Ignore non-steady-state volumes in T2* estimation.

Author: tsalo

fmriprep/interfaces/multiecho.py

@@ -68,6 +68,11 @@ class T2SMapInputSpec(CommandLineInputSpec):
             'monoexponential model is fit to the raw data.'
         ),
     )
+    n_exclude = traits.Int(
+        argstr='--exclude %s',
+        position=5,
+        desc='Number of volumes from the beginning of the run to exclude from T2*/S0 estimation.',
+    )
 
 
 class T2SMapOutputSpec(TraitedSpec):
@@ -103,6 +108,9 @@ class T2SMap(CommandLine):
     def _format_arg(self, name, trait_spec, value):
         if name == 'echo_times':
             value = [te * 1000 for te in value]
+        if name == 'n_exclude':
+            # Convert to a range
+            value = f'0:{value}'
         return super()._format_arg(name, trait_spec, value)
 
     def _list_outputs(self):

fmriprep/workflows/bold/fit.py

@@ -981,7 +981,10 @@ def init_bold_native_wf(
         # Do NOT set motion_xfm on outputnode
         # This prevents downstream resamplers from double-dipping
         workflow.connect([
-            (inputnode, bold_t2s_wf, [('bold_mask', 'inputnode.bold_mask')]),
+            (inputnode, bold_t2s_wf, [
+                ('bold_mask', 'inputnode.bold_mask'),
+                ('dummy_scans', 'inputnode.skip_vols'),
+            ]),
             (boldref_bold, join_echos, [('out_file', 'bold_files')]),
             (join_echos, bold_t2s_wf, [('bold_files', 'inputnode.bold_file')]),
             (join_echos, outputnode, [('bold_files', 'bold_echos')]),

fmriprep/workflows/bold/t2s.py

@@ -107,7 +107,10 @@ def init_bold_t2s_wf(
 The optimally combined time series was carried forward as the *preprocessed BOLD*.
 """
 
-    inputnode = pe.Node(niu.IdentityInterface(fields=['bold_file', 'bold_mask']), name='inputnode')
+    inputnode = pe.Node(
+        niu.IdentityInterface(fields=['bold_file', 'bold_mask', 'skip_vols']),
+        name='inputnode',
+    )
 
     outputnode = pe.Node(niu.IdentityInterface(fields=['bold', 't2star_map']), name='outputnode')
 
@@ -122,7 +125,10 @@ def init_bold_t2s_wf(
     )
     workflow.connect([
         (inputnode, dilate_mask, [('bold_mask', 'in_mask')]),
-        (inputnode, t2smap_node, [('bold_file', 'in_files')]),
+        (inputnode, t2smap_node, [
+            ('bold_file', 'in_files'),
+            ('skip_vols', 'n_exclude'),
+        ]),
         (dilate_mask, t2smap_node, [('out_mask', 'mask_file')]),
         (t2smap_node, outputnode, [('optimal_comb', 'bold'),
                                    ('t2star_map', 't2star_map')]),