diff --git a/mriqc/workflows/diffusion/output.py b/mriqc/workflows/diffusion/output.py
index 43c68b38..d6847086 100644
--- a/mriqc/workflows/diffusion/output.py
+++ b/mriqc/workflows/diffusion/output.py
@@ -216,160 +216,6 @@ def _gen_entity(inlist):
 
     ])
     # fmt: on
-
-    if True:
-        return workflow
-
-    # Generate crown mask
-    # Create the crown mask
-    dilated_mask = pe.Node(BinaryDilation(), name='dilated_mask')
-    subtract_mask = pe.Node(BinarySubtraction(), name='subtract_mask')
-    parcels = pe.Node(niu.Function(function=_carpet_parcellation), name='parcels')
-
-    bigplot = pe.Node(FMRISummary(), name='BigPlot', mem_gb=mem_gb * 3.5)
-
-    ds_report_carpet = pe.Node(
-        DerivativesDataSink(
-            base_directory=reportlets_dir,
-            desc='carpet',
-            datatype='figures',
-        ),
-        name='ds_report_carpet',
-        run_without_submitting=True,
-    )
-
-    # fmt: off
-    workflow.connect([
-        # (inputnode, rnode, [("in_iqms", "in_iqms")]),
-        (inputnode, bigplot, [('hmc_epi', 'in_func'),
-                              ('hmc_fd', 'fd'),
-                              ('fd_thres', 'fd_thres'),
-                              ('in_dvars', 'dvars'),
-                              ('outliers', 'outliers'),
-                              (('meta_sidecar', _get_tr), 'tr')]),
-        (inputnode, parcels, [('epi_parc', 'segmentation')]),
-        (inputnode, dilated_mask, [('brain_mask', 'in_mask')]),
-        (inputnode, subtract_mask, [('brain_mask', 'in_subtract')]),
-        (dilated_mask, subtract_mask, [('out_mask', 'in_base')]),
-        (subtract_mask, parcels, [('out_mask', 'crown_mask')]),
-        (parcels, bigplot, [('out', 'in_segm')]),
-        (inputnode, ds_report_carpet, [('name_source', 'source_file')]),
-        (bigplot, ds_report_carpet, [('out_file', 'in_file')]),
-    ])
-    # fmt: on
-
-    if config.workflow.fft_spikes_detector:
-        mosaic_spikes = pe.Node(
-            PlotSpikes(
-                out_file='plot_spikes.svg',
-                cmap='viridis',
-                title='High-Frequency spikes',
-            ),
-            name='PlotSpikes',
-        )
-
-        ds_report_spikes = pe.Node(
-            DerivativesDataSink(
-                base_directory=reportlets_dir,
-                desc='spikes',
-                datatype='figures',
-            ),
-            name='ds_report_spikes',
-            run_without_submitting=True,
-        )
-
-        # fmt: off
-        workflow.connect([
-            (inputnode, ds_report_spikes, [('name_source', 'source_file')]),
-            (inputnode, mosaic_spikes, [('in_ras', 'in_file'),
-                                        ('in_spikes', 'in_spikes'),
-                                        ('in_fft', 'in_fft')]),
-            (mosaic_spikes, ds_report_spikes, [('out_file', 'in_file')]),
-        ])
-        # fmt: on
-
-    if not verbose:
-        return workflow
-
-    # Verbose-reporting goes here
-    from nireports.interfaces import PlotContours
-
-    mosaic_zoom = pe.Node(
-        PlotMosaic(
-            cmap='Greys_r',
-        ),
-        name='PlotMosaicZoomed',
-    )
-
-    plot_bmask = pe.Node(
-        PlotContours(
-            display_mode='y' if config.workflow.species.lower() in ('rat', 'mouse') else 'z',
-            levels=[0.5],
-            colors=['r'],
-            cut_coords=10,
-            out_file='bmask',
-        ),
-        name='PlotBrainmask',
-    )
-
-    ds_report_zoomed = pe.Node(
-        DerivativesDataSink(
-            base_directory=reportlets_dir,
-            desc='zoomed',
-            datatype='figures',
-        ),
-        name='ds_report_zoomed',
-        run_without_submitting=True,
-    )
-
-    ds_report_background = pe.Node(
-        DerivativesDataSink(
-            base_directory=reportlets_dir,
-            desc='background',
-            datatype='figures',
-        ),
-        name='ds_report_background',
-        run_without_submitting=True,
-    )
-
-    ds_report_bmask = pe.Node(
-        DerivativesDataSink(
-            base_directory=reportlets_dir,
-            desc='brainmask',
-            datatype='figures',
-        ),
-        name='ds_report_bmask',
-        run_without_submitting=True,
-    )
-
-    ds_report_norm = pe.Node(
-        DerivativesDataSink(
-            base_directory=reportlets_dir,
-            desc='norm',
-            datatype='figures',
-        ),
-        name='ds_report_norm',
-        run_without_submitting=True,
-    )
-
-    # fmt: off
-    workflow.connect([
-        (inputnode, ds_report_norm, [('mni_report', 'in_file'),
-                                     ('name_source', 'source_file')]),
-        (inputnode, plot_bmask, [('epi_mean', 'in_file'),
-                                 ('brain_mask', 'in_contours')]),
-        (inputnode, mosaic_zoom, [('epi_mean', 'in_file'),
-                                  ('brain_mask', 'bbox_mask_file')]),
-        (inputnode, mosaic_noise, [('epi_mean', 'in_file')]),
-        (inputnode, ds_report_zoomed, [('name_source', 'source_file')]),
-        (inputnode, ds_report_background, [('name_source', 'source_file')]),
-        (inputnode, ds_report_bmask, [('name_source', 'source_file')]),
-        (mosaic_zoom, ds_report_zoomed, [('out_file', 'in_file')]),
-        (mosaic_noise, ds_report_background, [('out_file', 'in_file')]),
-        (plot_bmask, ds_report_bmask, [('out_file', 'in_file')]),
-    ])
-    # fmt: on
-
     return workflow