From 83b1c4ed56b154b621b046591edd67b66ce7a343 Mon Sep 17 00:00:00 2001
From: Mathieu Boudreau <emb6150@gmail.com>
Date: Tue, 1 Oct 2024 09:19:05 -0300
Subject: [PATCH] Try adding new section + equations

---
 .../myst-02-IR_SignalModelling.md             | 33 +++++++++++++++++++
 binder/requirements.txt                       |  4 ++-
 binder/runtime.txt                            |  1 +
 3 files changed, 37 insertions(+), 1 deletion(-)
 create mode 100644 2 T1 Mapping/Inversion Recovery T1 Mapping/myst-02-IR_SignalModelling.md

diff --git a/2 T1 Mapping/Inversion Recovery T1 Mapping/myst-02-IR_SignalModelling.md b/2 T1 Mapping/Inversion Recovery T1 Mapping/myst-02-IR_SignalModelling.md
new file mode 100644
index 0000000..efacd74
--- /dev/null
+++ b/2 T1 Mapping/Inversion Recovery T1 Mapping/myst-02-IR_SignalModelling.md	
@@ -0,0 +1,33 @@
+---
+title: Signal Modelling
+subtitle: Inversion Recovery
+date: 2024-07-25
+authors:
+  - name: Mathieu Boudreau
+    affiliations:
+      - NeuroPoly Lab, Polytechnique Montreal, Quebec, Canada
+numbering:
+  figure:
+    template: Fig. %s
+---
+
+## Articles with code vs articles from code
+The steady-state longitudinal magnetization of an inversion recovery experiment can be derived from the Bloch equations for the pulse sequence {θ<sub>180</sub> – TI – θ<sub>90</sub> – (TR-TI)}, and is given by:
+
+\begin{equation}\label{eq:1}
+M_{z}(TI) = M_0 \frac{1-\text{cos}(\theta_{180})e^{- \frac{TR}{T_1}} -[1-\text{cos}(\theta_{180})]e^{- \frac{TI}{T_1}}}{1 - \text{cos}(\theta_{180}) \text{cos}(\theta_{90}) e^{- \frac{TR}{T_1}}}
+\end{equation}
+
+where M<sub>z</sub> is the longitudinal magnetization prior to the θ<sub>90</sub> pulse. If the in-phase real signal is desired, it can be calculated by multiplying Eq. 1 by <i>k</i>sin(θ<sub>90</sub>)e<sup>-TE/T<sub>2</sub></sup>, where <i>k</i> is a constant. This general equation can be simplified by grouping together the constants for each measurements regardless of their values (i.e. at each TI, same TE and θ<sub>90</sub> are used) and assuming an ideal inversion pulse:
+
+\begin{equation}\label{eq:2}
+M_z(TI) = C(1-2e^{- \frac{TI}{T_1}} + e^{- \frac{TR}{T_1}})
+\end{equation}
+
+where the first three terms and the denominator of Eq. 1 have been grouped together into the constant C. If the experiment is designed such that TR is long enough to allow for full relaxation of the magnetization (TR > 5T<sub>1</sub>), we can do an additional approximation by dropping the last term in Eq. 2:
+
+\begin{equation}\label{eq:3}
+M_z(TI) = C(1-2e^{- \frac{TI}{T_1}})
+\end{equation}
+
+The simplicity of the signal model described by Eq. 3, both in its equation and experimental implementation, has made it the most widely used equation to describe the signal evolution in an inversion recovery T<sub>1</sub> mapping experiment. The magnetization curves are plotted in Figure 2 for approximate T<sub>1</sub> values of three different tissues in the brain. Note that in many practical implementations, magnitude-only images are acquired, so the signal measured would be proportional to the absolute value of Eq. 3.
diff --git a/binder/requirements.txt b/binder/requirements.txt
index 296d654..19962b6 100644
--- a/binder/requirements.txt
+++ b/binder/requirements.txt
@@ -1 +1,3 @@
-numpy
\ No newline at end of file
+numpy
+plotly
+networkx
\ No newline at end of file
diff --git a/binder/runtime.txt b/binder/runtime.txt
index e69de29..f31904f 100644
--- a/binder/runtime.txt
+++ b/binder/runtime.txt
@@ -0,0 +1 @@
+python-3.10
\ No newline at end of file