CT and MR for bone mineral density and trabecular bone score assessment in osteoporosis evaluation

Lee, Haein; Park, Sunghoon; Kwack, Kyu-Sung; Yun, Jae Sung

doi:10.1038/s41598-023-43850-z

Cited by 7 publications

(1 citation statement)

References 33 publications

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“…On this respect, there have been recent attempts to diagnose osteoporosis using MR-based proton density fat fraction (PDFF) measurements. In a recent study, CTbased HU values demonstrated good performance and PDFF showed fair performance to diagnose osteopenia and osteoporosis, suggesting that PDFF also could be used to investigate BMD without exposure to ionizing radiation [51].…”

Section: Future Perspectives: Artificial Intelligencementioning

confidence: 99%

Phantomless Computed Tomography-Based Quantitative Bone Mineral Density Assessment: A Literature Review

Mallio,

Vertulli,

Bernetti

et al. 2024

Applied Sciences

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The global surge in aging populations has intensified osteoporosis challenges, necessitating improved diagnostic methods. While dual X-ray absorptiometry (DXA) is the conventional standard in assessing bone mineral density (BMD), the exploration of quantitative computed tomography (QCT) has been proposed, particularly phantomless techniques. Challenges in single-energy CT, emphasizing internal calibration standards like subcutaneous fat, are discussed. Advances in PL-QCT, notably with automatic region of interest (ROI) selection, show improved accuracy. Dual-energy CT (DECT) introduces new dimensions for musculoskeletal analysis. Despite advancements, challenges persist, including interindividual variability and patient-specific factors. Evolving single-energy CT and DECT techniques show promise in refining BMD assessment and osteoporosis diagnosis, enhancing patient care. Continued research and integration into clinical practice are vital for realizing these advancements’ full benefits. In this review, we evaluate and summarize current evidence on the feasibility and different approaches to achieve analysis of BMD with phantomless QCT.

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Section: Future Perspectives: Artificial Intelligencementioning

confidence: 99%

Phantomless Computed Tomography-Based Quantitative Bone Mineral Density Assessment: A Literature Review

Mallio,

Vertulli,

Bernetti

et al. 2024

Applied Sciences

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Chemical Shift‐Encoded MRI of the Lumbar Vertebral Bone Marrow for Detecting Osteoporosis With Low Trabecular Bone Quality in Patients With Breast Cancer Receiving Aromatase Inhibitors

Misaka,

Hashimoto,

Ashikaga

et al. 2024

Magnetic Resonance Imaging

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BackgroundOsteoporosis with low trabecular bone quality (OLB) in patients with breast cancer receiving aromatase inhibitor (AI) therapy is associated with an increased risk of vertebral fractures. The capability of chemical shift‐encoded MRI (CSE‐MRI) in detecting OLB needs to be investigated.PurposeTo assess the diagnostic performance of proton density fat fraction (PDFF) and R2* measurements from CSE‐MRI for detecting OLB in postmenopausal women with breast cancer undergoing AI therapy.Study TypeProspective.Population126 postmenopausal females (mean age: 69.5 ± 8.8 years) receiving AIs (average period: 41.6 ± 26.5 months) after breast cancer surgery.Field Strength/Sequence1.5‐T, three‐dimensional CSE‐MRI (six echoes), T1‐weighted Dixon, short tau inversion recovery, and diffusion‐weighted images.AssessmentBoth CSE‐MRI and dual‐energy x‐ray absorptiometry were performed on the same day. Measurements included averaged PDFF, R2*, bone mineral density (BMD), and trabecular bone score (TBS) from L1 to L4 vertebrae. A T‐score ≤ −2.5 from BMD measurements indicated osteoporosis, whereas T‐scores of ≤ − 2.5 plus TBS ≤‐3.7 indicated OLB. The diagnostic performance of PDFF, R2*, and the combination of PDFF and R2* for identifying osteoporosis or OLB was assessed.Statistical TestsStudent's t‐test; Mann–Whitney U test; χ2 or Fisher exact tests; Pearson correlation; multivariate analysis; Receiver operating characteristic (ROC) analysis with the area under the curve (AUC); logistic regression model; intraclass correlation coefficient. A P‐value <0.05 was considered statistically significant.ResultsFor detecting osteoporosis, AUC values were 0.59 (PDFF), 0.66 (R2*), and 0.65 (combined PDFF and R2*). Significant mean differences were noted between patients with and without OLB for PDFF (66.11 ± 5.36 vs. 57.49 ± 6.43) and R2* (46.62 ± 9.24 vs. 63.36 ± 12.44). AUC values for detecting OLB were 0.75 (PDFF), 0.82 (R2*), and 0.84 (combined PDFF and R2*).Data ConclusionR2* may perform better than PDFF for identifying OLB in patients with breast cancer receiving AIs.Level of Evidence2Technical EfficacyStage 4

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Factors influencing vertebral collapse in osteoporotic vertebral fractures: a case–control study of symptomatic patients attended in the emergency department

Ruiz Santiago,

Láinez Ramos-Bossini,

Moraleda-Cabrera

2023

Arch Osteoporos

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CT and MR for bone mineral density and trabecular bone score assessment in osteoporosis evaluation

Cited by 7 publications

References 33 publications

Phantomless Computed Tomography-Based Quantitative Bone Mineral Density Assessment: A Literature Review

Phantomless Computed Tomography-Based Quantitative Bone Mineral Density Assessment: A Literature Review

Chemical Shift‐Encoded MRI of the Lumbar Vertebral Bone Marrow for Detecting Osteoporosis With Low Trabecular Bone Quality in Patients With Breast Cancer Receiving Aromatase Inhibitors

Factors influencing vertebral collapse in osteoporotic vertebral fractures: a case–control study of symptomatic patients attended in the emergency department

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