Publication Details

AFRICAN RESEARCH NEXUS

SHINING A SPOTLIGHT ON AFRICAN RESEARCH

biochemistry, genetics and molecular biology

T2-weighted MRI signal predicts hormone and tumor responses to somatostatin analogs in acromegaly

Endocrine-Related Cancer, Volume 23, No. 11, Year 2016

GH-secreting pituitary adenomas can be hypo-, iso- or hyper-intense on T2-weighted MRI sequences. We conducted the current multicenter study in a large population of patients with acromegaly to analyze the relationship between T2-weighted signal intensity on diagnostic MRI and hormonal and tumoral responses to somatostatin analogs (SSA) as primary monotherapy. Acromegaly patients receiving primary SSA for at least 3 months were included in the study. Hormonal, clinical and general MRI assessments were performed and assessed centrally. We included 120 patients with acromegaly. At diagnosis, 84, 17 and 19 tumors were T2-hypo-, iso- and hyper-intense, respectively. SSA treatment duration, cumulative and mean monthly doses were similar in the three groups. Patients with T2-hypo-intense adenomas had median SSA-induced decreases in GH and IGF-1 of 88% and 59% respectively, which were significantly greater than the decreases observed in the T2-iso- and hyper-intense groups (P < 0.001). Tumor shrinkage on SSA was also significantly greater in the T2-hypo-intense group (38%) compared with the T2-iso- and hyper-intense groups (8% and 3%, respectively; P < 0.0001). The response to SSA correlated with the calculated T2 intensity: The lower the T2-weighted intensity, the greater the decrease in random GH (P < 0.0001, r = 0.22), IGF-1 (P < 0.0001, r = 0.14) and adenoma volume (P < 0.0001, r = 0.33). The T2-weighted signal intensity of GH-secreting adenomas at diagnosis correlates with hormone reduction and tumor shrinkage in response to primary SSA treatment in acromegaly. This study supports its use as a generally available predictive tool at diagnosis that could help to guide subsequent treatment choices in acromegaly.

Statistics
Citations: 77
Authors: 41
Affiliations: 24
Identifiers
Research Areas
Cancer
Study Design
Cross Sectional Study