Datasets
Models
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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"id": "304f6b0b",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Looking in indexes: https://pypi.org/simple, https://pip.repos.neuron.amazonaws.com\n",
"Collecting pydicom\n",
" Downloading pydicom-2.3.0-py3-none-any.whl (2.0 MB)\n",
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m2.0/2.0 MB\u001b[0m \u001b[31m17.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m:00:01\u001b[0m\n",
"\u001b[?25hRequirement already satisfied: PyAthena in /home/ec2-user/anaconda3/envs/python3/lib/python3.8/site-packages (2.9.3)\n",
"Requirement already satisfied: boto3>=1.4.4 in /home/ec2-user/anaconda3/envs/python3/lib/python3.8/site-packages (from PyAthena) (1.23.10)\n",
"Requirement already satisfied: botocore>=1.5.52 in /home/ec2-user/anaconda3/envs/python3/lib/python3.8/site-packages (from PyAthena) (1.26.10)\n",
"Requirement already satisfied: tenacity>=4.1.0 in /home/ec2-user/anaconda3/envs/python3/lib/python3.8/site-packages (from PyAthena) (8.0.1)\n",
"Requirement already satisfied: jmespath<2.0.0,>=0.7.1 in /home/ec2-user/anaconda3/envs/python3/lib/python3.8/site-packages (from boto3>=1.4.4->PyAthena) (0.10.0)\n",
"Requirement already satisfied: s3transfer<0.6.0,>=0.5.0 in /home/ec2-user/anaconda3/envs/python3/lib/python3.8/site-packages (from boto3>=1.4.4->PyAthena) (0.5.2)\n",
"Requirement already satisfied: urllib3<1.27,>=1.25.4 in /home/ec2-user/anaconda3/envs/python3/lib/python3.8/site-packages (from botocore>=1.5.52->PyAthena) (1.26.8)\n",
"Requirement already satisfied: python-dateutil<3.0.0,>=2.1 in /home/ec2-user/anaconda3/envs/python3/lib/python3.8/site-packages (from botocore>=1.5.52->PyAthena) (2.8.2)\n",
"Requirement already satisfied: six>=1.5 in /home/ec2-user/anaconda3/envs/python3/lib/python3.8/site-packages (from python-dateutil<3.0.0,>=2.1->botocore>=1.5.52->PyAthena) (1.16.0)\n",
"Installing collected packages: pydicom\n",
"Successfully installed pydicom-2.3.0\n",
"\u001b[33mWARNING: You are using pip version 22.0.4; however, version 22.1.2 is available.\n",
"You should consider upgrading via the '/home/ec2-user/anaconda3/envs/python3/bin/python -m pip install --upgrade pip' command.\u001b[0m\u001b[33m\n",
"\u001b[0m"
]
}
],
"source": [
"import sys\n",
"!{sys.executable} -m pip install pydicom PyAthena"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "3bdb2363",
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"Matplotlib is building the font cache; this may take a moment.\n"
]
}
],
"source": [
"import boto3\n",
"import tempfile\n",
"from tqdm.notebook import tqdm as with_progress_bar\n",
"from concurrent.futures import ProcessPoolExecutor\n",
"\n",
"import numpy as np\n",
"import pandas as pd\n",
"\n",
"import scipy.stats\n",
"from sklearn import linear_model\n",
"import matplotlib.pyplot as plt\n",
"\n",
"import pydicom #!{sys.executable} -m pip install pydicom\n",
"\n",
"from pyathena import connect #!{sys.executable} -m pip install PyAthena\n",
"from pyathena.cursor import DictCursor"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "627c6367",
"metadata": {},
"outputs": [],
"source": [
"s3 = boto3.client(\"s3\")\n",
"cfn = boto3.client(\"cloudformation\")"
]
},
{
"cell_type": "markdown",
"id": "4cb90f72",
"metadata": {},
"source": [
"# Background\n",
"\n",
"Modern clinical analysis projects may include data from several different modalities—genomics data, clinical observations, and imaging data may all be part of a patient’s case. Unfortunately, these data types are often kept in different formats and located in different places, so gathering and managing them in a coherent can be challenging. For example, NCI has several open datasets containing genomics data, patient clinical data, and imaging data. Some of this data is accessible through The Cancer Genome Atlas ([TCGA](https://www.cancer.gov/about-nci/organization/ccg/research/structural-genomics/tcga)) and associated API's, and the imaging data is stored in The Cancer Imaging Archive ([TCIA](https://wiki.cancerimagingarchive.net/)). The data is linked by the unique identifier assigned to patients during the studies, but it is difficult to link datasets with distinct API's.\n",
"Here, we used [AWS Glue](https://aws.amazon.com/glue/) ETL jobs to organize this disparate data into S3 buckets. \n",
"\n",
"Once in S3, we can easily link the datasets using [AWS Athena](https://aws.amazon.com/athena/) to query across different tables and pull information for analysis.\n",
"\n",
"What follows is a brief demonstration of how a researcher might build a cohort and use multimodal data for a analysis process."
]
},
{
"cell_type": "markdown",
"id": "9d54b020",
"metadata": {},
"source": [
"# Basic Athena queries for multimodal cohort building\n",
"\n",
"We have tables crawled by glue and stored in `s3` buckets containing patient test data and patient clinical metadata. First we connect to the database and create an Athena cursor to query. "
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "95935192",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"us-west-1\n",
"Project: GenomicsAnalysis\n",
"Database: genomicsanalysis\n",
"Work Group: genomicsanalysis-us-west-1\n",
"S3 bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n"
]
}
],
"source": [
"import os, jmespath\n",
"\n",
"session = boto3.session.Session()\n",
"region = session.region_name\n",
"print(region)\n",
"\n",
"project_name = os.environ.get('RESOURCE_PREFIX')\n",
"database_name = project_name.lower()\n",
"work_group_name = project_name.lower() + '-' + region\n",
"print('Project:', project_name)\n",
"print('Database:', database_name)\n",
"print('Work Group:', work_group_name)\n",
"\n",
"resources = cfn.describe_stacks(StackName='{0}-Pipeline'.format(project_name))\n",
"query = 'Stacks[].Outputs[?OutputKey==`DataLakeBucket`].OutputValue'\n",
"data_lake_bucket = path = jmespath.search(query, resources)[0][0]\n",
"print('S3 bucket:', data_lake_bucket)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "481267a4",
"metadata": {},
"outputs": [],
"source": [
"conn = connect(s3_staging_dir=f's3://{data_lake_bucket}/query-output',\n",
" region_name=region,\n",
" schema_name=database_name)\n",
"cursor = conn.cursor(DictCursor, work_group=work_group_name)"
]
},
{
"cell_type": "markdown",
"id": "8c61595e",
"metadata": {},
"source": [
"Next, we will count the number of unique patients in our full dataset:"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "070836f6",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"There are 1026 patients.\n"
]
}
],
"source": [
"STATEMENT = 'SELECT COUNT(DISTINCT bcr_patient_barcode) AS all_patients FROM clinical_patient;'\n",
"query_res = cursor.execute(STATEMENT).fetchall()\n",
"print(f\"There are {query_res[0]['all_patients']} patients.\")"
]
},
{
"cell_type": "markdown",
"id": "8354a850",
"metadata": {},
"source": [
"Let's quickly look at the age distribution of our patients. If no age is recorded for a patient, we'll set them to -1 to distinguish them from the main age distribution."
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "a632b7c5",
"metadata": {},
"outputs": [
{
"data": {
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",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"STATEMENT = 'SELECT age_at_initial_pathologic_diagnosis AS dx_age FROM clinical_patient;'\n",
"query_res = cursor.execute(STATEMENT).fetchall()\n",
"ages = []\n",
"for row in query_res:\n",
" try:\n",
" ages.append(int(row['dx_age']))\n",
" except ValueError:\n",
" ages.append(-1)\n",
"plt.hist(ages, bins=16)\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"id": "32cdff13",
"metadata": {},
"source": [
"## Narrowing the cohort\n",
"\n",
"Let's now look to see how many patients have tumor mutation data recorded in their clinical history. Our clinical data has records for EGFR, KRAS, and ALK-EML4 translocation status, but for the purposes of this analysis, let's focus only on EGFR."
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "defa9a58",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"egfr_mutation_status egfr_mutation_identified_type\n",
"NO [Not Available] 474\n",
"[Not Available] [Not Available] 395\n",
"YES [Not Available] 76\n",
"[Unknown] [Not Available] 55\n",
"YES Other 10\n",
" Exon 19 Deletion 9\n",
" L858R 4\n",
"NO Other 1\n",
"YES L861Q 1\n",
" T790M 1\n",
"dtype: int64"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"STATEMENT = \"\"\"\n",
"SELECT egfr_mutation_status, egfr_mutation_identified_type\n",
"FROM clinical_patient\n",
"\"\"\"\n",
"query_res = cursor.execute(STATEMENT).fetchall()\n",
"egfr_status = pd.DataFrame(query_res)\n",
"egfr_status.value_counts()"
]
},
{
"cell_type": "markdown",
"id": "f8bd85da",
"metadata": {},
"source": [
"It appears that 450 patients out of our full set of 1026 do not have EGFR mutation status recorded in their clinical history. Additionally, most of the patients who have an identified EGFR mutation do not have any data available about their mutation type. We will try to enrich that data by searching for specific EGFR mutations in the `tcga_mutation` table."
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "b311c0ac",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"egfr_mutation_status egfr_mutation_identified_type variant_type\n",
"NO [Not Available] [SNP] 13\n",
"[Not Available] [Not Available] [DEL] 11\n",
"NO [Not Available] [DEL] 10\n",
"[Not Available] [Not Available] [SNP] 9\n",
"YES Exon 19 Deletion [DEL] 7\n",
" L858R [SNP] 3\n",
" Exon 19 Deletion [SNP] 1\n",
" L861Q [SNP] 1\n",
" Other [DEL] 1\n",
" T790M [SNP] 1\n",
"[Unknown] [Not Available] [SNP] 1\n",
"dtype: int64"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"STATEMENT = \"\"\"\n",
"WITH egfr_mutation_type AS (\n",
" SELECT submitter_id, array_agg(distinct variant_type) as variant_type, \n",
" array_agg(distinct hgvsp_short) as hgvsp_short\n",
" FROM tcga_mutation\n",
" WHERE hugo_symbol = 'EGFR'\n",
" AND (exon_number = '19/28' and variant_type = 'DEL') \n",
" OR (hgvsp_short = 'p.L858R')\n",
" OR (hgvsp_short = 'p.T790M')\n",
" OR (hgvsp_short = 'p.L861Q')\n",
" GROUP BY submitter_id\n",
")\n",
"\n",
"SELECT bcr_patient_barcode, egfr_mutation_status, egfr_mutation_identified_type,\n",
" egfr_mutation_type.variant_type, egfr_mutation_type.hgvsp_short\n",
"FROM clinical_patient\n",
"LEFT JOIN egfr_mutation_type ON bcr_patient_barcode = egfr_mutation_type.submitter_id\n",
"\"\"\"\n",
"egfr_status_enhanced = pd.DataFrame(cursor.execute(STATEMENT).fetchall())\n",
"egfr_status_enhanced[[\"egfr_mutation_status\", \"egfr_mutation_identified_type\", \"variant_type\"]].value_counts()"
]
},
{
"cell_type": "markdown",
"id": "2f84a232",
"metadata": {},
"source": [
"With the mutation data, we're able to identify 21 additional patients with either Exon 19 Deletion or one of the three common SNPs. Interestingly, 23 additional patients were identified as having an EGFR mutation through the mutation data, who were recorded as having no EGFR mutation in their clinical history.\n",
"\n",
"Let's save the list of patient IDs having EGFR mutations for further analysis."
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "674d6007",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"We have 58 patients in our cohort.\n"
]
}
],
"source": [
"egfr_snp_mut = egfr_status_enhanced[egfr_status_enhanced.variant_type.isin(('[SNP]','[DEL]'))]\n",
"print(f'We have {len(egfr_snp_mut)} patients in our cohort.')"
]
},
{
"cell_type": "markdown",
"id": "e7c6bfc4",
"metadata": {},
"source": [
"## Image analysis\n",
"\n",
"Let's see how many patients in our small cohort have image data available.\n"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "3a781ada",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
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"\n",
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" vertical-align: top;\n",
" }\n",
"\n",
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" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>_col0</th>\n",
" <th>patient_id</th>\n",
" <th>series_uid</th>\n",
" <th>description</th>\n",
" <th>mod</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>TCGA-LUAD</td>\n",
" <td>TCGA-J2-8192</td>\n",
" <td>1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112...</td>\n",
" <td>SAG CHEST</td>\n",
" <td>CT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>TCGA-LUAD</td>\n",
" <td>TCGA-J2-8192</td>\n",
" <td>1.3.6.1.4.1.14519.5.2.1.3983.9002.138321164626...</td>\n",
" <td>SOFT TISSUE</td>\n",
" <td>CT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>TCGA-LUAD</td>\n",
" <td>TCGA-38-6178</td>\n",
" <td>1.3.6.1.4.1.14519.5.2.1.8421.9002.241095233362...</td>\n",
" <td>coronals</td>\n",
" <td>PT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>TCGA-LUAD</td>\n",
" <td>TCGA-38-4628</td>\n",
" <td>1.3.6.1.4.1.14519.5.2.1.8421.9002.101564030988...</td>\n",
" <td>LOCALIZER</td>\n",
" <td>CT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>TCGA-LUAD</td>\n",
" <td>TCGA-50-6591</td>\n",
" <td>1.3.6.1.4.1.14519.5.2.1.6450.9002.160846153697...</td>\n",
" <td>Topogram</td>\n",
" <td>CT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>TCGA-LUAD</td>\n",
" <td>TCGA-50-6591</td>\n",
" <td>1.3.6.1.4.1.14519.5.2.1.6450.9002.846229601736...</td>\n",
" <td>CT Spiral 5.0 B70s</td>\n",
" <td>CT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>TCGA-LUAD</td>\n",
" <td>TCGA-50-6591</td>\n",
" <td>1.3.6.1.4.1.14519.5.2.1.6450.9002.198989343210...</td>\n",
" <td>FUSED PET/CT</td>\n",
" <td>CT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>TCGA-LUAD</td>\n",
" <td>TCGA-38-6178</td>\n",
" <td>1.3.6.1.4.1.14519.5.2.1.8421.9002.570696184372...</td>\n",
" <td>Reformatted</td>\n",
" <td>CT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>TCGA-LUAD</td>\n",
" <td>TCGA-38-6178</td>\n",
" <td>1.3.6.1.4.1.14519.5.2.1.8421.9002.500879414859...</td>\n",
" <td>PE STUDY ST</td>\n",
" <td>CT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>TCGA-LUAD</td>\n",
" <td>TCGA-38-6178</td>\n",
" <td>1.3.6.1.4.1.14519.5.2.1.8421.9002.904457022040...</td>\n",
" <td>CT WB 5.0 B30f</td>\n",
" <td>CT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>TCGA-LUAD</td>\n",
" <td>TCGA-38-6178</td>\n",
" <td>1.3.6.1.4.1.14519.5.2.1.8421.9002.633911416262...</td>\n",
" <td>PET WB</td>\n",
" <td>PT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>TCGA-LUAD</td>\n",
" <td>TCGA-38-4628</td>\n",
" <td>1.3.6.1.4.1.14519.5.2.1.8421.9002.631687863423...</td>\n",
" <td>LOCALIZER</td>\n",
" <td>CT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>TCGA-LUAD</td>\n",
" <td>TCGA-J2-8192</td>\n",
" <td>1.3.6.1.4.1.14519.5.2.1.3983.9002.126841153385...</td>\n",
" <td>CHST COR</td>\n",
" <td>CT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>TCGA-LUAD</td>\n",
" <td>TCGA-38-6178</td>\n",
" <td>1.3.6.1.4.1.14519.5.2.1.8421.9002.126815156494...</td>\n",
" <td>Topogram 0.6 T20s</td>\n",
" <td>CT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>TCGA-LUAD</td>\n",
" <td>TCGA-38-6178</td>\n",
" <td>1.3.6.1.4.1.14519.5.2.1.8421.9002.704097504641...</td>\n",
" <td>Chest 5.0 B31f</td>\n",
" <td>CT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>TCGA-LUAD</td>\n",
" <td>TCGA-38-6178</td>\n",
" <td>1.3.6.1.4.1.14519.5.2.1.8421.9002.209868708527...</td>\n",
" <td>LUNG</td>\n",
" <td>CT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>TCGA-LUAD</td>\n",
" <td>TCGA-38-6178</td>\n",
" <td>1.3.6.1.4.1.14519.5.2.1.8421.9002.188001454543...</td>\n",
" <td>CT 5.0 B40s</td>\n",
" <td>CT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td>TCGA-LUAD</td>\n",
" <td>TCGA-38-4628</td>\n",
" <td>1.3.6.1.4.1.14519.5.2.1.8421.9002.168412371278...</td>\n",
" <td>unenhanced</td>\n",
" <td>CT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>TCGA-LUAD</td>\n",
" <td>TCGA-38-4628</td>\n",
" <td>1.3.6.1.4.1.14519.5.2.1.8421.9002.202400537682...</td>\n",
" <td>LOCALIZER</td>\n",
" <td>CT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td>TCGA-LUAD</td>\n",
" <td>TCGA-J2-8192</td>\n",
" <td>1.3.6.1.4.1.14519.5.2.1.3983.9002.160354988389...</td>\n",
" <td>LUNG</td>\n",
" <td>CT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>TCGA-LUAD</td>\n",
" <td>TCGA-J2-8192</td>\n",
" <td>1.3.6.1.4.1.14519.5.2.1.3983.9002.319652475863...</td>\n",
" <td>Processed Images</td>\n",
" <td>CT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>TCGA-LUAD</td>\n",
" <td>TCGA-38-6178</td>\n",
" <td>1.3.6.1.4.1.14519.5.2.1.8421.9002.159774352322...</td>\n",
" <td>Recon 2: RENAL STONE STUDY</td>\n",
" <td>CT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td>TCGA-LUAD</td>\n",
" <td>TCGA-38-6178</td>\n",
" <td>1.3.6.1.4.1.14519.5.2.1.8421.9002.251867863723...</td>\n",
" <td>SCOUT</td>\n",
" <td>CT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23</th>\n",
" <td>TCGA-LUAD</td>\n",
" <td>TCGA-38-6178</td>\n",
" <td>1.3.6.1.4.1.14519.5.2.1.8421.9002.300289362965...</td>\n",
" <td>Reformatted</td>\n",
" <td>CT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24</th>\n",
" <td>TCGA-LUAD</td>\n",
" <td>TCGA-38-6178</td>\n",
" <td>1.3.6.1.4.1.14519.5.2.1.8421.9002.416884313303...</td>\n",
" <td>PET WB-uncorrected</td>\n",
" <td>PT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25</th>\n",
" <td>TCGA-LUAD</td>\n",
" <td>TCGA-38-4628</td>\n",
" <td>1.3.6.1.4.1.14519.5.2.1.8421.9002.320536261464...</td>\n",
" <td>LOCALIZER</td>\n",
" <td>CT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>26</th>\n",
" <td>TCGA-LUAD</td>\n",
" <td>TCGA-38-4628</td>\n",
" <td>1.3.6.1.4.1.14519.5.2.1.8421.9002.210839207287...</td>\n",
" <td>LOCALIZER</td>\n",
" <td>CT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>27</th>\n",
" <td>TCGA-LUAD</td>\n",
" <td>TCGA-38-6178</td>\n",
" <td>1.3.6.1.4.1.14519.5.2.1.8421.9002.270738505972...</td>\n",
" <td>Chest Thin Mip Coronal</td>\n",
" <td>CT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>28</th>\n",
" <td>TCGA-LUAD</td>\n",
" <td>TCGA-38-6178</td>\n",
" <td>1.3.6.1.4.1.14519.5.2.1.8421.9002.864459481049...</td>\n",
" <td>Reformatted</td>\n",
" <td>CT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29</th>\n",
" <td>TCGA-LUAD</td>\n",
" <td>TCGA-38-6178</td>\n",
" <td>1.3.6.1.4.1.14519.5.2.1.8421.9002.560858650969...</td>\n",
" <td>Reformatted</td>\n",
" <td>CT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>30</th>\n",
" <td>TCGA-LUAD</td>\n",
" <td>TCGA-38-6178</td>\n",
" <td>1.3.6.1.4.1.14519.5.2.1.8421.9002.139127263722...</td>\n",
" <td>PET WB</td>\n",
" <td>PT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>31</th>\n",
" <td>TCGA-LUAD</td>\n",
" <td>TCGA-38-6178</td>\n",
" <td>1.3.6.1.4.1.14519.5.2.1.8421.9002.900734700813...</td>\n",
" <td>projections</td>\n",
" <td>PT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>32</th>\n",
" <td>TCGA-LUAD</td>\n",
" <td>TCGA-38-6178</td>\n",
" <td>1.3.6.1.4.1.14519.5.2.1.8421.9002.335999811444...</td>\n",
" <td>PET WB Uncorrected</td>\n",
" <td>PT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>33</th>\n",
" <td>TCGA-LUAD</td>\n",
" <td>TCGA-38-6178</td>\n",
" <td>1.3.6.1.4.1.14519.5.2.1.8421.9002.256607735971...</td>\n",
" <td>PROJECTIONS</td>\n",
" <td>PT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>34</th>\n",
" <td>TCGA-LUAD</td>\n",
" <td>TCGA-38-4628</td>\n",
" <td>1.3.6.1.4.1.14519.5.2.1.8421.9002.513003795645...</td>\n",
" <td>without contrast</td>\n",
" <td>CT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>35</th>\n",
" <td>TCGA-LUAD</td>\n",
" <td>TCGA-50-6591</td>\n",
" <td>1.3.6.1.4.1.14519.5.2.1.6450.9002.325710935120...</td>\n",
" <td>FUSED LUNG WINDOW</td>\n",
" <td>CT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>36</th>\n",
" <td>TCGA-LUAD</td>\n",
" <td>TCGA-50-6591</td>\n",
" <td>1.3.6.1.4.1.14519.5.2.1.6450.9002.243448495980...</td>\n",
" <td>DYNAMIC MODE</td>\n",
" <td>CT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>37</th>\n",
" <td>TCGA-LUAD</td>\n",
" <td>TCGA-38-4628</td>\n",
" <td>1.3.6.1.4.1.14519.5.2.1.8421.9002.926531525790...</td>\n",
" <td>unenhanced</td>\n",
" <td>CT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>38</th>\n",
" <td>TCGA-LUAD</td>\n",
" <td>TCGA-50-6591</td>\n",
" <td>1.3.6.1.4.1.14519.5.2.1.6450.9002.210914875533...</td>\n",
" <td>PET WB-uncorrected</td>\n",
" <td>PT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>39</th>\n",
" <td>TCGA-LUAD</td>\n",
" <td>TCGA-38-6178</td>\n",
" <td>1.3.6.1.4.1.14519.5.2.1.8421.9002.157893423003...</td>\n",
" <td>SCOUT</td>\n",
" <td>CT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>40</th>\n",
" <td>TCGA-LUAD</td>\n",
" <td>TCGA-38-6178</td>\n",
" <td>1.3.6.1.4.1.14519.5.2.1.8421.9002.305555591466...</td>\n",
" <td>CT WB 5.0 eFoV</td>\n",
" <td>CT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>41</th>\n",
" <td>TCGA-LUAD</td>\n",
" <td>TCGA-38-6178</td>\n",
" <td>1.3.6.1.4.1.14519.5.2.1.8421.9002.554748855172...</td>\n",
" <td>CORONALS</td>\n",
" <td>PT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>42</th>\n",
" <td>TCGA-LUAD</td>\n",
" <td>TCGA-50-6591</td>\n",
" <td>1.3.6.1.4.1.14519.5.2.1.6450.9002.333850093573...</td>\n",
" <td>CT Spiral 5.0 B40s</td>\n",
" <td>CT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>43</th>\n",
" <td>TCGA-LUAD</td>\n",
" <td>TCGA-50-6591</td>\n",
" <td>1.3.6.1.4.1.14519.5.2.1.6450.9002.156462637139...</td>\n",
" <td>LOCALIZER</td>\n",
" <td>CT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>44</th>\n",
" <td>TCGA-LUAD</td>\n",
" <td>TCGA-J2-8192</td>\n",
" <td>1.3.6.1.4.1.14519.5.2.1.3983.9002.323310556191...</td>\n",
" <td>SCOUT</td>\n",
" <td>CT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>45</th>\n",
" <td>TCGA-LUAD</td>\n",
" <td>TCGA-38-6178</td>\n",
" <td>1.3.6.1.4.1.14519.5.2.1.8421.9002.467784322053...</td>\n",
" <td>RENAL STONE STUDY</td>\n",
" <td>CT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>46</th>\n",
" <td>TCGA-LUAD</td>\n",
" <td>TCGA-38-6178</td>\n",
" <td>1.3.6.1.4.1.14519.5.2.1.8421.9002.182465758586...</td>\n",
" <td>Smart Prep Series</td>\n",
" <td>CT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>47</th>\n",
" <td>TCGA-LUAD</td>\n",
" <td>TCGA-38-6178</td>\n",
" <td>1.3.6.1.4.1.14519.5.2.1.8421.9002.135538674486...</td>\n",
" <td>THINS FOR CORONAL</td>\n",
" <td>CT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>48</th>\n",
" <td>TCGA-LUAD</td>\n",
" <td>TCGA-38-6178</td>\n",
" <td>1.3.6.1.4.1.14519.5.2.1.8421.9002.868226940509...</td>\n",
" <td>Reformatted</td>\n",
" <td>CT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>49</th>\n",
" <td>TCGA-LUAD</td>\n",
" <td>TCGA-38-4628</td>\n",
" <td>1.3.6.1.4.1.14519.5.2.1.8421.9002.433116391104...</td>\n",
" <td>without contrast</td>\n",
" <td>CT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>50</th>\n",
" <td>TCGA-LUAD</td>\n",
" <td>TCGA-38-4628</td>\n",
" <td>1.3.6.1.4.1.14519.5.2.1.8421.9002.257453429620...</td>\n",
" <td>without contrast</td>\n",
" <td>CT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>51</th>\n",
" <td>TCGA-LUAD</td>\n",
" <td>TCGA-50-6591</td>\n",
" <td>1.3.6.1.4.1.14519.5.2.1.6450.9002.316574097062...</td>\n",
" <td>PET WB</td>\n",
" <td>PT</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" _col0 patient_id \\\n",
"0 TCGA-LUAD TCGA-J2-8192 \n",
"1 TCGA-LUAD TCGA-J2-8192 \n",
"2 TCGA-LUAD TCGA-38-6178 \n",
"3 TCGA-LUAD TCGA-38-4628 \n",
"4 TCGA-LUAD TCGA-50-6591 \n",
"5 TCGA-LUAD TCGA-50-6591 \n",
"6 TCGA-LUAD TCGA-50-6591 \n",
"7 TCGA-LUAD TCGA-38-6178 \n",
"8 TCGA-LUAD TCGA-38-6178 \n",
"9 TCGA-LUAD TCGA-38-6178 \n",
"10 TCGA-LUAD TCGA-38-6178 \n",
"11 TCGA-LUAD TCGA-38-4628 \n",
"12 TCGA-LUAD TCGA-J2-8192 \n",
"13 TCGA-LUAD TCGA-38-6178 \n",
"14 TCGA-LUAD TCGA-38-6178 \n",
"15 TCGA-LUAD TCGA-38-6178 \n",
"16 TCGA-LUAD TCGA-38-6178 \n",
"17 TCGA-LUAD TCGA-38-4628 \n",
"18 TCGA-LUAD TCGA-38-4628 \n",
"19 TCGA-LUAD TCGA-J2-8192 \n",
"20 TCGA-LUAD TCGA-J2-8192 \n",
"21 TCGA-LUAD TCGA-38-6178 \n",
"22 TCGA-LUAD TCGA-38-6178 \n",
"23 TCGA-LUAD TCGA-38-6178 \n",
"24 TCGA-LUAD TCGA-38-6178 \n",
"25 TCGA-LUAD TCGA-38-4628 \n",
"26 TCGA-LUAD TCGA-38-4628 \n",
"27 TCGA-LUAD TCGA-38-6178 \n",
"28 TCGA-LUAD TCGA-38-6178 \n",
"29 TCGA-LUAD TCGA-38-6178 \n",
"30 TCGA-LUAD TCGA-38-6178 \n",
"31 TCGA-LUAD TCGA-38-6178 \n",
"32 TCGA-LUAD TCGA-38-6178 \n",
"33 TCGA-LUAD TCGA-38-6178 \n",
"34 TCGA-LUAD TCGA-38-4628 \n",
"35 TCGA-LUAD TCGA-50-6591 \n",
"36 TCGA-LUAD TCGA-50-6591 \n",
"37 TCGA-LUAD TCGA-38-4628 \n",
"38 TCGA-LUAD TCGA-50-6591 \n",
"39 TCGA-LUAD TCGA-38-6178 \n",
"40 TCGA-LUAD TCGA-38-6178 \n",
"41 TCGA-LUAD TCGA-38-6178 \n",
"42 TCGA-LUAD TCGA-50-6591 \n",
"43 TCGA-LUAD TCGA-50-6591 \n",
"44 TCGA-LUAD TCGA-J2-8192 \n",
"45 TCGA-LUAD TCGA-38-6178 \n",
"46 TCGA-LUAD TCGA-38-6178 \n",
"47 TCGA-LUAD TCGA-38-6178 \n",
"48 TCGA-LUAD TCGA-38-6178 \n",
"49 TCGA-LUAD TCGA-38-4628 \n",
"50 TCGA-LUAD TCGA-38-4628 \n",
"51 TCGA-LUAD TCGA-50-6591 \n",
"\n",
" series_uid \\\n",
"0 1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112... \n",
"1 1.3.6.1.4.1.14519.5.2.1.3983.9002.138321164626... \n",
"2 1.3.6.1.4.1.14519.5.2.1.8421.9002.241095233362... \n",
"3 1.3.6.1.4.1.14519.5.2.1.8421.9002.101564030988... \n",
"4 1.3.6.1.4.1.14519.5.2.1.6450.9002.160846153697... \n",
"5 1.3.6.1.4.1.14519.5.2.1.6450.9002.846229601736... \n",
"6 1.3.6.1.4.1.14519.5.2.1.6450.9002.198989343210... \n",
"7 1.3.6.1.4.1.14519.5.2.1.8421.9002.570696184372... \n",
"8 1.3.6.1.4.1.14519.5.2.1.8421.9002.500879414859... \n",
"9 1.3.6.1.4.1.14519.5.2.1.8421.9002.904457022040... \n",
"10 1.3.6.1.4.1.14519.5.2.1.8421.9002.633911416262... \n",
"11 1.3.6.1.4.1.14519.5.2.1.8421.9002.631687863423... \n",
"12 1.3.6.1.4.1.14519.5.2.1.3983.9002.126841153385... \n",
"13 1.3.6.1.4.1.14519.5.2.1.8421.9002.126815156494... \n",
"14 1.3.6.1.4.1.14519.5.2.1.8421.9002.704097504641... \n",
"15 1.3.6.1.4.1.14519.5.2.1.8421.9002.209868708527... \n",
"16 1.3.6.1.4.1.14519.5.2.1.8421.9002.188001454543... \n",
"17 1.3.6.1.4.1.14519.5.2.1.8421.9002.168412371278... \n",
"18 1.3.6.1.4.1.14519.5.2.1.8421.9002.202400537682... \n",
"19 1.3.6.1.4.1.14519.5.2.1.3983.9002.160354988389... \n",
"20 1.3.6.1.4.1.14519.5.2.1.3983.9002.319652475863... \n",
"21 1.3.6.1.4.1.14519.5.2.1.8421.9002.159774352322... \n",
"22 1.3.6.1.4.1.14519.5.2.1.8421.9002.251867863723... \n",
"23 1.3.6.1.4.1.14519.5.2.1.8421.9002.300289362965... \n",
"24 1.3.6.1.4.1.14519.5.2.1.8421.9002.416884313303... \n",
"25 1.3.6.1.4.1.14519.5.2.1.8421.9002.320536261464... \n",
"26 1.3.6.1.4.1.14519.5.2.1.8421.9002.210839207287... \n",
"27 1.3.6.1.4.1.14519.5.2.1.8421.9002.270738505972... \n",
"28 1.3.6.1.4.1.14519.5.2.1.8421.9002.864459481049... \n",
"29 1.3.6.1.4.1.14519.5.2.1.8421.9002.560858650969... \n",
"30 1.3.6.1.4.1.14519.5.2.1.8421.9002.139127263722... \n",
"31 1.3.6.1.4.1.14519.5.2.1.8421.9002.900734700813... \n",
"32 1.3.6.1.4.1.14519.5.2.1.8421.9002.335999811444... \n",
"33 1.3.6.1.4.1.14519.5.2.1.8421.9002.256607735971... \n",
"34 1.3.6.1.4.1.14519.5.2.1.8421.9002.513003795645... \n",
"35 1.3.6.1.4.1.14519.5.2.1.6450.9002.325710935120... \n",
"36 1.3.6.1.4.1.14519.5.2.1.6450.9002.243448495980... \n",
"37 1.3.6.1.4.1.14519.5.2.1.8421.9002.926531525790... \n",
"38 1.3.6.1.4.1.14519.5.2.1.6450.9002.210914875533... \n",
"39 1.3.6.1.4.1.14519.5.2.1.8421.9002.157893423003... \n",
"40 1.3.6.1.4.1.14519.5.2.1.8421.9002.305555591466... \n",
"41 1.3.6.1.4.1.14519.5.2.1.8421.9002.554748855172... \n",
"42 1.3.6.1.4.1.14519.5.2.1.6450.9002.333850093573... \n",
"43 1.3.6.1.4.1.14519.5.2.1.6450.9002.156462637139... \n",
"44 1.3.6.1.4.1.14519.5.2.1.3983.9002.323310556191... \n",
"45 1.3.6.1.4.1.14519.5.2.1.8421.9002.467784322053... \n",
"46 1.3.6.1.4.1.14519.5.2.1.8421.9002.182465758586... \n",
"47 1.3.6.1.4.1.14519.5.2.1.8421.9002.135538674486... \n",
"48 1.3.6.1.4.1.14519.5.2.1.8421.9002.868226940509... \n",
"49 1.3.6.1.4.1.14519.5.2.1.8421.9002.433116391104... \n",
"50 1.3.6.1.4.1.14519.5.2.1.8421.9002.257453429620... \n",
"51 1.3.6.1.4.1.14519.5.2.1.6450.9002.316574097062... \n",
"\n",
" description mod \n",
"0 SAG CHEST CT \n",
"1 SOFT TISSUE CT \n",
"2 coronals PT \n",
"3 LOCALIZER CT \n",
"4 Topogram CT \n",
"5 CT Spiral 5.0 B70s CT \n",
"6 FUSED PET/CT CT \n",
"7 Reformatted CT \n",
"8 PE STUDY ST CT \n",
"9 CT WB 5.0 B30f CT \n",
"10 PET WB PT \n",
"11 LOCALIZER CT \n",
"12 CHST COR CT \n",
"13 Topogram 0.6 T20s CT \n",
"14 Chest 5.0 B31f CT \n",
"15 LUNG CT \n",
"16 CT 5.0 B40s CT \n",
"17 unenhanced CT \n",
"18 LOCALIZER CT \n",
"19 LUNG CT \n",
"20 Processed Images CT \n",
"21 Recon 2: RENAL STONE STUDY CT \n",
"22 SCOUT CT \n",
"23 Reformatted CT \n",
"24 PET WB-uncorrected PT \n",
"25 LOCALIZER CT \n",
"26 LOCALIZER CT \n",
"27 Chest Thin Mip Coronal CT \n",
"28 Reformatted CT \n",
"29 Reformatted CT \n",
"30 PET WB PT \n",
"31 projections PT \n",
"32 PET WB Uncorrected PT \n",
"33 PROJECTIONS PT \n",
"34 without contrast CT \n",
"35 FUSED LUNG WINDOW CT \n",
"36 DYNAMIC MODE CT \n",
"37 unenhanced CT \n",
"38 PET WB-uncorrected PT \n",
"39 SCOUT CT \n",
"40 CT WB 5.0 eFoV CT \n",
"41 CORONALS PT \n",
"42 CT Spiral 5.0 B40s CT \n",
"43 LOCALIZER CT \n",
"44 SCOUT CT \n",
"45 RENAL STONE STUDY CT \n",
"46 Smart Prep Series CT \n",
"47 THINS FOR CORONAL CT \n",
"48 Reformatted CT \n",
"49 without contrast CT \n",
"50 without contrast CT \n",
"51 PET WB PT "
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"patient_ids = '(' + ','.join(f\"'{p}'\" for p in egfr_snp_mut['bcr_patient_barcode']) + ')'\n",
"STATEMENT = \"\"\"\n",
"SELECT arbitrary(imgs.collection), arbitrary(imgs.patientid) as patient_id, imgs.seriesinstanceuid AS series_uid, \n",
" arbitrary(imgs.seriesdescription) as description, arbitrary(imgs.modality) as mod\n",
"FROM tcia_image_series imgs\n",
"WHERE imgs.patientid IN {patient_ids}\n",
"GROUP BY imgs.seriesinstanceuid\n",
"\"\"\".format(patient_ids=patient_ids)\n",
"res_all_img_study = pd.DataFrame(cursor.execute(STATEMENT).fetchall())\n",
"res_all_img_study"
]
},
{
"cell_type": "markdown",
"id": "3872d1bd",
"metadata": {},
"source": [
"To visualize the patient images, we retrieve them directly from the TCIA API to the data lake bucket, and then visualize them using Matplotlib within the notebook."
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "6f7e6c74",
"metadata": {},
"outputs": [],
"source": [
"import io\n",
"import requests\n",
"from zipfile import ZipFile\n",
"\n",
"TCIA_API = \"https://services.cancerimagingarchive.net/services/v4/TCIA/query/\"\n",
"S3_RESOURCE = boto3.resource(\"s3\")\n",
"\n",
"def get_image_stream_unzip(seriesuid, bucket_name=data_lake_bucket):\n",
" \"\"\"Get Zip file from API, unpack in memory and write to S3 bucket\"\"\"\n",
" url = TCIA_API + \"getImage\"\n",
" parameters = {\"SeriesInstanceUID\": seriesuid}\n",
" output_keys = []\n",
" with requests.get(url, params=parameters, stream=True) as req:\n",
" req.raise_for_status()\n",
" with io.BytesIO() as byte_stream:\n",
" for chunk in req.iter_content(chunk_size=10000):\n",
" byte_stream.write(chunk)\n",
" with ZipFile(byte_stream, \"r\") as zo:\n",
" list_of_files = [i for i in zo.namelist() if i.endswith(\"dcm\")]\n",
" for dcm in list_of_files:\n",
" item = zo.read(dcm)\n",
" bucket_key = f\"tcia-images/{seriesuid}/{dcm.replace('./', '')}\"\n",
" S3_RESOURCE.Bucket(bucket_name).put_object(Key=bucket_key, Body=item)\n",
" print(f\"Writing DICOM object: {bucket_key} to bucket: {bucket_name}\")\n",
" output_keys.append(bucket_key)\n",
" return output_keys\n",
"\n",
"def get_dicom_from_s3(dicom_bucket, dicom_key):\n",
" # retrieve and load the dicom file\n",
" with tempfile.TemporaryFile() as tmpf:\n",
" S3_RESOURCE.Bucket(dicom_bucket).download_fileobj(dicom_key, tmpf)\n",
" tmpf.seek(0)\n",
" dcm = pydicom.dcmread(tmpf)\n",
" return dcm\n",
" \n",
"def show_dicom(dcm):\n",
" # render a dicom using matplotlib\n",
" if len(dcm.pixel_array.shape) == 3:\n",
" pixels = dcm.pixel_array.sum(axis=0)\n",
" else:\n",
" pixels = dcm.pixel_array\n",
" \n",
" plt.figure(figsize=(6,6), dpi=100)\n",
" plt.imshow(pixels, cmap=plt.cm.gray)"
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "fb61f361",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/1-117.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/2-118.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/3-119.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/4-120.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/5-121.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/6-122.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/7-123.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/8-124.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/9-125.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/10-126.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/11-127.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/12-128.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/13-129.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/14-130.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/15-131.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/16-132.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/17-133.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/18-134.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/19-135.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/20-136.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/21-137.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/22-138.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/23-139.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/24-140.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/25-141.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/26-142.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/27-143.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/28-144.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/29-145.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/30-146.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/31-147.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/32-148.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/33-149.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/34-150.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/35-151.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/36-152.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/37-153.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/38-154.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/39-155.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/40-156.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/41-157.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/42-158.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/43-159.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/44-160.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/45-161.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/46-162.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/47-163.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/48-164.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/49-165.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/50-166.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/51-167.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/52-168.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/53-169.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/54-170.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/55-171.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/56-172.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/57-173.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/58-174.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/59-175.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/60-176.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/61-177.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/62-178.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/63-179.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/64-180.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/65-181.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/66-182.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/67-183.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/68-184.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/69-185.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/70-186.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/71-187.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/72-188.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/73-189.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/74-190.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/75-191.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/76-192.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/77-193.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/78-194.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/79-195.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/80-196.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/81-197.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/82-198.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/83-199.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/84-200.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/85-201.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/86-202.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/87-203.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/88-204.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/89-205.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/90-206.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/91-207.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/92-208.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/93-209.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/94-210.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/95-211.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/96-212.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/97-213.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/98-214.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/99-215.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/100-216.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/101-217.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/102-218.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/103-219.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/104-220.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/105-221.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/106-222.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/107-223.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/108-224.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/109-225.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/110-226.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/111-227.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/112-228.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/113-229.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/114-230.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/115-231.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/116-232.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/117-233.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/118-234.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/119-235.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/120-236.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/121-237.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/122-238.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/123-239.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/124-240.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/125-241.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/126-242.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/127-243.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/128-244.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/129-245.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/130-246.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/131-247.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/132-248.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/133-249.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/134-250.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/135-251.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/136-252.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/137-253.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/138-254.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/139-255.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/140-256.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/141-257.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/142-258.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/143-259.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/144-260.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/145-261.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/146-262.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/147-263.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/148-264.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/149-265.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/150-266.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/151-267.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/152-268.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/153-269.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/154-270.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/155-271.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/156-272.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/157-273.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/158-274.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/159-275.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/160-276.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/161-277.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/162-278.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/163-279.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/164-280.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/165-281.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/166-282.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/167-283.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/168-284.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/169-285.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/170-286.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/171-287.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/172-288.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/173-289.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/174-290.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/175-291.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/176-292.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/177-293.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/178-294.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/179-295.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/180-296.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/181-297.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/182-298.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/183-299.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/184-000.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/185-001.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/186-002.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/187-003.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/188-004.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/189-005.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/190-006.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/191-007.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/192-008.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/193-009.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/194-010.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/195-011.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/196-012.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/197-013.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/198-014.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/199-015.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/200-016.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/201-017.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/202-018.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/203-019.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/204-020.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/205-021.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/206-022.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/207-023.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n",
"Writing DICOM object: tcia-images/1.3.6.1.4.1.14519.5.2.1.3983.9002.224322675112552870107739342981/208-024.dcm to bucket: genomicsanalysis-pipeline-datalakebucket-tvpzhmu7lrij\n"
]
}
],
"source": [
"dicom_keys = get_image_stream_unzip(res_all_img_study['series_uid'][0])"
]
},
{
"cell_type": "code",
"execution_count": 15,
"id": "ce81e0e6",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 600x600 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"show_dicom(get_dicom_from_s3(data_lake_bucket, dicom_keys[len(dicom_keys)//2]))"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3.9.6 64-bit",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
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