Details

Autor(en) / Beteiligte

• Bisdas, Sotirios
• Grewal, Jai
• Stieber, Volker
• Cavaliere, Robert
• Devoe, Craig
• Jensen, Randy
• Brownell, Elise
• Runk, Tina
• Dupont-Roettger, Diana

Titel

CTNI-45. RESPONSE EVALUATION OF AR-67 FROM A PHASE-2 RECURRENT GLIOBLASTOMA TRIAL BY ARTIFICIAL INTELLIGENCE ASSISTED TUMOR VOLUMETRIC ESTIMATION: COMPARISON WITH THE SUM OF THE PERPENDICULAR DIAMETERS PRODUCT

Ist Teil von

• Neuro-oncology (Charlottesville, Va.), 2021-11, Vol.23 (Supplement_6), p.vi70-vi70

Erscheinungsjahr

2021

Quelle

Oxford Journals 2020 Medicine

Beschreibungen/Notizen

• Abstract BACKGROUND Modified Radiographic Response Assessment in Neuro-Oncology (“mRANO”) criteria based on SPDP form the basis for assessing treatment response in Glioblastoma but are subject to sampling bias and difficulty in differentiating between pseudo- and true disease progression. Volumetric image analysis using AI may overcome these limitations of standard techniques and improve our ability to detect changes earlier and more accurately. METHODS Images from eight reGBM patients enrolled in a Phase-2 reGBM study of Vivacitas Oncology’s drug, AR-67, were re-assessed using IAG’s AI-assisted volumetric measurements. A median of five MRI time points from each patient were included. The mRANO response was determined by central reading and tumor volumetric measurement using IAG’s proprietary platform. Statistical significance was set at p< .0001. RESULTS Four patients showed responses, two patients showed stable disease, and two patients showed progressive disease. Tumor volume was correlated (r=0.97) with SPDP, but was driven by high coefficients in large lesions. Standard SPDP overestimated tumor size in larger tumors using the Bland-Altman analysis (mean difference: 829; 95% CI: 704 to -2362) leading to discrepancies in response rates. For example, the mean response rate based on IAG’s volumetric criteria was +22% (1.29) compared with +17% using SPDP (0.81). Eight out of 45 time-points also differed in the directionality of responses (e.g., increase vs. decrease) with SPDP underestimating the positive effects of AR-67 compared to AI analysis. CONCLUSIONS IAG’s AI-assisted tumor volumetric analysis is feasible for clinical trials and may be more sensitive for evaluating treatment-related response rates vs. SPDP methodology. This is particularly true for measuring large lesions, and may also allow for more accurately differentiating between pseudo- and true disease progression. The data included eight patients’ MRI images from a Phase-2 reGBM study, showing that five patients achieved the primary end-point of six months Progression-Free Survival, suggesting AR-67’s therapeutic potential.