Selective Cell Size MRI Differentiates Brain Tumors from Radiation Necrosis

Sean P. Devan, Xiaoyu Jiang, Guozhen Luo, Jingping Xie, James D. Quirk, John A. Engelbach, Hannah Harmsen, Eliot T. McKinley, Jing Cui, Zhongliang Zu, Albert Attia, Joel R. Garbow, John C. Gore, Colin D. McKnight, Austin N. Kirschner, Junzhong Xu

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

Brain metastasis is a common characteristic of late-stage lung cancers. High doses of targeted radiotherapy can control tumor growth in the brain but can also result in radiotherapy-induced necrosis. Current methods are limited for distinguishing whether new parenchymal lesions following radiotherapy are recurrent tumors or radiotherapy-induced necrosis, but the clinical management of these two classes of lesions differs significantly. Here, we developed, validated, and evaluated a new MRI technique termed selective size imaging using filters via diffusion times (SSIFT) to differentiate brain tumors from radiotherapy necrosis in the brain. This approach generates a signal filter that leverages diffusion time dependence to establish a cell size–weighted map. Computer simulations in silico, cultured cancer cells in vitro, and animals with brain tumors in vivo were used to comprehensively validate the specificity of SSIFT for detecting typical large cancer cells and the ability to differentiate brain tumors from radiotherapy necrosis. SSIFT was also implemented in patients with metastatic brain cancer and radiotherapy necrosis. SSIFT showed high correlation with mean cell sizes in the relevant range of less than 20 mm. The specificity of SSIFT for brain tumors and reduced contrast in other brain etiologies allowed SSIFT to differentiate brain tumors from peritumoral edema and radiotherapy necrosis. In conclusion, this new, cell size–based MRI method provides a unique contrast to differentiate brain tumors from other pathologies in the brain.

Original languageEnglish
Pages (from-to)3603-3613
Number of pages11
JournalCancer research
Volume82
Issue number19
DOIs
StatePublished - Oct 1 2022

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