systems (1.5 T, 3.0 T, and 7.0 T) owing to its capability in generating a uniform B\({}_{1}\)-field over a large portion of the imaging volume. The birdcage RF coil driven in quadrature mode generates a circularly polarized B\({}_{1}\)-field, which reduces the RF power requirement by a factor of 0.5 to 0.7 depending on the shape and the size of the subject; additionally, it increases the receiver sensitivity by \(\sqrt{2}\) over the linear mode [2; 3]. Birdcage RF coils can be categorized into low-pass (capacitors placed on legs), high-pass (on end-rings), and hybrid (both on legs and end-rings) configurations. Many different variants of birdcage RF coils were designed, such as circular, elliptical [4], and asymmetric shapes [5; 6], to closely match the RF coil outline to the subject outline as well as the space constraint for improved B\({}_{1}\)-field homogeneity and overall performance. Numerous analytical and theoretical solutions were reported previously for both circular [7; 8; 9; 10; 11; 12] and noncircular [13; 14; 15; 16; 17] birdcage RF coils to optimize the B\({}_{1}\)-field and the capacitor values for the desired resonance at a specified Larmor frequency. These numerical solutions were based on equivalent circuit analysis by which the optimum capacitor values of the birdcage RF coil and their frequency response spectrum were calculated. However, these calculations yielded substantial errors in the optimum capacitor values for large-sized shielded birdcage RF coil designs, resulting in degraded B\({}_{1}\)-field performance. In the aforementioned numerical solutions, quasi-static conditions were assumed in calculating the B\({}_{1}\)-field, and the electromagnetic (EM) interaction between the RF coil and the target object placed inside the RF coil was disregarded [18]. Many studies were conducted to solve problems pertaining to EM interactions between the RF coil and the target object by solving [PERSON]'s equation using the EM toolbox based on various solvers, such as finite element method (FEM), finite difference time domain method (FDTD), method of moments (MOM), hybrid approaches, and others [19; 20; 21; 22; 23; 24]. Through these EM simulations, EM parameters such as EM fields (e.g., B\({}_{1}\)- and E-fields) and the specific absorption rate (SAR) related to safety could be calculated to evaluate the RF coil performance [25; 26; 27]. However, these EM simulation studies did not account for the RF circuitry, such as tuning, matching, and decoupling conditions at the excitation port of the RF coil, which can alter the total power balance of the RF coil as well as B\({}_{1}\)-field and SAR distribution [28]. A two-way link between RF circuitry and EM simulations was demonstrated for the RF coil co-simulation approach, which offered significant time reduction in RF coil analysis with a human model via tuning/matching as a post-simulation adjustment [29]. To obtain the optimal lumped element value for the RF coil, a network co-simulation approach was used [30]. This method yielded variations in the SAR estimates based on the decoupling between the excitation ports. In particular, while designing an RF coil for RF transmission, an accurate SAR distribution is crucial for ensuring RF safety standard guidelines [31]. Apart from numerical and EM simulation considerations, physical constraints such as conductor length, conductor width, and ratio of RF shield diameter to RF coil diameter affect the homogeneity of the B\({}_{1}\)-field and the transmission power efficiency of the RF coil [32]. RF shields are used in every MRI system to prevent the coupling of the RF coil with other RF electronic hardware, specifically those with gradient coils [33]. According to various commercial MRI system specifications, the minimum distance between the RF shield and the RF coil is typically at least 5 cm.