Photo taken from Edward Cliff/LinkedIn
Feb 5, 2024, 13:51
Edward Cliff: Congrats to my co-registrar Shin Wai for leading this in-depth analysis of PET radiomics to predict lymphoma relapse histology
Edward Cliff, Fellow at Harvard Medical School and Brigham & Women’s Hospital, made the following post on LinkedIn:
“Congrats to my co-registrar Shin Wai for leading this in-depth analysis of PET radiomics to predict lymphoma relapse histology, just out in Blood Advances.
Most clinically-applicable findings:
- SUVMax ≥25 or ΔSUVMax ≥150% were highly specific for aggressive transformation of indolent lymphoma (96%/94% respectively).
- The optimal cut-off for SUVMax to diagnose transformed disease was ≥12, with a sensitivity of 71%, specificity of 61%, PPV of 50%, and NPV of 78%.
- For patients with suspected lymphoma relapse, total lesion glycolysis (TLG), which combines tumour volume and glycolytic activity to assess overall metabolic tumour load, was most accurate at distinguishing relapsed lymphoma from benign tissue. TLG ≥245 distinguished lymphoma with 63% sensitivity, 86% specificity, 97% PPV, 30% NPV, and odds ratio 12.1.Check out the full open access paper.”
Source: Edward Cliff/LinkedIn
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