Everolimus-induced pulmonary toxicity: Findings on 18F-FDG PET/CT imaging

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The everolimus–exemestane combination is indicated in advanced breast cancer treatment and usually well tolerated. The objective of the study was to determine the frequency of everolimus lung side effects and investigate their imaging characteristics on positron emission tomography with 18F-fluoro-deoxy-glucose combined with computerized tomography (18F-FDG PET/CT).Our single-center retrospective descriptive study systematically included all patients with metastatic breast cancer treated by this combination (n = 29 representing 57 18F-FDG PET/CT). Number of segments involved was quantified. Maximum standardized uptake value (SUVmax), average standardized uptake value (SUVmean), metabolic target volume (MTV), and total lesion glycolysis (TLG) were measured. Severe pneumopathy was studied by subgroup analysis.Pleuroparenchymal anomalies rate detected on 18F-FDG PET/CT was 62%. Alveolar-interstitial lesions were mainly observed (89%) and affected 2.8 segments (0.5–11.5) with a median of 2 segments. S7 and S10 were the most involved segments with SUVmax 3.9 (1.3–8.8) and SUVmean 2.2 (0.7–4.9). Statistically significant difference (P = .02) was found with number of segment involved to characterize severe pneumopathy (average of 6.3 segments [2.5–11.5] vs 1.9 segments [0.5–8] for interstitial lung disease) but not with SUVmax, SUVmean, MTV, TLG (P = .14, 0.22, 0.22, and 0.17, respectively).The 18F-FDG PET/CT could highlight pulmonary everolimus side effects, with a typical imaging pattern: alveolar-interstitial opacities associated with moderate uptake, more or less extensive, mainly affecting the lower lobes. Rarely, a pseudotumoral aspect may be detected, corresponding to a pitfall. MTV or TLG showed a tendency to differentiate severe pneumopathy vs interstitial lung disease but no statistically significant differences was observed contrarily to the number of segments involved. Further studies are necessary to determine if the 18F-FDG PET/CT could early predict adverse effects of mTOR inhibitors.

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