OBJECTIVE: To compare the effectiveness of O-arm navigation and C-arm navigation for guiding percutaneous long sacroiliac screws in treatment of Denis type Ⅱ sacral fractures. METHODS: A retrospective study was conducted on clinical data of the 46 patients with Denis type Ⅱ sacral fractures between April 2021 and October 2022. Among them, 19 patients underwent O-arm navigation assisted percutaneous long sacroiliac screw fixation (O-arm navigation group), and 27 patients underwent C-arm navigation assisted percutaneous long sacroiliac screw fixation (C-arm navigation group). There was no significant difference in gender, age, causes of injuries, Tile classification of pelvic fractures, combined injury, the interval from injury to operation between the two groups ( P>0.05). The intraoperative preparation time, the placement time of each screw, the fluoroscopy time of each screw during placement, screw position accuracy, the quality of fracture reduction, and fracture healing time were recorded and compared, postoperative complications were observed. Pelvic function was evaluated by Majeed score at last follow-up. RESULTS: All operations were completed successfully, and all incisions healed by first intention. Compared to the C-arm navigation group, the O-arm navigation group had shorter intraoperative preparation time, placement time of each screw, and fluoroscopy time, with significant differences ( P<0.05). There was no significant difference in screw position accuracy and the quality of fracture reduction ( P>0.05). There was no nerve or vascular injury during screw placed in the two groups. All patients in both groups were followed up, with the follow-up time of 6-21 months (mean, 12.0 months). Imaging re-examination showed that both groups achieved bony healing, and there was no significant difference in fracture healing time between the two groups ( P>0.05). During follow-up, there was no postoperative complications, such as screw loosening and breaking or loss of fracture reduction. At last follow-up, there was no significant difference in pelvic function between the two groups ( P>0.05). CONCLUSION Compared with the C-arm navigation, the O-arm navigation assisted percutaneous long sacroiliac screws for the treatment of Denis typeⅡsacral fractures can significantly shorten the intraoperative preparation time, screw placement time, and fluoroscopy time, improve the accuracy of screw placement, and obtain clearer navigation images.
Humans ; Fracture Fixation, Internal/methods* ; Retrospective Studies ; Imaging, Three-Dimensional ; Bone Screws ; Surgery, Computer-Assisted ; Tomography, X-Ray Computed ; Spinal Fractures/surgery* ; Fractures, Bone/surgery* ; Pelvic Bones/injuries* ; Postoperative Complications ; Neck Injuries

The registration of preoperative magnetic resonance (MR) images and intraoperative ultrasound (US) images is very important in the planning of brain tumor surgery and during surgery. Considering that the two-modality images have different intensity range and resolution, and the US images are degraded by lots of speckle noises, a self-similarity context (SSC) descriptor based on local neighborhood information was adopted to define the similarity measure. The ultrasound images were considered as the reference, the corners were extracted as the key points using three-dimensional differential operators, and the dense displacement sampling discrete optimization algorithm was adopted for registration. The whole registration process was divided into two stages including the affine registration and the elastic registration. In the affine registration stage, the image was decomposed using multi-resolution scheme, and in the elastic registration stage, the displacement vectors of key points were regularized using the minimum convolution and mean field reasoning strategies. The registration experiment was performed on the preoperative MR images and intraoperative US images of 22 patients. The overall error after affine registration was (1.57 ± 0.30) mm, and the average computation time of each pair of images was only 1.36 s; while the overall error after elastic registration was further reduced to (1.40 ± 0.28) mm, and the average registration time was 1.53 s. The experimental results show that the proposed method has prominent registration accuracy and high computational efficiency.
Humans ; Imaging, Three-Dimensional/methods* ; Magnetic Resonance Imaging/methods* ; Ultrasonography/methods* ; Algorithms ; Surgery, Computer-Assisted/methods*

Magnetic resonance (MR) imaging is an important tool for prostate cancer diagnosis, and accurate segmentation of MR prostate regions by computer-aided diagnostic techniques is important for the diagnosis of prostate cancer. In this paper, we propose an improved end-to-end three-dimensional image segmentation network using a deep learning approach to the traditional V-Net network (V-Net) network in order to provide more accurate image segmentation results. Firstly, we fused the soft attention mechanism into the traditional V-Net's jump connection, and combined short jump connection and small convolutional kernel to further improve the network segmentation accuracy. Then the prostate region was segmented using the Prostate MR Image Segmentation 2012 (PROMISE 12) challenge dataset, and the model was evaluated using the dice similarity coefficient (DSC) and Hausdorff distance (HD). The DSC and HD values of the segmented model could reach 0.903 and 3.912 mm, respectively. The experimental results show that the algorithm in this paper can provide more accurate three-dimensional segmentation results, which can accurately and efficiently segment prostate MR images and provide a reliable basis for clinical diagnosis and treatment.
Male ; Humans ; Prostate/diagnostic imaging* ; Image Processing, Computer-Assisted/methods* ; Magnetic Resonance Imaging/methods* ; Imaging, Three-Dimensional/methods* ; Prostatic Neoplasms/diagnostic imaging*

OBJECTIVE: To investigate the feasibility of MRI three-dimensional (3D) reconstruction model in quantifying glenoid bone defect by comparing with CT 3D reconstruction model measurement. METHODS: Forty patients with shoulder anterior dislocation who met the selection criteria between December 2021 and December 2022 were admitted as study participants. There were 34 males and 6 females with an average age of 24.8 years (range, 19-32 years). The injury caused by sports injury in 29 cases and collision injury in 6 cases, and 5 cases had no obvious inducement. The time from injury to admission ranged from 4 to 72 months (mean, 28.5 months). CT and MRI were performed on the patients' shoulder joints, and a semi-automatic segmentation of the images was done with 3D slicer software to construct a glenoid model. The length of the glenoid bone defect was measured on the models by 2 physicians. The intra-group correlation coefficient ( ICC) was used to evaluate the consistency between the 2 physicians, and Bland-Altman plots were constructed to evaluate the consistency between the 2 methods. RESULTS: The length of the glenoid bone defects measured on MRI 3D reconstruction model was (3.83±1.36) mm/4.00 (0.58, 6.13) mm for physician 1 and (3.91±1.20) mm/3.86 (1.39, 5.96) mm for physician 2. The length of the glenoid bone defects measured on CT 3D reconstruction model was (3.81±1.38) mm/3.80 (0.60, 6.02) mm for physician 1 and (3.99±1.19) mm/4.00 (1.68, 6.38) mm for physician 2. ICC and Bland-Altman plot analysis showed good consistency. The ICC between the 2 physicians based on MRI and CT 3D reconstruction model measurements were 0.73 [95% CI (0.54, 0.85)] and 0.80 [95% CI (0.65, 0.89)], respectively. The 95% CI of the difference between the two measurements of physicians 1 and 2 were (-0.46, 0.49) and (-0.68, 0.53), respectively. CONCLUSION The measurement of glenoid bone defect based on MRI 3D reconstruction model is consistent with that based on CT 3D reconstruction model. MRI can be used instead of CT to measure glenoid bone defects in clinic, and the soft tissue of shoulder joint can be observed comprehensively while reducing radiation.
Male ; Female ; Humans ; Young Adult ; Adult ; Imaging, Three-Dimensional/methods* ; Tomography, X-Ray Computed/methods* ; Joint Instability ; Shoulder Joint/diagnostic imaging* ; Shoulder Dislocation ; Magnetic Resonance Imaging/methods*

OBJECTIVE: To explore correlation between femoral mechanical axis and Blumensaat line (FMBL) angle of knee joint (angle between Blumensaat line and femoral mechanical axis), α angle (angle between Blumensaat line and axis of distal femur in sagittal plane) on EOS biplane imaging and non-contact anterior cruciate ligament(ACL) injury, and evaluate angle for its accuracy in predicting the populations prone to non-contact ACL injury. METHODS: From February 2018 to October 2020, EOS imaging and clinical data from 88 patients (176 knees) with unilateral non-contact ACL injury were retrospectively analyzed, including 53 males and 35 females, aged from 18 to 45 years old with an average of (30.3±6.2) years old, 48 patients on the left side and 40 patients on the right side. The patients were divided into ACL-affected group and ACL-health group according to side of ACL injuries, and 51 patients (51 knees) with non-ACL identified from EOS database were included in normal control group, including 28 males and 23 females, aged from 20 to 44 years old with an average of (31.6±5.5) years old, 26 patients on the left side and 25 patients on the right side. Full-length EOS imaging of skeleton extremitatis inferioris among three groups were reconstructed to 3D images of skeletal system with EOS software, and then FMBL angle and α angle were measured on the images. Univariate binary Logistic regression analysis was performed to determine the influence of the univariate(FMBL angle or α angle) on ACL status(normal or torn). And the angle cutoff value for univariate was selected based on receiver operating characteristics curve (ROC) to got the best accuracy. RESULTS: There was no statistically significant difference in age, gender and side distribution between ACL-injured group and normal control group(P>0.05). Statistical analyses (one-way ANOVA) indicated no significant difference in FMBL angle between ACL-injured knee group (32.8±2.3)° and ACL-injured contralateral knee group(32.5±2.3)°(P>0.05), but the values between two groups were significantly lower than that in normal control group (37.0±2.0)°(P<0.001). There was no statistically significant difference in α angle among three groups (P>0.05). Univariate binary Logistic regression analysis demonstrated that FMBL angle was risk factor for non-contact ACL injury[OR=0.433, 95%CI(0.330, 0.569), P<0.001]. The area under ROC curve for FMBL angle was 0.909[95%CI(0.861, 0.958), P<0.001], and the sensitivity and specificity were 70.5% and 98.0% respectively, cut-off value was 33.7°. CONCLUSION FMBL angle formed by Blumensaat line and femoral mechanical axis is one of the risk factors for non-contact ACL injury and has good predictive accuracy. The general population with FMBL angle below 33.7° may be increased risk for ACL injury.
Male ; Female ; Humans ; Adolescent ; Young Adult ; Adult ; Middle Aged ; Anterior Cruciate Ligament Injuries/diagnostic imaging* ; Retrospective Studies ; Imaging, Three-Dimensional ; Magnetic Resonance Imaging/methods* ; Anterior Cruciate Ligament/diagnostic imaging* ; Knee Joint/diagnostic imaging*

OBJECTIVE: To explore the technical aspects of the accuracy of cervical pedicle screw placement with O-arm guidance. METHODS: The clinical data of 21 patients who underwent cervical pedicle screw fixation by O-arm real-time guidance from December 2015 to January 2020 were analyzed retrospectively. There were 15 males and 6 females, aged from 29 to 76 years old with an average of (45.3±11.5) years. The postoperative CT scan was utilized to evaluate the placement of the pedicle screw and classified according to the Gertzbein and Robbins classification. RESULTS: A total of 132 pedicle screws were implanted in 21 patients, 116 at C₃-C₆ and 16 at C₁ and C₂. According to Gertzbein & Robbins classification, the overall breach rates were found to be 11.36% (15/132) with 73.33% (11 screws) Grade B, 26.67% (4 screws) Grade C, and no Grade D or E screw breaches. There were no pedicle screw placement related complications at final follow-up. CONCLUSION The application of O-arm real-time guidance technology can make cervical pedicle screw placement reliable. High accuracy and better intra-operative control can increase surgeon's confidence in using cervical pedicle instrumentation. Considering the high-risk nature of anatomical area around cervical pedicle and the possibility of catastrophic complications, the spine surgeon should have sufficient surgical skills, experience, ensures stringent verification of the system, and never relies solely on the navigation system.
Male ; Female ; Humans ; Adult ; Middle Aged ; Aged ; Retrospective Studies ; Imaging, Three-Dimensional ; Surgery, Computer-Assisted ; Tomography, X-Ray Computed ; Pedicle Screws ; Spinal Fusion

OBJECTIVES: To investigate the reliability and accuracy of deep learning technology in automatic sex estimation using the 3D reconstructed images of the computed tomography (CT) from the Chinese Han population. METHODS: The pelvic CT images of 700 individuals (350 males and 350 females) of the Chinese Han population aged 20 to 85 years were collected and reconstructed into 3D virtual skeletal models. The feature region images of the medial aspect of the ischiopubic ramus (MIPR) were intercepted. The Inception v4 was adopted as the image recognition model, and two methods of initial learning and transfer learning were used for training. Eighty percent of the individuals' images were randomly selected as the training and validation dataset, and the remaining were used as the test dataset. The left and right sides of the MIPR images were trained separately and combinedly. Subsequently, the models' performance was evaluated by overall accuracy, female accuracy, male accuracy, etc. RESULTS: When both sides of the MIPR images were trained separately with initial learning, the overall accuracy of the right model was 95.7%, the female accuracy and male accuracy were both 95.7%; the overall accuracy of the left model was 92.1%, the female accuracy was 88.6% and the male accuracy was 95.7%. When the left and right MIPR images were combined to train with initial learning, the overall accuracy of the model was 94.6%, the female accuracy was 92.1% and the male accuracy was 97.1%. When the left and right MIPR images were combined to train with transfer learning, the model achieved an overall accuracy of 95.7%, and the female and male accuracies were both 95.7%. CONCLUSIONS The use of deep learning model of Inception v4 and transfer learning algorithm to construct a sex estimation model for pelvic MIPR images of Chinese Han population has high accuracy and well generalizability in human remains, which can effectively estimate the sex in adults.
Adult ; Female ; Humans ; Male ; Deep Learning ; Imaging, Three-Dimensional ; Pelvis ; Reproducibility of Results ; Tomography, X-Ray Computed ; Young Adult ; Middle Aged ; Aged ; Aged, 80 and over

BACKGROUND: Since the popularization of computed tomography (CT) technology, the detection rate of pulmonary ground glass nodules (GGNs) with imaging follow-up as the main management method has increased significantly. The purpose of this study is to quantitatively analyze the changes of pulmonary GGNs during the follow-up process with three-dimensional reconstruction technology, explore the natural progression of pulmonary GGNs, and provide effective basis for clinical guidance for patients to conduct reasonable management of nodules. METHODS: A total of 115 cases of pulmonary GGNs with regular follow-up in the Combined Outpatient Department of Zhoushan Hospital from March 2015 to November 2022 were enrolled. Quantitative imaging features of nodules were extracted by semi-automatic segmentation of 3D Slicer software to evaluate the growth of nodules and clinical intervention during follow-up. RESULTS: The average baseline age of the patients was (56.9±10.1) yr. The mean follow-up time was (48.8±18.9) months. The two-dimensional diameter of baseline CT scan was (7.9±2.9) mm, and the maximum three-dimensional diameter was (10.1±3.4) mm. The two-dimensional diameter of the last CT scan was (9.9±4.7) mm, and the maximum three-dimensional diameter was (11.4±5.1) mm. A total of 27 cases (23.5%) showed an increase during follow-up, with a median volume doubling time of 822 days and a median mass doubling time of 1,007 days. 32 cases were surgically resected, including 6 cases of invasive adenocarcinoma (IAC), 16 cases of minimally invasive adenocarcinoma (MIA), 8 cases of adenocarcinoma in situ (AIS) and 2 cases of atypical adenomatous hyperplasia (AAH). Five nodules underwent surgical intervention due to the progression of two-dimensional diameter, which was pathologically confirmed as pre-invasive lesions, but their three-dimensional maximum diameter showed no significant change. Nodular morphology, lobulated sign, spiculated sign and vacuole signs all promoted the growth of nodules in univariate analysis. There were significant differences in age, baseline diameter, mean CT value, median CT value, 10% and 90% percentile CT number between the growth group and the stable group (P<0.05). Multivariate Logistic regression analysis showed that age and average CT value were risk factors for nodule growth (P<0.05). Receiver-operating characteristic (ROC) curve analysis results indicated that the age ≥63 years old, the baseline three-dimensional maximum diameter ≥9.2 mm, and the average CT value ≥-507.8 HU were more likely to accelerate the growth of GGNs. The maximum three-dimensional diameter ≥14.4 mm and the average CT value ≥-495.7 HU may be a higher malignant probability. CONCLUSIONS GGNs show an inert growth process, and the use of three-dimensional measurements during follow-up is of greater significance. For persistent glass grinding nodules ≥63 years old, the baseline three-dimensional maximum diameter ≥9.2 mm, and the average CT value ≥-507.8 HU are more likely to increase. However, most nodules still have good prognosis after progression, and long-term follow-up is safe.
Humans ; Middle Aged ; Lung Neoplasms/pathology* ; Imaging, Three-Dimensional ; Neoplasm Invasiveness ; Retrospective Studies ; Multiple Pulmonary Nodules/pathology* ; Adenocarcinoma/pathology*

OBJECTIVES: To examine the reliability and accuracy of Walker's model for estimating the sex of Han adults in western China by using cranium three-dimensional (3D) CT reconstruction, and to study the suitable cranial sex estimation model for Han people in western China. METHODS: A total of 576 cranial CT 3D reconstructed images from Hanzhong Hospital in Shaanxi Province from 2017 to 2021 were collected. These images were divided into the experimental group with 486 samples and the validation group with 90 samples. Walker's model was used by observer 1 to estimate the sex of experimental group samples. The logistic function applicable to Han people in western China was corrected by observer 1. The 90 samples in the validation group were scored and substituted into the modified logistic function to complete the back substitution test by observer 1, 2 and 3. RESULTS: The accuracy of sex estimation of Han adults in western China was 63.2%-77.2% by applying Walker's model. The accuracy of modified logistic function was 82.9%. The accuracy of sex estimation through back substitution test by 3 observers was 75.6%-91.1%, with a Kappa value of 0.689 (P<0.05) for inter-observer consistency and 0.874 (P<0.05) for intra-observer consistency. CONCLUSIONS There are great differences in bone characteristics among people from different regions. The modified logistic function can achieve higher accuracy in Han adults in western China.
Humans ; Adult ; Reproducibility of Results ; Sex Determination by Skeleton/methods* ; Forensic Anthropology ; Skull/anatomy & histology* ; Imaging, Three-Dimensional ; China ; Tomography, X-Ray Computed

In light of the increasing digitalization of dentistry, the automatic determination of three-dimensional (3D) craniomaxillofacial features has become a development trend. 3D craniomaxillofacial landmarks and symmetry reference plane determination algorithm based on point clouds has attracted a lot of attention, for point clouds are the basis for virtual surgery design and facial asymmetry analysis, which play a key role in craniomaxillofacial surgery and orthodontic treatment design. Based on the studies of our team and national and international literatures, this article presented the deep geometry learning algorithm to determine landmarks and symmetry reference plane based on 3D craniomaxillofacial point clouds. In order to provide reference for future clinical application, we describe the development and latest research in this field, and analyze and discuss the advantages and limitations of various methods.
Humans ; Imaging, Three-Dimensional/methods* ; Facial Asymmetry ; Algorithms