The aim of the study was to address the need for quantifying the global cancer time evolution magnitude from a pair of time-consecutive positron emission tomography-computed tomography (PET-CT) scans. In particular, we focus on the computation of indicators using image-processing techniques that seek to model non-Hodgkin’s lymphoma (NHL) progression or response severity.
A total of 89 pairs of time-consecutive PET-CT scans from NHL patients were stored in a nuclear medicine station for subsequent analysis. These were classified by a consensus of nuclear medicine physicians into progressions, partial responses, mixed responses, complete responses, and relapses. The cases of each group were ordered by magnitude following visual analysis. Thereafter, a set of quantitative indicators designed to model the cancer evolution magnitude within each group were computed using semiautomatic and automatic image-processing techniques. Performance evaluation of the proposed indicators was measured by a correlation analysis with the expert-based visual analysis.
The set of proposed indicators achieved Pearson’s correlation results in each group with respect to the expert-based visual analysis: 80.2% in progressions, 77.1% in partial response, 68.3% in mixed response, 88.5% in complete response, and 100% in relapse. In the progression and mixed response groups, the proposed indicators outperformed the common indicators used in clinical practice [changes in metabolic tumor volume, mean, maximum, peak standardized uptake value (SUVmean, SUVmax, SUVpeak), and total lesion glycolysis] by more than 40%.
Computing global indicators of NHL response using PET-CT imaging techniques offers a strong correlation with the associated expert-based visual analysis, motivating the future incorporation of such quantitative and highly observer-independent indicators in oncological decision making or treatment response evaluation scenarios.
aDepartment of Radiology, Faculty of Medicine
bComputer Vision Center, Building O, Autonomous University of Barcelona
cDepartment of Nuclear Medicine, Hospital de Sant Pau
dDepartment of Applied Mathematics, Faculty of Mathematics, University of Barcelona, Barcelona, Spain
Correspondence to Frederic Sampedro, MSc, Faculty of Medicine, Autonomous University of Barcelona, 08193 Barcelona, Spain Tel: +34 699 805 231; e-mail: firstname.lastname@example.org
Received September 5, 2014
Received in revised form October 19, 2014
Accepted November 26, 2014