Brain Metastases and Treatment Open access Peer reviewed

Pathology-validated structural and physiologic habitat imaging for differentiating radiation necrosis from tumor recurrence in brain metastases

Ji Eun Park, Guowen Shao, Shivani Baisiwala, Nakyoung Kim and 13 more

Journal of Neuro-Oncology | Aug 28, 2026

Abstract

Abstract

PURPOSE: Differentiating tumor recurrence from radiation necrosis (RN) after stereotactic radiosurgery (SRS) remains a major diagnostic challenge in brain metastasis. We aimed to validate established MRI-based tumor habitat analysis for distinguishing tumor from RN in an independent cohort with histopathological ground truth. MATERIALS AND METHODS: This retrospective study included 104 patients (104 lesions) with pathologically confirmed recurrent metastatic tumors (n = 68) or RN (n = 36) who underwent structural and physiologic MRI. Tumor habitats were generated using an established unsupervised clustering model applied to normalized T1-weighted enhanced, T2-weighted, apparent diffusion coefficient, and cerebral blood volume maps. Structural habitats (enhancing tissue, solid low-enhancing, nonviable) and physiologic habitats (hypervascular, hypovascular cellular, nonviable) were quantified as absolute volumes and volume fractions. Logistic regression and receiver operating characteristics analysis evaluated the ability to differentiate tumor and RN. Composite habitat scores integrating structural and physiologic habitats were also developed. RESULTS: Recurrent metastatic tumors showed higher contrast-enhancing volume (P = .006), higher solid low-enhancing habitat volume (P = .029) and fraction (P = .04), higher hypervascular habitat volume (P = .02) and fraction (P = .03), and lower nonviable tissue habitat fractions on structural (P = .003) and physiologic MRI (P = .015), compared with RN. The combined structural and physiologic MRI habitat score showed the highest diagnostic performance (AUC, 0.80; 95% CI: 0.71-0.87; sensitivity, 89.7%; specificity, 58.3%). CONCLUSION: MRI-based tumor habitat analysis provides a pathology-validated approach to distinguish tumor recurrence from radiation necrosis in patients with prior radiation therapy.

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Authors

Researchers on this paper

Ji Eun Park

first | Johns Hopkins University | ORCID 0000-0002-4419-4682

Guowen Shao

middle | University of California, Los Angeles

Shivani Baisiwala

middle | University of California, Los Angeles

Nakyoung Kim

middle

Amelia Tan

middle | Stanford University

Francesco Sanvito

middle | University of California, Los Angeles | ORCID 0000-0003-3379-9958

Andrea Liang

middle | University of California, Los Angeles

Zexi Wang

middle

Gianluca Nocera

middle | IRCCS Ospedale San Raffaele | ORCID 0000-0002-8499-5257

Catalina Raymond

middle | ORCID 0000-0003-2757-439X

Vien Le

middle | ORCID 0000-0003-2933-332X

Ho Sung Kim

middle | Asan Medical Center

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Citation

BibTeX

@article{Park2026Pathology,
  title = {Pathology-validated structural and physiologic habitat imaging for differentiating radiation necrosis from tumor recurrence in brain metastases},
  author = {Ji Eun Park and Guowen Shao and Shivani Baisiwala and Nakyoung Kim and Amelia Tan and Francesco Sanvito and Andrea Liang and Zexi Wang and Gianluca Nocera and Catalina Raymond and Vien Le and Ho Sung Kim and Noriko Salamon and Whitney B. Pope and Won Kim and B. Ellingson and Jingwen Yao},
  journal = {Journal of Neuro-Oncology},
  year = {2026},
  doi = {10.1007/s11060-026-05761-7},
  url = {https://doi.org/10.1007/s11060-026-05761-7}
}

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