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Background <p>Differentiating lymphoma from benign and metastatic lymphadenopathies using conventional ultrasound remains clinically challenging. Despite the utility of ultrasound elastography in assessing tissue stiffness, the intermediate stiffness profile of lymphoma frequently leads to misclassification. To address this diagnostic gap, we conducted a comprehensive systematic review and Bayesian diagnostic meta-analysis to evaluate the performance of various elastography modalities.</p> Methods <p>Following PRISMA 2020 guidelines (PROSPERO: CRD420251184980), we systematically searched PubMed, Embase, Web of Science, and the Cochrane Library. Original studies evaluating elastography against valid reference standards were included, and methodological quality was assessed using the QUADAS-2 tool. Diagnostic performance was synthesized via a robust two-tiered Bayesian bivariate hierarchical random-effects model to calculate pooled sensitivity, specificity, diagnostic odds ratios (DOR), and likelihood ratios (PLR/NLR) for both overall and modality-specific analyses.</p> Results <p>Twenty studies encompassing 2,342 patients and 2,626 superficial lymph nodes (981 benign, 895 lymphoma, 750 metastatic) were included. In differentiating lymphoma from benign lymphadenopathy, Shear Wave Velocity (SWV) exhibited the highest sensitivity (0.913) and lowest negative likelihood ratio (NLR, 0.117). Conversely, aggregated Strain Elastography (SE) scoring achieved the highest specificity (0.909) and positive likelihood ratio (PLR, 7.59). When distinguishing lymphoma from metastatic nodes, Virtual Touch Tissue Imaging (VTI) techniques demonstrated robust diagnostic yield for identifying lymphoma; specifically, the VTI ratio achieved the highest diagnostic odds ratio (DOR, 39.4), with a sensitivity of 0.92 and an NLR of 0.11.</p> Conclusion <p>Ultrasound elastography provides significant modality-specific diagnostic value for stratifying lymphadenopathy. SWV effectively excludes lymphoma from benign nodes, whereas SE scoring optimizes its confirmation. Furthermore, VTI techniques robustly distinguish lymphoma from metastasis. However, given substantial inter-study heterogeneity, elastography should be integrated as a complementary multiparametric adjunct to guide biopsy triage, rather than replace definitive histopathological evaluation.</p>

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Elastography for distinguishing lymphoma from benign and metastatic lymphadenopathy: a systematic review and Bayesian meta-analysis

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月10日

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  • Fatemeh Mahdavi Sabet,
  • Shayan Forghani,
  • Amirhossein Shahsavand,
  • Mohammadamin Kharaghani,
  • Reza Samiee,
  • Fahimeh Zeinalkhani,
  • Elham Neshan

摘要

Background

Differentiating lymphoma from benign and metastatic lymphadenopathies using conventional ultrasound remains clinically challenging. Despite the utility of ultrasound elastography in assessing tissue stiffness, the intermediate stiffness profile of lymphoma frequently leads to misclassification. To address this diagnostic gap, we conducted a comprehensive systematic review and Bayesian diagnostic meta-analysis to evaluate the performance of various elastography modalities.

Methods

Following PRISMA 2020 guidelines (PROSPERO: CRD420251184980), we systematically searched PubMed, Embase, Web of Science, and the Cochrane Library. Original studies evaluating elastography against valid reference standards were included, and methodological quality was assessed using the QUADAS-2 tool. Diagnostic performance was synthesized via a robust two-tiered Bayesian bivariate hierarchical random-effects model to calculate pooled sensitivity, specificity, diagnostic odds ratios (DOR), and likelihood ratios (PLR/NLR) for both overall and modality-specific analyses.

Results

Twenty studies encompassing 2,342 patients and 2,626 superficial lymph nodes (981 benign, 895 lymphoma, 750 metastatic) were included. In differentiating lymphoma from benign lymphadenopathy, Shear Wave Velocity (SWV) exhibited the highest sensitivity (0.913) and lowest negative likelihood ratio (NLR, 0.117). Conversely, aggregated Strain Elastography (SE) scoring achieved the highest specificity (0.909) and positive likelihood ratio (PLR, 7.59). When distinguishing lymphoma from metastatic nodes, Virtual Touch Tissue Imaging (VTI) techniques demonstrated robust diagnostic yield for identifying lymphoma; specifically, the VTI ratio achieved the highest diagnostic odds ratio (DOR, 39.4), with a sensitivity of 0.92 and an NLR of 0.11.

Conclusion

Ultrasound elastography provides significant modality-specific diagnostic value for stratifying lymphadenopathy. SWV effectively excludes lymphoma from benign nodes, whereas SE scoring optimizes its confirmation. Furthermore, VTI techniques robustly distinguish lymphoma from metastasis. However, given substantial inter-study heterogeneity, elastography should be integrated as a complementary multiparametric adjunct to guide biopsy triage, rather than replace definitive histopathological evaluation.