Advanced imaging characterization of post-chemoradiation glioblastoma stratified by diffusion MRI phenotypes known to predict favorable anti-VEGF response

Francesco Sanvito^#^{1

2}, Irina Kryukov^#^{1

2}, Jingwen Yao^{1

2}, Ashley Teraishi^{1

2}, Catalina Raymond^{1

2}, John Gao², Cole Miller², Phioanh L Nghiemphu^{3

4}, Albert Lai^{3

4}, Linda M Liau⁵, Kunal Patel⁵, Richard G Everson⁵, Blaine S C Eldred^{3

4}, Robert M Prins⁵, David A Nathanson⁶, Noriko Salamon², Timothy F Cloughesy³, Benjamin M Ellingson^{7

8

9

10

11

12}

Affiliations

¹ UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California Los Angeles, Los Angeles, CA, USA.
² Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA.
³ Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA.
⁴ UCLA Neuro-Oncology Program, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA.
⁵ Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
⁶ Department of Pharmacology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA.
⁷ UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California Los Angeles, Los Angeles, CA, USA. bellingson@mednet.ucla.edu.
⁸ Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA. bellingson@mednet.ucla.edu.
⁹ Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA. bellingson@mednet.ucla.edu.
¹⁰ Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California Los Angeles, Los Angeles, CA, USA. bellingson@mednet.ucla.edu.
¹¹ Medical Scientist Training Program, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA. bellingson@mednet.ucla.edu.
¹² Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA. bellingson@mednet.ucla.edu.

^# Contributed equally.

PMID: 40227555
PMCID: PMC12170782
DOI: 10.1007/s11060-025-05019-8

Advanced imaging characterization of post-chemoradiation glioblastoma stratified by diffusion MRI phenotypes known to predict favorable anti-VEGF response

Francesco Sanvito et al. J Neurooncol. 2025 Jul.

. 2025 Jul;173(3):583-594.

doi: 10.1007/s11060-025-05019-8. Epub 2025 Apr 14.

Authors

Affiliations

¹ UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California Los Angeles, Los Angeles, CA, USA.
² Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA.
³ Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA.
⁴ UCLA Neuro-Oncology Program, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA.
⁵ Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
⁶ Department of Pharmacology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA.
⁷ UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California Los Angeles, Los Angeles, CA, USA. bellingson@mednet.ucla.edu.
⁸ Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA. bellingson@mednet.ucla.edu.
⁹ Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA. bellingson@mednet.ucla.edu.
¹⁰ Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California Los Angeles, Los Angeles, CA, USA. bellingson@mednet.ucla.edu.
¹¹ Medical Scientist Training Program, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA. bellingson@mednet.ucla.edu.
¹² Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA. bellingson@mednet.ucla.edu.

^# Contributed equally.

PMID: 40227555
PMCID: PMC12170782
DOI: 10.1007/s11060-025-05019-8

Abstract

Purpose: Recurrent glioblastomas showing a survival benefit from anti-VEGF agents are known to exhibit a distinct diffusion MRI phenotype. We aim to characterize advanced imaging features of this glioblastoma subset.

Methods: MRI scans from 87 patients with IDH-wildtype glioblastoma were analyzed. All patients had completed standard chemoradiation and were anti-VEGF-naïve. Contrast-enhancing tumor segmentations were used to extract: the lowest peak of the double gaussian distribution of apparent diffusion coefficient values (ADC_L) calculated from diffusion MRI, relative cerebral blood flow (rCBV) values from perfusion MRI, MTR_asym @ 3ppm from pH-weighted amine CEST MRI, quantitative T₂ and T₂* relaxation times (qT₂ and qT₂*), T₁w subtraction map values, and contrast-enhancing tumor volume. Lesions were categorized as high- or low-ADC_L using a cutoff of 1240 µm²/s, according to previous studies.

Results: High-ADC_L lesions showed significantly lower rCBV (1.02 vs. 1.28, p = 0.0057), higher MTR_asym @ 3ppm (2.36% vs. 2.10%, p = 0.0043), and higher qT₂ (114.8 ms vs. 100.9 ms, p = 0.0094), compared to low-ADC_L lesions. No group differences were seen in contrast-enhancing tumor volume, T₁w subtraction map values, and qT₂*, nor in clinical variables such as sex category, MGMT status, and EGFR status. Finally, no clear group-specific preferential locations were seen.

Conclusion: Post-chemoradiation glioblastomas with a diffusion MRI phenotype that is known to predict a favorable response to anti-VEGF (ADC_L ≥1240 µm²/s) have distinct biological features, with different perfusion and metabolic characteristics, and T₂ relaxation times.

Keywords: Anti-VEGF; Anti-angiogenic; Bevacizumab; Diffusion-weighted imaging; Glioblastoma; Perfusion-weighted imaging.

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Conflict of interest statement

Declarations. Ethics approval and consent to participate: The collection and analysis of clinical and imaging data for this research was approved by the institutional review board under the identification number IRB#19-002084. Competing interests: BME is on the advisory board and is a paid consultant for Medicenna, MedQIA, Servier Pharmaceuticals, Siemens, Janssen Pharmaceuticals, Imaging Endpoints, Kazia, Chimerix, Sumitomo Dainippon Pharma Oncology, ImmunoGenesis, Ellipses Pharma, Monteris, Neosoma, Alpheus Medical, Sagimet Biosciences, Sapience Therapeutics, Orbus Therapeutics, and the Global Coalition for Adap- tive Research (GCAR). TFC is cofounder, major stock holder, consultant and board member of Katmai Pharmaceuticals, holds stock for Erasca, member of the board and paid consultant for the 501c3 Global Coalition for Adaptive Research, holds stock in Chimerix and receives milestone payments and possible future royalties, member of the scientific advisory board for Break Through Cancer, member of the scientific advisory board for Cure Brain Cancer Foundation, has provided paid consulting services to Blue Rock, Vida Ventures, Lista Therapeutics, Stemline, Novartis, Roche, Sonalasense, Sagimet, Clinical Care Options, Ideology Health, Servier, Jubilant, Immvira, Gan & Lee, BrainStorm, Katmai, Sapience, Inovio, Vigeo Therapeutics, DNATrix, Tyme, SDP, Kintara, Bayer, Merck, Boehinger Ingelheim, VBL, Amgen, Kiyatec, Odonate Thera- peutics QED, Medefield, Pascal Biosciences, Bayer, Tocagen, Karyo- pharm, GW Pharma, Abbvie, VBI, Deciphera, VBL, Agios, Genocea, Celgene, Puma, Lilly, BMS, Cortice, Novocure, Novogen, Boston Biomedical, Sunovion, Insys, Pfizer, Notable labs, Medqia, Trizel, Medscape and has contracts with UCLA for the Brain Tumor Program with Roche, VBI, Merck, Novartis, BMS, AstraZeneca, Servier. The Regents of the University of California (T.F.C. employer) has licensed intellectual property co-invented by TFC to Katmai Pharmaceuticals.

Figures

**Fig. 1**
Flow-chart of patients included and excluded from the study

**Fig. 2**
Differences in multiparametric MRI metrics between diffusion MRI phenotypes. Lesions bearing a high-ADC_L MR diffusion phenotype (ADC_L ≥1240 µm²/s) exhibit lower rCBV (C), higher MTR_asym @ 3ppm (D), and higher qT₂ (E) compared to the low-ADC_L group. The differences in MTR_asym @ 3ppm may be partly due to underlying qT₂ differences, but multivariate analyses showed significant differences in MTR_asym @ 3ppm even after adjusting for qT₂. No significant group differences were seen in contrast-enhancing tumor volume (A), contrast-enhancement intensity (B), and qT₂* (F). a.u. = arbitrary units, cc = cubic centimeters, ms = milliseconds. **p < 0.01 surviving a Benjamini-Hochberg correction

**Fig. 3**
Representative cases. The figure shows post-chemoradiation multiparametric MRI images obtained from a 38-year-old female patient with a frontal glioblastoma WHO grade 4, IDH wild-type, MGMT unmethylated, EGFR non-amplified (case A), and from a 61-year-old female patient with a thalamic glioblastoma WHO grade 4, IDH wild-type, MGMT methylated, EGFR non-amplified (case B). In addition to higher ADC_L, case A also exhibited lower rCBV, higher MTR_asym @ 3ppm, and longer qT₂, compared to case B

**Fig. 4**
Multiparametric k-means clustering of contrast-enhancing tumor quantitative MRI metrics. A k-means clustering analysis was conducted using ADC_L (as a continuous variable), median rCBV, and median MTR_asym @ 3 ppm extracted from the contrast-enhancing tumor. k-means identified two distinct clusters (cluster 1 and cluster 2), which almost perfectly corresponded to the high-ADC_L and low-ADC_L groups, respectively, with the exception of only one high-ADC_L lesion assigned to cluster 2

See this image and copyright information in PMC

References

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Advanced imaging characterization of post-chemoradiation glioblastoma stratified by diffusion MRI phenotypes known to predict favorable anti-VEGF response

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Advanced imaging characterization of post-chemoradiation glioblastoma stratified by diffusion MRI phenotypes known to predict favorable anti-VEGF response

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Conflict of interest statement

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