JNM: Predictive role of PET for cancer treatment affirmed

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Volume rendering of staging 18F-FDG PET demonstrates difficulties posed in defining primary lesion dimensions on CT in presence of atelectasis.

Regional and local characterization of 18F-FDG PET tracer heterogeneity in tumors are more powerful than global measurements currently used in clinical practice, which means they could hold "the potential to revolutionize the predictive role of PET in cancer treatment,” according to research published in the March issue of the Journal of Nuclear Medicine.

18F-FDG PET is often used in clinical routine for diagnosis, staging and response to therapy assessment or prediction. The standardized uptake value (SUV) in the primary or regional area is the most common quantitative measurement derived from PET images used for those purposes.

Therefore, Florent Tixier, MD, from Inserm in Brest, France, and colleagues undertook the study to propose and evaluate new parameters obtained by textural analysis of baseline PET scans for the prediction of therapy response in esophageal cancer.

The researchers included 41 patients with newly diagnosed esophageal cancer treated with combined radiochemotherapy in this study, all of whom underwent pretreatment whole-body 18F-FDG PET. They were treated with radiotherapy and alkylatinlike agents (5-fluorouracil-cisplatin or 5-fluorouracil-carboplatin); and they classified patients as nonresponders (progressive or stable disease), partial responders or complete responders according to the Response Evaluation Criteria in Solid Tumors.

Different image-derived indices obtained from the pretreatment PET tumor images were considered, according to the study authors, which included usual indices such as maximum SUV, peak SUV and mean SUV and a total of 38 features (such as entropy, size and magnitude of local and global heterogeneous and homogeneous tumor regions) extracted from the five different textures.

Tixier and colleagues found that the relationships between pairs of voxels, characterizing local tumor metabolic nonuniformities, were able to significantly differentiate all three patient groups. They noted that regional measures of tumor characteristics, such as size of nonuniform metabolic regions and corresponding intensity nonuniformities within these regions, were also significant factors for prediction of response to therapy.

Receiver-operating-characteristic curve analysis showed that tumor textural analysis can provide nonresponder, partial-responder and complete-responder patient identification with higher sensitivity (76 to 92 percent) than any SUV measurement.

“Although only 18F-FDG images in esophageal cancer have been considered here, clearly the same indices applied in other PET radiotracer studies in the same or different tumor types may help create even stronger links between imaging and underlying tumor biology,” the authors concluded.

This study was supported by a grant from the Ligue Contre le Cancer, IFR148-ScInBioS and a fellowship from the French Ministry of Education and Research.