Predicting Grade of Esophageal Squamous Carcinoma: Can Stretched Exponential Model-Based DWI Perform Better Than Bi-Exponential and Mono-Exponential Model?

Background: To evaluate and compare the potential performance of various diffusion parameters obtained from mono-exponential model (MEM)-, bi-exponential model (BEM)-, and stretched exponential model (SEM)-based diffusion-weighted imaging (DWI) in grading of esophageal squamous carcinoma (ESC). Methods: Eighty-two patients with pathologically confirmed ESC without treatment underwent multi-b-value DWI scan with 13 b values (0~12,00 s/mm2). The apparent diffusion coefficient (ADC) deriving from the MEM; the pure molecular diffusion (ADCslow), pseudo-diffusion coefficient (ADCfast), perfusion, and fraction (f) deriving from the BEM; and the distributed diffusion coefficient (DDC) and water molecular diffusion heterogeneity index (α) deriving from the SEM were calculated and compared between poorly differentiated and well/moderately differentiated ESC, respectively. The prediction parameters and diagnostic efficiency were compared by drawing receiver operating characteristic (ROC) curves. Results: The ADC, ADCslow, ADCfast, and DDC in poorly ESC were significantly lower than those in well/moderately differentiated ones. By using only one parameter, ADCslow, DDC had the moderate diagnostic efficiency and the areas under the curve (AUC) were 0.758 and 0.813 in differentiating ESC. The DDC had the maximum AUC with sensitivity (88.00%) and specificity (68.42%). Combining ADC with ADCfast, ADCslow, and DDC and combining ADCslow with ADCfast can provide a higher diagnostic accuracy with AUC ranging from 0.756, 0.771, 0.816, and 0.793, respectively. Conclusion: Various parameters derived from different DWI models including MEM, BEM, and SEM were potentially helpful in grading ESC. DDC obtained from SEM was the most promising diffusion parameter for predicting the grade of ESC.

Altered Spontaneous Brain Activity in Patients With Diabetic Osteoporosis Using Regional Homogeneity: A Resting-State Functional Magnetic Resonance Imaging Study.

Background: The pathophysiological mechanism of cognitive impairment by osteoporosis in type 2 diabetes mellitus (T2DM) remains unclear. This study aims to further investigate the regional spontaneous brain activity changes of patients with diabetic osteoporosis (DOP), and the correlation between abnormal brain regions and bone metabolites. Methods: A total of 29 subjects with T2DM were recruited, including fourteen patients with DOP and thirteen patients without osteoporosis (Control group). Based on the resting-state functional magnetic resonance imaging (rs-fMRI) datasets acquired from all the subjects, a two-sample t-test was performed on individual normalized regional homogeneity (ReHo) maps. Spearman correlation analysis was performed between the abnormal ReHo regions with the clinical parameters and Montreal Cognitive Assessment (MOCA) scores. Results: In the DOP group, we demonstrated the significantly increased ReHo values in the left middle temporal gyrus (MTG), right superior occipital gyrus (SOG), aright superior parietal lobule (SPL), right angular gyrus (AG), and left precuneus (PE). Additionally, we also found a significant positive correlation between increased ReHo values in the left MTG and the average bone mineral density (BMD AVG), and average T scores (T AVG). The ReHo values of the right SOG and right SPL showed a negative correlation with MOCA scores, as well as a negative correlation between increased ReHo values in the right SPL and osteocalcin (OC) level. Conclusion: Patients with DOP showed increased spontaneous activity in multiple brain regions. The results indicated that osteoporosis exacerbated cognitive impairment and brain damage. Also, the OC might be considered as a bone marker to track the progression of cognitive impairment.

Radiomics nomogram based on dual-energy spectral CT imaging to diagnose low bone mineral density.

BACKGROUND: Osteoporosis is associated with a decrease of bone mineralized component as well as a increase of bone marrow fat. At present, there are few studies using radiomics nomogram based fat-water material decomposition (MD) images of dual-energy spectral CT as an evaluation method of abnormally low Bone Mineral Density (BMD). This study aims to establish and validate a radiomics nomogram based the fat-water imaging of dual-energy spectral CT in diagnosing low BMD. METHODS: Ninety-five patients who underwent dual-energy spectral CT included T11-L2 and dual x-ray absorptiometry (DXA) were collected. The patients were divided into two groups according to T-score, normal BMD(T ≥ -1) and abnormally low BMD (T < -1). Radiomic features were selected from fat-water imaging of the dual-energy spectral CT. Radscore was calculated by summing the selected features weighted by their coefficients. A nomogram combining the radiomics signature and significant clinical variables was built. The ROC curve was performed to evaluate the performance of the model. Finally, we used decision curve analysis (DCA) to evaluate the clinical usefulness of the model. RESULTS: Five radiomic features based on fat-water imaging of dual-energy spectral CT were constructed to distinguish abnormally low BMD from normal BMD, and its differential performance was high with an area under the curve (AUC) of 0.95 (95% CI, 0.89-1.00) in the training cohort and 0.97 (95% CI, 0.91-1.00) in the test cohort. The radiomics nomogram showed excellent differential ability with AUC of 0.96 (95%CI, 0.91-1.00) in the training cohort and 0.98 (95%CI, 0.93-1.00) in the test cohort, which performed better than the radiomics model and clinics model only. The DCA showed that the radiomics nomogram had a higher benefit in differentiating abnormally low BMD from normal BMD than the clinical model alone. CONCLUSION: The radiomics nomogram incorporated radiomics features and clinical factor based the fat-water imaging of dual-energy spectral CT may serve as an efficient tool to identify abnormally low BMD from normal BMD well.

Prediction of acute versus chronic osteoporotic vertebral fracture using radiomics-clinical model on CT.

PURPOSE: This paper aims to use radiomics-clinical analysis based on CT imaging to distinguish between acute and chronic osteoporotic vertebral fractures. METHOD: A total of 147 patients who underwent both dual-energy X-ray absorptiometry (DEXA), CT and MRI of the spine were analyzed retrospectively. The patients were assigned to either a training cohort (n = 103) or a validation cohort (n = 44). The radiomics model and combined nomogram model were established by multivariate logistic regression analysis. The predictive performance was assessed with receiver operating characteristic (ROC) curve. RESULTS: Fourteen radiomic features based on spine CT images were constructed to distinguish acute versus chronic osteoporotic vertebral fractures, and its differentialperformance was good with an area under the curve (AUC) of 0.90 (95% CI, 0.84-0.95) in the training cohort and 0.82 (95% CI, 0.69-0.94) in the validation cohort. Based on the radiomic signature and clinical fracture line feature, a combined nomogram was developed and showed excellent differential ability with highest AUC of 0.93 (95 %CI,0.88-0.98) in the training cohort and 0.86 (95 %CI,0.73-0.98) in the validation cohort, which performed better than the clinical model significantly only. CONCLUSIONS: A quantitative nomogram based on clinical fracture line feature and radiomic features of CT images can be used to distinguish acute and chronic osteoporotic vertebral fractures with excellent predictive ability, which can be served as a potential decision support tool to assist clinicians in evaluating the phase of vertebral fractures timely, especially in situation where spine MRI was not available for patient.

Preliminary quantitative analysis of vertebral microenvironment changes in type 2 diabetes mellitus using FOCUS IVIM-DWI and IDEAL-IQ sequences.

PURPOSE: To explore the application of intravoxel incoherent motion diffusion-weighted imaging(IVIM-DWI) on account of field-of-view optimized and constrained undistorted single shot (FOCUS) and iteraterative decomposition of water and fat with echo asymmetry and least-squares estimation quantitation(IDEAL-IQ) sequences in evaluating the vertebral microenvironment changes of type 2 diabetes mellitus(T2DM) patients and the correlation with bone mineral density(BMD). METHOD: 128 T2DM patients (mean age 63.4 ± 5.28 years) underwent both dual-energy X-ray absorptiometry (DEXA) and spine MRI. The FOCUS IVIM-DWI and IDEAL-IQ derived parameters of the vertebral body(L1, L2, L3, L4)were measured on corresponding maps of the lumbar spine. The subjects were divided into 3 groups according to T-scores as follows: normal (n = 37), osteopenia (n = 43), and osteoporosis(n = 48) group.One-way analysis of variance (ANOVA) were used to compare the vertebral parameters(ADCslow, ADCfast, f, FF, R2*) among three BMD cohorts.Receiver operating characteristic (ROC) analyses and Spearman's rank correlation were performed to test the diagnostic performance and the correlation between them respectively. RESULTS: There were significant differences in vertebral ADCslow, ADCfast, FF and R2* between the three groups (P < 0.05).Statistically, BMD was moderately negatively correlated with FF (r = -0.584, P < 0.001) and weakly positively with ADCslow (r = 0.334, P < 0.001), meanwhile moderately positively correlated with R2*(r = 0.509, P < 0.001) and ADCfast(0.545, P < 0.001).ADCfast was moderately negatively correlated with FF (r = -0.417, P < 0.001), weakly positively correlated with R2*(0.359, P < 0.001).Compared with the area under the curve (AUC) of ADCslow, ADCfast, FF and R2*, the AUC of ADCfast was higher in identifying between normal and abnormal(osteopenia and osteoporosis), normal from osteopenia, while the AUC of FF was higher in identifying osteopenia from osteoporosis. CONCLUSIONS: FOCUS IVIM-DWI and IDEAL-IQ of lumbar spine might be useful to evaluate the vertebral microenvironment changes of T2DM patients.

Diffusional kurtosis imaging in evaluation of microstructural changes of spinal cord in cervical spondylotic myelopathy feasibility study.

To explore the value of diffusion kurtosis imaging in the changes of spinal cord microstructures in patients with early cervical spondylotic myelopathy.Twenty nine patients with cervical myelopathy were selected in this study. All images were acquired on a 3.0 T MR scanner (Skyra, Siemens Medical Systems, Germany). The imaging parameters for diffusion kurtosis imaging were as follows: repetition time/echo time, 3000/91 ms; averages, 2; slice thickness/gap, 3/0.3 mm; number of slices, 17; field of view, 230 × 230 mm; Voxel size, 0.4 × 0.4 × 3.0 mm; 3 b-values (0, 1000, and 2000 s/mm) with diffusion encoding in 20 directions for each b-value. Values for fractional anisotropy, mean diffusivity, and mean diffusional kurtosis (MK) were calculated and compared between unaffected and affected spinal cords.In all patients MK was significantly lower in normal appearing spinal cords adjacent to the affected cervical spinal cords than in normal cervical spinal cords (0.862 ±â€Š0.051 vs 0.976 ±â€Š0.0924, P < .0001), but the difference of fractional anisotropy and apparent diffusion coefficient was no significant (P > .05). The affected cervical spinal cords had lower MK (0.716 ±â€Š0.0753), FA and higher apparent diffusion coefficient than normal cervical spinal cords (P < .001).MK values in the cervical spinal cord may reflect microstructural changes of spinal cord damage in cervical myelopathy, and it could potentially provide more information that obtained with conventional diffusion metrics.

Quantitative DCE-MRI: an efficient diagnostic technique for evaluating early micro-environment permeability changes in ankylosing spondylitis.

BACKGROUND: In the management of early inflammatory joint of ankylosing spondylitis (AS), there is a need for reliable noninvasive quantitative monitoring biomarker to closely assess status of synovitis progression. Cognizant to this,studies geared on improving techniques for quantitative evaluation of micro-environment permeability of the joint space are necessary. Such improved techniques may provide tissue perfusion as important biological parameters and can further help in understanding the origin of early changes associated with AS. The purpose of this study was to prospectively evaluate the diagnostic performance and determine longitudinal relationships of early micro-environment active in the joint space of the sacroiliac joint (SIJ) with a rat model by using quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). METHODS: Thirty wistar male rats were randomly assigned to the model (n = 15) or control (n = 15) group. All rats underwent DCE-MRI of SIJ region at fixed time points (12, 17 and 22 weeks),between September 2018 and October 2019. Differences in permeability parameters between the two groups at the same time point were compared by using an independent samples t test. Spearman correlations of DCE-MRI parameters with different time points in model group were analyzed. All statistical analyses were performed with software. RESULTS: At 12 weeks,the Ktrans,Kep and Ve values in the model group were slightly lower than those in control group,but all the differences were not statistically significant (p > 0.05). Compared with control group,the transfer constant (Ktrans) values increased significantly at 17 weeks and 22 weeks in model group,while the rate constant (Kep) and volume of extravascular extracellular space (Ve) significantly increased only at 22 weeks(p < 0.05). The Ktrans,Kep and Ve were positively correlated with increasing time points (r = 0.946, P<0.01 for Ktrans; r = 0.945, P<0.01 for Kep; and r = 0.832, P<0.01 for Ve). CONCLUSION: Quantitative DCE-MRI parameters are valuable for evaluating the early longitudinal relationship of micro-environment permeability changes in the joint space of SIJ.