Radiation injury vs. recurrent brain metastasis: combining textural feature radiomics analysis and standard parameters may increase F-FET PET accuracy without dynamic scans.

OBJECTIVES

We investigated the potential of textural feature analysis of O-(2-[F]fluoroethyl)-L-tyrosine (F-FET) PET to differentiate radiation injury from brain metastasis recurrence.

METHODS

Forty-seven patients with contrast-enhancing brain lesions (n = 54) on MRI after radiotherapy of brain metastases underwent dynamic F-FET PET. Tumour-to-brain ratios (TBRs) of F-FET uptake and 62 textural parameters were determined on summed images 20-40 min post-injection. Tracer uptake kinetics, i.e., time-to-peak (TTP) and patterns of time-activity curves (TAC) were evaluated on dynamic PET data from 0-50 min post-injection. Diagnostic accuracy of investigated parameters and combinations thereof to discriminate between brain metastasis recurrence and radiation injury was compared.

RESULTS

Diagnostic accuracy increased from 81 % for TBR alone to 85 % when combined with the textural parameter Coarseness or Short-zone emphasis. The accuracy of TBR alone was 83 % and increased to 85 % after combination with the textural parameters Coarseness, Short-zone emphasis, or Correlation. Analysis of TACs resulted in an accuracy of 70 % for kinetic pattern alone and increased to 83 % when combined with TBR.

CONCLUSIONS

Textural feature analysis in combination with TBRs may have the potential to increase diagnostic accuracy for discrimination between brain metastasis recurrence and radiation injury, without the need for dynamic F-FET PET scans.

KEY POINTS

• Textural feature analysis provides quantitative information about tumour heterogeneity • Textural features help improve discrimination between brain metastasis recurrence and radiation injury • Textural features might be helpful to further understand tumour heterogeneity • Analysis does not require a more time consuming dynamic PET acquisition.