Literature DB >> 24327584

Investigation of the diffusion abnormality index as a new imaging biomarker for early assessment of brain tumor response to radiation therapy.

Reza Farjam1, Christina I Tsien, Felix Y Feng, Diana Gomez-Hassan, James A Hayman, Theodore S Lawrence, Yue Cao.   

Abstract

BACKGROUND: Diffusion MRI, although having the potential to be a biomarker for early assessment of tumor response to therapy, could be confounded by edema and necrosis in or near the brain tumors. This study aimed to develop and investigate the ability of the diffusion abnormality index (DAI) to be a new imaging biomarker for early assessment of brain metastasis response to radiation therapy (RT).
METHODS: Patients with either radiosensitive or radioresistant brain metastases that were treated by whole brain RT alone or combined with bortezomib as a radiation sensitizer had diffusion-weighted (DW) MRI pre-RT and 2 weeks (2W) after starting RT. A patient-specific diffusion abnormality probability function (DAProF) was created to account for abnormal low and high apparent diffusion coefficients differently, reflecting respective high cellularity and edema/necrosis. The DAI of a lesion was then calculated by the integral of DAProF-weighted tumor apparent diffusion coefficient histogram. The changes in DAI from pre-RT to 2W were evaluated for differentiating the responsive, stable, and progressive tumors and compared with the changes in gross tumor volume and conventional diffusion metrics during the same time interval.
RESULTS: In lesions treated with whole brain RT, the DAI performed the best among all metrics in predicting the posttreatment response of brain metastases to RT. In lesions treated with whole brain RT + bortezomib, although DAI was the best predictor, the performance of all metrics worsened compared with the first group.
CONCLUSIONS: The ability of DAI for early assessment of brain metastasis response to RT depends upon treatment regimes.

Entities:  

Keywords:  DW-MRI; cancer; diffusion abnormality index; imaging biomarker

Mesh:

Substances:

Year:  2013        PMID: 24327584      PMCID: PMC3870818          DOI: 10.1093/neuonc/not153

Source DB:  PubMed          Journal:  Neuro Oncol        ISSN: 1522-8517            Impact factor:   12.300


  29 in total

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Review 8.  The Use of Quantitative Imaging in Radiation Oncology: A Quantitative Imaging Network (QIN) Perspective.

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