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[ENH] Apply derivative definition to qMRI appendix #1813

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merged 11 commits into from
Aug 29, 2024
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71 changes: 45 additions & 26 deletions src/appendices/qmri.md
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Expand Up @@ -133,10 +133,13 @@ A guide for using macros can be found at

Please visit the [file collections appendix](./file-collections.md#magnetic-resonance-imaging) to see the list of currently supported qMRI applications.

### Quantitative maps are derivatives
### Outputs are quantitative maps

Regardless of how they are obtained (pre- or post-generated), qMRI maps are stored in the `derivatives` directory.
For example a `T1map` can be generated from an `MP2RAGE` file collection using either options.
qMRI maps are stored differently depending on the process that generated them.
Pre-generated qMRI maps MAY be stored as part of a raw BIDS dataset,
where as it MAY be stored in a derivative BIDS dataset if it were post-generated.
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See the example below of a `T1map` generated from an `MP2RAGE` file collection using either options.
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If the map is post-generated:

Expand All @@ -151,15 +154,25 @@ A guide for using macros can be found at
"qMRI-software-name": {
"sub-01": {
"anat": {
"sub-01_T1map.nii.gz": "",
"sub-01_T1map.nii.gz": " # --> T1 map stored as part a derivative dataset",
"sub-01_T1map.json": "",
"sub-01_UNIT1.nii.gz": "",
"sub-01_UNIT1.nii.gz": " # --> UNI T1 stored as part a derivative dataset",
"sub-01_UNIT1.json": "",
},
},
},
},
},
"sub-01": {
"anat": {
"sub-01_inv-1_part-mag_MP2RAGE.nii.gz":"",
"sub-01_inv-1_part-phase_MP2RAGE.nii.gz":"",
"sub-01_inv-1_MP2RAGE.json":"",
"sub-01_inv-2_part-mag_MP2RAGE.nii.gz":"",
"sub-01_inv-2_part-phase_MP2RAGE.nii.gz":"",
"sub-01_inv-2_MP2RAGE.json":"",
},
},
},
}
) }}

Expand All @@ -172,25 +185,30 @@ A guide for using macros can be found at
{{ MACROS___make_filetree_example(
{
"ds-example": {
"derivatives": {
"Siemens": {
"sub-01": {
"anat": {
"sub-01_T1map.nii.gz": "",
"sub-01_T1map.json": "",
"sub-01_UNIT1.nii.gz": "",
"sub-01_UNIT1.json": "",
},
},
},
"sub-01": {
"anat": {
"sub-01_inv-1_part-mag_MP2RAGE.nii.gz":"",
"sub-01_inv-1_part-phase_MP2RAGE.nii.gz":"",
"sub-01_inv-1_MP2RAGE.json":"",
"sub-01_inv-2_part-mag_MP2RAGE.nii.gz":"",
"sub-01_inv-2_part-phase_MP2RAGE.nii.gz":"",
"sub-01_inv-2_MP2RAGE.json":"",
"sub-01_T1map.nii.gz": " # --> T1 map stored as part a raw dataset",
"sub-01_T1map.json": "",
"sub-01_UNIT1.nii.gz": " # --> UNI T1 stored as part a raw dataset",
"sub-01_UNIT1.json": "",
},
},
}
}
) }}

Note: Even though the process from which pre-generated qMRI maps are obtained (vendor pipelines) is not known,
vendors generally allow exporting of the corresponding input data.
It is RECOMMENDED to share them along with the vendor outputs, whenever possible for a qMRI method supported by BIDS.
!!! note "Sharing of vendor outputs"

Even though the process from which pre-generated qMRI maps are obtained (vendor pipelines) is not known,
vendors generally allow exporting of the corresponding input data.
It is RECOMMENDED to share them along with the vendor outputs,
whenever possible for a qMRI method supported by BIDS.

### Example datasets

Expand Down Expand Up @@ -326,7 +344,7 @@ A guide for using macros can be found at

`dataset_description.json`:

```text
```json
{
"Name": "qMRLab Outputs",
"BIDSVersion": "1.5.0",
Expand Down Expand Up @@ -526,12 +544,13 @@ as an input to offline calculation of a `T1map` using a dictionary lookup approa
provided by the stock sequence. Instead, the `magnitude` and `phase` images are exported. Please
see the relevant discussion at [qMRLab issue #255](https://github.com/qMRLab/qMRLab/issues/255).

Therefore, the `UNIT1` image provided by the scanner is RECOMMENDED to be stored under the `anat`
raw dataset directory along with the `MP2RAGE` file collection and to be used as the primary input
for quantifying a `T1map`.
Therefore, the `UNIT1` image provided by the scanner
MUST be stored under the `anat` in a raw BIDS dataset
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along with the `MP2RAGE` file collection
and to be used as the primary input for quantifying a `T1map`.

If an additional `UNIT1` image is calculated offline, then the output is to be stored in the
`derivatives` directory with necessary provenance information.
If an additional `UNIT1` image is calculated offline,
then the output is to be stored in a derivative BIDS dataset with necessary provenance information.
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##### `NumberShots` metadata field

Expand Down
4 changes: 1 addition & 3 deletions src/derivatives/introduction.md
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Expand Up @@ -6,9 +6,7 @@ outputs in subsequent processing.
Standardizing derivatives is motivated by use cases where formalized
machine-readable access to processed data enables higher-level processing.

The following sections cover additions to and divergences from "raw" BIDS.
Raw data are data that have been curated into BIDS from a non-BIDS source.
If a dataset is derived from at least one other valid BIDS dataset, then it is a derivative dataset.
The following sections cover additions to and divergences from raw BIDS.

Examples:

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6 changes: 6 additions & 0 deletions src/schema/objects/common_principles.yaml
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Expand Up @@ -46,6 +46,9 @@ dataset:
description: |
A set of neuroimaging and behavioral data acquired for a purpose of a particular study.
A dataset consists of data acquired from one or more subjects, possibly from multiple sessions.
derivative:
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display_name: derivative dataset
description: If a dataset is derived from at least one other valid BIDS dataset, then it is a derivative dataset.
deprecated:
display_name: DEPRECATED
description: |
Expand Down Expand Up @@ -97,6 +100,9 @@ modality:
the technique is sufficiently uniform to define the modalities `eeg`, `meg` and `ieeg`.
When applicable, the modality is indicated in the **suffix**.
The modality may overlap with, but should not be confused with the **data type**.
raw:
display_name: raw dataset
description: A raw BIDS dataset is data that have been curated into BIDS from a non-BIDS source.
run:
display_name: Run
description: |
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2 changes: 2 additions & 0 deletions src/schema/rules/common_principles.yaml
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Expand Up @@ -16,3 +16,5 @@
- suffix
- extension
- deprecated
- raw
- derivative
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