Applicator output factors may be measured in a number of ways: either direct measurement at the water surface, measured at depth and corrected to the surface via a depth dose, or measured in air and converted to dose to water via a ratio of backscatter factors. There are reports of differences in measured output factors and those calculated using the ratio of published backscatter factors.14 It has been recommended that output factors are measured in water14 and then may be checked against published BJR supplement 25 data.11
The utilisation of ex vivo bone tissue culture for the study of skeletal growth and development was reported about 90 years ago using an embryonic chick model.36,37 A subsequent study by Fell and Robinson36 encountered some challenges in that the culture media then had to be supplemented with embryonic extract, plasma or serum. Culture media with such supplements were difficult to reproduce because the supplements were usually not produced in their purest form and contained variable concentrations of undesirable substances such as hormones. It is also difficult to differentiate between the cancellous or cortical bone growth requirements, as they differ in terms of their chemical matrices and as such respond to environmental changes independently.12,17,14
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Previous clinical studies have demonstrated a grade-dependent increase in [1-13C]lactate labelling in PCa21, breast59 and renal60 tumours, which is also supported by the reported association between a glycolytic phenotype and poor clinical outcomes in these tumour types36,61,62. Here, we observed differences in [1-13C]lactate signal in tumours of the same grade but a different prevalence of Gleason pattern 4 disease, which suggests that HP 13C-MRI can detect subtle but clinically important intra-grade metabolic heterogeneity, despite the limitations of its spatial resolution, with as little as 10% of the tumour containing GP4 disease. While the observed metabolic profile of GP3 and GP4 glands was similar, this ability to non-invasively differentiate tumours based on %GP4 will be particularly useful in the management of low-to-intermediate-risk disease on active surveillance, for which this parameter is key to determining treatment63. More specifically, HP 13C-MRI may improve baseline selection of patients suitable for active surveillance enrolment, where men harbouring tumours with high [1-13C]lactate labelling could be considered for immediate radical treatment or be offered more stringent follow-up to enable timely detection of any disease progression. Furthermore, it may improve subsequent assessment on surveillance by providing a quantitative metabolic measure of tumour progression to supplement the subjective MRI-derived Prostate Cancer Radiological Estimation of Change in Sequential Evaluation (PRECISE) scoring system used in clinical practice64. Finally, prospective validation of our findings in larger cohorts will enable an increase in the statistical power for evaluating metabolic differences between GP3 and low %GP4 lesions, compared with high %GP4 and GP5 disease. Significant metabolic differences between these subgroups would not only further justify the suitability of this technique for active surveillance of patients with low %GP4 disease, but also underpins the clinical utility of HP 13C-MRI for non-invasive metabolic risk-stratification of PCa. 2ff7e9595c
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