Investigation of Diagnostic Biomarkers for Osteoporosis Based on Differentially Expressed Gene Profile with <scp>QCT and mDixon‐Quant</scp> Techniques

Zhu, Shan; Guo, L. Jay; Xu, Haowen; Li, Xiaofeng; Wang, Zhi; He, Feng

doi:10.1111/os.13094

Cited by 4 publications

(3 citation statements)

References 23 publications

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“…However, visual semi-quantitative assessment methods are affected by inter-observer differences, which will affect the results of analysis to some extent. The mDIXON-Quant sequence is a 3-dimensional Fast Field Echo (3D-FFE) sequence that uses multiple acquired echoes to generate water, fat, in-phase, and inverted images synthesized from water-fat images ( 24 – 26 ). Because there is almost no limit on echo time, mDIXON-Quant has the advantage of being more efficient and accurate than other MR fat quantification techniques.…”

Section: Discussionmentioning

confidence: 99%

Correlation between degeneration of cervical intervertebral disc and degeneration of paravertebral muscle

Li,

Long,

Wang

et al. 2024

Front. Endocrinol.

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ObjectiveTo investigate the relationship between degeneration of cervical intervertebral disc and degeneration of paravertebral muscles[multifidus (MF), cervical semispinalis (SCer), semispinalis capitis (SCap) and splenius capitis (SPL)].Methods82 patients with chronic neck pain were randomly selected, including 43 males and 39 females, with 50.73 0.7.51 years old. All patients were scanned by 3.0T MRI Philips Ingenia performed conventional MRI sequence scanning and fat measurement sequence mDIXON-Quant scanning of cervical. Fat infiltration (FI) and cross-sectional area (CSA) of cervical paravertebral muscle (MF, SCer, SCap and SPL) at central level of C5–6 disc were measured by Philips 3.0T MRI image post-processing workstation. According to Pfirrmann grading system, there was no grade I in the included cases. The number of grade IIr IV cases were n=16, 40, 19 and 7 respectively. CSA and FI of cervical paravertebral muscles were compared with t test or one-way ANOVA, Spearman correlation analysis was used to evaluate the correlation between age, disc degeneration, and CSA, FI of cervical paravertebral muscles, and multiple linear regression analysis was used to analyze the independent influencing factors of CSA and FI.ResultsCSA of cervical paravertebral muscles in male patients was significantly higher than that in female patients (all P<0.001), but there was no significant difference in FI (all P>0.05). Age was weakly correlated with CSA of MF+SCer, moderately correlated with CSA of SCap and SPL (r=-0.256, -0.355 and -0.361, P<0.05), weakly correlated with FI of SCap and SPL (r= 0.182 and 0.264, P<0.001), moderately correlated with FI of MF+SCer (r=0.408, P<0.001). There were significant differences in FI with disc degeneration (P<0.001, P=0.028 and P=0.005). Further correlation analysis showed that disc degeneration was strongly correlated with FI of MF+SCer (r=0.629, P<0.001), and moderately correlated with FI of SCap and SPL (r=0.363, P=0.001; r=0.345, P=0.002). Multiple linear regression analysis showed that sex and age were the influencing factors of CSA of SCap and SPL, sex was the independent influencing factor of CSA of MF+SCer, and disc degeneration was the independent influencing factor of FI.ConclusionsAge is negatively correlated with CSA and positively correlated with FI. Disc degeneration was correlated with FI of paravertebral muscles, especially with FI of MF and SCer. Sex and age were the influencing factors of CSA, while disc degeneration was the independent influencing factor of FI.

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Section: Discussionmentioning

confidence: 99%

Correlation between degeneration of cervical intervertebral disc and degeneration of paravertebral muscle

Li,

Long,

Wang

et al. 2024

Front. Endocrinol.

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“…T2* mapping generated by mDIXON Quant enables the evaluation of bone microstructure and facilitates the detection of changes in bone mineral density. 14 However, studies assessing the associations of MRI functional parameters with cytogenetic abnormalities in MM are very limited. 15,16 Therefore, this study aimed to establish quantitative criteria for identifying HRMM utilizing DWIBS and mDIXON Quant imaging as well as clinical parameters, and to assess the associations of diffuse infiltration with cytogenetic abnormalities in MM.…”

mentioning

confidence: 99%

“…Fat fraction (FF) measurement could help assess bone marrow fat content. T2* mapping generated by mDIXON Quant enables the evaluation of bone microstructure and facilitates the detection of changes in bone mineral density 14 . However, studies assessing the associations of MRI functional parameters with cytogenetic abnormalities in MM are very limited 15,16 …”

mentioning

confidence: 99%

Quantitative Analysis of Whole‐Body MRI for Accessing the Degree of Diffuse Infiltration Patterns and Identifying High Risk Cases of Newly Diagnosed Multiple Myeloma

Sun,

Wang,

Wang

et al. 2023

Magnetic Resonance Imaging

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BackgroundAccurate identification of high‐risk multiple myeloma (HRMM) is important for prognostication. The degree of diffuse infiltration patterns on magnetic resonance imaging (MRI) is associated with patient prognosis in multiple myeloma. However, objective indexes to determine the degree of diffuse infiltration patterns are unavailable.PurposeTo investigate whether qualitative and quantitative evaluations of diffuse infiltration patterns on MRI could identify HRMM.Study TypeRetrospective.SubjectsTotally, 180 patients (79 HRMM and 101 standard‐risk MM) were assessed. The presence of del(17p), t(4;14), t(14;16), t(14;20), gain 1q, and/or p53 mutations was considered to indicate HRMM.Field Strength/Sequence3.0 T/diffusion‐weighted whole‐body imaging with background body signal suppression (DWIBS), modified Dixon chemical‐shift imaging Quant (mDIXON Quant), and short TI inversion recovery (STIR).AssessmentQualitative analysis involved assessing the degree of diffuse marrow infiltration (mild, moderate, or severe), and quantitative analysis involved evaluating apparent diffusion coefficient (ADC), fat fraction (FF), and T2* values. Clinical data such as sex, age, hemoglobin, serum albumin, serum calcium, serum creatinine, serum lactate dehydrogenase, β2‐microglobulin, and bone marrow plasma cells (BMPCs) were also included.Statistical TestsUnivariate and multivariate analyses, receiver operating characteristic (ROC) curve. P < 0.05 was considered statistically significant.ResultsThe high‐risk group had significantly higher ADC and T2* and lower FF compared with the standard‐risk group. Multivariate analysis indicated BMPCs as a significant independent risk factor for HRMM (odds ratio (OR) = 1.019, 95% CI 1.004–1.033), while FF was a significant independent protective factor associated with HRMM (OR = 0.972, 95% CI 0.946–0.999). The combination of BMPCs and FF achieved the highest areas under the curve (AUC) of 0.732, with sensitivity and specificity of 70.9% and 68.3%, respectively.Data ConclusionCompared with qualitative analysis, FF value was independently associated with HRMM. The quantitative features of diffuse marrow infiltration on MRI scans are more effective in detecting HRMM.Level of Evidence3Technical EfficacyStage 2

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DeepmdQCT: A multitask network with domain invariant features and comprehensive attention mechanism for quantitative computer tomography diagnosis of osteoporosis

Zhang,

Lin,

Pan

et al. 2024

Computers in Biology and Medicine

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Investigation of Diagnostic Biomarkers for Osteoporosis Based on Differentially Expressed Gene Profile with QCT and mDixon‐Quant Techniques

Cited by 4 publications

References 23 publications

Correlation between degeneration of cervical intervertebral disc and degeneration of paravertebral muscle

Correlation between degeneration of cervical intervertebral disc and degeneration of paravertebral muscle

Quantitative Analysis of Whole‐Body MRI for Accessing the Degree of Diffuse Infiltration Patterns and Identifying High Risk Cases of Newly Diagnosed Multiple Myeloma

DeepmdQCT: A multitask network with domain invariant features and comprehensive attention mechanism for quantitative computer tomography diagnosis of osteoporosis

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