Dataset Information

Tumor Habitat Analysis Using Longitudinal Physiological MRI to Predict Tumor Recurrence After Stereotactic Radiosurgery for Brain Metastasis.

ABSTRACT:

Objective

It is difficult to predict the treatment response of tissue after stereotactic radiosurgery (SRS) because radiation necrosis (RN) and tumor recurrence can coexist. Our study aimed to predict tumor recurrence, including the recurrence site, after SRS of brain metastasis by performing a longitudinal tumor habitat analysis.

Materials and methods

Two consecutive multiparametric MRI examinations were performed for 83 adults (mean age, 59.0 years; range, 27-82 years; 44 male and 39 female) with 103 SRS-treated brain metastases. Tumor habitats based on contrast-enhanced T1- and T2-weighted images (structural habitats) and those based on the apparent diffusion coefficient (ADC) and cerebral blood volume (CBV) images (physiological habitats) were defined using k-means voxel-wise clustering. The reference standard was based on the pathology or Response Assessment in Neuro-Oncologycriteria for brain metastases (RANO-BM). The association between parameters of single-time or longitudinal tumor habitat and the time to recurrence and the site of recurrence were evaluated using the Cox proportional hazards regression analysis and Dice similarity coefficient, respectively.

Results

The mean interval between the two MRI examinations was 99 days. The longitudinal analysis showed that an increase in the hypovascular cellular habitat (low ADC and low CBV) was associated with the risk of recurrence (hazard ratio [HR], 2.68; 95% confidence interval [CI], 1.46-4.91; P = 0.001). During the single-time analysis, a solid low-enhancing habitat (low T2 and low contrast-enhanced T1 signal) was associated with the risk of recurrence (HR, 1.54; 95% CI, 1.01-2.35; P = 0.045). A hypovascular cellular habitat was indicative of the future recurrence site (Dice similarity coefficient = 0.423).

Conclusion

After SRS of brain metastases, an increased hypovascular cellular habitat observed using a longitudinal MRI analysis was associated with the risk of recurrence (i.e., treatment resistance) and was indicative of recurrence site. A tumor habitat analysis may help guide future treatments for patients with brain metastases.

SUBMITTER: Lee DH

PROVIDER: S-EPMC9971843 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature

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Publications

Tumor Habitat Analysis Using Longitudinal Physiological MRI to Predict Tumor Recurrence After Stereotactic Radiosurgery for Brain Metastasis.

Lee Da Hyun DH Park Ji Eun JE Kim NakYoung N Park Seo Young SY Kim Young-Hoon YH Cho Young Hyun YH Kim Jeong Hoon JH Kim Ho Sung HS

Korean journal of radiology 20230206 3

<h4>Objective</h4>It is difficult to predict the treatment response of tissue after stereotactic radiosurgery (SRS) because radiation necrosis (RN) and tumor recurrence can coexist. Our study aimed to predict tumor recurrence, including the recurrence site, after SRS of brain metastasis by performing a longitudinal tumor habitat analysis.<h4>Materials and methods</h4>Two consecutive multiparametric MRI examinations were performed for 83 adults (mean age, 59.0 years; range, 27-82 years; 44 male a ...[more]

PMID: 36788768

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Project description:Background At present, the simple prognostic models based on clinical information for predicting the treatment outcomes of brain metastases (BMs) are subjective and delayed. Thus, we performed this systematic review of multiple studies to assess the potential of quantitative magnetic resonance imaging (MRI) biomarkers for the early prediction of treatment outcomes of brain metastases with stereotactic radiosurgery (SRS). Methods We systematically searched the PubMed, Embase, Cochrane, Web of Science, and Clinical Trials.gov databases for articles published between February 1, 1991, and April 11, 2022, with no language restrictions. We included studies involving patients with BMs receiving SRS; the included patients were required to have definite pathology of a primary tumor and complete imaging data (pre- and post-SRS). We excluded the articles that included patients who had undergone previous surgery and those that did not include regular follow-up or corresponding MRI scans. Results We identified 2,162 studies, of which 26 were included in our analysis, involving a total of 1,362 participants. All 26 studies explored the relevant MRI parameters to predict the prognosis of patients with BMs who received SRS. The outcomes were generalized according to the relationships between the anatomical/morphological, microstructural, vascular, and metabolic changes and SRS. Generally, with traditional MRI, there are several quantitative prognostic models based on preradiosurgical radiomics that predict the outcome of SRS treatment in local BM control. With the implementation of advanced MRI, the relative apparent diffusion coefficient (ADC), perfusion fraction (f), relative cerebral blood volume (rCBV), relative regional cerebral blood flow (rrCBF), interstitial fluid pressure (IFP), quadratic of time-dependent leakage (Ktrans2), extracellular extravascular volume (ve), choline/creatine (Cho/Cr), nuclear Overhauser effect (NOE) peak, and intraextracellular water exchange rate constant (kIE) were confirmed to be indicative of the therapeutic effect of SRS for BMs. Conclusions Quantitative MRI biomarkers extracted from traditional or advanced MRI at different time points, which can represent the anatomical/morphological, microstructural, vascular, and metabolic changes, respectively, have been proposed as promising markers for the early prediction of SRS response in those with BMs. There are some limitations in this review, including the risk of selection bias, the limited number of study objects, the incomparability of the total data, and the subjectivity of the review process.

Dataset Information

Tumor Habitat Analysis Using Longitudinal Physiological MRI to Predict Tumor Recurrence After Stereotactic Radiosurgery for Brain Metastasis.

Objective

Materials and methods

Results

Conclusion

Publications

Tumor Habitat Analysis Using Longitudinal Physiological MRI to Predict Tumor Recurrence After Stereotactic Radiosurgery for Brain Metastasis.

Similar Datasets

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