## 3 Results  
The data acquisition during uninterrupted artificial ventilation with OCT and IVM was tested prior to the animal experiments. A periodic pattern from a function generator mimicking the movement of the pleura up to 1.5 Hz was applied to a loudspeaker with a structured target (data not shown). This enabled us to verify the functionality of the surface-tracking algorithm for IVM and the continuous OCT scanning mode with post-processing rearrangement of the acquired images. Figure 4 shows exemplary measurement data during in vivo experiments. A collection of the measurement data for IVM and OCT is provided as a supplemental video file online (Video S1: 4D imaging of alveolar dynamics in ventilated rats). OCT and IVM images at four representative time points (during inspiration, at max. inspiration, during expiration and at max. expiration) were chosen to better illustrate the different positions and structures of the alveolar tissue. The pressure-time curve at the top of Figure 4 is a schematic of the used pressure-controlled ventilation mode during experiments performed with a frequency of 60 breaths per minute (f = 1 Hz) from 2 mbar (positive end-expiratory pressure) to 11 mbar (end-inspiratory pressure) with an inspiration-to-expiration ratio (I:E) of 1:1. Figure 3: Measurement setup for investigating lung tissue dynamics. The animal is anesthetized and connected to the ventilator. Optical access to alveolar structures for OCT and IVM is achieved by resecting a thoracic window without harming the pleura visceralis in order to keep the physiological thoracic pressure conditions intact. The 5 V trigger signal generated from the ventilator is acquired by the imaging PC using an USB data acquisition board. The IVM image sequence is measured immediately before starting OCT data acquisition. It becomes clearly visible that the use of the tunable focus lens is essential to keeping the lung surface in focal plane for IVM over the whole ventilation cycle (compare to first row in Figure 4 \"IVM without focus adaption\"). Without tracking the lung surface, just a part of the video sequence (in this example at end-inspiratory plateau) is sharp enough to distinguish tissue structures and alveolar boarders. Compared to the second row of Figure 4, one can see the advantages of the electrically tunable focus lens for visualization of the tissue movement in axial direction over the whole ventilation cycle. The last row of Figure 4 shows the corresponding OCT data stacks after rearrangement of the measured cross sections during uninterrupted artificial ventilation. OCT images show the average tissue movement during one ventilation cycle as enface view calculated from the 3D OCT stacks 25 \(\upmu\)m beneath the pleura visceralis. Thereby, the alveoli become visible and the tissue structure can be compared to the IVM images (indicated by the green circle). During phases of high tissue movement in inspiration and expiration, image reconstruction is affected by disturbances as a result of jitter, as the B-scan was not synchronized to the ventilation or of the long overall measurement duration of 5.3 min (34 3D stacks with 320 \(\times\) 320 \(\times\) 512 pixels). Therefore, tissue movement is not exactly identical in each ventilation cycle, resulting in slight differences of the tissue structures within the OCT cross sections. This problem was mostly fixed by alignment of the pleura position during post-processing using open  
Figure 4: Visualization of lung tissue dynamics during artificial ventilation with OCT and IVM. Pressure-controlled ventilation was performed from 2–11 mbar at a frequency of 1 Hz and an inspiration-to-expiration ratio (I:E) of 1:1 showing a pressure-time course illustrated in the upper diagram. The advantage of the tunable liquid focus lens for IVM can be seen by comparing first and second rows. Most of the tissue movement cannot be imaged properly without focus adaption, so structural information was lost.