Fat fraction quantification of lumbar spine: comparison of T1-weighted two-point Dixon and single-voxel magnetic resonance spectroscopy in diagnosis of multiple myeloma

Pei, Xiao-Jiao; Lian, Yu-Fei; Yan, Yuchang; Jiang, Tao; Liu, Aijun; Shi, Qinglei; Pan, Zhenyu

doi:10.5152/dir.2020.19401

Cited by 7 publications

(5 citation statements)

References 27 publications

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“…Pei et al. ( 16 ) previously reported that the fat content of bone marrow decreased by MRI, and a large sample retrospective study from the Korean reported consistent findings ( 17 ).…”

Section: Discussionmentioning

confidence: 69%

Serum Abnormal Metabolites for Evaluating Therapeutic Response and Prognosis of Patients With Multiple Myeloma

et al. 2022

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AimsTo evaluate abnormal metabolites related to treatment response and prognosis of multiple myeloma (MM) patients through ultra performance liquid chromatography tandem mass spectrometry (UPLC-MS).MethodsForty-six symptomatic MM patients were included in this study who had a prior high level of positive monoclonal proteins before receiving targeted therapy with bortezomib-based regimens. UPLC-MS along with traditional immunofixation was performed on MM diagnostic samples and effective serum samples, and UPLC-MS was used to target valuable metabolic markers related to M protein.MM patients were segregated into pre-therapy (pre-T) and post-therapy (post-T) groups according to the response after chemotherapy. A monoclonal protein could be detected at baseline in 33 newly diagnosed MM (NDMM), 13 refractory and relapsed MM (RRMM) patients and 20 healthy controls (HC) by immunofixation.ResultsBetween pre-T and post-T patients, the data showed that 32, 28 and 3 different metabolites were significantly correlated with M protein in IgG, IgA and light chain-type MM, respectively. These identified metabolites were significantly enriched in arginine and proline metabolism as well as glycerophospholipid metabolism pathways. Among them, PC (19:0/22:2) was displayed to increase significantly and consistently with M protein in each subtype of MM after treatment, which obviously indicated that it was related to the treatment response of MM. Further survival analysis of metabolic markers found that aspartic acid, LysoPE (16:0), SM (d18:1/17:0), PC (18:0/24:1), PC (16:0/16:0), TG (18:1/18:1/22:5) and LysoPE (18:2) reaching a certain cutoff value may be associated with shorter progression free survival (PFS). Finally, Cox multivariate regression analysis identified three factors were independent prognostic factors of MM. Moreover, there were significantly different in PC (19:0/22:2) and in aspartic acid between MM patients and healthy people.ConclusionThis work identified significant metabolic disorders in 46 pairs off pre- and post-therapy MM patients, specifically in arginine, proline and glycerophospholipid pathways. The abnormal metabolites have the potential to serve as new biomarkers for evaluating treatment response and prognosis, as well as early monitoring of disease activity. Therefore, these systematic studies on abnormal metabolites as biomarkers for diagnosis and treatment will provide the evidence for future precise treatment of MM.

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“…Pei et al. ( 16 ) previously reported that the fat content of bone marrow decreased by MRI, and a large sample retrospective study from the Korean reported consistent findings ( 17 ).…”

Section: Discussionmentioning

confidence: 69%

Serum Abnormal Metabolites for Evaluating Therapeutic Response and Prognosis of Patients With Multiple Myeloma

et al. 2022

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“…Second, it can only perform single-site sampling instead of volumetric scanning; that is, sampling bias. Finally, the technical precision of MRS may need to be reconsidered because of the lack of sufficiently high spectral resolution at clinical field strengths, resulting in difficulty in completely distinguishing the water and fat peaks on fat quantification [ 11 , 15 ]. Therefore, the ideal IDEAL-IQ requires full consideration and correction of confounding factors.…”

Section: Discussionmentioning

confidence: 99%

Repeatability and Image Quality of IDEAL-IQ in Human Lumbar Vertebrae for Fat and Iron Quantification across Acquisition Parameters

Shan

Ding

Lin

et al. 2022

Computational and Mathematical Methods in Medicine

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Echo asymmetry and least square estimation-IQ (IDEAL-IQ) were used to quantify fat and iron to verify the effects of collection parameters on repeatability and image quality of water and fat in human vertebral body. Six IDEAL-IQ sequences were used to scan 48 healthy adult women. Reproducibility of fat and iron quantification and image quality were assessed for six IDEAL-IQ sequences. The results showed that the correlation index (0.987, 0.721) of FF and R2 ∗ between scans of sequence 2 was higher than that of other sequences, and the consistency of fat quantification was better than that of iron (0.860 vs. 0.579) ( P < 0.001 ). Sequence 2 had the highest image quality score (4.9) and the lowest CV score (9.2%). In the FF figure, SNR (18.8) and CNR ( 17.8 ± 6.4 ) were the highest, while CV was the lowest (36.7%, 36.1%). In the R2 ∗ figure, sequence 3 had the highest SNR (21.8) and CNR (20.5), but its CV (51.8% and 56.1%) was significantly higher than that of sequence 2. The occurrence of fat-water exchange (FWS) was lowest in sequence 2 and sequence 4 (0, N = 96 ). In conclusion, the fat quantification of IDEAL-IQ was robust to the changes of collection parameters, and section thickness (ST) had a certain effect on maintaining good repeatability of R2 ∗ quantification. The higher the ST was, the better the image quality of FF and R2 ∗ was maintained and stable and the less the occurrence of FWS.

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“…MRS is considered by many scholars to be the gold standard for the quantitative assessment of fat composition in vivo; however, it is extremely limited in skeletal system disease due to its long scan time and complex post-processing [6]. With the advent of aqueous lipid separation technology, rapid and accurate assessment of BMFF has become possible, and the results match well with MRS measurements [7,8]. This indicates that water-lipid separation technology has unquestionable feasibility and application value in clinical practice.…”

Section: The Clinical Diagnosis Of Osteoporosis Is Based On T-scores ...mentioning

confidence: 99%

Quantitative analysis of vertebral fat fraction in osteoporosis using IDEAL-IQ sequences

Zhu

Sheng

2023

Preprint

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Objective To investigate the predictive value of vertebral fat fraction (FF) values from IDEAL-IQ sequences in distinguishing between normal bone mass, osteopenia, and osteoporosis.Methods We recruited 105 women and 69 men over 30 years of age who voluntarily underwent DXA, QCT scans, and MRI examinations and collected clinical information from each subject. Bone mineral density (BMD) values measured by DXA and QCT were used as reference standards. The intra-observer correlation coefficient (ICC) was used to assess the reproducibility of inter-observer and intra-observer measurements. One-way ANOVA, Pearson correlation analysis, and subject work characteristic curve analysis were performed.Results The age, height, weight, BMD, and FF values in the DXA and QCT subgroups were significantly different (P < 0.05). Interestingly, FF was correlated with visceral adiposity (r = 0.221, P = 0.003) in the QCT grouping. FF was moderately negatively correlated with aBMD values (r = − 0.515, P < 0.001; after correcting for gender and age: r = − 0.316, P < 0.001), and FF showed a significant negative correlation with vBMD (r = − 0.790, P < 0.001; after correcting for gender and age: r = − 0.601, P < 0.001). Lumbar FF was positively correlated with age (r = 0.643, P < 0.001). In the DXA subgroup, the area under the curve (AUC) value of the FF values for distinguishing low bone mass was estimated to be 0.714, with a sensitivity of 0.822, a specificity of 0.518, and a cut-off value of 42.85%. In the QCT subgroup, the AUC of the FF values for distinguishing low bone mass was estimated to be 0.869, with a sensitivity of 0.841, a specificity of 0.721, and a cut-off value of 47.97%.Conclusions The vertebral FF value from IDEAL-IQ sequences has the potential to be a new biological marker for the assessment of osteopenia and osteoporosis. The FF value was more effective in assessing low bone mass measured by QCT than DXA, so QCT combined with IDEAL-IQ sequences is superior for obtaining a comprehensive assessment of osteoporosis.

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Fat fraction quantification of lumbar spine: comparison of T1-weighted two-point Dixon and single-voxel magnetic resonance spectroscopy in diagnosis of multiple myeloma

Cited by 7 publications

References 27 publications

Serum Abnormal Metabolites for Evaluating Therapeutic Response and Prognosis of Patients With Multiple Myeloma

Serum Abnormal Metabolites for Evaluating Therapeutic Response and Prognosis of Patients With Multiple Myeloma

Repeatability and Image Quality of IDEAL-IQ in Human Lumbar Vertebrae for Fat and Iron Quantification across Acquisition Parameters

Quantitative analysis of vertebral fat fraction in osteoporosis using IDEAL-IQ sequences

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