{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Vascular, Extracellular and Restricted Diffusion for Cytometry in Tumors (VERDICT)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Panagiotaki et al. (2014) proposed a multi-compartment model called VERDICT to characterize the composition of tumorous tissues. VERDICT models the diffusion in tumor cells, the extra-cellular space and surrounding bloodvessels as a restricted Sphere, an isotropic Gaussian Ball and a Stick compartment, respectively. VERDICT's design is as follows:\n", "\\begin{equation}\n", " E_{\\textrm{VERDICT}}= \\underbrace{f_{\\textrm{Tumor}}\\overbrace{E(D|\\lambda_{\\textrm{intra}})}^{\\textrm{Sphere}}}_{\\textrm{Tumor Cells}} + \\underbrace{f_{\\textrm{extra}}\\overbrace{E(\\cdot|\\lambda_{iso})}^{\\textrm{Ball}}}_{\\textrm{Hindered Extra-Cellular}}+\\underbrace{f_{blood}\\overbrace{E(\\lambda_\\parallel, \\boldsymbol{\\mu})}^{\\textrm{Stick}}}_{\\textrm{Vascular}}\n", "\\end{equation}\n", "where $D$ is the sphere's diameter. VERDICT uses the Gaussian Phase approximation to model the sphere *(Balinov et al. 1993)*, which accounts to changes in gradient pulse duration $\\delta$ and separation $\\Delta$. Furthermore, some particular parameter constraints are imposed:\n", "- The intra-cellular (intra-spherical) diffusivity is fixed to 0.9e-9 m^2/s\n", "- The extra-cellular Gaussian diffusivity is also fixed to 0.9e-9 m^2/s\n", "- The optimization range for $\\lambda_\\parallel$ of the Vascular Stick is set between (3.05-10)e-9 m^2/s\n", "\n", "We can define the VERDICT model in the following lines of code:" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Using Dmipy to set up the VERDICT model" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We first load the necessary modules to import the Sphere, Ball, and Stick models." ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/home/rutger/anaconda2/lib/python2.7/site-packages/h5py/__init__.py:34: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.\n", " from ._conv import register_converters as _register_converters\n" ] } ], "source": [ "from dmipy.signal_models import sphere_models, cylinder_models, gaussian_models" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The Sphere model must be initiated with VERDICT's setting for intra-spherical diffusivity, while the Ball and Stick model are regularly imported." ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "collapsed": true }, "outputs": [], "source": [ "sphere = sphere_models.S4SphereGaussianPhaseApproximation(diffusion_constant=0.9e-9)\n", "ball = gaussian_models.G1Ball()\n", "stick = cylinder_models.C1Stick()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We then assemble the three models into a multi-compartment model:" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "['G1Ball_1_lambda_iso',\n", " 'S4SphereGaussianPhaseApproximation_1_diameter',\n", " 'C1Stick_1_mu',\n", " 'C1Stick_1_lambda_par',\n", " 'partial_volume_0',\n", " 'partial_volume_1',\n", " 'partial_volume_2']" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from dmipy.core.modeling_framework import MultiCompartmentModel\n", "verdict_mod = MultiCompartmentModel(models=[sphere, ball, stick])\n", "verdict_mod.parameter_names" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Visualize the model:" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "image/png": 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HDh0SO06XVV1dTXPnziUA9OKLL7brPaOsc9uwYQPZ29uTi4sLrVu3jkdgO5ns7GyaOHGi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3nppZdQSvHzzz/z/vvv89VXX7F7926CgoLYsmULmZmZAAQHB7Nu3To6OzvZuXMnp0+fpqysDKPR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\nQgghhBBCCHEbDf8Hu8BhY/nQTtAAAAAASUVORK5CYII=\n", "text/plain": [ "" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from IPython.display import Image\n", "verdict_mod.visualize_model_setup(view=False, cleanup=False, with_parameters=True)\n", "Image('Model Setup.png')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We then fix the Ball's diffusivity, and adjust the Stick's optimization range for $\\lambda_\\parallel$ for the optimization." ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "collapsed": true }, "outputs": [], "source": [ "verdict_mod.set_fixed_parameter('G1Ball_1_lambda_iso', 0.9e-9)\n", "verdict_mod.set_parameter_optimization_bounds(\n", " 'C1Stick_1_lambda_par', [3.05e-9, 10e-9])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We are now ready to fit the data." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Fitting VERDICT to UCL Example Data" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "As illustration data we use the voxel of VERDICT data that is freely available at the UCL website at http://camino.cs.ucl.ac.uk/index.php?n=Tutorials.VERDICTcol. We prepared the script to easily import the acquisition scheme and example data from there:" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Acquisition scheme summary\n", "\n", "total number of measurements: 220\n", "number of b0 measurements: 49\n", "number of DWI shells: 41\n", "\n", "shell_index |# of DWIs |bvalue [s/mm^2] |gradient strength [mT/m] |delta [ms] |Delta[ms] |TE[ms]\n", "0 |19 |20 |0 |3.0 |10.0 |17.0 \n", "1 |3 |148 |160 |3.0 |10.0 |17.0 \n", "2 |3 |231 |200 |3.0 |10.0 |17.0 \n", "3 |3 |333 |240 |3.0 |10.0 |17.0 \n", "4 |3 |454 |280 |3.0 |10.0 |17.0 \n", "5 |3 |593 |320 |3.0 |10.0 |17.0 \n", "6 |3 |751 |360 |3.0 |10.0 |17.0 \n", "7 |3 |927 |400 |3.0 |10.0 |17.0 \n", "8 |12 |4 |0 |3.0 |20.0 |27.0 \n", "9 |3 |78 |80 |3.0 |20.0 |27.0 \n", "10 |3 |176 |120 |3.0 |20.0 |27.0 \n", "11 |3 |313 |160 |3.0 |20.0 |27.0 \n", "12 |3 |489 |200 |3.0 |20.0 |27.0 \n", "13 |3 |704 |240 |3.0 |20.0 |27.0 \n", "14 |3 |959 |280 |3.0 |20.0 |27.0 \n", "15 |3 |1253 |320 |3.0 |20.0 |27.0 \n", "16 |3 |1585 |360 |3.0 |20.0 |27.0 \n", "17 |9 |0 |0 |3.0 |30.0 |37.0 \n", "18 |3 |119 |80 |3.0 |30.0 |37.0 \n", "19 |3 |268 |120 |3.0 |30.0 |37.0 \n", "20 |3 |478 |160 |3.0 |30.0 |37.0 \n", "21 |3 |747 |200 |3.0 |30.0 |37.0 \n", "22 |3 |1075 |240 |3.0 |30.0 |37.0 \n", "23 |3 |1464 |280 |3.0 |30.0 |37.0 \n", "24 |3 |1912 |320 |3.0 |30.0 |37.0 \n", "25 |3 |2420 |360 |3.0 |30.0 |37.0 \n", "26 |3 |2988 |400 |3.0 |30.0 |37.0 \n", "27 |13 |9 |0 |3.0 |40.0 |47.0 \n", "28 |3 |160 |80 |3.0 |40.0 |47.0 \n", "29 |3 |361 |120 |3.0 |40.0 |47.0 \n", "30 |3 |643 |160 |3.0 |40.0 |47.0 \n", "31 |3 |1004 |200 |3.0 |40.0 |47.0 \n", "32 |3 |1446 |240 |3.0 |40.0 |47.0 \n", "33 |3 |1969 |280 |3.0 |40.0 |47.0 \n", "34 |3 |2572 |320 |3.0 |40.0 |47.0 \n", "35 |3 |3255 |360 |3.0 |40.0 |47.0 \n", "36 |3 |4018 |400 |3.0 |40.0 |47.0 \n", "37 |6 |0 |0 |3.5 |8.0 |15.0 \n", "38 |42 |958 |400 |3.5 |8.0 |15.0 \n", "39 |2 |0 |0 |10.0 |30.0 |44.0 \n", "40 |3 |305 |40 |10.0 |30.0 |44.0 \n", "41 |3 |2748 |120 |10.0 |30.0 |44.0 \n", "42 |3 |0 |0 |10.0 |40.0 |47.0 \n", "43 |3 |419 |40 |10.0 |40.0 |47.0 \n", "44 |3 |1679 |80 |10.0 |40.0 |47.0 \n", "45 |3 |3778 |120 |10.0 |40.0 |47.0 \n" ] } ], "source": [ "from dmipy.data import saved_data\n", "scheme, data = saved_data.panagiotaki_verdict()\n", "scheme.print_acquisition_info" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can see that the VERDICT acquisition scheme is very particular, having many shells with different diffusion times and often only 3 perpendicular measurements per shell, with the exception of one DTI shell with 42 measurements.\n", "\n", "To fit the data we use the MIX algorithm *(Farooq et al. 2016)*, which is efficient for finding the global minimum in models with many compartments. We set parallel processing to False since there is only one voxel." ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Setup MIX optimizer in 2.90870666504e-05 seconds\n", "Fitting of 1 voxels complete in 3.41024303436 seconds.\n", "Average of 3.41024303436 seconds per voxel.\n" ] } ], "source": [ "verdict_fit = verdict_mod.fit(scheme, data, solver='mix', use_parallel_processing=False)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Visualize results" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "To illustrate that Dmipy's VERDICT implementation is correct, we show that we can produce a very similar signal fitting plots as the one shown on the UCL website. On the left we show their original graph, and on the right we show Dmipy's predicted signal together with the measured signal attenuation." ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "image/png": 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pASM3xZXgx6Oz8WOvIvxNdScA3WPHhsHNm8vwY7lS4LdBfZG0eJsS/S0kY2bL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\nABPA8y2e58aLbmTsr2MZv2G81/V4JDAYbnoP2j4Fv86AmbdCgm+jBiW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Sk1LoMe5HPlmz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6TSLmG/UgpUKSUiIpJXBd9QnMAyYcSus9+qD9Kqoy6fOc3uVb/7YGciril6551UfPdd4tav5/DT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RlVsbh3/vpFd6qKEKIghSIqiICDZK6EXAhtLEo9hF9OjBo9+xK1YEREVp0ktAUKqoIE2lWiD0\n3hPSy/7+CIkhBpIJ2TOT5Lm99pVkZs+8jxgT3Wuvd33C8YTj9FvUj7WH19qylkdyOKDN09B/OpzZ\nB+Nuhp3L3J1KJIu/jxejujTkswERHI1JJPKDH5i6bp/TxaUbelxhU0J7qBglIhdwdus9XTsVkdzm\nSGWf81Qo759j277MLQE9uoiTj237TLa/NEdKRESKqtBba2AlphH7Q8G7oxrefAv+wSFsjJpTiMlE\nRDxPaPv21Jw5A++KFdk/ZCjHRo/GSi34VqeXcl3l65jacSoVAirw4HcPMnnH5CLXSXFZ6t0Og1dA\nSBWY3AtWv6M5UuJR2tWvyOJHWxNRoywjZ2/hX1M2cTY+Jd+v/83Xnp8ddlExSkT+Ia9roFldVMb5\n4pWIFHPZOqUwFF4XUy6dUtlnVXl88SZ7Qe2Ch60LOqU0R0pERIoi38pBBFxdjnM/HCTdiQso2fn4\n+dPk9o7s3PAzpw8XvKglIlIU+NWqRc2vp1GqV09OfjKWfQ8MJPX4cVvWCg8NZ1LHSbSu1prX1r3G\nS2teIiWtYD+ri6RydWDQd9CwOyx7CabfC0n53xJNxG5hof58+UALRnaoz7fbjtLhve9Zt/tUvl77\nwfKdNqcrXCpGiUiWzCKTuqNE5LLk6JQq9C6mS2zd59Gyd0nl0SkFKkiJiEjREnprDayky+uOanJH\nJF5eXmxcNL8Qk4mIeCaHvz9VXnmFyq++SsLmzUR370Hcz+tsWSvIJ4j32r7HkMZDmPXXLAZ+O5AT\nCSfy9dqbv76ZjUc32pLLZXyDoOcEuP3/4PeFMP4WOPGXu1OJZHE4DEPb1GH2Qzfg6+2g77g1vPPd\nn6SmpV/ydY+00zZ9IiIiIiIiIlKC+FQKIqBRec79eKjA3VFBpctwVeu2bFu5lITYmEJOKCLimUp3\n70bN6V/jFRLCvvvv58QnY7HSL30BuiAcxsEjTR/hzTZvsuPkDvot7Mf2k5ee03ck7ggnE08ycvXI\nQs/jcsbADQ/DvXMh/gSMbwe/L3J3KpELNK5WmqjhsyID9wAAIABJREFUrenetBrvL/uLvuPWcuB0\n/EXP79+yhgvTXT4Vo0SkQCzLKnAnlYiUIC6eI1UkZi7lMUcqe4eU5kiJiEhREnprdazkNGJXF7w7\nqnmnbqQmJ/Hbt7pAKCIlh3+9etScMYPQ9u05Pno0+x98kNTTp21Zq33N9nzZ4UsA7vvmPhbvXnzR\nczPnSx2NP8qMP2fYksflat0EQ1ZlbN83rR8s/z+wofgnUlDBft683eca3uvbhN+PxNLhvdVEbT7k\n7liFQsUoEblA1jwotP2eiBQSF86RwjJZ2wJ6fPEmR0Htwqc0R0pERIoen4p/d0elxRWsO6p8eA1q\nNWnOL0uiSE1OLuSEIiKeyys4iCpvv0Wl/7xI/Jq17O7Rk/hffrFlravKXcXUTlO5qtxVPP3907y/\n6X3SrYsXZNKtdMb+NtaWLG5ROhzuXwxN74bv34Cpd0KCPcU/kYLq2qQqi4a3pk6FYB6e8gsjZm4m\nPjnV3bEui4pRIpIrC5OvjqfsxSsRkYvKZY5UoRaNMgtS54teJuOLC4peBTlsl6Og9s+nc58jlVc2\ndVKJiIi7hN5SHSsljXOrDxT4PZpHdif+7Bl2/Liy8IKJiBQBxhjK9OtHjalTMV5e7L3nXk5NnJjV\noVSYygeUZ8LtE+hZtyfjt4zn0RWPci753D/yZBrUaFChZ3ArH3/o8iF0egd2rYBxbeHoNnenErlA\n9XKBzHjweh5uewXTN+4n8oMf2Hbw762Mv/usaH3PqhglIiIiIiIiIoXCp2IQAY0rcO6nQ6SdK1hn\nU/Wrr6FCjVpsjJprywVYERFPF3B1Q2rNmklwmzYcffU1Dg5/lLTY2EJfx8fLh/9c/x9GthjJ6gOr\nuXvR3eyP2Z/1fJBPUNbnn2/9nH0x+wo9g1sZA9cOhPsXQUoCfHorbJnp7lQiF/DxcvDUHVcyeVBL\n4pPSuHvCz1nP/bX+qBuTOU/FKBH5h6xuJyc6njQ3SkTyzbqwgym/3T75ed8Luq8gqwPrgs+dOVzp\nItv25TZHqtD+zERERGyQ0R2VXuDZUcYYIiK7c/LAPvb8urGQ04mIFA1epUpR7cMPCBsxgtgVK9jd\nsxeJ27cX+jrGGPpf1Z+xt43lROIJ+i7sy5pDa/5x3uG4w/Re0Jv5u+YXvxsFwlvA0FVQqTHMGghL\nnoe0or0dmhQ/N9QpzzePtqZd/bCsx+peW9GNiZynYpSIXJIzRSbNmRKRfMteNDo/RypzW73Cev/M\nglfWtoDGgmyP5edwuUts25dXUeqCP7scxTQVrkSkIIwx7Y0xfxhjdhpjns3l+QHGmOPGmF/PH8Vs\n/x4pKJ+wQAKuqUDcZXRHXXlDa4LLlGVD1JxCTiciUnQYYyh3/wBqfDkRKymJPX37cfrr6bYUg1pW\nbsnUTlMJCwxj2NJhTN4xOWMuLxDsE8yjzR6lQbkGPP/D8zy7+llikwu/U8utQirBfQugxRBY8yF8\n1Q3iTjj/PqvfhlGlCvZakTyUCfJl3D3Ns76+7YGGbkzjPBWjRCRXlmXlex5U5nn5nTMlIpIlW1Eq\ns2hUaIWTbP9/ln1OVVbh3PrnYS7yerdwslMKcv9zM4YLzhERyQ9jjBfwEdABaAD0M8Y0yOXUry3L\nanL++NSlIcWjhd5SHSs1ndjvCzY7ysvbh6YdurBv628c2xNdyOlERIqWwGbNqDVnNoEtWnDkP//h\n0IgRpMfFFfo64SHhTOo4iZuq3cRr617j5TUvAzDsmmEMbDSQT2//lEeaPsKSPUvovaA3vx3/rdAz\nuJW3L3R8E7p9AgfWw9g2cHCTc+/x+6KMj6d2F34+ES6c5Tbl571uTOI8FaNEJE8qMImI7bIXpSj8\nbeiMZc6/d7aiVI73NpkdWp7EiU6pzOzGZNsG8XwhKuscEZH8awHstCwr2rKsZGAa0NXNmaQI8akQ\nSGCTMOLWHCYttmDdUY1vbY+PfwAb1R0lIoJ32bKEjxtLhUeHExO1kN197iRp585CXyfIJ4jRbUcz\ntPFQFu9ZDMCY38Yw488ZeDm8GNJ4CF+0/wKA+765j/Gbx5OWnlboOdyqST94YAkYB3zWHn6Z5O5E\nIrna8HXh/wywk4pRIiIiIiIiklNVYH+2rw+cfyynnsaYzcaYmcaY8NzeyBgzxBizwRiz4fjx43Zk\nFQ8V0i48oztqVcG6o/yDgmnU9jZ+/+l7Yk9quyMREeNwUH7YMKp/NoG0M2fY3bsPZ+fPL/R1HMbB\nw00f5q02b2EwnEs5x9jfxmY93ySsCTM6z+D2mrfz/i/vM/i7wRyNO1roOdyqShMYshJqXA/z/gVR\nj0NqPm6uiDv/3zp/LLQznQgAdeKL1k2nKkaJyCVl36rvUj/ess7Lx7Z+IiIXlb0LqDDmSGXruDJW\nxg+o3LYEzOyKyngc92/Rl5tctu0zhqxZWBnnnO+O+vuUjI6o8+dodpSIOCG3nxY5fzouAGpaltUY\nWApMzO2NLMsaZ1lWhGVZERUqVCjkmOLJfCoEEtg0jLifC94d1axjF6x0i18WLyjkdCIiRVfQdddR\na/ZsAho25NAzIzj84n9IT0oq9HXuqHkHz7V8joqBFRl6zdALngvxDeH11q/zSqtX2HpiKz0X9GT5\nvuWFnsGtgsrBXbOg1aOw4TP4ohPEHL70a2IPZXzc9KX9+aTEq9eiorsjOEXFKBHJF2fmQWlbPxG5\nbBeZI1XgQkpmQer855lfZxa8sM4XbDyxCJVdjm37MmdBWZl/P5BRVDt/Ssbn1t8v0+woEcm/A0D2\nTqdqwKHsJ1iWddKyrMwrX+OB5ojkENquOlZaOrEr9+d9ci5KhVWi7nWt2Lx0MckJ8YWcTkSk6PKp\nGEb1Lz6n3ODBnJk+nT19+5G8t/Dnx/St35elvZfSu17vfzxnjKHrFV2ZHjmdqsFVeXTFo7yy9hUS\nUxMLPYfbeHnDbf+F3l/A0W0wrg3sXXPx8ys3yfiYFAuHfnFJRCm5bnugobsjOEXFKBHJU/aup/xS\nOUpELlsuc6QyZ0kV/D1Ntk6ovwte2YteRUaOTqnMuViQ8bnJnH9l/v5as6NExAnrgbrGmFrGGF+g\nL3DBPkDGmMrZvuwC7HBhPikivMsHENi0Iud+PkJaTMG6oyIiu5EUH8fWFd8VcjoRkaLNeHsT9uQT\nVPtkDCmHDrG7Zy9ilnzr8hw1S9VkUodJDGg4gK//+Jp+C/vx1+m/XJ7DVg27w+Bl4BsMEyNh3fjc\n7/Rrek/Gx7Rk+PRWWP02FLeZWiIFpGKUiIiIiIiIXMCyrFTgYWAJGUWm6ZZlbTPG/NcY0+X8acON\nMduMMb8Bw4EB7kkrni60XTikF7w7qvIVV1K1fgM2LppHepou6ImI5BRy883Unj0L39q1Ofjooxz5\n3/+wkgt2A0BB+Xj58GTEk4y9dSynE0/TN6ovU3+filWctmYIuwoGL4crboVFT8HchyAl4cJz9v6U\n8bHNM1A/Epb9N2N7v9OF37Umsm31QXdHcIqKUSLilLzmRmV2UWmrPhEpNNnnSJ2f7VSgDqacW/PB\n391DUHhbArpStm37MuddZe/2ypqBdX5mlJW1aZ+ISN4sy1pkWVY9y7LqWJb1f+cfe9GyrPnnPx9p\nWVZDy7KusSyrrWVZv7s3sXgq73IBBDaryLl1h0k7W7CZJs0juxNz/Bh/rfupkNOJiBQPPlWrUnPS\nV5S55x5Of/kVe+65h5RDh/J+YSG7oeoNzOoyi5aVW/K/n//H8BXDOZ142uU5bBNQGvpOhZtHwm9T\n4LM74My+v5//85uMjxsnZmzt1+0TOLIVxrSC36Zp33QpVOsX7XF3BKeoGCUiTlGRSUTcJsespwIV\njbIVa4z5u4Dzjy0BoWhs25dtm76sr3M5J+vvyVzkHBEREZuFtqsO6RBTwO6oOs1bUKZyFTZEzSle\nd9mLiBQi4+tLpeefo+ro0STv3MXu7j04t2qVy3OUCyjHR7d8xIhrR/DjwR/pNb8X6w6vc3kO2zgc\ncPOz0O9rOLUHxraBXSsynqvXIePjdQ9l/M9qk34w7Aeo2BDmDIWZ90P8KbdFl+Ll2o413R3BKSpG\niUi+ZO96yus6ZuZ5uuopIrbIUTQq8BwpK5cX/aPTyMM7pbLlNdb5qlMu52TNkMqqSomIiLiWd1l/\ngppXJG7dEVIL0B3lcHjRrGM3juz8k4N/bLchoYhI8RHa/g5qzZqJd+XK7B/6IMfeeRcrNdWlGYwx\n3N3gbqZ0mkKgTyCDvh3Ee5veIyU9xaU5bHVlexiyAoIrwqQe8ON7UOP6jOca9f77vDI14f5F0O4F\n2LEgo0sqeqU7Eou4lYpRIiIiIiIiImK7kLbhYEHsioJ1RzVs0w7/kFA2LJhTyMlERIof35o1qTlt\nKqV79+LkuHHsu/8BUo4dc3mO+mXr83Xk1/So24NPt3zKgG8GsD+2YL8HPFK5OjBoKTToCt+9CCtf\nz/08hxfc9BQM/A58A+HLrrDkeUgt2Pa1IgBr5uxydwSnqBhVBBhjsg5nXyNiB23VJyJul60jyOk5\nUjlmLF3qvAtmTHn4tn0W1vk/iwsePL9Nn2ZFiYiI+3mX9ScooiJx64+Qesb5i28+fv40ua0Duzb+\nzOnDRWtgt4iIOzj8/an88stUfu1VErZuZXePnsSt/dnlOQJ9Ahl1wyjebvM2u2N203tBb6Kio1ye\nwzZ+wdDrc7jtZTh35NLnVm0GQ7+HiIGw5kMY1xaObnNNTil2khNc2/F4uVSM8nDGmKzt0TK2Psv7\nKpiKUGKn7Fv1Xeo7Leu8fGzrJyJyWbJt23ex7fSyb7WX/WdTbo/n+t7nD48uSOUsRGXKLNh5am4R\nESlRQtqFAxC7Yl8eZ+auyR2ReHl5sXHhvMKMJSJSrJXu1o1a07/GKzSUfQ88wIlPPsFKT3d5jttr\n3s6szrO4ssyVjFw9kudWP0dcSpzLc9jCGGg1HFo+CD6B8Ofii5/rGwSR70D/6RB3LKMgteZjcMM/\nEynaitoYTRWjipnM4pWI3SxMvjuk1EklIrbL7HY6/2nOwpLlxHGx9/b4OVJ5dHmpMUpERDyBd+nz\n3VEbjpJ6OtHp1weVLsNVrduxbdUy4mPO2pBQRKR48qtbl1ozphPasSPHR7/H/qEPknr6tMtzVA6u\nzIQ7JvDQNQ+xcPdCei/ozdYTW12ewzbb50JKPKx+K+9z690Bw9ZAnXawZCRM6g4xh+zPKMVGvRYV\n3R3BKSpGFSMqRImrqOtJRDxWtqJU9qJR9uecq0T98/0zu7CyryEiIiL5F9K2OlDw2VERkd1ITU7i\nt+8WFWYsEZFizxEURJU336DSqFHEr13L7u49iP/lF5fn8HZ4M6zJMD6/43NS01O5Z9E9TNgygXSr\nGHQGtRkBoVUyPuZHcAXoNxUiR8P+dfDx9bBtrr0Zpdi47YGG7o7gFBWjRERERERERMRlvEv7EXRt\npYzuqFPOd0eVq1adWk2a8+uShaQmJ9uQUESk+DLGUKbvndSYNhXj7c3ee+7l5BdfuOUG92YVmzGj\n8wzaVW/H6E2jGfLdEI7FH3N5jkLVfAA8sSPjY34ZAxH3w9DVULY2zLgP5gyDxBi7Uoq4hYpRxYwx\n5oKZUZofJXa71BZ8f886A/VQiYhL5ehgKtSfQBfZts+jaFs+ERHxcCFtw8FcRndU5x7Enz3Djh9W\nFm4wEZESIqBhQ2rNnkXwzW049trrHBw+nLSYfxY/4tevJz0hwbYcpfxK8Vabt3jphpfYfHwzveb3\nYtX+Vbat59HKXwEDv4WbnoHN0+CTVrB3jbtTiQfbtvqguyM4RcWoYiTzwn/2Oxnyc1dDZgEr+yGS\nlwsLTSIiHih70QibZjxlK3p55BwpERERD+Vdyo+gFpWI21iw7qjwho2pULM2G6LmYGngu4hIgXiF\nhlLtgw8IGzGC2BUr2d2zFwnbtmU9n3bmDHvvuZc/WrTk9PTptuUwxtCjbg+mRU6jYlBFHl7+MK/+\n/CpJaUm2remxvHyg3fNw/2LAwBcdYdnLkJbi7mTigVZO+cPdEZyiYpRcUMTKWcwSyY+8rrtmzZhy\nSRoRkdzlOkeqsN7YQnOkREREnBTaNhwcELN8n9OvNcYQEdmdUwf3s/u3jTakExEpGYwxlLt/ADW+\n/BIrJYW9/fpzetrXWJZFenx8xkkpKRx9623bs9QuVZvJHSdzT4N7mPL7FPov7M+uM7tsX9cjVW8J\nD/4A1/SH1W/BhNvgxF/uTiWepohdxlcxSkRERERERERczivUj+AWlYnfdJTUk85vAXXl9a0JLluO\njVFzbEgnIlKyBDZrSq05swls0YIjo0Zx6OlnsLLP5XNRF6qvly/PXPsMH9/yMScSTtA3qi/T/5he\nMm+e9w+Fbh9B74lweg980hrWT4CS+GchxYKKUR4uo6Pk7+3zcv7g1ZZ64m6WZeW7xeBS86VERGyX\nc46UDVv25ZwjpW37RERELi3k5nBwOIhZ7vzsKC9vb5p16MK+rZs5tifahnQiIiWLd5kyhI8bS4VH\nhxOzaBH7Bg3Oes5KTOTMrFkuKwq1rtaaWV1m0axiM15e+zJPrHyCs0lnXbK2x2nYDYb9BNWvg4VP\nwJQ74dwxd6cScZqKUUXApbbPu9gvAG23J66W3636RETc6iJzpAp7277sRS9t2yciInJxXqG+BLes\nRPwvR0k94Xx3VKNb7sDHP4AN6o4SESkUxuGg/LBhVP9sAumJiRc8fvj5f7P/wQdJOeqaQkj5gPKM\nuXUMT0U8xcoDK+k5vyfrj6x3ydoeJ7QK3D0b2r8G0Svh4+vhj2/cnUrcJKxmyAUfiwrjIQULjwhR\nEuXWbSXirIzvI8jrX+W/z8v7XBGRQnWRuXXWhaeQjx9lBVvbMmAy3li/dsVGKnuKx4uIiLA2bNjg\n7hjiYdJikznyxnoCGpWnbJ8rnX79ionj+XVJFIM+mEBIufI2JBQRKZlSjh3j4ONPkLxnD+UfeRiS\nUzj2zjsYPz8qvfgCoR07umzXpm0ntzHi+xHsi9nH4MaDGXbNMLwd3i5Z2+Mc3Q6zB8PRrdD8frjj\n/8A3yN2ppAQzxmy0LCsir/PUGSUiIiIiIiIibuMV4ktQy8rE/3KMlAJ0RzXr0AUr3WLTN/NtSCci\nUnL5hIVRc/Ik6v34A2X79qXsvfdQa85s/GrW5NCTT3Hw8SdIPX3aJVkalmvI9MjpdL2iK+M2j2PA\n4gEcPHfQJWt7nIoNYPByuOER2PhFxiypgxvdnUokTypGichly9yCz6BbskXEc1m5HDmfN9i/bZ/m\nSImIiPxTSJtqGG8Hscv2Of3aUmEVqXddK7YsW0JyQrwN6UREJJNfrVrUmDyJCk88QeyyZURHdiZ2\n2TKXrB3oE8jLrV7mjZveYNeZXfSa34tvdpfQreq8/eD2V+DeeZCaCBNuh1VvQlqqu5OJXJSKUSJS\naCwM1iXKUVlFK12EFRFXy60SlcuR/cvCLkhlX0NzpERERC7kFeJL0PWVif/1GCnHnS8oRUR2Jyk+\nji3Lv7MhnYiIZGe8vSk/ZDC1Zs7EOyyMA/96mEMjniUtJsYl63eo1YEZnWdQp3Qdnvn+Gf79w7+J\nTymhNyPUbgPDfoSrusCKV+CLjnBqt7tTieRKxSgRKRTOF5p0FVZEPFCOopEtBaNsnVKZPzdVmBIR\nEYGQmwreHVXpinpUrd+QTd/MIz0tzYZ0IiKSk/+V9aj19TTKP/QQZ6OiiO7chXM//OiStauFVOOL\n9l8wpPEQ5u+aT5+oPmw/ud0la3ucgDLQ6zPoMR6O7cjYtu/XKRpYLB5HxSgRscGlu6MyC1ciIh7N\nwr6CUY5OLHVKiYiIgFewL0E3VCH+t+OkHCtYd1TM8WP8+bNrLoSKiAgYX18qDH+EmtOm4QgOZv+g\nQRweNYr0uDjb1/Z2ePNI00eYcMcEElMTuWvRXUzcNpF0K932tT2OMdC4T0aXVOXGMHcYzLgP4k+5\nO5lIFhWjRERERERERMQjhNxUDePjIKYA3VF1mregTOUqbIyag6W7wUVEXCqg0dXUmj2Lsg88wJmv\npxPdrTvx69e7ZO1rK13LrC6zaFOtDW9teIthS4dxIuGES9b2OKWrw30L4NZR8PsiGHMD7Fru7lQi\ngIpRIlKInO96UhuAiHg4O+dI8fcbW8bK6o5Sh5SIiJRkXkE+BN9QhYTNx0k56txd9cbhoHmnbhzZ\n9RcHf99mU0IREbkYh58fFZ95mhqTvgJg7733cfS110lPTLR97VJ+pXj35nd54boX2HR0Ez3n92T1\ngdW2r+uRHF5w4+MwaCn4hcBX3WHxSEix/5+DyKWoGCUiNrn01VRt1SciRUYuc6Ts2LYvc45U9jVE\nRERKouDW1TA+XgXqjmpwUzv8Q0LZEDXXhmQiIpIfgc2bU3vuHMr068upL75gd4+eJGzebPu6xhj6\nXNmHaZHTKBdQjoeWPcTr614nOS3Z9rU9UpUmMGQVtBgCaz+GcTfDkS3uTiUlmIpRIlLoVGgSkWLL\nzk6pHEUvzZESEZGSKqs7assJp7ujfPz8aXJ7R3Zt/JlThw7alFBERPLiCAqi0osvEj7hU9Lj49nT\nrz/HRo/GSra/MFSndB2mdppK//r9mbRjEnctuovos9G2r+uRfAOh45tw10yIPwnj28FPH0B6CZyr\nJW6nYpSIiIiIiIiIeJTg1lUxvl7ELHW+O6rJ7Z3w8vZm0yJ1R4mIuFtwq1bUXjCfUl26cPKTsezu\ncyeJv/9u+7p+Xn6MbDmSD9t9yNG4o/SN6susP2eV3JmCdW+Dh9bAFbfBt/+GL7vA2QPuTiUljIpR\nImIbQ36mQuXvLBERj3GRbfsKe43Mbfu0ZZ+IiJREF3RHHXGuOyqodBkatG7LtpXLiI85a1NCERHJ\nL6+QEKq8+j+qffwRqSdOsLt3H058MhYrNdX2tduEt2Fml5k0rtCYUWtG8eSqJzmbVEJ/NwSVh76T\nocsHcHATjLkBts5ydyopQVSMEhFbWJaV5xXUzO38dJFVRIosC/vmPGUreKkoJSIiJVFI66oYPy9i\nlu51+rXNO3UnNSWZ375bZEMyEREpiJB27ai9YD4ht97C8dGj2dP/LpKi7d8+LywwjHG3jeOxZo+x\nYt8Kei/ozaajm2xf1yMZA83uhQdXQ7m6MPMBmD0EEktogU5cSsUoEbFd/q6d6gqriBRRuRSN7H5/\nFaVERKQkcAT6ENyqCglbT5J86JxTry1XLZxaTSP4dclCUl0wn0RERPLHu0wZqr37LlXfeZuUvXvZ\n3b0HpyZOxLJ5hpHDOBjYaCBfdvgSb4c39y+5nzG/jiE13f7uLI9Urg48sATaPAtbZsKYVrDnR3en\nkmJOxSgRsY1lWX93SOVxji6sikiRl8vWfa7olDIF/EtERKQoCLmxKsbfi5hlzs+OiojsTvzZM2xf\nvcKGZCIicjlCO3akdtQCgq6/nqOvvsa++waQfMD+GUaNKjRiRucZdKrViY9/+5iBSwZy+Nxh29f1\nSF7e0HYkPLAYHN7wRSdYOgpSdROH2EPFKBERERERERHxSBndUVVJ3OZ8d1R4w8aE1azDxoVzbb/j\nXkREnOddoQLVxnxM5f/9j8QdO4ju0pXTX0/PuLHZRkE+Qfyv9f94tfWr/HH6D3ou6Mm3e761dU2P\nFt4iY9u+pnfDD+/Cp7fA8T/cnUqKIRWjRERERApTtu4lu7ftwzJgLDAWlpOHiIhIUZHVHbXUue4o\nYwwRkd04dXA/u3/baFM6ERG5HMYYSvfoTu358wi4pjFH/vMf9g8eQsqRI7avHVk7khmRM6gZWpMn\nVz3JqJ9GEZ8Sb/u6HskvBLp+CHdOgrMHYOxNsG482FwYlJJFxSgRcZFLX43N2KpP20aJSDGRrRpl\n57Z9lrH+LnrlWPeiB9k+ioiIFAGOAG9CbqxK4vaTJB90rjuq3vWtCS5Xng0L5tiUTkRECoNPlSpU\nnzCBii++QPzGjUR37sLZefNs75IKDw1nYoeJDGo0iNl/zabvwr78fup3W9f0aFd1hofWQI1WsOgp\nmNwbYo+6O5UUEypGiYjtNBNKREo0mzuljGUwlrmg6HXRczUrSkREiqjgG6ti/L2JWbrXqdd5eXvT\nrH1n9m/bzNHdu2xKJyIihcE4HJTt35/ac+fgV7cuh0Y8y8Hhw0k9edLWdX0cPjza7FHG3z6ec8nn\n6L+wP19t/8r2QpjHCqkEd8+CDm/CntUw5nr4faG7U0kxoGKUiIiIiIiIiHg0h783Ia2rkrjjFMkH\nYp16beNb2+MbEMDGKHVHiYgUBb41alDjqy8Je/ppzq36nujIzsQssX+mU8vKLZnVZRatqrTijfVv\n8NCyhziZYG8hzGMZAy2HwJBVEFoFpvWH+cMhybkOZZHsVIwSERfKzx35Jp/niYgUIRfZtq8w3jdz\nBlRmd1Ru72/O/2UZS1v0iYhIkRXcqgqOQG+nZ0f5BQbRqN3t/LFmNTEnjtuUTkRECpPx8qLcwAeo\nNWsmPlWqcPDRRzn41NOknTlj67pl/Mvwfrv3ea7lc6w7vI6e83vy08GfbF3To4XVh0HLodVjsOlL\nGNsaDmxwdyopolSMEhGXyG2rPpPj4Pw5xvzzuYsdIiJFjsVFi0YFfb/MolT2glf2988sWKkQJSIi\nRZnD35vg1lVJ/P0Uyfud645q1qErlmXxy+IFNqUTERE7+NWtS81pUyn/yMPELF5MdOcunFu1ytY1\njTH0q9+PqZFTKeNfhqFLh/LW+rdISUuxdV2P5e0Lt70EA6IgLQUm3A4rX4e0VHcnkyJGxSgRcakL\nikhZlSeTy238uTx3qfNFRIqSXIpGhSFrJlTO90cFfBERKR6Cb8jsjnJudlRohTDqtWzF5qWLSYqP\ntymdiIjYwfj4UOFf/6Lm19PwKl2K/UMf5PALL5B2zt4t4+qVqcfUTlO588o7mbh9Inctuos9Z/fY\nuqZHq3kjPPgDXN0TVv4PPm8Pp6LdnUqKEBWp/9BTAAAgAElEQVSjRERERERERKRIcPh5E3xTNRL/\nOE3SvhinXhvRuQfJCfFsXWH/3BERESl8AQ0bUnPWLMoNHsyZWbPZ3aUrcWt/tnVNf29//n3dvxnd\ndjSH4g7RJ6oPc3fOxbJK6LYTAaWh53joOQGO/wmftIZNX0FJ/fMQp6gYJSIuY1nWBR1N2X9xW5Z1\nwZHbY9mfy/l6EZEiKZc5UgXukjq/VZ/J1gNlLJN9GVBTqYiIFAPB11fBEeT87KhKdepS7aqr2bho\nHulpaTalExEROzl8fQl78glqTJ6E8fFh34ABHPm//5GekGDrurdUv4WZnWdydfmreeHHFxjx/Qhi\nk/+5ZWxsciwTtkywNYtHaNQLhv0IVZrC/Idh+j0Qd9LdqcTDqRglIm6R81pofq+N6hqqiBRL2bbU\nu6xt+zJnR2V+aXK8cWEVvkRERNzI4edFyE3VSPrzNEl7neuOah7ZndgTx/lz7Q82pRMREVcIbNqU\nWnPnUOaeezj91Vfs7tad+F9+sXXNSkGVGH/beIY3Hc63e7+l94Le/Hrs1wvOGfH9CEZvGk30mRKw\nfV3pcLh3Ptz2MvyxGMbcADuXujuVeDAVo0TEpbK6m7J1R2V+bXKcZ3JcJTUAxvyjQ0pEpFi4SMGo\nIMz5vy62TqEUvkRERNwo6PoqOIJ8nJ4dVafZtZSpXJUNUSV4iyURkWLCERBApeefo/oXn2OlpLD3\nrrs59vbbpCcn27aml8OLwY0HM7HDRAAGLB7A2N/Gkpae0XEbfTajCDVv1zzbMngUhwNaDYfByzO2\n8JvUE74ZASn2dqpJ0aRilIh4hOwFqos6X4gSESn2rAuLRU4VjM53R2V1RV3kHHVKiYhIUebw9SKk\nTTWS/jpD0p6z+X6dcTho3qkbR6P/4uCObTYmFBERVwm67jpqzZ9H6Z49ODn+U/b07EXCNnt/xl9T\n4RpmdJ7B7TVv58NfP2TQt4M4EneEY/HHAJi8YzJJaUm2ZvAolRvDkJXQchj8/AmMuxkOb87fa/eu\ngV0rbAwnnkLFKBEREREREREpcoKuq4wj2Mfp2VEN2rQjICSUDQvn2JRMRERczSs4mMovv0z42E9I\nO3OGPXf25fhHH2GlpNi2ZohvCK+3fp1XWr3CtpPb6Dm/J2X8ygCQlJZEr/m9WH9kvW3rexyfAOjw\nGtw9GxLOwPh28ON7kJ7HnMbP28NX3VyTUdxKxSgRcYvctuGDjK34TLZzcj4mIlJiZOtccrpDKvNF\n+TxX2/aJiEhRlNUdtfMMSbvz3x3l4+vHNbd3YteGnzl16ICNCUVExNWC27Sh9oL5hLZvz4kPPmRP\n334k7dxp23rGGLpe0ZUZnWdQLaQaxxIyOqP8vfxJSU/hgSUP8NKal4hNjrUtg8e54hZ4aA1c2R6+\nexG+7Apn9rs7lXgAFaNExGNkbdWXbX5U5pwobdEnIiVWXkUp4+RxiTUy10Hb9omISBER1PJ8d9R3\nzs2OanpHJ7x8fNi4cK5NyURExF28Spem6ltvUnX0aFIOHWJ3j56cnPAZVloeHTqXoUZoDSZ1mISP\nwwcAb+PN7C6zua/Bfcz+azZd53Zl2b5ltq3vcQLLQp+voOtHcOgXGNMKtsy89Gs2fuGSaOI+KkaJ\niJtdeHXUsqwL50edL0KpECUiJV4uRancnr/kURjriIiIeBCHrxchN4eTFH2WpOgz+X5dYKnSNLip\nHdtXLSc+Jv9dVSIiUnSEtr+D2gvmE3RTa469+SZ777mX5L3O3bzgDB8vH0a2HEnFwIo8ce0TBPoE\n8tS1TzGl4xTK+JfhsRWP8cTKJzgef9y2DB7FGGh6Nzy4GipcCbMGwqxBGVv45WbV667NJy6nYpSI\niIiIiIiIFFnBLSvhCPHl7HfOzY5q3qkbqSnJ/PbtIpuSiYiIu3mXL0+1Dz6gyuuvkfTXX0R3686p\nyZOx0tNtWa93vd4s7b2U3vV6Zz3WsHxDpkVO49Fmj7Jq/yq6zuvK7L9ml5wbr8vWhvu/gbbPw9bZ\nGV1Su1f/87w2I1yfTVxKxSgRcZuMuVEXv+teN+OLiOQiW+eSMTbO1ctl2z4RERFPZHy8CLm5Gsm7\nz5K4K//dUeWqhlO72bX8siSKlOQkGxOKiIg7GWMo1bUrtRfMJ7B5c46+/Ar7Bg4k5dAhl2Xwcfgw\nqNEgZnWZRb0y9fjPT/9h0LeD2BtjX6eWR/HyhjbPwMDvwNsXJnbOmCeVmgQV6oOXj7sTiguoGCUi\nHuLCq5yZW/WVmLtEREScZV24A59txaIcRSkVpkRExBMFt6iMI9SXmO/2OvX/EM07dSch5iw7Vq+w\nMZ2IiHgCn0qVCB8/jkovvUTCb5uJ7tKVM7Nc26FUs1RNPrvjM168/kW2n9xOz/k9mbBlAinpKS7L\n4FbVmsPQ1dD8PvjxPfj0Fji5E9JStE1fCaBilIi4VeY8qNwubKoQJSKSB+vCTy/VbVooa+XoyhIR\nEfEUxsdB6M3hJO+JIcmJ7qjwho0Iq1WHjVFzbduySUREPIcxhjJ39qH2vLn416/P4eef58BD/yL1\nuOvmODmMg971ejOv2zxurHojozeNpv/C/mw7uc1lGdzKLxg6vwd9p0LMIUhPzeiM0jZ9xZ6KUSIi\nIiLFgXVhl5StxSJ1SomIiAcKurYSXqG+xCzdl+8b24wxRER259ShA+z+daPNCUVExFP4hodT/cuJ\nVBz5LHE//UR0ZGdiFrl2hmBYYBij247m3Zvf5UTCCfov7M/bG94mITXBpTncpn5HGLYGKl8DXr7u\nTiMuoGKUiIiIiIiIiBR5xsdBSNvz3VE7898dVe+6GwkuV54NC2bbmE5ERDyNcTgoe9991JozG58a\nNTj4xJMcePxxUk+fdmmOW2vcyrxu8+h+RXe+2PYFPeb1YO3htS7N4DYhFSHuOCTHaZu+EkDFKBHx\nCBlb9enWehGRy5JtGz1Xb9uHfoSLiIgHCLq2El6l/JzqjvLy9qZZhy7s376Fo9E7bU4oIiKexq92\nbWpOmUyFxx4jdukyojt3IXb5cpdmCPUNZdQNo5hw+wQcxsHgbwfzwo8vcDbprEtzuEWbERBaRdv0\nlQAqRomIiIgUNxcpStlWL8payAVbBIqIiFyC8T7fHbU3hqS/8t8d1fiWO/ANCGBD1Bwb04mIiKcy\n3t6Uf3AotWZMx7tcOQ489C8OjXyOtNhYl+ZoUbkFs7rMYuDVA1mwawFd53ZlyZ4lxXuuevMB8MSO\njI9SrKkYJSIeIbMryhiT5yEiIrkwuRznZWticsksKXVKiYiIOwVFVMSrtB8xS/fm++KdX2AQjdrd\nwR9rVhNzwnVD7EVExLP4169PrRnTKffgUM7Om0d0l67E/fSTazN4+/NY88eYFjmNsMAwnlr1FMNX\nDOdI3BGX5hApbCpGiYiIiIiIiEixkdUdtS+WpD/zP/ejWccuAPyyeIFd0UREpAgwvr6EPfYYNadO\nweHvz74HBnLkv/8lPS7OpTnql63PlE5TeLL5k6w9tJZu87rx9e9fk26luzSHSGFRMUpEPEb2uxYt\ny8r1EBGRHCznjgu27bOje+mCNixt2yciIu4R1DyjO+qsE7OjQsuHUe+6G9m8dDFJ8fE2JxQREU8X\ncM011Jozm7L33cfpqdOI7t6D+I0bXZrB2+HNgKsHMLvLbK4ufzWv/PwKAxYPIPpstEtziBQGFaNE\nxKNkFp20HZ+IiE0s923bpx/tIiLiKsbbQUi7cFL2x5L4R/67oyIiu5OcEM+W5UtsTCciIkWFw9+f\niiOfpcaXEyE9nb1338PR198gPSnJpTnCQ8MZf9t4Xm71MrvO7KLX/F6M/W0sKWkpLs0hcjlUjCoC\nnJ2Vo9k6IiIickk5OqVs7WDKZS3NkxIREVcIal4RrzLOzY6qVKcu1RpczaZv5pOelmZzQhERKSoC\nr72W2vPmUvrOPpz6/HN29+hJwpYtLs1gjKHbFd2Y120et1S/hQ9//ZA+UX3YfHyzS3OIFJSKUSIi\nIiIiIvIPxpj2xpg/jDE7jTHPXuK8XsYYyxgT4cp8InkxXg5C21Un5cA5En8/le/XRUR2J/bEcf5c\n+4ON6UREpKhxBAVRedQowsePJ/3cOfb07cfx99/HSk52aY7yAeV5s82bvN/2fWKSY7h70d28vu51\n4lO0xax4NhWjPJwx5oJ5OXl1Ozl7voin0veviIiLZOtasn07vVzmSYmIZzLGeAEfAR2ABkA/Y0yD\nXM4LAYYDP7s2oUj+BDYLw6usPzFOzI6q3fRaylSpxoaoOZpbKyIi/xDc+kZqL5hPqchITnw8ht13\n9iXxjz9dnqNt9bbM6zqPPlf2YdKOSXSf150fDupGCvFcKkYVM/oPZRERESmQHNvp2bZtX7b1srbt\nExFP1ALYaVlWtGVZycA0oGsu570MvAEkujKcSH5ldEeFk3LwHIk78tcdZRwOmnfsytHonRzYsdXm\nhCIiUhR5hYZS5fXXqPbhB6QeO8buXr04MW48Z+bOZUf9q0iPi3NJjmDfYP593b+Z2H4ift5+DFs6\njJGrR3I6Mf/zEkVcRcWoYij7zCgVp6Qo0/eviIibuLpTyqBZUiKepyqwP9vXB84/lsUY0xQItywr\n6lJvZIwZYozZYIzZcPz48cJPKpKHwKYV8Srn79TsqAZt2hEQEsqGqDk2pxMRkaIs5NZbqb1gPiFt\n23L8nXc4/OxIAPbce69LczSr2IwZnWcwtPFQFu9ZTNe5XYmKjtK1NfEoKkYVQ9qmT0RERC5bjk6p\nzKKULf9pkWP7PhHxCLn925h1NcMY4wDeBZ7M640syxpnWVaEZVkRFSpUKMSIIvljvEzG7KhDcSRu\nP5mv1/j4+tHkjk5Eb1zHqUMHbE4oIiJFmXfZslR9bzRV3nor67Gkbds58MhwUg4fdlkOPy8/Hm76\nMNMjpxMeEs7I1SMZtmwYh84dclkGkUtRMUpERERERERyOgCEZ/u6GpD9SkYIcDWw0hizB7gOmG+M\niXBZQhEnBDYJw7t8QMbsqPT83SXe5PZOePn4sDFqrs3pRESkqDPGUCqyE/j5Zjzg7c251avZ1SmS\nkxM+w0pJcVmWumXq8mWHL3m2xbNsOrqJbvO6MXnHZNLS01yWQSQ3KkbJBdv6ZR4i7pDb96K+N0VE\nPEC2DqnMeVK2rmUK6RCRy7EeqGuMqWWM8QX6AvMzn7Qs66xlWeUty6ppWVZNYC3QxbKsDe6JK3Jp\nxssQ0i6clMP5744KLFWaBje1Y/v3y4mPOWtzQhERKQ4qPf883pUqUenFF6gdtYCgFi049uab7O7R\nk/iNG12Ww8vhxV1X3cXcrnNpVrEZr617jXu/uZe/Tv/lsgwiOakYVcwU5GJ99m39Mg8RV8vt+/Bi\nh4iIuIk7tu3jfF3JcuIg20cRKRDLslKBh4ElwA5gumVZ24wx/zXGdHFvOpGCCbwmsztqb767o5p3\n6kZqSjK/LlloczoRESkOyvTpQ92VKyjTpw++1aoR/skYqn30IWlx59h7190cGvkcqadOuSxPleAq\njLllDK+2fpV9sfvoE9WHD3/5kOS0ZJdlEMlkPOTCrkeE8FTZC0w5/3kZY3J97GLn5/beHvI9ICIi\nIkWNufBTW/6TImexKz9rmHyeV/yoH0w8XkREhLVhg5qnxH3ifznGqa//oOxd9QlslL8ZZnNef4nD\nO/9k8Eef4ePrZ3NCEREpjtLj4zkx5hNOfv45jqAgwh5/nNJ9emMcrusVOZV4ijfXv0lUdBS1StXi\npRteomlYU5etL8WXMWajZVl5btetzigRERERERERKRECrqmAdwXnZkdFRHYnIeYsO75fYXM6EREp\nrhyBgYQ9+QS1587Bv149jowaxZ6+/Ujcvt1lGcr6l+XV1q8y5tYxJKYmcu839/LK2lc4l3zOZRmk\nZFMxqgi41PZkF3tM25mJiIiI7bJtjWfbLKns2+5lnyd1MSW3K0pERPLBOAyht1Qn9Wg8CVtP5Os1\n1Ro0IqxWHTYsnIuVnm5zQhERKc78rriC6l9OpMobr5Ny8CC7e/XmyCv/R1psrMsy3Fj1RuZ2ncvd\nV93N9D+m03VeV1buX+my9aXkUjFKRERERC5ftllSFPYsqexFqIsVpbI/LyIicgkBjSvgHZb/7ihj\nDBGde3D60AGif9E2kyIicnmMMZTq0oU63yyiTN87OT15Mrs6duRs1EKXNRcE+gQyosUIJnWcRKhv\nKI8sf4SnVj3FiYT83aghUhAqRomIiIhI4cjRKWXrBKPMtURERJyU0R1Vg9Rj8SRsOZ6v19Rr2YqQ\nchXYGDXH5nQiIlJSeIWGUunFF6k5fTo+YRU59NRT7HvgAZKid7ssQ+MKjZkeOZ2HmzzM8n3L6Tq3\nK3N3ztWOW2ILFaNEREREpPDl6GC67E6p7O+XU/aOKRERkXwIaFQe74qB+e6O8vL2plmHzuzfvoWj\n0TtdkFBEREqKgEZXU3P611R88QUSt25jd9euHHvvPdITE12yvo+XD0OvGcrMLjO5ovQVvPDjCwz+\nbjD7Y/e7ZH0pOVSMEhEREREREZESJWt21PEEEjbnrzuq0S134BsQwAZ1R4mISCEzXl6U7d+fOt8s\nIqRDe06O+YToyM7Erlzpsgy1S9Xm8/af8++W/2bria30mNeDidsmkpqe6rIMUrypGCUiIiIi9smx\nbZ+53C6pnN1RmhMlIiIFFHB1eXwqBRKzLH/dUX6BQTS6pT1/rFlNzIljLkgoIiIljXf58lR94w2q\nT5yI8fPjwIPD2P/ww6QcOuSS9R3GwZ3172Ru17lcV/k63trwFnctuovfT/3ukvWleFMxSkRERETs\nl60oZfs8KRERkXwwDkPILTVIPZ5A/G/5645q1qEzAJu+WWBnNBERKeGCWrag9pzZVHjiCeJ++JFd\nnSI5+emnWCkpLlm/UlAl3m/3Pm+2eZMjcUfoG9WX0RtHk5jqmq0DpXhSMUpEREREXMfiH/OkCvQe\nma9VV5SIiFyGgIbl8KkUROyyfVhpef9SCS0fxpXXt2bLssUkxce5IKGIiJRUxteX8kMGUzsqiqAb\nbuDYW28T3b078evXu2Z9Y2hfsz3zu82nc53OTNg6gV4LerH+iGvWl+JHxSgRERERERERKZGMwxB6\na3VSTyQQ/2v+tt6LiOxOckICW5YtsTmdiIgI+FarSvhHH1Lt44+x4hPYe8+9HBrxLKknT7pk/VJ+\npXi51cuMv308aelpPLDkAUb9NIqY5BiXrC/Fh4pRIiIiIuIeOTqknJollbXfn4iIyOXxb1gOn8pB\nxC7PX3dUxdpXEN6gEZu+WUBaqoa6i4iIa4S0a0vthVGUGzKEs4sWsatDR05Pm4aVluaS9a+rfB2z\nu87m/ob3M2fnHLrO7crSvUtdsrYUDypGiYiIiIh7ZZsnleu2fcbJQ0RExAnGGEJvrUHqyUTif8lf\nd1TzyO7EnjzOnz//aHM6ERGRvzkCAgh74nF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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import matplotlib.pyplot as plt\n", "%matplotlib inline\n", "import numpy as np\n", "import matplotlib.image as mpimg\n", "img=mpimg.imread(\"http://camino.cs.ucl.ac.uk/uploads/Tutorials/VCLSsynth.png\")\n", " \n", "mask_nonzero = scheme.gradient_strengths>0.\n", "G_nonzero = scheme.gradient_strengths[mask_nonzero]\n", "Delta_nonzero = scheme.Delta[mask_nonzero]\n", "delta_nonzero = scheme.delta[mask_nonzero]\n", "\n", "predicted_data = verdict_fit.predict()[0]\n", "predicted_data_nonzero = predicted_data[mask_nonzero]\n", "data_nonzero = data[mask_nonzero]\n", "\n", "fig, axs = plt.subplots(1, 2, figsize=[30, 10])\n", "axs = axs.ravel()\n", "axs[0].imshow(img)\n", "axs[0].set_title('UCL Verdict Results', fontsize=30)\n", "axs[0].axis('off')\n", "\n", "for delta_, Delta_ in np.unique(np.c_[scheme.shell_delta, scheme.shell_Delta], axis=0):\n", " mask = np.all([Delta_nonzero == Delta_, delta_nonzero == delta_], axis=0)\n", " axs[1].plot(G_nonzero[mask], predicted_data_nonzero[mask])\n", " axs[1].scatter(G_nonzero[mask], data_nonzero[mask], s=3., marker='o')\n", "axs[1].set_title('Dmipy Verdict Results', fontsize=30)\n", "axs[1].set_xlabel('G(T/m)', fontsize=20)\n", "axs[1].set_ylabel('S', fontsize=20);" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "While we didn't exactly duplicate their graph style, we can see that both the plots and signal fitting are very similar between Dmipy's and UCL's implementation.\n", "\n", "Showing the fitting parameters, we can also see that Dmipy's estimate of the tumor cell diameter is 1.54e-5m, i.e. 15.4$\\mu m$, which falls exactly within the ranges that Panagiotaki et al. reports." ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'C1Stick_1_lambda_par': array([6.58332016e-09]),\n", " 'C1Stick_1_mu': array([[ 2.12873298, -2.53619312]]),\n", " 'S0': array([[1., 1., 1., 1., 1., 1.]]),\n", " 'S4SphereGaussianPhaseApproximation_1_diameter': array([1.54025803e-05]),\n", " 'partial_volume_0': array([0.76130392]),\n", " 'partial_volume_1': array([0.09744434]),\n", " 'partial_volume_2': array([0.14125174])}" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "verdict_fit.fitted_parameters" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## References\n", "- Panagiotaki, Eletheria, et al. \"Noninvasive quantification of solid tumor microstructure using VERDICT MRI.\" Cancer research 74.7 (2014): 1902-1912.\n", "- Balinov, Balin, et al. \"The NMR self-diffusion method applied to restricted diffusion. Simulation of echo attenuation from molecules in spheres and between planes.\" Journal of Magnetic Resonance, Series A 104.1 (1993): 17-25.\n", "- Farooq, Hamza, et al. \"Microstructure Imaging of Crossing (MIX) White Matter Fibers from diffusion MRI.\" Nature Scientific reports 6 (2016)." ] } ], "metadata": { "kernelspec": { "display_name": "Python 2", "language": "python", "name": "python2" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 2 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython2", "version": "2.7.13" } }, "nbformat": 4, "nbformat_minor": 2 }