Table 2 –
Summary of pathologies and findings for 21 studies investigating elastography in patients with intracranial tumors
| Author, year | Pathology (n) | Elasticity results | Conclusions |
|---|---|---|---|
| Alawaji et al., 2021 [39] | Epidermoid cyst (4) | YM: Epidermoid cyst - 167 kPA, adjacent brain tissue - 20 kPa | Can differentiate epidermoid cysts + adjacent tissue; detect residual microscopic tumors |
| Cepeda et al., 2020 [15] | GBM (26), brain metastases (10) | Elastography AUCs: 0.85–0.99, B-mode AUCs: 0.79–0.94 | Machine learning algorithms can differentiate GBM and metastases |
| Cepeda, Arrese et al., 2021 [24] | Meningioma (18) | MTE: Soft - 95 ± 13, hard - 131 ± 7; algorithm AUC=0.96 | Machine learning algorithm can predict meningioma consistency; MTE provides a semi-quantitative analysis of elasticity |
| Cepeda, Garcia-Garcia et al., 2021 [17] | GBM (16) | NR | A radiomic feature of USE is significantly associated with overall survival; quantitative texture analysis of USE is feasible. |
| Cepeda, Garcia-Garcia et al., 2021 [16] | HGG (21), LGG (9), meningioma (10) | MTE: HGG - 85, LGG - 84, meningioma - 120; Ki-67 < 10% - 110.34, Ki-67 > 10% - 80 | Tumor MTE positively correlated with fractional anisotropy and negatively with Ki-67 index. Developed regression model to calculate MTE from fractional anisotropy |
| Chakraborty et al., 2012 [18] | GBM (12), intracranial metastases (2), other (10) | NA | USE and surgical findings of tumor stiffness are comparable, but USE did not demarcate the brain-tumor interface as accurately as B-mode US. |
| Chan et al., 2021 [19] | HGG (8), LGG (9), malignant embryonal tumor (6), meningioma (3), other (7) | YM: Tumors - 33.5 kPa, normal brain - 14.9 kPa. Residual tumor detection sensitivity: SWE - 94%, US - 73%, surgeon - 36% | YM measurements correlated with surgeons’ stiffness grading. SWE significantly outperformed surgeons in detecting residual tumor. |
| Chauvet et al., 2015 [20] | Meningioma (16), metastasis (15), HGG (18), LGG (14) | YM: Meningioma - 33.1 kPa, LGG - 23.7 kPa, HGG - 11.4 kPa, metastasis - 16.7 kPa. | Low and high-grade glioma stiffness differ significantly |
| Hughes et al., 2015 [25] | Meningioma (14) | MRE sensitivity: heterogenous tumors – 75%, hard tumors – 60%, soft tumors – 100% | MRE effective in ruling-in, but not out, heterogenous tumors. Less consistency between MRE and operative findings for small/vascular tumors. |
| Hughes et al., 2016 [29] | Pituitary macroadenoma (10) | MRE: soft tumors - 1.38 kPa; intermediate tumors - 1.94 kPa | Pituitary macroadenomas designated by surgeons as soft or intermediate differ significantly in elasticity. |
| Lagerstrand et al., 2021 [30] | Pituitary adenoma (10) | Virtual MRE: 8.32 | Virtual MRE constructed to display high resolution images and identify regions of stiffness that affect surgical outcomes. |
| Murphy et al., 2013 [38] | Meningioma (12) | Scatter chart only, averages not provided | MRE tumor stiffness correlated with surgeon’s assessment, superior to conventional MRI. |
| Pepa et al., 2020 [40] | Meningioma (36) | NA; elastograms qualitatively categorized | USE has greater accuracy and sensitivity than MRI for meningioma consistency and brain-tumor interface. |
| Prada et al., 2019 [26] | Glioma (45), meningioma (8), metastases (4), other (7) | NA; elastograms qualitatively categorized | LGG is stiffer while HGG is softer than normal brain. Elastography superior to B-mode US for identifying lesion margins |
| Sakai et al., 2016 [27] | Meningioma (13), pituitary adenoma (11), vestibular schwannoma (6), glioma (4) | MRE: Meningiomas - 1.9 kPa, pituitary adenomas - 1.2 kPa, vestibular schwannomas - 2.0 kPa, gliomas - 1.5 kPa. | MRE can discriminate tumors; stiffness significantly correlated with surgeon’s qualitative assessment of tumor consistency |
| Selbekk et al., 2005 [23] | Metastasis (1), low-grade astrocytoma (1) | NR | Tumors had lower strain than surrounding tissue. Elastography qualitatively similar to B-mode US but detected tumors absent on B-mode US. |
| Selbekk et al., 2012 [21] | LGG (8), high-grade astrocytoma (7) | Average contrast: Strain – 0.60, B-mode: 0.39 | Elastography offers better discrimination between tumors and healthy brain than B-mode US, but appears noisier. |
| Takamura et al., 2021 [28] | Meningiomas: Meningothelial (15), fibrous (12), transitional (8), angiomatous (1) | MRE: Meningioma – 3.12 kPa; stiffness inversely correlated with tumor thickness | Stiffness and intraoperative consistency significantly correlated, but did not significantly differentiate histologic subtypes. |
| Yin et al., 2015 [13] | Vestibular schwannomas (9) | NA; tumor-brain adhesion qualitatively categorized as no, partial, or complete slip interface | Slip interface imaging can reliably predict tumor adhesion and may help in preoperative planning. |
| Yin et al., 2017 [14] | Meningiomas (25) | NA; tumor-brain adhesion qualitatively categorized as no, partial, or complete slip interface | Slip interface imaging agreed with surgical findings in 72% of cases and can preoperatively evaluate tumor adhesion to brain, helping predict the surgical resection plane. |
| Yin et al., 2021 [22] | LGG (86), HGG (86) | YM: LGG – 19.7 kPa, HGG – 9.6 kPa, peritumor tissue – 8.2 kPa; HGG AUC: 0.86 | SWE can reliably differentiate low and high-grade gliomas. Optimal cutoff value for HGG is 12.1 kPa. |
AUC – area under the curve; GBM – glioblastoma; HGG – high-grade glioma; LGG – low-grade glioma; MRE – Magnetic Resonance Elastography; MTE – Mean Tissue Elasticity; NA – not applicable; NR – not reported; SWE – shear wave elastography; US – ultrasound; USE – ultrasound elastography; YM – Young’s Modulus