To assess the achievable acceleration factor of CS-PI for bowel motility imaging, resulting scans should be compared to fully sampled reference scans. While this is straightforward in many applications concerning static tissues or during breath-hold (e.g., in the liver), in the bowel, this is complicated by its constant motion. To objectively investigate the use of CS, we have performed static scans after temporarily stabilising bowel motility by administering a spasmolytic drug. This allowed acquisition of fully sampled 3D scans uncorrupted by bowel motion, which served as reference static scans. In an additional session, to capture bowel motility, we acquired CS-PI- and SENSE-accelerated dynamic scans of the small bowel without administering any spasmolytic drugs.
Six healthy subjects (four males, two females; median age 27.5, range 19–30 years) were recruited prospectively by advertisement: three subjects for static scans and three subjects for dynamic scans. Inclusion criteria included healthy, human volunteers who were willing to undergo minimal bowel preparation and MRI. Exclusion criteria for this study were age younger than 18 years or older than 45 years, history of abdominal surgery, gastrointestinal diseases, or current gastrointestinal symptoms. Additional exclusion criteria were contraindications to MRI and, for the static experiment, contraindications for the spasmolytic drug used. Permission of the Medical Ethics Committee of the Amsterdam UMC was obtained, and all subjects gave full written informed consent.
To ensure a similar preparation among subjects, all volunteers were instructed to fast for 4 h prior to the MRI session. During the 30 min prior to the MRI scans, they ingested 1 L of 2.5% mannitol solution at regular intervals of 10 min. Mannitol served the purpose of good bowel distension and contrast for clinical evaluation. To secure minimal movement of the bowel, which inevitably causes severe motion artefacts in the fully sampled scan, 10 mg of scopolaminebutyl (Buscopan; Boehringer-Ingelheim, Ingelheim, Germany) was intravenously injected directly before the fully sampled non-accelerated scan was acquired in the static session.
General MRI protocol
Scans were acquired in supine position with a 3-T Ingenia scanner (Philips, Best, The Netherlands), using a combination of a posterior coil located in the table (number of channels = 16) and an anterior torso-coil (number of channels = 16) covering the entire abdominal region. After initial scout sequences, coronal 3D scans of the bowel were acquired in multiple breath-holds using a balanced fast field-echo sequence. This sequence was chosen because of its superior lumen wall contrast, a key component for existing tracking techniques for quantification of small bowel motility [2,3,4]. The scan parameters were chosen based on the settings of the diagnostic abdominal balanced fast field-echo sequences at our centre (Table 1).
Two experiments were performed: a static experiment and a dynamic experiment. In the static experiment, fully sampled reference scans were acquired with an acquisition time of 16.4 s, followed by multiple prospectively undersampled CS-PI and SENSE scans using acceleration factors of 3×, 4×, 5×, 6×, 7×. Thus, in total, eleven scans per volunteer were acquired. In the dynamic experiment, multiple prospectively undersampled CS-PI and SENSE scans were acquired using acceleration factors of 5×, 6×, 7×, acquiring 6, 8, 9 time frames, respectively (nine scans per volunteer in total). The static and dynamic scan protocols are listed in Table 2.
An in-house developed scanner software patch (PROUD, or PROspective Undersampling in multiple Dimensions) was implemented to sample predefined k-space trajectories. These were read from a text-file created in MATLAB (The Mathworks Inc., NA, MA, USA), containing all subsequent (k-y, k-z)-coordinates.
Static scan sessions
Figure 1a shows the undersampling patterns of the CS-PI-accelerated static scans for all acceleration factors used. Note that these are 2D sampling patterns that were used to accelerate 3D scans in k-y and k-z phase encoding directions. They are characterised by a non-uniform sampling pattern consisting of a fully sampled auto calibration area in the centre of k-space and a Poisson disk distribution in the periphery. This permits auto-calibrated PI and leads to incoherent aliasing to support CS . In addition to the accelerated static scans, the fully acquired static dataset was also retrospectively undersampled using the same sampling patterns. Retrospective undersampling ensured that the bowel position was identical to the fully sampled scan, allowing determination of a quantitative structural similarity index between the full and accelerated scans. An overview of all reconstructions is given in Table 3.
Dynamic scan sessions
For prospectively accelerated dynamic bowel motility scans, both the use of equal (Fig. 1b, top) and varying (Fig. 1b, bottom) sampling patterns were investigated. The latter is thought to create incoherent sampling over time and allows to exploit sparsity in the temporal domain during CS-PI reconstruction.
For both static and dynamic SENSE-accelerated scans, equidistant (uniform) undersampling patterns in k-y and k-z directions were used, supplemented by an elliptical k-space shutter. Because of the smaller dimension of the slice encoding direction, a smaller acceleration factor was used in k-z direction. All scans and their corresponding acquisition time are listed in Table 4.
Reconstructions were performed offline with a Windows PC in MATLAB (The Mathworks Inc., NA, MA, USA), using an in-house built reconstruction pipeline developed within ReconFrame (GyroTools, Zürich, Switzerland), in combination with the open-source Berkeley Advanced Reconstruction Toolbox (BART) , enabling CS-PI reconstruction. For the static scan session, CS-PI-accelerated data was reconstructed with an iterative CS-PI reconstruction technique using L1 wavelet regularisation, as well as total variation regularisation, both in k-y and k-z dimension. The regularisation weights were optimised for every acceleration factor separately: λ = 0.002 (3×, 4×); λ = 0.0035 (5×); λ = 0.001 (6×); λ = 0.005 (7×). For the dynamic scans sessions, CS-PI-accelerated data was reconstructed with an iterative CS-PI reconstruction technique using total variation regularisation in the temporal domain only (regularisation parameter λ = 0.01, 20 iterations for all scans). All SENSE-accelerated data was reconstructed using a standard SENSE algorithm available in ReconFrame.
The reconstruction errors of the retrospectively undersampled scans were evaluated with the mean structural similarity index measure (SSIM), which is a similarity metric designed to predict human visual perception . This metric could not be used in the prospectively undersampled dataset because the metric cannot differentiate between the errors originating from the reconstruction or from possible bowel motility.
Fully sampled, retrospectively and prospectively undersampled CS-PI and SENSE reconstructions were scored by two independent abdominal radiologists with 2 and 20 years’ experience in two sessions. Image quality characteristics (artefacts, contrast, and sharpness) were evaluated. During scoring, the radiologists first assessed the image quality characteristics in the scans per set by putting the three images in their preference order for all characteristics separately and for a general quality score assigned accordingly. The score ranged from 1 (least favourable) to 3 (most favourable); an equal score was allowed in the case of similar quality. Secondly, the radiologists scored the diagnostic quality of the separate scans within the set with a 4-point scale, as follows: 0 = non-diagnostic; 1 = poor; 2 = adequate; 3 = good. Considering the small sample size of this explorative study, all outcomes were assessed by descriptive statistics only.
Static scoring session
In the static experiment scoring session (session 1), CS-PI and SENSE reconstruction were compared to the fully sampled (reference) reconstructions. The radiologists viewed the three blinded scan types as a set (full/CS-PI/SENSE) in a randomised order (Fig. 5), totalling 30 sets (15 prospective undersampled, 15 retrospective undersampled).
Dynamic scoring session
In the dynamic experiment scoring session (session 2), CS-PI reconstructions from data acquired with equal sampling pattern (CS1) were compared to those acquired with a varying sampling pattern (CS2) and the SENSE reconstructions. The radiologists viewed the three blinded scan types as a set (CS1, CS2, SENSE), in a randomised order, totalling nine sets, all prospectively undersampled.