Objective To explore the predicting value of quantitative CT features of peritumoral nodules for the risk of thymic epi-thelial tumors(TETs).Methods A total of 108 patients with TETs confirmed by pathology were analyzed retrospectively.Accord-ing to the WHO classification of thymic tumors,the patients were divided into high-risk group and low-risk group.The quantitative CT features included the long diameter,volume,mass,and distance between peritumoral nodules and main tumor.The values of these features were assessed using the Mann-Whitney U test,and the thresholds were determined using the receiver operating characteristic(ROC)curve.Results Among 108 TETs patients,there were 45 patients with peritumoral nodules on chest CT,including 30 high-risk group and 15 low-risk group,respectively.Interobserver consistencies were well with intraclass correlation coefficient(ICC)between 0.886 and 0.907.The long diameter,volume,and mass of peritumoral nodules were greater in the high-risk group than in the low-risk group(P＜0.05),and there was no significant difference in the distance to the main tumor(P＞0.05).The mass of peritumoral nodules had the best diagnostic performance in predicting TETs risk,and the thresholds was 27.84 mg with the area under the curve(AUC)of 0.889,sensitivity of 83.3％,specificity of 87.5％,and accuracy of 85.3％,respectively.Conclusion The quantitative CT features of peritumoral nodules especially mass can be useful in predicting the risk of TETs.

Objective:To investigate the application status of emergency radiology in China, and to provide data support for the standardized development, scientific management and big data research of emergency radiology.Methods:From August 12th to October 19th, 2022, a questionnaire survey was conducted through WeChat"Questionnaire Star"to send targeted questionnaires to investigate the relevant data of the current status of emergency radiology in China, mainly including digital radiography (DR) and computed tomography (CT). This study was initiated by the Chinese Emergency Radiology Database Collaboration Group, and comprehensively investigated emergency imaging personnel, equipment, workload, critical value reporting process, and artificial intelligence (AI) application status.Results:There were 123 hospitals in the study. The survey showed that emergency DR/CT reports were mainly completed by residents and above (69.1%). There were 21 DR brands, 10 CT brands and 8 MR brands used for emergency imaging examinations. The median number of DR examinations in tertiary hospitals and secondary hospitals investigated from January to June 2022 was 4 642 and 2 015 cases respectively, and the median number of CT examinations was 16 512 and 3 762 cases respectively. The average single-shift workload of DR in the emergency radiology department during the day and night shift in tertiary hospitals was mainly ≤20 copies and 21-50 copies, and the average single-shift workload of CT in the emergency radiology department during the day and night shift was mainly 21-50 copies and 51-100 copies, while the average single-shift workload of DR/CT in the emergency radiology department during the day/night shift in secondary hospitals was mainly ≤20 copies. In terms of critical value reporting process, 74.8% of emergency imaging doctors and 84.6% of emergency imaging technicians took the way of phone/text message to notify the clinical doctor or the patients′ family. The overall deployment rate of AI in emergency imaging was about 60.2%. 75% of the respondents believed that in the future, AI can improve emergency radiology work from aspects such as emergency screening, aided diagnosis and process optimization.Conclusions:The emergency medical imaging mainly based on DR and CT has the current situations such as generally low seniority of doctors, diverse brands of imaging equipments, large volume of examinations and intense workload per doctor, especially in tertiary hospitals, and dependence on traditional means for critical value reporting. At present, AI is emerging in the field of emergency imaging, and there is still a long way to go to play the huge potential of AI in the intelligent whole process of emergency imaging in the future.

Objective To compare the fetal imaging quality in different positions and the maternal comfort level in a super large-bore magnet,so as to estimate the application value of left lying position scanning in fetal brain MRI.Methods A total of 32 pregnant women in the third trimester who underwent fetal brain imaging in a super large-bore magnet(75cm)were collected.Each subject completed left lying position and supine position scanning and scored the comfort of the two.Radiologists scored the image subjectively,and objectively measured signal-to-noise ratio(SNR)and contrast-to-noise ratio(CNR)of fetal brain images.Results The comfort score of the left lying position(4.3±0.7)was higher than that of the supine position(3.4±0.7),and the difference was statistically significant(P＜0.001).The subjective score showed that there was no significant difference between the left lying position and the supine position in terms of brain image quality(P＞0.05),which could meet the needs of clinical diagnosis.The objective score showed that SNR of midbrain in left lying position was higher than in supine position(P＜0.05).The CNR of left occipital lobe in left lying position was higher than in supine position(P＜0.05).Conclusion In super large-bore magnet,left lying position scanning is a safe and pregnancy-friendly option that can not only improve maternal comfort level,but also improve fetal brain imaging.

Objective:To evaluate spectral CT metal artifacts reduction (MAR) technique in reducing metal artifacts of spinal implants in a phantom.Methods:Ovine spines were chosen as anthropomorphic phantom. The phantom including the pedicle screws, 3D-printed vertebral body (VB) and mesh cage were examined using spectral CT. Postoperative CT images were reconstructed at 70—140 keV with 10 keV interval of MAR and non-MAR. Artifact index (AI) and signal-to-noise ratio (SNR) were evaluated by CT and SD values in ROIs around the implants. Visibility of bony structures, the artifacts of pedicle screw, 3D-printed VB and mesh cage were subjectively evaluated. Plotting curves of AI and SNR with the increasing keV were drawn. The AI and SNR were compared at lower (70 keV), medium (100 keV) and high (130 keV) level between MAR and non-MAR images using the paired t-test, and the subjective scores were compared using Wilcoxon signed rank-sum test. Results:The AI values around pedicle screws (anterior, posterior and lateral), 3D-printed VB and mesh cage decreased with the increase of keV, while SNR improved in MAR and non-MAR images. The AI values in the anterior, lateral and posterior pedicle screws and lateral titanium implants were significantly lower in MAR than those in non-MAR ( P<0.05). The AI value in posterior 3D-printed vertebral was lower in MAR than that of non-MAR only at 70 keV ( P<0.001). The SNR values in the anterior and posterior pedicle screws, 3D-printed VB increased with the increase of keV, but decreased in other ROIs. In the subjective evaluation, the image scores of MAR were higher than those of non-MAR ( P<0.05). Conclusion:Spectral CT using the MAR reconstruction can effectively reduce metal artifacts of spinal implants. The effect is better in pedicle screw and mesh cage than 3D-printed VB.

Objective:To investigate the accuracy of 3.0 T MR in the diagnosis of full thickness tear and partial thickness tear of the supraspinatus-infraspinatus tendon, and to analyze the causes of missed diagnosis and misdiagnosis of the supraspinatus-infraspinatus tendon tear.Methods:The MRI diagnosis report and arthroscopic surgery records of 210 patients with shoulder joint injuries in Peking University Third Hospital were analyzed retrospectively. Taking the results of arthroscopic surgery as the gold standard, the diagnostic accuracy, sensitivity, specificity, positive predictive value and negative predictive values of 3.0 T MR for full thickness tear and partial thickness tear of the supraspinatus-infraspinatus tendon were calculated, and the reasons of missed diagnosis and misdiagnosis were analyzed.Results:In 210 patients with rotator cuff injury, the diagnostic accuracy, sensitivity, specificity, positive predictive value and negative predictive value of MRI for full thickness tear of the supraspinatus-infraspinatus tendon were 81.4% (171/210), 83.1% (98/118), 79.3% (73/92), 83.7% (98/117) and 78.4% (73/93) respectively. The diagnostic accuracy, sensitivity, specificity, positive predictive value and negative predictive value of MRI for partial tears of the supraspinatus-infraspinatus tendons were 77.6% (163/210), 65.7% (44/67), 83.2% (119/143), 64.7% (44/68) and 83.8% (119/142) respectively. Among the 44 cases of missed diagnosis and misdiagnosis of the supraspinatus-infraspinatus tendon tear, 21 cases (47.7%) occurred in the junction supraspinatus and infraspinatus tendon-osseous (stop). Among the 7 cases of intra-tendon tear of supraspinatus and infraspinatus muscle, 6 cases were misdiagnosed cases, which was the most easily missed diagnosed type of partial tear. The reason for missed diagnosis was that the signal of partial tear was not high (no fluid signal was shown on T 2WI). Complex laceration was also a type of missed diagnosis in partial tears. Among the 4 cases of superior and inferior surface tendons combined with intra-tendon lacerations, 3 cases were missed diagnosed. Conclusion:3.0 T MR has higher accuracy for the diagnosis of full thickness tear and partial thickness tear of supraspinatus-infraspinatus tendon, but there is still a certain rate of misdiagnosis and missed diagnosis. A full understanding of the causes of misdiagnosis and missed diagnosis of MR in the diagnosis of rotator cuff tears of supraspinatus and infraspinatus tendons is helpful to further improve the accuracy of MR in the diagnosis of supraspinatus and infraspinatus tendon injuries of shoulder joint.

Objective:To explore the value of X-ray signs with applying low dose of contrast agent to confirm successful puncture in direct shoulder MR arthrography.Methods:In total 669 patients who underwent shoulder MR arthrography in Peking University Third Hospital from January 2016 to August 2018 were retrospectively analyzed. All patients received the anterior approach puncture in shoulder arthrography. X-ray films were taken after 1-2 ml contrast agent was injected. Six X-ray signs of contrast agent distribution were recorded. MR arthrography findings were used to confirm whether the puncture was success. Kappa analysis was used to verify the consistency between each 2 signs. The accuracy rate of each X-ray sign to confirm the successful puncture was calculated. X-ray signs were paired to define the best diagnostic index of successful puncture.Results:Successful puncture was performed in arthrographies for all 669 cases .The displaying rates of six signs were as follows. Contrast agent distribution at overlapping humeral head away from the needle was 66.8% (447/669), in axillary recess was 64.7% (433/669), in glenohumeral space was 93.9% (628/669), in subscapular bursa was 69.8% (467/669), in sheath of long head tendon of biceps brachii (LHBT) was 1.9% (13/669), between LHBT and supraspinatus tendon was 17.2% (115/669). Consistency of each 2 signs was poor (Kappa<0.2), in which the poorest consistency was found between contrast agent overlapping humeral head away from the needle and contrast agent in glenohumeral space (Kappa=-0.115). With combining the above 2 signs, the accuracy rate for defining successful puncture was 100% (669/669).Conclusion:In direct shoulder arthrography by anterior approach, X-ray signs with low dose of contrast agent can be regard as the method to confirm successful puncture. The accuracy rate of the signs of contrast agent distribution at overlapping humeral head away from the needle or in glenohumeral space to define a successful puncture is 100%.

The cross-fusion research of artificial intelligence technology and spinal surgery represented by machine learning and neural network model is a new research direction and hot issue in the field of artificial intelligence in recent years. The anatomy and disease symptoms of the spine are complex, and the diagnosis and treatment of spinal surgery require rich clinical experience. However, the distribution of medical resources in China is seriously uneven. How to improve the ability of primary medical services so that the most extensive patient groups can benefitis still an urgent problem to be solved. Artificial intelligence is a technical science that researches and develops theories, methods, technologies, and application systems for simulating, extending and expanding human intelligence. With the advent of the era of big data medical technology, artificial intelligence technology may solve this problem by transforming "experts sinking" into "tech sinking" . At present, technologies such as confrontation learning, weakly supervised learning, intensive learning and graph neural networks have become research hotspots in the field of artificial intelligence, and have also played an important role in many fields of clinical medicine. Based on the advantages of deep learning and neural network in disease learning, many spine surgeons combine it with the diagnosis and treatment of cervical spondylosis, low back pain, lumbar degenerative diseases, spinal deformity, spinal tumors, and other spine-related diseases. The rapid location and accurate diagnosis of the disease not only makes it an effective tool for the comprehensive diagnosis of spinal diseases but also provides the basis for the most reasonable treatment options for spinal diseases. In the domestic application of artificial intelligence in the diagnosis and treatment of spinal surgery, it can also solve the problems of difficult diagnosis and complicated treatment of spinal diseases faced by primary doctors, reduce the rate of misdiagnosis and missed diagnosis, and effectively reduce the economic and social burden of spinal diseases. This paper reviews the research progress of artificial intelligence represented by deep learning in the field of diagnosis and treatment of spinal surgery at home and abroad, and the advantages and application prospects of artificial intelligence in the diagnosis and treatment of spinal surgery.

Objective To explore the best percentage of adaptive statistical iterative reconstruction Veo (ASiR-V)in detection of pulmonary nodule by chest ultralow dose CT (ULDCT).Methods 81 patients with pulmonary nodule detected by chest low dose CT (LDCT)underwent a local ULDCT scan at the center of the nodule with a range of 3 cm scan length.LDCT was performed with the mode of the Assist kV (120/100 kV)/Smart mA with noise indices of 14.1 HU and reconstructed with ASiR-V 50% algorithm.ULDCT was acquired at a tube potential of 120 kV and tube current-time product of 2.8 mAs and reconstructed with ASiR-V 50%,70% and 90%algorithms.Subjective and obj ective image qualities,sensitivities of detection and diameter of nodule among all ULDCT images were compared.Results Compared with the radiation dose of LDCT [(0.9 9±0.3 6)mSv],a 90.2% decrease was seen with the ULDCT, for which the calculated mean effective radiation dose was (0.097±0.007)mSv.The noise values of fat and paravertebral muscle for ULDCT reconstructed with ASiR-V 90% were 12.33±1.86 and 14.82±2.6,which were significantly lower than those in the group of ASiR-V 50% (1 9.73±1.98, 21.19±2.46)and the group of ASiR-V 70% (15.79±1.82,17.71±2.50)(P＜0.05).The subjective scores of images reconstructed with ASiR-V 70% (4.13±0.47)were the highest,which were slightly higher than those in 90%groups (4.03±0.38)(P＜0.05).No significant differences for overall sensitivity of nodule detection were observed among the ULDCT reconstructed with ASiR-V 50%(86.42%),ASiR-V 70%(87.04%)and ASiR-V 90% (88.89%)(P＞0.05).The mean nodule diameter measurements were (6.4±2.0)mm,(5.9±2.2)mm,(6.0±2.2)mm and (6.1 ±2.2)mm for LDCT and ULDCT (ASiR-V 50%,70% and 90%),respectively with P＞0.05.Conclusion At extremely low exposure levels,ASiR-V can obviously improve the image qualities of ULDCT,and 90% is the best percentage for lung algorithm reconstruction with a high sensitivity of pulmonary nodule detection.

Objective To explore the value of T1ρin the diagnosis of knee osteoarthritis(OA),and to compare the diagnostic ability of T1ρ, MR and arthroscopy for early patellar cartilage injury.Methods 28 patients underwent T1ρMR imaging.We processed the images and measured T1ρvalues of the normal and damage cartilage.All cases were recorded results of MR and arthroscopy.Results T1ρ sequence could show cartilage clearly,and performed different colour levels,T1ρvalues of normal cartilage were less than 50 ms,and increased with aggravation of cartilage injury.The differences ofⅠ-ⅡandⅢ-Ⅳhad statistically significant.9 cases in grade 0 under MR and arthroscopy performed high values in T1ρ,which similar to gradeⅠ-Ⅱinjury,the diagnosis sensitivity of T1ρfor early cartilage injury was higher than MR and arthroscopy.In addition,arthroscopy and MR had high consistency in the diagnosis of cartilage.Conclusion T1ρcan effectively predict early cartilage injury and knee OA non-invasively,and can detect early cartilageinjury before MR and arthroscopy.

Objective To assess the feasibility of quantitative measurement of subcutaneous and supraclavicular adipose tissue with iterative decomposition of water and fat with echo asymmetry and least square estimation-iron quantification sequence (IDEAL-IQ).Methods Totally 87 normal young female volunteers (20-35 years old) were recruited and divided into body mass index (BMI)＜24 kg/m2 group (n=72) and BMI≥24 kg/m2 group (n=15).Fat fraction (FF) and T2* relaxation rate (R2*) of supraclavicular adipose tissue,chest wall adipose tissue,abdominal wall adipose tissue and liver were measured,respectively.The differences of FF and R2* value of chest wall,subcutaneous and supraclavicular adipose tissue were compared between two groups,and the correlation between FF,R2* value of supraclavicular adipose tissue and BMI was respectively analyzed.Results FF of supraclavicular adipose tissue ([80.99 ± 7.73]％) was lower than that of chest wall subcutaneous adipose tissue ([93.04 ± 1.55] ％,P＜0.001).R2* of supraclavicular adipose tissue ([65.52±23.59]Hz) was higher than that of chest wall subcutaneous adipose tissue ([38.82±7.11]Hz,P＜0.001).The differences of FF and R2* values of supraclavicular adipose tissue,chest wall,abdominal wall subcutaneous adipose tissue and liver were significant between BMI＜24 kg/m2 group and BMI≥24 kg/m2 group (all P＜0.05).There was positive correlation (r=0.601,P＜0.001) between FF of supraclavicular adipose tissue and BMI and negative correlation (r=-0.409,P =0.001) between R2* of supraclavicular adipose tissue and BMI.Conclusion IDEAL-IQ technique can quantitatively assess the difference between subcutaneous and supraclavicular adipose tissue in healthy young women.FF and R2 * value has significant difference between the above mentioned positions.