The identification and measurement of tumours is a key requirement in the study of tumour development in mouse models of human cancer. Disease burden in autochthonous tumours, such as those arising in the lung, can be seen with non-invasive imaging, but cannot be accurately measured using standard tools such as callipers. Lung imaging is further complicated in the mouse due to instabilities arising from the rapid but cyclic cardio-respiratory motions, and the desire to use free-breathing animals. Female A/JOlaHsd mice were either injected (i.p.) with PBS 0.1ml/10g body weight (n = 6), or 10% urethane/PBS 0.1ml/10g body weight (n = 12) to induce autochthonous lung tumours. Cardio-respiratory synchronised bSSFP MRI, at 200 μm isotropic resolution was performed at 8, 13 and 18 weeks post induction. Images from the same mouse at different time points were aligned using threshold-based segmented masks of the lungs (ITK-SNAP and MATLAB) and tumour volumes were determined via threshold-based segmentation (ITK-SNAP).Scan times were routinely below 10 minutes and tumours were readily identifiable. Image registration allowed serial measurement of tumour volumes as small as 0.056 mm3. Repetitive imaging did not lead to mouse welfare issues. We have developed a motion desensitised scan that enables high sensitivity MRI to be performed with high throughput capability of greater than 4 mice/hour. Image segmentation and registration allows serial measurement of individual, small tumours. This allows fast and highly efficient volumetric lung tumour monitoring in cohorts of 30 mice per imaging time point. As a result, adaptive trial study designs can be achieved, optimizing experimental and welfare outcomes.