As there is an evident lack of studies regarding the use of deep learning-based reconstruction methods in the paediatric cohort, this study aimed to retrospectively assess GE Healthcare’s novel algorithm, Air Recon^TM DL, offering a methodology to the wider radiology community for performing these validation studies through a combined quantitative and qualitative approach. Due to the nature of this retrospective study, a proper comparison between ARDL reconstructed images and conventional reconstructed images was not possible. The images which formed part of this study were collected in a practical clinical setting, and although the MRI scanner can simultaneously output both ARDL and conventionally reconstructed images, the MRI parameters used by radiographers and GE applications specialists during protocol development were defined with use of the DL algorithm in mind. Ultimately, GE Healthcare’s ARDL reconstruction method improves image quality, with its main focus geared towards noise removal. The findings of this study suggests that although the quantitative analysis indicated a significant improvement in image quality, this enhancement did not significantly affect the interpretive outcomes, as revealed by the qualitative results. However, its use ensures that scans have image quality at least comparable to conventionally reconstructed images, while also achieving faster scan times.