# Coregistration and Spatial Compounding of
## 4 Discussion and Conclusions  
The feasibility to efficiently combine independent sequences of cardiac OA images can significantly advance the capabilities of this modality for cardiovascular research studies. In this work, we have shown two representative examples. By combining the images acquired by raster-scanning the transducer array, it was possible to identify cardiac structures such as the heart chambers or the coronary artery. Being able to visualize the entire heart is essential for quantifying key functional parameters. For example, the blood volume in the ventricles needs to be estimated to assess indicators of pumping effectiveness such as the end systolic volume (ESV), end diastolic volume (EDV), stroke volume (SV) and ejection fraction (EF). Oxygen saturation measurements in the heart can also be very valuable. For example, the oxygen saturation in the right atrium is an optimal estimator of mixed venous oxygen saturation (SvO2), which can be used to assess insufficiencies in cardiac output and oxygen delivery [25; 26]. Myoglobin and hemoglobin oxygen saturation values in the cardiac muscle can also potentially be used as bio-markers of heart diseases [27]. Image coregistration was facilitated by the periodicity of breathing and heart motion. Recently, we have shown that a sequence of volumetric OA images of the heart could be efficiently compressed via principal component analysis (PCA), which enabled reconstructing subsequent frames with only a few OA signals [28]. In this work, we have shown that the fundamental frequencies and higher harmonics of respiratory and cardiac cycles could clearly be distinguished even when using relatively short acquisition sequences of 100 frames (1 s). Combination of independent images can then potentially be done in a short time, which may enable studying dynamic events such as hemodynamic responses to a breathing gas challenge [29; 30]. It appears challenging to use the suggested approach to study faster events such as cardiac arrhythmias, which may represent a limitation of the methodology. However, frame rates in the order of kHz have recently been achieved in OAT [31; 32]. This can potentially facilitate the development of more advanced image compounding approaches. Fourier analysis has further been used to provide a useful means to stitch multiple images acquired during a hand-held scan with no available reference on the position of the transducer array [23]. The results obtained in this work suggest that it may be further possible to stich cardiac images acquired in a hand-held manner. This is of particular relevance considering the ongoing clinical translation of the OA technology [33; 34; 35]. Imaging the human heart is challenged by the strong acoustic distortion induced in the rib cage. It is also important to take into account that the relatively large depth at which the human heart is located represents a limitation due to the strong attenuation of light. However, efficient image stitching may  
Figure 3: Coregistration of multi-spectral volumetric images. (**a**) Maximum intensity projections (MIPs) along the depth direction of the three-dimensional optoacoustic images acquired for a single position of the array for three different excitation wavelengths. Two phases of the heart cycle corresponding to systole and diastole are shown. (**b**) MIPs of the un-mixed distributions of oxygenated (HbO2) and deoxygenated (Hb) hemoglobin for the same phases shown in (**a**). LA—Left atrium, LV—Left ventricle, CA—Coronary artery. enable finding \"acoustic and optical windows\" facilitating estimating cardiac parameters that cannot be measured with existing technologies. The enhanced information obtained by combining multiple sequences of images is of particular relevance in cardiovascular biology but can also be useful in other biomedical research fields where OA is currently being used. Generally, real-time imaging is affected by breathing motion artefacts. Arterial pulsation and structural motion induced by the heart beat can also affect the acquired images.