Role of serial F-18 FDG PET/CT scans in assessing treatment response and predicting relapses in patients with symptomatic sarcoidosis.

Venkata Nagarjuna Maturu, Sampanna Jung Rayamajhi, Ritesh Agarwal, Ashutosh Nath Aggarwal, Dheeraj Gupta, Bhagwant Rai Mittal

Abstract


ackground: Monitoring disease activity in sarcoidosis remains a clinical challenge as there is no gold standard. Positron emission tomography (PET) imaging is a novel tool to assess the metabolic activity. There is limited data on the role of serial PET scans in monitoring the disease activity. Methods: This is a prospective study of 27 sarcoidosis patients treated with systemic corticosteroids. Patients underwent two serial PET/CT scans: one before initiating therapy and the follow up scan at end of therapy. The metabolic response on PET scan was classified as: (a) complete metabolic response (CMR); (b) partial metabolic response (PMR); (c) stable metabolic disease (SMD); and, (d) progressive metabolic disease (PMD). Patients with either CMR or PMR were classified as PET responders while those with SMD or PMD were considered as PET non-responders. All patients were followed at 3, 6 and 12 months after completion of therapy. Relapse rates and relapse-free survival was compared between the various groups. Results: There was significant decline in the median SUVmax of the mediastinal lymph nodes, peripheral lymph nodes and the lung parenchyma in the follow up PET scan. Eight patients achieved CMR, 6 patients achieved PMR while 13 patients were PET non-responders. There was no difference in the clinical remission rates between the responders and non-responders. However, the relapse rate was significantly higher in non-responders vs. responders (61.5% vs. 14.2%, p=0.018). None of the patients who achieved a CMR relapsed during the study period. Conclusions: Patients with metabolic response on PET scan have significantly fewer relapses as compared to those with no response on PET scan. 


Keywords


Sarcoidosis; response assessment; positron emission tomography; metabolic activity; predicting relapse.

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ISSN: 2532-179X