Infer the appropriate MNIInfant cohort based on the participant's age

docs/usage.rst

@@ -30,6 +30,30 @@ Command-Line Arguments
    :nodefaultconst:
 
 
+Infant mode
+===========
+
+If ``--infant`` is used, the pipeline will select an MNIInfant template with the
+appropriate cohort based on the participant's age.
+
+``--infant`` is only compatible with ``--subject-anatomical-reference sessionwise``.
+
+.. note::
+
+    QSIPrep's cohort selection is derived from Nibabies.
+
+Participant Ages
+----------------
+
+QSIPrep will attempt to automatically extract participant ages (in months) from the BIDS layout. Specifically, these two files will be checked:
+
+Sessions file: <bids-root>/<subject>/subject_sessions.tsv
+
+Participants file: <bids-root>/participants.tsv
+
+Either file should include age (or if you wish to be more explicit: age_months) columns, and it is recommended to have an accompanying JSON file to further describe these fields, and explicitly state the values are in months.
+
+
 Note on using CUDA
 ==================
 

qsiprep/cli/parser.py

@@ -307,7 +307,11 @@ def _bids_filter(value, parser):
         "parts of the workflow (a space delimited list)",
     )
     g_conf.add_argument(
-        "--infant", action="store_true", help="configure pipelines to process infant brains"
+        "--infant",
+        action="store_true",
+        help="Configure pipelines to process infant brains. "
+        "If using this parameter, the anatomical-template will be changed to MNIInfant. "
+        "The appropriate MNIInfant cohort will be selected based on the participant's age.",
     )
     g_conf.add_argument(
         "--longitudinal",
@@ -649,11 +653,17 @@ def parse_args(args=None, namespace=None):
     opts = parser.parse_args(args, namespace)
 
     # Change anatomical_template based on infant parameter
+    opts.anatomical_template = "MNI152NLin2009cAsym"
     if opts.infant:
         config.loggers.cli.info(
-            "Infant processing mode enabled. Changing anatomical template to MNIInfant cohort-2."
+            "Infant processing mode enabled. "
+            "Inferring the subject's age and selecting the appropriate MNIInfant cohort."
         )
         opts.anatomical_template = "MNIInfant"
+        if opts.subject_anatomical_reference != "sessionwise":
+            config.loggers.cli.error(
+                "Infant processing requires --subject-anatomical-reference sessionwise"
+            )
 
     if opts.config_file:
         skip = {} if opts.reports_only else {"execution": ("run_uuid",)}

qsiprep/config.py

@@ -554,8 +554,7 @@ class workflow(_Config):
     anat_only = False
     """Execute the anatomical preprocessing only."""
     anatomical_template = None
-    """Keeps the :py:class:`~niworkflows.utils.spaces.SpatialReferences`
-    instance keeping standard and nonstandard spaces."""
+    """Anatomical template to use. This field doesn't include the cohort."""
     b0_threshold = None
     """Any value in the .bval file less than this will be considered a b=0 image."""
     b0_motion_corr_to = None

qsiprep/interfaces/anatomical.py

@@ -196,9 +196,8 @@ def clip_values(values):
 
 
 class _GetTemplateInputSpec(BaseInterfaceInputSpec):
-    template_name = traits.Enum(
-        "MNI152NLin2009cAsym",
-        "MNIInfant",
+    template_spec = traits.Str(
+        desc="Template specification of the form <template>[+<cohort>]",
         mandatory=True,
     )
     anatomical_contrast = traits.Enum("T1w", "T2w", "none")
@@ -221,17 +220,22 @@ def _run_interface(self, runtime):
             LOGGER.info("Using T1w modality template for ACPC alignment")
             anatomical_contrast = "T1w"
 
+        template_name = self.inputs.template_spec
+        cohort = None
+        if "+" in template_name:
+            template_name, cohort = template_name.split("+")
+
         template_path = get_template(
-            self.inputs.template_name,
-            cohort=[None, "2"],
+            template_name,
+            cohort=cohort,
             resolution="1",
             desc=None,
             suffix=anatomical_contrast,
             extension=".nii.gz",
         )
         mask_path = get_template(
-            self.inputs.template_name,
-            cohort=[None, "2"],
+            template_name,
+            cohort=cohort,
             resolution="1",
             desc="brain",
             suffix="mask",

qsiprep/interfaces/reports.py

@@ -44,7 +44,8 @@
 \t\t<li>Structural images: {n_t1s:d} T1-weighted {t2w}</li>
 \t\t<li>Diffusion-weighted series: inputs {n_dwis:d}, outputs {n_outputs:d}</li>
 {groupings}
-\t\t<li>Resampling targets: T1wACPC
+\t\t<li>Resampling targets: T1wACPC</li>
+\t\t<li>Transform targets: {output_spaces}</li>
 \t</ul>
 """
 
@@ -146,7 +147,7 @@ class SubjectSummaryInputSpec(BaseInterfaceInputSpec):
     session_id = Str(desc="Session ID")
     dwi_groupings = traits.Dict(desc="groupings of DWI files and their output names")
     output_spaces = traits.List(desc="Target spaces")
-    template = traits.Enum("MNI152NLin2009cAsym", "MNIInfant", desc="Template space")
+    template = Str(desc="Template space")
     freesurfer_status = traits.Enum("Not run", "Partial", "Full", desc="FreeSurfer status")
 
 
@@ -206,7 +207,7 @@ def _generate_segment(self):
             n_dwis=n_dwis,
             n_outputs=n_outputs,
             groupings=groupings,
-            output_spaces="T1wACPC",
+            output_spaces=["T1wACPC", self.inputs.template],
         )