Automatisierte Verfahren zur Volumetrie von Metastasen: Ermittlung der Tumorlast

[Oncological imaging for therapy response assessment]

This review illustrates different radiological methods for therapy response assessment in the field of oncological imaging. Unidimensional measurement of tumor size according to the response evaluation criteria in solid tumors (RECIST) is of utmost importance. The established RECIST definitions of changes in size are decisive for subdivision into the categories complete response (CR), partial response (PR), stable disease (SD) and progressive disease (PD), which are generally accepted as the concise characterization for therapy response. Problems with size-dependent response assessment occur particularly in targeted therapy and by phenomena, such as pseudoprogression. Several variants of functional imaging and their role in cancer imaging regarding practical requests are introduced.

Uncertainties in RECIST as a measure of volume for lung nodules and liver tumors

PURPOSE

The authors wish to determine the extent to which the Response Evaluation Criteria in Solid Tumors (RECIST) and the criteria of the World Health Organization (WHO) can predict tumor volumes and changes in volume using clinical data.

METHODS

The data presented are a reanalysis of data acquired in other studies, including the public database from the Lung Image Database Consortium (LIDC) and from a study of liver tumors.

RESULTS

The principal result is that a given RECIST diameter predicts volume to a factor of 16 or 10 for the two data sets, respectively, by examining 95% prediction bounds and that changes in volume are predicted only little better: to within a factor of 7 for the liver data. The WHO criteria reduce the prediction bounds by a factor of 1.3 in all cases. Also, the RECIST threshold of 10 mm to measure a nodule corresponds to a transition zone width of a factor of more than 2 in volume for the nodules in the LIDC database.

CONCLUSIONS

While the RECIST diameter is certainly correlated with the volume, and similarly for changes in these quantities, the use of the diameter introduces additional variation assuming volume is the quantity of interest. Exactly how much this reduces the statistical power of clinical drug trials is a key open question for future research.