Medial meniscal displacement and strain in three dimensions under compressive loads: MR assessment

PURPOSE

To investigate the 3D displacement and the local strain of the medial meniscus and its attachments under compressive loading.

MATERIALS AND METHODS

Magnetic resonance imaging (MRI) scans of six porcine knee joints were performed under unloaded and loaded conditions (100% and 200% body weight [BW]). Volumes were registered to obtain a 3D displacement field of the medial meniscus and its attachments, which were divided into five anatomic compartments. Finally, displacements of the center of mass of each compartment and the local strain were analyzed.

RESULTS

The meniscus and its attachments significantly displaced by up to 2.6 ± 1.2 mm (P < 0.01) under knee joint loads of 200% BW. An increase of 0.9 mm in the distance between posterior and anterior horn (P < 0.001) was observed. The meniscus and its attachment showed an average radial stretch of 0.6%, an average circumferential stretch of 0.9%, and an average axial compression of 11.6% at 200% BW.

CONCLUSION

High-resolution MRI was successfully combined with image registration to investigate the displacement and strain of the meniscus and its attachments under compression. The results of this study contribute to the basic understanding of meniscal movement which may impact the design of meniscal implants and the validation of finite element models in the future.

Online 3D Displacement Measurement Using Speckle Interferometer with a Single Illumination-Detection Path

Measurement systems for online nondestructive full-field three-dimensional (3D) displacement based on the single-shot and multiplexing techniques attract more and more interest, especially throughout the manufacturing industries. This paper proposes an accurate and easy-to-implement method based on an electronic speckle pattern interferometer (ESPI) with single illumination-detection path to realize the online nondestructive full-field 3D displacement measurement. The simple and compact optical system generates three different sensitivity vectors to enable the evaluation of the three orthogonal displacement components. By applying the spatial carrier phase-shifting technique, the desired information can be obtained in real time. The theoretical analysis and the measurement results have proven the feasibility of this ESPI system and quantified its relative measurement error.

Self-supervised Monocular Depth Estimation with 3D Displacement Module for Laparoscopic Images

We present a novel self-supervised training framework with 3D displacement (3DD) module for accurately estimating per-pixel depth maps from single laparoscopic images. Recently, several self-supervised learning based monocular depth estimation models have achieved good results on the KITTI dataset, under the hypothesis that the camera is dynamic and the objects are stationary, however this hypothesis is often reversed in the surgical setting (laparoscope is stationary, the surgical instruments and tissues are dynamic). Therefore, a 3DD module is proposed to establish the relation between frames instead of ego-motion estimation. In the 3DD module, a convolutional neural network (CNN) analyses source and target frames to predict the 3D displacement of a 3D point cloud from a target frame to a source frame in the coordinates of the camera. Since it is difficult to constrain the depth displacement from two 2D images, a novel depth consistency module is proposed to maintain depth consistency between displacement-updated depth and model-estimated depth to constrain 3D displacement effectively. Our proposed method achieves remarkable performance for monocular depth estimation on the Hamlyn surgical dataset and acquired ground truth depth maps, outperforming monodepth, monodepth2 and packnet models.

Three-Dimensional Characterization of Aortic Root Motion by Vascular Deformation Mapping

The aorta is in constant motion due to the combination of cyclic loading and unloading with its mechanical coupling to the contractile left ventricle (LV) myocardium. This aortic root motion has been proposed as a marker for aortic disease progression. Aortic root motion extraction techniques have been mostly based on 2D image analysis and have thus lacked a rigorous description of the different components of aortic root motion (e.g., axial versus in-plane). In this study, we utilized a novel technique termed vascular deformation mapping (VDM(D)) to extract 3D aortic root motion from dynamic computed tomography angiography images. Aortic root displacement (axial and in-plane), area ratio and distensibility, axial tilt, aortic rotation, and LV/Ao angles were extracted and compared for four different subject groups: non-aneurysmal, TAA, Marfan, and repair. The repair group showed smaller aortic root displacement, aortic rotation, and distensibility than the other groups. The repair group was also the only group that showed a larger relative in-plane displacement than relative axial displacement. The Marfan group showed the largest heterogeneity in aortic root displacement, distensibility, and age. The non-aneurysmal group showed a negative correlation between age and distensibility, consistent with previous studies. Our results revealed a strong positive correlation between LV/Ao angle and relative axial displacement and a strong negative correlation between LV/Ao angle and relative in-plane displacement. VDM(D)-derived 3D aortic root motion can be used in future studies to define improved boundary conditions for aortic wall stress analysis.

Repositioning accuracy of the implant- and abutment-level prosthetic components used in conventional and digital workflows

OBJECTIVES

To evaluate the repositioning accuracy of the implant- and abutment-level impression components (impression abutments and implant scan bodies) and implant abutments (with and without anti-rotational hex index); also, to estimate the tightening torque influence on the positional stability of abutments.

METHODS

Seven types of prosthetic components (n = 7) [impression pick-up copings (PC), implant scan bodies (ISB), non‑hex and hex titanium base implant abutments (TB H and TB NH), multi-unit impression copings (MU PC), multi-unit implant scan bodies (MU ISB), and multi-unit caps (MU C) (Medentika GmbH)] were tested. For repositioning accuracy tests a coordinate measuring machine (CMM) was used. During assembly 15 Ncm torque for all components was applied. After measurement, only hex and non‑hex abutments were torqued to 25 Ncm and their coordinates were again recorded to assess torque influence. The procedure was repeated 7 times for each component. Linear and 3D deviations, angulation to the vertical axis, and axial rotation were calculated. The Kruskal-Wallis test was used to compare the measurements between the groups. A post-hoc test (Mann-Whitney U test) was used for pairwise comparison to determine the influence of the torque (α=0.05).

RESULTS

Implant- and abutment-level components used for digital scans showed different positional discrepancies compared to ones used for conventional impressions and ranged from 10 to 37 µm. Hex abutments demonstrated statistically significantly lower 3D deviations (4.4 ± 7.1 µm) compared to non‑hex abutments (8.7 ± 6.1 µm). Torque influence was significantly lower for hex abutments than for non‑hex abutments.

CONCLUSIONS

Repositioning inaccuracies were found in all implant- and abutment-level impression components (impression abutments and implant scan bodies) and all abutments (with and without anti-rotational hex index) tested. Final tightening of the components could cause further positional discrepancies.

CLINICAL SIGNIFICANCE

The misfit of the prosthetic components used in conventional and digital workflows stays in the clinically acceptable range. Even when multiple connections and disconnections on the track of the laboratory preparation is needed, it should not have a negative influence for single teeth reconstructions. However, in the complex cases with multiple implants, repetitive repositioning of the prosthetic components may lead to the accumulation of vertical, horizontal and rotational errors leading to the clinical problems with the passive fit of the final framework.

A method for monitoring three dimensional surface deformation in mining areas combining SBAS-InSAR, GNSS and probability integral method

In the process of mineral resource extraction, monitoring surface deformation is crucial for ensuring the safety of engineering and ground infrastructure. Monitoring complete three-dimensional surface deformation is particularly significant. Traditional synthetic aperture radar (InSAR) technology provides deformation components only along the line of sight (LOS) and often lacks sufficient effective data in vegetation-covered mining areas and mining subsidence centers. To address this, this study proposes a method (SBAS-PIM) that combines SBAS-InSAR with the probabilistic integral method (PIM). This method leverages high-coherence points in mining areas and GNSS data from vegetation-covered regions to invert the parameters required by PIM, thus obtaining three-dimensional surface deformation results. The proposed method allows for the acquisition of three-dimensional deformation data with fewer InSAR points and GNSS data, significantly reducing labor costs and addressing the gap in InSAR monitoring of three-dimensional surface deformation in densely vegetated areas. Additionally, it accounts for the mutual influence of multiple adjacent working faces. Finally, through the application to a mining area in Heze, China, the maximum displacements in the vertical, east-west, and north-south directions were obtained as -2011, -418, and - 281 mm, respectively. The correlation coefficients between the vertical and east-west directions and GNSS data were both greater than or equal to 0.9, indicating that this method can effectively monitor the three-dimensional surface deformation of the mining area.

Assessing aortic motion with automated 3D cine balanced steady state free precession cardiovascular magnetic resonance segmentation

PURPOSE

To apply a free-running three-dimensional (3D) cine balanced steady state free precession (bSSFP) cardiovascular magnetic resonance (CMR) framework in combination with artificial intelligence (AI) segmentations to quantify time-resolved aortic displacement, diameter and diameter change.

METHODS

In this prospective study, we implemented a free-running 3D cine bSSFP sequence with scan time of approximately 4 min facilitated by pseudo-spiral Cartesian undersampling and compressed-sensing reconstruction. Automated segmentation of the aorta in all cardiac timeframes was applied through the use of nnU-Net. Dynamic 3D motion maps were created for three repeated scans per volunteer, leading to the detailed quantification of aortic motion, as well as the measurement and change in diameter of the ascending aorta.

RESULTS

A total of 14 adult healthy volunteers (median age, 28 years (interquartile range [IQR]: 26.0-31.3), 6 females) were included. Automated segmentation compared to manual segmentation of the aorta test set showed a Dice score of 0.93 ± 0.02. The median (IQR) over all volunteers for the largest maximum and mean ascending aorta (AAo) displacement in the first scan was 13.0 (4.4) mm and 5.6 (2.4) mm, respectively. Peak mean diameter in the AAo was 25.9 (2.2) mm and peak mean diameter change was 1.4 (0.5) mm. The maximum individual variability over the three repeated scans of maximum and mean AAo displacement was 3.9 (1.6) mm and 2.2 (0.8) mm, respectively. The maximum individual variability of mean diameter and diameter change were 1.2 (0.5) mm and 0.9 (0.4) mm.

CONCLUSION

A free-running 3D cine bSSFP CMR scan with a scan time of four minutes combined with an automated nnU-net segmentation consistently captured the aorta's cardiac motion-related 4D displacement, diameter, and diameter change.