Balanced Steady-state free precession (bSSFP) sequences are the gold standard in cardiac magnetic resonance (CMR) cine functional imaging due to the inherently high SNR and contrast between the blood pool and myocardium. However, when compared to spoiled gradient echo sequences, bSSFP is highly sensitive to inhomogeneities caused by the main magnetic field or by tissue susceptibility differences. These inhomogeneities lead to the well-known banding artifacts in bSSFP images, which along with flow-related artifacts can limit diagnostic information in CMR. Though banding can be minimized by using shorter TR and optimized pre-scan calibrations, it remains a challenge for CMR, especially at 3.0T. Recently, a “Geometric Solution” (GS) based on a novel elliptical signal model has been introduced and demonstrated in bSSFP applications outside the heart [1]. GS is capable of completely removing banding from four different phase- cycled bSSFP datasets, and mitigates flow artifacts [2]. This work investigates the feasibility of extending GS to CMR and explores its potential to enable longer TRs than have conventionally been feasible with bSSFP, permitting sub-millimeter resolution cine imaging free of banding artifacts.Cine imaging is usually limited in terms of spatial resolution, due to the requirement to keep TR short to limit banding artifacts in bSSFP. First, to assess the benefit of the GS in a clinically relevant cardiac protocol, cine bSSFP datasets with typical 1.9x1.9mm² spatial resolution were acquired. Second, to explore the ultra-high resolution parameter space typically inaccessible with bSSFP, sub-millimeter resolution datasets with high TR values were acquired. In both cases, four different phase cycles, 0°, 90°, 180°, and 270°, were collected, each in a separate breath-hold. Banding was then removed using the GS as described in [1]. This was compared to a complex sum (ComSum) of the four phase cycled datasets. Two short-axis cine datasets were acquired on a 3.0T clinical scanner (MR750w, GE Healthcare, Waukesha/WI, USA): one employed clinical parameters (TR/TE = 3.6/1.3ms, α = 50°, FOV = 360x288mm², matrix = 188x152, slice thickness = 8mm, BW = ±111.11kHz, resolution=1.9x1.9mm²), and the other used sub-millimeter resolution (TR/TE = 5.6/2.6ms, α = 65°, FOV = 360x252mm², matrix = 384x270, slice thickness = 8mm, BW = ±125.00kHz, resolution=0.9x0.9mm²). In both cases, no parallel imaging was applied, and standard shimming procedures were followed.Figures 1 and 2 show frames from the individual cine datasets. Several phase cycles show either significant banding in the cardiac region (white arrows) or flow related artifacts (blue arrows). The standard 180° phase-cycled images suffer from banding artifacts in the myocardium despite proper local shimming. The GS completely removes all banding from the FOV. Furthermore, the GS depicts mitigated flow-related dephasing in both datasets, and more homogenous overall image intensity relative to the phase-cycled data and the ComSum. However, in the ComSum and GS, a slight blurring compared to the individual phase-cycled images can be seen.This work represents the first known application of GS to cardiac bSSFP imaging. Despite severe banding and flow artifacts in some phase-cycled images, GS proved to be a promising tool for obtaining high-quality bSSFP cine datasets without visible banding in CMR. The GS also demonstrates mitigated flow artifacts relative to the ComSum [2], although the slight blurring observed in GS and ComSum datasets compared to standard 180° phase-cycled bSSFP images indicates that motion can still pose a challenge. Since four different phase cycles are necessary, care must be given to avoid misregistration artifacts due to respiratory motion. Future work will focus on optimizing data acquisition strategies to lower the additional scan time burden. Furthermore, motion compensation strategies similar to [3] may remove blurring by compensating any misregistration between the individual phase-cycled datasets. In summary, this initial feasibility study demonstrates the potential of GS to improve the robustness of clinical bSSFP CMR at 3.0T as well as to enable access to typically unavailable parameter spaces such as sub-millimeter resolution with very high TRs. This may improve clinical CMR performance at both 1.5T or 3.0T.