Detection of Glioblastoma Subclinical Recurrence Using Serial Diffusion Tensor Imaging

Abstract

Glioblastoma is an aggressive brain tumor with a propensity for intracranial recurrence. We hypothesized that tumors can be visualized with diffusion tensor imaging (DTI) before they are detected on anatomical magnetic resonance (MR) images. We retrospectively analyzed serial MR images from 30 patients, including the DTI and T1-weighted images at recurrence, at 2 months and 4 months before recurrence, and at 1 month after radiation therapy. The diffusion maps and T1 images were deformably registered longitudinally. The recurrent tumor was manually segmented on the T1-weighted image and then applied to the diffusion maps at each time point to collect mean FA, diffusivities, and neurite density index (NDI) values, respectively. Group analysis of variance showed significant changes in FA (p = 0.01) and NDI (p = 0.0015) over time. Pairwise t tests also revealed that FA and NDI at 2 months before recurrence were 11.2% and 6.4% lower than those at 1 month after radiation therapy (p < 0.05), respectively. Changes in FA and NDI were observed 2 months before recurrence, suggesting that progressive microstructural changes and neurite density loss may be detectable before tumor detection in anatomical MR images. FA and NDI may serve as non-contrast MR-based biomarkers for detecting subclinical tumors.

Radiomics signature for temporal evolution and recurrence patterns of glioblastoma using multimodal magnetic resonance imaging

“…Radiomics‐based quantitative phenotyping using multivariate classification is prevalent in neuro‐oncology research; however, it has been limited to delineating tumor grade and genotype 35 . Recurrence predictions have been performed on a preoperative scan with a predefined region of interest around the tumor, not accounting for the time duration between the first scan and recurrence, as well as recurrence patterns that may occur at a distant location 14,15,17 . We employ a multivariate classification scheme and create two separate classifiers for distant and local recurrences based on the disparity in the underlying discriminative radiomic patterns.…”

“…To this end, subtle changes in apparent diffusion coefficient (ADC) and FLAIR quantifiers in the preoperative MRI scan, in the area of relapse, have been illustrated 14 . Recently, multimodal radiomics and diffusion multicompartment models have been employed to predict the recurrence infiltration patterns on preoperative multimodal MRI 14–17 . Nonetheless, these works usually only focus on the pre‐existing peritumoral edema as the area of probable recurrence, while relapse in distant/multifocal locations is not considered.…”

Is Diffusion Tensor Imaging-Guided Radiotherapy the New State-of-the-Art? A Review of the Current Literature and Technical Insights

“…However, glioma cells are found outside this core region due to the tumoral spread. As glioma cells migrate, it is thought to cause a loss of axonal integrity, leading to increased diffusivity and the T2 signal, and it is difficult to differentiate from vasogenic edema [34,35]. It has been suggested that diffusion imaging can improve the identification of non-enhancing tumour infiltration.…”

A Comparison of Single- and Multiparametric MRI Models for Differentiation of Recurrent Glioblastoma from Treatment-Related Change

“…Despite the introduction of tumor-treating fields and the vascular epithelial growth factor (VEGF) inhibitor bevacizumab [ 4 , 5 ] to the standard approach of radical resection followed by concomitant radiochemotherapy [ 6 , 7 ] and significant advancements regarding guided surgical resection including the application of 5-aminolevulinic acid and contrast-enhanced ultrasound [ 8 ], this glioma subtype still marks a therapeutical challenge [ 9 , 10 , 11 , 12 , 13 ] and has the poorest prognosis with a median survival of under two years [ 14 ]. Furthermore, its high recurrence rate [ 15 ] limiting the patient’s survival represents a radiologic problem: Innumerable studies tried to differentiate between recurrent tumors and treatment related changes [ 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 ]—a question with the highest clinical impact [ 25 , 26 ] and a neuroradiological challenge. Whereas initial diagnosis of GBM is often reliably feasible due to its typical radiological features, e.g., peripheral irregular ring enhancement, intralesional hemorrhage, and central necrosis [ 7 , 27 , 28 ], imaging of recurrent and/or progressive residual high-grade GBM is similar to therapy associated cerebral radiation necrosis (increasing contrast enhancement and progressive peritumoral edema at least six months up to several years after radiotherapy [ 29 ], often progresses without treatment) or pseudoprogression (increasing contrast enhancement and progressive peritumoral edema within three to six months following radiotherapy, often resolves spontaneously) after surgical resection and concomitant radiochemotherapy; both show strong contrast enhancement, increasing fluid-attenuated inversion recovery (FLAIR) hyperintensities adjacent to the enhancement, and present with punctiform intralesional hemorrhage and necrosis [ 29 , 30 ].…”