SUVmax is currently the most common semi-quantitative method of response assessment on FDG PET. By defining the tumour volume of interest (VOI), a measure of total glycolytic volume (TGV) may be obtained. We aimed to comprehensively examine, in a phantom setting, the accuracy of TGV in reflecting actual lesion activity and to compare TGV with SUVmax for response assessment. The algorithms for VOI generation from which TGV was derived included fixed threshold techniques at 50% of maximum (MAX50), 70% of maximum (MAX70), an adaptive threshold of 50% of (maximum + background)/2 (BM50) and a semi-automated iterative region-growing algorithm, GRAB. Comparison with both actual lesion activity and response scenarios was performed. SUVmax correlated poorly with actual lesion activity (r = 0.651) and change in lesion activity (r = 0.605). In a response matrix scenario SUVmax performed poorly when all scenarios were considered, but performed well when only clinically likely scenarios were included. The TGV derived using MAX50 and MAX70 algorithms performed poorly in evaluation of lesion change. The TGV derived from BM50 and GRAB algorithms however performed extremely well in correlation with actual lesion activity (r = 0.993 and r = 0.982, respectively), change in lesion activity (r = 0.972 and r = 0.963, respectively) and in the response scenario matrix. TGV(GRAB) demonstrated narrow confidence bands when modelled with actual lesion activity. Measures of TGV generated by iterative algorithms such as GRAB show potential for increased sensitivity of metabolic response monitoring compared to SUVmax, which may have important implications for improved patient care.