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Purpose: To maximize acquisition bandwidth in zero echo time (ZTE) sequences, readout gradients are already switched on during the RF pulse, creating unwanted slice selectivity. The resulting image distortions are amplified especially when the anatomy of interest is not located at the isocenter. We aim to characterize off-center ZTE MRI of extremities such as the shoulder, knee, and hip, adjusting the carrier frequency of the RF pulse excitation for each TR. Methods: In ZTE MRI, radial encoding schemes are used, where the distorted slice profile due to the finite RF pulse length rotates with the k-space trajectory. To overcome these modulations for objects far away from the magnet isocenter, the frequency of the RF pulse is shifted for each gradient setting so that artifacts do not occur at a given off-center target position. The sharpness of the edges in the images were calculated and the ZTE acquisition with off-center excitation was compared to an acquisition with isocenter excitation both in phantom and in vivo off-center MRI of the shoulder, knee, and hip at 1.5 and 3T MRI systems. Results: Distortion and blurriness artifacts on the off-center MRI images of the phantom, in vivo shoulder, knee, and hip images were mitigated with off-center excitation without time or noise penalty, at no additional computational cost. Conclusion: The off-center excitation allows ZTE MRI of the shoulder, knee, and hip for high-bandwidth image acquisitions for clinical settings, where positioning at the isocenter is not possible.

Abstract Background In this work, we compare input level, feature level and decision level data fusion techniques for automatic detection of clinically significant prostate lesions (csPCa). Methods Multiple deep learning CNN architectures were developed using the Unet as the baseline. The CNNs use both multiparametric MRI images (T2W, ADC, and High b-value) and quantitative clinical data (prostate specific antigen (PSA), PSA density (PSAD), prostate gland volume & gross tumor volume (GTV)), and only mp-MRI images (n = 118), as input. In addition, co-registered ground truth data from whole mount histopathology images (n = 22) were used as a test set for evaluation. Results The CNNs achieved for early/intermediate / late level fusion a precision of 0.41/0.51/0.61, recall value of 0.18/0.22/0.25, an average precision of 0.13 / 0.19 / 0.27, and F scores of 0.55/0.67/ 0.76. Dice Sorensen Coefficient (DSC) was used to evaluate the influence of combining mpMRI with parametric clinical data for the detection of csPCa. We compared the DSC between the predictions of CNN’s trained with mpMRI and parametric clinical and the CNN’s trained with only mpMRI images as input with the ground truth. We obtained a DSC of data 0.30/0.34/0.36 and 0.26/0.33/0.34 respectively. Additionally, we evaluated the influence of each mpMRI input channel for the task of csPCa detection and obtained a DSC of 0.14 / 0.25 / 0.28. Conclusion The results show that the decision level fusion network performs better for the task of prostate lesion detection. Combining mpMRI data with quantitative clinical data does not show significant differences between these networks (p = 0.26/0.62/0.85). The results show that CNNs trained with all mpMRI data outperform CNNs with less input channels which is consistent with current clinical protocols where the same input is used for PI-RADS lesion scoring. Trial registration The trial was registered retrospectively at the German Register for Clinical Studies (DRKS) under proposal number Nr. 476/14 & 476/19.

Abstract Magnetic resonance imaging (MRI) provides a multitude of techniques to detect and characterize myocardial infarction. To correlate MRI findings with histology, in most cases terminal animal studies are performed; however, precise extraction and spatial correlation of myocardial tissue samples to MRI image data is difficult. In this proof of concept study, we present a 3D-printing technique to facilitate the extraction of tissue samples from myocardial regions. Initially, seven pig hearts embedded in formaldehyde were imaged on a clinical 3 T system to define biopsy targets on high resolution ex vivo images. Magnitude images and R2*-maps acquired with a 3D multi-echo gradient echo sequence and 0.58 mm isotropic resolution were used to create digital models of the cardiac anatomy. Biopsy guides were 3D-printed to steer the extraction of myocardial samples. In total, 61 tissue samples were extracted with an average offset of the tissue sample location from the target location of 0.59 ± 0.36 mm. This offset was not dependent on the distance of the target point to the epicardial surface. Myocardial tissue could be extracted from all samples. The presented method enables extraction of myocardial tissue samples that are selected by ex vivo MRI with submillimeter precision.

In closed-bore MRI units, assistance systems play a crucial role in overcoming patient access limitations during percutaneous interventions. In this work, we present eGantryMate, a piezo-motor-driven assistance system specifically designed for MR-guided needle interventions in high-field MRI systems. eGantryMate consists of an instrument positioning unit and a control unit equipped with piezo motors, radiofrequency filters, and shielding. Paired with a real-time tracking sequence for automatic marker detection and projection of the instrument trajectory onto the MR image, eGantryMate enables precise and efficient needle interventions. Targeting experiments were performed by inserting a biopsy needle into a series of fiducial targets in a phantom, and usability experiments were conducted in vivo without needle insertion. The results show artifact-free MR imaging, minimal temperature rise on the instrument positioning unit, and precise targeting capabilities. These findings demonstrate eGantryMate’s ability to perform real-time needle alignments and insertions within the magnet bore, highlighting its potential to enhance the acceptability and efficacy of MR-guided interventions.

Abstract Pigs are frequently applied as animal models in cardiovascular research due to their anatomical and physiological similarity to humans. For study planning and refinement, precise knowledge of the cardioaortic dimensions is essential. In a retrospective single-center study, the cardioaortic dimensions and left ventricular function of German Landrace pigs were assessed using cardiac MRI. All parameters were compared between male and female pigs and analyzed for correlation with body weight. In total, 15 pigs were included (7 male and 8 female, weight 60.9 ± 7.0 kg). The left ventricle revealed an end-diastolic diameter of 50.5 ± 4.4 mm and an ejection fraction of 51.2 ± 9.8%. The diameters of the ascending and descending aorta were 21.3 ± 2.3 and 16.2 ± 1.4 mm, respectively. There were no significant differences between male and female pigs, except that males had a smaller end-diastolic left ventricular volume (p = 0.041). A moderate correlation was found between body weight and the aortic annulus diameter (R = 0.57, p = 0.027). In conclusion, cardiac MRI allows precise quantification of porcine cardioaortic dimensions. For medical device testing, size differences between pigs and humans should be considered.

Abstract Objective To analyze and compare the effects of a traditional laboratory-fabricated Hyrax expander (T-Hyrax) and two different 3D-printed Hyrax expander models relative to tension points, force distribution, and areas of concentration in the craniofacial complex during maxillary expansion using finite element analysis. Materials and methods Three maxillary expanders with similar designs, but various alloys were modeled: a T-Hyrax, a fully printed Hyrax (F-Hyrax), and a hybrid printed Hyrax (H-Hyrax). The stress distributions and magnitude of displacements were assessed with a 5 mm expansion in a symmetrical finite element model. The areas of interest included the teeth, alveolar processes, midpalatal suture, nasal complex, circummaxillary sutures (CS), and the expanders themselves. Results The highest stress value (29.2 MPa) was found at the midpalatal suture of the F-Hyrax, while the lowest stress (0.90 MPa) was found at the temporozygomatic suture in the T-Hyrax. On average, the F-Hyrax increased stress at the CS by 24.76% compared with the T-Hyrax and H-Hyrax. The largest displacements were found at the upper incisor (U1) and anterior nasal spine (ANS). The findings indicated an average increase of 12.80% displacement at the CS using the F-Hyrax compared to the T-Hyrax. Conclusion The F-Hyrax exerts more stress and displacement on the maxilla than both the T-Hyrax and H-Hyrax, where the weak link appears to be the solder joint.