br Experimental design materials and methods

Experimental design, materials and methods We used the following steps to reconstruct data from Figs. 1B and 1C of Larkin et al. [2]. Fig. 1C of Larkin et al. [2] contains 3 lines representing the Kaplan-Meier estimates of survival probabilities for patients with negative programmed death 1 ligand BAY 87-2243 randomized to nivolumab monotherapy, ipilimumab monotherapy and combination therapy. Isolate these 3 lines using Adobe Illustrator [3], as described in Figs. 1–7. Use similar methods to isolate the 3 lines from Fig. 1B of Larkin et al. [2] that correspond to patients with positive programmed death 1 ligand expression. Save the isolated lines as separate jpeg files. Consider a jpeg file containing a single line – for example, the jpeg file corresponding to Fig. 7. Launch the DigitizeIt software package [4] in your computer and open this jpeg file. To digitize the line, select the desired minimum and maximum points on the horizontal (i.e., x) and vertical (i.e., y) axes, click the “Line” icon and left click the mouse on any part of the line. This will digitize the line and show the times (x-axis) and survival probability estimates (y-axis) in the output frame, which can be saved as a text file. The demo video in the DigitizeIt software page [4] gives a detailed description of this step. Apply this step to each jpeg file to obtain 6 text files. To obtain patient-level data, first pre-process the (x,y) values corresponding to each line obtained in Step 2 using Program 1. Next, use these parameters as the input for Program 2, which is an R function written by Guyot et al. [6], to obtain the reconstructed patient-level data. These steps are shown in Figs. 8–14.
Funding sources This work was supported by research grants R01 CA137420, R01 CA197402 and P30 CA008748 from the National Cancer Institute, USA, and grant UL1RR024996 from the Clinical and Translational Science Center at Weill Cornell Medical College, New York, USA. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
Acknowledgements
Data
Experimental design, materials and methods
Acknowledgements This work was supported by Grants-in-Aid for Scientific Research both from the Japanese Ministry of Education, Culture, Sports, Science, and Technology (MEXT) and from the Japanese Ministry of Health, Labor, and Welfare (MHLW). This work was also supported by Takeda Science Foundation.
Data The data are based on Magnetic Resonance Images (MRI) and histological analyses of human postmortem brains. Histological slices of each brain were co-registered to the respective whole brain MRI scan. Data were acquired in 11 postmortem (PM) brains. Using these data, 8 cytoarchitectonic regions of interest (cROIs) where identified. 4 regions were defined in the occipital lobe: human Occipital cortex 1 (hOc1) and hOc2 [1], hOc3 ventral (hOc3v) and hOc4v [11], Fusiform Gyrus 1 (FG1) and FG2 [2], and FG3 and FG4 [8]. Details about original area definitions can be found in the respective publications.
Experimental design, materials and methods Each of the MRIs of the postmortem brain anatomies was manually segmented to separate gray from white matter using ITK-SNAP (http://www.itksnap.org/pmwiki/pmwiki.php). The segmentations were then used to create a cortical surface reconstruction for each individual brain and each hemisphere, separately. Subsequently, each brain׳s anatomical T1-weighted image, cortical segmentation, and cytoarchitectonic areas were further analyzed in BrainVoyager QX 2.8 (Brain Innovation, Maastricht, The Netherlands) and FreeSurfer (http://surfer.nmr.mgh.harvard.edu). Cytoarchitectonic areas were projected from each brain׳s volume to their cortical surface reconstruction. We then used cortex-based alignment [4,7] to register each brain and the respective cROIs to a common brain template in which we generated a group probability map of each cROI. Details about atlas generation are described in Rosenke et al. [10].