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We sought to evaluate the reliability and validity of the Korean adaptation of the Scoliosis Japanese Questionnaire-27 (SJ-27). This involved translating the English SJ-27 into Korean and back-translating it, followed by completing all stages of the cross-cultural adaptation process. Subsequently, the Korean SJ-27, along with the validated Scoliosis Research Society-22 (SRS-22) questionnaire, was administered to 140 consecutive idiopathic scoliosis patients wearing a brace. Reliability was determined using kappa statistics to assess agreement for each item, the intraclass correlation coefficient (ICC), and Cronbach's α. Construct validity was established by comparing responses on the SJ-27 with those on the SRS-22 using Pearson's correlation coefficient. All items showed kappa statistics indicating agreement above 0.6. The SJ-27 demonstrated excellent test-retest reliability (ICC=0.91). Internal consistency measured by Cronbach's α was very good (α = 0.898). The Korean version of the SJ-27 exhibited significant correlations with both the total score and individual domain scores of the SRS-22. The adapted Korean SJ-27 was effectively translated and showed acceptable measurement properties, making it suitable for assessing outcomes in Korean-speaking patients with idiopathic scoliosis.

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BACKGROUND: Accurate estimation of implant size before surgery is crucial in preparing for total knee arthroplasty. However, this task is time-consuming and labor-intensive. To alleviate this burden on surgeons, we developed a reliable artificial intelligence (AI) model to predict implant size. METHODS: We enrolled 714 patients with knee osteoarthritis who underwent total knee arthroplasty from March 2010 to February 2014. All surgeries were performed by the same surgeon using implants from the same manufacturer. We collected 1412 knee anteroposterior (AP) and lateral view x-ray images and retrospectively investigated the implant size. We trained the AI model using both AP and lateral images without any clinical or demographic information and performed data augmentation to resolve issues of uneven distribution and insufficient data. Using data augmentation techniques, we generated 500 images for each size of the femur and tibia, which were then used to train the model. Using data augmentation techniques, we generated 500 images for each size of the femur and tibia, which were then used to train the model. We used ResNet-101 and optimized the model with the aim of minimizing the cross-entropy loss function using both the Stochastic Gradient Descent (SGD) and Adam optimizer. RESULTS: The SGD optimizer achieved the best performance in internal validation. The model showed micro F1-score 0.91 for femur and 0.87 for tibia. For predicting within ± one size, micro F1-score was 0.99 for femur and 0.98 for tibia. CONCLUSION: We developed a deep learning model with high predictive power for implant size using only simple x-ray images. This could help surgeons reduce the time and labor required for preoperative preparation in total knee arthroplasty. While similar studies have been conducted, our work is unique in its use of simple x-ray images without any other data, like demographic features, to achieve a model with strong predictive power.

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In recent years, finite element analysis (FEA) has been instrumental in comparing the biomechanical stability of various implants for femur fracture treatment and in studying the advantages and disadvantages of different surgical techniques. This analysis has proven helpful for enhancing clinical treatment outcomes. Therefore, this study aimed to numerically analyze fixed stability according to location using FEA. In this study, a virtual finite element model was created based on a clinically anatomically reduced patient. It incorporated positive and negative support derived from intramedullary and extramedullary reduction from the anteroposterior (AP) view and neutral support from the lateral view. The generated model was analyzed to understand the biomechanical behavior occurring in each region under applied physiological loads. The simulation results of this study showed that the average von Mises stress (AVMS) of the nail when performing intramedullary reduction for femoral fixation was 187% of the anatomical reduction and 171% of the extramedullary reduction, and individually up to 2.5 times higher. In other words, intramedullary reduction had a very high possibility of fixation failure compared to other reduction methods. This risk is amplified significantly, especially in situations where bone strength is compromised due to factors such as old age or osteoporosis, which substantially affects the stability of fixation. Extramedullary reduction, when appropriately positioned, demonstrates greater stability than anatomical reduction. It exhibits stable fixation even in scenarios with diminished bone strength. In instances in which the bone density was low in the support position, as observed in the lateral view, the AVMS on the nail appeared to be relatively low, particularly in cases of positive support. Additionally, the femur experienced lower equivalent stress only in the extramedullary reduction-negative position. Moreover, by comparing different reduction methods and bone stiffness values using the same femoral shape, this study offers insights into the selection of appropriate reduction methods. These insights could significantly inform decision making regarding surgical strategies for intertrochanteric fractures.

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Background and Objectives: Few studies have investigated the socioeconomic factors associated with retear after rotator cuff repair. This study aimed to identify the risk factors, including socioeconomic factors, for rotator cuff retear in patients who underwent arthroscopic rotator cuff repair. Materials and Methods: This retrospective study included 723 patients diagnosed with full-thickness rotator cuff tears who underwent arthroscopic rotator cuff repair from March 2010 to March 2021. The outcome variable was rotator cuff retear observed on postoperative magnetic resonance imaging or ultrasonography. Sex, age, obesity, diabetes, symptom duration, and tear size were the independent variables. Socioeconomic variables included occupation, educational level, type of medical insurance, and area of residence. We compared patients with and without retear and estimated the effects of the independent factors on retear risk. Results: The mean age of the patients, symptom duration, and tear size were 62.4 ± 8.0 years, 1.8 ± 1.7 years, and 21.8 ± 12.5 mm, respectively. The age, type of medical insurance, diabetes, tear size, and symptom duration differed significantly between patients with and without retearing (p < 0.05). Age, occupation, type of medical insurance, diabetes, initial tear size, and symptom duration significantly affected the risk of retear. Patients who performed manual labor had a significantly higher retear rate (p = 0.005; OR, 1.95; 95% CI, 1.23-3.11). The highest retear risk was seen in patients with Medicaid insurance (p < 0.001; OR, 4.34; 95% CI, 2.09-9.02). Conclusions: Age, initial tear size, and symptom duration significantly affect retear risk after arthroscopic rotator cuff repair. Occupation and type of medical insurance were also risk factors for retear. Socioeconomically vulnerable patients may be at a greater risk of retear. Proactive efforts are required to expand early access to medical care.

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Obesity is a potential risk factor for meniscal tear (MT). We utilized meta-analysis of observational studies and Mendelian randomization (MR) analyses to elucidate the association between body mass index (BMI) and MT. In meta-analysis, a search was performed on June 27, 2022, using PubMed and Embase databases. Odds ratios and 95% confidence intervals were extracted from included studies. In MR analyses, the research utilized summary-level data on BMI and MT obtained from Genetic Investigation of Anthropometric Traits and the FinnGen Consortium, respectively. In meta-analysis, four studies comprising 826,383 participants were included. The pooled odds ratio of MT in the high BMI group was 1.32 (95% confidence interval, 0.83-2.09), compared with the nonhigh BMI group. The pooled odds ratio in the under 30 group was 1.76 (95% confidence interval, 0.61-5.03). In MR analyses, one standard deviation increase in genetically predicted BMI was associated with meniscus derangement as a chronic subtype of MT (odds ratio, 1.36; 95% confidential interval, 1.17-1.59). We found that a high BMI was not associated with an increased likelihood of MT based on meta-analysis of observational studies; however, by complementing MR analyses, we elucidated the causality of BMI increase on meniscus derangement as a chronic subtype of MT.

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The facet joint contributes to lumbar spine stability as it supports the weight of body along with the intervertebral discs. However, most studies on the causes of degenerative lumbar diseases focus on the intervertebral discs and often overlook the facet joints. This study aimed to investigate the impact of facet joint degeneration on the degenerative changes and diseases of the lumbar spine. A finite element model of the lumbar spine (L1-S1) was fabricated and validated to study the biomechanical characteristics of the facet joints. To simulate degeneration of the facet joint, the model was divided into four grades based on the number of degenerative segments (L4-L5 or L4-S1) and the contact condition between the facet joint surfaces. Finite element analysis was performed on four spine motions: flexion, extension, lateral bending, and axial torsion, by applying a pure moment to the upper surface of L1. Important parameters that could be used to confirm the effect of facet joint degeneration on the lumbar spine were calculated, including the range of motion (ROM) of the lumbar segments, maximum von Mises stress on the intervertebral discs, and reaction force at the facet joint. Facet joint degeneration affected the biomechanical characteristics of the lumbar spine depending on the movements of the spine. When analyzed by dividing it into degenerative onset and onset-adjacent segments, lumbar ROM and the maximum von Mises stress of the intervertebral discs decreased as the degree of degeneration increased in the degenerative onset segments. The reaction force at the facet joint decreased with flexion and increased with lateral bending and axial torsion. In contrast, lumbar ROM of the onset-adjacent segments remained almost unchanged despite severe degeneration of the facet joint, and the maximum von Mises stress of the intervertebral discs increased with flexion and extension but decreased with lateral bending and axial torsion. Additionally, the facet joint reaction force increased with extension, lateral bending, and axial rotation. This analysis, which combined the ROM of the lumbar segment, maximum von Mises stress on the intervertebral disc, and facet joint reaction force, confirmed the biomechanical changes in the lumbar spine due to the degeneration of isolated facet joints under the load of spinal motion. In the degenerative onset segment, spinal instability decreased, whereas in the onset-adjacent segment, a greater load was applied than in the intact state. When conducting biomechanical studies on the lumbar spine, considering facet joint degeneration is important since it can lead to degenerative spinal diseases, including adjacent segment diseases.

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Background: Measuring accurate and reliable scores of quality of life in patients with ankylosing spondylitis (AS) is important in both decision-making and treatment planning for the disease. Questionnaire, The ankylosing spondylitis quality of life (ASQoL), is one of the representative tools for assessing how seriously AS patients view their disease severity, activity, as well as their overall health. To make these types of questionnaires readable and understandable, local language translation of surveys should be required. A Korean version of the ASQoL questionnaire has accordingly been developed. This study assessed the Korean version of the ASQoL survey to evaluate the reliability and validity of it. Methods: Translation and reverse translation of the English ASQoL survey were conducted. A total of 120 consecutive AS patients received a mail including the Korean-translated 36-Item Short Form Survey (SF-36), the ASQoL survey, and the visual analog scale (pain). The coefficient of intraclass correlation and Cronbach's alpha were computed, and factor analysis, as well as reliability assessments utilizing the kappa agreement statistics for each item, was undertaken. By analyzing the responses to SF-36 and ASQoL questionnaire utilizing Pearson's correlation coefficient, construct validity was calculated. Results: Factor analysis was performed regarding pain, physical function, and mental function. The kappa statistic of agreement was larger than 0.6 for all items. The ASQoL questionnaire had adequate test and re-test reliability (0.814). Furthermore, Cronbach'sα, the internal consistency, was very good (0.877). The Korean-translated ASQoL questionnaire demonstrated a significantly strong correlation between the single domain and total SF-36 scores. Conclusions: The Korean version of the ASQoL questionnaire showed acceptable properties of measurement and successful translation. Thus, it can be said that the questionnaire is appropriate for evaluating the outcomes of Korean patients with AS.

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In this work, we proposed a novel computer modeling and simulation technique for motion tracking of lung bronchi (or tumors) under respiration using 9 cases of computed tomography (CT)-based patient-specific finite element (FE) models and Ogden's hyperelastic model. In the fabrication of patient-specific FE models for the respiratory system, various organs such as the mediastinum, diaphragm, and thorax that could affect the lung motions during breathing were considered. To describe the nonlinear material behavior of lung parenchyma, the comparative simulation for biaxial tension-compression of lung parenchyma was carried out using several hyperelastic models in ABAQUS, and then, Ogden's model was adopted as an optimal model. Based on the aforementioned FE models and Ogden's material model, the 9 cases of respiration simulation were carried out from exhalation to inhalation, and the motion of lung bronchi (or tumors) was tracked. In addition, the changes in lung volume, lung cross-sectional area on the axial plane during breathing were calculated. Finally, the simulation results were quantitatively compared to the inhalation/exhalation CT images of 9 subjects to validate the proposed technique. Through the simulation, it was confirmed that the average relative errors of simulation to clinical data regarding to the displacement of 258 landmarks in the lung bronchi branches of total subjects were 1.10%~2.67%. In addition, the average relative errors of those with respect to the lung cross-sectional area changes and the volume changes in the superior-inferior direction were 0.20%~5.00% and 1.29 ~ 9.23%, respectively. Hence, it was considered that the simulation results were coincided well with the clinical data. The novelty of the present study is as follows: (1) The framework from fabrication of the human respiratory system to validation of the bronchi motion tracking is provided step by step. (2) The comparative simulation study for nonlinear material behavior of lung parenchyma was carried out to describe the realistic lung motion. (3) Various organs surrounding the lung parenchyma and restricting its motion were considered in respiration simulation. (4) The simulation results such as landmark displacement, lung cross-sectional area/volume changes were quantitatively compared to the clinical data of 9 subjects.

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One of the key aspects of the diagnosis and treatment of atypical femoral fractures is the early detection of incomplete fractures and the prevention of their progression to complete fractures. However, an incomplete atypical femoral fracture can be misdiagnosed as a normal lesion by both primary care physicians and orthopedic surgeons; expert consultation is needed for accurate diagnosis. To overcome this limitation, we developed a transfer learning-based ensemble model to detect and localize fractures. A total of 1050 radiographs, including 100 incomplete fractures, were preprocessed by applying a Sobel filter. Six models (EfficientNet B5, B6, B7, DenseNet 121, MobileNet V1, and V2) were selected for transfer learning. We then composed two ensemble models; the first was based on the three models having the highest accuracy, and the second was based on the five models having the highest accuracy. The area under the curve (AUC) of the case that used the three most accurate models was the highest at 0.998. This study demonstrates that an ensemble of transfer-learning-based models can accurately classify and detect fractures, even in an imbalanced dataset. This artificial intelligence (AI)-assisted diagnostic application could support decision-making and reduce the workload of clinicians with its high speed and accuracy.

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Context: Circulating adipokines and ghrelin affect bone remodeling by regulating the activation and differentiation of osteoblasts and osteoclasts. Although the correlation between adipokines, ghrelin, and bone mineral density (BMD) has been studied over the decades, its correlations are still controversial. Accordingly, an updated meta-analysis with new findings is needed. Objective: This study aimed to explore the impact of serum adipokine and ghrelin levels on BMD and osteoporotic fractures through a meta-analysis. Data sources: Studies published till October 2020 in Medline, Embase, and the Cochrane Library were reviewed. Study selection: We included studies that measured at least one serum adipokine level and BMD or fracture risk in healthy individuals. We excluded studies with one or more of the following: patients less than 18 years old, patients with comorbidities, who had undergone metabolic treatment, obese patients, patients with high physical activities, and a study that did not distinguish sex or menopausal status. Data extraction: We extracted the data that include the correlation coefficient between adipokines (leptin, adiponectin, and resistin) and ghrelin and BMD, fracture risk by osteoporotic status from eligible studies. Data synthesis: A meta-analysis of the pooled correlations between adipokines and BMD was performed, demonstrating that the correlation between leptin and BMD was prominent in postmenopausal women. In most cases, adiponectin levels were inversely correlated with BMD. A meta-analysis was conducted by pooling the mean differences in adipokine levels according to the osteoporotic status. In postmenopausal women, significantly lower leptin (SMD = -0.88) and higher adiponectin (SMD = 0.94) levels were seen in the osteoporosis group than in the control group. By predicting fracture risk, higher leptin levels were associated with lower fracture risk (HR = 0.68), whereas higher adiponectin levels were associated with an increased fracture risk in men (HR = 1.94) and incident vertebral fracture in postmenopausal women (HR = 1.18). Conclusions: Serum adipokines levels can utilize to predict osteoporotic status and fracture risk of patients. Systematic review registration: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021224855, identifier CRD42021224855.

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This study describes a computational analysis technique for evaluating the effect of screw spacing and angle on the pediatric hip locking plate system in proximal femoral osteotomy in pediatric patients having DDH with an aberrant femoral head and femoral angle. Under static compressive load conditions, the stresses of the screw and bone were examined as the screw spacing and angle changed. The spacing and angle of various screws were specifically considered as variables in this study based on the pile mechanism studied in civil engineering. As with the group pile mechanism, the tighter the screw spacing under static compressive loads, the more the overlapping effect between the bone stresses and the screws develops, increasing the risk of injuring the patient's bone. Therefore, a series of simulations was performed to determine the optimal screw spacing and angles to minimize the overlapping effect of bone stress. In addition, a formula for determining the minimum screw spacing was proposed based on the computational simulation results. Finally, if the outcomes of this study are applied to pediatric patients with DDH in the pre-proximal femoral osteotomy stage, post-operative load-induced femur damage will be reduced.

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Background: This study aimed to identify the relationship between gait parameters and health-related quality of life (HRQOL) in patients with ankylosing spondylitis (AS). Methods: The study group comprised 134 patients with AS and 124 patients were enrolled as controls. All study participants underwent instrumented gait analysis and completed clinical questionnaires. The kinematic parameters of gait were walking speed, step length, cadence, stance phase, single support, double support, phase coordination index (PCI), and gait asymmetry (GA). For each patient, a visual analog scale (VAS; 0-10) score was used to assess back pain, 36-item short form survey (SF-36) questionnaire was administered to evaluate the HRQOL, and Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) was calculated. Using kinematic parameters and questionnaires, statistical analyses were done to investigate significant differences between the groups. Relationship of gait kinematic data and questionnaires of clinical outcome was also evaluated. Results: Among the 134 patients with AS, 34 were women and 100 were men. In the control group, 26 were women and 98 were men. The patients with AS and control group patients had significant differences in terms of walking speed, step length, single support, PCI, and GA. However, such differences were not observed in cadence, stance phase, and double support (p > 0.05). In correlation analyses, gait kinematic parameters and clinical outcomes were significantly related with each other. In multiple regression analysis performed to identify predictive factors for clinical outcome, walking speed was found to predict VAS, and walking speed and step length were found to predict the BASDAI and SF-36 scores. Conclusions: Patients with and without AS had significant differences in the gait parameters. Correlation analysis showed significant correlation between the gait kinematic data and clinical outcomes. In particular, walking speed and step length successfully predicted clinical outcomes in patients with AS.

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BACKGROUND: We aimed to investigate whether densitometry results and volumetric bone mineral density (vBMD) can predict vertebral fragility fractures (VFF) in postmenopausal women. METHODS: We enrolled 271 postmenopausal women aged >45 years who visited our hospital for health check-ups between September 2016 and September 2017. The lumbar spine (LS) and femoral neck (FN) densitometry results and trabecular bone score (TBS) were calculated using dual energy X-ray absorptiometry. vBMD was assessed using central quantitative computed tomography (cQCT). Baseline and follow-up X-ray images were reviewed to evaluate thoracolumbar vertebral compression fractures (CFs), according to the Genant criteria. RESULTS: At baseline, 76 patients (28.0%) had CF. Additional or progressive fractures were noted in 26 participants (9.6%) with a median follow-up of 19.5 months. The median TBS and cQCT were significantly higher in participants without baseline CF than those with baseline CF (p<0.001). During the follow-up, Kaplan-Meier analysis showed that T-scores of the LS and FN <-2.5, degraded microarchitecture based on the TBS (≤1.200), and vBMD <80 mg/cm3 was significantly associated with future osteoporotic CF. The final multivariate Cox regression analysis showed that baseline CF and low TBS and vBMD were significant risk factors for future VFF. CONCLUSIONS: Participants with baseline CF and degraded microarchitecture had higher CF predisposition. Moreover, cQCT can predict future vertebral fractures.

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The complex shape of the foot, consisting of 26 bones, variable ligaments, tendons, and muscles leads to misdiagnosis of foot fractures. Despite the introduction of artificial intelligence (AI) to diagnose fractures, the accuracy of foot fracture diagnosis is lower than that of conventional methods. We developed an AI assistant system that assists with consistent diagnosis and helps interns or non-experts improve their diagnosis of foot fractures, and compared the effectiveness of the AI assistance on various groups with different proficiency. Contrast-limited adaptive histogram equalization was used to improve the visibility of original radiographs and data augmentation was applied to prevent overfitting. Preprocessed radiographs were fed to an ensemble model of a transfer learning-based convolutional neural network (CNN) that was developed for foot fracture detection with three models: InceptionResNetV2, MobilenetV1, and ResNet152V2. After training the model, score class activation mapping was applied to visualize the fracture based on the model prediction. The prediction result was evaluated by the receiver operating characteristic (ROC) curve and its area under the curve (AUC), and the F1-Score. Regarding the test set, the ensemble model exhibited better classification ability (F1-Score: 0.837, AUC: 0.95, Accuracy: 86.1%) than other single models that showed an accuracy of 82.4%. With AI assistance for the orthopedic fellow, resident, intern, and student group, the accuracy of each group improved by 3.75%, 7.25%, 6.25%, and 7% respectively and diagnosis time was reduced by 21.9%, 14.7%, 24.4%, and 34.6% respectively.

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STUDY DESIGN: A prospective study. PURPOSE: To obtain the results of four body image questionnaires analyzed for validity in Korean and compare them to radiographic findings and quality of life scores. OVERVIEW OF LITERATURE: Each of the four body image questionnaires has been studied, but comparative studies of each other are rare. METHODS: Adolescent idiopathic scoliosis (AIS) patients ages 10 to 19 years completed the Korean version of the Quality of Life Profile for Spinal Deformities (K-QLPSD), the Scoliosis Research Society-22 self-image subscale (K-SRS-22-si), Korean version of the Spinal Appearance Questionnaire (K-SAQ), Korean version of the Body Image Disturbance Questionnaire-Scoliosis (K-BIDQ-S), and Korean version of the Italian Spine Youth Quality of Life (K-ISYQOL). Four body image questionnaires were compared with K-ISYQOL and radiographic major curve magnitude, coronal balance, and sagittal balance. Spearman's correlation was performed to compare the four body image questionnaires. RESULTS: The study included 84 AIS patients, with a mean age of 12.6 years and a major Cobb angle of 29.4°. The four surveys were correlated with major curve magnitude and K-ISYQOL. K-SAQ and K-BIDQ-S were correlated better than K-QLPSD, and K-SRS-22-si was correlated with K-ISYQOL. The four surveys were moderately correlated with major curve magnitude, but there was no correlation with age, coronal balance, and sagittal balance. CONCLUSIONS: K-SAQ and K-BIDQ-S correlate better with K-ISYQOL than K-QLPSD and K-SRS-22-si.

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Despite advances in diagnostic and therapeutic methods, the prognosis of patients with hepatocellular carcinoma (HCC) remains poor due to the delay in diagnosis. Herein, we aimed to discover a highly sensitive and specific biomarker for HCC based on genomic big data analysis and create an HCC-targeted imaging probe using carbon nanodots (CNDs) as contrast agents. In genomic analysis, we selected glucose transporter 2 (GLUT2) as a potential imaging target for HCC. We confirmed the target suitability by immunohisto-chemistry tests of 339 patient samples, where 81.1% of the patients exhibited underexpression of GLUT2, i.e., higher GLUT2 intensity in non-tumor tissues than in tumor tissues. To visualize GLUT2, we conjugated CNDs with glucosamine (GLN) as a targeting ligand to yield glucosamine-labeled CNDs (GLN-CNDs). A series of in vitro and in vivo experiments were conducted on GLUT2-modified HepG2 cells to confirm the specificity of the GLN-CNDs. Since the GLUT2 expression is higher in hepatocytes than in HCC cells, the GLUT2-targeted contrast agent is highly attached to normal cells. However, it is possible to produce images in the same form as the images obtained with a cancer cell-targeted contrast agent by inverting color scaling. Our results indicate that GLUT2 is a promising target for HCC and that GLN-CNDs may potentially be used as targeted imaging probes for diagnosing HCC.

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