First, here is the theorem in question.
Theorem (Oksendal Thm. 5.2.1)
Let $T>0$ and $$ \begin{array}{l} b :[0,T]\times\Bbb R^n \to {\mathbb{R}^n};\\ \sigma :[0,T]\times\Bbb R^n\to {\mathbb{R}^{n \times m}}; \end{array} $$ be measurable functions for which there exist constants $C$ and $D$ such that $$ \begin{array}{l} |b(t,x)|+|\sigma (t,x)|\le C(1+|x|);\\ |b(t,x)-b(t,y)|+|\sigma(t,x)-\sigma(t,y)|\le D|x-y|; \end{array} $$ Let $Z$ be a random variable that is independent of the $\sigma$-algebra generated by $B_s$, $s ≥ 0$, and with finite second moment: $$ E[|Z|^2]<\infty $$ Then the stochastic differential equation/initial value problem $$ \begin{array}{l} {\rm{d}}{X_t} =b(t,X_t)\mathrm dt+\sigma(t,X_t)\mathrm dB_t,\quad \text{for } t \in [0,T];\\ X_0 = Z; \end{array} $$ has a Pr-almost surely unique $t$-continuous solution $(t,ω)\mapsto X_t(ω)$ such that $X$ is adapted to the filtration $\mathcal F_t^Z$ generated by $Z$ and $B_s$, $s\leq t$, and $$ E\left[\int_0^T|X_t|^2\,\mathrm dt\right]<\infty. $$
I am stuck at a few places in the uniqueness part of the proof below.
For the first step, I expanded the squared term to find $$ E[|X_t-\hat X_t|^2]< 3 E[|X_t-\hat X_t|^2]=3E[|Z-\hat Z|^2]+3E\left(\int_0^t a\,\mathrm ds\right)^2+3E\left(\int_0^t \gamma\,\mathrm dB_s\right)^2\\ +6E\left(\int_0^t a\,\mathrm ds+\int_0^t \gamma\,\mathrm dB_s\right)\\ +6E\left((Z-\hat Z)\int_0^t a\,\mathrm ds\int_0^t \gamma\,\mathrm dB_s\right) $$ but am not sure how to proceed to get the second line. What do I do with the last two terms?
For the second arrow, I know this comes from the assumed Lipschitz continuity but am not able to fill in the steps between the lines.
Lastly, why do we need the statement marked with the $({\color{red}\ast})$? And why is the set $[0,T]$ intersected with the rationals?
Thank you in advance for any help with this.

$$3tE\bigg(\int_0^t a^2 ds\bigg)=3tE\bigg(\int_0^t (b(s,X_s)-b(s,\hat{X}_s))^2 ds\bigg)$$ $$\leq 3tD^2E\bigg( \int_0^t (X_s-\hat{X}_s)^2 \bigg)ds$$
and using the same reasoning we have
$$E\bigg(\int_0^t \gamma^2 ds\bigg)\leq 3D^2E\bigg( \int_0^t (X_s-\hat{X}_s)^2 \bigg)ds.$$
I am not one hundred percent sure about this last part, maybe some other use could tell us whether this is right or not.
$$E(|X(t,\omega)-\hat X(t,\omega)|^2)=0$$ By simplicity of notation let $Z_t=X(t,\omega)-\hat X(t,\omega)$.
The this implies that for each fixed $t\in[0,T]$ $$P\big(\{\omega:Z_t(\omega)=0\}\big)=1.$$
(this means that $X$ is a modification of $\hat X$).
We actually need to show that
$$P\big(\{\omega:Z_t(\omega)=0,\forall t\in[0,T]\}\big)=1.$$ (this means the processes are indistinguishable).
Start by taking an ordering of the rational numbers in $[0,T]$, $(r_1,r_2,\cdots)$.
Then for each fixed $r_n$ we have that $P\big(\{\omega:Z_{r_n}(\omega)=0\}\big)=1$, this means that for each $r_n$ there exists $\Omega_n$ with full measure such that $Z_{r_n}(\omega)=0$ for all $\omega\in\Omega_n$.
Now take $\Omega'=\bigcap_{n=1}^{\infty} \Omega_n$. Then we have that $P(\Omega')=1$, and for each $\omega\in\Omega'$, $Z_{r_n}(\omega)=0$, for all $n$. This means that $$P(Z_t=0,\forall t\in[0,T]\cap Q)=1$$ Then use the fact that the process is continuous and you are done.