Preoperative Adult-Type Diffuse Glioma Subtype Prediction with Dynamic Contrast-Enhanced MR Imaging and Diffusion Weighted Imaging in Tumor Cores and Peritumoral Tissue—A Standardized Multicenter Study
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Design
2.2. Patients
2.3. MR Imaging
2.4. Image Analysis
2.5. Postoperative Tumor Subtyping
- (i).
- Glioblastomas, IDH wildtype;
- (ii).
- Astrocytomas, IDH mutant;
- (iii).
- Oligodendrogliomas, IDH mutant and 1p/19q-codeleted.
2.6. Statistical Analysis
3. Results
3.1. Patients
3.2. Comparison of DKI and DCE-MRI Parameters in Each ROI
3.3. Diagnostic Performance in Differentiating IDH Wildttype from IDH Mutant Gliomas
3.4. Diagnostic Performance in Differentiating Astocytomas, IDH Mutant from Oligodendrogliomas, IDH Mutant
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Patients enrolled in the study | 108 |
Patients excluded due to histopathological/molecular results | 24 |
Patients excluded due to insufficient MRI quality | 25 |
Patients included in the analysis | 59 |
Mean age of the included patients ± standard deviation | 45.3 ± 15.7 |
Female/Male ratio | 1:1.6 |
Glioblastoma, IDH wildtype (WHO grade 4) | 31 (47.4%) |
Astrocytoma, IDH mutant (WHO grade 2) | 12 (18.5%) |
Astrocytoma, IDH mutant (WHO grade 3) | 1 (1.5%) |
Astrocytoma, IDH mutant (WHO grade 4) | 4 (6.2%) |
Oligodendroglioma, IDH mutant (WHO grade 2) | 3 (4.6%) |
Oligodendroglioma, IDH mutant (WHO grade 3) | 8 (12.3%) |
ROI1 | ROI2 | ROI3 | ROI4 | ROI5 | ROI with Maximum AUC | ||
---|---|---|---|---|---|---|---|
ADC | AUC (95% CI) | 0.641 (0.452–0.830) | 0.855 * (0.738–0.972) | 0.902 * (0.812–0.992) | 0.894 * (0.797–0.991) | 0.910 * (0.824–0.995) | 0.910 * (0.824–0.995) |
Sensitivity | 0.933 | 0.867 | 0.767 | 0.833 | 0.833 | 0.833 | |
Specificity | 0.529 | 0.824 | 0.941 | 0.882 | 0.882 | 0.882 | |
MK | AUC (95% CI) | 0.698 * (0.522–0.874) | 0.816 * (0.672–0.959) | 0.882 * (0.680–0.963) | 0.798 * (0.638–0.958) | 0.778 * (0.609–0.948) | 0.882 * (0.680–0.963) |
Sensitivity | 0.867 | 0.933 | 0.993 | 0.800 | 0.867 | 0.993 | |
Specificity | 0.588 | 0.706 | 0.665 | 0.882 | 0.665 | 0.665 | |
Ktrans | AUC (95% CI) | 0.945 * (0.885–1.000) | 0.788 * (0.648–0.928) | 0.584 (0.414–0.754) | 0.586 (0.423–0.750) | 0.588 (0.417–0.760) | 0.945 * (0.885–1.000) |
Sensitivity | 0.833 | 0.600 | 0.733 | 0.467 | 0.467 | 0.833 | |
Specificity | 0.941 | 0.941 | 0.529 | 0.824 | 0.765 | 0.941 | |
Kep | AUC (95% CI) | 0.769 * (0.628–0.909) | 0.759 * (0.612–0.905) | 0.629 (0.463–0.796) | 0.575 (0.409–0.740) | 0.506 (0.321–0.690) | 0.769 * (0.628–0.909) |
Sensitivity | 0.700 | 0.700 | 0.500 | 0.567 | 0.800 | 0.700 | |
Specificity | 0.765 | 0.824 | 0.765 | 0.706 | 0.353 | 0.765 | |
vp | AUC (95% CI) | 0.516 (0.350–0.681) | 0.590 (0.422–0.758) | 0.575 (0.398–0.751) | 0.614 (0.443–0.784) | 0.541 (0.371–0.711) | 0.614 (0.443–0.784) |
Sensitivity | 0.367 | 0.267 | 1.000 | 0.800 | 0.500 | 0.800 | |
Specificity | 0.941 | 0.882 | 0.235 | 0.471 | 0.806 | 0.471 | |
ve | AUC (95% CI) | 0.963 * (0.917–1.000) | 0.841 * (0.721–0.961) | 0.490 (0.321–0.659) | 0.637 (0.476–0.798) | 0.633 (0.463–0.804) | 0.963 * (0.917–1.000) |
Sensitivity | 0.867 | 0.900 | 0.667 | 0.700 | 0.533 | 0.867 | |
Specificity | 0.941 | 0.706 | 0.176 | 0.706 | 0.765 | 0.941 | |
CBV | AUC (95% CI) | 0.924 * (0.848–1.000) | 0.755 * (0.610–0.900) | 0.580 (0.411–0.750) | 0.520 (0.353–0.686) | 0.520 (0.347–0.692) | 0.924 * (0.848–1.000) |
Sensitivity | 0.867 | 0.733 | 0.600 | 0.200 | 0.600 | 0.867 | |
Specificity | 0.941 | 0.765 | 0.529 | 1.000 | 0.588 | 0.941 | |
TTP | AUC (95% CI) | 0.859 * (0.742–0.976) | 0.792 * (0.654–0.930) | 0.651 (0.492–0.810) | 0.527 (0.353–0.701) | 0.545 (0.371–0.719) | 0.859 * (0.742–0.976) |
Sensitivity | 0.833 | 0.733 | 0.567 | 0.433 | 0.600 | 0.833 | |
Specificity | 0.824 | 0.882 | 0.706 | 0.647 | 0.471 | 0.824 | |
Peak | AUC (95% CI) | 0.939 * (0.868–1.000) | 0.749 * (0.611–0.887) | 0.508 (0.340–0.676) | 0.608 (0.444–0.772) | 0.653 (0.487–0.819) | 0.939 * (0.868–1.000) |
Sensitivity | 0.900 | 0.700 | 0.500 | 0.533 | 0.567 | 0.900 | |
Specificity | 0.941 | 0.824 | 0.294 | 0.824 | 0.765 | 0.941 | |
AUC | AUC (95% CI) | 0.947 * (0.884–1.000) | 0.776 * (0.645–0.908) | 0.435 (0.268–0.603) | 0.635 (0.476–0.795) | 0.663 (0.484–0.832) | 0.947 * (0.884–1.000) |
Sensitivity | 0.833 | 0.633 | 0.467 | 0.433 | 0.700 | 0.833 | |
Specificity | 1.000 | 0.882 | 0.235 | 0.882 | 0.665 | 1.000 | |
Wash in | AUC (95% CI) | 0.669 * (0.510–0.828) | 0.614 (0.451–0.777) | 0.627 (0.469–0.786) | 0.596 (0.434–0.758) | 0.567 (0.396–0.737) | 0.669 * (0.510–0.828) |
Sensitivity | 0.500 | 0.700 | 0.467 | 0.400 | 0.300 | 0.500 | |
Specificity | 0.824 | 0.588 | 0.882 | 0.882 | 0.882 | 0. 824 | |
Wash out | AUC (95% CI) | 0.894 * (0.798–0.991) | 0.814 * (0.687–0.941) | 0.625 (0.464–0.787) | 0.533 (0.362–0.705) | 0.429 (0.258–0.6011) | 0.894 * (0.798–0.991) |
Sensitivity | 0.833 | 0.833 | 0.467 | 0.233 | 0.333 | 0.833 | |
Specificity | 0.941 | 0.824 | 0.765 | 0.941 | 0.471 | 0. 941 | |
Combined ve and ADC | AUC (95% CI) | 0.976 * (0.943–1.000) | |||||
Sensitivity | 0.933 | ||||||
Specificity | 0.882 |
ROI1 | ROI2 | ROI3 | ROI4 | ROI5 | ROI with Maximum AUC | ||
---|---|---|---|---|---|---|---|
ADC | AUC (95% CI) | 0.615 (0.398–0.832) | 0.802 * (0.621–0.984) | 0.818 * (0.649–0.988) | 0.738 * (0.544–0.932) | 0.781 * (0.600–0.961) | 0.818 * (0.649–0.988) |
Sensitivity | 0.824 | 0.882 | 0.824 | 0.824 | 0.882 | 0.824 | |
Specificity | 0.455 | 0.455 | 0.727 | 0.636 | 0.636 | 0.727 | |
MK | AUC (95% CI) | 0.604 (0.381–0.827) | 0.802 * (0.619–0.986) | 0.749 * (0.547–0.950) | 0.674 (0.454–0.893) | 0.658 (0.442–0.874) | 0.802 * (0.619–0.986) |
Sensitivity | 0.824 | 0.824 | 0.765 | 0.765 | 0.588 | 0.824 | |
Specificity | 0.455 | 0.818 | 0.636 | 0.627 | 0.818 | 0.818 | |
Ktrans | AUC (95% CI) | 0.556 (0.334–0.778) | 0.519 (0.290–0.747) | 0.572 (0.330–0.814) | 0.781 * (0.576–0.968) | 0.663 (0.444–0.883) | 0.781 * (0.576–0.968) |
Sensitivity | 0.353 | 0.588 | 0.765 | 0.941 | 0.765 | 0.941 | |
Specificity | 0.818 | 0.545 | 0.634 | 0.636 | 0.636 | 0.636 | |
Kep | AUC (95% CI) | 0.663 (0.456–0.871) | 0.588 (0.373–0.804) | 0.572 (0.356–0.788) | 0.652 (0.429–0.876) | 0.594 (0.377–0.810) | 0.652 (0.429–0.876) |
Sensitivity | 0.706 | 0.412 | 0.706 | 0.706 | 0.588 | 0.706 | |
Specificity | 0.636 | 0.727 | 0.455 | 0.818 | 0.636 | 0.818 | |
vp | AUC (95% CI) | 0.465 (0.224–0.706) | 0.743 * (0.551–0.935) | 0.647 (0.418–0.867) | 0.690 (0.467–0.912) | 0.652 (0.428–0.877) | 0.743 * (0.551–0.935) |
Sensitivity | 0.941 | 0.588 | 0.824 | 0.765 | 1.000 | 0.588 | |
Specificity | 0.273 | 0.909 | 0.636 | 0.636 | 0.364 | 0.909 | |
ve | AUC (95% CI) | 0.599 (0.380–0.818) | 0.556 (0.327–0.785) | 0.476 (0.238–0.713) | 0.722 * (0.510–0.933) | 0.556 (0.315–0.797) | 0.722 * (0.510–0.933) |
Sensitivity | 0.471 | 0.941 | 0.176 | 0.941 | 0.765 | 0.941 | |
Specificity | 0.818 | 0.273 | 0.545 | 0.545 | 0.545 | 0.545 | |
CBV | AUC (95% CI) | 0.460 (0.228–0.692) | 0.492 (0.261–0.723) | 0.594 (0.354–0.833) | 0.701 (0.487–0.914) | 0.647 (0.417–0.877) | 0.701 (0.487–0.914) |
Sensitivity | 0.471 | 0.588 | 0.706 | 0.706 | 0.588 | 0.706 | |
Specificity | 0.273 | 0.182 | 0.636 | 0.727 | 0.818 | 0.727 | |
TTP | AUC (95% CI) | 0.561 (0.328–0.795) | 0.583 (0.344–0.822) | 0.545 (0.312–0.779) | 0.492 (0.263–0.721) | 0.455 (0.225–0.685) | 0.583 (0.344–0.822) |
Sensitivity | 1.000 | 0.882 | 0.706 | 1.000 | 0.529 | 0.882 | |
Specificity | 0.273 | 0.455 | 0.545 | 0.182 | 0.182 | 0.455 | |
Peak | AUC (95% CI) | 0.620 (0.403–0.838) | 0.476 (0.241–0.711) | 0.513 (0.266–0.760) | 0.636 (0.401–0.871) | 0.636 (0.418–0.854) | 0.636 (0.401–0.871) |
Sensitivity | 0.412 | 0.294 | 0.824 | 0.882 | 0.529 | 0.882 | |
Specificity | 0.818 | 0.545 | 0.455 | 0.545 | 0.837 | 0.545 | |
AUC | AUC (95% CI) | 0.572 (0.353–0.792) | 0.471 (0.237–0.704) | 0.497 (0.239–0.756) | 0.701 (0.484–0.917) | 0.658 (0.438–0.877) | 0.701 (0.484–0.917) |
Sensitivity | 0.471 | 0.353 | 0.941 | 0.941 | 0.765 | 0.941 | |
Specificity | 0.818 | 0.364 | 0.636 | 0.545 | 0.636 | 0.545 | |
Wash in | AUC (95% CI) | 0.492 (0.247–0.737) | 0.663 (0.431–0.895) | 0.599 (0.354–0.844) | 0.519 (0.269–0.769) | 0.497 (0.262–0.733) | 0.663 (0.431–0.895) |
Sensitivity | 0.882 | 0.765 | 0.882 | 0.176 | 0.294 | 0.765 | |
Specificity | 0.364 | 0.536 | 0.545 | 0.545 | 0.455 | 0.536 | |
Wash out | AUC (95% CI) | 0.567 (0.314–0.819) | 0.642 (0.415–0.868) | 0.535 (0.296–0.773) | 0.540 (0.316–0.764) | 0.428 (0.189–0.667) | 0.642 (0.415–0.868) |
Sensitivity | 0.824 | 0.824 | 0.765 | 0.529 | 0.235 | 0.824 | |
Specificity | 0.545 | 0.636 | 0.545 | 0.636 | 0.455 | 0.636 | |
Combined ve and ADC | AUC (95% CI) | 0.840 * (0.645–1.000) | |||||
Sensitivity | 0.941 | ||||||
Specificity | 0.818 |
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Zerweck, L.; Klose, U.; Würtemberger, U.; Richter, V.; Nägele, T.; Gohla, G.; Grundmann-Hauser, K.; Estler, A.; Ruff, C.; Erb, G.; et al. Preoperative Adult-Type Diffuse Glioma Subtype Prediction with Dynamic Contrast-Enhanced MR Imaging and Diffusion Weighted Imaging in Tumor Cores and Peritumoral Tissue—A Standardized Multicenter Study. Diagnostics 2025, 15, 532. https://doi.org/10.3390/diagnostics15050532
Zerweck L, Klose U, Würtemberger U, Richter V, Nägele T, Gohla G, Grundmann-Hauser K, Estler A, Ruff C, Erb G, et al. Preoperative Adult-Type Diffuse Glioma Subtype Prediction with Dynamic Contrast-Enhanced MR Imaging and Diffusion Weighted Imaging in Tumor Cores and Peritumoral Tissue—A Standardized Multicenter Study. Diagnostics. 2025; 15(5):532. https://doi.org/10.3390/diagnostics15050532
Chicago/Turabian StyleZerweck, Leonie, Uwe Klose, Urs Würtemberger, Vivien Richter, Thomas Nägele, Georg Gohla, Kathrin Grundmann-Hauser, Arne Estler, Christer Ruff, Gunter Erb, and et al. 2025. "Preoperative Adult-Type Diffuse Glioma Subtype Prediction with Dynamic Contrast-Enhanced MR Imaging and Diffusion Weighted Imaging in Tumor Cores and Peritumoral Tissue—A Standardized Multicenter Study" Diagnostics 15, no. 5: 532. https://doi.org/10.3390/diagnostics15050532
APA StyleZerweck, L., Klose, U., Würtemberger, U., Richter, V., Nägele, T., Gohla, G., Grundmann-Hauser, K., Estler, A., Ruff, C., Erb, G., Ernemann, U., & Hauser, T.-K. (2025). Preoperative Adult-Type Diffuse Glioma Subtype Prediction with Dynamic Contrast-Enhanced MR Imaging and Diffusion Weighted Imaging in Tumor Cores and Peritumoral Tissue—A Standardized Multicenter Study. Diagnostics, 15(5), 532. https://doi.org/10.3390/diagnostics15050532