Objective To explore the program for calculating the necrotic articular surface area (NASA) and the ratio of NASA to whole articular surface area (WASA) of osteonecrosis of the femoral head (ONFH), to verify the accuracy of this calculation and to predict the collapse of the femoral head clinically using this program. Methods From June 2001 to June 2003, The specimens of the necrotic femoral head from eight patients (13 hips) were obtained by total hip arthroplasty. The magnetic resonance imaging (MRI) was taken in all patients before operation. According to a series of T1-weight pictures, the NASA and the ratio of NASA to WASA were calculated by designing program. The specimens of the necrotic femoral head were sawed into lays similar to MRI pictures using the coordinate paper stick on the auricular surface, the data processing were done by analytic instrument for pictures. The data of both were analyzed statistically by software SPSS 10.0 edition. The NASA and the ratio of NASA to WASA were calculated on MRI in ARCO Stage Ⅰ, Ⅱ 16 patients (25 hips) with non-operation. Follow-up was done to the patients with collapse of the femoral head and to the patients with no collapse for at least 24 months. The data were compared in collapse group and non-collapse group. Results There were no significant differences between MRI pictures calculation and specimens measurement (NASA: 0.412, ratio of NASA to WASA: 0.812, Pgt;0.05). Of the 25 hips followed up, collapse occurred in 17 hips. NASA was 31.06±8.10 cm2, (95% CI: 26.58 to 35.55)，the ratio of NASA to WASA was 58.91%±15.11%, (95% CI: 51.14to 66.68). No collapse appeared in 8 hips. NASA was 14.16±9.32 cm2(95% CI: 6.04 to 21.95), the ratio of NASA to WASA was 29.48%±19.76%(95% CI: 12.97to 45.99). The ratio in the patients with collapse was beyond 33%. Conclusion The NASA and the ratio of NASA to WASA in patients withONFH can be accurately calculated with the MRI pictures. The possibility of collapse can be predicted by this method. As it is complicated in operation, improvement should be made in order to put itinto clinical use.
ObjectivesTo systematically review the clinical efficacy of three-dimensional (3D) visualization vs. two-dimensional (2D) imaging technique in hepatectomy.MethodsPubMed, EMbase, The Cochrane Library, CBM, CNKI, WanFang Data and VIP databases were electronically searched to collect clinical trials which compared 3D visualization with conventional 2D imaging technique for hepatectomy from inception to September 2017. Two reviewers independently screened literature, extracted data and assessed the risk bias of included studies, and then, meta-analysis was performed by using RevMan 5.3 software.ResultsA total of 11 studies involving 953 patients were included. The results of meta-analysis showed that: compared to 2D imaging technique, 3D visualization technique could improve R0 resection rate (OR=2.91, 95%CI 1.31 to 6.43, P=0.009), had lower incidence of postoperative complication (OR=0.55, 95%CI 0.38 to 0.80, P=0.002), less amount of blood transfusion in operation (MD=–96.05, 95%CI –126.78 to –65.31, P<0.000 01), lower discrepancy range between the volume of the predicted liver resection and actual resection volume (MD=–94.38, 95%CI –185.46 to –3.30,P=0.04), shorter operation time (MD=–33.58, 95%CI –60.09 to –7.08, P=0.01), and lower intraoperative blood loss (MD=–79.70, 95%CI –139.86 to –19.53, P=0.009), the differences were statistically significant. There were no statistical differences between two groups in postoperative hospital stay time (MD=–0.75, 95%CI –2.45 to 0.95, P=0.39).ConclusionsThe current evidence shows that application of 3D visualization technique in hepatectomy can predict the liver resection volume more accurately, improve the R0 resection rate, shorten operation time, decrease intraoperative blood transfusion volume and the amount of bleeding, and reduce the incidence of postoperative complications. Due to limited quality and quantity of the included studies, more high-quality studies are required to verify above conclusion.
Objective To summarize and analyze the MRI imaging findings of advanced gastric cancer in order to improve the level of image diagnosis. Methods The plain and dynamic enhanced MRI findings in 8 volunteers and 30 patients with pathologically proven advanced gastric cancer were retrospectively analyzed. Results The stomach wall of advanced gastric cancer was inhomogeneous thickening with iso intensity or little hypo intensity signal on T1WI， and iso intensity or little hyper intensity signal on T2WI. Cases with serosal infiltration， the serous appearred indistinctly and rough. In some cases， the low signal zones between gastic wall and fat space were interrupted on T1WI out-of-phase image. Cases with adjacent organs invaded， the fat space was rough or disappeared. The lesions showed obvious irregular or hierarchy enhancement on MRI dynamic contrast scanning. Conclusions Inhomogeneous thickening of gastic wall with abnormal signal intensity， indistinctness or disappearance of fat space， irregular or hierarchy enhancement are very valuable as diagnostic signs in patients suspective of advanced gastric cancer.
Diffusion tensor imaging (DTI) is a rapid development technology in recent years of magnetic resonance imaging. The diffusion tensor interpolation is a very important procedure in DTI image processing. The traditional spectral quaternion interpolation method revises the direction of the interpolation tensor and can preserve tensors anisotropy, but the method does not revise the size of tensors. The present study puts forward an improved spectral quaternion interpolation method on the basis of traditional spectral quaternion interpolation. Firstly, we decomposed diffusion tensors with the direction of tensors being represented by quaternion. Then we revised the size and direction of the tensor respectively according to different situations. Finally, we acquired the tensor of interpolation point by calculating the weighted average. We compared the improved method with the spectral quaternion method and the Log-Euclidean method by the simulation data and the real data. The results showed that the improved method could not only keep the monotonicity of the fractional anisotropy (FA) and the determinant of tensors, but also preserve the tensor anisotropy at the same time. In conclusion, the improved method provides a kind of important interpolation method for diffusion tensor image processing.
With the change of medical diagnosis and treatment mode, the quality of medical image directly affects the diagnosis and treatment of the disease for doctors. Therefore, realization of intelligent image quality control by computer will have a greater auxiliary effect on the radiographer’s filming work. In this paper, the research methods and applications of image segmentation model and image classification model in the field of deep learning and traditional image processing algorithm applied to medical image quality evaluation are described. The results demonstrate that deep learning algorithm is more accurate and efficient than the traditional image processing algorithm in the effective training of medical image big data, which explains the broad application prospect of deep learning in the medical field. This paper developed a set of intelligent quality control system for auxiliary filming, and successfully applied it to the Radiology Department of West China Hospital and other city and county hospitals, which effectively verified the feasibility and stability of the quality control system.
Objective To investigate application of medical digital imaging systems and computer technologies in orthpedics. Methods The main computer-assisted surgery systems comprise the four following subcategories. Results ①A collection and recording process for digital data on each patient, including preoperative images (CT scans, MRI, standard X-rays), intraoperative visualization (fluoroscopy, ultrasound), and intraoperative position and orientation of surgical instruments or bone sections (using 3D localisers). Data merging based on the matching of preoperative imaging (CT scans, MRI, standard X-rays) and intraoperative visualization (anatomical landmarks, or bone surfaces digitized intraoperatively via 3D localiser; intraoperative ultrasound images processed for delineationof bone contours). ②In cases where only intraoperative images are used for computer-assisted surgical navigation, the calibration of the intraoperative imaging system replaces the merged data system, which is then no longer necessary. ③A system that provides aid in decisionmaking, so that the surgical approach is planned on basis of multimodal information: the interactive positioning of surgical instruments or bone sections transmitted via pre- or intraoperative images, display of elements to guide surgicalnavigation (direction, axis, orientation, length and diameter of a surgical instrument, impingement, etc.). And ④ A system that monitors the surgical procedure, thereby ensuring that the optimal strategy defined at the preoperative stage is taken into account. Conclusion It is possible that computer-assisted orthopedic surgery systems will enable surgeons to better assess the accuracy and reliability of the various operative techniques, an indispensable stage in the optimization of surgery.
The growing rate of public health problem for increasing number of people afflicted with poor sleep quality suggests the importance of developing portable sleep electroencephalogram (EEG) monitoring systems. The system could record the overnight EEG signal, classify sleep stages automatically, and grade the sleep quality. We in our laboratory collected the signals in an easy way using a single channel with three electrodes which were placed in frontal position in case of the electrode drop-off during sleep. For a test, either silver disc electrodes or disposable medical electrocardiographic electrodes were used. Sleep EEG recorded by the two types of electrodes was compared to each other so as to find out which type was more suitable. Two algorithms were used for sleep EEG processing, i.e. amplitude-integrated EEG (aEEG) algorithm and sample entropy algorithm. Results showed that both algorithms could perform sleep stage classification and quality evaluation automatically. The present designed system could be used to monitor overnight sleep and provide quantitative evaluation.
ObjectiveTo find out the risk factors affecting the prognoses and microvascular invasion (MVI) of patients with China Liver Cancer Staging-stageⅠ a (CNLC Ⅰ a) hepatocellular carcinoma (HCC). MethodsBased on the established inclusion and exclusion criteria, the clinicopathologic information and follow-up data of patients with CNLC Ⅰ a HCC were retrospectively collected, who underwent radical resection in the West China Hospital of Sichuan University from Jan. 2012 to Dec. 2016. The Cox proportional hazards regression was utilized to analyze the risk factors affecting the prognosis of patients with CNLC Ⅰ a HCC, and the non-conditional logistic regression was utilized to analyze the preoperative clinical indicators associating with MVI. ResultsA total of 300 patients with CNLC Ⅰ a HCC were included in this study, among which 51 (17.0%) cases accompanied with MVI. The follow-up period ranged from 2 to 104 months (median 39 months), with a recurrence time ranging from 2 to 104 months (median 52 months), and an overall survival time ranging from 3 to 104 months (median 98 months). During the follow-up period, postoperative recurrence occurred in 145 (48.3%) cases. The Cox proportional hazards regression analysis revealed that: tumor diameter >3 cm, presences of MVI and satellite nodules increased the risk of shortened recurrence time for the patients with CNLC Ⅰ a HCC (P<0.05); Factors including gamma-glutamyltranspeptidase level >60 U/L, tumor low differentiation, presences of MVI and satellite nodules were associated with shortened overall survival time for the patients with CNLC Ⅰ a HCC (P<0.05). The preoperative alpha-fetoprotein level ≥400 μg/L and tumor diameter >3 cm increased the risk of presence of MVI for the patients with CNLC Ⅰ a HCC [χ2=3.059, OR(95%CI)=2.357(1.047, 5.306), P=0.038; χ2=3.002, OR(95%CI)=2.301(1.026, 5.162), P=0.043]. ConclusionThe results of this study suggest that adopting corresponding strategies to address the risk factors affecting prognosis of patients with CNLC Ⅰ a HCC and the risk factors associated with MVI can have a significant clinical impact on improving surgical treatment outcomes for these patients.
Hepatic sinusoidal obstruction syndrome (HSOS) can be easily missed or misdiagnosed as Budd-Chiari syndrome in clinical practice. The authors displayed the imaging pictures of one patient with HSOS and made a brief description of typical imaging features, underlying pathophysiological mechanisms, and differential diagnosis of HSOS, with the hope of improving the understanding of HSOS and reducing the rates of leak diagnosis or misdiagnosis.
Objective To investigate the value of indocyanine green fluorescence imaging in common bile duct reexploration. Methods The clinical data of 32 patients who underwent open common bile duct reexploration in the Affiliated Hospital of Southwest Medical University from January 2018 to December 2020 were collected retrospectively. All patients divided into the control group (conventional exploration group, 20 patients) and the fluorescence imaging group (using indocyanine green fluorescence imaging, 12 patients) according to the operational manner. The intraoperative and postoperative results of two groups were analyzed. Results The operative time [(165.2±6.9) min vs. (130.8±5.5) min], the time to find extrahepatic bile duct [(43.9±3.8) min vs. (23.1±4.1) min] and the amount of bleeding [(207.7±7.7) mL vs. (127.5±15.3) mL] in the control group were longer or more than those in the fluorescence imaging group (P<0.05). The incidence of postoperative infection in the control group [7 cases (35.0%) vs. 0 cases (0.0%)] and the length of hospital stay [(10.8±2.8) d vs. (7.1±1.3) d] were higher or longer than those in the fluorescence imaging group (P<0.05). There were no significant difference between the two groups in the incidence of postoperative bile fistula [6 cases (30.0%) vs. 2 cases (16.7%)] and the incidence of residual stones [3 cases (15.0%) vs. 3 cases (25.0%), P＞0.05]. Conclusion Indocyanine green fluorescence imaging appears to be a feasible, expeditious, useful, and effective imaging method while performing reexploration.