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GE ISTHMUS/Hyper Sequence (#137)
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* Update ge_pfile.py

* Update ge_read_pfile.py

* Update "Dim_"

Updated functionality to correctly handle "Dim_" across each sub experiment.

* Hyper Echo Time for Long TE

Added Hyper Echo Time for Long TE

* Update twix_special_case.py

* Update twix_special_case.py

* GE ISTHMUS/Hyper Sequence

Adding functionality to handle GE ISTHMUS/Hyper data. A new custom (_process_hbcd) function for handling the data has been added to the ge_pfile.py. I've also included version 30.x into the get_hdr_fields.py.

* Update ge_hdr_fields.py

Remove added line

* Fix linting, line 349 still has undefined variables on.

* Fix up leftover strings from twix special handling

---------

Co-authored-by: William T Clarke <[email protected]>
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@agudmundson @wtclarke
agudmundson and wtclarke authored Jul 3, 2024
1 parent 7c284c8 commit b5459cb
Showing 1 changed file with 139 additions and 0 deletions.
139 changes: 139 additions & 0 deletions spec2nii/GE/ge_pfile.py
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Original file line number Diff line number Diff line change
Expand Up @@ -107,6 +107,8 @@ def _process_svs_pfile(pfile):
data, meta, dwelltime, fname_suffix = _process_slaser(pfile)
elif psd in ('jpress', 'jpress_ac', 'gaba', 'hbcd', 'probe-p-mega_rml', 'repress7'):
data, meta, dwelltime, fname_suffix = _process_gaba(pfile)
elif psd in ('hbcd'): # ATG
data, meta, dwelltime, fname_suffix = _process_hbcd(pfile) # ATG
else:
raise UnsupportedPulseSequenceError(f'Unrecognised sequence {psd}.')

Expand Down Expand Up @@ -271,6 +273,143 @@ def _process_gaba(pfile):
return [metab, water], [meta, meta_ref], dwelltime, ['', '_ref']


def _process_hbcd(pfile):
"""
Input:
Pfile Object
Output:
List of NumPy Data Arrays
List of File Name Suffixes
Details:
Hyper/ISTHMUS Sequence
The Integrated Short-TE and Hadamard-edited Multi-Sequence (ISTHMUS)
incorporates a Short TE (35ms) PRESS, Long-TE (80ms) HERCULES, and
a water reference for each.
Data is organized within the file as follows:
( 1) Long TE Reference : 80ms Unsupressed Water
(32) Long TE Edited : 80ms Water Suppressed HERCULES
( 1) Short TE Reference : 35ms Unsupressed Water
(32) Short TE Unedited : 35ms Water Suppressed PRESS
( 1) Long TE Reference : 80ms Unsupressed Water
(32) Short TE Unedited : 35ms Water Suppressed PRESS
( 1) Short TE Reference : 35ms Unsupressed Water
(32) Short TE Unedited : 35ms Water Suppressed PRESS
( 1) Long TE Reference : 80ms Unsupressed Water
(32) Short TE Unedited : 35ms Water Suppressed PRESS
( 1) Short TE Reference : 35ms Unsupressed Water
(32) Short TE Unedited : 35ms Water Suppressed PRESS
( 1) Long TE Reference : 80ms Unsupressed Water
(32) Short TE Unedited : 35ms Water Suppressed PRESS
( 1) Short TE Reference : 35ms Unsupressed Water
(32) Short TE Unedited : 35ms Water Suppressed PRESS
Data is directly separated from the raw data (pfile.map.raw_data) where the data
mapper (GABA mapper) is simply used to populate in the raw data.
Author : Aaron Gudmundson, Johns Hopkins University, 2024
Contact: [email protected]
"""

# Additional Imports
import copy

# Editing Parameters
edit_cases = 4 # 4 Editing Conditions
edit_pulse_1 = 4.58 # 4.58 ppm
edit_pulse_2 = 1.90 # 1.90 ppm
edit_pulse_4 = 4.18 # 4.18 ppm
pulse_length = 0.02 # Edit Pulse 20 ms

dim_header = {'EditCondition': ['A', 'B', 'C', 'D']} # 4 Subscans
edit_pulse_val = {'A': {'PulseOffset': [edit_pulse_1, edit_pulse_2], 'PulseDuration': pulse_length},
'B': {'PulseOffset': [edit_pulse_4, edit_pulse_2], 'PulseDuration': pulse_length},
'C': {'PulseOffset': edit_pulse_1, 'PulseDuration': pulse_length},
'D': {'PulseOffset': edit_pulse_4, 'PulseDuration': pulse_length}}

# All Data (Skip 1st Transient - GE automatically has historically included a 'noise' transient)
raw_data = pfile.map.raw_data[:, :, :, :, 1:, :] # Raw Data from Mapper

# Long TE HERCULES Metabolite Data
lTE_metab = copy.deepcopy(raw_data) # Long TE Metab
lTE_mask = np.ones(lTE_metab.shape[4], dtype=bool) # Create a Mask
lTE_mask[::33] = False # Remove Water Refs
lTE_mask[: 33] = False # Remove PRESS
lTE_metab = lTE_metab[:, :, :, :, lTE_mask, :] # Isolated HERCULES

# Handle Incomplete
if lTE_mask.shape[-1] % 4 != 0: # Incomplete Acquisition
old_num_avgs = lTE_mask.shape[-1] # Old Total Averages
new_num_avgs = (lTE_mask.shape[-1] // 4) * 4 # New Total Averages
lTE_metab = lTE_metab[:, :, :, :, :new_num_avgs, :] # Remove Incomplete

notestring = '80ms HERCULES' # Note Incomplete Data
notestring = f'{notestring} - Correcting - Incomplete Averages' # Note Incomplete Data
notestring = f'{notestring} {old_num_avgs} --> {new_num_avgs}' # Note Incomplete Data
print(f'{notestring} \t Corrected**') # Note Incomplete Data

bef_shape = list(lTE_metab.shape) # Remove Averages Dim
bef_shape[4] = bef_shape[4] // 4 # Closest multiple of 4
bef_shape.append(edit_cases) # Include Subscans
lTE_metab = lTE_metab.reshape(bef_shape) # With Subscan Dim

lTE_metab_meta = _populate_metadata(pfile, water_suppressed=True) # Acquisition Information
lTE_metab_meta.set_standard_def('EchoTime', 0.080) # TE
lTE_metab_meta.set_standard_def('WaterSuppressed', True) # Water Suppression
lTE_metab_meta.set_standard_def('EditPulse', edit_pulse_val) # Header Edit Info

lTE_metab_meta.set_dim_info(0, 'DIM_DYN') # Dimension Info
lTE_metab_meta.set_dim_info(1, 'DIM_COIL') # Dimension Info
lTE_metab_meta.set_dim_info(2, 'DIM_EDIT', hdr=dim_header) # Dimension Info

# Short TE HERCULES Metabolite Data
sTE_metab = copy.deepcopy(raw_data[:, :, :, :, 1:33, :])

sTE_metab_meta = _populate_metadata(pfile, water_suppressed=True) # Acquisition Information
sTE_metab_meta.set_standard_def('EchoTime', 0.035) # TE
sTE_metab_meta.set_standard_def('WaterSuppressed', True) # Water Suppression

sTE_metab_meta.set_dim_info(0, 'DIM_DYN') # Dimension Info
sTE_metab_meta.set_dim_info(1, 'DIM_COIL') # Dimension Info

# Long TE Reference Water Data
lTE_water = copy.deepcopy(raw_data[:, :, :, :, 0::66, :])

lTE_water_meta = _populate_metadata(pfile, water_suppressed=False) # Acquisition Information
lTE_water_meta.set_standard_def('EchoTime', 0.080) # TE
lTE_water_meta.set_standard_def('WaterSuppressed', False) # Water Suppression

lTE_water_meta.set_dim_info(0, 'DIM_DYN') # Dimension Info
lTE_water_meta.set_dim_info(1, 'DIM_COIL') # Dimension Info

# Short TE Reference Water Data
sTE_water = copy.deepcopy(raw_data[:, :, :, :, 33::66, :])

sTE_water_meta = _populate_metadata(pfile, water_suppressed=False) # Acquisition Information
sTE_water_meta.set_standard_def('EchoTime', 0.035) # TE
sTE_water_meta.set_standard_def('WaterSuppressed', False) # Water Suppression

sTE_water_meta.set_dim_info(0, 'DIM_DYN') # Dimension Info
sTE_water_meta.set_dim_info(1, 'DIM_COIL') # Dimension Info

# Dwell Time
dwelltime = 1 / pfile.hdr.rhr_spectral_width

data = [lTE_metab, sTE_metab, lTE_water, sTE_water] # ISTHMUS Data
meta = [lTE_metab_meta, sTE_metab_meta, lTE_water_meta, sTE_water_meta] # ISTHMUS Header
ref_names = ['_edited', '_short_te', '_ref_edited', '_ref_short_te'] # ISTHMUS Naming

print('Returning ISTHMUS Data:')
for ii in range(len(data)):
print(' {:02d} {:<14} '.format(ii, ref_names[ii]), data[ii].shape)
print(' ')

return data, meta, dwelltime, ref_names


def _process_mrsi_pfile(pfile):
"""Handle MRSI data
Expand Down

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