MP2RAGE in BIDS

gudapatis · January 22, 2024, 8:59pm

Hello,

I have a dataset consisting of 7T MP2RAGE scans, and I’m encountering two challenges that I need assistance with:

Many subjects have multiple runs, each generating T1map, UNI-DEN, UNI, INV2 scans. The problem is that there are more than one nifti-json pair associated with each type, and the only differing fields in the JSON files are StationName, AcquisitionTime, and SAR. The NIFTIs themselves appear similar except for the orientation, where the “duplicates” are usually tilted at an angle. How should I appropriately name these files to avoid confusion?
In general, how should I name the MP2RAGE outputs? I’ve noticed that there are no INV1 scans. Could this absence be a potential issue?

I appreciate any guidance or suggestions you can provide on these matters. Thank you!

Steven · January 22, 2024, 9:24pm

Hi @gudapatis and welcome to neurostars!

Have you consulted the BIDS specification? Quantitative MRI - Brain Imaging Data Structure v1.9.0

Best,
Steven

gudapatis · January 23, 2024, 1:34am

Hi @Steven ,

I’ve reviewed the information, and I have a few questions:

The first question I had remains unanswered.
Could you guide me on locating the label for “part”?
Regarding the naming convention, should the UNI-DEN images be labeled as T1w, and only the UNI scans named as UNIT1?

Appreciate all your help!

Thank you!

Steven · January 23, 2024, 2:04am

Hi @gudapatis,

You can use the run-<> label.

What are the nature of each nifti-json pair? If they are off-the-scanner reconstructions, you can use the rec-<> label to differentiate. If different acquisition types, the acq-<> label.

I haven’t worked with these file types, perhaps it’s in the JSON somewhere?

I wish I knew more about qMRI to guide you here, but I don’t know. Perhaps you can look at BIDS examples with qMRI such as https://github.com/bids-standard/bids-examples/tree/eff47f104210a142a71abd058417fc91a82ba95a/qmri_mp2rageme (there are others there too if you search for qmri) for more help.

Best,
Steven

jsein · January 23, 2024, 7:34am

Welcome to Neurostars!

The MP2RAGE sequence consists in the acquisition of two images, namely INV1 and INV2, that differs in TI, TR and flip angle. All the other parameters are the same and so is the orientation. The T1map, UNI-DEN and UNI images are all derived from these two images. It is a bit strange that the INV1 one does not appear in your dataset, either it was not saved after the acquisition, or it was not converted in NIFTI.

You can get more details in those papers:

original implementation of MP2RAGE: Marques, J.; Kober, T.; Krueger, G.; van der Zwaag, W.; Van de Moortele, P.; Gruetter, R. MP2RAGE, a Self Bias-Field Corrected Sequence for Improved Segmentation and T1-Mapping at High Field. NeuroImage 2010, 49(19819338), 1271–1281. Redirecting.
One way to reconstruct the UNI-DEN image (image without the salt and pepper background): O’Brien, K. R.; Kober, T.; Hagmann, P.; Maeder, P.; Marques, J.; Lazeyras, F.; Krueger, G.; Roche, A. Robust T1-Weighted Structural Brain Imaging and Morphometry at 7T Using MP2RAGE. PLoS ONE 2014, 9 (6), e99676. Robust T1-Weighted Structural Brain Imaging and Morphometry at 7T Using MP2RAGE.

Yes, I would do that, you can add the label _acq-MP2RAGE_rec_UNIDEN for instance. I would put those sub-SUB_ses-SES_acq-MP2RAGE_rec-UNIDEN_run-RUN_T1w images in the input BIDS_DIR/sub-SUB/ses-SES/anat folder so that BIDSApps such as fmriprep find those T1w images right away for preprocessing.

Remi-Gau · January 23, 2024, 12:27pm

Link to the mp2rage bids example: https://github.com/bids-standard/bids-examples/tree/eff47f104210a142a71abd058417fc91a82ba95a/qmri_mp2rage

Remi-Gau · January 23, 2024, 1:24pm

I agree that the lack of INV1 output is a bit strange.

Regarding the label for the part entity you should be able to figure it out from looking at the images themselves. In most cases they will be magnitude images.

examples for some inv2 images:

magnitude

phase

gudapatis · January 23, 2024, 4:42pm

Thank you for your responses! @Steven @Remi-Gau @jsein
I still have some confusion regarding the presence of multiple NIfTI-JSON pairs for the same type of image within a single session (the only differing fields in the JSON files that belong to the same rec are StationName, AcquisitionTime, and SAR.). I’ve included an example of the dataset structure below for better understanding. Additionally, I’m assuming that distinct series are associated with different runs.

- sub-1234
    - ses-01
        - anat
            - Series_005_[MR_-_tfl_wip944_b17stx_NEW_MP2RAGE_T1_Images]_tf1_wip944_b17st_NEW_MP2RAGE_T1_Images_19700101000000_5.json
            - Series_005_[MR_-_ _tfl_wip944_b17stx_NEW_MP2RAGE_T1_Images]_tfl_wip944_b17stx_NEW_MP2RAGE_T1_Images_19700101000000_5.nii.gz
            - Series_005_[MR_-_tfl_wip944_b17stx_NEW_MP2RAGE_T1_Images]_tfl_wip944_b17stx_NEW_MP2RAGE_T1_Images_20000101000000_5.json
            - Series_005_[MR_-_tf1_wip944_b17stx_NEW_MP2RAGE_T1_Images]_tfl_wip944_b17stx_NEW_MP2RAGE_T1_Images_20000101000000_5.nii.gz
            - Series_006_[MR_-_tf1_wip944_b17stx_NEW_MP2RAGE_UNI_DEN]_tfl_wip944_b17stx_NEW_MP2RAGE_UNI-DEN_19700101000000_6.json
            - Series_006_[MR_-_tfl_wip944_b17stx_NEW_MP2RAGE_UNI_DEN]_tf1_wip944_b17stx_NEW_MP2RAGE_UNI-DEN_19700101000000_6.nii.gz 
            - Series_006_[MR_-_tfl_wip944_b17stx_NEW_MP2RAGE_UNI_DEN]_tf1_wip944_b17stx_NEW_MP2RAGE_UNI-DEN_20000101000000_6.json
            - Series_006_[MR_-_tfl_wip944_b17stx_NEW_MP2RAGE_UNI_DEN]_tf1_wip944_b17st_NEW_MP2RAGE_UNI-DEN_20000101000000_6.nii.gz 
            - Series_007_[MR_-_tfl_wip944_b17stx_NEW_MP2RAGE_UNI_DEN]_tfl_wip944_b17stx_NEW_MP2RAGE_UNI-DEN_19700101000000_7.json
            - Series_007_[MR_-_tf1_wip944_b17stx_NEW_MP2RAGE_UNI_DEN]_tf1_wip944_b17stx_NEW_MP2RAGE_UNI-DEN_19700101000000_7.nii.gz
            - Series_007_[MR_-_tf1_wip944_b17stx_NEW_MP2RAGE_UNI_Images]_tf1_wip944_b17stX_NEW_MP2RAGE_UNI_Images_19700101000000_7.json
            - Series_007_[MR_-_ _tf1_wip944_b17stx_NEW_MP2RAGE_UNI_Images]_tf1_wip944_b17stx_NEW_MP2RAGE_UNI_Images_19700101000000_7.nii.gz
            - Series_008_[MR_-_ Series_008_[MR_-_tfl_wip944_b17stx_NEW_MP2RAGE_INV2]_tf1_wip944_b17stx_NEW_MP2RAGE_INV2_19700101000000_8.json 
            - Series_008_[MR_-_ Series_008_[MR_-_tfl_wip944_b17stx_NEW_MP2RAGE_INV2]_tf1_wip944_b17stx_NEW_MP2RAGE_INV2_19700101000000_8.nii.gz
            - Series_008_[MR_-_ _tf1_wip944_b17stx_NEW_MP2RAGE_INV2]_tfl_wip944_b17stx_NEW_MP2RAGE_INV2_20000101000000_8.json
            - Series_008_[MR_-_tf1_wip944_b17stx_NEW_MP2RAGE_INV2]_tfl_wip944_b17stx_NEW_MP2RAGE_INV2_20000101000000_8.nii.gz
            - Series_008_[MR_-_tf1_wip944_b17stx_NEW_MP2RAGE_UNI_Images]_tfl_wip944_b17stx_NEW_MP2RAGE_UNI_Images_19700101000000_8.json
            - Series_008_[MR_-_tfl_wip944_b17stx_NEW_MP2RAGE_UNI_Images]_tfl_wip944_b17stx_NEW_MP2RAGE_UNI_Images_19700101000000_8.nii.gz
            - Series_009_[MR_-_tfl_wip944_b17stx_NEW_MP2RAGE_INV2]_tfl_wip944_b17stx_NEW_MP2RAGE_INV2_19700101000000_9.json
            - Series_009_[MR_-_tf1_wip944_b17stx_NEW_MP2RAGE_INV2]_tf1_wip944_b17stx_NEW_MP2RAGE_INV2_19700101000000_9.nii.gz

Steven · January 23, 2024, 4:44pm

Hi @gudapatis,

Hard to say for sure without seeing example JSON outputs to compare. May you please share, for example, the contents of the first two JSONs on that list?

Best,
Steven

gudapatis · January 23, 2024, 5:24pm

Sure @Steven
Series_005_[MR_-_tfl_wip944_b17stx_NEW_MP2RAGE_T1_Images]_tf1_wip944_b17st_NEW_MP2RAGE_T1_Images_19700101000000_5.json :

{"Modality": "MR",
"MagneticFieldStrength": 6.98,
"ImagingFrequency": 297.217,
"Manufacturer": "Siemens",
"ManufacturersModelName": "DicomCleaner",
"DeviceSerialNumber": "18973",
"StationName": "PSYCH15-015_1111",
"PatientPosition": "HFS",
"SoftwareVersions": "Thu Oct 18 06:41:18 EDT 2018",
"MRAcquisitionType": "3D",
"SeriesDescription": "fl_wip944_b17stx_NEW_MP2RAGE_T1_Images",
"ProtocolName": "tfl_wip944_b17stx_NEW_MP2RAGE_T1_Images",
"ScanningSequence"; "GR\\IR",
"SequenceVariant"; "SP\\MP",
"Scanoptions": "IR\\PFP",
"SequenceName": "tfl3d1rs",
"ImageType": ["ORIGINAL", "PRIMARY", "T1 MAP", "ND"],
"SeriesNumber": 5,
"AcquisitionTime": "00:16:7.639000",
"AcquisitionNumber": 1,
"SliceThickness": 0.5,
"SAR": 0.0762767,
"EchoTime": 0.00575,
"RepetitionTime": 5,
"PercentPhaseFOV": 90.2222,
"PercentSampling": 100,
"PhaseEncodingSteps": 305,
"AcquisitionMatrixPE": 406,
"ReconMatrixPE": 406,
"PixelBandwidth": 171,
"ImageOrientationPatientDICOM": [
1,
0,
0,
0,
1,
0	],
"InPlanePhaseEncodingDirectionDICOM": "COL",
"ConversionSoftware": "dcm2niix",
"ConversionSoftwareVersion": "v1.0.20211006"}

Series_005_[MR_-_tfl_wip944_b17stx_NEW_MP2RAGE_T1_Images]_tfl_wip944_b17stx_NEW_MP2RAGE_T1_Images_20000101000000_5.json :

{ "Modality": "MR",
"MagneticFieldstrength": 6.98,
"ImagingFrequency": 297.216,
"Manufacturer": "Siemens"
"ManufacturersModelName": "DicomCleaner",
"DeviceSerialNumber": "18973",
"StationName": "W20660D59YW052_1",
"PatientPosition": "HFS",
"SoftwareVersions": "Thu Oct 18 06:41:18 EDT 2018",
"MRAcquisitionType": "3D",
"SeriesDescription": "tfl_wip944_b17stx_NEW_MP2RAGE_T1_Images",
"ProtocolName": "tfl_wip944_b17stx_NEW_MP2RAGE_T1_Images",
"ScanningSequence": "GR\\IR".
"SequenceVariant": "SP\\MP",
"ScanOptions": "IR\\PFP",
"SequenceName": "tfl3d1rs"
"ImageType": ["ORIGINAL”, “PRIMARY", "T1 MAP", "ND"],
"SeriesNumber": 5,
"AcquisitionTime": "00:25:30.144000",
"AcquisitionNumber": 1,
"SliceThickness": 0.5,
"SAR": 0.0705607,
"EchoTime": 0.00575,
"RepetitionTime": 5,
"PercentPhaseFOV": 90.2222,
"PercentSampling": 100,
"PhaseEncodingSteps": 305,
"AcquisitionMatrixPE": 406,
"ReconMatrixPE": 406,
"PixelBandwidth": 171,
"ImageorientationPatientDICOM": [
1,
0,
0,
0,
0.981293,
-0.192522 ],
"InPlanePhaseEncodingDirectionDICOM": "COL",
"ConversionSoftware": "dcm2niix",
"ConversionSoftwareVersion": "v1.0.20211006"}

jsein · January 23, 2024, 10:11pm

Thank you for sharing. Hum difficult to understand why you get all these files at first sight.

What we can see:

This is a WIP (work-in-progress) Siemens MRI sequence, meaning that the MRI operator get much more options for parametrizing this kind sequence and also more options for generating output images.
From these two json files, it looks like this two images could come from two runs of a MP2RAGE sequence ( see the difference in AcquisitionTime and also in SAR).
But those images have the same SeriesNumber which tends to contradict what I just wrote…

It would be useful to look at DICOM folders that you got from the scanner and also if possibly you had a PDF printout of the MRI protocol from the scanner. You could see from the sequence directly which choices were made to save output images.

I have another question: how were generated these NIFTI/JSON files? Which software was used? dcm2niix?

gudapatis · January 23, 2024, 10:50pm

Thanks @jsein! Seems like we do not have the PDF printout of the MRI protocol from the scanner. I’ve used dcm2niix to generate the NIFTI/JSONs : dcm2niix -z y -m y -o $OUTDIR $INDIR. I’ve also tried it without -m and it produces a similar output.

jsein · January 23, 2024, 11:10pm

ok!
Well my gut feeling for now is that there where two runs from the same MP2RAGE sequence that were launched, each of them producing:

one INV2 image
one UNI image (with black and pepper background)
one T1map image
one UNIDEN image (like UNI but with black and pepper background removed)

The INV1 is missing, it had to be acquired by the sequence to be able to reconstruct the UNI and T1map images but perhaps it was unchecked from the list of outputs in the sequence and was not saved.

gudapatis · January 24, 2024, 7:43pm

Thanks @jsein! So the above example would look something like this?

Series_005_XXX_T1_Images_19700101000000_5.nii.gz -> run-01_T1map
Series_005_XXX_T1_Images_20000101000000_5.nii.gz -> run-02_T1map
Series_006_XXX_UNI-DEN_19700101000000_6.nii.gz -> run-03_T1w
Series_006_XXX_UNI-DEN_20000101000000_6.json - > run-04_T1w
Series_007_XXX_UNI-DEN_19700101000000_7.nii.gz -> run-05_T1w
Series_007_XXX_UNI_Images_19700101000000_7.nii.gz -> run-05_UNIT1
Series_008_XXX_INV2_19700101000000_8.nii.gz -> run-06_inv-02
Series_008_XXX_INV2_20000101000000_8.nii.gz -> run-07_inv-02
Series_008_XXX_UNI_Images_19700101000000_8.nii.gz -> run-06_UNIT1
Series_009_XXX_INV2_19700101000000_9.nii.gz -> run-08_inv-2

jsein · January 24, 2024, 9:58pm

I would rather do:

Series_005_XXX_T1_Images_19700101000000_5.nii.gz -> run-01_T1map.nii.gz
Series_005_XXX_T1_Images_20000101000000_5.nii.gz -> run-02_T1map.nii.gz
Series_006_XXX_UNI-DEN_19700101000000_6.nii.gz -> run-01_T1w.nii.gz
Series_006_XXX_UNI-DEN_20000101000000_6.json - > run-02_T1w.json
Series_007_XXX_UNI-DEN_19700101000000_7.nii.gz -> run-01_T1w.nii.gz
Series_007_XXX_UNI_Images_19700101000000_7.nii.gz -> run-01_UNIT1.nii.gz
Series_008_XXX_INV2_19700101000000_8.nii.gz -> run-01_inv-2_MP2RAGE.nii.gz
Series_008_XXX_INV2_20000101000000_8.nii.gz -> run-02_inv-2_MP2RAGE.nii.gz
Series_008_XXX_UNI_Images_19700101000000_8.nii.gz -> run-01_UNIT1.nii.gz --> not sure about this one, perhaps a phase image?
Series_009_XXX_INV2_19700101000000_9.nii.gz -> run-01_inv-2_MP2RAGE.nii.gz --> not sure of this one , perhaps the phase image?

Could you share the content of :

Series_008_[MR_-_ Series_008_[MR_-_tfl_wip944_b17stx_NEW_MP2RAGE_INV2]_tf1_wip944_b17stx_NEW_MP2RAGE_INV2_19700101000000_8.json
and:
Series_009_[MR_-_tfl_wip944_b17stx_NEW_MP2RAGE_INV2]_tfl_wip944_b17stx_NEW_MP2RAGE_INV2_19700101000000_9.json ?

and also:

Series_007_[MR_-_tf1_wip944_b17stx_NEW_MP2RAGE_UNI_Images]_tf1_wip944_b17stX_NEW_MP2RAGE_UNI_Images_19700101000000_7.json
and:
Series_008_[MR_-_tf1_wip944_b17stx_NEW_MP2RAGE_UNI_Images]_tfl_wip944_b17stx_NEW_MP2RAGE_UNI_Images_19700101000000_8.json?

gudapatis · January 25, 2024, 6:07am

Series_008_[MR_-_ Series_008_[MR_-_tfl_wip944_b17stx_NEW_MP2RAGE_INV2]_tf1_wip944_b17stx_NEW_MP2RAGE_INV2_19700101000000_8.json :

{
	"Modality": "MR",
	"MagneticFieldStrength": 6.98,
	"ImagingFrequency": 297.217,
	"Manufacturer": "Siemens",
	"ManufacturersModelName": "DicomCleaner",
	"DeviceSerialNumber": "18973",
	"StationName": "PSYCH15-015_1111",
	"PatientPosition": "HFS",
	"SoftwareVersions": "Thu Oct 18 06:41:18 EDT 2018",
	"MRAcquisitionType": "3D",
	"SeriesDescription": "tfl_wip944_b17stx_NEW_MP2RAGE_INV2",
	"ProtocolName": "tfl_wip944_b17stx_NEW_MP2RAGE_INV2",
	"ScanningSequence": "GR\\IR",
	"SequenceVariant": "SP\\MP",
	"ScanOptions": "IR\\PFP",
	"SequenceName": "tfl3d1rs",
	"ImageType": ["ORIGINAL", "PRIMARY", "M", "ND"],
	"SeriesNumber": 8,
	"AcquisitionTime": "00:16:9.527000",
	"AcquisitionNumber": 1,
	"SliceThickness": 0.5,
	"SAR": 0.0762767,
	"EchoTime": 0.00575,
	"RepetitionTime": 5,
	"InversionTime": 2.78,
	"FlipAngle": 3,
	"PercentPhaseFOV": 90.2222,
	"PercentSampling": 100,
	"PhaseEncodingSteps": 305,
	"AcquisitionMatrixPE": 406,
	"ReconMatrixPE": 406,
	"PixelBandwidth": 171,
	"ImageOrientationPatientDICOM": [
		1,
		0,
		0,
		0,
		1,
		0	],
	"InPlanePhaseEncodingDirectionDICOM": "COL",
	"ConversionSoftware": "dcm2niix",
	"ConversionSoftwareVersion": "v1.0.20211006"
}

Series_009_[MR_-_tfl_wip944_b17stx_NEW_MP2RAGE_INV2]_tfl_wip944_b17stx_NEW_MP2RAGE_INV2_19700101000000_9.json :

{
	"Modality": "MR",
	"MagneticFieldStrength": 6.98,
	"ImagingFrequency": 297.217,
	"Manufacturer": "Siemens",
	"ManufacturersModelName": "DicomCleaner",
	"DeviceSerialNumber": "18973",
	"StationName": "PSYCH15-015_1111",
	"PatientPosition": "HFS",
	"SoftwareVersions": "Thu Oct 18 06:41:18 EDT 2018",
	"MRAcquisitionType": "3D",
	"SeriesDescription": "tfl_wip944_b17stx_NEW_MP2RAGE_INV2",
	"ProtocolName": "tfl_wip944_b17stx_NEW_MP2RAGE_INV2",
	"ScanningSequence": "GR\\IR",
	"SequenceVariant": "SP\\MP",
	"ScanOptions": "IR\\PFP",
	"SequenceName": "tfl3d1rs",
	"ImageType": ["ORIGINAL", "PRIMARY", "M", "ND"],
	"SeriesNumber": 9,
	"AcquisitionTime": "00:08:14.822000",
	"AcquisitionNumber": 1,
	"SliceThickness": 0.5,
	"SAR": 0.0994492,
	"EchoTime": 0.00575,
	"RepetitionTime": 5,
	"InversionTime": 2.78,
	"FlipAngle": 3,
	"PercentPhaseFOV": 90.2222,
	"PercentSampling": 100,
	"PhaseEncodingSteps": 305,
	"AcquisitionMatrixPE": 406,
	"ReconMatrixPE": 406,
	"PixelBandwidth": 171,
	"ImageOrientationPatientDICOM": [
		1,
		0,
		0,
		0,
		0.987136,
		-0.159881	],
	"InPlanePhaseEncodingDirectionDICOM": "COL",
	"ConversionSoftware": "dcm2niix",
	"ConversionSoftwareVersion": "v1.0.20211006"
}

Series_007_[MR_-_tf1_wip944_b17stx_NEW_MP2RAGE_UNI_Images]_tf1_wip944_b17stX_NEW_MP2RAGE_UNI_Images_19700101000000_7.json :

{
	"Modality": "MR",
	"MagneticFieldStrength": 6.98,
	"ImagingFrequency": 297.217,
	"Manufacturer": "Siemens",
	"ManufacturersModelName": "DicomCleaner",
	"DeviceSerialNumber": "18973",
	"StationName": "PSYCH15-015_1111",
	"PatientPosition": "HFS",
	"SoftwareVersions": "Thu Oct 18 06:41:18 EDT 2018",
	"MRAcquisitionType": "3D",
	"SeriesDescription": "tfl_wip944_b17stx_NEW_MP2RAGE_UNI_Images",
	"ProtocolName": "tfl_wip944_b17stx_NEW_MP2RAGE_UNI_Images",
	"ScanningSequence": "GR\\IR",
	"SequenceVariant": "SP\\MP",
	"ScanOptions": "IR\\PFP",
	"SequenceName": "tfl3d1rs",
	"ImageType": ["ORIGINAL", "PRIMARY", "M", "ND", "UNI"],
	"SeriesNumber": 7,
	"AcquisitionTime": "00:08:47.383000",
	"AcquisitionNumber": 1,
	"SliceThickness": 0.5,
	"SAR": 0.0983129,
	"EchoTime": 0.00575,
	"RepetitionTime": 5,
	"PercentPhaseFOV": 90.2222,
	"PercentSampling": 100,
	"PhaseEncodingSteps": 305,
	"AcquisitionMatrixPE": 406,
	"ReconMatrixPE": 406,
	"PixelBandwidth": 171,
	"ImageOrientationPatientDICOM": [
		1,
		0,
		0,
		0,
		0.996637,
		0.0819385	],
	"InPlanePhaseEncodingDirectionDICOM": "COL",
	"ConversionSoftware": "dcm2niix",
	"ConversionSoftwareVersion": "v1.0.20211006"
}

Series_008_[MR_-_tf1_wip944_b17stx_NEW_MP2RAGE_UNI_Images]_tfl_wip944_b17stx_NEW_MP2RAGE_UNI_Images_19700101000000_8.json :

{
	"Modality": "MR",
	"MagneticFieldStrength": 6.98,
	"ImagingFrequency": 297.217,
	"Manufacturer": "Siemens",
	"ManufacturersModelName": "DicomCleaner",
	"DeviceSerialNumber": "18973",
	"StationName": "PSYCH15-015_1111",
	"PatientPosition": "HFS",
	"SoftwareVersions": "Thu Oct 18 06:41:18 EDT 2018",
	"MRAcquisitionType": "3D",
	"SeriesDescription": "tfl_wip944_b17stx_NEW_MP2RAGE_UNI_Images",
	"ProtocolName": "tfl_wip944_b17stx_NEW_MP2RAGE_UNI_Images",
	"ScanningSequence": "GR\\IR",
	"SequenceVariant": "SP\\MP",
	"ScanOptions": "IR\\PFP",
	"SequenceName": "tfl3d1rs",
	"ImageType": ["ORIGINAL", "PRIMARY", "M", "ND", "UNI"],
	"SeriesNumber": 8,
	"AcquisitionTime": "00:08:12.935000",
	"AcquisitionNumber": 1,
	"SliceThickness": 0.5,
	"SAR": 0.0994492,
	"EchoTime": 0.00575,
	"RepetitionTime": 5,
	"PercentPhaseFOV": 90.2222,
	"PercentSampling": 100,
	"PhaseEncodingSteps": 305,
	"AcquisitionMatrixPE": 406,
	"ReconMatrixPE": 406,
	"PixelBandwidth": 171,
	"ImageOrientationPatientDICOM": [
		1,
		0,
		0,
		0,
		0.987136,
		-0.159881	],
	"InPlanePhaseEncodingDirectionDICOM": "COL",
	"ConversionSoftware": "dcm2niix",

Thanks @jsein !!

jsein · January 25, 2024, 8:56am

Thank you for this information. This is what I am looking at in those files:

"AcquisitionTime" : It is supposed to tell you when this image was acquired. However it is an optional tag and I read in some places that it may not be always reliable. However for your dataset I look at it to try to see which images belong to the same acquisition (keep in mind that one MP2RAGE acquisition should in principle produce several images: INV1, INV2, UNI, UNI-DEN, T1map).
"SAR": This should also be specific for each acquisition, so the images coming from the same acquisition should have the same value of SAR.
-"ImageType": ["ORIGINAL", "PRIMARY", "M", "ND"]: This will tell you what kind of reconstruction we are dealing with. If you see a "M", it is a magnitude image, if it is a "P" instead then it is a phase image.
“ImageOrientationPatientDICOM”: there is a nice description of this field here. Again, the images coming from the same acquisition should all the same values.

My suggestion would be to determine which images are coming form the same acquisition based on those tags, and in that case, I would suggest to use the same run number for every image coming from the same acquisition. For example run-01_inv-1_MP2RAGE, run-01_inv-2_MP2RAGE, run-01_T1w, run-01_UNIT1, run-01_T1map.

gudapatis · January 29, 2024, 12:24pm

Thanks a lot for all your help @jsein !!