Purpose <p>Differentiating recurrence from treatment-induced changes (TIC) in post-therapy gliomas remains a significant diagnostic challenge. This prospective study evaluated the diagnostic efficacy and prognostic value of dynamic contrast-enhanced MRI (DCE-MRI) distributed parameter (DP) model versus <sup>18</sup>F-fluoroethyltyrosine (FET) positron emission tomography (PET) in differentiating gliomas recurrence from TIC.</p> Methods <p>Adults with new or increasing contrast-enhancing lesions in MRI after treatment were prospectively included. Patients were additionally examined using <sup>18</sup>F-FET PET and DCE-MRI. DCE parameters was processed using DP and compared with maximum standardized uptake value (SUVmax), mean standardized uptake value and mean tumor-to-brain ratio measured from <sup>18</sup>F-FET PET images. Diagnostic test properties and prognosis value of DCE-MRI were determined.</p> Results <p>Normalized cerebral blood volume (nCBV ≥ 2.32) and normalized cerebral blood flow (nCBF ≥ 1.11) demonstrated sensitivities of 0.78 and 0.75, specificities of 0.88 and 1.00, diagnostic accuracy of ​0.80​ for both, and areas under the receiver operating characteristic curves (AUCs) of ​0.86​ and ​0.85, respectively. For ​FET-PET​, SUVmax cutoff of 2.36​ achieved sensitivity of ​0.93, specificity of ​0.57, accuracy of ​0.85, and AUCs of ​0.72. Weak correlations existed between DCE-MRI and FET-PET parameters (<i>r</i>: -0.05–0.20; <i>p</i> &gt; 0.05). Over a median follow-up of 11 months (IQR 8.75–15), patients with nCBV ≥ 2.32 had significantly shorter median progression-free survival (9 months vs. not-reached; <i>p</i> = 0.02).</p> Conclusion <p>DCE-MRI incorporating DP demonstrated strong diagnostic performance in distinguishing recurrent gliomas from TIC, with diagnostic accuracy comparable to <sup>18</sup>F-FET PET. Furthermore, nCBV demonstrated prognostic value for clinical outcomes in glioma patients.</p>

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The diagnostic and prognosis value of dynamic contrast-enhanced MRI distributed parameter model and 18F- fluoroethyltyrosine PET on differentiating recurrent glioma from treatment-induced change

  • Ruize Zhu,
  • Zhenyu Li,
  • Zujun Hou,
  • Tong-San Koh,
  • Xiuqi Guan,
  • Yan Ren,
  • Zhifeng Shi,
  • Zhiyong Qin,
  • Zhen Fan

摘要

Purpose

Differentiating recurrence from treatment-induced changes (TIC) in post-therapy gliomas remains a significant diagnostic challenge. This prospective study evaluated the diagnostic efficacy and prognostic value of dynamic contrast-enhanced MRI (DCE-MRI) distributed parameter (DP) model versus 18F-fluoroethyltyrosine (FET) positron emission tomography (PET) in differentiating gliomas recurrence from TIC.

Methods

Adults with new or increasing contrast-enhancing lesions in MRI after treatment were prospectively included. Patients were additionally examined using 18F-FET PET and DCE-MRI. DCE parameters was processed using DP and compared with maximum standardized uptake value (SUVmax), mean standardized uptake value and mean tumor-to-brain ratio measured from 18F-FET PET images. Diagnostic test properties and prognosis value of DCE-MRI were determined.

Results

Normalized cerebral blood volume (nCBV ≥ 2.32) and normalized cerebral blood flow (nCBF ≥ 1.11) demonstrated sensitivities of 0.78 and 0.75, specificities of 0.88 and 1.00, diagnostic accuracy of ​0.80​ for both, and areas under the receiver operating characteristic curves (AUCs) of ​0.86​ and ​0.85, respectively. For ​FET-PET​, SUVmax cutoff of 2.36​ achieved sensitivity of ​0.93, specificity of ​0.57, accuracy of ​0.85, and AUCs of ​0.72. Weak correlations existed between DCE-MRI and FET-PET parameters (r: -0.05–0.20; p > 0.05). Over a median follow-up of 11 months (IQR 8.75–15), patients with nCBV ≥ 2.32 had significantly shorter median progression-free survival (9 months vs. not-reached; p = 0.02).

Conclusion

DCE-MRI incorporating DP demonstrated strong diagnostic performance in distinguishing recurrent gliomas from TIC, with diagnostic accuracy comparable to 18F-FET PET. Furthermore, nCBV demonstrated prognostic value for clinical outcomes in glioma patients.