Even small differences in texture due to acquisition slice thickness resulted in measurably different fractal signatures.
Volumetric perfusion imaging was obtained using a pseudo-continuous ASL tagging scheme with a 3D interleaved spiral FSE readout (3D spiral FSE ASL) with parameters as: TR/TE = 5128/15.9 ms, flip angle = 111o, FOV = 20 cm × 20 cm, x, y matrix = 1024 × 8 (spiral acquisition), slice thickness = 3.0 mm.
Rates were normalised to the tumour volume included within the spectroscopy acquisition slice.
Imaging parameters were as follows: FOV = 32 mm, matrix = 256 × 256, 17 slices (interleaved slice acquisition), slice thickness = 1 mm.
A transverse image of a mouse with a subcutaneous HT29 xenograft (tumour outlined) is shown in Figure 8C, with the acquisition slice for C-MRS indicated (grey lines).
In order to compare data from different tumours, the apparent rate constants obtained from kinetic modelling were normalised to the tumour volume included in the acquisition slice.
An acquisition slice thickness of 0.625 mm was utilised with a pitch of 0.984 1, a noise index of 28 (modulated) and a large field of view.
In both experiments, T1-weighted scans were subsequently used to select 30 axial slices (interleaved slice acquisition, slice thickness = 1.5 mm, no gap) covering bilateral S1 and adjacent areas (see Fig. 2).
These advantages arise from the volume acquisition (slice reconstruction, multiplanar reconstruction and 3D reformatting) and faster scanning (reduced need for sedation and intravenous contrast media) associated with CT angiography [ 20].
The above observations were largely true for lung, liver and lymph nodes and therefore can be considered an artefact of data acquisition (slice interval) rather than tumour type/location or segmentation algorithm.
