DOI: 10.5061/dryad.37pvmcvm0
title: Phase-contrast MRI data of 18 Chiari-I malformation patients and 21 controls

description: We collected phase-contrast MRI data (5-mm midline sagittal section,
 rostro-caudal direction) and obtained average velocity in certain
 Regions-0f-Interest (ROIs). The measured ROIs are cerebellar tonsil,
 ventral spinal subarachnoid space, dorsal spinal subarachnoid space, upper
 portion of syrinxes, upper cervical cord, and medulla. Data obtained from
 18 Chiari-I patients (preoperative and postoperative) and 21 controls are
 included. Because the preoperative MRI data was missing in one patient,
 the preoperative studies included 17 MRI sessions. The unit of the data is
 cm/sec. The data are synchronized with pre-processing so that the rise of
 the caudal CSF movement be placed at the center of the cardiac cycle.
description: We performed phase-contrast MRI on 18 patients with Chiari-I
 malformationc(associated with syringomyelia) and 21 controls. The MRI on
 the patientscwas taken before andcafter surgery (foramen magnum
 decompression). Phase-contrast MRI was takn on the
 midline sagittal section with 5-mmcthickness. The movement in the FH
 (foot-head) direction was encoded withcvelocity encoding (VENC) of 10
 cm/sec. On the data of each MRI session, six regions of
 interest (ROIs) were placed; namely, cerebellar tonsil (tonsil), ventral
 subarachnoid space just below the foramen magnum (sa), dorsal subarachnoid
 space just below the foramen magnum (cm), the upper portion of the syrinx
 (syrinx), the cord segment between the fouth ventricle and the syrinx
 (cord), the medulla (medulla). The average flow speed inside each ROI was
 measured at each time point in the cardiac cycle. The
 acquired data were synchronized with post-processing so that the maximal
 caudal velocity of 'sa' will be at the center of the data of 50
 bins encompassing a cardiac cycle.
description: The data file is a json-format dump of a python object. Because
 the original python object contained numpy array, we had to encode the
 object into the one with normal python lists. To restore the original
 python object, please use the function 'decode_'.
 The file '57.mp4' is the movie of phase-contrast MRI of
 the session No. 57, which is a preoperative session of a Chiari-I patient.
 The data is shown with color coding with the rostral velocity encoded in
 yellow and the caudal velocity encoded in dark blue. This movie shows the
 paradoxical upward movement of the upper spinal cord during the phase
 where the CSF in the subarachnoid space is moving downward.
 The 'encoded_data.json' file contains all the data of
 the MRI sessions processed as above. This file is was created by dumping a
 python object containing all the data using the 'json' module of
 python version 3. It can be imported to restore the original python object
 using the 'json' module as follows. A function in the
 'analyze.py' (decode_data()) is needed for this
 restoration. ---------------python
 code----------------<br> import json<br> with
 open('encoded_data.json', 'rt') as f:<br>    
 encoded_data = json.load(f)<br>     datafile =
 decode_data(encoded_data)<br>
 ------------------------------------------ # Usage of
 analyze.py The 'datafile' is a python
 dictionary with the keys indicating the MRI<br> session
 number. Various functions to manupulate this data file
 are provided in<br> 'analyze.py'. To
 obtain the list of session_id of preoperative studies.<br>
 syrinx_sessions_raw()<br> which gives the list [1, 5, 9, 14, 24, 28,
 36, 41, 45, 52, 55, 57, 60, 62, 68, 80, 81] To obtain
 the list of session_id of control studies.<br>
 control_sessions_raw()<br> which gives the list [70, 71, 72, 73, 74,
 75, 76, 77, 78, 79, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93]
 To obtain the list of session_id of postoperative
 studies.<br> postop_sessions()<br> which gives the list [4, 8,
 13, 16, 23, 35, 40, 44, 47, 51, 54, 56, 59, 66, 67, 69, 82, 94]
 The correspondence between the preoperative session_id and the
 postoperative sesion_id in a same patient is given below.
 [[1,4], [5,8], [9,13], [14,16], [24,51], [28,35], [36,40],
 [41,44], [45,47], [52,54], [55,56], [57,59], [60,69], [62,66], [68,94],
 [80,67], [81,82]] The figures in the article were
 created using the functions<br> 'draw_mean_graph()' and
 'draw_two_locations_with CI()'.