Methods: A total of 349 patients with aSAH and IVH, including 122 males and 227 females, aged 22 to 85 (59±11) years underwent CT scan in the General Hospital of Eastern Theater Command from January 2010 to December 2019 were used as dataset 1 to construct a prognostic model. A prognostic model was constructed for data set 1, and the functional recovery of patients 12 months after discharge was evaluated using the modified Rankin Scale (mRS). According to the results, those patients were divided into two groups: good outcome group (n=267) and poor outcome group (n=82). In addition, 63 aSAH patients with IVH, including 27 males and 36 females, aged 32 to 87 (61±12) years who were admitted to the General Hospital of Eastern Theater Command from January 2020 to December 2021 were collected as dataset 2 for independent verification of the model, including 30 patients with poor prognosis. Clinical information (age and gender), laboratory indicators (blood routine and blood biochemistry), and imaging quantitative indicators (such as volume, density, shape of each ventricle hemorrhage area outlined and extracted on head CT scan etc.) were recorded for all patients (dataset 1 and 2). The clinical, laboratory and imaging quantitative indicators of dataset 1 were screened by using L1 regularization and multiple logistic regression method was used to construct the clinical-laboratory index model, image quantitative index model and image-clinical multi-dimensional fusion model, according to the weight coefficient of features in the clinical-laboratory index model and image quantitative index model, screen out the main features. The model was trained and internally validated by 5-fold cross-validation. The model was validated independently in dataset 2. Results: The AUC (area under the ROC curve) of clinical-laboratory index model, image quantitative index model and multidimensional fusion model constructed based on dataset 1 were 0.75 (95%CI: 0.69-0.81), 0.68 (95%CI: 0.61-0.74) and 0.86 (95%CI: 0.82-0.91). The Delong test showed that there were statistically significant differences between the performance of the multi-dimensional fusion model and the clinical-laboratory index model or image quantitative index model (all P<0.05). The AUC of clinical-laboratory index model, image quantitative index model and multidimensional fusion model of dataset 2 were 0.79 (95%CI: 0.68-0.91), 0.70 (95%CI: 0.57-0.83) and 0.81 (95%CI: 0.70-0.92). In addition, in the clinical-laboratory index model and imaging quantitative index model constructed based on data 1, age, Hunt-Hess grade on admission, Neutrophil/Lymphocyte (N/L) (the weight coefficients in the clinical-laboratory index model were 1.00, -0.59 and 0.44) and the standard deviation of third ventricle hemorrhage density, minimum hemorrhage density of the fourth ventricle, and left ventricle hemorrhage sphericity (the weight coefficients in the image quantitative index model were -1.00, 0.85 and -0.84) were the main features of the screening. Conclusions: Quantitative imaging indicators of ventricular hemorrhage (standard deviation of third ventricular hemorrhage density, minimum density of fourth ventricular hemorrhage, and left ventricular sphericity) are helpful to predict the poor prognosis of patients with aSAH with ventricular hemorrhage. Dimensional fusion model has greater value in predicting poor prognosis of patients.

[Qualitative and quantitative PET/MRI in the evaluation of axillary lymph node metastasis in patients with breast cancer].

Objective: To investigate the value of qualitative and quantitative PET/MRI in the evaluation of axillary lymph node metastasis in patients with breast cancer. Methods: A total of 33 patients with breast cancer underwent preoperative PET/MRI examinations in Jingling Hospital from February to August in 2022 were retrospectively collected. All these patients were female, aged from 34 to 73 (51.4±11.3) years. Histopathological results and follow-up data were deemed as the referent standard, and the images were independently evaluated by two experienced breast imaging radiologists. The qualitative PET/MRI evaluation procedures were designed to evaluated the MRI alone to classify the axillary lymph nodes firstly, and then, the axillary lymph nodes status was reclassified by combining MRI and PET images. The net reclassification improvement index (NRI) was calculated using the R Programming Language (RStudio). The quantitative PET/MRI evaluation of the maximum standard uptake value (SUVmax) of axillary lymph nodes were measured by two radiologists, respectively, and the average value was compared with the referent standard to conduct a receiver operating characteristic (ROC) curve to select the optimal cutoff value of SUVmax. Based on the cutoff value and MRI classification results, axillary lymph nodes status was divided into quantitative PET/MRI positive or negative. The sensitivity, specificity and accuracy of MRI and quantitative PET/MRI in evaluating axillary lymph node metastasis were compared, and the area under the ROC curve (AUC) was compared. Results: There was no significant difference in sensitivity, specificity and accuracy between MRI and quantitative PET/MRI in evaluating lymph node metastasis of breast cancer (81.82% vs 95.46%; 81.82% vs 100%; 81.82% vs 96.97%) (all P>0.05). The AUC had a statistically significant difference [0.82 (0.65 to 0.93) vs 0.98 (0.85 to 1.00), P=0.026)]. According to the referent standard, in the 11 cases without ipsilateral axillary lymph node metastasis, the SUVmax was 0.83±0.18, while in the 22 cases with ipsilateral axillary lymph node metastasis, the SUVmax was [4.36 (1.77, 5.85)]. Compared with MRI alone, the NRI of qualitative PET/MRI in evaluating lymph node metastasis was 36.36% (P=0.021). Conclusion: Compared with MRI alone, quantitative PET/MRI has a higher AUC for evaluating axillary lymph node metastasis in patients with breast cancer, and qualitative PET/MRI had a better reclassification power in the evaluation of axillary lymph node metastasis.

[Characteristics of the white matter involvement sites on MRI in patients with multiple gliomas].

The retrospective study included 122 cases of multiple glioma and 183 cases of single glioma. Of these, there were 74 males and 48 female with multiple gliomas, aged 18 to 83 (53±13) years, and 104 males and 79 females with single gliomas, aged 10 to 84 (51±14) years. A standard spatial-based lesion analysis method was used for constructing a spatially distributed frequency heatmap of multiple gliomas, to observe the characteristics of their white matter invasion sites. The spatial distribution was more frequent in the subventricular zone, corpus callosum and cingulate gyrus in the multiple glioma group compared to the single glioma group (P<0.001).The white matter areas of multiple gliomas were more extensively involved, with more frequent involvement of the conjoined fibers (corpus callosum, P<0.05) and contact fibers (cingulate, dome, 0.05

[To promote actively clinical application of advanced cardiovascular CT imaging].

In recent years, cardiovascular imaging has become an important tool to evaluate cardiovascular diseases, which can provide anatomical and function information in multidimensional ways, and is expected to have a positive impact on the diagnosis and treatment of cardiovascular diseases. This editorial briefly describes the current status of advanced cardiovascular CT imaging in cardiovascular diseases on diagnosis, treatment, decision-making and prognostic evaluation, including CT-derived flow fractional reserve, CT perfusion, pericoronary adipose tissue and application of artificial intelligence, in order to promote the clinical transformation of these technologies.

[Hemodynamics-based analysis of factors associated with aneurysm rupture in different sides of the internal carotid artery].

Objective: To explore the influence of hemodynamics, morphological and clinical characteristics on rupture risk of the dorsal and non-dorsal internal carotid artery aneurysms (ICAAs). Methods: A total of 111 patients diagnosed with aneurysm by digital subtraction angiography (DSA) or surgery, underwent cranial CT angiography (CTA) were retrospectively collected from January 2010 to December 2016 at the Department of Diagnostic Radiology, Jinling Clinical College of Xuzhou Medical University (General Hospital of Eastern Theater Command). Among them, 41 were males and 70 were females, ranging in age from 32 to 83 (56±11) years old. The patients were divided into the ruptured group (n=54) and unruptured group (n=57) based on the hemorrhagic manifestation on non-enhanced CT images or DSA or surgery of the head. Demographics and the morphological characteristics of the aneurysms were evaluated. Hemodynamic parameters, including wall share stress, wall share stress gradient, and others were obtained in overall using computational fluid dynamics simulation technique. Characteristics were compared between the ruptured and unruptured groups. Logistic regression analysis was applied to evaluate the independent risk factors for rupture, and the hemodynamic characteristics associated with dorsal and non-dorsal aneurysms were analyzed, respectively. Results: Compared with the unruptured group, patients in the ruptured group were younger ((54.2±11.4) years and (58.3±9.9) years, P=0.033), mostly female (74.1% vs 52.6%, P<0.05), with a higher proportion of hypertension (46.3% vs 22.8%, P=0.009). The ruptured internal carotid artery aneurysms (ICAAs) were more frequently located at the dorsal of an arterial arch (57.4% vs 36.8%, P<0.05), and the flow of the blood was more complex, concentrated, unstable, and with a smaller impingement zone (68.5% vs 33.3%,55.6% vs 10.5%,72.2% vs 26.3% and 79.6% vs 36.8%, respectively, all P<0.05). Logistic regression demonstrated that women, hypertension, dorsal, concentrated flow pattern, and unstable flow pattern were an independent risk factors for ICAAs rupture [OR=3.551 (1.080-11.679), 3.900 (1.172-12.976), 4.966 (1.504-16.401), 51.893 (7.913-340.296) and 50.015 (8.423-296.985), respectively, all P<0.05]. The ruptured ICAAs located at non-dorsal had more concentrated, unstable, and with smaller impingement zone (P<0.05), while those at dorsal had more complex, concentrated, and unstable flow patterns, and with smaller impingement zone (all P<0.05). Conclusion: Women, hypertension, dorsal concentration, and unstable flow pattern are independent risk factors for the rupture of ICAAs. The dorsal locations of ICAAs could have a higher risk of rupture.

[The analysis of structural magnetic resonance imaging manifestation of hippocampus based on voxel and spherical harmonic surface morphometry in mesial temporal lobe epilepsy].

Objective: To compare the hippocampal volume and local surface morphology changes in patients with mesial temporal lobe (mTLE) using the voxel-based morphometry and spherical harmonic methods respectively. Methods: A total of 66 patients (31 males and 35 females, age range from 17 to 48 (28±8) years) with mTLE and 80 age-and gender-matched controls (38 males and 42 females, age range from 19 to 46 (27±7) years) were retrospectively collected from July 2009 to February 2019 at Jinling hospital.. High resolution structural MRI of the whole brain, three-dimensional T1-weighted data(3DT1) were acquired from each subject. The changes of hippocampal volume and surface morphology were evaluated between mTLE groups and controls for observing the hippocampal atrophy pattern by using voxel-based morphometry and spherical harmonic shape descriptions point distribution model respectively. Pearson correlation analysis was conducted for observing the relationship between the morphological changes of hippocampus and disease duration. Results: Compared with the controls, hippocampal volume on the affected side in patients with mTLE was significantly reduced (Z-score:-1.55±0.57 vs 0.38±0.58, P<0.001) and negatively correlated with disease duration (r=-0.297, P=0.016). Furthermore, surface morphology analysis subtly showed that the atrophy of the affected hippocampus in patients with mTLE mainly located in the head, mesial lateral part and posterior tail of the hippocampus. Their displacement values were negatively correlated with disease duration (r=-0.336, P=0.006) and positively associated with the hippocampal grey matter volume (r=0.336, P=0.006). Conclusions: Voxel-based morphometry analysis reveals a global reduction in hippocampal volume, while the morphological measurement method based on surface shape can describe the local morphological changes of hippocampal atrophy.

[Association of coronary perivascular fat attenuation index, the parameters of plaque and fractional flow reserve].

Objective: To explore the association of coronary perivascular fat attenuation index (FAI), the parameters of plaque and fractional flow reserve (FFR). Methods: A total of 113 patients (with 141 plaques) (78 males and 35 females, age from 40 to 83 years) with stable coronary artery disease were retrospectively collected from Jingling Hospital and Shanghai Sixth People's Hospital. All the patients underwent coronary CT angiography and invasive FFR examinations. The quantitative and qualitative parameters of plaque and vessel (such as the length and volume of plaque, the characteristics of plaque and high-risk plaque) and the FAI around the plaque were measured. The patients were divided into positive FAI group (n=46) and negative FAI group (n=66) according to the standard of whether the threshold of FAI≥ -70 HU. The quantitative indexes, including age, the length and volume of plaque, minimal lumen area (MLA) and FAI, as well as the qualitative indexed, including the characteristics of plaque, the number and characteristic of high-risk plaque and the number of patients and plaque with positive FFR were compared between the two groups. Further, logistic regression analysis was performed to analyze the correlation among myocardial ischemia, age, the length of plaque, minimal lumen area (MLA), FAI and so on. ROC curve was used for evaluating the performance of each parameter. Results: Compared to the negative FAI group, positive FAI group had lower MLA (2.00±1.33 mm2 vs 4.13±2.41 mm2, P<0.001). The proportion of patients and vessels with FFR<0.75 in positive FAI group were significantly higher than that in negative FAI group (21.3% vs 4.5%, P=0.006; 23.2% vs 8.2%, P=0.016). The FAI between high-risk plaque and non-high-risk plaque had no significant difference (21.2% vs 16.1%, P=0.451). FAI predicted myocardial ischemia (AUC=0.666, P=0.021) and significantly improved the prediction efficiency of complex model(0.915 vs 0.951,P=0.033). Conclusion: Lower MLA and higher incidence of myocardial ischemia were associated with patients with higher FAI. In addition, FAI has a certain prediction efficiency and can provide incremental value for the determination of myocardial ischemia.

[Application of deep learning-based chest CT auxiliary diagnosis system in emergency trauma patients].

Objective: To investigate the diagnostic efficacy and potential application value of deep learning-based chest CT auxiliary diagnosis system in emergency trauma patients. Methods: A total of 403 patients, including 254 males and 149 females aged from 16 to 100 (50±19) years, who received emergency treatment for trauma and chest CT examination in the Eastern Theater General Hospital from September 2019 to November 2019 were retrospectively analyzed. Dr. Wise Lung Analyzer's chest CT auxiliary diagnosis system was applied to detect 5 types of injuries, including pneumothorax, pleural effusion/hemothorax, pulmonary contusion (shown as consolidation and ground glass opacity), rib fractures, and other fractures (including thoracic vertebrae, sternum, scapula and clavicle, etc.) and 6 other abnormalities (bullae, emphysema, pulmonary nodules, stripe, reticulation, pleural thickening). The diagnostic reference standards were labeled by two radiologists independently. The sensitivity and specificity of the auxiliary diagnosis system were evaluated. The imaging diagnostic reports were compared with the results of the auxiliary diagnosis system, and the diagnostic consistency between the two was calculated by using the Kappa test. Results: According to the reference standards, among the 403 patients, 29 were pneumothorax, 75 were pleural effusion/hemothorax, 131 were pulmonary contusion, 124 were rib fractures, and 63 were other fractures. The sensitivity and specificity of the auxiliary diagnosis system for detection of pneumothorax, pleural effusion/hemothorax, rib fractures, and other fractures were 96.6%, 97.6%, 80.0%, 99.7%, 99.2%, 83.9%, 84.1%, and 99.7%, respectively. The sensitivity of detecting lung contusion was 97.7%. There was a high consistency between the auxiliary diagnosis system and imaging diagnosis in the diagnosis of injuries, in which the kappa values of pneumothorax, pleural effusion, rib fracture and other fractures were 0.783, 0.821, 0.706 and 0.813, respectively (all P<0.001). Two cases of pneumothorax, three cases of pleural effusion/hemothorax, nine cases of rib fractures, and six cases of other fractures missed by imaging diagnosis were all detected by the auxiliary diagnosis system. The detection sensitivity of the auxiliary diagnosis system was higher for emphysema, pulmonary nodules and stripe (all>85%), but lower for bullae, reticulation and pleural thickening. Conclusions: The deep learning-based chest CT auxiliary diagnosis system could effectively assist chest CT to detect injuries in emergency trauma patients, which was expected to optimize the clinical workflow.

[Magnetic resonance imaging morphological study of the effects of juvenile febrile convulsions on the brain structure of medial temporal lobe epilepsy].

Objective: To investigate the effect of febrile convulsions on gray matter volume (GMV) in medial temporal lobe epilepsy (mTLE) and its correlation with disease duration. Methods: A retrospective study was conducted to collect 41 mTLE patients with a history of febrile convulsions (mTLE-FC), 42 mTLE patients with no initial precipitating injury (mTLE-noIPI), and 42 normal and age and sex matched normal controls. High-resolution T1-weighted (T(1)WI) whole brain MR scans were performed on all subjects. Voxel-based morphometry were used to obtain GMV brain maps, and the GMV differences between the three groups of subjects were compared (P<0.01, GRF corrected). Finally, Spearmen rank correlation analysis was used to explore the correlation between GMV changes and the course of disease. Results: Compared with the normal control subjects, each mTLE group showed extensive GMV reduction, mainly in the affected hippocampus, thalamus, temporal lobe, and bilateral cerebellum. Further analysis found that mTLE-FC group had more significant reductions in GMV than the mTLE-noIPI group in the affected hippocampus, amygdala, inferior temporal gyrus, contralateral hippocampus, para hippocampus, and inner cingulate gyrus. At the same time, the affected amygdala and hippocampal GMV in the mTLE-FC group was significantly negatively related to the course of disease (r=-0.381, P=0.014), while the mTLE-noIPI group had no downward trend (r=0.081, P=0.611). The atrophic trend of the affected amygdala and hippocampus in patients with mTLE-FC was significantly greater than that in patients with mTLE-noIPI (P=0.029, permutation test). Conclusions: There is extensive damage to the gray matter structure of bilateral cerebral hemispheres, mainly in the hippocampus, in mTLE patients. The brain damage of mTLE patients with a history of juvenile fever convulsions is more extensive and serious, and the trend of progressive exacerbation with the course of the disease is more obvious, suggesting mTLE associated with juvenile fever convulsions may have different pathophysiological mechanisms.

[Radiation dose and image quality of noncontrast chest CT in domestic and imported main stream manufacturers].

Objective: To compare the radiation dose and image quality of noncontrast chest CT and detection of ground-glass opacity pulmonary nodules (GGN) in domestic 128-slice spiral CT with the other CT scanners from three main stream manufacturers. Methods: From May 8, 2018 to October 31, 2018, noncontrast chest CT images from Neusoft 128-slice CT (75 males, 25 females, (42±16) years), dual-source 64-slice CT (53 males, 47 females, (50±16) years) and dual-source 128-slice CT scanners(69 males, 31 females, (62±17) years), Toshiba 128-slice CT (51 males, 49 females, (58±13) years) and GE 128-slice CT scanner (55 males, 45 females, (60±10) years) were collected in Eastern Theater Command and Tianjin People's Hospital. Radiation dose and image quality were evaluated.GGN detected both in Neusoft CT and dual-source CT scanners were used to analyze the displaying ability of lesions. Results: The noise in lung window of Neusoft CT ((37.8±4.9) HU) was higher than that of other mainstream CT scanners, and the noise in mediastinal window ((8.4±1.9) HU) was lower than that of GE 128-slice CT ((9.8±3.2) HU), but higher than that of dual-source CT and Toshiba 128-slice CT ((6.9±3.5)HU) (P<0.05). The absolute value of lung SNR in Neusoft CT was lower than that of other mainstream CT scanners, and the SNR in aorta (4.6±1.3) was lower than those of dual-source CT and Toshiba 128-slice CT(6.8±2.2) (P<0.05), but was not statistically significant compared with GE 128-slice CT (5.0±1.7). The mean CT value of upper lung ((-863±31) HU) at Neusoft CT was higher than 128-row dual-source CT ((-869±35) HU), and the mean CT value of aorta ((37±7) HU) was lower than that of Toshiba 128-slice CT((42±7) HU) and GE 128-slice CT ((45±9) HU) (P<0.05), while the mean CT values of the remaining lung and aorta were not statistically significant (P>0.05). The two readers had good to excellent consistency for image quality in five scanners (the highest kappa value=0.984). The delineation ability of Neusoft CT for GGN boundary was lower than that of dual-source CT (P<0.05), but had similar abilities to display the solid components, lobulation, burring, vacuoles, vascular bundle sign and pleural depression sign of GGN (all P>0.05). Radiation dose of Neusoft CT was lower than Toshiba 128-slice CT, but higher than dual-source 64-sliceCT and GE 128-slice CT scanners (P<0.05). Conclusions: With lower radiation dose than Toshiba 128-slice CT, Neusoft CT chest examination can meet the requirements of clinical diagnosis, but higher radiation dose and the lower image quality than dual-source CT and GE 128-slice CT shown in this study indicate further improvement is needed in terms of software and hardware.

[The altered topology of brain structural network in patients with acute stress response after traffic accident].

Objective: To explore the changes of brain activities in traffic accident survivors with acute stress response (ASR) within a week by using complex networks analysis method based on graph-theory, and to find out the alteration of topological properties in structural brain network. Method: From January, 2013 to February, 2016, twenty traffic accidents survivors with acute stress disorders (Acute Stress Disorder Interview, ASDI>3)and twenty healthy controls underwent the 3T diffusion tensor imaging (DTI) magnetic resonance imaging scan in Nanjing General Hospital.The graph-theory analysis method was used to compare the structural brain network properties and nodal features between ASR survivors and controls.Statistical analyses were also performed by including anxiety and depression as covariates to evaluate their effect.In additional, Pearson correlation was performed between abnormal parametric values and clinical indices. Results: (1) The brain structural networks had small-world properties in both groups; (2) while compared with healthy controls, patients with ASR showed increased weighted connectivity strength (Si, 1.36±0.47 vs 0.92±0.38, P=0.008) and nodal betweenness centrality (BCi, 20±15 vs 7±6, P=0.002) in left triangular part of inferior frontal (IFG triang_L), increased Si in orbital part of inferior frontal gyrus (1.10±0.31 vs 0.77±0.30, P=0.004) and obviously decreased Si in left caudate (0.75±0.24 vs 1.04±0.35, P=0.004); (3) furthermore, the inclusion of anxiety and depression as covariates abolished nodal parameters differences in IFG triang_L, left caudate, thalamus and inferior temporal gyrus. Conclusions: The brain structure network in ASR patients has small world properties.But nodal parameters change obviously in some nodes compared with healthy controls and mainly locate in prefrontal lobe and striatum. High levels of anxiety and depression in ASR patients may partly account for these alterations.

[Impairments of gray matter in MRI-negative epileptic patients with different seizure types].

Objective: To investigate the damage of gray matter structure in MRI-negative epilepsy patients with different symptoms by voxel-based morphometry (VBM). Methods: From June, 2009 to October, 2016, ninety MRI-negative epilepsy patients and thirty-five healthy volunteers underwent the 3T magnetic resonance imaging scan in Nanjing General Hospital. The patients were divided into three groups, including idiopathic generalized tonic-clonic seizure (I-GTCS), secondarily generalized tonic-clonic seizure (S-GTCS), and partial seizure (PS) according to different symptoms. The three-dimensional high-resolution T1 structural MRI data was obtained for the voxel-based morphometry. Data of gray matter structure from four groups were compared using one-way analysis of variance (ANOVA). An independent-sample t test was performed in order to compare gray matter volume of the three patient groups with controls respectively. According the results of ANOVA, impaired brain regions were selected as regions of interest in order to carry out correlation analysis between gray matter volume and disease duration. Results: ANOVA showed significant differences in gray matter structure of bilateral thalamus and frontal lobe between four groups (alphasim correction, P<0.01). Independent-sample t test showed that the volume of bilateral thalamus and frontal lobe decreased in all three patients groups (alphasim correction, P<0.01) .The volume of bilateral thalamus showed significantly negatively correlation with disease duration in I-GTCS patients (r=-0.466, P<0.01). Conclusions: Generalized seizures and partial seizures all can cause damage to the gray matter structure, especially in thalamus and frontal lobe. The impairments of thalamus and frontal lobe in patients with different seizure types are different with the progression of disease, which suggests that influences of different epilepsy seizures on the thalamo-cortical network are different.

[Study of functional connectivity density mapping in patients with acute stress response by using resting-state functional MRI after traffic accident].

Objective: To explore the changes of brain activity in traffic accident survivors with acute stress response within a week by using functional connectivity density (FCD) method. Method: A total of 20 traffic accidents survivors with acute stress disorders (acute stress disorder interview >3) and twenty healthy controls from Nanjing Jinling Hospital underwent the 3.0 T resting-state functional magnetic resonance imaging scan from January 2013 to February 2016. Functional connectivity density mapping was used to compare the brain functional connective networks between acute stress response survivors and controls. In additional, Pearson correlation was performed between abnormal short, long-range FCD values and clinical indices. Results: (1) Compared with controls, patients with acute stress response showed decreased short-range FCD in left ventromedial prefrontal cortex (-0.815±0.264 vs-0.468±0.615, t=-2.198, P<0.05), left hippocampal and parahippocampal gyri (-1.212±0.135 vs-0.887±0.234), t=-5.070, all P<0.05), and increased short-range FCD in right precentral gyrus(0.428±0.256 vs 0.016±0.298, t=4.456, P<0.05), left inferior parietal and superior parietal lobes (0.623±0.290 vs 0.143±0.300, t=4.878, allP<0.05); (2)compared with normal controls, ASR patients showed increased long-range FCD in left precuneus (0.502±0.400 vs-0.042±0.253, t=4.879, P<0.05); (3)the HAMA score of patients positively correlated with short-range FCD value of the left vmPFC (r=0.50, P<0.05). Conclusion: The long-and short-range functional connectivity in frontal-limbic system is widely changed in survivors with acute stress response, especially the short-range FCD change more significantly, and partly correlated with the severity of their stress symptoms.

[Application of low dose CT angiography with 70 kV in patients with peripheral arterial diseases].

Objective: To assess the image quality, radiation dose and diagnostic efficiency of peripheral arterial CT angiography (CTA) performed at tube voltage of 70 and 120 kV. Methods: Between January 2014 and December 2015, a total of 200 consecutive patients with known or suspected lower extremity arteriosclerosis obliterans (LEASO) underwent CTA.Patients were randomly divided into 2 groups by different scanning protocols.Group A (n=100): 70 kV and 0.8 ml/kg contrast agent, group B (n=100): 120 kV and 100 ml contrast agent.The vessel enhancement, image noise, signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of 3 segments were quantified for each protocol.30 patients in group A (420 vessels) and 28 patients in group B (384 vessels) confirmed by DSA.Based on vessel assessments, compared with DSA findings, the diagnostic efficacy of 70 kV and 120 kV protocols for the detection of stenoses over 50% was evaluated.The dose of radiation and contrast agent were recorded.Subjective image quality was evaluated. Results: The subjective image quality of segment crural of group A was significantly higher than that of group B (2.20±0.36 vs 1.72±0.34, P<0.01). The enhancement of 3 segments in group A (500 HU) were significantly higher than these in group B (310 HU) (P<0.05). For the detection of stenoses over 50%, the sensitivity, positive and negative predictive values and accuracy of segment crural in group A (98.6%, 95.8%, 98.1%, 96.7%) were significantly higher than that in group B (90.9%, 88.5%, 91.0%, 89.7%) (P<0.05). Mean DLP for 70-kV protocol was significantly lower than that for 120-kV protocol ( (396±34) vs (1 041±159) mGy·cm, P=0.001). Mean dose of contrast agent and the total amount of iodine for 70-kV protocol were significantly lower than that for 120-kV protocol (53.5 vs 100 ml; 18.7 vs 35 g; P<0.01). Conclusion: CT angiography of peripheral arteries with a low tube voltage of 70 kV and low dose of iodine provides reliable information and serves as a rapidly performed and easily available imaging modality in the diagnosis of LEASO.

Identification of new subtypes and potential genetic signatures in triple-negative breast cancer using weighted gene co-expression network analysis.

OBJECTIVE: Triple-negative breast cancer (TNBC) is a heterogeneous disease with aggressive behavior and poor prognosis. Here, we used gene expression profiling to define new subtypes of TNBC, which may improve prevention and treatment through personalized medicine. MATERIALS AND METHODS: Gene expression profiles from the public datasets GSE76250, GSE61724, GSE61723, and GES76275 were subjected to co-expression analysis to identify differentially expressed genes (DEGs) between TNBC and non-TNBC tissues. Consistency clustering was used to define TNBC subtypes, whose correlation with gene modules was analyzed. Enrichment analysis was used to identify module genes' biological functions and pathways. Single-sample gene set enrichment analysis was used to assess immune cell infiltration in the different TNBC subtypes, and the ChAMP package was used to examine methylation sites in TNBC. RESULTS: A total of 4,958 DEGs in TNBC were identified, which showed the same expression differences across all datasets as in the dataset GSE76250 and clustered into 9 co-expression modules. TNBC samples clustered into two subtypes based on nine hub genes from the modules. Class I showed the most significant correlation with module 1, whose genes were related mainly to interleukin-1 response, while class II showed the most significant correlation with module 6, whose genes were related mainly to the transforming growth factor-ß pathway. Class I was significantly enriched in cell cycle and DNA replication, and tumors of this subtype showed lower immune cell infiltration than class II tumors. Tumor infiltration by Th2 cells correlated positively with the expression of MCM10 and negatively with the expression of PREX2. A greater methylation of CIDEC, DLC1, EDNRB, EGR2 and SRPK1 correlated with better prognosis. CONCLUSIONS: Class I TNBC, for which a useful biomarker is MCM10, may be associated with a worse prognosis than class II TNBC, for which PREX2 may serve as a biomarker.

Amplification of the telomerase RNA component gene as a new genetic marker for disease progression and prognosis in esophageal squamous cell carcinoma.

Amplification of the human telomerase RNA component (TERC) gene was found in esophageal squamous cell carcinoma (ESCC). However, its roles in the progression and prognosis of ESCC have not been well understood. The amplification of TERC in normal mucosa, low-grade and high-grade intraepithelial neoplasia, and invasive ESCC samples were evaluated using a fluorescence in situ hybridization assay. The amplification of TERC invariably occurred in high-grade intraepithelial neoplasia and invasive ESCC, partially occurred in low-grade intraepithelial neoplasia specimens, and seldom occurred in normal mucosa. The average signal ratio of TERC to chromosome 3 centromere-specific probe (TERC/CSP3) was 1.00 ± 0.01 (average ± standard deviation) in normal mucosas, 1.01 ± 0.08 in low-grade intraepithelial neoplasias, 1.39 ± 0.26 in high-grade intraepithelial neoplasias, and 1.56 ± 0.41 in invasive ESCC. High TERC/CSP3 ratio was positively associated with lymph node metastasis (P = 0.005) and advanced tumor stage (P = 0.045). Patients with high amplification of TERC had poor survival (P = 0.01). The amplification of TERC could be used as a new genomic marker for disease progression and prognosis of ESCC. The amplified TERC gene may be a potential therapeutic target for ESCC.

Machine Learning-Based Prediction of Small Intracranial Aneurysm Rupture Status Using CTA-Derived Hemodynamics: A Multicenter Study.

BACKGROUND AND PURPOSE: Small intracranial aneurysms are being increasingly detected while the rupture risk is not well-understood. We aimed to develop rupture-risk models of small aneurysms by combining clinical, morphologic, and hemodynamic information based on machine learning techniques and to test the models in external validation datasets. MATERIALS AND METHODS: From January 2010 to December 2016, five hundred four consecutive patients with only small aneurysms (<5 mm) detected by CTA and invasive cerebral angiography (or surgery) were retrospectively enrolled and randomly split into training (81%) and internal validation (19%) sets to derive and validate the proposed machine learning models (support vector machine, random forest, logistic regression, and multilayer perceptron). Hemodynamic parameters were obtained using computational fluid dynamics simulation. External validation was performed in other hospitals to test the models. RESULTS: The support vector machine performed the best with areas under the curve of 0.88 (95% CI, 0.85-0.92) and 0.91 (95% CI, 0.74-0.98) in the training and internal validation datasets, respectively. Feature ranks suggested hemodynamic parameters, including stable flow pattern, concentrated inflow streams, and a small (<50%) flow-impingement zone, and the oscillatory shear index coefficient of variation, were the best predictors of aneurysm rupture. The support vector machine showed an area under the curve of 0.82 (95% CI, 0.69-0.94) in the external validation dataset, and no significant difference was found for the areas under the curve between internal and external validation datasets (P = .21). CONCLUSIONS: This study revealed that machine learning had a good performance in predicting the rupture status of small aneurysms in both internal and external datasets. Aneurysm hemodynamic parameters were regarded as the most important predictors.

Artificial Intelligence in the Management of Intracranial Aneurysms: Current Status and Future Perspectives.

Intracranial aneurysms with subarachnoid hemorrhage lead to high morbidity and mortality. It is of critical importance to detect aneurysms, identify risk factors of rupture, and predict treatment response of aneurysms to guide clinical interventions. Artificial intelligence has received worldwide attention for its impressive performance in image-based tasks. Artificial intelligence serves as an adjunct to physicians in a series of clinical settings, which substantially improves diagnostic accuracy while reducing physicians' workload. Computer-assisted diagnosis systems of aneurysms based on MRA and CTA using deep learning have been evaluated, and excellent performances have been reported. Artificial intelligence has also been used in automated morphologic calculation, rupture risk stratification, and outcomes prediction with the implementation of machine learning methods, which have exhibited incremental value. This review summarizes current advances of artificial intelligence in the management of aneurysms, including detection and prediction. The challenges and future directions of clinical implementations of artificial intelligence are briefly discussed.