diff --git a/CHANGELOG.md b/CHANGELOG.md
index 2d3b794..08d459c 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -1,5 +1,13 @@
 # Changelog
 
+## [1.8.1] - 2026-02-02
+
+### Changed
+
+Fixed a bug originating from Skyline: in the absence of IDMS, the area value is now entered in the ratios column instead of NA. The issue is now resolved.
+
+# Changelog
+
 ## [1.8.0] - 2025-10-07
 
 ### Changed
diff --git a/ms_reader/__init__.py b/ms_reader/__init__.py
index 29654ee..2d986fc 100644
--- a/ms_reader/__init__.py
+++ b/ms_reader/__init__.py
@@ -1 +1 @@
-__version__ = "1.8.0"
+__version__ = "1.8.1"
diff --git a/ms_reader/skyline_convert.py b/ms_reader/skyline_convert.py
index bc6a98b..f839e81 100644
--- a/ms_reader/skyline_convert.py
+++ b/ms_reader/skyline_convert.py
@@ -125,6 +125,21 @@ def handle_na(row):
     return row
 
 
+def compare_values(data):
+    """
+    This method allows you to verify that the values in the ‘Response Ratio’ column do not correspond to areas.
+    In the absence of IDMS, Skyline defaults to entering the metabolite area instead of NA.
+    To detect this case, the values in the ‘Area’ and ‘Response Ratio’ columns are compared: if they are similar 
+    (indicating that it is an area and not a ratio), the ‘Response Ratio’ value is replaced by np.nan.
+    
+    :param data: DataFrame containing the Skyline data
+    """
+    df_area = pd.to_numeric(data["Area"], errors="coerce")
+    df_ratio = pd.to_numeric(data["Response Ratio"], errors="coerce")
+
+    mask = np.isclose(df_area, df_ratio, equal_nan=True, rtol=0.005)
+    data.loc[mask, "Response Ratio"] = np.nan
+
 def import_skyline_dataset(skyline_file):
     """
     Import skyline dataset and transform into MS_Reader compatible format
@@ -152,7 +167,7 @@ def import_skyline_dataset(skyline_file):
         data["Calculated Amt"].replace(to_replace=re.compile(pattern='∞'), value="NaN", inplace=True)
         data["Calculated Amt"] = data["Calculated Amt"].apply(convert_calculated_amt)
     data = data.apply(handle_na, axis=1)
-
+    compare_values(data)
     return data