INTRODUCTION: Ultrasonography (US) is the current standard of care for imaging surveillance in patients at risk of hepatocellular carcinoma (HCC). Magnetic resonance imaging (MRI) has been explored as an alternative, given the higher sensitivity of MRI, although this comes at a higher cost. We performed a cost-effective analysis comparing US and dual-sequence non-contrast-enhanced MRI (NCEMRI) for HCC surveillance in the local setting. METHODS: Cost-effectiveness analysis of no surveillance, US surveillance and NCEMRI surveillance was performed using Markov modelling and microsimulation. At-risk patient cohort was simulated and followed up for 40 years to estimate the patients' disease status, direct medical costs and effectiveness. Quality-adjusted life years (QALYs) and incremental cost-effectiveness ratio were calculated. RESULTS: Exactly 482,000 patients with an average age of 40 years were simulated and followed up for 40 years. The average total costs and QALYs for the three scenarios - no surveillance, US surveillance and NCEMRI surveillance - were SGD 1,193/7.460 QALYs, SGD 8,099/11.195 QALYs and SGD 9,720/11.366 QALYs, respectively. CONCLUSION Despite NCEMRI having a superior diagnostic accuracy, it is a less cost-effective strategy than US for HCC surveillance in the general at-risk population. Future local cost-effectiveness analyses should include stratifying surveillance methods with a variety of imaging techniques (US, NCEMRI, contrast-enhanced MRI) based on patients' risk profiles.
Humans ; Adult ; Carcinoma, Hepatocellular/diagnostic imaging* ; Liver Neoplasms/diagnostic imaging* ; Cost-Effectiveness Analysis ; Cost-Benefit Analysis ; Quality-Adjusted Life Years ; Magnetic Resonance Imaging/methods*

Objective To explore the optimal parameters for virtual mono-energetic imaging of liver solid lesions. Methods A retrospective analysis was performed on 60 patients undergoing contrast-enhanced spectral CT of the abdomen.The iodine concentration values of hepatic arterial phase images and the CT values of different mono-energetic images were measured.The correlation coefficient and coefficient of variation were calculated. Results The average correlation coefficients between iodine concentrations and CT values of hepatic solid lesion images at 40,45,50,55,60,65,and 70 keV were 0.996,0.995,0.993,0.989,0.978,0.970,and 0.961,respectively.The correlation coefficients at 40(P=0.007),45(P=0.022),50 keV (P=0.035)were higher than that at 55 keV,and the correlation coefficients at 40 keV(P=0.134) and 45 keV(P=0.368) had no significant differences from that at 50 keV.The coefficients of variation of the CT values at 40,45,and 50 keV were 0.146,0.154,and 0.163,respectively. Conclusion The energy of 40 keV is optimal for virtual mono-energetic imaging of liver solid lesions in the late arterial phase,which is helpful for the diagnosis of liver diseases.
Humans ; Tomography, X-Ray Computed ; Retrospective Studies ; Abdomen ; Iodine ; Liver/diagnostic imaging* ; Signal-To-Noise Ratio ; Radiographic Image Interpretation, Computer-Assisted/methods*

In real-time ultrasound,molecular targeted contrast agent is introduced into the blood circulation through peripheral intravenous injection to enhance the imaging signal of target lesions after binding to the corresponding intravascular receptors,which can realize early diagnosis,staging of diseases,assessment of treatment response,and targeted treatment.In addition,molecular targeted ultrasound contrast agents provide a platform for the delivery of drugs and genes via microbubbles,and nanoscale contrast agents can be infiltrated through vascular endothelium into the interstitial space of the lesion for imaging or treatment.The available studies of molecular targeted ultrasound contrast agents mainly focus on the preclinical trials.Some clinical trials have been conducted in humans and preliminarily confirm the safety and feasibility of targeted ultrasound contrast agents.The molecular targeted ultrasound contrast agents enjoy a broad prospect in clinical application.
Humans ; Contrast Media/chemistry* ; Molecular Targeted Therapy ; Ultrasonography/methods* ; Diagnostic Imaging

Objective To investigate the influencing factors and establish a model predicting the performance of needle visualization in fine-needle aspiration (FNA) of thyroid nodules. Methods This study prospectively included 175 patients who underwent FNA of thyroid nodules in the Department of Ultrasound in China-Japan Friendship Hospital and compared the display of the needle tips in the examination of 199 thyroid nodules before and after the application of needle visualization.We recorded the location,the positional relationship with thyroid capsule,ultrasonic characteristics,and the distribution of the soft tissue strip structure at the puncture site of the nodules with unclear needle tips display before using needle visualization.Furthermore,according to the thyroid imaging reporting and data system proposed by the American College of Radiology,we graded the risk of the nodules.Lasso-Logistic regression was employed to screen out the factors influencing the performance of needle visualization and establish a nomogram for prediction. Results The needle tips were not clearly displayed in the examination of 135 (67.8%) and 53 (26.6%) nodules before and after the application of needle visualization,respectively,which showed a significant difference (P<0.001).Based on the positional relationship between the nodule and capsule,anteroposterior/transverse diameter (A/T) ratio,blood supply,and the distribution of subcutaneous strip structure at the puncture site,a nomogram was established to predict the probability of unclear display of the needle tips after application of needle visualization.The C-index of the prediction model was 0.75 (95%CI=0.67-0.84) and the area under the receiver operating characteristic curve was 0.72.The calibration curve confirmed the appreciable reliability of the prediction model,with the C-index of 0.70 in internal validation. Conclusions Needle visualization can improve the display of the needle tip in ultrasound-guided FNA of thyroid nodules.The nomogram established based on ultrasound features such as the positional relationship between the nodule and capsule,A/T ratio,blood supply,and the distribution of subcutaneous strip structure at the puncture site can predict whether needle visualization is suitable for the examination of nodules.
Humans ; Thyroid Nodule/diagnostic imaging* ; Biopsy, Fine-Needle/methods* ; Reproducibility of Results ; Ultrasonography ; Retrospective Studies ; Thyroid Neoplasms

Objective To investigate the clinical value of high-frequency ultrasound in the diagnosis of pronator teres syndrome (PTS). Methods The high-frequency ultrasound was employed to examine and measure the median nerve of the pronator teres muscle in 30 patients with PTS and 30 healthy volunteers (control group).The long-axis diameter (LA),short-axis diameter (SA) and cross-sectional area (CSA) of the median nerve were measured.The receiver operating characteristic curve of the median nerve ultrasonic measurement results was established,and the area under the curve (AUC) was calculated.The diagnostic efficiency of each index for PTS was compared with the surgical results as a reference. Results The PTS group showed larger LA[(5.02±0.50) mm vs.(3.89±0.41) mm;t=4.38,P=0.013],SA[(2.55±0.46) mm vs.(1.70±0.41) mm;t=5.19,P=0.009],and CSA[(11.13±3.72) mm² vs.(6.88±2.68) mm²;t=8.42,P=0.008] of the median nerve than the control group.The AUC of CSA,SA,and LA was 94.3% (95%CI=0.912-0.972,Z=3.586,P=0.001),77.7% (95%CI=0.734-0.815,Z=2.855, P=0.006),and 78.8% (95%CI=0.752-0.821,Z=3.091,P=0.004),respectively.With 8.63 mm² as the cutoff value,the sensitivity and specificity of CSA in diagnosing PTS were 93.3% and 90.0%,respectively. Conclusion High-frequency ultrasound is a practical method for diagnosing PTS,and the CSA of median nerve has a high diagnostic value.
Humans ; Forearm/innervation* ; Muscle, Skeletal/innervation* ; Median Nerve/diagnostic imaging* ; Ultrasonography/methods* ; Sensitivity and Specificity

Alzheimer's disease (AD) is a progressive and irreversible neurodegenerative disease. Neuroimaging based on magnetic resonance imaging (MRI) is one of the most intuitive and reliable methods to perform AD screening and diagnosis. Clinical head MRI detection generates multimodal image data, and to solve the problem of multimodal MRI processing and information fusion, this paper proposes a structural and functional MRI feature extraction and fusion method based on generalized convolutional neural networks (gCNN). The method includes a three-dimensional residual U-shaped network based on hybrid attention mechanism (3D HA-ResUNet) for feature representation and classification for structural MRI, and a U-shaped graph convolutional neural network (U-GCN) for node feature representation and classification of brain functional networks for functional MRI. Based on the fusion of the two types of image features, the optimal feature subset is selected based on discrete binary particle swarm optimization, and the prediction results are output by a machine learning classifier. The validation results of multimodal dataset from the AD Neuroimaging Initiative (ADNI) open-source database show that the proposed models have superior performance in their respective data domains. The gCNN framework combines the advantages of these two models and further improves the performance of the methods using single-modal MRI, improving the classification accuracy and sensitivity by 5.56% and 11.11%, respectively. In conclusion, the gCNN-based multimodal MRI classification method proposed in this paper can provide a technical basis for the auxiliary diagnosis of Alzheimer's disease.
Humans ; Alzheimer Disease/diagnostic imaging* ; Neurodegenerative Diseases ; Magnetic Resonance Imaging/methods* ; Neural Networks, Computer ; Neuroimaging/methods* ; Cognitive Dysfunction/diagnosis*

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 investigate the feasibility of predicting proximal junctional kyphosis (PJK) in adults after spinal deformity surgery based on back-forward Bending CT localization images and related predictive indicators. METHODS: A retrospective analysis was performed for 31 adult patients with spinal deformity who underwent posterior osteotomy and long-segment fusion fixation between March 2017 and March 2020. There were 5 males and 26 females with an average age of 62.5 years (range, 30-77 years). The upper instrumented vertebrae (UIV) located at T ₅ in 1 case, T ₆ in 1 case, T ₉ in 13 cases, T ₁₀ in 12 cases, and T ₁₁ in 4 cases. The lowest instrumented vertebrae (LIV) located at L ₁ in 3 cases, L ₂ in 3 cases, L ₃ in 10 cases, L ₄ in 7 cases, L ₅ in 5 cases, and S ₁ in 3 cases. Based on the full-length lateral X-ray film of the spine in the standing position before and after operation and back-forward Bending CT localization images before operation, the sagittal sequence of the spine was obtained, and the relevant indexes were measured, including thoracic kyphosis (TK), lumbar lordosis (LL), local kyphosis Cobb angle (LKCA) [the difference between the different positions before operation (recovery value) was calculated], kyphosis flexibility, hyperextension sagittal vertical axis (hSVA), T ₂-L ₅ hyperextension C ₇-vertebral sagittal offset (hC ₇-VSO), and pre- and post-operative proximal junctional angle (PJA). At last follow-up, the patients were divided into PJK and non-PJK groups based on PJA to determine whether they had PJK. The gender, age, body mass index (BMI), number of fusion segments, number of cases with coronal plane deformity, bone mineral density (T value), UIV position, LIV position, operation time, intraoperative blood loss, osteotomy grading, and related imaging indicators were compared between the two groups. The hC ₇-VSO of the vertebral body with significant differences between groups was taken, and the receiver operating characteristic curve (ROC) was used to evaluate its accuracy in predicting the occurrence of PJK. RESULTS: All 31 patients were followed up 13-52 months, with an average of 30.0 months. The patient's PJA was 1.4°-29.0° at last follow-up, with an average of 10.4°; PJK occurred in 8 cases (25.8%). There was no significant difference in gender, age, BMI, number of fusion segments, number of cases with coronal plane deformity, bone mineral density (T value), UIV position, LIV position, operation time, intraoperative blood loss, and osteotomy grading between the two groups ( P>0.05). Imaging measurements showed that the LL recovery value and T ₈-L ₃ vertebral hC ₇-VSO in the PJK group were significantly higher than those in the non-PJK group ( P>0.05). There was no significant difference in hyperextension TK, hyperextension LL, hyperextension LKCA, TK recovery value, LL recovery value, kyphosis flexibility, hSVA, and T ₂-T ₇, L ₄, L ₅ vertebral hC ₇-VSO ( P>0.05). T ₈-L ₃ vertebral hC ₇-VSO was analyzed for ROC curve, and combined with the area under curve and the comprehensive evaluation of sensitivity and specificity, the best predictive index was hC ₇-L ₂, the cut-off value was 2.54 cm, the sensitivity was 100%, and the specificity was 60.9%. CONCLUSION Preoperative back-forward Bending CT localization image can be used to predict the occurrence of PJK after posterior osteotomy and long-segment fusion fixation in adult spinal deformity. If the patient's T ₈-L ₂ vertebral hC ₇-VSO is too large, it indicates a higher risk of postoperative PJK. The best predictive index is hC ₇-L ₂, and the cut-off value is 2.54 cm.
Male ; Female ; Humans ; Adult ; Middle Aged ; Retrospective Studies ; Blood Loss, Surgical ; Thoracic Vertebrae/surgery* ; Kyphosis/surgery* ; Lordosis/surgery* ; Spinal Fusion/methods* ; Tomography, X-Ray Computed ; Postoperative Complications/diagnostic imaging* ; Lumbar Vertebrae/surgery*

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*