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JRSBRT 2.1, p. 51-62

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Quantitative analysis of pre- and post-treatment PET-CT scans using deformable image registration methods
Liza J. Stapleford, Jerome C. Landry, Eduard Schriebmann, Anthony Waller, Lin Pan, Sungjin Kim, Zhengjia Chen, Ian Croscker and Timothy H. Fox

Background and Purpose: To investigate the utility of quantitative PET analysis for early prediction of local control following stereotactic body radiation therapy (SBRT).

Materials and Methods: An initial test cohort of fourteen cases and a validation cohort of twenty-three cases were analyzed. All patients had metastatic or recurrent cancer and underwent PET-CTs pre- and post- SBRT to a variety of sites. Local failure was defined as biopsy proven persistent/recurrent disease or progressive disease on radiologic imaging. Using deformable registration, radiation dose was transferred to the PET-CTs. Using the prescription isodose as the volume of interest (VOI), response was assessed by generating metabolic volume histograms (MVH). MVH curves examine metabolic heterogeneity in the VOI. Exploratory analyses of the test cohort evaluated the viability of multiple iso-SUV and iso-volumetric points selected from the MVH curves to serve as novel markers of response. Standard PET response markers (maximum/mean SUV and qualitative analysis) were also assessed.

Results: In the initial cohort, ten of fourteen patients achieved local control at last follow-up, a median of 225 days following post-SBRT PET. Three out of four local failures had an increase in max SUV, while all patients who achieved local control had a reduction in max SUV (p=0.01). Exploratory analyses using multiple iso-SUV and iso-volumetric points did not yield any factors associated with local control (p>0.05). In the validation cohort, lower post- treatment max SUV (p=.03) and reduction in max SUV (p<0.05) were significantly associated with local control.

Conclusion:
 Reduction in max SUV following SBRT is associated with local control.

Keywords: SBRT; SBRT; PET; Response assessment; Deformable image registration

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