diff --git a/config/DCE_deltaCt.config.yaml b/config/DCE_deltaCt.config.yaml
index 9de5a42..0df6ab0 100644
--- a/config/DCE_deltaCt.config.yaml
+++ b/config/DCE_deltaCt.config.yaml
@@ -1,7 +1,6 @@
 
 # General (previously Qbi.runner options)
-#data_dir: null
-output_dir: logs/qMRI_processes
+# data_dir: null
 # no_audit: True # -- this is a madym option
 
 # Inputs
@@ -10,7 +9,7 @@ T1_path: madym_output/T1_VFA/T1.nii.gz
 
 dce_im_ext: .nii.gz
 dce_meta_ext: .json
-#roi_path: null
+roi_path: null
 
 # Parameters
 dce_limits: [2, 9, 11, 15] 
@@ -21,6 +20,7 @@ equal_var: True
 
 # Output
 maps_dir: DCE_output_maps
+output_dir: logs/qMRI_processes/DCE_deltaCt.log
 
 
 
diff --git a/workflow/Snakefile b/workflow/Snakefile
index 3826ec5..83ad8a1 100644
--- a/workflow/Snakefile
+++ b/workflow/Snakefile
@@ -2,3 +2,28 @@
 # Please follow the best practices: 
 # https://snakemake.readthedocs.io/en/stable/snakefiles/best_practices.html,
 # in particular regarding the standardized folder structure mentioned there. 
+
+from snakemake.utils import min_version
+min_version("6.15")
+
+# workdir: "path/to/workdir"
+
+# # Preprocessing
+# include: "rules/OE_IR_T1_mapping.smk"
+# include: "rules/DCE_VFA_T1_mapping.smk"
+# include: "rules/OE_deltaR1.smk"
+
+include: "rules/DCE_deltaCt.smk"
+
+# include: "rules/DCE_ETM.smk"
+# # include: "rules/OE_DCE_hypoxia_mapping.smk"
+
+# # Postprocessing
+# include: "OE_DCE_summary.smk"
+
+rule all:
+    input:
+        expand("{maps_dir}/{key}{ext}",
+            maps_dir = data_path("maps_dir"),
+            key = ['C_t', 'delta_C', 'C_baseline', 'C_enhancing', 'C_p_vals', 'S_p_vals'],
+            ext = ".nii.gz"),
\ No newline at end of file
diff --git a/workflow/rules/DCE_deltaCt.smk b/workflow/rules/DCE_deltaCt.smk
new file mode 100644
index 0000000..d7f30d1
--- /dev/null
+++ b/workflow/rules/DCE_deltaCt.smk
@@ -0,0 +1,40 @@
+'''
+Wrapper for PreclinicalMRI.dynamic.compute_dataset_delta_Ct
+'''
+import os
+from snakemake.utils import validate
+
+configfile: workflow.source_path("../../config/DCE_deltaCt.config.yaml")
+validate(config, workflow.source_path("../schemas/DCE_deltaCt.schema.yaml"))
+
+data_dir = config.get("data_dir")
+assert os.path.exists(data_dir), f"The folder {data_dir} does not exist"
+workdir: data_dir
+
+def data_path(path_key):
+    rel_path = config.get(path_key)
+    return rel_path if rel_path is not None else []
+
+rule DCE_deltaCt:
+    conda:
+      "../envs/conda_env.yml"
+    input:
+        images = f"{data_path('dce_path')}{config['dce_im_ext']}",
+        metadata = f"{data_path('dce_path')}{config['dce_meta_ext']}",
+        T1_path = data_path('T1_path'),
+        roi_path = data_path('roi_path')
+    output:
+        expand("{maps_dir}/{key}{ext}",
+            maps_dir = data_path("maps_dir"),
+            key = ['C_t', 'delta_C', 'C_baseline', 'C_enhancing', 'C_p_vals', 'S_p_vals'],
+            ext = ".nii.gz"),
+    params:
+        dce_limits = config["dce_limits"],
+        relax_coeff = config["relax_coeff"],
+        average_fun = config["average_fun"],
+        alternative = config["alternative"],
+        equal_var = config["equal_var"]
+    log:
+        config["output_dir"]
+    script:
+        "../scripts/DCE_deltaCt.py"
diff --git a/workflow/schemas/DCE_deltaCt.schema.yaml b/workflow/schemas/DCE_deltaCt.schema.yaml
index 3981900..7bcd588 100644
--- a/workflow/schemas/DCE_deltaCt.schema.yaml
+++ b/workflow/schemas/DCE_deltaCt.schema.yaml
@@ -7,7 +7,6 @@ properties:
   data_dir:
     type: string
     description: 'Base data path'
-    default: './test'
 
   roi_path:
     type: ["null", string]
@@ -17,14 +16,19 @@ properties:
   #Output dir
   maps_dir:
     type: string
-    description: 'Location of saved output maps, relative to data_dir'
+    description: 'Relative path to output maps'
     default: 'DCE_output_maps'
 
+  output_dir:
+    type: string
+    description: 'Relative path to log file'
+    default: logs/qMRI_processes/DCE_deltaCt.log
+
   #DCE input options
   dce_path:
     type: string
     description: 'Relative path to DCE 4D-image volumes'
-    default: 'dynamic'
+    default: 'dce/dce_dyn_echo1'
 
   dce_im_ext:
     type: string
diff --git a/workflow/scripts/DCE_deltaCt.py b/workflow/scripts/DCE_deltaCt.py
index a8f3e50..ed07fba 100644
--- a/workflow/scripts/DCE_deltaCt.py
+++ b/workflow/scripts/DCE_deltaCt.py
@@ -1,100 +1,40 @@
 '''
-_summary_
+Wrapper for PreclinicalMRI.dynamic.compute_dataset_delta_Ct
 '''
 import os
 import numpy as np
+from contextlib import redirect_stdout, redirect_stderr
 
-from QbiPy.tools.runner import QbiRunner, bool_option
 from QbiPy.image_io.analyze_format import write_nifti_img
 from PreclinicalMRI.dynamic import dce
 
-#---------------------------------------------------------
-def add_options(runner):
-    parser = runner.parser
-
-    #General input arguments
-    parser.add('--roi_path', type=str, nargs='?', default=None,
-        help='Relative path to roi mask file')
-
-    #DCE input options
-    parser.add('--dce_path', type=str, nargs='?', default='dynamic',
-        help='Relative path to DCE 4D-image volumes')
-    parser.add('--dce_im_ext', type=str, nargs='?', default='.nii.gz',
-        help='File extension of the DCE volumes')
-    parser.add('--dce_meta_ext', type=str, nargs='?', default='.json',
-        help='File extension of the DCE volumes meta-info')
-    parser.add('--dce_limits', type=int, nargs=4, required=True,
-        help='Limits for the DCE volumes, 4 element integer list')
-    parser.add('--T1_path', type=str, nargs='?', default='madym_output/T1_VFA/T1.nii.gz',
-        help='Relative path to T1 image')
-    parser.add('--relax_coeff', type=float, nargs='?', default=3.4,
-        help='Relaxivity constant for contrast agent - units... ')
-    
-    #Summary stats options
-    parser.add('--average_fun', type=str, nargs='?', default='median',
-        help='Method used for temporal average {median, mean}.')
-    parser.add('--alternative', type=str, nargs='?', default='less',
-        help='Apply 1-sided or 2-sided t-test: less = baseline lower than enhancing. Use "two-sided" for 2-sided.')
-    parser.add('--equal_var', type=bool_option, nargs='?', default=True, 
-        const = True, help='Assume equal variance in pre/post enhancing periods')
-    
-    # TODO: Unused?
-    # parser.add('--sig_level', type=float, nargs='?', default=0.05,
-    #     help='Significance level for p-value map thresholds')
-    
-    #Output dir
-    parser.add('--maps_dir', type=str, nargs='?', default='DCE_output_maps',
-        help='Location of saved output maps, relative to data_dir')
-
-#---------------------------------------------------------
-def run_DCE_deltaCt(
-    data_dir:str,
-    dce_limits:np.array, 
-    dce_path:str,
-    dce_im_ext:str,
-    dce_meta_ext:str,
-    T1_path:str,
-    roi_path:str,
-    relax_coeff:float,
-    average_fun:str,
-    alternative:str,
-    equal_var:bool,
-    maps_dir:str
-):
-    print('Running DCE_deltaCt')
-    dce_data = dce.compute_dataset_delta_Ct(
-        data_dir, 
-        dce_limits, 
-        dce_path = dce_path,
-        dce_im_ext = dce_im_ext,
-        dce_meta_ext = dce_meta_ext,
-        T1_path = T1_path,
-        roi_path = roi_path,
-        relax_coeff = relax_coeff,
-        average_fun = average_fun,
-        alternative = alternative,
-        equal_var = equal_var,
-        debug = 0)
-    
-    maps_dir = os.path.join(data_dir, maps_dir)
-    os.makedirs(maps_dir, exist_ok = True)
-
-    for key,value in dce_data.items():
-        print(f'{key} has shape {value.shape}')
-        nii_filepath = os.path.join(maps_dir, key + '.nii.gz')
-        write_nifti_img(
-            img_data = value, 
-            filename = nii_filepath, 
-            sform_matrix=np.eye(4), 
-            scale = 1.0, 
-            dtype = None)
-
-#---------------------------------------------------------
-def main(args = None):
-    runner = QbiRunner()
-    add_options(runner)
-    runner.run(run_DCE_deltaCt, args)
-
-#----------------------------------------------------------
-if __name__ == '__main__':
-    main()
+with open(snakemake.log[0], "w") as log:
+    with redirect_stderr(log), redirect_stdout(log):
+
+        print('Running DCE_deltaCt')
+        dce_data = dce.compute_dataset_delta_Ct(
+            snakemake.config["data_dir"], 
+            snakemake.config["dce_limits"], 
+            dce_path = snakemake.config["dce_path"],
+            dce_im_ext = snakemake.config["dce_im_ext"],
+            dce_meta_ext = snakemake.config["dce_meta_ext"],
+            T1_path = snakemake.config["T1_path"],
+            roi_path = snakemake.config["roi_path"],
+            relax_coeff = snakemake.config["relax_coeff"],
+            average_fun = snakemake.config["average_fun"],
+            alternative = snakemake.config["alternative"],
+            equal_var = snakemake.config["equal_var"],
+            debug = 0)
+
+        maps_dir = os.path.join(snakemake.config["data_dir"], snakemake.config["maps_dir"])
+        os.makedirs(maps_dir, exist_ok = True)
+
+        for key,value in dce_data.items():
+            print(f'{key} has shape {value.shape}')
+            nii_filepath = os.path.join(maps_dir, key + '.nii.gz')
+            write_nifti_img(
+                img_data = value, 
+                filename = nii_filepath, 
+                sform_matrix=np.eye(4), 
+                scale = 1.0, 
+                dtype = None)