get_volumes.py

#!/usr/bin/env python
# -*- coding: utf-8 -*-

import os
import argparse
import json
from glob import glob
import csv

def get_quantification_value(quantDict, roi, side, type):
    try:
        return quantDict[roi]['total'][side][type]
    except:
        return -1

def volumes(databasePath, output):
    centers = [elt for elt in os.listdir(os.path.join(databasePath))
               if os.path.isdir(os.path.join(databasePath, elt))]
    cw = csv.writer(open(output, 'w'))
    row = [ 'CENTER', 'SUBJECT_NAME', 'SUBJECT_AGE', 'MRITIMEPOINT', 'MRIEXAMDATE',
            'WHOLE_BRAIN_ML', 'WHOLE_BRAIN_ICV',
            'GREY_MATTER_ML', 'GREY_MATTER_ICV',
            'WHITE_MATTER_ML', 'WHITE_MATTER_ICV',
            'HIPPOCAMPUS_ML', 'HIPPOCAMPUS_ICV',
            'RIGHT_HIPPOCAMPUS_ML', 'RIGHT_HIPPOCAMPUS_ICV',
            'LEFT_HIPPOCAMPUS_ML', 'LEFT_HIPPOCAMPUS_ICV',
            'AMYGDALA_ML', 'AMYGDALA_ICV',
            'RIGHT_AMYGDALA_ML', 'RIGHT_AMYGDALA_ICV',
            'LEFT_AMYGDALA_ML', 'LEFT_AMYGDALA_ICV',
            'WMH_ML', 'WMH_ICV',
        ]
    cw.writerow(row)
    for center in centers:
        print('Center', center)
        centerPath = os.path.join(databasePath, center)
        subjects = [elt for elt in os.listdir(centerPath)
                    if os.path.isdir(os.path.join(databasePath, center, elt))]
        for i, subject in enumerate(subjects):
            timepoints = sorted([elt for elt in os.listdir(os.path.join(centerPath, subject, 't1mri'))
                                 if os.path.isdir(os.path.join(databasePath, center, subject, 't1mri', elt))])

            for j, acq in enumerate(timepoints):
                print('Timepoint', acq)
                name = subject
                age = None
                tp = 'M000' if j == 0 else 'M024'
                date = acq
                wbml = None
                wbicv = None
                gmml = None
                gmicv = None
                wmml = None
                wmicv = None
                hml = None
                hicv = None
                rhml = None
                rhicv = None
                lhml = None
                lhicv = None
                aml = None
                aicv = None
                raml = None
                raicv = None
                laml = None
                laicv = None
                wmhml = None
                wmhicv = None
    
                brainVolumes = \
                    glob(os.path.join(databasePath, center, subject, 'results', acq, \
                                    '*', 'quantification*json'))
                clinical = \
                    glob(os.path.join(databasePath, center, subject, 'clinical', acq, \
                                    'json', 'clini*json'))

                with open(brainVolumes[0], 'r') as fd:
                    quantJson = json.load(fd)
                    wbml = get_quantification_value(quantJson, 'Whole Brain', 'Both', 'volume_ml')
                    wbicv = get_quantification_value(quantJson, 'Whole Brain', 'Both', 'volume_icv')
                    gmml = get_quantification_value(quantJson, 'Grey Matter', 'Both', 'volume_ml')
                    gmicv = get_quantification_value(quantJson, 'Grey Matter', 'Both', 'volume_icv')
                    wmml = get_quantification_value(quantJson, 'White Matter', 'Both', 'volume_ml')
                    wmicv = get_quantification_value(quantJson, 'White Matter', 'Both', 'volume_icv')
                    hml = get_quantification_value(quantJson, 'Hippocampus', 'Both', 'volume_ml')
                    hicv = get_quantification_value(quantJson, 'Hippocampus', 'Both', 'volume_icv')
                    rhml = get_quantification_value(quantJson, 'Hippocampus', 'Right', 'volume_ml')
                    rhicv = get_quantification_value(quantJson, 'Hippocampus', 'Right', 'volume_icv')
                    lhml = get_quantification_value(quantJson, 'Hippocampus', 'Left', 'volume_ml')
                    lhicv = get_quantification_value(quantJson, 'Hippocampus', 'Left', 'volume_icv')
                    aml = get_quantification_value(quantJson, 'Amygdala', 'Both', 'volume_ml')
                    aicv = get_quantification_value(quantJson, 'Amygdala', 'Both', 'volume_icv')
                    raml = get_quantification_value(quantJson, 'Amygdala', 'Right', 'volume_ml')
                    raicv = get_quantification_value(quantJson, 'Amygdala', 'Right', 'volume_icv')
                    laml = get_quantification_value(quantJson, 'Amygdala', 'Left', 'volume_ml')
                    laicv = get_quantification_value(quantJson, 'Amygdala', 'Left', 'volume_icv')
                    wmhml = get_quantification_value(quantJson, 'WMH', 'Both', 'volume_ml')
                    wmhicv = get_quantification_value(quantJson, 'WMH', 'Both', 'volume_icv')
 
                with open(clinical[0], 'r') as pd:
                    js = json.load(pd)
                    age = float(js['subject']['subject_age'])

                row = [center, name, age, tp, date, \
                    wbml, wbicv, gmml, gmicv, wmml, wmicv, hml, hicv, \
                    rhml, rhicv, lhml, lhicv, aml, aicv, raml, raicv, laml, laicv, wmhml, wmhicv]

                if not any(x is None for x in row):
                    cw.writerow(row)


                


if __name__ == '__main__':

    descriptionMsg = \
        '''Compute Brain Volumes on subjects of given center of given db.'''
    parser = argparse.ArgumentParser(description=descriptionMsg)

    parser.add_argument('-d', '--database',
                        help='database path')
    parser.add_argument('-o', '--output',
                        help='output CSV')
    args = parser.parse_args()

    databasePath = args.database
    outputCsv = args.output

    volumes(databasePath, outputCsv)