Effect of Different Enhancement Thresholds.

<p>A) Axial T1-weighted post-contrast image after volumetric analysis has been performed which shows in green the detected enhancing tumor volume using a 25% threshold level. B) Detected enhancing tumor volume using a 40% threshold level. C) While increasing the threshold decreases the calculated tumor volume, the volumes across different threshold levels are highly correlated.</p

Detection of Enhancement that is Obscured by Blood Products.

<p>A) Uncontrasted T1-weighted axial image showing resection cavity blood products (bright on T1). B) T1-weighted post-contrast axial image showing the difficulty in determining residual enhancing tumor. C) Our volumetric analysis is able to detect the obscured enhancing tumor tissue (shown in green). D) T1-weighted post-contrast axial image at 2.5 months later after the blood has resolved verifying the underlying enhancing tumor volume.</p

Traditional Non-Volumetric Measurements do not Adequately Describe Residual Enhancement in Surgical Resection Cavities.

<p>A) This schematic resection cavity has residual rim enhancement in gray. RECIST criteria measurement ‘A’ or ‘a’ or ‘b’ or Macdonald criteria measurement ‘A*B’ or ‘a*b’ would not adequately describe residual tumor volume and additional tumor growth around the rim or collapse of the resection cavity may be over- or under-interpreted. B) Differences in axial slice acquisition also impact measurements made by traditional criteria more than volumentric measurements. One scan could obtain axial slice ‘c’ with enhancing tumor measurement ‘x’ but a subsequent scan in the same patient could obtain axial slice ‘d’, causing an incorrect assessment of tumor response.</p

Detection of Enhancing Tumor Volume Despite Resection Cavity Collapse.

<p>A) T1-weighted post-contrast axial image showing a resection cavity with rim enhancement. RECIST measurement would be A and Macdonald measurement would be “A * B”. B) T1-weighted post-contrast axial image showing the same patient 3 months postoperatively who had collapse of his resection cavity. RECIST measurement would be “a” and Macdonald measurement would be “a * b”, both of which would be smaller than the measurements from the initial scan above, but this change would be describing only the resection cavity configuration and not the underlying tumor burden.</p

Automated Assessment of Enhancing Tumor Volume.

<p>A) T1-weighted post-contrast axial images are automatically fused with the pre-contrast sequences. B) The tumor region of interest (blue area) and nearby normal brain (purple area) are outlined roughly by hand. C) The enhancing nasal mucosa region is automatically detected with a built-in anatomic atlas (red area) and serves as a threshold for enhancement. D) Tissue that is present on the post-contrast images but not the pre-contrast that is above the enhancement threshold appears in yellow. This includes enhancing tissue such as vasculature, tumor, and superficial structures. Enhancing tumor volume is defined as the green area within the manually-defined blue tumor region of interest.</p

Effect of Inter-observer Differences in Definition of Tumor Volume.

<p>A) Axial T1-weighted post-contrast image showing a limited user-defined tumor region of interest. B) The same axial image now showing a large user-defined tumor region of interest that encompasses the meningeal enhancement. C) While including the meninges increases the enhancing volume, similar trends in changes of volume over time are seen.</p

The frequency of T_Regs and anti-PEPvIII humoral responses are inversely correlated.

<p>Patient sera from peripheral blood (vaccine 4) and leukapheresis samples were analyzed for levels of anti-PEPvIII antibodies and humoral responses were plotted against the frequency of T_Regs (Foxp3⁺ of CD4⁺). Assuming the assessments within individuals are independent, the Spearman correlation coefficient for both saline and daclizumab treated patients overall is (R = −0.93, p<0.0001).</p

Daclizumab remains bound to T_Regs a month after administration.

<p>(A) CD4⁺Foxp3⁺ T_Regs from day 35±2 leukapheresis samples (saline n = 3, daclizumab n = 3) were determined by flow cytometry and were additionally stained with anti-CD25 antibodies that bind the same CD25 eptiope as daclizumab (competing clone 2A3) or bind a separate epitope (non-competing clone MA251). The ratio of the frequency of CD4⁺CD25⁺Foxp3⁺ T_Regs as determined by MA251 or 2A3 binding was used as an indirect indicator of surface daclizumab expression. The percent change in the ratio was calculated from ratios determined from baseline (vaccine 1) samples, unpaired t-test *p = 0.0353. (B) CD4⁺CD25⁺Foxp3⁺ T_Regs were determined by FACS analysis of PBMC and examined for human antibody expression as a direct indicator of daclizumab binding to the surface of T_Regs. PBMCs from a saline and a daclizumab treated patient from vaccine 1 (Pre-Daclizumab) and leukapheresis at day 35±2 (Post-Daclizumab) time-points were assessed.</p

<i>In vivo</i> effects of daclizumab on the effector T-cell to regulatory T-cell ratio.

<p>(A–B) Effector T-cells (CD4⁺ or CD8⁺) to T_Reg ratios were derived by dividing the absolute number of effector T-cells by the absolute number of T_Regs at the indicated time-points; the absolute number of cells was determined by a combination of CBC and FACS analysis. The ratios of effector T-cells to T_Regs as compared to baseline were generated by dividing the individual patient CD4⁺∶T_Reg or CD8⁺∶T_Reg ratio at every time point by the ratio at vaccine 1 (V-1 = baseline). A two sample t-test averaged over the V-2, V-3 and LP time-points was utilized to examine the difference between the daclizumab and saline groups in the CD4⁺∶T_Reg (p = 0.0757) and CD8⁺∶T_Reg (p = 0.0153) ratios.</p

ZAP IT Patient Characteristics.

<p>> As of the lock date of the data, the indicated patient had 12 cycles of TMZ but continued with additional cycles of TMZ treatment.</p