Differentiating tumor recurrence from treatment necrosis: a review of neuro-oncologic imaging strategies

Abstract

Differentiating treatment-induced necrosis from tumor recurrence is a central challenge in neuro-oncology. These 2 very different outcomes after brain tumor treatment often appear similarly on routine follow-up imaging studies. They may even manifest with similar clinical symptoms, further confounding an already difficult process for physicians attempting to characterize a new contrast-enhancing lesion appearing on a patient's follow-up imaging. Distinguishing treatment necrosis from tumor recurrence is crucial for diagnosis and treatment planning, and therefore, much effort has been put forth to develop noninvasive methods to differentiate between these disparate outcomes. In this article, we review the latest developments and key findings from research studies exploring the efficacy of structural and functional imaging modalities for differentiating treatment necrosis from tumor recurrence. We discuss the possibility of computational approaches to investigate the usefulness of fine-grained imaging characteristics that are difficult to observe through visual inspection of images. We also propose a flexible treatment-planning algorithm that incorporates advanced functional imaging techniques when indicated by the patient's routine follow-up images and clinical condition.

Figures

Fig. 1.

Ambiguities involved in differentiating between tumor recurrence and treatment necrosis based on routinely collected structural imaging sequences: T1 with Gadolinium contrast (T1-post Gad), T2-weighted images, and fluid attenuated inverse recovery (FLAIR). (A, B, C) T1-post Gad, T2-weighted, and FLAIR images of histopathologically confirmed case of glioblastoma recurrence, respectively. The patient underwent surgical resection of right temporal lobe tumor, followed by combined temozolomide/radiation therapy. (D, E, F) T1-post Gad, T2-weighted, and FLAIR images of pathologically proven case of treatment necrosis. The patient underwent surgical resection of right parietal oligodendroglioma, followed by combined chemotherapy (Avastin) and radiation therapy.

Fig. 2.

The usefulness of ADC histogram analysis in differentiating among pure tumor recurrence, pure treatment necrosis, and mixture of 2 etiology types. (A) ADC map with labeled region of interest (ROI) outlining the lesion extent determined using structural images. (B) ADC histogram with a 2-component normal mixture model fitted to the data (shown in red curve). The patient underwent surgical resection of right temporal lobe glioblastoma, followed by combined temozolomide/radiation therapy. High ADC values in the temporal lobe and low choline with use of MR spectroscopy suggested treatment necrosis; however, the pathological verification confirmed tumor recurrence.

Fig. 3.

MR spectroscopic imaging of patient shown in Fig. 1 A with glioblastoma in temporal lobe treated with surgical resection. (A) Metabolite spectra corresponding to voxels selected inside the lesion. (B) Metabolite spectra corresponding to voxels selected inside the peri-lesional brain tissue. The lack of elevated choline (Cho) peak inside the lesion suggested treatment necrosis; however, histopathological verification proved it to be tumor recurrence.

Fig. 4.

Flowchart illustrating the proposed flexible treatment algorithm that combines multiple functional imaging techniques with structural imaging for treatment of patients with brain tumor.