ENH: Calculate T1/T2 ratio

smriprep/interfaces/calc.py

@@ -0,0 +1,90 @@
+# emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-
+# vi: set ft=python sts=4 ts=4 sw=4 et:
+#
+# Copyright 2024 The NiPreps Developers <[email protected]>
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+# We support and encourage derived works from this project, please read
+# about our expectations at
+#
+#     https://www.nipreps.org/community/licensing/
+#
+"""Image calculation interfaces."""
+
+import os
+from pathlib import Path
+
+import nibabel as nb
+import numpy as np
+from nipype.interfaces.base import (
+    File,
+    SimpleInterface,
+    TraitedSpec,
+)
+
+
+class T1T2RatioInputSpec(TraitedSpec):
+    t1w_file = File(exists=True, mandatory=True, desc='T1-weighted image')
+    t2w_file = File(exists=True, mandatory=True, desc='T2-weighted image')
+    mask_file = File(exists=True, desc='Brain mask')
+
+
+class T1T2RatioOutputSpec(TraitedSpec):
+    t1t2_file = File(exists=True, desc='T1/T2 ratio image')
+
+
+class T1T2Ratio(SimpleInterface):
+    input_spec = T1T2RatioInputSpec
+    output_spec = T1T2RatioOutputSpec
+
+    def _run_interface(self, runtime):
+        self._results['t1t2_file'] = make_t1t2_ratio(
+            self.inputs.t1w_file, self.inputs.t2w_file, self.inputs.mask_file, newpath=runtime.cwd
+        )
+        return runtime
+
+
+def make_t1t2_ratio(
+    t1w_file: str,
+    t2w_file: str,
+    mask_file: str | None = None,
+    newpath: str | None = None,
+) -> str:
+    t1w = nb.load(t1w_file)
+    t2w = nb.load(t2w_file)
+    if mask_file is not None:
+        mask = np.asanyarray(nb.load(mask_file).dataobj) != 0
+    else:
+        mask = np.ones(t1w.shape, dtype=bool)
+
+    t1w_data = t1w.get_fdata(dtype=np.float32)
+    t2w_data = t2w.get_fdata(dtype=np.float32)
+
+    t1t2_data = np.zeros_like(t1w_data)
+
+    ratio = t1w_data[mask] / t2w_data[mask]
+    ratio[~np.isfinite(ratio)] = 0
+    minval = ratio.min()
+    maxval = ratio.max()
+
+    t1t2_data[mask] = (ratio - minval) / (maxval - minval) * 100
+
+    t1t2 = nb.Nifti1Image(t1t2_data, t1w.affine, t1w.header)
+    t1t2.header.set_data_dtype(np.float32)
+
+    t1t2_path = Path(newpath or os.getcwd()) / 't1t2_ratio.nii.gz'
+
+    t1t2.to_filename(t1t2_path)
+
+    return str(t1t2_path)

smriprep/interfaces/tests/test_calc.py

@@ -0,0 +1,24 @@
+import nibabel as nb
+from nipype.pipeline import engine as pe
+from templateflow import api as tf
+
+from ..calc import T1T2Ratio
+
+
+def test_T1T2Ratio(tmp_path):
+    t1w = tf.get('MNI152NLin2009cAsym', desc=None, resolution=1, suffix='T1w')
+    t2w = tf.get('MNI152NLin2009cAsym', desc=None, resolution=1, suffix='T2w')
+    mask = tf.get('MNI152NLin2009cAsym', desc='brain', resolution=1, suffix='mask')
+
+    t1t2 = pe.Node(
+        T1T2Ratio(t1w_file=t1w, t2w_file=t2w, mask_file=mask),
+        name='t1t2',
+        base_dir=tmp_path,
+    )
+
+    result = t1t2.run()
+
+    t1t2ratio = nb.load(result.outputs.t1t2_file)
+    assert t1t2ratio.shape == (193, 229, 193)
+    assert t1t2ratio.get_fdata().min() == 0.0
+    assert t1t2ratio.get_fdata().max() == 100.0

smriprep/workflows/anatomical.py

@@ -57,6 +57,8 @@
 import smriprep
 
 from ..interfaces import DerivativesDataSink
+
+# from ..interfaces.calc import T1T2Ratio
 from ..utils.misc import apply_lut as _apply_bids_lut
 from ..utils.misc import fs_isRunning as _fs_isRunning
 from .fit.registration import init_register_template_wf
@@ -645,6 +647,7 @@ def init_anat_fit_wf(
                 'sphere_reg_fsLR',
                 'sphere_reg_msm',
                 'anat_ribbon',
+                't1t2_ratio',
                 # Reverse transform; not computable from forward transform
                 'std2anat_xfm',
                 # Metadata
@@ -1308,6 +1311,16 @@ def init_anat_fit_wf(
         LOGGER.info('ANAT Stage 8a: Found pre-computed cortical ribbon mask')
         outputnode.inputs.anat_ribbon = precomputed['anat_ribbon']
 
+    if t2w and 't1t2ratio' not in precomputed:
+        LOGGER.info('ANAT Stage 8b: Creating T1w/T2w ratio map')
+        # Commented out to pacify linter.
+        # t1t2_ratio = pe.Node(T1T2Ratio(), name='t1t2_ratio')
+
+    elif not t2w:
+        LOGGER.info('ANAT No T2w images provided - skipping Stage 8b')
+    else:
+        LOGGER.info('ANAT Found precomputed T1w/T2w ratio map - skipping Stage 8b')
+
     # Stage 9: Baseline fsLR registration
     if len(precomputed.get('sphere_reg_fsLR', [])) < 2:
         LOGGER.info('ANAT Stage 9: Creating fsLR registration sphere')