Biophysical model‐based parameters to classify tumor recurrence from radiation‐induced necrosis for brain metastases

Abstract

Purpose Stereotactic radiosurgery (SRS) is used for local control treatment of patients with intracranial metastases. As a result of SRS, some patients develop radiation‐induced necrosis. Radiographically, radiation‐induced necrosis can appear similar to tumor recurrence in magnetic resonance (MR) T1‐weighted contrast‐enhanced imaging, T2‐weighted MR imaging, and Fluid‐Attenuated Inversion Recovery (FLAIR) MR imaging. Radiographic ambiguities often necessitate invasive brain biopsies to determine lesion etiology or cause delayed subsequent therapy initiation. We use a biomechanically coupled tumor growth model to estimate patient‐specific model parameters and model‐derived measures to noninvasively classify etiology of enhancing lesions in this patient population. Methods In this initial, preliminary retrospective study, we evaluated five patients with tumor recurrence and five with radiation‐induced necrosis. Longitudinal patient‐specific MR imaging data were used in conjunction with the model to parameterize tumor cell proliferation rate and tumor cell diffusion coefficient, and Dice correlation coefficients were used to quantify degree of correlation between model‐estimated mechanical stress fields and edema visualized from MR imaging. Results Results found four statistically relevant parameters which can differentiate tumor recurrence and radiation‐induced necrosis. Conclusions This preliminary investigation suggests potential of this framework to noninvasively determine the etiology of enhancing lesions in patients who previously underwent SRS for intracranial metastases.

Clinical assessment of a biophysical model for distinguishing tumor progression from radiation necrosis

“…Specifically, we utilize a reaction-diffusion model of tumor growth that includes mechanical coupling to the surrounding tissue stiffness, creating a mechanically restricted cell diffusion growth model as described in previous work. 13 We relied on the assumption that the parameters of D 0 (cellular diffusion coefficient) and k (cell proliferation rate) are significantly different in tumor growth vs radiation necrosis. We fit these parameters to "observed tumor cellularity" and use them to calculate a mechanical solid stress distribution, which is compared the observed edema using a Dice similarity coefficient.…”

“…A previously developed mechanistic modeling approach was used to estimate the biophysical properties of lesion expansion based on conventional MR imaging. 13 Patients treated with SRS were followed with serial imaging at the discretion of the care team, most often at 1-3 month intervals, to evaluate for enhancement and radiographic evidence of recurrence/progression or necrosis. All patients in this database exhibited lesion growth on follow-up imaging and were histologically confirmed for tissue diagnosis; see Table I.…”

“…For mechanistic modeling analysis, a previously developed reaction-diffusion logistic growth model mechanically coupled to the surrounding tissue was used to extract biophysical model-based diffusion coefficient; 13,15,16 see Fig. 2.…”

“…While a brief description for the methodological implementation of this mechanistic modeling approach follows, a more complete description is provided as supplementary material and in our previous proof-of-concept work. 13 The coupled set of partial differential equations governing the model are shown in eqs. (1-3) which describe tumor cell proliferation, mechanoinhibitory tumor cell diffusion, and deformation mass effect due to mechanical solid stress fields imparted by an expanding lesion.…”

“…In recent work, we introduced a biophysical tumor growth model coupled to longitudinal lesion changes observed from MRI data following SRS for brain metastasis that showed preliminary promise as such a method in a limited ten patient cohort proof-ofconcept analysis. 13 As a follow-up to that preliminary study, in this work we seek to evaluate this mechanistic biophysical modeling method within a separate and larger scale cohort of patients with pathologically confirmed radiation necrosis or tumor progression. We additionally seek to compare the predicative accuracy of the mechanistic model-based method to a radiomics method for radiographic assessment of image morphometric and texture features.…”