CURRENT MEASURES OF METABOLIC HETEROGENEITY WITHIN CERVICAL CANCER DO NOT PREDICT DISEASE OUTCOME

Current measures of metabolic heterogeneity within cervical cancer do not predict disease outcome

Current measures of metabolic heterogeneity within cervical cancer do not predict disease outcome

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Abstract Background A previous study evaluated the intra-tumoral heterogeneity observed in the uptake read more of F-18 fluorodeoxyglucose (FDG) in pre-treatment positron emission tomography (PET) scans of cancers of the uterine cervix as an indicator of disease outcome.This was done via a novel statistic which ostensibly measured the spatial variations in intra-tumoral metabolic activity.In this work, we argue that statistic is intrinsically non-spatial, and that the apparent delineation between unsuccessfully- and successfully-treated patient groups via that statistic is spurious.Methods We first offer a straightforward mathematical demonstration of our argument.Next, we recapitulate an assiduous re-analysis of the originally published data which was derived from FDG-PET imagery.

Finally, we present the results of a principal component analysis of FDG-PET images similar to those previously analyzed.Results We find that the previously published measure of intra-tumoral heterogeneity is intrinsically non-spatial, and actually is only a surrogate for tumor volume.We also find that an optimized linear combination of more canonical heterogeneity quantifiers does not predict disease outcome.Conclusions Current measures of intra-tumoral redken shades 9gi metabolic activity are not predictive of disease outcome as has been claimed previously.The implications of this finding are: clinical categorization of patients based upon these statistics is invalid; more sophisticated, and perhaps innately-geometric, quantifications of metabolic activity are required for predicting disease outcome.

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