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


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. 


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

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ISSN: 2532-179X