Assessing osteoporosis in postmenopausal women: preliminary results using a novel lumbar spine phantom-based MRI scoring method.

OBJECTIVE: To develop a novel magnetic resonance imaging (MRI) phantom for producing F-score (for fat) and W-score (for water) and to evaluate the performance of these scores in assessing osteoporosis and related vertebral fractures. MATERIALS AND METHODS: First, a real-time phantom consisting of oil and water tubes was manufactured. Then, 30 female volunteers (age: 62.3 ± 6.3 years) underwent lumbar spine examination with MRI (using a novel phantom) and dual-energy X-ray absorptiometry (DXA), following ethical approval. MRI phantom-based F-score and W-score were defined by normalizing the vertebral signal intensities (SIs) by the oil and water SIs of the phantom on T1- and T2-weighted images, respectively. The diagnostic performances of the new scores for assessing osteoporosis and vertebral fractures were examined using receiver operating characteristic analysis and compared with DXA-measured areal bone mineral density (DXA-aBMD). RESULTS: The F-score and W-score were greater in the osteoporotic patients (3.93 and 2.29) than the non-osteoporotic subjects (3.05 and 1.79) and achieved AUC values of 0.85 and 0.74 (p < 0.05), respectively, when detecting osteoporosis. Similarly, F-score and W-score had greater values for the fracture patients (3.94 and 2.53) than the non-fracture subjects (3.14 and 1.69) and produced better AUC values (0.90 for W-score and 0.79 for F-score) compared to DXA-aBMD (AUC: 0.27, p < 0.05). In addition, the F-score and W-score had a strong correlation (r = 0.77; p < 0.001). CONCLUSION: A novel real-time lumber spine MRI phantom was developed, based upon which newly defined F-score and W-score were able to detect osteoporosis and demonstrated an improved ability over DXA-aBMD in differentiating patients with vertebral fractures.

Comparisons of hounsfield units and volumetric bone density in discriminating vertebral fractures on lumber CT scans.

PURPOSE: To compare the performance of areal Hounsfield units (aHU), volumetric Hounsfield units (vHU), and volumetric bone mineral density (vBMD) by quantitative CT (QCT) in discriminating vertebral fractures (VFs) risk. METHODS: We retrospectively included CT scans of the lumber spine 101 VFs cases (60 women, mean age: 64 ± 4 years; 41 men, mean age: 73 ± 10 years) and sex- and age-matched 101 control subjects (60 women, mean age: 64 ± 4 years; 41 men, mean age: 72 ± 7 years). In order to assess the discriminatory capability of aHU, vHU, and vBMD measurements at the L1 and L2 levels in identifying vertebral fractures, we conducted binary logistic regression and receiver operating characteristic (ROC) curve analyses in men and women. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated. RESULTS: In both men and women with and without VFs, aHU, vHU, and vBMD were highly correlated with each other (r2 from 0.832 to 0.957, all p < 0.001). There was a statistically significant difference in aHU, vHU, and vBMD between subjects with and without VFs (p < 0.001). When age, gender and BMI were taken into account as covariances and adjusted simultaneously, odds ratios (ORs) for aHU, vHU, and vBMD values, which represent the risk of VFs, were significant (p < 0.001). Compared with aHU and vHU, vBMD was more strongly associated with VF risk (vBMD: OR, 6.29; 95% CI, 3.83-10.35 vs vHU: OR, 3.64; 95% CI, 2.43-5.46 vs aHU: OR, 2.56; 95% CI, 1.79-3.67). In both men and women, further, vBMD had higher values for AUC, sensitivity, specificity, PPV, and NPV compared to vHU, with vHU in turn surpassing aHU. The area under the receiver operating characteristic curve (AUC) for discriminating VFs using the average aHU, vHU, and vBMD of two vertebrae was 0.72, 0.77 and 0.87 in men and 0.76, 0.79, and 0.86 in women. In both men and women, there exist statistically significant differences in the AUC when employing the three measurements-namely, aHU, vHU, and vBMD-to discriminate fractures (p < 0.05). CONCLUSIONS: The QCT-measured volumetric bone mineral density is more associated with acute VFs than vHU and aHU values of the lumber spine. Although the use of vHU and aHU values for the diagnosis of osteoporosis and discriminating fracture risk is limited to scanner- and imaging protocol-specific, they have great potential for opportunistic osteoporosis screening, particularly vHU.

Reference Values for Paravertebral Muscle Size and Myosteatosis in Chinese Adults, a Nationwide Multicenter Study.

RATIONALE AND OBJECTIVES: The paravertebral muscles, characterized by their susceptibility to severe size loss and fat infiltration in old age, lack established reference values for age-related variations in muscle parameters. This study aims to fill this gap by establishing reference values for paravertebral muscles in a Chinese adult population. MATERIALS AND METHODS: This cross-sectional study utilized the baseline data from the prospective cohort China Action on Spine and Hip (CASH). A total of 4305 community-dwelling participants aged 21-80 years in China were recruited between 2013 and 2017. Pregnant women, individuals with metal implants, limited mobility or diseases/conditions (spinal tumor, infection, etc.) affecting lumbar vertebra were excluded from the study. Psoas and paraspinal muscles were measured in quantitative computed tomography (QCT) images at the L3 and L5 levels using Osirix software. Age-related reference values for muscle area, density, and fat fraction were constructed as percentile charts using the lambda-mu-sigma (LMS) method. RESULTS: The paravertebral muscles exhibited an age-related decline in muscle area and density, coupled with an increase in muscle fat fraction. Between the ages of 25 and 75, the reductions in psoas and paraspinal muscle cross-sectional area at the L3 level were - 0.47%/yr and - 0.53%/yr in men, and - 0.19%/yr and - 0.23%/yr in women, respectively. Notably, accelerated muscle loss was observed during menopause and postmenopause in women (45-75 years) and intermittently during middle and old age in men (35-55 and 60-75 years). Besides, the age-related decreases in PSMA, PMA, and PSMD and the increases in PSMFF were more pronounced in L5 than in L3 CONCLUSION: This study shows distinct patterns of accelerated muscle loss were identified in menopausal and postmenopausal women and in middle-aged and old men. The findings contribute valuable information for future investigations on paravertebral muscle loss and myosteatosis.

Assessment of 3.0 Tesla magnetic resonance imaging in Madelung's deformity: findings and implications.

OBJECTIVE: The aim of the study was to investigate the 3.0 Tesla magnetic resonance imaging (MRI) features of Madelung's deformity. MATERIALS AND METHODS: The wrist MRI scans of 19 patients clinically diagnosed with Madelung's deformity and 20 patients without deformity were consecutively selected from Beijing Jishuitan Hospital between April 2019 and December 2022 for observation, in the case group and control group, respectively. Multiple linear regression was used to analyze the factors affecting tilting angle and width of central disc (CD, also termed as triangular fibrocartilage, the main component of triangular fibrocartilage complex), while the chi-square test was used to compare the occurrences of CD (radial) attachment displacement, VL, and RTL. p < 0.05 indicated statistical significance. RESULTS: Madelung's deformity significantly contributed to the tilting and thickening of the CD. In the case group, the tilting angle and thickness of CD were (51.46 ± 1.33)° and (0.23 ± 0.01) cm, respectively, which was statistically significant (p < 0.05); the radial attachment of the CD significantly shifted away from the distal articular surface level (χ2 = 39.00, p < 0.001), with a mean displacement of (0.97 ± 0.38) cm. Furthermore, the cases demonstrated abnormally developed Vickers ligament (χ2 = 35.19, p < 0.001) and radiotriquetral ligament (χ2 = 25.66, p < 0.001). CONCLUSION: MRI provides a notable advantage in diagnosing Madelung's deformity. Compared with the control group, patients with Madelung's deformity exhibited tilting and thickening of the CD. Additionally, the radial attachment of the CD was significantly shifted proximally with abnormal development of Vickers and radiotriquetral ligaments.

Risk prediction of second hip fracture by bone and muscle density of the hip varies with time after first hip fracture: A prospective cohort study.

Purpose: Predictors of 'imminent' risk of second hip fracture are unknown. The aims of the study were to explore strength of hip areal bone mineral density (aBMD), and muscle area and density for predicting second hip fracture at different time intervals. Methods: Data of the Chinese Second Hip Fracture Evaluation were analyzed, a longitudinal study to evaluate the risk of second hip fracture (of the contralateral hip) by using CT images obtained immediately after first hip fracture. Muscle cross-sectional area and density were measured of the gluteus maximus (G.MaxM) and gluteus medius and minimus (G.Med/MinM) and aBMD of the proximal femur at the contralateral unfractured side. Patients were followed up for a median time of 4.5 years. Separate Cox models were used to predict second hip fracture risk at different time intervals after first event adjusted for age, sex, BMI and diabetes. Results: The mean age of subjects with imminent (within 1st or 2nd year) second hip fracture was 79.80 ± 5.16 and 81.56 ± 3.64 years. In the 1st year after the first hip fracture, femoral neck (FN) aBMD predicted second hip fracture (HR 5.88; 95 % CI, 1.32-26.09). In the remaining years of follow-up after 2nd year, muscle density predicted second hip fracture (G.MaxM HR 2.13; 95 % CI, 1.25-3.65,G.Med/MinM HR 2.10; 95 % CI, 1.32-3.34). Conclusions: Our results show that femoral neck aBMD is an important predictor for second hip fracture within the first year and therefore suggest supports the importance concept of early and rapid-acting bone-active drugs to increase hip BMD. In addition, the importance of muscle density predicting second hip fracture after the second year suggest post hip fracture rehabilitation and exercise programs could also be important to reduce muscle fatty infiltration.

External validation of a convolutional neural network algorithm for opportunistically detecting vertebral fractures in routine CT scans.

The Convolutional Neural Network algorithm achieved a sensitivity of 94% and specificity of 93% in identifying scans with vertebral fractures (VFs). The external validation results suggest that the algorithm provides an opportunity to aid radiologists with the early identification of VFs in routine CT scans of abdomen and chest. PURPOSE: To evaluate the performance of a previously trained Convolutional Neural Network (CNN) model to automatically detect vertebral fractures (VFs) in CT scans in an external validation cohort. METHODS: Two Chinese studies and clinical data were used to retrospectively select CT scans of the chest, abdomen and thoracolumbar spine in men and women aged ≥50 years. The CT scans were assessed using the semiquantitative (SQ) Genant classification for prevalent VFs in a process blinded to clinical information. The performance of the CNN model was evaluated against reference standard readings by the area under the receiver operating characteristics curve (AUROC), accuracy, Cohen's kappa, sensitivity, and specificity. RESULTS: A total of 4,810 subjects were included, with a median age of 62 years (IQR 56-67), of which 2,654 (55.2%) were females. The scans were acquired between January 2013 and January 2019 on 16 different CT scanners from three different manufacturers. 2,773 (57.7%) were abdominal CTs. A total of 628 scans (13.1%) had ≥1 VF (grade 2-3), representing 899 fractured vertebrae out of a total of 48,584 (1.9%) visualized vertebral bodies. The CNN's performance in identifying scans with ≥1 moderate or severe fractures achieved an AUROC of 0.94 (95% CI: 0.93-0.95), accuracy of 93% (95% CI: 93%-94%), kappa of 0.75 (95% CI: 0.72-0.77), a sensitivity of 94% (95% CI: 92-96%) and a specificity of 93% (95% CI: 93-94%). CONCLUSION: The algorithm demonstrated excellent performance in the identification of vertebral fractures in a cohort of chest and abdominal CT scans of Chinese patients ≥50 years.

Associations of Quantitative and Qualitative Muscle Parameters With Second Hip Fracture Risk in Older Women: A Prospective Cohort Study.

Older women with a first hip fracture exhibit heightened susceptibility and incidence of second fracture and potentially severe consequences. This prospective study was to compare the predictive power of qualitative and quantitative muscle parameters for a second hip fracture in older women with a first hip fracture. A total of 206 subjects were recruited from the longitudinal Chinese Second Hip Fracture Evaluation study. Hip computed tomography (CT) scans were obtained immediately after the first fracture. Muscle fat infiltration was assessed according to the Goutallier classification qualitatively. Quantitative parameters included cross-sectional area and density of gluteus maximus (G.MaxM) and gluteus medius and minimus (G.Med/MinM) muscles. CT X-ray absorptiometry was used to measure the areal bone mineral density (aBMD) of the contralateral femur. Cox proportional hazards models were used to compute hazard ratios (HR) of second hip fracture risk. The mean age of subjects was 74.9 (±9.5) years at baseline. After 4.5 years, 35 had a second hip fracture, 153 without a second hip fracture, and 18 died. Except for the combined G.MinM Goutallier grade 3 and 4 groups before adjustment for covariates (HR = 5.83; 95% confidence interval [CI] 1.49-22.83), there were no significant HRs for qualitative classification to predict a second hip fracture. Among quantitative metrics, after adjustment for covariates, G.Med/MinM density was significant in the original (HR = 1.44; CI 1.02-2.04) and competing risk analyses (HR = 1.46; CI 1.02-2.07). After additional adjustment for femoral neck (FN) aBMD, G.Med/MinM density remained borderline significant for predicting a second hip fracture in competing risk analysis (HR = 1.43; CI 0.99-2.06; p = 0.057). Our study revealed that Goutallier classification was less effective than quantitative muscle metrics for predicting hip second fracture in this elderly female cohort. After adjustment for FN aBMD, G.Med/MinM density is a borderline independent predictor of second hip fracture risk. © 2023 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.

Automated Segmentation and Classification of Knee Synovitis Based on MRI Using Deep Learning.

OBJECTIVES: To develop a deep learning (DL) model for segmentation of the suprapatellar capsule (SC) and infrapatellar fat pad (IPFP) based on sagittal proton density-weighted images and to distinguish between three common types of knee synovitis. MATERIALS AND METHODS: This retrospective study included 376 consecutive patients with pathologically confirmed knee synovitis (rheumatoid arthritis, gouty arthritis, and pigmented villonodular synovitis) from two institutions. A semantic segmentation model was trained on manually annotated sagittal proton density-weighted images. The segmentation results of the regions of interest and patients' sex and age were used to classify knee synovitis after feature processing. Classification by the DL method was compared to the classification performed by radiologists. RESULTS: Data of the 376 patients (mean age, 42 ± 15 years; 216 men) were separated into a training set (n = 233), an internal test set (n = 93), and an external test set (n = 50). The automated segmentation model showed good performance (mean accuracy: 0.99 and 0.99 in the internal and external test sets). On the internal test set, the DL model performed better than the senior radiologist (accuracy: 0.86 vs. 0.79; area under the curve [AUC]: 0.83 vs. 0.79). On the external test set, the DL diagnostic model based on automatic segmentation performed as well or better than senior and junior radiologists (accuracy: 0.79 vs. 0.79 vs. 0.73; AUC: 0.76 vs. 0.77 vs. 0.70). CONCLUSION: DL models for segmentation of SC and IPFD can accurately classify knee synovitis and aid radiologic diagnosis.

Construction and Application of Rib Fracture Diagnosis Model Based on YOLOv3 Algorithm.

OBJECTIVES: The artificial intelligence-aided diagnosis model of rib fractures based on YOLOv3 algorithm was established and applied to practical case to explore the application advantages in rib fracture cases in forensic medicine. METHODS: DICOM format CT images of 884 cases with rib fractures caused by thoracic trauma were collected, and 801 of them were used as training and validation sets. A rib fracture diagnosis model based on YOLOv3 algorithm and Darknet53 as the backbone network was built. After the model was established, 83 cases were taken as the test set, and the precision rate, recall rate, F1-score and radiology interpretation time were calculated. The model was used to diagnose a practical case and compared with manual diagnosis. RESULTS: The established model was used to test 83 cases, the fracture precision rate of this model was 90.5%, the recall rate was 75.4%, F1-score was 0.82, the radiology interpretation time was 4.4 images per second and the identification time of each patient's data was 21 s, much faster than manual diagnosis. The recognition results of the model was consistent with that of the manual diagnosis. CONCLUSIONS: The rib fracture diagnosis model in practical case based on YOLOv3 algorithm can quickly and accurately identify fractures, and the model is easy to operate. It can be used as an auxiliary diagnostic technique in forensic clinical identification.

Deep Learning-Based Fully Automated Segmentation of Regional Muscle Volume and Spatial Intermuscular Fat Using CT.

RATIONALE AND OBJECTIVES: We aim to develop a CT-based deep learning (DL) system for fully automatic segmentation of regional muscle volume and measurement of the spatial intermuscular fat distribution of the gluteus maximus muscle. MATERIALS AND METHODS: A total of 472 subjects were enrolled and randomly assigned to one of three groups: a training set, test set 1, and test set 2. For each subject in the training set and test set 1, we selected six slices of the CT images as the region of interest for manual segmentation by a radiologist. For each subject in test set 2, we selected all slices of the gluteus maximus muscle on the CT images for manual segmentation. The DL system was constructed using Attention U-Net and the Otsu binary thresholding method to segment the muscle and measure the fat fraction of the gluteus maximus muscle. The segmentation results of the DL system were evaluated using the Dice similarity coefficient (DSC), Hausdorff distance (HD), and the average surface distance (ASD) as metrics. Intraclass correlation coefficients (ICCs) and Bland-Altman plots were used to assess agreement in the measurements of fat fraction between the radiologist and the DL system. RESULTS: The DL system showed good segmentation performance on the two test sets, with DSCs of 0.930 and 0.873, respectively. The fat fraction of the gluteus maximus muscle measured by the DL system was in agreement with the radiologist (ICC=0.748). CONCLUSION: The proposed DL system showed accurate, fully automated segmentation performance and good agreement with the radiologist at fat fraction evaluation, and can be further used for muscle evaluation.

Marrow adipose tissue is increased in overweight and obese women with PCOS independently of hyperandrogenism related obesity and metabolic disorders.

Purpose: This study aimed to investigate the increase in bone marrow adipose tissue (BMAT) in overweight and obese women with polycystic ovary syndrome (PCOS) and its relationship with hyperandrogenism, obesity, and metabolic disorders. Methods: The study included 87 overweight or obese women with PCOS (mean age 29 ± 4 years), as well as 87 age-matched controls recruited from a separate population study. All PCOS patients were measured for anthropometric features, abdominal adipose tissue areas, BMAT, biochemistry, and sex hormones. BMAT was compared between the PCOS patients and controls. In PCOS patients, subgroup comparisons of BMAT and its associations with body adiposity indices, biochemistry, and sex hormones were analyzed. The odds ratios (ORs) of elevated BMAT (defined as BMAT ≥ 38%) were calculated. Results: On average BMAT was increased by 5.6% ( ± 11.3%) in PCOS patients compared to controls. BMAT were significantly higher in the upper tertiles of total cholesterol (TC) and low density lipoprotein-cholesterol (LDL-C). BMAT was not correlated with abdominal adiposity indices or biochemistry except for LDL-C (r = 0.253-0.263, p = 0.014-0.018). LDL-C was not significantly different between the normal and abnormal androgen PCOS subgroups (p = 0.10-0.887). LDL-C, follicle stimulating hormone (FSH), and total testosterone (TT) were risk factors for elevated BMAT, with ORs of 1.899 (p = 0.038-0.040), 1.369 (p = 0.030-0.042), and 1.002 (p = 0.040-0.044) for each unit increase, respectively. Conclusion: BMAT was increased in overweight and obese PCOS patients, but the increase in BMAT was not associated with the hyperandrogenism related obesity or metabolic disorders.

Site-Specific Differences in Bone Mineral Density of Proximal Femur Correlate with the Type of Hip Fracture.

The aim of this study was to investigate whether site-specific differences in bone mineral density (BMD) of proximal femur correlate with the type of hip fracture using quantitative computed tomography. Femoral neck (FN) fractures were classified as nondisplaced or displaced subtypes. Intertrochanteric (IT) fractures were classified as A1, A2, or A3. The severe hip fractures were identified as displaced FN fractures or unstable IT fractures (A2 and A3). In total, 404 FN fractures (89 nondisplaced and 317 displaced) and 189 IT fractures (76 A1, 90 A2, and 23 A3) were enrolled. Areal BMD (aBMD) and volumetric BMD (vBMD) were measured in the regions of total hip (TH), trochanter (TR), FN, and IT of the contralateral unfractured femur. IT fractures exhibited lower BMD than FN fractures (all p ≤ 0.01). However, unstable IT fractures had higher BMD compared with stable ones (p < 0.01). After adjusting for covariates, higher BMD in TH and IT were associated with IT A2 (A1 vs. A2: odds ratios (ORs) from 1.47 to 1.69, all p < 0.01). Low bone measurements were risk factors for stable IT fractures (IT A1 vs. FN fracture subtypes: ORs from 0.40 to 0.65, all p < 0.01). There are substantial site-specific differences in BMD between IT fractures A1 and displaced FN fractures. Higher bone density was associated with unstable IT fracture when compared with stable ones. The understanding of biomechanics of various fracture types could help to improve the clinical management of these patients.

Risk Factors Associated with Bone Marrow Adiposity Deposition in Postmenopausal Women in the CASH China Study.

Purpose: To investigated the factors that influence BMAC. Patients and Methods: Quantitative computed tomography (QCT) and magnetic resonance imaging (MRI) were applied to measure abdominal fat areas, liver fat content, erector muscle fat content, and BMAC of the L2-4 vertebrae. Sex hormone, adipokine, and inflammatory factor levels were measured on the same day. Results: Although age, erector muscle fat content, estradiol, testosterone, and adiponectin/leptin levels showed correlations with BMAC in the correlation analysis, the equations obtained from the whole population by multivariate analysis were unclear. Patients were stratified according to BMAC quartiles, and differences were found in vBMD, age, estradiol, testosterone, and erector muscle fat content among the four quartiles. Logistic analyses confirmed that age, estradiol/testosterone ratio, and TNF-α had independent effects on BMAC in all quartiles. In addition, height was related to higher BMAC quartiles, and glucose was related to lower BMAC quartiles. Conclusion: Compared to other body fats, BMAC is a unique fat depot. Age, estradiol/testosterone ratio, and TNF-α are all key influencing factors related to BMAC in postmenopausal women. Furthermore, height and glucose levels were related to BMAC in the higher and lower BMAC quartiles, respectively.

Percentiles for paraspinal muscle parameters at the L3 vertebra level in patients undergoing lumbar computed tomography scanning.

BACKGROUND: Computed tomography (CT) is the gold standard for analyzing muscle parameters. PURPOSE: To clarify sex-specific paraspinal muscle area (PMA), paraspinal muscle index (PMI), and muscle fat infiltration (MFI) percentiles. MATERIAL AND METHODS: This was a cross-sectional study of 760 individuals (45% men; age range = 20-92 years; mean age = 53.4 ± 21.1 years) with a body mass index (BMI) in the range of 16.4-38.1 kg/m2. CT scans were retrospectively used to establish PMA, PMI, and MFI at L3 level using a deep-learning (DL) tool. Sex-specific distributions for these parameters were assessed based on associations between age/BMI and individual muscle parameters, after which age- and BMI-specific percentile estimates were determined. The 5th percentile was regarded as the cutoff for PMA/PMI, and the 95th percentile was regarded as the cutoff for MFI. RESULTS: Sex-specific PMA, PMI, and MFI cutoffs in the paraspinal muscles group were 52.9 cm2, 15.0 cm2/m2, and 33.3%, respectively, in men, and 33.2 cm2, 9.5 cm2/m2, and 41.2% in women. Age was moderately negatively correlated with PMA and was strongly negatively correlated with PMI, but age was strongly positively correlated with MFI. BMI was moderately positively correlated with PMA/PMI in men and strongly positively correlated in women; BMI was weakly positively correlated with MFI, thus enabling the establishment of age- and BMI-specific cutoff percentiles. CONCLUSION: Sex-specific PMA, PMI, and MFI percentiles and age- and BMI-specific cutoff values for these parameters were successfully established for an outpatient population.

Biomechanical MRI detects reduced bone strength in subjects with vertebral fractures.

Vertebral fracture is one of the most serious consequences of osteoporosis. Estimation of vertebral strength from magnetic resonance imaging (MRI) scans may provide a new approach for the prediction of vertebral fractures. To that end, we sought to establish a biomechanical MRI (BMRI) method to compute vertebral strength and test its ability to distinguish fracture from non-fracture subjects. This case-control study included 30 subjects without vertebral fractures and 15 subjects with vertebral fractures. All subjects underwent MRI with a mDIXON-Quant sequence and quantitative computed tomography (QCT), from which proton fat fraction-based bone marrow adipose tissue (BMAT) content and volumetric bone mineral density (vBMD) were measured, respectively. Nonlinear finite element analysis was applied to MRI and QCT scans of L2 vertebrae to compute vertebral strength (BMRI- and BCT-strength). The differences in BMAT content, vBMD, BMRI-strength and BCT-strength between the two groups were examined by t-tests. Receiver operating characteristic (ROC) analysis was performed to assess the ability of each measured parameter to distinguish fracture from non-fracture subjects. Results showed that the fracture group had 23 % lower BMRI-strength (P < .001) and 19 % higher BMAT content (P < .001) than the non-fracture group, whereas no significant difference in vBMD was detected between the two groups. A poor correlation was found between vBMD and BMRI-strength (R2 = 0.33). Compared to vBMD and BMAT content, BMRI- and BCT-strength had the larger area under the curve (0.82 and 0.84, respectively) and provided better sensitivity and specificity in separating fracture from non-fracture subjects. In conclusion, BMRI is capable of detecting reduced bone strength in patients with vertebral fracture, and may serve as a new approach for risk assessment of vertebral fracture.

A classifier-combined method for grading breast cancer based on Dempster-Shafer evidence theory.

Background: Preoperative non-invasive histologic grading of breast cancer is essential. This study aimed to explore the effectiveness of a machine learning classification method based on Dempster-Shafer (D-S) evidence theory for the histologic grading of breast cancer. Methods: A total of 489 contrast-enhanced magnetic resonance imaging (MRI) slices with breast cancer lesions (including 171 grade Ⅰ, 140 grade Ⅱ, and 178 grade Ⅲ lesions) were used for analysis. All the lesions were segmented by two radiologists in consensus. For each slice, the quantitative pharmacokinetic parameters based on a modified Tofts model and the textural features of the segmented lesion on the image were extracted. Principal component analysis was then used to reduce feature dimensionality and obtain new features from the pharmacokinetic parameters and texture features. The basic confidence assignments of different classifiers were combined using D-S evidence theory based on the accuracy of three classifiers: support vector machine (SVM), Random Forest, and k-nearest neighbor (KNN). The performance of the machine learning techniques was evaluated in terms of accuracy, sensitivity, specificity, and the area under the curve. Results: The three classifiers showed varying accuracy across different categories. The accuracy of using D-S evidence theory in combination with multiple classifiers reached 92.86%, which was higher than that of using SVM (82.76%), Random Forest (78.85%), or KNN (87.82%) individually. The average area under the curve of using the D-S evidence theory combined with multiple classifiers reached 0.896, which was larger than that of using SVM (0.829), Random Forest (0.727), or KNN (0.835) individually. Conclusions: Multiple classifiers can be effectively combined based on D-S evidence theory to improve the prediction of histologic grade in breast cancer.

Muscle size and density are independently associated with death after hip fracture: A prospective cohort study.

BACKGROUND: Mortality following hip fracture is high and incompletely understood. We hypothesize that hip musculature size and quality are related to mortality following hip fracture. This study aims to investigate the associations of hip muscle area and density from hip CT with death following hip fracture as well as assess the dependence of this association on time after hip fracture. METHODS: In this secondary analysis of the prospectively collected CT images and data from the Chinese Second Hip Fracture Evaluation, 459 patients were enrolled between May 2015 and June 2016 and followed up for a median of 4.5 years. Muscle cross-sectional area and density were measured of the gluteus maximus (G.MaxM) and gluteus medius and minimus (G.Med/MinM) and aBMD of the proximal femur. The Goutallier classification (GC) was used for qualitatively assessing muscle fat infiltration. Separate Cox models were used to predict mortality risk adjusted for covariates. RESULTS: At the end of the follow-up, 85 patients were lost, 81 patients (64% women) had died, and 293 (71% women) survived. The mean age of non-surviving patients at death (82.0 ± 8.1 years) was higher than that of the surviving patients (74.4 ± 9.9 years). The Parker Mobility Score and the American Society of Anesthesiologists scores of the patients that died were respectively lower and higher compared to the surviving patients. Hip fracture patients received different surgical procedures, and no significant difference in the percentage of hip arthroplasty was observed between the dead and the surviving patients (P = 0.11). The cumulative survival was significantly lower for patients with low G.MaxM area and density and low G.Med/MinM density, independent of age and clinical risk scores. The GC grades were not associated with the mortality after hip fracture. Muscle density of both G.MaxM (adj. HR 1.83; 95% CI, 1.06-3.17) and G.Med/MinM (adj. HR 1.98; 95% CI, 1.14-3.46) was associated with mortality in the 1st year after hip fracture. G.MaxM area (adj. HR 2.11; 95% CI, 1.08-4.14) was associated with mortality in the 2nd and later years after hip fracture. CONCLUSION: Our results for the first time show that hip muscle size and density are associated with mortality in older hip fracture patients, independent of age and clinical risk scores. This is an important finding to better understand the factors contributing to the high mortality in older hip fracture patients and to develop better future risk prediction scores that include muscle parameters.

The lumbar spinal endplate lesions grades and association with lumbar disc disorders, and lumbar bone mineral density in a middle-young general Chinese population.

BACKGROUND: Lumbar vertebral endplates lesions (LEPLs), one of the etiologies of low back pain (LBP), are one of the most prevalent causes of health-care costs. Despite progressively becoming the focus in recent years, almost all studies have concentrated on symptomatic patients rather than general populations. As a result, our study was designed to determine the prevalence and distribution patterns of LEPLs in a middle-young general population, as well as their associations with lumbar disc herniation (LDH), lumbar disc degeneration (LDD), and lumbar vertebral volumetric bone mineral density (vBMD). METHODS: Seven hundred fifty-four participants aged 20-60 years were recruited from the subjects enrolled in a 10-year longitudinal study of degeneration of the spine and knee being conducted at the Beijing Jishuitan Hospital and 4 of them were excluded due to the missing of MRIs. In this observational study, a lumbar quantitative computed tomography (QCT) and MRI scan were performed among participants within 48 h. T2-weighted sagittal lumbar MRI images for all included subjects were identified for LEPLs by two independent observers based on morphological and local characteristics. Lumbar vertebral vBMD was measured with QCT. The age, BMI, waistline, hipline, lumbar vBMD, LDD, and LDH were measured to investigate their associations with LEPLs. RESULTS: The prevalence of LEPLs was higher among the male subjects. 80% of endplates were recognition as no lesions with a substantial disparity between female (75.6%) and male subjects (83.4%) (p < 0.001). The most common lesions were "wavy/irregular" and "notched", and "fracture" is most involved in L3-4 inferior endplate both in two genders. LEPLs were found to be associated with LDH (≥ 2 levels: OR = 6.859, P < 0.001; 1 level: OR = 2.328, P = 0.002 in men. OR = 5.004, P < 0.001; OR = 1.805, P = 0.014 in women) reference for non-LDH, and hipline in men (OR = 1.123, P < 0.001). CONCLUSIONS: LEPLs are the common findings on lumbar MRIs in general population, particularly in men. The presence of these lesions and advance from slightly to severely could be mainly attributed to LDH and men's higher hipline.