diff --git a/examples/notebooks/qmri_sg_challenge_2024_t1.ipynb b/examples/notebooks/qmri_sg_challenge_2024_t1.ipynb
index 3132edc31..9d10f72e2 100644
--- a/examples/notebooks/qmri_sg_challenge_2024_t1.ipynb
+++ b/examples/notebooks/qmri_sg_challenge_2024_t1.ipynb
@@ -387,6 +387,30 @@
     "\n",
     "plt.show()"
    ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "25",
+   "metadata": {},
+   "source": [
+    "### Next steps\n",
+    "\n",
+    "The 2024 ISMRM QMRI Challenge also included the estimation of $T_2^*$ maps from multi-echo data. You can find the\n",
+    "the data here: https://zenodo.org/record/10868361. You can download it using the same method as above and then\n",
+    "unpacking the 'T2star.zip' file.\n",
+    "\n",
+    "As a signal model $q$ you can use `~mrpro.operators.models.MonoExponentialDecay` describing the signal decay as\n",
+    "\n",
+    "$q(TE) = M_0 e^{-TE/T_2^*}$\n",
+    "\n",
+    "with the equilibrium magnetization $M_0$, the echo time $TE$, and $T_2^*$\n",
+    "\n",
+    "Give it a try and see if you can obtain good $T_2^*$ maps!\n",
+    "```{note}\n",
+    "The echo times $TE$ can be found in `IData.header.te`. A good starting value for $M_0$ is the signal at the shortest\n",
+    "echo time. A good starting value for $T_2^*$ is 20 ms.\n",
+    "```"
+   ]
   }
  ],
  "metadata": {
diff --git a/examples/scripts/qmri_sg_challenge_2024_t1.py b/examples/scripts/qmri_sg_challenge_2024_t1.py
index 4292f32c0..67098f7db 100644
--- a/examples/scripts/qmri_sg_challenge_2024_t1.py
+++ b/examples/scripts/qmri_sg_challenge_2024_t1.py
@@ -210,3 +210,22 @@ def show_images(*images: torch.Tensor, titles: list[str] | None = None) -> None:
 fig.colorbar(im, ax=axes[0, 2])
 
 plt.show()
+
+# %% [markdown]
+# ### Next steps
+#
+# The 2024 ISMRM QMRI Challenge also included the estimation of $T_2^*$ maps from multi-echo data. You can find the
+# the data here: https://zenodo.org/record/10868361. You can download it using the same method as above and then
+# unpacking the 'T2star.zip' file.
+#
+# As a signal model $q$ you can use `~mrpro.operators.models.MonoExponentialDecay` describing the signal decay as
+#
+# $q(TE) = M_0 e^{-TE/T_2^*}$
+#
+# with the equilibrium magnetization $M_0$, the echo time $TE$, and $T_2^*$
+#
+# Give it a try and see if you can obtain good $T_2^*$ maps!
+# ```{note}
+# The echo times $TE$ can be found in `IData.header.te`. A good starting value for $M_0$ is the signal at the shortest
+# echo time. A good starting value for $T_2^*$ is 20 ms.
+# ```