Objective To investigate a modified robotized hydraulictensor for management of the ligament balance in the total knee arthroplasty. Methods The effect of the modified robotized hydraulic tensor on the mechanical behaviour of the ligament system balance in the total knee arthroplasty was analyzed andthe related information was obtained. Results The robotized hydraulic tensor acted as a tensorsensor system, which could assist the surgeon by providing thequantitative information to align the lower limb in extension, equalize the articular spaces in extension and flexion, balance the internal and external forces, and define the femoral component rotation, and by providing the information toplan the releasing of the soft tissues and the rotating of the femoral component. Conclusion The modified robotized hydraulic tensor can enable the surgeon to properly manage the ligament balance in the total knee arthroplasty.
Objective To explore the effectiveness of computer-aided technology in the treatment of primary elbow osteoarthritis combined with stiffness under arthroscopy. Methods The clinical data of 32 patients with primary elbow osteoarthritis combined with stiffness between June 2018 and December 2020 were retrospectively analyzed. There were 22 males and 10 females with an average age of 53.4 years (range, 31-71 years). X-ray film and three-dimensional CT examinations showed osteophytes of varying degrees in the elbow joint. Loose bodies existed in 16 cases, and there were 7 cases combined with ulnar nerve entrapment syndrome. The median symptom duration was 2.5 years (range, 3 months to 22.5 years). The location of bone impingement from 0° extension to 140° flexion of the elbow joint was simulated by computer-aided technology before operation and a three-dimensional printed model was used to visualize the amount and scope of impinging osteophytes removal from the anterior and posterior elbow joint to accurately guide the operation. Meanwhile, the effect of elbow joint release and impinging osteophytes removal was examined visually under arthroscopy. The visual analogue scale (VAS) score, Mayo elbow performance score (MEPS), and elbow range of motion (extension, flexion, extension and flexion) were compared between before and after operation to evaluate elbow function. Results The mean operation time was 108 minutes (range, 50-160 minutes). All 32 patients were followed up 9-18 months with an average of 12.5 months. There was no other complication such as infection, nervous system injury, joint cavity effusion, and heterotopic ossification, except 2 cases with postoperative joint contracture at 3 weeks after operation due to the failure to persist in regular functional exercises. Loose bodies of elbow and impinging osteophytes were removed completely for all patients, and functional recovery was satisfactory. At last follow-up, VAS score, MEPS score, extension, flexion, flexion and extension range of motion significantly improved when compared with preoperative ones (P<0.05). Conclusion Arthroscopic treatment of primary elbow osteoarthritis combined with stiffness using computer-aided technology can significantly reduce pain, achieve satisfactory functional recovery and reliable effectiveness.
ObjectiveTo investigate the application and technical essentials of computer-assisted navigation in the surgical management of periacetabular fractures and pelvic fractures. MethodsBetween May 2010 and May 2011, 39 patients with periacetabular or anterior and posterior pelvic ring fractures were treated by minimally invasive fixation under computer-assisted navigation and were followed up more than 2 years, and the clinical data were analyzed retrospectively. There were 21 males and 18 females, aged 15-64 years (mean, 36 years). Fractures were caused by traffic accident in 23 cases, crush injury in 6 cases, and falling from height in 10 cases. Of them, 6 cases had acetabular fractures; 6 cases had femoral neck fractures; 18 cases had dislocation of sacroiliac joint; and 15 cases had anterior pelvic ring injuries. All patients were treated with closed or limited open reduction and screw fixations assisted with navigation. ResultsEighty-nine screws were inserted during operation, including 8 in the acetabulum, 18 in the neck of the femur, 33 in the sacroiliac joint, and 30 in the symphysis pubis and pubic rami. The mean time of screw implanted was 20 minutes (range, 11-38 minutes), and the average blood loss volume was 20 mL (range, 10-50 mL). The postoperative pelvic X-ray and three dimensional CT scan showed good reduction of fractures and good position of the screws. No incision infection, neurovascular injury, or implant failure occurred. All patients were followed up 27-33 months with an average of 29.6 months. The patients could walk with full weight loading at 6-12 weeks after operation (mean, 8 weeks); at last follow-up, the patients could walk on the flat ground, stand with one leg, and squat down, and they recovered well enough to do their job and to live a normal life. ConclusionMinimally invasive fixation under computer-assisted navigation may be an excellent method to treat some specific types of periacetabular and anterior and posterior pelvic ring fractures because it has the advantages of less trauma and blood loss, lower complication incidence, and faster recovery.
ObjectiveTo compare the application effects between personal specific instrumentation (PSI) and computer-assisted navigation surgery (CAS) in total knee arthroplasty (TKA). MethodsThe literature comparing the application effects of PSI and CAS in TKA in recent years was widely consulted, and the difference between PSI-TKA and CAS-TKA in operation time, lower limb alignment, blood loss, and knee function were compared. ResultsCompared to CAS-TKA, PSI-TKA simplifies operation procedures and shortens operation time but probably has worse lower limb alignment. It is still controversial in comparison of perioperative blood loss and knee function between two techniques. ConclusionPSI-TKA and CAS-TKA both have advantages and disadvantages, and their differences need to be confirmed by further high-quality clinical trial.
Clinically, non-contrastive computed tomography (NCCT) is used to quickly diagnose the type and area of stroke, and the Alberta stroke program early computer tomography score (ASPECTS) is used to guide the next treatment. However, in the early stage of acute ischemic stroke (AIS), it’s difficult to distinguish the mild cerebral infarction on NCCT with the naked eye, and there is no obvious boundary between brain regions, which makes clinical ASPECTS difficult to conduct. The method based on machine learning and deep learning can help physicians quickly and accurately identify cerebral infarction areas, segment brain areas, and operate ASPECTS quantitative scoring, which is of great significance for improving the inconsistency in clinical ASPECTS. This article describes current challenges in the field of AIS ASPECTS, and then summarizes the application of computer-aided technology in ASPECTS from two aspects including machine learning and deep learning. Finally, this article summarizes and prospects the research direction of AIS-assisted assessment, and proposes that the computer-aided system based on multi-modal images is of great value to improve the comprehensiveness and accuracy of AIS assessment, which has the potential to open up a new research field for AIS-assisted assessment.
Objective To investigate the value of computer-aided design (CAD) in defining the resection boundary, reconstructing the pelvis and hip in patients with pelvis tumors. Methods Between November 2006 and April 2009, 5 cases of pelvis tumors were treated surgically using CAD technology. There were 3 males and 2 females with an average age of 36.4 years (range, 24-62 years). The cause was osteosarcoma, giant cell tumor of bone, and angiosarcoma in 1 case, respectively,and chondrosarcoma in 2 cases. According to the Enneking system for staging benign and mal ignant musculoskeletal tumors, regions I, I + II, III, IV, and I + IV is in 1 case, respectively. According to the principle of reverse engineering, 5 patients with pelvis tumors were checked with lamellar CT/MRI scanning, whose two-dimensional data were obtained in disease area. The three-dimensional reconstruction of pelvic anatomical model, precise resection boundary of tumor, individual surgical template, individual prosthesis, and surgical simulation were precisely made by computer with CAD software. Based on the proposal of CAD, the bone tumor was resected accurately, and allograft il ium with internal fixation instrument or allogeneic il ium with personal ized prosthetic replacement were used to reconstruct the bone defect after tumor was resected. Results The operation was successfully performed in 5 cases. The average operation time was 7.9 hours, and the average blood loss was 3 125 mL. Hemorrhage and cerebrospinal fluid leakage occurred in 1 case, respectively, and were cured after debridement. Five patients were followed up from 24 to 50 months (mean, 34.5 months). All patients began non-weight bearing walk with double crutches at 4-6 weeks after operation, and began walk at 3-6 months after operation. Local recurrence developed in 2 patients at 18 months after operation, and resection and radiotherapy were performed. According to International Society of Limb Salvage criteria for curative effectiveness of bone tumor l imb salvage, the results were excellent in 2 and good in 3. Conclusion The individual surgical template, individual prosthesis, and surgical simulation by CAD ensure the precision and rel iabil ity of pelvis tumors resection. The CAD technology promotes pelvis tumor resection and the reconstruction of pelvis to individual treatment stage, and good curative effectiveness can be obtained.
To enhance the accuracy of computer-aided diagnosis of adolescent depression based on electroencephalogram signals, this study collected signals of 32 female adolescents (16 depressed and 16 healthy, age: 16.3 ± 1.3) with eyes colsed for 4 min in a resting state. First, based on the phase synchronization between the signals, the phase-locked value (PLV) method was used to calculate brain functional connectivity in the θ and α frequency bands, respectively. Then based on the graph theory method, the network parameters, such as strength of the weighted network, average characteristic path length, and average clustering coefficient, were calculated separately (P < 0.05). Next, using the relationship between multiple thresholds and network parameters, the area under the curve (AUC) of each network parameter was extracted as new features (P < 0.05). Finally, support vector machine (SVM) was used to classify the two groups with the network parameters and their AUC as features. The study results show that with strength, average characteristic path length, and average clustering coefficient as features, the classification accuracy in the θ band is increased from 69% to 71%, 66% to 77%, and 50% to 68%, respectively. In the α band, the accuracy is increased from 72% to 79%, 69% to 82%, and 65% to 75%, respectively. And from overall view, when AUC of network parameters was used as a feature in the α band, the classification accuracy is improved compared to the network parameter feature. In the θ band, only the AUC of average clustering coefficient was applied to classification, and the accuracy is improved by 17.6%. The study proved that based on graph theory, the method of feature optimization of brain function network could provide some theoretical support for the computer-aided diagnosis of adolescent depression.
Objective To improve the accuracy of the acetabular component placement using the nonimage based surgical navigation system. Methods Twenty-three patients (14 males, 9 females; age, 28-55 years;26 hips）with hip disease underwent the total hip arthroplasty (THA) using the nonimage based surgicalnavigation system from February 2004 to April 2006. Rheumatoid arthritis was found in 3 patients (3 hips), necrosis of the femoral head in 6 patients (6 hips), and osteoarthritis in 14 patients (16 hips). All the patients were randomly divided into the following 2 groups: the navigated group (11 patients, 13 hips), treated by THA using the nonimage based surgical navigation system; and the control group (12 patients, 13 hips), treated by the traditional THA. According to thedesign of the study, the acetabular component was placed in the best inclination angle (45°) and the anteversion angle (15°). The postoperative component position was examined. Results No fracture, dislocation, infection or injury to the sciatic nerve was found. In the navigated group, the inclination and the anteversion reached 15.4±1.4° and 45.5±1.3°, respectively. In the control group,the inclination and the anteversion were 13.9±7.6° and 43.7±6.4°, respectively. The inclination difference was considered statistically significant (Plt;0.01). All the patients were followed up for 10-40 months,averaged 26 months. In the navigated group, the postoperative average Harris hip score was 95 (range,85-110), with an excellent result in 11 hips and a good result in 2 hips. In the control group, the postoperative average Harris hip score was 92 (range,75-110), with an excellent result in 9 hips, a good result in 3 hips, and a fair result in 1 hip. The Harris hip score difference was considered statistically significant (Plt;0.05). There was a significantly better result obtained in the navigated group than in the control group. Conclusion The acetabular component can be implanted accurately by the nonimage based surgical navigation system, which can reduce the incidence of the loosening of the prostheses and has an important value in clinical practice.
This paper performs a comprehensive study on the computer-aided detection for the medical diagnosis with deep learning. Based on the region convolution neural network and the prior knowledge of target, this algorithm uses the region proposal network, the region of interest pooling strategy, introduces the multi-task loss function: classification loss, bounding box localization loss and object rotation loss, and optimizes it by end-to-end. For medical image it locates the target automatically, and provides the localization result for the next stage task of segmentation. For the detection of left ventricular in echocardiography, proposed additional landmarks such as mitral annulus, endocardial pad and apical position, were used to estimate the left ventricular posture effectively. In order to verify the robustness and effectiveness of the algorithm, the experimental data of ultrasonic and nuclear magnetic resonance images are selected. Experimental results show that the algorithm is fast, accurate and effective.
The convolutional neural network (CNN) could be used on computer-aided diagnosis of lung tumor with positron emission tomography (PET)/computed tomography (CT), which can provide accurate quantitative analysis to compensate for visual inertia and defects in gray-scale sensitivity, and help doctors diagnose accurately. Firstly, parameter migration method is used to build three CNNs (CT-CNN, PET-CNN, and PET/CT-CNN) for lung tumor recognition in CT, PET, and PET/CT image, respectively. Then, we aimed at CT-CNN to obtain the appropriate model parameters for CNN training through analysis the influence of model parameters such as epochs, batchsize and image scale on recognition rate and training time. Finally, three single CNNs are used to construct ensemble CNN, and then lung tumor PET/CT recognition was completed through relative majority vote method and the performance between ensemble CNN and single CNN was compared. The experiment results show that the ensemble CNN is better than single CNN on computer-aided diagnosis of lung tumor.